WO2024065272A1

WO2024065272A1 - Point cloud coding method and apparatus, point cloud decoding method and apparatus, and device and storage medium

Info

Publication number: WO2024065272A1
Application number: PCT/CN2022/122117
Authority: WO
Inventors: 孙泽星
Original assignee: Oppo广东移动通信有限公司
Priority date: 2022-09-28
Filing date: 2022-09-28
Publication date: 2024-04-04

Abstract

Provided in the present application are a point cloud coding method and apparatus, a point cloud decoding method and apparatus, and a device and a storage medium. The method comprises: in point cloud decoding, for example, in AVS-based point cloud decoding, when the current node of an (N-1)th layer in an octree is decoded, first, determining a first parameter corresponding to the current node, wherein the first parameter is used for determining whether at least one non-zero sub-node of the current node comprises a repeated point, the current node being a non-zero node of the (N-1)th layer in the octree of a point cloud, and N being the total number of layers of the octree; and then, performing geometric decoding on the current node on the basis of the first parameter. For example, when it is determined, on the basis of a first parameter, that an ith non-zero sub-node of the current node does not comprise a repeated point, the decoding of repeated point information of the ith non-zero sub-node is skipped, so as to reduce the decoding complexity of a point cloud and save on the decoding time, and thus improving the decoding efficiency.

Description

Point cloud encoding and decoding method, device, equipment and storage medium

Technical Field

The present application relates to the field of point cloud technology, and in particular to a point cloud encoding and decoding method, device, equipment and storage medium.

Background technique

The surface of the object is collected by the acquisition device to form point cloud data, which includes hundreds of thousands or even more points. In the video production process, the point cloud data is transmitted between the point cloud encoding device and the point cloud decoding device in the form of point cloud media files. However, such a large number of points brings challenges to transmission, so the point cloud encoding device needs to compress the point cloud data before transmission.

The compression of point clouds is also called the encoding of point clouds. In the process of point cloud encoding, different encoding models are used to correspond the points in the point cloud to nodes and encode the nodes, some of which include duplicate points. The current encoding and decoding methods, such as the Audio Video Standard (AVS) of point clouds, need to encode and decode the duplicate point information of each non-zero leaf node in the leaf node of the octree, thereby reducing the encoding and decoding efficiency of the point cloud.

Summary of the invention

The embodiments of the present application provide a point cloud encoding and decoding method, apparatus, device and storage medium, which reduce the complexity of point cloud encoding and decoding, save encoding and decoding time, and thus improve the encoding and decoding efficiency of point cloud.

In a first aspect, an embodiment of the present application provides a point cloud decoding method, comprising:

Determine a first parameter corresponding to a current node, where the first parameter is used to determine whether at least one non-zero child node of the current node includes a duplicate point, where the current node is a non-zero node in the N-1th layer of an octree of the point cloud, where the octree is obtained by node division of the point cloud, where N is the total number of layers of the octree, and where N is a positive integer greater than 1;

Based on the first parameter, geometric decoding is performed on the current node.

In a second aspect, the present application provides a point cloud encoding method, comprising:

Determine a first parameter corresponding to a current node, where the first parameter is used to determine whether at least one child node of the current node includes a duplicate point, where the current node is a node in the N-1th layer of an octree of the point cloud, where the octree is obtained by node division of the point cloud, where N is the total number of layers of the octree, and where N is a positive integer greater than 1;

Based on the first parameter, geometric encoding is performed on the current node.

In a third aspect, the present application provides a point cloud decoding device for executing the method in the first aspect or its respective implementations. Specifically, the device includes a functional unit for executing the method in the first aspect or its respective implementations.

In a fourth aspect, the present application provides a point cloud encoding device for executing the method in the second aspect or its respective implementations. Specifically, the device includes a functional unit for executing the method in the second aspect or its respective implementations.

In a fifth aspect, a point cloud decoder is provided, comprising a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in the first aspect or its implementation manners.

In a sixth aspect, a point cloud encoder is provided, comprising a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in the second aspect or its respective implementations.

In a seventh aspect, a point cloud encoding and decoding system is provided, comprising a point cloud encoder and a point cloud decoder. The point cloud decoder is used to execute the method in the first aspect or its respective implementations, and the point cloud encoder is used to execute the method in the second aspect or its respective implementations.

In an eighth aspect, a chip is provided for implementing the method in any one of the first to second aspects or their respective implementations. Specifically, the chip includes: a processor for calling and running a computer program from a memory, so that a device equipped with the chip executes the method in any one of the first to second aspects or their respective implementations.

In a ninth aspect, a computer-readable storage medium is provided for storing a computer program, wherein the computer program enables a computer to execute the method of any one of the first to second aspects or any of their implementations.

In a tenth aspect, a computer program product is provided, comprising computer program instructions, which enable a computer to execute the method in any one of the first to second aspects or their respective implementations.

In an eleventh aspect, a computer program is provided, which, when executed on a computer, enables the computer to execute the method in any one of the first to second aspects or in each of their implementations.

In a twelfth aspect, a code stream is provided, which is generated based on the method of the second aspect. Optionally, the code stream includes at least one of the first parameter and the second parameter.

Based on the above technical solution, in point cloud decoding, for example, in point cloud decoding based on AVS, when decoding the current node of the N-1th layer in the octree, first determine the first parameter corresponding to the current node, the first parameter is used to determine whether at least one non-zero child node of the current node includes duplicate points, the current node is a non-zero node of the N-1th layer in the octree of the point cloud, N is the total number of layers of the octree, and then based on the first parameter, the current node is geometrically decoded. For example, when it is determined based on the first parameter that the i-th non-zero child node of the current node does not include duplicate points, the decoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the decoding complexity of the point cloud, saving decoding time, and improving decoding efficiency.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1A is a schematic diagram of a point cloud;

Figure 1B is a partial enlarged view of the point cloud;

FIG2 is a schematic diagram of six viewing angles of a point cloud image;

FIG3 is a schematic block diagram of a point cloud encoding and decoding system according to an embodiment of the present application;

FIG4A is a schematic block diagram of a point cloud encoder provided in an embodiment of the present application;

FIG4B is a schematic block diagram of a point cloud decoder provided in an embodiment of the present application;

FIG5 is a schematic diagram of a point cloud decoding method flow chart provided by an embodiment of the present application;

FIG6 is a schematic diagram of an octree partition;

FIG7 is a schematic diagram of an octree and a prediction tree partition;

FIG8 is a schematic diagram of an octree involved in an embodiment of the present application;

FIG9 is a schematic diagram of a point cloud encoding method flow chart provided by an embodiment of the present application;

FIG10 is a schematic block diagram of a point cloud decoding device provided in an embodiment of the present application;

FIG11 is a schematic block diagram of a point cloud encoding device provided in an embodiment of the present application;

FIG12 is a schematic block diagram of an electronic device provided in an embodiment of the present application;

FIG. 13 is a schematic block diagram of a point cloud encoding and decoding system provided in an embodiment of the present application.

Detailed ways

The present application can be applied to the field of point cloud upsampling technology, for example, can be applied to the field of point cloud compression technology.

In order to facilitate understanding of the embodiments of the present application, the relevant concepts involved in the embodiments of the present application are briefly introduced as follows:

Point cloud refers to a set of irregularly distributed discrete points in space that express the spatial structure and surface properties of a three-dimensional object or three-dimensional scene. Figure 1A is a schematic diagram of a three-dimensional point cloud image, and Figure 1B is a partial enlarged view of Figure 1A. It can be seen from Figures 1A and 1B that the point cloud surface is composed of densely distributed points.

Two-dimensional images have information expressed at each pixel point, and the distribution is regular, so there is no need to record its position information; however, the distribution of points in the point cloud in three-dimensional space is random and irregular, so it is necessary to record the position of each point in space to fully express a point cloud. Similar to two-dimensional images, each position has corresponding attribute information during the acquisition process.

Point cloud data is a specific record form of point cloud. Points in the point cloud may include the location information of the point and the attribute information of the point. For example, the location information of the point may be the three-dimensional coordinate information of the point. The location information of the point may also be called the geometric information of the point. For example, the attribute information of the point may include color information, reflectance information, normal vector information, etc. Color information reflects the color of an object, and reflectance information reflects the surface material of an object. The color information may be information in any color space. For example, the color information may be (RGB). For another example, the color information may be information about brightness and chromaticity (YcbCr, YUV). For example, Y represents brightness (Luma), Cb (U) represents blue color difference, Cr (V) represents red, and U and V represent chromaticity (Chroma) for describing color difference information. For example, according to the point cloud obtained by the laser measurement principle, the points in the point cloud may include the three-dimensional coordinate information of the point and the laser reflection intensity (reflectance) of the point. For another example, according to the point cloud obtained by the photogrammetry principle, the points in the point cloud may include the three-dimensional coordinate information of the point and the color information of the point. For another example, a point cloud is obtained by combining the principles of laser measurement and photogrammetry. The points in the point cloud may include the three-dimensional coordinate information of the point, the laser reflection intensity (reflectance) of the point, and the color information of the point. FIG2 shows a point cloud image, where FIG2 shows six viewing angles of the point cloud image. Table 1 shows the point cloud data storage format composed of a file header information part and a data part:

Table 1

In Table 1, the header information includes the data format, data representation type, the total number of point cloud points, and the content represented by the point cloud. For example, the point cloud in this example is in the ".ply" format, represented by ASCII code, with a total number of 207242 points, and each point has three-dimensional position information XYZ and three-dimensional color information RGB.

Point clouds can flexibly and conveniently express the spatial structure and surface properties of three-dimensional objects or scenes. Point clouds are obtained by directly sampling real objects, so they can provide a strong sense of reality while ensuring accuracy. Therefore, they are widely used, including virtual reality games, computer-aided design, geographic information systems, automatic navigation systems, digital cultural heritage, free viewpoint broadcasting, three-dimensional immersive remote presentation, and three-dimensional reconstruction of biological tissues and organs.

Point cloud data can be obtained by at least one of the following ways: (1) computer equipment generation. Computer equipment can generate point cloud data based on virtual three-dimensional objects and virtual three-dimensional scenes. (2) 3D (3-Dimension) laser scanning acquisition. 3D laser scanning can be used to obtain point cloud data of static real-world three-dimensional objects or three-dimensional scenes, and millions of point cloud data can be obtained per second; (3) 3D photogrammetry acquisition. The visual scene of the real world is collected by 3D photography equipment (i.e., a group of cameras or camera equipment with multiple lenses and sensors) to obtain point cloud data of the visual scene of the real world. 3D photography can be used to obtain point cloud data of dynamic real-world three-dimensional objects or three-dimensional scenes. (4) Point cloud data of biological tissues and organs can be obtained by medical equipment. In the medical field, point cloud data of biological tissues and organs can be obtained by medical equipment such as magnetic resonance imaging (MRI), computed tomography (CT), and electromagnetic positioning information.

Point clouds can be divided into dense point clouds and sparse point clouds according to the way they are acquired.

Point clouds are divided into the following types according to the time series of the data:

The first type of static point cloud: the object is stationary, and the device that obtains the point cloud is also stationary;

The second type of dynamic point cloud: the object is moving, but the device that obtains the point cloud is stationary;

The third type of dynamic point cloud acquisition: the device that acquires the point cloud is moving.

Point clouds can be divided into two categories according to their uses:

Category 1: Machine perception point cloud, which can be used in autonomous navigation systems, real-time inspection systems, geographic information systems, visual sorting robots, emergency rescue robots, etc.

Category 2: Point cloud perceived by the human eye, which can be used in point cloud application scenarios such as digital cultural heritage, free viewpoint broadcasting, 3D immersive communication, and 3D immersive interaction.

The above point cloud acquisition technology reduces the cost and time of point cloud data acquisition and improves the accuracy of data. The change in the point cloud data acquisition method makes it possible to acquire a large amount of point cloud data. With the growth of application demand, the processing of massive 3D point cloud data encounters bottlenecks of storage space and transmission bandwidth.

Taking a point cloud video with a frame rate of 30fps (frames per second) as an example, the number of points in each point cloud frame is 700,000, and each point has coordinate information xyz (float) and color information RGB (uchar). The data volume of a 10s point cloud video is approximately 0.7 million (4Byte 3 + 1Byte 3) 30fps 10s = 3.15GB, while the YUV sampling format is 4:2:0, and the frame rate is 24fps. The 10s data volume of a 1280 720 two-dimensional video is approximately 1280 720 12bit 24frames 10s ≈ 0.33GB, and the data volume of a 10s two-view 3D video is approximately 0.33X2 = 0.66GB. It can be seen that the data volume of a point cloud video far exceeds that of a two-dimensional video and a three-dimensional video of the same length. Therefore, in order to better realize data management, save server storage space, and reduce the transmission traffic and transmission time between the server and the client, point cloud compression has become a key issue in promoting the development of the point cloud industry.

The following is an introduction to the relevant knowledge of point cloud encoding and decoding.

FIG3 is a schematic block diagram of a point cloud encoding and decoding system involved in an embodiment of the present application. It should be noted that FIG3 is only an example, and the point cloud encoding and decoding system of the embodiment of the present application includes but is not limited to that shown in FIG3. As shown in FIG3, the point cloud encoding and decoding system 100 includes an encoding device 110 and a decoding device 120. The encoding device is used to encode (which can be understood as compression) the point cloud data to generate a code stream, and transmit the code stream to the decoding device. The decoding device decodes the code stream generated by the encoding device to obtain decoded point cloud data.

The encoding device 110 of the embodiment of the present application can be understood as a device with a point cloud encoding function, and the decoding device 120 can be understood as a device with a point cloud decoding function, that is, the embodiment of the present application includes a wider range of devices for the encoding device 110 and the decoding device 120, such as smartphones, desktop computers, mobile computing devices, notebook (e.g., laptop) computers, tablet computers, set-top boxes, televisions, cameras, display devices, digital media players, point cloud game consoles, vehicle-mounted computers, etc.

In some embodiments, the encoding device 110 may transmit the encoded point cloud data (such as a code stream) to the decoding device 120 via the channel 130. The channel 130 may include one or more media and/or devices capable of transmitting the encoded point cloud data from the encoding device 110 to the decoding device 120.

In one example, the channel 130 includes one or more communication media that enable the encoding device 110 to transmit the encoded point cloud data directly to the decoding device 120 in real time. In this example, the encoding device 110 can modulate the encoded point cloud data according to the communication standard and transmit the modulated point cloud data to the decoding device 120. The communication medium includes a wireless communication medium, such as a radio frequency spectrum, and optionally, the communication medium may also include a wired communication medium, such as one or more physical transmission lines.

In another example, the channel 130 includes a storage medium, which can store the point cloud data encoded by the encoding device 110. The storage medium includes a variety of locally accessible data storage media, such as optical disks, DVDs, flash memories, etc. In this example, the decoding device 120 can obtain the encoded point cloud data from the storage medium.

In another example, the channel 130 may include a storage server that can store the point cloud data encoded by the encoding device 110. In this example, the decoding device 120 can download the stored encoded point cloud data from the storage server. Optionally, the storage server can store the encoded point cloud data and transmit the encoded point cloud data to the decoding device 120, such as a web server (e.g., for a website), a file transfer protocol (FTP) server, etc.

In some embodiments, the encoding device 110 includes a point cloud encoder 112 and an output interface 113. The output interface 113 may include a modulator/demodulator (modem) and/or a transmitter.

In some embodiments, the encoding device 110 may further include a point cloud source 111 in addition to the point cloud encoder 112 and the input interface 113 .

The point cloud source 111 may include at least one of a point cloud acquisition device (e.g., a scanner), a point cloud archive, a point cloud input interface, and a computer graphics system, wherein the point cloud input interface is used to receive point cloud data from a point cloud content provider, and the computer graphics system is used to generate point cloud data.

The point cloud encoder 112 encodes the point cloud data from the point cloud source 111 to generate a code stream. The point cloud encoder 112 transmits the encoded point cloud data directly to the decoding device 120 via the output interface 113. The encoded point cloud data can also be stored in a storage medium or a storage server for subsequent reading by the decoding device 120.

In some embodiments, the decoding device 120 includes an input interface 121 and a point cloud decoder 122 .

In some embodiments, the decoding device 120 may further include a display device 123 in addition to the input interface 121 and the point cloud decoder 122 .

The input interface 121 includes a receiver and/or a modem. The input interface 121 can receive the encoded point cloud data through the channel 130 .

The point cloud decoder 122 is used to decode the encoded point cloud data to obtain decoded point cloud data, and transmit the decoded point cloud data to the display device 123.

The decoded point cloud data is displayed on the display device 123. The display device 123 may be integrated with the decoding device 120 or may be external to the decoding device 120. The display device 123 may include a variety of display devices, such as a liquid crystal display (LCD), a plasma display, an organic light emitting diode (OLED) display, or other types of display devices.

In addition, Figure 3 is only an example, and the technical solution of the embodiment of the present application is not limited to Figure 3. For example, the technology of the present application can also be applied to unilateral point cloud encoding or unilateral point cloud decoding.

The current point cloud encoder can use the geometry point cloud compression (G-PCC) codec framework or the video point cloud compression (V-PCC) codec framework provided by the Moving Picture Experts Group (MPEG) of the International Standards Organization, or the AVS-PCC codec framework provided by the Audio Video Standard (AVS). Both G-PCC and AVS-PCC are aimed at static sparse point clouds, and their coding frameworks are roughly the same.

The following uses the AVS-PCC encoding and decoding framework as an example to explain the point cloud encoder and point cloud decoder applicable to the embodiments of the present application.

FIG. 4A is a schematic block diagram of a point cloud encoder provided in an embodiment of the present application.

From the above, we can know that the points in the point cloud can include the location information of the points and the attribute information of the points. Therefore, the encoding of the points in the point cloud mainly includes location encoding and attribute encoding. In some examples, the location information of the points in the point cloud is also called geometric information, and the corresponding location encoding of the points in the point cloud can also be called geometric encoding.

In the AVS-PCC coding framework, the geometric information of the point cloud and the corresponding attribute information are encoded separately.

The process of position encoding includes: preprocessing the points in the point cloud, such as coordinate transformation, quantization, and removal of duplicate points; then, geometric encoding the preprocessed point cloud, such as constructing an octree, and geometric encoding based on the constructed octree to form a geometric code stream. At the same time, based on the position information output by the constructed octree, the position information of each point in the point cloud data is reconstructed to obtain the reconstructed value of the position information of each point.

The attribute encoding process includes: given the reconstruction information of the input point cloud position information and the original value of the attribute information, selecting one of the two prediction modes to predict the point cloud attributes, quantizing the predicted results, and performing arithmetic coding to form an attribute code stream.

As shown in Figure 4A, position encoding can be achieved by the following units:

Coordinate translation, coordinate quantization unit 201, octree construction (Analyze octree) unit 202, octree reconstruction (Reconstruct geometry) unit 203, first entropy coding (Arithmetic enconde) unit 204.

The coordinate translation and coordinate quantization unit 201 can be used to transform the world coordinates of points in the point cloud into relative coordinates. For example, the geometric coordinates of the point are respectively subtracted from the minimum value of the xyz coordinate axis, which is equivalent to a DC removal operation to achieve the conversion of the coordinates of the points in the point cloud from world coordinates to relative coordinates. Optionally, it will be decided whether to divide the entire point cloud sequence into multiple slices (point cloud slices) based on the parameter configuration, and each divided slice will be treated as a single independent point cloud serial processing. Next, the point cloud is quantized and duplicate points are removed. The number of coordinates can be reduced by quantization; after quantization, originally different points may be assigned the same coordinates, based on which, duplicate points can be deleted by deduplication operations; for example, multiple clouds with the same quantized position and different attribute information can be merged into one cloud through attribute conversion. In some embodiments of the present application, quantization and removal of duplicate points are optional steps. In some embodiments, quantization and removal of duplicate points are also referred to as voxelization.

The octree construction unit 202 can use the octree encoding method to encode the position information of the quantized points. For example, the point cloud is contained in a bounding box, the bounding box of the point cloud is divided in the form of an octree, and the placeholder code of each node is encoded. In the octree-based geometric code framework, the bounding box is divided into sub-cubes in sequence, and the non-empty (including the points in the point cloud) sub-cubes are continued to be divided until the leaf node obtained by the division is a 1x1x1 unit cube. The division is stopped. Thus, the position of the point can correspond to the position of the octree one by one, and the position of the point in the octree is counted and its flag is recorded as 1 for geometric encoding.

The octree reconstruction unit 203 can perform position reconstruction based on the position information output by the octree construction unit 202 to obtain the reconstruction value of the position information of each point in the point cloud data. In the geometric reconstruction process based on the octree, the placeholder code of each node is obtained by continuous parsing in the order of breadth-first traversal, and the nodes are continuously divided in turn until the division is stopped when a 1x1x1 unit cube is obtained, and the number of points contained in each leaf node is obtained by parsing, and finally the geometric reconstruction value of the point cloud is restored.

The first entropy coding unit 204 can use entropy coding to perform arithmetical coding on the position information output by the octree analysis unit 203 to generate a geometric code stream; the geometric code stream can also be called a geometry bitstream.

Attribute encoding can be achieved through the following units:

A spatial conversion unit 210 , a property difference unit 211 , a property prediction unit 212 , a property transformation unit 213 , a quantization unit 214 and a second entropy coding unit 214 .

It should be noted that the point cloud encoder 200 may include more, fewer or different functional components than those shown in FIG. 4A .

The space conversion unit 210 can be used to convert the RGB color space of the point in the point cloud into a YUV color space or other formats. At present, attribute encoding is mainly performed on color and reflectivity information. First, it is determined whether to perform color space conversion. If color space conversion is performed, the space conversion unit 210 converts the color information from the RGB color space to the YUV color space.

The attribute difference unit 211, also called a recoloring unit, uses the reconstructed geometric information to recolor the color information so that the uncoded attribute information corresponds to the reconstructed geometric information.

After recoloring to obtain the original value of the point attribute information, you can choose either attribute prediction or attribute transformation to process the points in the point cloud.

In some embodiments, if the encoding end selects an attribute prediction method to encode the attributes of the points, the attribute prediction unit 212 is used to reorder the point cloud and then perform differential prediction. There are two methods of reordering: Morton reordering and Hilbert reordering. For the cat1A sequence and the cat2 sequence, Hilbert reordering is performed; for the cat1B sequence and the cat3 sequence, Morton reordering is performed. The attribute of the sorted point cloud is predicted using a differential method, and the attribute residual of the point is obtained based on the attribute prediction of the point and the original value of the attribute. The quantization unit 214 quantizes the attribute residual of the point to obtain the quantized attribute residual. The second entropy coding unit 215 performs entropy coding on the attribute residual quantized by the quantization unit 214 to obtain a binary attribute code stream.

The attribute transformation unit 213 is used to perform wavelet transformation on the point cloud attributes to obtain transformation coefficients. The quantization unit 214 quantizes the transformation coefficients to obtain quantized transformation coefficients. In addition, the attribute transformation unit 213 performs inverse quantization and inverse wavelet transformation on the quantized transformation coefficients to obtain attribute reconstruction values. Then, the attribute transformation unit 213 calculates the difference between the original attribute of the point and the attribute reconstruction value of the point to obtain the attribute residual of the point. The quantization unit 214 quantizes the attribute residual of the point to obtain the quantized attribute residual of the point. The second entropy coding unit 215 performs entropy coding on the attribute residual quantized by the quantization unit 214 and the quantized transformation coefficient to obtain a binary attribute code stream.

FIG4B is a schematic block diagram of a point cloud decoder provided in an embodiment of the present application.

As shown in Fig. 4B, the decoder 300 can obtain the point cloud code stream from the encoding device, and obtain the position information and attribute information of the points in the point cloud by parsing the code. The decoding of the point cloud includes position decoding and attribute decoding.

The process of position decoding includes: performing arithmetic decoding on the geometric code stream; merging after building the octree, reconstructing the position information of the point to obtain the reconstructed information of the point's position information; performing coordinate transformation on the reconstructed information of the point's position information to obtain the point's position information. The point's position information can also be called the point's geometric information.

The attribute decoding process includes: obtaining the residual value of the attribute information of the point in the point cloud by parsing the attribute code stream; obtaining the residual value of the attribute information of the point after dequantization by dequantizing the residual value of the attribute information of the point; based on the reconstruction information of the point position information obtained in the position decoding process, selecting one of attribute prediction compensation and attribute inverse transformation to perform point cloud processing to obtain the reconstructed value of the attribute information of the point; performing color space inverse conversion on the reconstructed value of the attribute information of the point to obtain a decoded point cloud.

As shown in FIG4B , position decoding can be achieved by the following units:

The first entropy decoding unit 301, the octree reconstruction (synthesize octree) unit 302, the inverse coordinate quantization and inverse coordinate translation unit 303.

The first entropy decoding unit 301 may decode the geometric code stream by using an entropy decoding method to obtain the placeholder information of each node in the octree.

The octree reconstruction unit 301 reconstructs the octree based on the placeholder information of each node in the octree decoded by the first entropy decoding unit 301. In the geometric reconstruction process based on the octree, the placeholder code of each node is obtained by continuous parsing in the order of breadth-first traversal, and the nodes are continuously divided in turn until a 1x1x1 unit cube is obtained, and the division is stopped when the division obtains the number of points contained in each leaf node, and finally the geometric reconstruction value of the point cloud is restored.

The inverse coordinate quantization and inverse coordinate translation unit 303 performs inverse coordinate translation and inverse quantization operations on the geometric reconstruction value of the point cloud reconstructed by the octree reconstruction unit 302 to obtain the geometric reconstruction value of the midpoint of the point cloud in the world coordinate.

Attribute encoding can be achieved through the following units:

A second entropy decoding unit 310, an inverse quantization unit 311, an attribute prediction compensation unit 312, an attribute inverse transformation unit 313 and an inverse spatial transformation (inverse trasform colors) unit 314.

In some embodiments, if the encoding end uses attribute prediction to encode the attribute information of the point cloud, the second entropy decoding unit 310 decodes the attribute code stream to obtain the quantized attribute residual, and the inverse quantization unit 313 inversely quantizes the quantized attribute residual to obtain the attribute residual value. The attribute prediction compensation unit 312 obtains the attribute prediction value of the point in the point cloud based on the reconstructed geometric information of the point cloud, and then adds the attribute prediction value to the attribute residual value to obtain the attribute reconstruction value of the point. Then, the inverse space conversion unit 314 performs color space inverse conversion on the attribute reconstruction value of the point, for example, from the YUV color space to the RGB color space, to obtain the reconstructed attribute information of the point cloud.

In some embodiments, if the encoding end uses attribute coding to encode the attribute information of the point cloud, the second entropy decoding unit 310 decodes the attribute code stream to obtain the quantized attribute residual and the quantized transformation coefficient. The inverse quantization unit 313 inversely quantizes the quantized attribute residual and the quantized transformation coefficient to obtain the attribute residual and the transformation coefficient of the point. The attribute inverse transformation unit 313 performs an inverse wavelet transform on the transformation coefficient of the point in the point cloud based on the reconstructed geometric information of the point cloud to obtain the attribute reconstruction value of the point in the point cloud, and then adds the attribute reconstruction value to the attribute residual value to obtain the reconstructed attribute value of the point. Then, the inverse space conversion unit 314 performs an inverse color space conversion on the reconstructed attribute value of the point, for example, from the YUV color space to the RGB color space, to obtain the reconstructed attribute information of the point cloud.

It should be noted that decompression is the inverse process of compression. Similarly, the functions of each unit in the decoder 300 can refer to the functions of the corresponding units in the encoder 200. In addition, the point cloud decoder 300 may include more, fewer or different functional components than those in FIG. 4B.

In some embodiments, there are 4 general test conditions for AVS PCC:

Condition 1: The geometric position is limitedly lossy and the attributes are lossy;

Condition 2: The geometric position is lossless, but the attributes are lossy;

Condition 3: The geometric position is lossless, and the attributes are limitedly lossy;

Condition 4: The geometric position and attributes are lossless.

Exemplarily, the universal test sequence includes five categories, namely Cat1A, Cat1B, Cat1C, Cat2-frame and Cat3, wherein Cat1A and Cat2-frame point clouds only contain reflectivity attribute information, Cat1B and Cat3 point clouds only contain color attribute information, and Cat1B point cloud contains both color and reflectivity attribute information.

Based on the algorithm used for attribute compression, point cloud attribute compression methods include but are not limited to the following:

The first one is that attribute compression adopts an intra-frame prediction-based method.

For example, at the encoding end, the points in the point cloud are processed in a certain order, such as the original acquisition order of the point cloud, the Morton order, the Hilbert order, etc., and the prediction algorithm is first used to obtain the attribute prediction value, and the attribute residual is obtained according to the attribute value and the attribute prediction value. Then, the attribute residual is quantized to generate a quantized residual, and finally the quantized residual is encoded.

At the decoding end, the points in the point cloud are processed in a certain order, such as the original acquisition order of the point cloud, the Morton order, the Hilbert order, etc., and the prediction algorithm is first used to obtain the attribute prediction value. Then, the decoding obtains the quantized residual, and then the quantized residual is dequantized. Finally, the attribute reconstruction value is obtained based on the attribute prediction value and the dequantized residual.

The second is a resource-constrained attribute compression method based on intra-frame prediction and DCT transform. In this method, when encoding the quantized transform coefficients, there is a limit of a maximum number of points X (such as 4096), that is, at most every X points are encoded as a group.

Exemplarily, at the encoding end, the points in the point cloud are processed in a certain order, such as the original acquisition order of the point cloud, the Morton order, the Hilbert order, etc., and the entire point cloud is first divided into a number of small groups with a maximum length of Y (such as 2), and then the small groups are combined into a number of large groups (the number of points in each large group does not exceed X, such as 4096). Then, the prediction algorithm is used to obtain the attribute prediction value, and the attribute residual is obtained according to the attribute value and the attribute prediction value. The attribute residual is subjected to DCT transformation in small groups to generate transformation coefficients, and then the transformation coefficients are quantized to generate quantized transformation coefficients, and finally the quantized transformation coefficients are encoded in large groups.

At the decoding end, the points in the point cloud are processed in a certain order, such as the original acquisition order of the point cloud, the Morton order, the Hilbert order, etc. First, the entire point cloud is divided into several small groups with a maximum length of Y (such as 2), and then these small groups are combined into several large groups (the number of points in each large group does not exceed X, such as 4096), and the quantized transformation coefficients are decoded in large groups. Next, the prediction algorithm is used to obtain the attribute prediction value, and then the quantized transformation coefficients are dequantized and inversely transformed in small groups. Finally, the attribute reconstruction value is obtained based on the attribute prediction value and the dequantized and inversely transformed coefficients.

The third is a resource-infinite attribute compression method based on intra-frame prediction and DCT transformation. In this method, when encoding the quantized transformation coefficients, there is no limit on the maximum number of points X, that is, all coefficients are encoded together.

For example, at the encoding end, the points in the point cloud are processed in a certain order, such as the original acquisition order of the point cloud, the Morton order, the Hilbert order, etc., and the entire point cloud is first divided into a number of small groups with a maximum length of Y (such as 2). Then, a prediction algorithm is used to obtain attribute prediction values, and attribute residuals are obtained according to the attribute values and the attribute prediction values. The attribute residuals are subjected to DCT transformation in small groups to generate transformation coefficients, and then the transformation coefficients are quantized to generate quantized transformation coefficients. Finally, the quantized transformation coefficients of the entire point cloud are encoded.

At the decoding end, the points in the point cloud are processed in a certain order, such as the original acquisition order of the point cloud, the Morton order, the Hilbert order, etc. The entire point cloud is first divided into several small groups with a maximum length of Y (such as 2), and the quantized transformation coefficients of the entire point cloud are obtained by decoding. Then, the prediction algorithm is used to obtain the attribute prediction value, and the quantized transformation coefficients are dequantized and inversely transformed in small groups. Finally, the attribute reconstruction value is obtained based on the attribute prediction value and the dequantized and inversely transformed coefficients.

The fourth one is that attribute compression adopts a method based on multi-layer wavelet transform.

Exemplarily, at the encoding end, a multi-layer wavelet transform is performed on the entire point cloud to generate transform coefficients, and then the transform coefficients are quantized to generate quantized transform coefficients, and finally the quantized transform coefficients of the entire point cloud are encoded.

At the decoding end, decoding obtains the quantized transform coefficients of the entire point cloud, and then dequantizes and inversely transforms the quantized transform coefficients to obtain attribute reconstruction values.

The above is the basic process of the point cloud codec based on the AVS codec framework. With the development of technology, some modules or steps of the framework or process may be optimized. This application is applicable to the basic process of the point cloud codec based on the AVS codec framework, but is not limited to this framework and process.

The following introduces octree-based geometric coding and prediction tree-based geometric coding.

Octree-based geometric encoding includes: first, coordinate transformation of geometric information so that all point clouds are contained in a bounding box. Then quantization is performed. This step of quantization mainly plays a role of scaling. Due to quantization rounding, the geometric information of some points is the same. Whether to remove duplicate points is determined based on parameters. The process of quantization and removal of duplicate points is also called voxelization. Next, the bounding box is continuously divided into trees (octree/quadtree/binary tree) in the order of breadth-first traversal, and the placeholder code of each node is encoded. In an implicit geometric division method, the bounding box of the point cloud is first calculated.

Assume that the bounding box of _dx > _dy > _dz corresponds to a cuboid. During geometric partitioning, binary tree partitioning will be performed based on the x-axis to obtain two child nodes. When the condition of _dx = _dy > _dz is met, quadtree partitioning will be performed based on the x-axis and y-axis to obtain four child nodes. When the condition of _dx = _dy = _dz is finally met, octree partitioning will be performed until the leaf node obtained by partitioning is a 1x1x1 unit cube. The partitioning will be stopped, and the points in the leaf node will be encoded to generate a binary code stream. In the process of binary tree/quadtree/octree partitioning, two parameters are introduced: K and M. Parameter K indicates the maximum number of binary tree/quadtree partitioning before octree partitioning; parameter M is used to indicate that the minimum block side length corresponding to binary tree/quadtree partitioning is ^2M . At the same time, K and M must meet the following conditions: Assuming d _max = max(d _x , _dy , d _z ), d _min = min(d _x , _dy , d _z ), parameter K satisfies: K＞＝d _max -d _min ; parameter M satisfies: M＞＝d _min . The reason why parameters K and M meet the above conditions is that in the process of geometric implicit partitioning of G-PCC, the priority of partitioning is binary tree, quadtree and octree. When the node block size does not meet the conditions of binary tree/quadtree, the node will be partitioned by octree until it is partitioned to the minimum unit of leaf node 1X1X1. However, the geometric information coding mode based on octree has an efficient compression rate only for points with correlation in space, while for points in isolated positions in geometric space, the use of direct coding mode (Direct Coding Model, referred to as DCM) coding can greatly reduce the complexity. For all nodes in the octree, the use of DCM is not represented by flag information, but is inferred by the parent node and neighbor information of the current node. There are two ways to determine whether the current node is eligible for DCM encoding:

(1) The current node has only one occupied child node, and the parent node of the current node's parent node has only two occupied child nodes, that is, the current node has at most one neighbor node.

(2) The parent node of the current node has only one child node, the current node. At the same time, the six neighbor nodes that share a face with the current node are also empty nodes.

If the current node does not have the DCM coding qualification, it will be divided into octrees. If it has the DCM coding qualification, the number of points contained in the node will be further determined. When the number of points is less than the threshold 2, the node will be DCM-encoded, otherwise the octree division will continue. When the DCM coding mode is applied, the geometric coordinates X, Y, and Z components of the points contained in the current node will be directly encoded independently. When the side length of a node is ^2d , d bits are required to encode each component of the geometric coordinates of the node, and the bit information is directly encoded into the bit stream.

It should be noted that when nodes are divided into leaf nodes, in the case of geometric lossless coding, the number of repeated points in the leaf nodes needs to be encoded. Finally, the placeholder information of all nodes is encoded to generate a binary code stream. In addition, G-PCC currently introduces a plane coding mode. In the process of geometric division, it will determine whether the child nodes of the current node are in the same plane. If the child nodes of the current node meet the conditions of the same plane, the child nodes of the current node will be represented by the plane.

In octree-based geometric decoding, the decoding end obtains the placeholder code of each node by continuously parsing in the order of breadth-first traversal, and continuously divides the nodes in turn until a 1X1X1 unit cube is obtained. The number of points contained in each leaf node is parsed, and finally the geometric reconstructed point cloud information is restored.

The geometric coding based on the prediction tree includes: first, sorting the input point cloud. The currently used sorting methods include unordered, Morton order, azimuth order and radial distance order. At the encoding end, the prediction tree structure is established by using two different methods, including: KD-Tree (high-latency slow mode) and using the laser radar calibration information to divide each point into different Lasers, and establish a prediction structure according to different Lasers (low-latency fast mode). Next, based on the structure of the prediction tree, traverse each node in the prediction tree, predict the geometric position information of the node by selecting different prediction modes to obtain the prediction residual, and quantize the geometric prediction residual using the quantization parameter. Finally, through continuous iteration, the prediction residual of the prediction tree node position information, the prediction tree structure and the quantization parameters are encoded to generate a binary code stream.

Based on the geometric decoding of the prediction tree, the decoding end reconstructs the prediction tree structure by continuously parsing the bit stream, and then obtains the geometric position prediction residual information and quantization parameters of each prediction node through parsing, and dequantizes the prediction residual to recover the reconstructed geometric position information of each node, and finally completes the geometric reconstruction of the decoding end.

After the geometric encoding is completed, the geometric information is reconstructed. At present, attribute encoding is mainly performed on color information. First, the color information is converted from the RGB color space to the YUV color space. Then, the point cloud is recolored using the reconstructed geometric information so that the unencoded attribute information corresponds to the reconstructed geometric information.

Currently in the point cloud encoding and decoding of AVS, for each voxel-level leaf node in the octree, it is necessary to encode and decode the duplicate point information of the leaf node, but not every leaf node has duplicate points. Therefore, encoding and decoding duplicate point information for each leaf node increases the complexity of encoding and decoding, wastes a lot of encoding and decoding time, and makes the encoding and decoding efficiency low.

In order to solve the above technical problems, in the embodiment of the present application, in point cloud encoding and decoding, for example, in point cloud encoding and decoding based on AVS, when encoding and decoding the current node of the N-1th layer in the octree of the point cloud, the first parameter corresponding to the current node is first determined, and the first parameter is used to determine whether at least one non-zero child node of the current node includes duplicate points. The current node is a non-zero node of the N-1th layer in the octree of the point cloud, and N is the total number of layers of the octree. Then, based on the first parameter, the current node is geometrically decoded. For example, when it is determined based on the first parameter that the i-th non-zero child node of the current node does not include duplicate points, the encoding and decoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the encoding and decoding complexity of the point cloud, saving encoding and decoding time, and improving the encoding and decoding efficiency.

The point cloud encoding and decoding method involved in the embodiments of the present application is introduced below in conjunction with specific embodiments.

First, taking the decoding end as an example, the point cloud decoding method provided in the embodiment of the present application is introduced.

Fig. 5 is a schematic diagram of a point cloud decoding method according to an embodiment of the present application. The point cloud decoding method according to the embodiment of the present application can be implemented by the point cloud decoding device shown in Fig. 3 or Fig. 4B.

As shown in FIG5 , the point cloud decoding method of the embodiment of the present application includes:

S101, determining a first parameter corresponding to the current node;

S102. Perform geometric decoding on the current node based on the first parameter.

Among them, the first parameter is used to determine whether at least one non-zero child node of the current node includes duplicate points. The current node is a non-zero node in the N-1th layer of the octree of the point cloud. The octree is obtained by node division of the point cloud. N is the total number of layers of the octree, and N is a positive integer greater than 1.

The point cloud decoding method proposed in the embodiment of the present application can be applied to a variety of point cloud decoding scenarios. In some embodiments, if the point cloud decoding method of the embodiment of the present application is applied to AVS, the above octree is obtained by dividing the point cloud into nodes based on the AVS method.

The point cloud of the embodiment of the present application can be understood as a point cloud block or point cloud slice that can be decoded individually.

For example, the point cloud in the embodiment of the present application is the entire point cloud sequence that has not been divided.

For another example, if the embodiment of the present application decides to divide the point cloud sequence based on parameter configuration, the point cloud of the embodiment of the present application can be understood as a point cloud slice in at least one slice into which the entire point cloud sequence is divided.

As can be seen from the above, the point cloud includes geometric information and attribute information, and the decoding of the point cloud includes geometric decoding and attribute decoding. The embodiments of the present application relate to geometric decoding of the point cloud. That is, the decoded points involved in the embodiments of the present application refer to points in the point cloud whose geometric information has been decoded, and the undecoded points refer to points in the point cloud whose geometric information has not been decoded.

In some embodiments, the geometric information of the point cloud is also referred to as the position information of the point cloud. Therefore, the geometric decoding of the point cloud is also referred to as the position decoding of the point cloud.

In some embodiments, if the current point cloud only uses octree coding in AVS geometric coding, and does not use prediction tree coding, that is, the prediction tree coding algorithm is closed. At this time, the encoding end constructs the octree structure of the point cloud based on the octree coding method. For example, as shown in Figure 6, the point cloud is surrounded by the smallest cuboid, and the bounding box is first divided into octrees to obtain 8 nodes. The occupied nodes among these 8 nodes, that is, the nodes including the points, continue to be divided into octrees, and so on, until they are divided into voxel-level positions, for example, into 1X1X1 cubes. The point cloud octree structure obtained by such division includes multiple layers of nodes, for example, including N layers. When encoding, the placeholder information of each layer is encoded layer by layer until the voxel-level leaf nodes of the last layer are encoded. That is to say, in octree coding, the point cloud is divided through the octree, and finally the points in the point cloud are divided into the voxel-level leaf nodes of the octree. By encoding the entire octree, the encoding of the point cloud is realized.

Correspondingly, the decoding end first decodes the geometric code stream of the point cloud to obtain the occupancy information of the root node of the octree of the point cloud, and based on the occupancy information of the root node, determines the child nodes included in the root node, that is, the nodes included in the second layer of the octree. Then, the geometric code stream is decoded to obtain the occupancy information of each node in the second layer, and based on the occupancy information of each node, determines the nodes included in the third layer of the octree, and so on.

In some embodiments, in the AVS geometric coding of the current point cloud, the coding end can use prediction tree coding while using octree coding, that is, the prediction tree coding algorithm is turned off. At this time, as shown in Figure 7, the octree is first used to perform octree division on the bounding box of the point cloud, and the division is divided to a preset depth. For example, after division to 3 layers, for each non-zero node obtained by the division, it is determined whether the node is encoded by prediction tree or octree. If it is determined that the node is encoded by prediction tree, the prediction tree coding method is used to perform prediction tree coding on the geometric information of the points included in the node. For example, it is determined that the first node in the third layer uses the prediction tree coding method, then the points included in the node are sorted, and the preset prediction tree coding method is used to construct a prediction tree for the sorted points, such as constructing an L3C2 single chain. Then, based on the structure of the prediction tree, each node in the prediction tree is traversed, and the geometric position information of the node is predicted by selecting different prediction modes to obtain the prediction residual, and the geometric prediction residual is quantized using the quantization parameter. Finally, through continuous iteration, the prediction residual, prediction tree structure and quantization parameter of the prediction tree node position information are encoded. If it is determined that the node is divided by octree, the octree partitioning method is used to divide the node until it is divided into leaf nodes at the voxel level, and the occupancy information of each node in the octree is encoded to form a geometric code stream. The gray nodes in Figure 7 are non-empty nodes.

Optionally, if the node is encoded using a prediction tree encoding method, the encoding end indicates that the node is encoded using the prediction tree encoding method through a parameter. For example, the parameter may be a first flag, and the encoding end indicates that the node is encoded using the prediction tree encoding method by setting the first flag to true, for example, setting the first flag to 1. In this way, the decoding end determines that the node is encoded using the prediction tree encoding method by decoding the first flag, and correspondingly, performs geometric decoding on the node using the prediction tree decoding method to obtain the geometric reconstruction values of the points included in the node.

In this embodiment, the decoding end decodes the geometric code stream of the point cloud, obtains the placeholder information of the nodes in the octree, and reconstructs the octree based on the placeholder information. As shown in FIG8 , after the third layer is constructed, in the process of reconstructing the octree, if it is determined that a certain node adopts prediction tree coding, for example, the value of the first flag corresponding to the node obtained by decoding is set to true, then it is determined that the node adopts prediction tree coding. In this way, the decoding end uses the prediction tree decoding method to perform geometric decoding on the node and obtains the geometric reconstruction value of the point included in the node. If it is determined that the node adopts octree coding, the octree is reconstructed on the node based on the placeholder information of the node until the leaf node at the voxel level.

It can be seen from the above Figures 6 and 7 that in the point cloud geometry coding of AVS, regardless of whether the prediction tree coding is turned on, at least some points in the point cloud are divided into octrees and finally divided into leaf nodes at the voxel level.

In some embodiments, since some points in the point cloud have the same coordinate information, these points with the same coordinates are divided into the same leaf node of the octree, so that the leaf node includes repeated points.

Currently, when encoding the node of the N-1th layer of the octree (i.e., the second to last layer of the octree), the encoder not only encodes the placeholder information of the node, but also encodes the repeated point information of the non-zero child nodes (i.e., leaf nodes) of the node. Correspondingly, when decoding the node of the N-1th layer of the octree, the decoder not only decodes the placeholder information of the node, but also decodes the repeated point information of the non-zero child nodes of the node. This will increase the complexity of decoding, waste decoding time, and reduce decoding efficiency.

From the above, it can be seen that in the octree of the point cloud, not every leaf node includes duplicate points. It can even be understood that only a few leaf nodes in the octree of the point cloud include duplicate points. Based on this, in an embodiment of the present application, when decoding the current node of the N-1th layer of the octree of the point cloud, the first parameter corresponding to the current node is first determined. The first parameter is used to determine whether at least one non-zero child node (i.e., leaf node) of the current node includes duplicate points, and then based on the first parameter, the current node is decoded. For example, when it is determined based on the first parameter that the i-th non-zero child node of the current node does not include duplicate points, the decoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the decoding complexity of the point cloud, saving decoding time, and improving decoding efficiency.

The embodiments of the present application mainly relate to the decoding process of the nodes in the N-1th layer of the point cloud octree. The N-1th layer can also be understood as the second to last layer of the octree of the point cloud.

When decoding the non-zero nodes in the N-1th layer of the octree, it is necessary not only to decode the placeholder information of the non-zero node, but also to decode the repeated point information included in the non-zero child nodes of the node. The non-zero child nodes of the non-zero nodes in the N-1th layer are the voxel-level leaf nodes of the octree, that is, the last layer nodes.

In an embodiment of the present application, the decoding process for each non-zero node in the N-1th layer of the octree is basically the same. For the convenience of description, the decoding process of the embodiment of the present application is introduced by taking the current node in the N-1th layer of the octree as an example.

In some embodiments, the current node can be understood as any non-zero node in the N-1th layer of the octree, and the non-zero node is also called a non-empty node, or an occupied node. The non-zero node can be understood as a node including at least one non-zero child node, or a node including at least one point in the point cloud.

In some embodiments, the current node may be understood as a non-zero node in the N-1th layer of the octree that is currently waiting to be decoded.

In the embodiment of the present application, before decoding the current node, the first parameter corresponding to the current node is first determined, and then the current node is decoded based on the first parameter. In the embodiment of the present application, the method for determining the first parameter corresponding to the current node is different, and the corresponding method for decoding the current node based on the first parameter is also different. The following is a detailed introduction to several methods for determining the first parameter corresponding to the current node and the process for decoding the current node based on the first parameter involved in the embodiment of the present application.

In case 1, the above S101 includes the following steps S101-A1 to S101-A2:

S101-A1, determine the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer;

S101-A2: Determine a first parameter based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer.

In the embodiment of the present application, the encoding end encodes the nodes in the octree based on the breadth-first traversal method. Correspondingly, the decoding end decodes the nodes in the octree based on the breadth-first traversal method.

In this case 1, the first parameter corresponding to the current node is determined based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer of the octree of the point cloud. The first parameter can be understood as the number of points in the current point cloud whose geometric information cannot be determined. Then, based on the first parameter, the current node is decoded. For example, based on the first parameter, it is determined whether the non-zero child nodes of the current node include duplicate points. If it is determined based on the first parameter that the non-zero child nodes of the current node do not include duplicate points, the duplicate point information of the non-zero child nodes of the current node is skipped to reduce the decoding complexity of the point cloud, save decoding time, and thus improve decoding efficiency.

The embodiment of the present application does not limit the specific method in which the decoding end obtains the total number of points in the point cloud.

In some embodiments, the encoding end writes the total number of points of the point cloud into the geometric code stream, so that the decoding end obtains the total number of points of the point cloud by decoding the geometric code stream.

In some embodiments, the encoder writes the total number of points of the point cloud into the geometry brick header (gbh) of the point cloud. In this way, the decoder obtains the total number of points of the point cloud by decoding the geometry brick header of the point cloud.

In some embodiments, since the point cloud includes at least one point, in order to save code words, when encoding the total number of points in the point cloud, the encoder divides the number of points in the point cloud into the low-order part num_points_lower of the number of points contained in the slice and the high-order part num_points_upper of the number of points contained in the slice, and writes num_points_lower and num_points_upper into the geometry unit header. Correspondingly, when decoding, the decoder decodes the geometry unit header to obtain num_points_lower and num_points_upper, and then adds num_points_upper and um_points_lower to obtain the total number of points in the point cloud.

In one example, the parameters of the geometry unit head are specifically shown in Table 2:

Table 2

In Table 2, num_points_upper and num_points_lower are used to specify the total number of points in the point cloud.

That is to say, the decoding end obtains the total number of points of the point cloud by decoding num_points_upper and num_points_lower shown in Table 2.

In some embodiments, num_points_upper, an unsigned integer, indicates the number of bits of points in the slice that are higher than 16 bits. num_points_lower, an unsigned integer, indicates the lower 16 bits of points in the slice. At this time, the decoder determines the total number of points in the point cloud based on the following formula (1):

num_points＝((num_points_upper<<16)+num_points_lower) (1)

Among them, num_points is the total number of points in the point cloud.

Similarly, the embodiment of the present application does not limit the method for determining the number of non-zero nodes in the N-1th layer of the octree of the point cloud.

In some embodiments, the encoder may write the number of non-zero nodes included in the N-1th layer in the octree into the geometry bitstream. In this way, the decoder may obtain the number of non-zero nodes in the N-1th layer by decoding the geometry bitstream.

In some embodiments, it can be seen from the above that the encoding end encodes the placeholder information of the nodes of each layer of the octree in a breadth-first traversal manner, for example, based on the non-zero child nodes included in each non-zero node in the N-2th layer, determines the placeholder information of each non-zero node in the N-2th layer, and then writes the placeholder information of each non-zero node in the N-2th layer into the geometry code stream. In this way, the decoding end decodes the placeholder information of each non-zero node in the N-2th layer and can determine the number of non-zero nodes included in the N-1th layer.

For example, as shown in Figure 8, assuming that the octree of the point cloud includes 4 layers, that is, N=4, and the placeholder information of the root node of the first layer is 0000010, it means that only one node in the second layer of the octree is occupied, that is, the 7th node is occupied. Assuming that the occupancy information of the 7th node in the second layer is 01010101, it means that 4 nodes in the third layer of the octree are occupied. Assuming that the placeholder information of the second node in the third layer is 01010101, the placeholder information of the fourth node in the third layer is 01010100, the placeholder information of the sixth node in the third layer is 00000010, and the placeholder information of the eighth node in the fourth layer is also 00000010. Therefore, in this embodiment, the decoding end can determine the number of non-zero nodes in the N-1 layer based on the placeholder information of the N-2 layer of the octree of the point cloud. For example, if the placeholder information of the N-2 layer is 01010101, it means that the N-1 layer includes 4 nodes, and these 4 nodes are occupied nodes, that is, non-zero nodes.

After the decoding end determines the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer through the above method, the first parameter corresponding to the current node is determined based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer.

The embodiment of the present application does not limit the specific method of determining the first parameter corresponding to the current node based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer.

In some embodiments, the decoding end determines the difference between the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer as the first parameter. In this embodiment, by determining the number of occupied nodes in the N-1th layer, it can be determined that the occupied nodes include at least one non-zero child node, that is, the occupied nodes in the N-1th layer correspond to at least one point. Therefore, the difference between the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer of the octree is determined as the number of points with uncertain geometric information in the point cloud, that is, the first parameter. For example, the point cloud includes 10 points, and the N-1th layer includes 4 non-zero nodes, which means that each of the 4 non-zero nodes in the N-1th layer includes at least one non-zero child node, and a non-zero child node includes at least one point. Therefore, it can be determined that the number of points with uncertain position information in the current point cloud is 10-4=6, and then the first parameter corresponding to the current node is determined to be 6.

In a possible implementation, the first parameter is determined based on the following formula (4):

resPointCount＝num_points–nodeCount (4)

Among them, resPointCount is the first parameter corresponding to the current node, num_points is the total number of points in the point cloud, and nodeCount is the number of nodes included in the N-1th layer of the octree of the point cloud.

In some embodiments, the N-1th layer of the octree can be expressed as occtree_depth_minus1, that is, the octree depth occtree_depth minus 1, where the octree depth occtree_depth is N.

After the first parameter corresponding to the current node is determined based on the above method, the above step S102 is executed to decode the current node based on the first parameter.

In some embodiments, if the first parameter corresponding to the current node is determined to be 0, for example, the total number of points in the point cloud is a, and the N-1th layer of the octree of the point cloud includes a nodes, then the first parameter is determined to be 0, which means that each non-zero node in the N-1th layer includes a non-zero child node, and the non-zero child node includes a point in the point cloud, and no duplicate points are included. At this time, when decoding the nodes in the N-1th layer, the duplicate point information of the non-zero child nodes of each non-zero node is skipped, thereby reducing the decoding complexity and saving decoding time.

In some embodiments, if it is determined that the first parameter corresponding to the current node is not 0, the above S102 is as shown in the following situation 1.

In case 1, the above S102 includes the following steps S102-A1 to S102-A2:

S102-A1. For the i-th non-zero child node of the current node, determine a second parameter corresponding to the i-th non-zero child node, where the second parameter is used to indicate the number of points whose geometric positions in the point cloud have been decoded when decoding the i-th non-zero child node;

S102-A2: Determine whether to decode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter.

From the above, it can be seen that the current node includes at least one non-zero child node. When decoding the current node, the specific process of determining whether to decode the repeated point information of each non-zero child node included in the current node is the same. For the sake of ease of description, the i-th non-zero child node of the current node is taken as an example for explanation.

In this case 1, the decoding end determines the first parameter corresponding to the current node based on the above steps S102-A1 to S102-A2. The first parameter can be understood as the number of points in the point cloud whose current position information is not determined. Next, the second parameter corresponding to the i-th non-zero child node of the current node is determined. The second parameter is used to indicate the number of points whose geometric positions in the point cloud have been decoded when decoding the i-th non-zero child node. Finally, based on the first parameter corresponding to the current node and the second parameter corresponding to the i-th non-zero child node, it is determined whether the i-th non-zero child node includes duplicate points, and then it is determined whether to decode the duplicate point information of the i-th non-zero child node.

The specific process of determining the second parameter corresponding to the i-th non-zero child node is introduced below.

The embodiment of the present application does not limit the specific method of determining the second parameter corresponding to the current i-th non-zero child node.

In some embodiments, during decoding, the decoding end records in real time the number of points whose geometric positions have been decoded in the current point cloud, and then when decoding the current node, determines the number of points determined by the geometric position information that has been determined before decoding the repeated point information of the i-th non-zero child node.

In some embodiments, determining the second parameter corresponding to the i-th non-zero child node in the above S102-A1 includes the following steps S102-A11 and S102-A12:

S102-A11. Determine the number of first decoded points corresponding to the i-th non-zero child node in the point cloud.

In this embodiment, the decoding end determines the second parameter corresponding to the i-th non-zero subnode by determining the first number of decoded points corresponding to the i-th non-zero subnode in the point cloud and based on the first number of decoded points corresponding to the i-th non-zero subnode in the point cloud. For example, the first number of decoded points corresponding to the i-th non-zero subnode in the point cloud is determined as the second parameter corresponding to the i-th non-zero subnode.

In this embodiment, the first number of decoded points corresponding to the i-th non-zero child node can be understood as the total number of points currently decoded by the decoding end when determining whether to decode the repeated point information of the i-th non-zero child node of the current node.

In some embodiments, the decoding end starts a counter during decoding, and the counter is used to record the number of decoded points in real time, so that when decoding the i-th non-zero child node, the first decoded point number corresponding to the i-th non-zero child node can be obtained from the counter.

In some embodiments, when decoding the i-th non-zero child node, the decoding end determines the number of first decoded points corresponding to the i-th non-zero child node through the following steps:

S102-A11-1. Determine the number of third decoded points corresponding to the i-th non-zero child node;

S102-A11-2. Determine the number of first decoded points based on the number of third decoded points.

The third decoded point can be understood as a decoded point in the leaf node of the octree. The decoding end determines the number of first decoded points corresponding to the i-th non-zero child node by determining the number of points included in the decoded leaf node before the i-th non-zero child node.

The implementation methods for determining the number of the third decoded points corresponding to the i-th non-zero child node in the above S102-A11-1 include but are not limited to the following:

Method 1: if the current node is the first non-zero node in the N-1th layer, the above S102-A11-1 includes the following steps S102-A11-1-a1 and S102-A11-1-a2:

S102-A11-1-a1, determine the number of non-zero child nodes of the current node;

S102-A11-1-a2. Determine the number of third decoded points corresponding to the i-th non-zero child node based on the number of non-zero child nodes of the current node.

In method 1, if the current node is the first non-zero node in the N-1th layer of the octree, the number of non-zero child nodes included in the current node is determined, and based on the number of non-zero child nodes of the current node, the number of third decoded points corresponding to the i-th non-zero child node is determined.

The method of determining the number of non-zero child nodes of the current node includes at least the following examples:

Example 1: The encoder writes the number of non-zero child nodes of each non-zero node in the N-1th layer of the octree into the geometry bitstream. In this way, the decoder can obtain the number of non-zero child nodes of each non-zero node in the N-1th layer by decoding the geometry bitstream, and further obtain the number of non-zero child nodes of the current node.

Example 2: The encoder writes the placeholder information of each non-zero node in the N-1th layer into the decoded code stream. Exemplarily, the encoder determines the placeholder information of the current node based on the occupancy of each non-zero child node of the current node in the N-1th layer. Assuming that among the 8 child nodes of the current node, the 2nd child node, the 4th child node, the 6th child node and the 8th child node are occupied, the placeholder information of the current node is determined to be 01010101, and the placeholder information is written into the geometric code stream. In this way, when the decoder decodes the current node in the N-1th layer, the placeholder information of the current node obtained by decoding is 01010101, and it can be determined that the current node includes 4 non-zero child nodes.

After the decoding end determines the number of non-zero child nodes of the current node, the number of third decoded points corresponding to the i-th non-zero child node is determined based on the number of non-zero child nodes of the current node.

Among them, the methods for determining the number of third decoded points corresponding to the i-th non-zero child node based on the number of non-zero child nodes of the current node in S102-A11-1-a2 include but are not limited to the following:

Method 1: If the i-th non-zero child node is the first non-zero child node of the current node, the number of non-zero child nodes included in the current node is reduced by 1 to determine the third number of decoded points corresponding to the i-th non-zero child node.

For example, as shown in FIG8 , assuming that the current node is the first non-zero node in the third layer in FIG8 , and the placeholder information of the current node is 01010101, it can be determined that the current node includes 4 non-zero child nodes. Assuming that the i-th non-zero child node is the first non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of the 4 non-zero child nodes of the current node can be determined, so the geometric position information of the 4 non-zero child nodes included in the current node has been decoded, that is, the 4 non-zero child nodes included in the current node are decoded points for the first non-zero child node in the current node. It should be noted that when determining the first parameter above, it is assumed that the current node includes a decoded point, therefore, it is necessary to reduce the number of non-zero child nodes included in the current node by 1, and determine it as the third number of decoded points corresponding to the i-th non-zero child node, for example, the third number of decoded points corresponding to the i-th non-zero child node is determined to be 4-1=3.

Method 2: If the i-th non-zero child node is not the first non-zero child node of the current node, obtain the sum of the first number of repeated points included in the non-zero child nodes of the current node that are located before the i-th non-zero child node; subtract 1 from the number of non-zero child nodes included in the current node, and then add it to the sum of the first number of repeated points to obtain the third number of decoded points corresponding to the i-th non-zero child node.

In method 2, if the i-th non-zero child node of the current node is not the i-th non-zero child node of the current node, that is, before the i-th child node, at least one non-zero child node of the current node has been decoded, the decoded non-zero child nodes may include duplicate points. Therefore, when determining the third number of decoded points corresponding to the i-th child node, the number of decoded duplicate points needs to be considered.

Specifically, if the current node is the first non-zero node in the N-1th layer, and the i-th non-zero child node of the current node is not the first non-zero child node of the current node, then obtain the sum of the first number of repeated points included in the non-zero child nodes of the current node that are located before the i-th non-zero child node; subtract 1 from the number of non-zero child nodes included in the current node, and then add it to the sum of the first number of repeated points to obtain the third number of decoded points corresponding to the i-th non-zero child node.

For example, assuming that the current node is the first non-zero node in the third layer in Figure 8, and the placeholder information of the current node is 01010101, it can be determined that the current node includes 4 non-zero child nodes. Assume that the first child node of the current node includes 1 repeated point, and assume that the i-th non-zero child node is the second non-zero child node of the current node. When determining whether the node has repeated point information of the second non-zero child node of the current node, first determine the number of decoded points corresponding to the second non-zero child node. Specifically, the number of decoded points corresponding to the second non-zero child node is the number of non-zero child nodes included in the current node minus 1, plus 1 repeated point of the first child node of the current node, and the number of decoded points corresponding to the second non-zero child node is 4-1+1=4.

In one example, the decoding end records the number of the third decoded points corresponding to the i-th non-zero child node in the current node through the following instructions:

Among them, codedCount is the number of the third decoded points corresponding to the i-th non-zero child node in the current node, codedCount is initialized to 0, nodeCount is the number of nodes in the N-1th layer of the octree, childCount is the number of non-zero child nodes included in the nodes in the N-1th layer, and dupPointNum is the number of duplicate points included in the non-zero child nodes.

In the above-mentioned method 1, assuming that the current node is the first non-zero node in the N-1th layer, the process of determining the number of the third decoded points corresponding to the i-th non-zero child node of the current node is introduced.

Method 2: If the current node is not the first non-zero node in the N-1th layer, the above S102-A11-1 includes the following steps S102-A11-1-b1 to S102-A11-1-b3:

S102-A11-1-b1, determine the number of decoded points corresponding to each non-zero node before the current node in the N-1th layer;

S102-A11-1-b2, determine the number of non-zero child nodes of the current node;

S102-A11-1-b3. Based on the number of decoded points corresponding to each non-zero node before the current node in the N-1th layer and the number of non-zero child nodes of the current node, determine the third number of decoded points corresponding to the i-th non-zero child node.

In the second method, if the current node is not the first non-zero node in the N-1th layer of the octree, it means that before decoding the current node, at least one non-zero node in the N-1th layer of the octree has been decoded. Therefore, in this embodiment, when determining the number of third decoded points corresponding to the i-th non-zero child node of the current node, first determine the number of decoded points corresponding to each non-zero node before the current node in the N-1th layer of the octree, then determine the number of non-zero child nodes of the current node, and then determine the third number of decoded points corresponding to the i-th non-zero child node based on the number of decoded points corresponding to each non-zero node before the current node in the N-1th layer and the number of non-zero child nodes of the current node.

The following describes how to determine the number of decoded points corresponding to each non-zero node before the current node in the N-1th layer in S102-A11-1-b1.

In a possible implementation, the number of non-zero child nodes included in each non-zero node before the current node is first determined, and then the number of non-zero child nodes included in each non-zero node is added to obtain a value of 1. Next, the total number of decoded duplicate points corresponding to each non-zero node is determined, and then the value 1 is added to the total number of duplicate points to obtain a value of 2, and the number of non-zero nodes before the current node in the N-1 layer is subtracted from the value 2 to obtain the number of decoded points corresponding to each non-zero node before the current node in the N-1 layer. In this embodiment, the decoding end can record the number of non-zero child nodes of each non-zero node in the N-1 layer, and at the same time, separately record the number of decoded duplicate points. Finally, based on the separately recorded number of non-zero child nodes and the number of duplicate points, the number of decoded points corresponding to each non-zero node before the current node in the N-1 layer is determined.

For example, assume that the current node is the third non-zero node in the third layer of the octree shown in FIG8 . When decoding the third non-zero node, the first non-zero node and the second non-zero node in the N-1th layer before the third non-zero node have been decoded. Assume that the placeholder information of the first non-zero node is 01010101, and the first non-zero child node of the first non-zero node includes 1 repeated point, and the placeholder information of the second non-zero node is 01010100. When decoding the third non-zero node, determine the number of decoded points corresponding to each non-zero node in the N-1th layer before the current node. That is, determine the number of non-zero child nodes of the first non-zero node and the second non-zero node respectively. It can be seen from the placeholder information that the first non-zero node includes 4 non-zero child nodes, and the second non-zero node includes 3 non-zero child nodes. Therefore, the first non-zero node and the second non-zero node include 7 non-zero child nodes in total. In addition, the first non-zero child node of the first non-zero node obtained by decoding includes 1 repeated point. Therefore, the number of decoded points corresponding to the first non-zero node and the second non-zero node before the third non-zero node is 7+1-2=6.

In another possible implementation, the decoding end obtains the number of non-zero child nodes of a non-zero node and the number of second repeated points included in the non-zero child nodes of the non-zero node for a non-zero node among the non-zero nodes; subtracts 1 from the number of non-zero child nodes of the non-zero node, and adds the sum of the number of second repeated points included in the non-zero child nodes of the non-zero node to obtain the number of decoded points corresponding to the non-zero node. In this implementation, the decoding end determines the number of decoded points corresponding to each non-zero node before the current node in the N-1th layer of the octree in the same manner, that is, the decoding end determines the number of decoded points corresponding to each non-zero node before the current node, and finally sums the number of decoded points corresponding to each non-zero node.

Specifically, for each non-zero node located before the current node in the N-1th layer, first determine the number of non-zero child nodes included in the non-zero node based on the placeholder information of the non-zero node, subtract 1 from the number of non-zero child nodes of the non-zero node, and obtain the value a. Next, determine the sum of the number of second repeated points included in the non-zero child nodes of the non-zero node, which is recorded as the value b. Finally, add the value a and the value b to obtain the number of decoded points corresponding to the non-zero node. According to this method, the number of decoded points corresponding to each non-zero node located before the current node in the N-1th layer can be determined.

For example, assume that the current node is the third non-zero node in the third layer of the octree shown in Figure 8. When decoding the third non-zero node, the first non-zero node and the second non-zero node in the N-1th layer before the third non-zero node have been decoded. Assume that the placeholder information of the first non-zero node is 01010101, and the first non-zero child node of the first non-zero node includes 1 repeated point, and the placeholder information of the second non-zero node is 01010100. When decoding the third non-zero node, determine the number of decoded points corresponding to each non-zero node in the N-1th layer before the current node. From the placeholder information, we can see that the first non-zero node includes 4 non-zero child nodes, the second non-zero node includes 3 non-zero child nodes, and the first non-zero child node of the first non-zero node includes 1 repeated point. It can be determined that the number of decoded points corresponding to the first non-zero node is 4-1+1=4, and the number of decoded points corresponding to the second non-zero node is 3-1=2.

Based on the above method, the number of decoded points corresponding to each non-zero node located before the current node in the N-1th layer is determined, and at the same time, the number of non-zero child nodes of the current node is determined. The method for determining the number of non-zero child nodes of the current node can refer to the description of S102-A11-a1 above, and will not be repeated here.

Next, the decoding end determines the third number of decoded points corresponding to the i-th non-zero child node based on the number of decoded points corresponding to each non-zero node before the current node in the N-1th layer and the number of non-zero child nodes of the current node.

The embodiment of the present application does not limit the specific implementation method of determining the third number of decoded points corresponding to the i-th non-zero child node in the above S102-A11-b3 based on the number of decoded points corresponding to each non-zero node located before the current node in the N-1th layer and the number of non-zero child nodes of the current node.

In some embodiments, the above S102-A11-1-b3 includes the following steps S102-A11-1-b31 and S102-A11-1-b32:

S102-A11-1-b31, adding the numbers of decoded points corresponding to each non-zero node before the current node in the N-1th layer to obtain a first sum value;

S102-A11-1-b32. Determine the number of third decoded points corresponding to the i-th non-zero child node based on the first sum and the number of non-zero child nodes of the current node.

In this embodiment, the decoding end determines the number of decoded points corresponding to each non-zero node located before the current node in the N-1th layer of the octree based on the above method. Then, the decoding end adds the number of decoded points corresponding to each non-zero node located before the current node in the N-1th layer to obtain a first sum value, and determines the third number of decoded points corresponding to the i-th non-zero child node based on the first sum value and the number of non-zero child nodes of the current node, thereby accurately determining the third number of decoded points corresponding to the i-th non-zero child node.

Among them, the implementation method of determining the number of third decoded points corresponding to the i-th non-zero child node based on the first sum and the number of non-zero child nodes of the current node in the above S102-A11-1-b32 includes at least the following two methods:

Method 1: If the i-th non-zero child node is the first non-zero child node of the current node, then add the first sum value to the number of non-zero child nodes included in the current node to obtain the second sum value; subtract 1 from the second sum value to obtain the third number of decoded points corresponding to the i-th non-zero child node.

In this method 1, if the current node is not the first non-zero node in the N-1th layer, and the i-th non-zero child node of the current node is the first non-zero child node of the current node, then based on the above steps, the number of decoded points of each decoded non-zero node before the current node in the N-1th layer is added to obtain a first sum value. At the same time, since the placeholder information of the current node has been decoded, the geometric position information of each child node of the current node can be determined, so each child node of the current node is determined as a decoded point, and then the first sum value is added to the number of child nodes of the current node to obtain a second sum value. In addition, since it is assumed that the current node includes a decoded point when determining the first parameter above, in order to avoid repeated counting of the decoded point, the determined second sum value is subtracted by 1 to obtain the third number of decoded points corresponding to the i-th non-zero child node.

For example, as shown in FIG8 , assuming that the current node is the second non-zero node in the third layer in FIG8 , and the placeholder information of the current node is 01010100, it can be determined that the current node includes 3 non-zero child nodes. Assuming that the i-th non-zero child node is the first non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of the three non-zero child nodes of the current node can be determined, so the geometric position information of the three non-zero child nodes included in the current node has been decoded. As shown in FIG8 , each non-zero node located before the current node in the third layer is the first non-zero node in the third layer. Assuming that the placeholder information of the first non-zero node is 01010101, and the first non-zero child node of the first non-zero node includes a repeated point, therefore, based on the above method, it can be determined that the number of decoded points corresponding to the first non-zero node is 4-1+1, that is, the first sum value is 4. Then, the first sum value 4 is added to the number of non-zero child nodes of the current node 3, and the second sum value is 4+3=7. It should be noted that when determining the first parameter above, it is assumed that the current node includes a decoded point. Therefore, it is necessary to subtract 1 from the second sum value determined above to obtain the number of decoded points corresponding to the first non-zero child node. For example, the number of decoded points corresponding to the first non-zero child node determined is 7-1=6.

Method 2: If the i-th non-zero child node is not the first non-zero child node of the current node, then add the first sum value to the number of non-zero child nodes included in the current node to obtain a second sum value; subtract 1 from the second sum value to obtain a third sum value; obtain the sum of the first number of repeated points included in the non-zero child nodes before the i-th non-zero child node in the current node, and add the third sum value to the sum of the first number of repeated points to obtain the third number of decoded points corresponding to the i-th non-zero child node.

In this method 2, if the current node is not the first non-zero node in the N-1th layer, and the i-th non-zero child node of the current node is not the first non-zero child node of the current node, then based on the above steps, the number of decoded points of each decoded non-zero node before the current node in the N-1th layer is added to obtain a first sum value. At the same time, since the placeholder information of the current node has been decoded, the geometric position information of each child node of the current node can be determined, so each child node of the current node is determined as a decoded point, and then the first sum value is added to the number of child nodes of the current node to obtain a second sum value. In addition, since it is assumed that the current node includes a decoded point when determining the first parameter above, in order to avoid repeating the count of the decoded point, the determined second sum value is subtracted by 1 to obtain a third sum value. In method 2, since the i-th child node is not the first child node of the current node, and the child node before the i-th child node in the current node may include repeated points, it is necessary to obtain the sum of the first number of repeated points included in the non-zero child nodes before the i-th non-zero child node in the current node, and finally add the third sum value to the sum of the first number of repeated points to obtain the third number of decoded points corresponding to the i-th non-zero child node.

For example, assuming that the current node is the second non-zero node in the third layer in FIG8, and the placeholder information of the current node is 01010100, it can be determined that the current node includes 3 non-zero child nodes. Assuming that the i-th non-zero child node is the second non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of the three non-zero child nodes of the current node can be determined, so the geometric position information of the three non-zero child nodes included in the current node has been decoded. As shown in FIG8, each non-zero node located before the current node in the third layer is the first non-zero node in the third layer. Assuming that the placeholder information of the first non-zero node is 01010101, based on the above method, it can be determined that the number of decoded points corresponding to the first non-zero node is 4-1, that is, the first sum value is 3. Then, the first sum value 3 is added to the number of non-zero child nodes of the current node 3, and the second sum value is 3+3=6. It should be noted that when determining the first parameter, it is assumed that the current node includes a decoded point. Therefore, it is necessary to subtract 1 from the second sum value determined above to obtain the third value, for example, the third value is determined to be 6-1=5. Assuming that the first non-zero child node of the current node includes a repeated point, the repeated point is recorded as the first repeated point. In this way, the number of the first repeated points 1 is added to the third value 5, and the number of the third decoded points corresponding to the i-th non-zero child node is 1+5=6.

After determining the third number of decoded points corresponding to the i-th non-zero child node based on the above steps, execute step S102-A11-2 to determine the first number of decoded points based on the third number of decoded points.

For an isolated point P, directly compressing its coordinates is more efficient than using the octree method. This process of directly encoding the coordinates of the points in the node is called the Direct Coding Model (DCM). Whether the current node uses DCM can be inferred based on the information of neighboring nodes. This method is called the Inter Direct Coding Model (IDCM).

In the embodiment of the present application, when the point cloud adopts IDCM and does not adopt IDCM, it has an impact on the number of first decoded points corresponding to the i-th non-zero child node in the point cloud. The following describes the impact process of the number of first decoded points corresponding to the i-th non-zero child node when the point cloud adopts DCM and does not adopt IDCM.

In some embodiments, if the point cloud does not use IDCM, the third number of decoded points corresponding to the i-th non-zero child node is determined as the first number of decoded points corresponding to the i-th non-zero child node.

In this embodiment, if the point cloud does not use IDCM, that is, IDCM is turned off, it means that when encoding the octree, each node in the octree does not use direct encoding. Therefore, when decoding the current node, the octree does not include other first decoded points except the third decoded point corresponding to the i-th non-zero child node determined above. Among them, the first decoded point can be understood as a point whose geometric position has been decoded in the leaf node of the octree. At this time, the number of the third decoded points corresponding to the i-th non-zero child node determined above is directly determined as the number of the first decoded points corresponding to the i-th non-zero child node.

In some embodiments, if the point cloud adopts IDCM, the number of points included in the second node using IDCM that has been decoded in the octree is determined; the number of points included in the second node using IDCM and the third number of decoded points corresponding to the i-th non-zero child node determined above are added to obtain a new first number of decoded points corresponding to the i-th non-zero child node.

In this embodiment, if the point cloud adopts IDCM, that is, IDCM is turned on, then it means that at least one node in the octree of the point cloud may adopt direct coding to directly encode the geometric information of the points included in the node. Correspondingly, when decoding, the geometric information of the points included in the node is directly decoded. In this way, when determining the second decoded point corresponding to the i-th non-zero child node, it is necessary to add the number of points included in the decoded node (i.e., the second node) using IDCM in the octree to the number of the third decoded points corresponding to the i-th non-zero child node determined above.

For example, suppose that in the octree of the point cloud, there is a node using IDCM, suppose that this node using IDCM includes 1 point, and suppose that before decoding the current node, all nodes using IDCM have been decoded. Therefore, it can be determined that the number of points included in the node using IDCM in the octree is 1. This decoded point is added to the third decoded point corresponding to the i-th non-zero child node determined above.

In an example of this embodiment, the decoding end determines the second parameter corresponding to the i-th non-zero child node through the following instruction:

Wherein, pointCountIDCM represents the number of points included in the decoded node using IDCM in the octree. In this embodiment, based on the number of non-zero child nodes included in the current node, childCount, and the number of repeated points decoded before the i-th child node in the current node, dupPointNum, after determining the third number of decoded points codedCount corresponding to the i-th non-zero child node, the number of points pointCountIDCM included in the decoded node using IDCM in the octree is added to codedCount to obtain the first number of decoded points corresponding to the i-th non-zero child node.

After the decoding end determines the number of first decoded points corresponding to the i-th non-zero child node of the current node based on the above step S102-A11, it executes the following step S102-A12.

S102-A12. Determine a second parameter corresponding to the ith non-zero child node based on the number of first decoded points corresponding to the ith non-zero child node in the point cloud.

In the embodiment of the present application, when decoding the current node, before the decoding end determines whether to decode the repeated point information of the i-th non-zero child node of the current node, it first determines the first number of decoded points corresponding to the i-th non-zero child node based on the above steps, and then determines the second parameter corresponding to the i-th non-zero child node based on the first number of decoded points corresponding to the i-th non-zero child node, so that the second parameter determined in this way can reflect the number of points that have been decoded at the geometric position in the point cloud when decoding the i-th non-zero child node. Finally, based on the first parameter corresponding to the current node and the second parameter corresponding to the i-th non-zero child node, it is determined whether the i-th non-zero child node includes repeated points, and then it is determined whether to decode the repeated point information of the i-th non-zero child node.

From the above, it can be seen that in AVS geometric coding, octree can be used for coding, and octree and prediction tree can be combined for coding.

In the embodiment of the present application, when the point cloud adopts prediction tree coding and when the prediction tree coding is not adopted, the method of determining the second parameter corresponding to the i-th non-zero subnode based on the number of first decoded points corresponding to the i-th non-zero subnode in the point cloud is different. The specific process of determining the second parameter corresponding to the i-th non-zero subnode when the point cloud adopts prediction tree coding and when the prediction tree coding is not adopted is introduced below.

In the embodiment of the present application, based on the number of first decoded points corresponding to the i-th non-zero sub-node in the point cloud, determining the second parameter corresponding to the i-th non-zero sub-node includes at least the following methods:

Method 1: The number of first decoded points is determined as the second parameter.

In the geometric coding of AVS, if the point cloud adopts the prediction tree coding method, that is, the prediction tree coding method is turned off, then, among the decoded points corresponding to the i-th non-zero child node in the point cloud, except for the first decoded point corresponding to the i-th non-zero child node determined in the above embodiment, no other decoded points are included. In this case, when decoding the i-th non-zero child node of the current node, based on the above steps, the number of the first decoded points corresponding to the i-th non-zero child node is determined, and the number of the first decoded points corresponding to the i-th non-zero child node is determined as the second parameter corresponding to the i-th non-zero child node.

Mode 2: If the point cloud adopts the prediction tree encoding method, the above S102-A12 includes the following steps S102-A121 and S102-A122:

S102-A121, determining the number of second decoded points included in the first node of the octree using the prediction tree coding method;

S102-A122. Determine the sum of the first number of decoded points and the second number of decoded points as a second parameter.

In this method 2, if the point cloud adopts the prediction tree coding method, that is, the prediction tree coding method is turned on, at this time, it means that there may be at least one node in the octree of the point cloud that adopts the prediction tree coding method, and the points included in the node are encoded using the prediction tree coding method. For example, as shown in Figure 7, the prediction tree coding method is adopted for the first node of the third layer in the point cloud octree, for example, the points included in the node are sorted, and the preset prediction tree coding method is adopted to construct a prediction tree for the sorted points, for example, an L3C2 single chain is constructed. Then, based on the structure of the prediction tree, each node in the prediction tree is traversed, and the geometric position information of the node is predicted by selecting different prediction modes to obtain the prediction residual, and the geometric prediction residual is quantized and encoded using the quantization parameter to form a geometric code stream.

Correspondingly, when decoding the node, the decoding end uses the prediction tree decoding method to geometrically decode the node to obtain the geometric reconstruction value of the point included in the node. That is to say, in the embodiment of the present application, since the octree is traversed by the breadth-first principle, the position of the node encoded by the prediction tree in the octree is before the current node, that is, when decoding the current node, the node encoded by the prediction tree has been decoded. Therefore, when determining the second parameter corresponding to the i-th non-zero child node of the current node, it is necessary not only to determine the first number of decoded points corresponding to the above-mentioned i-th non-zero child node, but also to determine the number of decoded points included in the first node encoded by the prediction tree in the octree. For the convenience of description, the number of decoded points included in the first node encoded by the prediction tree is recorded as the second number of decoded points. Furthermore, the first number of decoded points corresponding to the i-th non-zero child node is added to the second number of decoded points included in the first node encoded by the prediction tree in the octree, and the result of the addition is determined as the second parameter corresponding to the i-th non-zero child node.

In an example of the second method, the decoder determines the second parameter corresponding to the i-th non-zero child node through the following instruction:

Wherein, pointCountPred represents the number of points included in the decoded first node encoded by the prediction tree in the octree, that is, the second number of decoded points. In this embodiment, based on the number of non-zero child nodes childCount included in the current node and the number of repeated points dupPointNum decoded before the i-th child node in the current node, after determining the first number of decoded points codedCount corresponding to the i-th non-zero child node, the second number of decoded points pointCountIDCM in the octree is added to codedCount to obtain the second parameter corresponding to the i-th non-zero child node.

In this case 1, after determining the second parameter corresponding to the i-th non-zero child node of the current node based on the above steps, execute the above S102-A2 to determine whether to decode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter.

The implementation of determining whether to decode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter in S102-A2 includes but is not limited to the following methods:

Method 1: If the first parameter is equal to the second parameter, skip decoding the repeated point information of the i-th non-zero child node.

From the above, it can be seen that the first parameter corresponding to the current node can be understood as the number of points with uncertain geometric position information in the point cloud when decoding the current node, or it can be understood as the number of undecoded points. The second parameter corresponding to the i-th non-zero child node of the current node can be understood as the number of currently decoded points.

In method 1, if the first parameter corresponding to the determined current node is equal to the second parameter corresponding to the i-th non-zero child node in the current node, it means that the i-th non-zero child node and subsequent undecoded leaf nodes do not include duplicate points. Therefore, the decoding of the duplicate point information of the i-th non-zero child node is skipped to save decoding time.

For example, assuming that the point cloud includes 10 points, assuming that the current node is the second non-zero node in the third layer in Figure 8, and the N-1th layer of the octree where the current node is located includes 4 non-zero nodes, therefore, it can be determined that the first parameter corresponding to the current node is 10-4=6.

Assuming that the placeholder information of the current node is 01010100, it can be determined that the current node includes 3 non-zero child nodes. Assuming that the i-th non-zero child node is the second non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of the three non-zero child nodes of the current node can be determined, so the geometric position information of the three non-zero child nodes included in the current node has been decoded. As shown in Figure 8, each non-zero node located before the current node in the third layer is the first non-zero node in the third layer. Assuming that the placeholder information of the first non-zero node is 01010101, assuming that the first non-zero child node of the current node includes 1 repeated point, therefore, based on the above method, it can be determined that the first number of decoded points corresponding to the i-th non-zero child node is 4-1+3-1+1=6. In this embodiment, assuming that the point cloud does not use prediction tree encoding, the first number of decoded points corresponding to the i-th non-zero child node, 6, is determined as the second parameter corresponding to the i-th non-zero child node.

In this example, the first parameter 6 corresponding to the current node is equal to the second parameter 6 corresponding to the i-th non-zero child node, and therefore, decoding of the repeated point information of the i-th non-zero child node is skipped.

Method 2: if the first parameter is greater than the second parameter and the i-th non-zero child node is the last voxel node of the octree, then the decoding of the duplicate point information of the i-th non-zero child node is skipped, and the difference between the first parameter and the second parameter is determined as the number of duplicate points included in the i-th non-zero child node.

In method 2, if the first parameter corresponding to the determined current node is equal to the second parameter corresponding to the i-th non-zero child node in the current node, it means that the i-th non-zero child node and subsequent undecoded leaf nodes may include duplicate points. At the same time, since the i-th non-zero child node is the last non-zero voxel node of the octree, it means that the i-th non-zero child node must include duplicate points, and the number of duplicate points included in the i-th non-zero child node is the difference between the first parameter and the second parameter.

For example, assuming that the point cloud includes 10 points, assuming that the current node is the fourth non-zero node in the third layer in Figure 8, and the N-1th layer of the octree where the current node is located includes 4 non-zero nodes, therefore, it can be determined that the first parameter corresponding to the current node is 10-4=6.

Assuming that the placeholder information of the current node is 00000010, it can be determined that the current node includes 1 non-zero child node. Assuming that the i-th non-zero child node is the only non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of 1 non-zero child node of the current node can be determined, so the geometric position information of 1 non-zero child node included in the current node has been decoded. As shown in Figure 8, the non-zero nodes before the current node in the third layer are the first non-zero node, the second non-zero node, and the third non-zero node in the third layer. Assuming that the placeholder information of the first non-zero node is 01010101, the placeholder information of the first non-zero node is 01010100, and the placeholder information of the first non-zero node is 00000100, the non-zero child nodes of the first three non-zero nodes do not include repeated points. Based on the above method, it can be determined that the number of the first decoded points corresponding to the i-th non-zero child node is 4-1+3-1+1-1+1-1=5. In this embodiment, assuming that the point cloud does not adopt prediction tree encoding, the first number of decoded points 5 corresponding to the i-th non-zero child node is determined as the second parameter corresponding to the i-th non-zero child node.

From the above, it can be seen that the first parameter 6 is greater than the second parameter 5, and the i-th non-zero child node is the last non-zero child node of the octree. Therefore, it can be determined that the i-th non-zero child node must include repeated points, and the number of repeated points included is 6-5=1. The repeated point information of the i-th non-zero child node is skipped for decoding, thereby saving decoding time and improving decoding efficiency.

Mode 3: If the first parameter is greater than the second parameter and the i-th non-zero child node is not the last voxel node of the octree, the duplicate point information of the i-th non-zero child node is decoded.

In method 3, if the first parameter corresponding to the determined current node is equal to the second parameter corresponding to the i-th non-zero child node in the current node, it means that the i-th non-zero child node and subsequent undecoded leaf nodes may include duplicate points. Therefore, in order to ensure the accuracy of decoding, the duplicate point information of the i-th non-zero child node is decoded.

Assuming that the placeholder information of the current node is 01010100, it can be determined that the current node includes 3 non-zero child nodes. Assuming that the i-th non-zero child node is the second non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of the three non-zero child nodes of the current node can be determined, so the geometric position information of the three non-zero child nodes included in the current node has been decoded. As shown in Figure 8, each non-zero node located before the current node in the third layer is the first non-zero node in the third layer. Assuming that the placeholder information of the first non-zero node is 01010101, assuming that the third non-zero child node of the current node includes 1 repeated point, therefore, based on the above method, it can be determined that the first number of decoded points corresponding to the i-th non-zero child node is 4-1+3-1=5. In this embodiment, assuming that the point cloud does not use prediction tree encoding, the first number of decoded points corresponding to the i-th non-zero child node, 5, is determined as the second parameter corresponding to the i-th non-zero child node.

In this example, if the first parameter 6 corresponding to the current node is greater than the second parameter 5 corresponding to the i-th non-zero child node, and the i-th non-zero child node is not the last voxel node of the octree, the duplicate point information of the i-th non-zero child node is decoded.

In the above situation 1, based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer of the octree, the first parameter corresponding to the current node is determined, and the second parameter corresponding to the i-th non-zero child node of the current node is determined. Based on the first parameter and the second parameter, it is determined whether to decode the duplicate point information of the i-th non-zero child node. For example, if the first parameter is equal to the second parameter, the decoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the decoding complexity of the point cloud, saving decoding time, and improving decoding efficiency.

The following introduces the process of determining the first parameter corresponding to the current node in situation 2 and performing geometric decoding of the current node based on the first parameter.

In case 2, the above S101 includes the following steps:

S101-B1, for the i-th non-zero child node in the current node, determine the total number of decoded repeated points corresponding to the i-th non-zero child node;

S101-B2. Determine the total number of decoded repeated points corresponding to the i-th non-zero child node as the first parameter.

In this case 2, when determining whether the i-th non-zero child node of the current node includes repeated points, the number of decoded repeated points corresponding to the i-th non-zero child node is first determined, where the decoded repeated points corresponding to the i-th non-zero child node can be understood as the repeated points that have been decoded by the decoding end before decoding the repeated point information of the i-th non-zero child node.

In some embodiments, the decoding end uses dupCount to record the number of duplicate points that have been decoded, where dupCount is initialized to 0.

In one example, the decoding end uses the following instruction to record the number of decoded repeated points:

dupCount+=dupPointNum

Wherein, dupPointNum represents the number of duplicate points included in a leaf node of the octree.

The decoding end determines the total number of decoded repeated points corresponding to the i-th non-zero child node, and determines the total number of decoded repeated points corresponding to the i-th non-zero child node as the first parameter, and then performs geometric decoding on the current node based on the first parameter.

In some embodiments, determining the total number of decoded repeated points corresponding to the i-th non-zero child node in the above S101-B1 includes:

S101-B11, determining the sum of the number of third decoded repeated points included in each non-zero child node located before the i-th non-zero child node in the octree;

S101-B12. Determine the total number of decoded repeated points corresponding to the i-th non-zero child node based on the sum of the third number of decoded repeated points.

In this embodiment, if the i-th non-zero child node is not the first non-zero leaf node in the octree, the sum of the number of decoded points included in each non-zero child node located before the i-th non-zero child node in the octree is determined. For the sake of ease of description, the decoded point is recorded as the third decoding point.

For example, as shown in Figure 8, assuming that the current node is the first non-zero node in the N-1th layer, the placeholder information of the current node is 010101010, the i-th non-zero child node is the third non-zero child node in the current node, and in the octree, there are two non-zero child nodes before the i-th non-zero child node. Assuming that one of the two non-zero child nodes includes two repeated points and the other non-zero child node includes one repeated point, it can be determined that the sum of the third decoded repeated points is 2+1=3.

Based on the above steps, after determining the sum of the third number of decoded repeated points included in each non-zero child node located before the i-th non-zero child node in the octree, the total number of decoded repeated points corresponding to the i-th non-zero child node is determined based on the sum of the third number of decoded repeated points.

Based on whether the point cloud adopts prediction tree coding, the implementation methods of determining the total number of decoded repeated points corresponding to the i-th non-zero child node based on the sum of the third number of decoded repeated points in the above S101-B12 include at least the following two methods:

Method 1: If the point cloud adopts the prediction tree encoding method, the sum of the fourth number of decoded repeated points included in the first node in the octree that adopts the prediction tree encoding method is determined; based on the sum of the third number of decoded repeated points and the sum of the fourth number of decoded repeated points, the total number of decoded repeated points corresponding to the i-th non-zero child node is determined.

In this method 1, if the point cloud adopts the predictive coding method, it can be known from the above that the decoding end completes the node in the octree that adopts the predictive tree coding method before decoding the current node. In this way, the sum of the fourth number of decoded repeated points included in the first node in the octree that adopts the predictive tree coding method can be obtained, and then based on the sum of the third number of decoded repeated points and the sum of the fourth number of decoded repeated points, the total number of decoded repeated points corresponding to the i-th non-zero child node is determined.

In some embodiments, if the point cloud is not encoded using IDCM, the sum of the third number of decoded duplicate points and the sum of the fourth number of decoded duplicate points are used to determine the total number of decoded duplicate points corresponding to the i-th non-zero child node.

In some embodiments, if the point cloud adopts the inferred direct coding mode IDCM, the total number of decoded duplicate points corresponding to the i-th non-zero child node is determined based on the sum of the third number of decoded duplicate points and the sum of the fourth number of decoded duplicate points, including: determining the sum of the fifth number of decoded duplicate points included in the second node using IDCM in the octree; and determining the total number of decoded duplicate points corresponding to the i-th non-zero child node by adding the sum of the third number of decoded duplicate points, the sum of the fourth number of decoded duplicate points, and the sum of the fifth number of decoded duplicate points.

Method 2: If the point cloud does not adopt the prediction tree encoding method, the total number of decoded repeated points corresponding to the i-th non-zero child node is determined based on the sum of the third number of decoded repeated points.

In one implementation of method 2, if the point cloud does not use the prediction tree encoding method and does not use the IDCM encoding method, the total number of decoded repeated points corresponding to the i-th non-zero child node is determined based on the sum of the third number of decoded repeated points.

In another implementation of method 2, if the point cloud does not use the prediction tree encoding method and uses the IDCM encoding method, then the sum of the fifth decoded duplicate points included in the second node using IDCM in the octree is determined, and the sum of the fifth decoded duplicate points is added to the sum of the third decoded duplicate points to obtain the total number of decoded duplicate points corresponding to the i-th non-zero child node.

Based on the above method, after the total number of decoded repeated points corresponding to the i-th non-zero child node is determined, the total number of decoded repeated points corresponding to the i-th non-zero child node is determined as the first parameter.

In case 2, the geometric decoding of the current node based on the first parameter in S102 includes the following steps S102-B1 and S102-B2:

S102-B1, determining the total number of repeated points in the point cloud;

S102-B2: Determine whether to decode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of decoded duplicate points corresponding to the i-th non-zero child node.

In case 2, when the decoding end determines whether to decode the repeated point information of the i-th non-zero child node of the current node, based on the above steps, the number of decoded repeated points corresponding to the i-th non-zero child node is determined as the first parameter. Then, the total number of repeated points in the point cloud is determined, and the number of decoded repeated points corresponding to the i-th non-zero child node is compared with the number of repeated points in the point cloud to determine whether the i-th non-zero child node includes repeated points, and then determine whether to decode the repeated point information of the i-th non-zero child node.

The methods for determining the total number of repeated points in the point cloud in S102-B1 include but are not limited to the following:

In method 1, the encoder writes the total number of repeated points of the point cloud into the geometry stream, so that the decoder obtains the total number of repeated points of the point cloud by decoding the geometry stream.

Method 2: The decoding end determines the total number of points in the point cloud and the total number of non-zero voxel nodes in the octree; the difference between the total number of points in the point cloud and the total number of non-zero voxel nodes in the octree is determined as the total number of repeated points in the point cloud.

In this method 2, the voxel-level nodes of the octree can be understood as the leaf nodes of the last voxel level of the octree. The non-zero voxel-level nodes of the octree include at least one point in the point cloud. Therefore, in method 2, the difference between the total number of points in the point cloud and the total number of voxel nodes in the octree is determined as the total number of repeated points in the point cloud.

Among them, the method for the decoding end to determine the total number of points of the point cloud can refer to the description of the above embodiment, and will not be repeated here.

In some embodiments, the decoding end determines the number of non-zero voxel nodes in the last layer of the octree through the placeholder information of each non-zero node in the N-1th layer of the octree.

After the decoding end determines the total number of duplicate points in the point cloud based on the above method 1 or method 2, it determines whether to decode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of decoded duplicate points corresponding to the i-th non-zero child node.

In some embodiments, if the total number of decoded duplicate points corresponding to the i-th non-zero child node is equal to the total number of duplicate points in the point cloud, it means that the duplicate points in the point cloud have been decoded, and the i-th non-zero child node and the leaf nodes after the i-th non-zero child node do not include duplicate points. Therefore, the decoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the decoding complexity of the point cloud, saving decoding time, and improving decoding efficiency.

In some embodiments, if the total number of decoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points in the point cloud, and the i-th non-zero child node is the last voxel node of the octree, it means that the i-th non-zero child node includes duplicate points. At this time, decoding the duplicate point information of the i-th non-zero child node is skipped, and the difference between the total number of duplicate points in the point cloud and the total number of decoded duplicate points corresponding to the i-th non-zero child node is determined as the number of duplicate points included in the i-th non-zero child node.

In some embodiments, if the total number of decoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points in the point cloud, and the i-th non-zero child node is the last voxel node of the octree, it means that the i-th non-zero child node or the leaf node after the i-th non-zero child node may include duplicate points. Therefore, in order to improve the decoding accuracy, the decoding end decodes the duplicate point information of the i-th non-zero child node.

From the above, it can be seen that the decoding end determines the first parameter corresponding to the current node in the octree-based point cloud decoding based on the above situation 1 and situation 2, and decodes the current node based on the first parameter.

The point cloud decoding method provided by the embodiment of the present application, in point cloud decoding, for example, in point cloud decoding based on AVS, when decoding the current node of the N-1th layer in the octree, first determine the first parameter corresponding to the current node, the first parameter is used to determine whether at least one non-zero child node of the current node includes duplicate points, the current node is a non-zero node of the N-1th layer in the octree of the point cloud, N is the total number of layers of the octree, and then based on the first parameter, the current node is geometrically decoded. For example, when it is determined based on the first parameter that the i-th non-zero child node of the current node does not include duplicate points, the decoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the decoding complexity of the point cloud, saving decoding time, and improving decoding efficiency.

The above takes the decoding end as an example to introduce in detail the point cloud decoding method provided in the embodiment of the present application. The following takes the encoding end as an example to introduce the point cloud encoding method provided in the embodiment of the present application.

Fig. 9 is a schematic diagram of a point cloud coding method according to an embodiment of the present application. The point cloud coding method according to the embodiment of the present application can be implemented by the point cloud coding device shown in Fig. 3 or Fig. 4 above.

As shown in FIG9 , the point cloud encoding method of the embodiment of the present application includes:

S201, determining a first parameter corresponding to the current node;

S202. Perform geometric encoding on the current node based on the first parameter.

Among them, the first parameter is used to determine whether at least one non-zero child node of the current node includes duplicate points. The current node is a non-zero node in the N-1th layer of the octree of the point cloud. The octree is obtained based on node division of the point cloud. N is the total number of layers of the octree, and N is a positive integer greater than 1.

The point cloud coding method proposed in the embodiment of the present application can be applied to a variety of point cloud coding scenarios. In some embodiments, if the point cloud coding method of the embodiment of the present application is applied to AVS, the above octree is obtained by dividing the point cloud into nodes based on the AVS method.

The point cloud of the embodiment of the present application can be understood as a point cloud block or point cloud slice that can be encoded individually.

As can be seen from the above, the point cloud includes geometric information and attribute information, and the encoding of the point cloud includes geometric encoding and attribute encoding. The embodiments of the present application relate to geometric encoding of point clouds. That is, the encoded points involved in the embodiments of the present application refer to points in the point cloud whose geometric information has been encoded, and the unencoded points refer to points in the point cloud whose geometric information has not been encoded.

In some embodiments, the geometric information of the point cloud is also referred to as the position information of the point cloud, and therefore, the geometric encoding of the point cloud is also referred to as the position encoding of the point cloud.

In some embodiments, in the AVS geometric coding of the current point cloud, the coding end can use prediction tree coding while using octree coding, that is, the prediction tree coding algorithm is turned off. At this time, as shown in Figure 7, the octree is first used to perform octree division on the bounding box of the point cloud, and the division is divided to a preset depth. For example, after division to 3 layers, for each non-zero node obtained by the division, it is determined whether the node is encoded by prediction tree or octree. If it is determined that the node is encoded by prediction tree, the prediction tree coding method is used to perform prediction tree coding on the geometric information of the points included in the node. For example, it is determined that the first node in the third layer uses the prediction tree coding method, then the points included in the node are sorted, and the preset prediction tree coding method is used to construct a prediction tree for the sorted points, such as constructing an L3C2 single chain. Then, based on the structure of the prediction tree, each node in the prediction tree is traversed, and the geometric position information of the node is predicted by selecting different prediction modes to obtain the prediction residual, and the geometric prediction residual is quantized using the quantization parameter. Finally, through continuous iteration, the prediction residual, prediction tree structure and quantization parameter of the prediction tree node position information are encoded. If it is determined that the node is divided by octree, the octree division method is used to divide the node until it is divided into leaf nodes at the voxel level, and the placeholder information of each node in the octree is encoded to form a geometric code stream.

It can be seen from Figures 6 and 7 above that in the AVS point cloud geometry coding, regardless of whether the prediction tree coding is turned on, at least some points in the point cloud are divided into octrees and finally divided into voxel-level leaf nodes.

At present, when encoding the node of the N-1th layer of the octree, the encoder not only encodes the placeholder information of the node, but also encodes the repeated point information of the child nodes (i.e., leaf nodes) of the node. Correspondingly, when encoding the node of the N-1th layer of the octree, the encoder not only encodes the placeholder information of the node, but also encodes the repeated point information of the child nodes of the node. This will increase the complexity of encoding, waste encoding time, and reduce encoding efficiency.

From the above, it can be seen that in the octree of the point cloud, not every leaf node includes duplicate points. It can even be understood that only a few leaf nodes in the octree of the point cloud include duplicate points. Based on this, in an embodiment of the present application, when encoding the current node of the N-1th layer of the octree of the point cloud, the first parameter corresponding to the current node is first determined. The first parameter is used to determine whether at least one child node (i.e., leaf node) of the current node includes duplicate points, and then based on the first parameter, the current node is encoded. For example, when it is determined based on the first parameter that the i-th non-zero child node of the current node does not include duplicate points, the encoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the encoding complexity of the point cloud, saving encoding time, and improving encoding efficiency.

The embodiments of the present application mainly relate to the encoding process of the nodes in the N-1th layer of the point cloud octree. The N-1th layer can also be understood as the second to last layer of the octree of the point cloud.

When encoding a node in the N-1th layer of the octree, it is necessary not only to encode the placeholder information of the node, but also to encode the repeated point information included in the child nodes of the node. The child nodes of the N-1th layer of the node are the voxel-level leaf nodes of the octree, that is, the last layer of nodes.

In an embodiment of the present application, the encoding process for each node in the N-1th layer of the octree is basically the same. For the convenience of description, the encoding process of the embodiment of the present application is introduced by taking the current node in the N-1th layer of the octree as an example.

In some embodiments, the current node can be understood as any non-zero node (also called a non-empty node) in the N-1th layer of the octree, where the non-zero node can be understood as a node including at least one child node, or a node including at least one point in the point cloud.

In some embodiments, the current node may be understood as a non-zero node in the N-1th layer of the octree that is currently waiting to be encoded.

In the embodiment of the present application, before encoding the current node, the first parameter corresponding to the current node is first determined, and then the current node is encoded based on the first parameter. In the embodiment of the present application, the method of determining the first parameter corresponding to the current node is different, and the corresponding method of encoding the current node based on the first parameter is also different. The following is a detailed introduction to several methods of determining the first parameter corresponding to the current node and the process of encoding the current node based on the first parameter involved in the embodiment of the present application.

In case 1, the above S201 includes the following steps S201-A1 to S201-A2:

S201-A1, determine the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer;

S201-A2: Determine a first parameter based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer.

In an embodiment of the present application, the encoding end encodes the nodes in the octree based on a breadth-first traversal method.

In this case 1, the first parameter corresponding to the current node is determined based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer of the octree of the point cloud. The first parameter can be understood as the number of points whose geometric information cannot be determined in the current point cloud. Then, based on the first parameter, the current node is encoded. For example, based on the first parameter, it is determined whether the child nodes of the current node include duplicate points. If it is determined based on the first parameter that the child nodes of the current node do not include duplicate points, the duplicate point information of the child nodes of the current node is skipped to reduce the encoding complexity of the point cloud, save encoding time, and thus improve encoding efficiency.

In some embodiments, the encoder writes the total number of points of the point cloud into the geometry brick header (gbh) of the point cloud. In this way, the decoder obtains the total number of points of the point cloud by decoding the geometry brick header (gbh) of the point cloud.

In some embodiments, since the point cloud includes at least one point, in order to save code words, the encoding end divides the number of points of the point cloud into the low-order part num_points_lower of the points contained in the slice and the high-order part num_points_upper of the points contained in the slice when encoding the total number of points in the point cloud, and writes num_points_lower and num_points_upper into the geometry unit header.

In one example, the parameters of the geometry unit head are specifically as shown in Table 2 above.

In some embodiments, it can be seen from the above that the encoder encodes the placeholder information of the nodes at each layer of the octree in a breadth-first traversal manner. For example, based on the child nodes included in each node in the N-2th layer, the placeholder information of each node in the N-2th layer is determined, and then the placeholder information of each node in the N-2th layer is written into the geometry stream. In this way, the decoder decodes the placeholder information of each node in the N-2th layer and can determine the number of nodes included in the N-1th layer.

After the encoder determines the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer, the encoder determines the first parameter corresponding to the current node based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer.

In some embodiments, the encoding end determines the difference between the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer as the first parameter. In this embodiment, by determining the number of occupied nodes in the N-1th layer, it can be determined that the occupied nodes include at least one non-zero child node, that is, the occupied nodes in the N-1th layer correspond to at least one point. Therefore, the difference between the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer of the octree is determined as the number of points with uncertain geometric information in the point cloud, that is, the first parameter. For example, the point cloud includes 10 points, and the N-1th layer includes 4 nodes, which means that each of the 4 nodes in the N-1th layer includes at least one non-zero child node, and a non-zero child node includes at least one point. Therefore, it can be determined that the number of points with uncertain position information in the current point cloud is 10-4=6, and then the first parameter corresponding to the current node is determined to be 6.

In a possible implementation, the first parameter is determined based on the above formula (4).

After the first parameter corresponding to the current node is determined based on the above method, the above step S202 is performed to encode the current node based on the first parameter.

In some embodiments, if the first parameter corresponding to the current node is determined to be 0, for example, the total number of points in the point cloud is a, and the N-1th layer of the octree of the point cloud includes a nodes, then the first parameter is determined to be 0, which means that each non-zero node in the N-1th layer includes a non-zero child node, and the non-zero child node includes a point in the point cloud, and no duplicate points are included. At this time, when encoding the nodes in the N-1th layer, the encoding of the duplicate point information of the non-zero child nodes of each non-zero node is skipped, thereby reducing the encoding complexity and saving encoding time.

In some embodiments, if it is determined that the first parameter corresponding to the current node is not 0, the above S202 is as shown in the following situation 1.

In case 1, the above S202 includes the following steps S202-A1 to S202-A2:

S202-A1. For the i-th non-zero child node of the current node, determine a second parameter corresponding to the i-th non-zero child node, where the second parameter is used to indicate the number of points whose geometric positions in the point cloud have been encoded when encoding the i-th non-zero child node;

S202-A2: Determine whether to encode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter.

From the above, it can be seen that the current node includes at least one non-zero child node. When encoding the current node, the specific process of determining whether to encode the repeated point information of each non-zero child node included in the current node is the same. For the sake of ease of description, the i-th non-zero child node of the current node is taken as an example for explanation.

In this case 1, the encoding end determines the first parameter corresponding to the current node based on the above steps S202-A1 to S202-A2. The first parameter can be understood as the number of points whose current position information is not determined in the point cloud. Next, the second parameter corresponding to the i-th non-zero child node of the current node is determined. The second parameter is used to indicate the number of points whose geometric positions in the point cloud have been encoded when encoding the i-th non-zero child node. Finally, based on the first parameter corresponding to the current node and the second parameter corresponding to the i-th non-zero child node, it is determined whether the i-th non-zero child node includes duplicate points, and then it is determined whether to encode the duplicate point information of the i-th non-zero child node.

In some embodiments, during encoding, the encoding end records in real time the number of points whose geometric positions have been encoded in the current point cloud, and then, when encoding the current node, determines the number of points determined by the geometric position information that has been determined before encoding the repeated point information of the i-th non-zero child node.

In some embodiments, determining the second parameter corresponding to the i-th non-zero child node in the above S202-A1 includes the following steps S202-A11 and S202-A12:

S202-A11. Determine the number of first encoded points corresponding to the i-th non-zero child node in the point cloud.

In this embodiment, the encoder determines the number of first encoded points corresponding to the i-th non-zero child node in the point cloud, and determines the second parameter corresponding to the i-th non-zero child node based on the number of first encoded points corresponding to the i-th non-zero child node in the point cloud. For example, the number of first encoded points corresponding to the i-th non-zero child node in the point cloud is determined as the second parameter corresponding to the i-th non-zero child node.

In this embodiment, the number of first encoded points corresponding to the i-th non-zero child node can be understood as the total number of points currently encoded by the encoding end when determining whether to encode repeated point information of the i-th non-zero child node of the current node.

In some embodiments, the encoding end starts a counter during encoding, and the counter is used to record the number of encoded points in real time, so that when encoding the i-th non-zero child node, the first number of encoded points corresponding to the i-th non-zero child node can be obtained from the counter.

In some embodiments, when encoding the i-th non-zero child node, the encoder determines the number of first encoded points corresponding to the i-th non-zero child node through the following steps:

S202-A11-1. Determine the number of third encoded points corresponding to the i-th non-zero child node;

S202-A11-1. Determine the number of first encoded points based on the number of third encoded points.

The third encoded point can be understood as an encoded point in the leaf node of the octree. The encoder determines the number of first encoded points corresponding to the i-th non-zero child node by determining the number of points included in the encoded leaf node before the i-th non-zero child node.

The implementation methods of determining the number of third encoded points corresponding to the i-th non-zero child node in the above S202-A11-1 include but are not limited to the following:

Method 1: if the current node is the first non-zero node in the N-1th layer, the above S202-A11-1 includes the following steps S202-A11-1-a1 and S202-A11-1-a2:

S202-A11-1-a1, determine the number of non-zero child nodes of the current node;

S202-A11-1-a2. Based on the number of non-zero child nodes of the current node, determine the number of third encoded points corresponding to the i-th non-zero child node.

In method 1, if the current node is the first non-zero node in the N-1th layer of the octree, the number of non-zero child nodes included in the current node is determined, and based on the number of non-zero child nodes of the current node, the number of third encoded points corresponding to the i-th non-zero child node is determined.

Exemplarily, the encoding end determines the placeholder information of the current node based on the occupancy of each child node of the current node in the N-1th layer. Assuming that among the 8 child nodes of the current node, the 2nd child node, the 4th child node, the 6th child node and the 8th child node are occupied, the placeholder information of the current node is determined to be 01010101. In this way, it can be determined that the current node includes 4 non-zero child nodes.

After determining the number of non-zero child nodes of the current node, the encoder determines the number of third encoded points corresponding to the i-th non-zero child node based on the number of non-zero child nodes of the current node.

Wherein, the manner of determining the number of third encoded points corresponding to the i-th non-zero child node based on the number of non-zero child nodes of the current node in S202-A11-a2 includes but is not limited to the following:

Method 1: If the i-th non-zero child node is the first non-zero child node of the current node, the number of non-zero child nodes included in the current node is reduced by 1 to determine the third number of encoded points corresponding to the i-th non-zero child node.

For example, as shown in FIG8 , assuming that the current node is the first non-zero node in the third layer in FIG8 , and the placeholder information of the current node is 01010101, it can be determined that the current node includes 4 non-zero child nodes. Assuming that the i-th non-zero child node is the first non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of the 4 non-zero child nodes of the current node can be determined, so the geometric position information of the 4 non-zero child nodes included in the current node has been encoded, that is, the 4 non-zero child nodes included in the current node are encoded points for the first non-zero child node in the current node. It should be noted that when determining the first parameter above, it is assumed that the current node includes an encoded point, therefore, it is necessary to reduce the number of non-zero child nodes included in the current node by 1, and determine it as the third number of encoded points corresponding to the i-th non-zero child node, for example, the number of encoded points corresponding to the i-th non-zero child node is determined to be 4-1=3.

Method 2: If the i-th non-zero child node is not the first non-zero child node of the current node, obtain the sum of the first number of repeated points included in the non-zero child nodes of the current node that are located before the i-th non-zero child node; subtract 1 from the number of non-zero child nodes included in the current node, and then add it to the sum of the first number of repeated points to obtain the third number of encoded points corresponding to the i-th non-zero child node.

In method 2, if the i-th non-zero child node of the current node is not the first non-zero child node of the current node, that is, before the i-th child node, at least one non-zero child node of the current node has been encoded, and the encoded non-zero child nodes may include repeated points. Therefore, when determining the third number of encoded points corresponding to the i-th child node, the number of encoded repeated points needs to be considered.

Specifically, if the current node is the first non-zero node in the N-1th layer, and the i-th non-zero child node of the current node is not the first non-zero child node of the current node, then obtain the sum of the first number of repeated points included in the non-zero child nodes of the current node that are located before the i-th non-zero child node; subtract 1 from the number of non-zero child nodes included in the current node, and then add it to the sum of the first number of repeated points to obtain the third number of encoded points corresponding to the i-th non-zero child node.

For example, assuming that the current node is the first non-zero node in the third layer in Figure 8, and the placeholder information of the current node is 01010101, it can be determined that the current node includes 4 non-zero child nodes. Assume that the first child node of the current node includes 1 repeated point, and assume that the i-th non-zero child node is the second non-zero child node of the current node. When determining whether the node has repeated point information of the second non-zero child node of the current node, first determine the number of encoded points corresponding to the second non-zero child node. Specifically, the number of encoded points corresponding to the second non-zero child node is the number of non-zero child nodes included in the current node minus 1, plus 1 repeated point of the first child node of the current node, and the number of encoded points corresponding to the second non-zero child node is 4-1+1=4.

In the above-mentioned method 1, assuming that the current node is the first non-zero node in the N-1th layer, the process of determining the number of the third encoded points corresponding to the i-th non-zero child node of the current node is introduced.

Method 2: If the current node is not the first non-zero node in the N-1th layer, the above S202-A11-1 includes the following steps S202-A11-1-b1 to S202-A11-1-b3:

S202-A11-1-b1, determine the number of encoded points corresponding to each non-zero node before the current node in the N-1th layer;

S202-A11-1-b2, determine the number of non-zero child nodes of the current node;

S202-A11-1-b3. Based on the number of encoded points corresponding to each non-zero node before the current node in the N-1th layer and the number of non-zero child nodes of the current node, determine the third number of encoded points corresponding to the i-th non-zero child node.

In the second method, if the current node is not the first non-zero node in the N-1th layer of the octree, it means that before encoding the current node, at least one non-zero node in the N-1th layer of the octree has been encoded. Therefore, in this embodiment, when determining the number of third encoded points corresponding to the i-th non-zero child node of the current node, first determine the number of encoded points corresponding to each non-zero node before the current node in the N-1th layer of the octree, then determine the number of non-zero child nodes of the current node, and then determine the third number of encoded points corresponding to the i-th non-zero child node based on the number of encoded points corresponding to each non-zero node before the current node in the N-1th layer and the number of non-zero child nodes of the current node.

The following is an introduction to determining the number of encoded points corresponding to each non-zero node located before the current node in the N-1th layer in S202-A11-1-b1.

In a possible implementation, the number of non-zero child nodes included in each non-zero node before the current node is first determined, and then the number of non-zero child nodes included in each non-zero node is added to obtain a value of 1. Next, the total number of encoded repeated points corresponding to each non-zero node is determined, and then the value 1 is added to the total number of repeated points to obtain a value of 2, and the number of non-zero nodes before the current node in the N-1th layer is subtracted from the value 2 to obtain the number of encoded points corresponding to each non-zero node before the current node in the N-1th layer. In this embodiment, the encoding end can record the number of non-zero child nodes of each non-zero node in the N-1th layer, and at the same time, separately record the number of encoded repeated points. Finally, based on the separately recorded number of non-zero child nodes and the number of repeated points, the number of encoded points corresponding to each non-zero node before the current node in the N-1th layer is determined.

For example, assume that the current node is the third non-zero node in the third layer of the octree shown in FIG8 . When encoding the third non-zero node, the first non-zero node and the second non-zero node in the N-1th layer before the third non-zero node have been encoded. Assume that the placeholder information of the first non-zero node is 01010101, and the first non-zero child node of the first non-zero node includes 1 repeated point, and the placeholder information of the second non-zero node is 01010100. When encoding the third non-zero node, determine the number of encoded points corresponding to each non-zero node in the N-1th layer before the current node. That is, determine the number of non-zero child nodes of the first non-zero node and the second non-zero node respectively. It can be seen from the placeholder information that the first non-zero node includes 4 non-zero child nodes, and the second non-zero node includes 3 non-zero child nodes. Therefore, the first non-zero node and the second non-zero node include 7 non-zero child nodes in total. In addition, the first non-zero child node of the first non-zero node obtained by encoding includes 1 repeated point. Therefore, the number of encoded points corresponding to the first non-zero node and the second non-zero node before the third non-zero node is 7+1-2=6.

In another possible implementation, the encoding end obtains the number of non-zero child nodes of a non-zero node and the number of second repeated points included in the non-zero child nodes of the non-zero node for a non-zero node among the non-zero nodes; subtracts 1 from the number of non-zero child nodes of the non-zero node, and then adds the sum of the number of second repeated points included in the non-zero child nodes of the non-zero node to obtain the number of encoded points corresponding to the non-zero node. In this implementation, the encoding end determines the number of encoded points corresponding to each non-zero node before the current node in the N-1th layer of the octree in the same manner, that is, the encoding end determines the number of encoded points corresponding to each non-zero node before the current node, and finally sums the number of encoded points corresponding to each non-zero node.

Specifically, for each non-zero node located before the current node in the N-1th layer, first determine the number of non-zero child nodes included in the non-zero node based on the placeholder information of the non-zero node, subtract 1 from the number of non-zero child nodes of the non-zero node, and obtain the value a. Next, determine the sum of the number of second repeated points included in the non-zero child nodes of the non-zero node, and record it as the value b. Finally, add the value a and the value b to obtain the number of encoded points corresponding to the non-zero node. According to this method, the number of encoded points corresponding to each non-zero node located before the current node in the N-1th layer can be determined.

For example, assume that the current node is the third non-zero node in the third layer of the octree shown in Figure 8. When encoding the third non-zero node, the first non-zero node and the second non-zero node in the N-1th layer before the third non-zero node have been encoded. Assume that the placeholder information of the first non-zero node is 01010101, and the first non-zero child node of the first non-zero node includes 1 repeated point, and the placeholder information of the second non-zero node is 01010100. When encoding the third non-zero node, determine the number of encoded points corresponding to each non-zero node in the N-1th layer before the current node. From the placeholder information, we can see that the first non-zero node includes 4 non-zero child nodes, the second non-zero node includes 3 non-zero child nodes, and the first non-zero child node of the first non-zero node includes 1 repeated point. It can be determined that the number of encoded points corresponding to the first non-zero node is 4-1+1=4, and the number of encoded points corresponding to the second non-zero node is 3-1=2.

Based on the above method, the number of encoded points corresponding to each non-zero node located before the current node in the N-1th layer is determined, and at the same time, the number of non-zero child nodes of the current node is determined. The method for determining the number of non-zero child nodes of the current node can refer to the description of S202-A11-a1 above, and will not be repeated here.

Next, the encoder determines the third number of encoded points corresponding to the i-th non-zero child node based on the number of encoded points corresponding to each non-zero node before the current node in the N-1th layer and the number of non-zero child nodes of the current node.

The embodiment of the present application does not limit the specific implementation method of determining the third number of encoded points corresponding to the i-th non-zero child node in the above S202-A11-1-b3 based on the number of encoded points corresponding to each non-zero node located before the current node in the N-1th layer and the number of non-zero child nodes of the current node.

In some embodiments, the above S202-A11-b3 includes the following steps S202-A11-1-b31 and S202-A11-1-b32:

S202-A11-1-b31, adding the numbers of encoded points corresponding to each non-zero node before the current node in the N-1th layer to obtain a first sum value;

S202-A11-1-b32. Determine the number of third encoded points corresponding to the i-th non-zero child node based on the first sum and the number of non-zero child nodes of the current node.

In this embodiment, the encoding end determines the number of encoded points corresponding to each non-zero node located before the current node in the N-1th layer of the octree based on the above method. Then, the encoding end adds the number of encoded points corresponding to each non-zero node located before the current node in the N-1th layer to obtain a first sum value, and determines the third number of encoded points corresponding to the i-th non-zero child node based on the first sum value and the number of non-zero child nodes of the current node, thereby accurately determining the third number of encoded points corresponding to the i-th non-zero child node.

Among them, the implementation method of determining the first number of encoded points corresponding to the i-th non-zero child node based on the first sum value and the number of non-zero child nodes of the current node in the above S202-A11-1-b32 includes at least the following two methods:

Method 1: If the i-th non-zero child node is the first non-zero child node of the current node, then add the first sum value to the number of non-zero child nodes included in the current node to obtain the second sum value; subtract 1 from the second sum value to obtain the third number of encoded points corresponding to the i-th non-zero child node.

In this method 1, if the current node is not the first non-zero node in the N-1th layer, and the i-th non-zero child node of the current node is the first non-zero child node of the current node, then based on the above steps, the number of encoded points of each encoded non-zero node located before the current node in the N-1th layer is added to obtain a first sum value. At the same time, since the placeholder information of the current node has been encoded, the geometric position information of each child node of the current node can be determined, so each child node of the current node is determined as an encoded point, and then the first sum value is added to the number of child nodes of the current node to obtain a second sum value. In addition, since it is assumed that the current node includes an encoded point when determining the first parameter above, in order to avoid repeating the count of the encoded point, the determined second sum value is subtracted by 1 to obtain the third number of encoded points corresponding to the i-th non-zero child node.

Method 2: If the i-th non-zero child node is not the first non-zero child node of the current node, then add the first sum value to the number of non-zero child nodes included in the current node to obtain a second sum value; subtract 1 from the second sum value to obtain a third sum value; obtain the sum of the first number of repeated points included in the non-zero child nodes before the i-th non-zero child node in the current node, and add the third sum value to the sum of the first number of repeated points to obtain the third number of encoded points corresponding to the i-th non-zero child node.

In this method 2, if the current node is not the first non-zero node in the N-1th layer, and the i-th non-zero child node of the current node is not the first non-zero child node of the current node, then based on the above steps, the number of encoded points of each encoded non-zero node before the current node in the N-1th layer is added to obtain a first sum. At the same time, since the placeholder information of the current node has been encoded, the geometric position information of each child node of the current node can be determined, so each child node of the current node is determined as an encoded point, and then the first sum is added to the number of child nodes of the current node to obtain a second sum. In addition, since it is assumed that the current node includes an encoded point when determining the first parameter above, in order to avoid repeating the count of the encoded point, the determined second sum is subtracted by 1 to obtain a third sum. In method 2, since the i-th child node is not the first child node of the current node, and the child node before the i-th child node in the current node may include repeated points, it is necessary to obtain the sum of the first number of repeated points included in the non-zero child nodes before the i-th non-zero child node in the current node, and finally add the third sum value to the sum of the first number of repeated points to obtain the third number of encoded points corresponding to the i-th non-zero child node.

After determining the third number of decoded points corresponding to the i-th non-zero child node based on the above steps, execute step S202-A11-2 to determine the first number of decoded points based on the third number of decoded points.

In some embodiments, for an isolated point P, directly compressing its coordinates is more efficient than using an octree method to compress. This process of directly encoding the coordinates of a point in a node is called a direct coding model (DCM). Whether the current node uses DCM can be inferred based on the information of neighboring nodes. This method is called an inferred direct coding model (IDCM).

In the embodiment of the present application, when the point cloud adopts IDCM and does not adopt IDCM, the number of first encoded points corresponding to the i-th non-zero child node in the point cloud is affected. The following describes the process of affecting the number of first encoded points corresponding to the i-th non-zero child node when the point cloud adopts DCM and does not adopt IDCM.

In some embodiments, if the point cloud does not adopt IDCM, the third number of encoded points corresponding to the i-th non-zero child node is determined as the first number of encoded points corresponding to the i-th non-zero child node.

In this embodiment, if the point cloud does not use IDCM, that is, IDCM is turned off, it means that when encoding the octree, each node in the octree does not use direct encoding. Therefore, when encoding the current node, the octree does not include other first encoded points except the third encoded point corresponding to the i-th non-zero child node determined above. Among them, the first encoded point can be understood as a point whose geometric position has been encoded in the leaf node of the octree. At this time, the number of the third encoded points corresponding to the i-th non-zero child node determined above is directly determined as the number of the first encoded points corresponding to the i-th non-zero child node.

In some embodiments, if the point cloud adopts IDCM, the number of points included in the second node encoded using IDCM in the octree is determined; the number of points included in the second node using IDCM and the third number of encoded points corresponding to the i-th non-zero child node determined above are added to obtain a new first number of encoded points corresponding to the i-th non-zero child node.

In this embodiment, if the point cloud adopts IDCM, that is, IDCM is turned on, then it means that at least one node in the octree of the point cloud may adopt direct coding to directly encode the geometric information of the points included in the node. Correspondingly, when encoding, the geometric information of the points included in the node is directly encoded. In this way, when determining the first encoded point corresponding to the i-th non-zero child node, it is necessary to add the number of points included in the encoded node (i.e., the second node) using IDCM in the octree to the number of the third encoded points corresponding to the i-th non-zero child node determined above.

For example, suppose that in the octree of the point cloud, there is a node using IDCM, suppose that this node using IDCM includes 1 point, and suppose that before encoding the current node, all nodes using IDCM have been encoded. Therefore, it can be determined that the number of points included in the node using IDCM in the octree is 1. This encoded point is added to the third encoded point corresponding to the i-th non-zero child node determined above.

After the encoder determines the number of first encoded points corresponding to the i-th non-zero child node of the current node based on the above step S202-A11, it executes the following step S202-A12.

S202-A12. Determine a second parameter corresponding to the ith non-zero child node based on the number of first encoded points corresponding to the ith non-zero child node in the point cloud.

In the embodiment of the present application, when encoding the current node, the encoding end first determines the number of first encoded points corresponding to the i-th non-zero child node based on the above steps before determining whether to encode the repeated point information of the i-th non-zero child node of the current node, and then determines the second parameter corresponding to the i-th non-zero child node based on the first number of encoded points corresponding to the i-th non-zero child node, so that the second parameter determined in this way can reflect the number of points encoded at the geometric position in the point cloud when encoding the i-th non-zero child node. Finally, based on the first parameter corresponding to the current node and the second parameter corresponding to the i-th non-zero child node, it is determined whether the i-th non-zero child node includes repeated points, and then it is determined whether to encode the repeated point information of the i-th non-zero child node.

In the embodiment of the present application, when the point cloud adopts prediction tree coding and when the prediction tree coding is not adopted, the method of determining the second parameter corresponding to the i-th non-zero child node based on the number of first encoded points corresponding to the i-th non-zero child node in the point cloud is different. The following introduces the specific process of determining the second parameter corresponding to the i-th non-zero child node when the point cloud adopts prediction tree coding and when the prediction tree coding is not adopted.

In the embodiment of the present application, based on the number of first encoded points corresponding to the i-th non-zero child node in the point cloud, determining the second parameter corresponding to the i-th non-zero child node includes at least the following methods:

Method 1: The number of first encoded points is determined as the second parameter.

In the geometric coding of AVS, if the point cloud adopts the prediction tree coding method, that is, the prediction tree coding method is turned off, then, among the encoded points corresponding to the i-th non-zero child node in the point cloud, except for the first encoded point corresponding to the i-th non-zero child node determined in the above embodiment, no other encoded points are included. In this case, when encoding the i-th non-zero child node of the current node, based on the above steps, the number of first encoded points corresponding to the i-th non-zero child node is determined, and the number of first encoded points corresponding to the i-th non-zero child node is determined as the second parameter corresponding to the i-th non-zero child node.

Mode 2: If the point cloud adopts the prediction tree encoding method, the above S202-A12 includes the following steps S202-A121 and S202-A122:

S202-A121, determining the number of second encoded points included in the first node of the octree using the prediction tree encoding method;

S202-A122. Determine the sum of the first number of encoded points and the second number of encoded points as the second parameter.

Correspondingly, when encoding the node, the encoding end uses the prediction tree encoding method to geometrically encode the node to obtain the geometric reconstruction value of the point included in the node. That is to say, in the embodiment of the present application, since the octree is traversed by the breadth-first principle, the position of the node encoded by the prediction tree in the octree is before the current node, that is, when encoding the current node, the node encoded by the prediction tree has been encoded. Therefore, when determining the second parameter corresponding to the i-th non-zero child node of the current node, it is necessary not only to determine the first number of encoded points corresponding to the above-mentioned i-th non-zero child node, but also to determine the number of encoded points included in the first node encoded by the prediction tree in the octree. For the convenience of description, the number of encoded points included in the first node encoded by the prediction tree is recorded as the second number of encoded points. Furthermore, the first number of encoded points corresponding to the i-th non-zero child node is added to the second number of encoded points included in the first node encoded by the prediction tree in the octree, and the result of the addition is determined as the second parameter corresponding to the i-th non-zero child node.

In this case 1, after determining the second parameter corresponding to the i-th non-zero child node of the current node based on the above steps, execute the above S202-A2 to determine whether to encode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter.

The implementation of determining whether to encode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter in S202-A2 includes but is not limited to the following methods:

From the above, we can know that the first parameter corresponding to the current node can be understood as the number of points with uncertain geometric position information in the point cloud when encoding the current node, or can be understood as the number of unencoded points. The second parameter corresponding to the i-th non-zero child node of the current node can be understood as the number of currently encoded points.

In method 1, if the first parameter corresponding to the determined current node is equal to the second parameter corresponding to the i-th non-zero child node in the current node, it means that the i-th non-zero child node and subsequent uncoded leaf nodes do not include duplicate points. Therefore, the encoding of the duplicate point information of the i-th non-zero child node is skipped to save encoding time.

Assuming that the placeholder information of the current node is 01010100, it can be determined that the current node includes 3 non-zero child nodes. Assuming that the i-th non-zero child node is the second non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of the three non-zero child nodes of the current node can be determined, so the geometric position information of the three non-zero child nodes included in the current node has been encoded. As shown in Figure 8, each non-zero node located before the current node in the third layer is the first non-zero node in the third layer. Assuming that the placeholder information of the first non-zero node is 01010101, assuming that the first non-zero child node of the current node includes 1 repeated point, therefore, based on the above method, it can be determined that the first number of encoded points corresponding to the i-th non-zero child node is 4-1+3-1+1=6. In this embodiment, assuming that the point cloud does not use prediction tree encoding, the first number of encoded points corresponding to the i-th non-zero child node, 6, is determined as the second parameter corresponding to the i-th non-zero child node.

In this example, the first parameter 6 corresponding to the current node is equal to the second parameter 6 corresponding to the i-th non-zero child node, and therefore, the encoding of the repeated point information of the i-th non-zero child node is skipped.

Method 2: if the first parameter is greater than the second parameter and the i-th non-zero child node is the last voxel node of the octree, then the encoding of the duplicate point information of the i-th non-zero child node is skipped, and the difference between the first parameter and the second parameter is determined as the number of duplicate points included in the i-th non-zero child node.

In method 2, if the first parameter corresponding to the determined current node is equal to the second parameter corresponding to the i-th non-zero child node in the current node, it means that the i-th non-zero child node and subsequent unencoded leaf nodes may include duplicate points. At the same time, since the i-th non-zero child node is the last non-zero voxel node of the octree, it means that the i-th non-zero child node must include duplicate points, and the number of duplicate points included in the i-th non-zero child node is the difference between the first parameter and the second parameter.

Assuming that the placeholder information of the current node is 00000010, it can be determined that the current node includes 1 non-zero child node. Assuming that the i-th non-zero child node is the only non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of 1 non-zero child node of the current node can be determined, so the geometric position information of 1 non-zero child node included in the current node has been encoded. As shown in Figure 8, the non-zero nodes before the current node in the third layer are the first non-zero node, the second non-zero node, and the third non-zero node in the third layer. Assuming that the placeholder information of the first non-zero node is 01010101, the placeholder information of the first non-zero node is 01010100, and the placeholder information of the first non-zero node is 00000100, the non-zero child nodes of the first three non-zero nodes do not include duplicate points. Based on the above method, it can be determined that the number of the first encoded points corresponding to the i-th non-zero child node is 4-1+3-1+1-1+1-1=5. In this embodiment, assuming that the point cloud does not adopt prediction tree encoding, the number of first encoded points 5 corresponding to the i-th non-zero child node is determined as the second parameter corresponding to the i-th non-zero child node.

From the above, it can be seen that the first parameter 6 is greater than the second parameter 5, and the i-th non-zero child node is the last non-zero child node of the octree. Therefore, it can be determined that the i-th non-zero child node must include repeated points, and the number of repeated points included is 6-5=1. The repeated point information of the i-th non-zero child node is skipped, thereby saving encoding time and improving encoding efficiency.

Mode 3: If the first parameter is greater than the second parameter and the i-th non-zero child node is not the last voxel node of the octree, the duplicate point information of the i-th non-zero child node is encoded.

In method 3, if the first parameter corresponding to the determined current node is equal to the second parameter corresponding to the i-th non-zero child node in the current node, it means that the i-th non-zero child node and subsequent unencoded leaf nodes may include duplicate points. Therefore, in order to ensure the accuracy of the encoding, the duplicate point information of the i-th non-zero child node is encoded.

Assuming that the placeholder information of the current node is 01010100, it can be determined that the current node includes 3 non-zero child nodes. Assuming that the i-th non-zero child node is the second non-zero child node of the current node, since the placeholder information of the current node is known, the geometric position information of the three non-zero child nodes of the current node can be determined, so the geometric position information of the three non-zero child nodes included in the current node has been encoded. As shown in Figure 8, each non-zero node located before the current node in the third layer is the first non-zero node in the third layer. Assuming that the placeholder information of the first non-zero node is 01010101, assuming that the third non-zero child node of the current node includes 1 repeated point, therefore, based on the above method, it can be determined that the first number of encoded points corresponding to the i-th non-zero child node is 4-1+3-1=5. In this embodiment, assuming that the point cloud does not use prediction tree encoding, the first number of encoded points corresponding to the i-th non-zero child node, 5, is determined as the second parameter corresponding to the i-th non-zero child node.

In this example, if the first parameter 6 corresponding to the current node is greater than the second parameter 5 corresponding to the i-th non-zero child node, and the i-th non-zero child node is not the last voxel node of the octree, the duplicate point information of the i-th non-zero child node is encoded.

In the above situation 1, based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer of the octree, the first parameter corresponding to the current node is determined, and the second parameter corresponding to the i-th non-zero child node of the current node is determined. Based on the first parameter and the second parameter, it is determined whether to encode the repeated point information of the i-th non-zero child node. For example, if the first parameter is equal to the second parameter, the repeated point information of the i-th non-zero child node is skipped, thereby reducing the encoding complexity of the point cloud, saving encoding time, and improving the encoding efficiency.

The following introduces the process of determining the first parameter corresponding to the current node in situation 2 and the geometric encoding process of the current node based on the first parameter.

In case 2, the above S201 includes the following steps:

S201-B1, for the i-th non-zero child node in the current node, determine the total number of encoded repeated points corresponding to the i-th non-zero child node;

S201-B2. Determine the total number of encoded repeated points corresponding to the i-th non-zero child node as the first parameter.

In this case 2, when determining whether the i-th non-zero child node of the current node includes repeated points, the number of encoded repeated points corresponding to the i-th non-zero child node is first determined, where the encoded repeated points corresponding to the i-th non-zero child node can be understood as the repeated points that have been encoded by the encoding end before encoding the repeated point information of the i-th non-zero child node.

In some embodiments, the encoder uses dupCount to record the number of repeated points that have been encoded, where dupCount is initialized to 0.

The encoding end determines the total number of encoded repeated points corresponding to the i-th non-zero child node, and determines the total number of encoded repeated points corresponding to the i-th non-zero child node as the first parameter, and then performs geometric encoding on the current node based on the first parameter.

In some embodiments, determining the total number of encoded repeated points corresponding to the i-th non-zero child node in S201-B1 includes:

S201-B11, determining the sum of the number of third encoded repeated points included in each non-zero child node located before the i-th non-zero child node in the octree;

S201-B12. Determine the total number of encoded repeated points corresponding to the i-th non-zero child node based on the sum of the third number of encoded repeated points.

In this embodiment, if the i-th non-zero child node is not the first non-zero leaf node in the octree, the sum of the number of encoded points included in each non-zero child node located before the i-th non-zero child node in the octree is determined. For the sake of ease of description, the encoded point is recorded as the third encoded point.

For example, as shown in Figure 8, assuming that the current node is the first non-zero node in the N-1th layer, the placeholder information of the current node is 010101010, the i-th non-zero child node is the third non-zero child node in the current node, and there are two non-zero child nodes before the i-th non-zero child node in the octree. Assuming that one of the two non-zero child nodes includes two repeated points and the other non-zero child node includes one repeated point, it can be determined that the sum of the third number of encoded repeated points is 2+1=3.

Based on the above steps, after determining the sum of the third number of encoded repeated points included in each non-zero child node located before the i-th non-zero child node in the octree, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined based on the sum of the third number of encoded repeated points.

Based on whether the point cloud adopts prediction tree coding, the implementation methods of determining the total number of encoded repeated points corresponding to the i-th non-zero child node based on the sum of the third number of encoded repeated points in the above S201-B12 include at least the following two methods:

Method 1: If the point cloud adopts the prediction tree coding method, the sum of the fourth number of encoded repeated points included in the first node in the octree using the prediction tree coding method is determined; based on the sum of the third number of encoded repeated points and the sum of the fourth number of encoded repeated points, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined.

In this method 1, if the point cloud adopts the predictive coding method, it can be known from the above that the encoder completes the node in the octree that adopts the predictive tree coding before encoding the current node. In this way, the sum of the fourth number of encoded repeated points included in the first node in the octree that adopts the predictive tree coding method can be obtained, and then based on the sum of the third number of encoded repeated points and the sum of the fourth number of encoded repeated points, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined.

In some embodiments, if the point cloud is not encoded using IDCM, the sum of the third number of encoded duplicate points and the sum of the fourth number of encoded duplicate points are used to determine the total number of encoded duplicate points corresponding to the i-th non-zero child node.

In some embodiments, if the point cloud adopts the inferred direct coding mode IDCM, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined based on the sum of the third number of encoded repeated points and the sum of the fourth number of encoded repeated points, including: determining the sum of the fifth number of encoded repeated points included in the second node using IDCM in the octree; adding the sum of the third number of encoded repeated points, the sum of the fourth number of encoded repeated points, and the sum of the fifth number of encoded repeated points to obtain the total number of encoded repeated points corresponding to the i-th non-zero child node.

Method 2: If the point cloud does not adopt the prediction tree encoding method, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined based on the sum of the third number of encoded repeated points.

In one implementation of method 2, if the point cloud does not use the prediction tree encoding method and does not use the IDCM encoding method, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined based on the sum of the third number of encoded repeated points.

In another implementation of method 2, if the point cloud does not adopt the prediction tree encoding method and adopts the IDCM encoding method, then the sum of the fifth number of encoded repeated points included in the second node using IDCM in the octree is determined, and the sum of the fifth number of encoded repeated points is added to the sum of the third number of encoded repeated points to obtain the total number of encoded repeated points corresponding to the i-th non-zero child node.

Based on the above method, after the total number of encoded repeated points corresponding to the i-th non-zero child node is determined, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined as the first parameter.

In case 2, the geometric encoding of the current node based on the first parameter in S202 includes the following steps S202-B1 and S202-B2:

S202-B1, determining the total number of repeated points in the point cloud;

S202-B2: Determine whether to encode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of encoded duplicate points corresponding to the i-th non-zero child node.

In case 2, when the encoder determines whether to encode the repeated point information of the i-th non-zero child node of the current node, based on the above steps, the number of encoded repeated points corresponding to the i-th non-zero child node is determined as the first parameter. Then, the total number of repeated points in the point cloud is determined, and the number of encoded repeated points corresponding to the i-th non-zero child node is compared with the number of repeated points in the point cloud to determine whether the i-th non-zero child node includes repeated points, and then determine whether to encode the repeated point information of the i-th non-zero child node.

In some embodiments, the encoder determines the number of non-zero voxel nodes in the last layer of the octree through the placeholder information of each non-zero node in the N-1th layer of the octree.

After the encoding end determines the total number of duplicate points in the point cloud based on the above method 1 or method 2, it determines whether to encode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of encoded duplicate points corresponding to the i-th non-zero child node.

In some embodiments, if the total number of encoded duplicate points corresponding to the i-th non-zero child node is equal to the total number of duplicate points in the point cloud, it means that the duplicate points in the point cloud have been encoded, and at this time, the i-th non-zero child node and the leaf nodes after the i-th non-zero child node do not include duplicate points. Therefore, the encoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the encoding complexity of the point cloud, saving encoding time, and improving encoding efficiency.

In some embodiments, if the total number of encoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points in the point cloud, and the i-th non-zero child node is the last voxel node of the octree, it means that the i-th non-zero child node includes duplicate points. At this time, the encoding of the duplicate point information of the i-th non-zero child node is skipped, and the difference between the total number of duplicate points in the point cloud and the total number of encoded duplicate points corresponding to the i-th non-zero child node is determined as the number of duplicate points included in the i-th non-zero child node.

In some embodiments, if the total number of encoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points in the point cloud, and the i-th non-zero child node is the last voxel node of the octree, it means that the i-th non-zero child node or the leaf node after the i-th non-zero child node may include duplicate points. Therefore, in order to improve the encoding accuracy, the encoding end encodes the duplicate point information of the i-th non-zero child node.

From the above, it can be seen that the encoding end determines the first parameter corresponding to the current node in the octree-based point cloud encoding based on the above situation 1 and situation 2, and encodes the current node based on the first parameter.

The point cloud geometry encoding method provided by the embodiment of the present application, in point cloud encoding, for example, in point cloud encoding based on AVS, when encoding the current node of the N-1th layer in the octree, first determine the first parameter corresponding to the current node, the first parameter is used to determine whether at least one non-zero child node of the current node includes duplicate points, the current node is a non-zero node of the N-1th layer in the octree of the point cloud, N is the total number of layers of the octree, and then based on the first parameter, the current node is geometrically encoded. For example, when it is determined based on the first parameter that the i-th non-zero child node of the current node does not include duplicate points, the encoding of the duplicate point information of the i-th non-zero child node is skipped, thereby reducing the encoding complexity of the point cloud, saving encoding time, and thus improving encoding efficiency.

It should be understood that FIGS. 6 to 9 are merely examples of the present application and should not be construed as limiting the present application.

The preferred embodiments of the present application are described in detail above in conjunction with the accompanying drawings. However, the present application is not limited to the specific details in the above embodiments. Within the technical concept of the present application, the technical solution of the present application can be subjected to a variety of simple modifications, and these simple modifications all belong to the protection scope of the present application. For example, the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present application will not further explain various possible combinations. For another example, the various different embodiments of the present application can also be arbitrarily combined, as long as they do not violate the ideas of the present application, they should also be regarded as the contents disclosed in the present application.

It should also be understood that in the various method embodiments of the present application, the size of the sequence number of each process does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application. In addition, in the embodiment of the present application, the term "and/or" is merely a description of the association relationship of associated objects, indicating that three relationships may exist. Specifically, A and/or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character "/" in this article generally indicates that the objects associated before and after are in an "or" relationship.

The method embodiment of the present application is described in detail above in conjunction with Figures 6 to 9 , and the device embodiment of the present application is described in detail below in conjunction with Figures 10 to 13 .

FIG. 10 is a schematic block diagram of a point cloud decoding device provided in an embodiment of the present application.

As shown in FIG10 , the point cloud decoding device 10 may include:

A determination unit 11 is used to determine a first parameter corresponding to a current node, where the first parameter is used to determine whether at least one non-zero child node of the current node includes a duplicate point, where the current node is a non-zero node in the N-1th layer of an octree of the point cloud, where the octree is obtained by node division of the point cloud, where N is a total number of layers of the octree, and where N is a positive integer greater than 1;

The decoding unit 12 is used to perform geometric decoding on the current node based on the first parameter.

In some embodiments, the determination unit 11 is specifically used to determine the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer; based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer, the first parameter is determined.

In some embodiments, the determination unit 11 is specifically configured to determine the difference between the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer as the first parameter.

In some embodiments, the decoding unit 12 is specifically used to determine, for the i-th non-zero child node of the current node, a second parameter corresponding to the i-th non-zero child node, wherein the second parameter is used to indicate the number of points whose geometric positions in the point cloud have been decoded when decoding the i-th non-zero child node, and i is a positive integer; based on the first parameter and the second parameter, determine whether to decode the duplicate point information of the i-th non-zero child node.

In some embodiments, the decoding unit 12 is specifically used to determine the first number of decoded points corresponding to the i-th non-zero subnode in the point cloud; based on the first number of decoded points corresponding to the i-th non-zero subnode in the point cloud, determine the second parameter corresponding to the i-th non-zero subnode.

In some embodiments, if the point cloud does not adopt the prediction tree encoding method, the decoding unit 12 is specifically used to determine the first number of decoded points as the second parameter.

In some embodiments, if the point cloud adopts the prediction tree encoding method, the decoding unit 12 is specifically used to determine the number of second decoded points included in the first node in the octree that adopts the prediction tree encoding method; and the sum of the first number of decoded points and the second number of decoded points is determined as the second parameter.

In some embodiments, the decoding unit 12 is specifically configured to determine the third number of decoded points corresponding to the i-th non-zero child node; and determine the first number of decoded points based on the third number of decoded points.

In some embodiments, the decoding unit 12 is specifically used to determine the number of non-zero child nodes of the current node if the current node is the first non-zero node in the N-1th layer; based on the number of non-zero child nodes of the current node, determine the number of third decoded points corresponding to the i-th non-zero child node.

In some embodiments, the decoding unit 12 is specifically used to determine the number of decoded points corresponding to the i-th non-zero child node as the value obtained by subtracting 1 from the number of non-zero child nodes included in the current node if the i-th non-zero child node is the first non-zero child node of the current node.

In some embodiments, the decoding unit 12 is specifically used to obtain the sum of the first number of repeated points included in the non-zero child nodes of the current node that are located before the i-th non-zero child node if the i-th non-zero child node is not the first non-zero child node of the current node; subtract 1 from the number of non-zero child nodes included in the current node, and then add the result to the sum of the first number of repeated points to obtain the third number of decoded points.

In some embodiments, the decoding unit 12 is specifically used to determine the number of decoded points corresponding to each non-zero node in the N-1 layer before the current node if the current node is not the first non-zero node in the N-1 layer; determine the number of non-zero child nodes of the current node; and determine the third number of decoded points corresponding to the i-th non-zero child node based on the number of decoded points corresponding to each non-zero node in the N-1 layer before the current node and the number of non-zero child nodes of the current node.

In some embodiments, the decoding unit 12 is specifically used to obtain, for any non-zero node among the non-zero nodes, the number of non-zero child nodes of the non-zero node and the sum of the second number of repeated points included in the non-zero child nodes of the non-zero node; subtract 1 from the number of non-zero child nodes of the non-zero node, and add the result to the sum of the second number of repeated points to obtain the number of decoded points corresponding to the non-zero node.

In some embodiments, the decoding unit 12 is specifically used to add the number of decoded points corresponding to each non-zero node in the N-1th layer that is located before the current node to obtain a first sum; based on the first sum and the number of non-zero child nodes of the current node, determine the third number of decoded points corresponding to the i-th non-zero child node.

In some embodiments, the decoding unit 12 is specifically used to add the first sum value and the number of non-zero child nodes included in the current node to obtain a second sum value if the i-th non-zero child node is the first non-zero child node of the current node; and subtract 1 from the second sum value to obtain the third number of decoded points corresponding to the i-th non-zero child node.

In some embodiments, the decoding unit 12 is specifically used to add the first sum value and the number of non-zero child nodes included in the current node to obtain a second sum value if the i-th non-zero child node is not the first non-zero child node of the current node; subtract 1 from the second sum value to obtain a third sum value; obtain the sum of the first number of repeated points included in the non-zero child nodes in the current node that are located before the i-th non-zero child node, and add the third sum value to the sum of the first number of repeated points to obtain the third number of decoded points corresponding to the i-th non-zero child node.

In some embodiments, if the point cloud does not adopt the inferred direct coding mode IDCM, the decoding unit 12 is specifically configured to determine the third number of decoded points as the first number of decoded points.

In some embodiments, if the point cloud adopts the inferred direct coding mode IDCM, the decoding unit 12 is specifically used to determine the number of points included in the second node of the octree adopting IDCM; and the sum of the third number of decoded points and the number of points included in the second node is determined as the first number of decoded points.

In some embodiments, the decoding unit 12 is specifically configured to skip decoding the repeated point information of the i-th non-zero child node if the first parameter is equal to the second parameter.

In some embodiments, the decoding unit 12 is specifically used to skip decoding the repeated point information of the i-th non-zero child node if the first parameter is greater than the second parameter and the i-th non-zero child node is the last voxel node of the octree, and determine the difference between the first parameter and the second parameter as the number of repeated points included in the i-th non-zero child node.

In some embodiments, the decoding unit 12 is specifically used to decode the duplicate point information of the i-th non-zero child node if the first parameter is greater than the second parameter and the i-th non-zero child node is not the last voxel node of the octree.

In some embodiments, the determination unit 11 is specifically used to determine the total number of decoded repeated points corresponding to the i-th non-zero child node in the current node, where i is a positive integer; and determine the total number of decoded repeated points corresponding to the i-th non-zero child node as the first parameter.

In some embodiments, the determination unit 11 is specifically used to determine the sum of the third number of decoded repeated points included in each non-zero child node located before the i-th non-zero child node in the octree; based on the sum of the third number of decoded repeated points, determine the total number of decoded repeated points corresponding to the i-th non-zero child node.

In some examples, if the point cloud adopts the prediction tree encoding method, the determination unit 11 is specifically used to determine the sum of the fourth number of decoded repeated points included in the first node in the octree that adopts the prediction tree encoding method; based on the sum of the third number of decoded repeated points and the sum of the fourth number of decoded repeated points, determine the total number of decoded repeated points corresponding to the i-th non-zero child node.

In some embodiments, if the point cloud adopts the inferred direct coding mode IDCM, the determination unit 11 is specifically used to determine the sum of the fifth number of decoded repeated points included in the second node using IDCM in the octree; the sum of the third number of decoded repeated points, the sum of the fourth number of decoded repeated points, and the sum of the fifth number of decoded repeated points are added to obtain the total number of decoded repeated points corresponding to the i-th non-zero child node.

In some embodiments, the decoding unit 12 is specifically used to determine the total number of repeated points in the point cloud; based on the total number of repeated points in the point cloud and the total number of decoded repeated points corresponding to the i-th non-zero child node, determine whether to decode the repeated point information of the i-th non-zero child node.

In some embodiments, the decoding unit 12 is specifically used to determine the total number of points in the point cloud and the total number of non-zero voxel nodes in the octree; and the difference between the total number of points in the point cloud and the total number of non-zero voxel nodes in the octree is determined as the total number of repeated points in the point cloud.

In some embodiments, the decoding unit 12 is specifically configured to skip decoding the repeated point information of the i-th non-zero child node if the total number of decoded repeated points corresponding to the i-th non-zero child node is equal to the total number of repeated points of the point cloud.

In some embodiments, the decoding unit 12 is specifically used to skip decoding the duplicate point information of the i-th non-zero child node if the total number of decoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points of the point cloud, and the i-th non-zero child node is the last voxel node of the octree, and determine the difference between the total number of duplicate points of the point cloud and the total number of decoded duplicate points corresponding to the i-th non-zero child node as the number of duplicate points included in the i-th non-zero child node.

In some embodiments, the decoding unit 12 is specifically used to decode the duplicate point information of the i-th non-zero child node if the total number of decoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points of the point cloud, and the i-th non-zero child node is not the last voxel node of the octree.

In some embodiments, the repeated point information includes the number of repeated points.

In some embodiments, the decoding unit 12 is specifically configured to decode the geometric code stream of the point cloud to obtain the total number of points of the point cloud.

In some embodiments, the decoding unit 12 is specifically configured to decode a geometric unit header of the point cloud to obtain a total number of points of the point cloud.

In some embodiments, the decoding unit 12 is specifically used to decode the geometric unit header to obtain the low-order part of the number of points contained in the slice corresponding to the point cloud and the high-order part of the number of points contained in the slice; based on the low-order part of the number of points contained in the slice and the high-order part of the number of points contained in the slice, the total number of points in the point cloud is obtained.

In some embodiments, the decoding unit 12 is specifically used to decode the geometric code stream of the point cloud to obtain the placeholder information of the current node; based on the placeholder information, obtain the number of non-zero child nodes included in the current node.

It should be understood that the device embodiment and the method embodiment may correspond to each other, and similar descriptions may refer to the method embodiment. To avoid repetition, no further description is given here. Specifically, the point cloud decoding device 10 shown in FIG. 10 may correspond to the corresponding subject in the point cloud decoding method of the embodiment of the present application, and the aforementioned and other operations and/or functions of each unit in the point cloud decoding device 10 are respectively for implementing the corresponding processes in the point cloud decoding method, and for the sake of brevity, no further description is given here.

FIG. 11 is a schematic block diagram of a point cloud encoding device provided in an embodiment of the present application.

As shown in FIG11 , the point cloud encoding device 20 includes:

A determination unit 21 is used to determine a first parameter corresponding to a current node, where the first parameter is used to determine whether at least one non-zero child node of the current node includes a duplicate point, where the current node is a non-zero node in the N-1th layer of the octree of the point cloud, where the octree is obtained by node division of the point cloud, where N is the total number of layers of the octree, and where N is a positive integer greater than 1;

The encoding unit 22 is used to perform geometric encoding on the current node based on the first parameter.

In some embodiments, the determination unit 21 is specifically used to determine the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer; based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer, determine the first parameter.

In some embodiments, the determination unit 21 is specifically configured to determine the difference between the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer as the first parameter.

In some embodiments, the encoding unit 22 is specifically used to determine, for the i-th non-zero child node of the current node, a second parameter corresponding to the i-th non-zero child node, wherein the second parameter is used to indicate the number of points whose geometric positions in the point cloud have been encoded when encoding the i-th non-zero child node; based on the first parameter and the second parameter, determine whether to encode the repeated point information of the i-th non-zero child node.

In some embodiments, if the point cloud does not adopt the prediction tree encoding method, the encoding unit 22 is specifically used to determine the number of first encoded points corresponding to the i-th non-zero child node in the point cloud as the second parameter.

In some embodiments, if the point cloud adopts the prediction tree encoding method, in some embodiments, the encoding unit 22 is specifically used to obtain the second number of encoded points included in the first encoding unit using the prediction tree encoding in the encoding unit of the point cloud, and the encoding unit is a non-zero node obtained by dividing the bounding box of the point cloud by a preset number of times; the sum of the first number of encoded points and the second number of encoded points is determined as the second parameter.

In some embodiments, the encoding unit 22 is specifically configured to determine the number of third encoded points corresponding to the i-th non-zero child node; and determine the number of first encoded points based on the third number of encoded points.

In some embodiments, the encoding unit 22 is specifically used to determine the number of non-zero child nodes of the current node if the current node is the first non-zero node in the N-1th layer; based on the number of non-zero child nodes of the current node, determine the number of third encoded points corresponding to the i-th non-zero child node.

In some embodiments, the encoding unit 22 is specifically used to, if the i-th non-zero child node is the first non-zero child node of the current node, reduce the number of non-zero child nodes included in the current node by 1, and determine the third number of encoded points corresponding to the i-th non-zero child node.

In some embodiments, the encoding unit 22 is specifically used to obtain the sum of the first number of repeated points included in the child nodes before the i-th non-zero child node in the current node if the i-th non-zero child node is not the first non-zero child node of the current node; subtract 1 from the number of non-zero child nodes included in the current node, and then add the result to the sum of the first number of repeated points to obtain the third number of encoded points corresponding to the i-th non-zero child node.

In some embodiments, the encoding unit 22 is specifically used to determine the number of encoded points corresponding to each non-zero node in the N-1 layer before the current node if the current node is not the first non-zero node in the N-1 layer; determine the number of non-zero child nodes of the current node; and determine the third number of encoded points based on the number of encoded points corresponding to each non-zero node in the N-1 layer before the current node and the number of non-zero child nodes of the current node.

In some embodiments, the encoding unit 22 is specifically used to obtain, for any non-zero node among the non-zero nodes, the number of non-zero child nodes of the non-zero node and the sum of the second number of repeated points included in the non-zero child nodes of the non-zero node; subtract 1 from the number of non-zero child nodes of the non-zero node, and add the result to the sum of the second number of repeated points to obtain the number of encoded points corresponding to the non-zero node.

In some embodiments, the encoding unit 22 is specifically used to add the number of encoded points corresponding to each non-zero node in the N-1th layer that is located before the current node to obtain a first sum; and determine the third number of encoded points based on the first sum and the number of non-zero child nodes of the current node.

In some embodiments, the encoding unit 22 is specifically used to add the first sum value and the number of non-zero child nodes included in the current node to obtain a second sum value if the i-th non-zero child node is the first non-zero child node of the current node; and subtract 1 from the second sum value to obtain the third number of encoded points.

In some embodiments, the encoding unit 22 is specifically used to add the first sum value and the number of non-zero child nodes included in the current node to obtain a second sum value if the i-th non-zero child node is not the first non-zero child node of the current node; subtract 1 from the second sum value to obtain a third sum value; obtain the sum of the first number of repeated points included in the non-zero child nodes in the current node that are located before the i-th non-zero child node, and add the third sum value to the sum of the first number of repeated points to obtain the third number of encoded points.

In some embodiments, if the point cloud does not adopt the inferred direct coding mode IDCM, the encoding unit 22 is specifically configured to determine the third number of encoded points as the first number of encoded points.

In some embodiments, if the point cloud adopts the inferred direct coding mode IDCM, the encoding unit 22 is specifically used to determine the number of points included in the second node of the octree adopting IDCM; the sum of the number of encoded points corresponding to the i-th non-zero child node and the number of points included in the second node is determined as the first number of encoded points.

In some embodiments, the encoding unit 22 is specifically configured to skip encoding repeated point information of the i-th non-zero child node if the first parameter is equal to the second parameter.

In some embodiments, the encoding unit 22 is specifically used to skip encoding the repeated point information of the i-th non-zero child node if the first parameter is greater than the second parameter and the i-th non-zero child node is the last voxel node of the octree, and determine the difference between the first parameter and the second parameter as the number of repeated points included in the i-th non-zero child node.

In some embodiments, the encoding unit 22 is specifically used to encode the duplicate point information of the i-th non-zero child node if the first parameter is greater than the second parameter and the i-th non-zero child node is not the last voxel node of the octree.

In some embodiments, the determination unit 21 is specifically used to determine the total number of encoded repeated points corresponding to the i-th non-zero child node in the current node, where i is a positive integer; and determine the total number of encoded repeated points corresponding to the i-th non-zero child node as the first parameter.

In some embodiments, the determination unit 21 is specifically used to determine the sum of the third number of encoded repeated points included in each non-zero child node located before the i-th non-zero child node in the octree; based on the sum of the third number of encoded repeated points, determine the total number of encoded repeated points corresponding to the i-th non-zero child node.

In some embodiments, if the point cloud adopts the prediction tree encoding method, the determination unit 21 is specifically used to determine the sum of the fourth number of encoded repeated points included in the first node in the octree that adopts the prediction tree encoding method; based on the sum of the third number of encoded repeated points and the sum of the fourth number of encoded repeated points, determine the total number of encoded repeated points corresponding to the i-th non-zero child node.

In some embodiments, if the point cloud adopts the inferred direct coding mode IDCM, the determination unit 21 is specifically used to determine the sum of the fifth number of encoded repeated points included in the second node using IDCM in the octree; the sum of the third number of encoded repeated points, the sum of the fourth number of encoded repeated points, and the sum of the fifth number of encoded repeated points are added to obtain the total number of encoded repeated points corresponding to the i-th non-zero child node.

In some embodiments, the encoding unit 22 is specifically used to determine the total number of repeated points in the point cloud; based on the total number of repeated points in the point cloud and the total number of encoded repeated points corresponding to the i-th non-zero child node, determine whether to encode the repeated point information of the i-th non-zero child node.

In some embodiments, the encoding unit 22 is specifically used to determine the total number of points in the point cloud and the total number of non-zero voxel nodes in the octree; and the difference between the total number of points in the point cloud and the total number of non-zero voxel nodes in the octree is determined as the total number of repeated points in the point cloud.

In some embodiments, the encoding unit 22 is specifically configured to skip encoding the repeated point information of the i-th non-zero child node if the total number of encoded repeated points corresponding to the i-th non-zero child node is equal to the total number of repeated points of the point cloud.

In some embodiments, the encoding unit 22 is specifically used to skip encoding the duplicate point information of the i-th non-zero child node if the total number of encoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points of the point cloud, and the i-th non-zero child node is the last voxel node of the octree, and determine the difference between the total number of duplicate points of the point cloud and the total number of encoded duplicate points corresponding to the i-th non-zero child node as the number of duplicate points included in the i-th non-zero child node.

In some embodiments, the encoding unit 22 is specifically used to encode the duplicate point information of the i-th non-zero child node if the total number of encoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points of the point cloud, and the i-th non-zero child node is not the last voxel node of the octree.

In some embodiments, the encoding unit 22 is further configured to write the total number of points of the point cloud into the geometric code stream of the point cloud.

In some embodiments, the encoding unit 22 is specifically configured to write the total number of points of the point cloud into a geometric unit header of the point cloud.

In some embodiments, the encoding unit 22 is specifically used to determine the low-order part of the number of points contained in the slice corresponding to the point cloud and the high-order part of the number of points contained in the slice based on the total number of points in the point cloud; and write the low-order part of the number of points contained in the slice and the high-order part of the number of points contained in the slice into the header of the geometric unit.

It should be understood that the device embodiment and the method embodiment may correspond to each other, and similar descriptions may refer to the method embodiment. To avoid repetition, it will not be repeated here. Specifically, the point cloud encoding device 20 shown in Figure 11 may correspond to the corresponding subject in the point cloud encoding method of the embodiment of the present application, and the aforementioned and other operations and/or functions of each unit in the point cloud encoding device 20 are respectively for implementing the corresponding processes in the point cloud encoding method. For the sake of brevity, they will not be repeated here.

The above describes the device and system of the embodiment of the present application from the perspective of the functional unit in conjunction with the accompanying drawings. It should be understood that the functional unit can be implemented in hardware form, can be implemented by instructions in software form, and can also be implemented by a combination of hardware and software units. Specifically, the steps of the method embodiment in the embodiment of the present application can be completed by the hardware integrated logic circuit and/or software form instructions in the processor, and the steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or a combination of hardware and software units in the decoding processor to perform. Optionally, the software unit can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory, and completes the steps in the above method embodiment in conjunction with its hardware.

FIG. 12 is a schematic block diagram of an electronic device provided in an embodiment of the present application.

As shown in FIG. 12 , the electronic device 30 may be a point cloud decoding device or a point cloud encoding device as described in an embodiment of the present application, and the electronic device 30 may include:

The memory 33 and the processor 32, the memory 33 is used to store the computer program 34 and transmit the program code 34 to the processor 32. In other words, the processor 32 can call and run the computer program 34 from the memory 33 to implement the method in the embodiment of the present application.

For example, the processor 32 may be configured to execute the steps in the method 200 according to the instructions in the computer program 34 .

In some embodiments of the present application, the processor 32 may include but is not limited to:

General-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

In some embodiments of the present application, the memory 33 includes but is not limited to:

Volatile memory and/or non-volatile memory. Among them, the non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM) or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM) and direct RAM bus random access memory (Direct Rambus RAM, DR RAM).

In some embodiments of the present application, the computer program 34 may be divided into one or more units, which are stored in the memory 33 and executed by the processor 32 to complete the method provided by the present application. The one or more units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program 34 in the electronic device 30.

As shown in FIG. 12 , the electronic device 30 may further include:

The transceiver 33 may be connected to the processor 32 or the memory 33 .

The processor 32 may control the transceiver 33 to communicate with other devices, specifically, to send information or data to other devices, or to receive information or data sent by other devices. The transceiver 33 may include a transmitter and a receiver. The transceiver 33 may further include an antenna, and the number of antennas may be one or more.

It should be understood that the various components in the electronic device 30 are connected via a bus system, wherein the bus system includes not only a data bus but also a power bus, a control bus and a status signal bus.

As shown in Figure 13, the point cloud encoding and decoding system 40 may include: a point cloud encoder 41 and a point cloud decoder 42, wherein the point cloud encoder 41 is used to execute the point cloud encoding method involved in the embodiment of the present application, and the point cloud decoder 42 is used to execute the point cloud decoding method involved in the embodiment of the present application.

The present application also provides a code stream, which is generated according to the above encoding method.

The present application also provides a computer storage medium on which a computer program is stored, and when the computer program is executed by a computer, the computer can perform the method of the above method embodiment. In other words, the present application embodiment also provides a computer program product containing instructions, and when the instructions are executed by a computer, the computer can perform the method of the above method embodiment.

When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (digital video disc, DVD)), or a semiconductor medium (e.g., a solid state drive (solid state disk, SSD)), etc.

Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the unit is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. For example, each functional unit in each embodiment of the present application may be integrated into a processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

A point cloud decoding method, characterized by comprising:

Determine a first parameter corresponding to a current node, where the first parameter is used to determine whether at least one non-zero child node of the current node includes a duplicate point, where the current node is a non-zero node in the N-1th layer of an octree of the point cloud, where the octree is obtained by node division of the point cloud, where N is the total number of layers of the octree, and where N is a positive integer greater than 1;

Based on the first parameter, geometric decoding is performed on the current node.
The method according to claim 1, characterized in that the determining the first parameter corresponding to the current node comprises:

Determine the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer;

The first parameter is determined based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer.
The method according to claim 2, characterized in that the determining the first parameter based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer comprises:

The difference between the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer is determined as the first parameter.
The method according to claim 3, characterized in that the geometric decoding of the current node based on the first parameter comprises:

For the i-th non-zero child node of the current node, determine a second parameter corresponding to the i-th non-zero child node, where the second parameter is used to indicate the number of points whose geometric positions in the point cloud have been decoded when decoding the i-th non-zero child node, and i is a positive integer;

Based on the first parameter and the second parameter, determine whether to decode the repeated point information of the i-th non-zero child node.
The method according to claim 4, characterized in that the determining the second parameter corresponding to the i-th non-zero child node comprises:

Determine the number of first decoded points corresponding to the i-th non-zero child node;

Based on the first number of decoded points, a second parameter corresponding to the i-th non-zero child node is determined.
The method according to claim 5, characterized in that, if the point cloud does not adopt a prediction tree encoding method, determining the second parameter corresponding to the i-th non-zero child node based on the first number of decoded points comprises:

The number of the first decoded points is determined as the second parameter.
The method according to claim 5, characterized in that if the point cloud adopts a prediction tree encoding method, the determining the second parameter corresponding to the i-th non-zero child node based on the first number of decoded points includes:

Determine the number of second decoded points included in the first node of the octree using the prediction tree encoding method;

The sum of the first number of decoded points and the second number of decoded points is determined as the second parameter.
The method according to claim 5, characterized in that the determining the number of first decoded points corresponding to the i-th non-zero child node comprises:

Determine the number of third decoded points corresponding to the i-th non-zero child node;

Based on the third number of decoded points, the first number of decoded points is determined.
The method according to claim 8, characterized in that the determining the number of third decoded points corresponding to the i-th non-zero child node comprises:

If the current node is the first non-zero node in the N-1th layer, determining the number of non-zero child nodes of the current node;

The third number of decoded points is determined based on the number of non-zero child nodes of the current node.
The method according to claim 9, characterized in that the determining the third number of decoded points based on the number of non-zero child nodes of the current node comprises:

If the i-th non-zero child node is the first non-zero child node of the current node, the value obtained by subtracting 1 from the number of non-zero child nodes included in the current node is determined as the third number of decoded points.
The method according to claim 9, characterized in that the determining the third number of decoded points based on the number of non-zero child nodes of the current node comprises:

If the i-th non-zero child node is not the first non-zero child node of the current node, then obtaining the sum of the first number of repeated points included in the non-zero child nodes of the current node that are located before the i-th non-zero child node;

The number of non-zero child nodes included in the current node is subtracted by 1, and then added to the sum of the first number of repeated points to obtain the third number of decoded points.
The method according to claim 8, characterized in that the determining the number of third decoded points corresponding to the i-th non-zero child node comprises:

If the current node is not the first non-zero node in the N-1th layer, determining the number of decoded points corresponding to each non-zero node in the N-1th layer before the current node;

Determine the number of non-zero child nodes of the current node;

The third number of decoded points is determined based on the number of decoded points corresponding to each non-zero node located before the current node in the N-1th layer and the number of non-zero child nodes of the current node.
The method according to claim 12, characterized in that the determining the number of decoded points corresponding to each non-zero node located before the current node in the N-1th layer comprises:

For any non-zero node among the non-zero nodes, obtain the number of non-zero child nodes of the non-zero node and the sum of the number of second repeated points included in the non-zero child nodes of the non-zero node;

The number of non-zero child nodes of the non-zero node is subtracted by 1, and then added to the sum of the second number of repeated points to obtain the number of decoded points corresponding to the non-zero node.
The method according to claim 12, characterized in that the determining the third number of decoded points based on the number of decoded points corresponding to each non-zero node located before the current node in the N-1th layer and the number of non-zero child nodes of the current node comprises:

Adding the numbers of decoded points corresponding to the non-zero nodes before the current node in the N-1th layer to obtain a first sum;

The third number of decoded points is determined based on the first sum value and the number of non-zero child nodes of the current node.
The method according to claim 14, characterized in that the determining the third number of decoded points based on the first sum value and the number of non-zero child nodes of the current node comprises:

If the i-th non-zero child node is the first non-zero child node of the current node, then the first sum value is added to the number of non-zero child nodes included in the current node to obtain a second sum value;

Subtract 1 from the second sum to obtain the third number of decoded points.
The method according to claim 14, characterized in that the determining the third number of decoded points based on the first sum value and the number of non-zero child nodes of the current node comprises:

If the i-th non-zero child node is not the first non-zero child node of the current node, then adding the first sum value to the number of non-zero child nodes included in the current node to obtain a second sum value;

Subtract 1 from the second sum to obtain a third sum;

The sum of the first number of repeated points included in the non-zero child nodes located before the i-th non-zero child node in the current node is obtained, and the third sum value is added to the sum of the first number of repeated points to obtain the third number of decoded points.
The method according to claim 8, characterized in that if the point cloud does not adopt an inferred direct coding mode IDCM, then determining the first number of decoded points based on the third number of decoded points comprises:

The third number of decoded points is determined as the first number of decoded points.
The method according to claim 8, characterized in that if the point cloud adopts an inferred direct coding mode IDCM, then determining the first number of decoded points based on the third number of decoded points comprises:

Determine the number of points included in the second node of the octree using IDCM;

The sum of the third number of decoded points and the number of points included in the second node is determined as the first number of decoded points.
The method according to any one of claims 4 to 18, characterized in that the determining whether to decode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter comprises:

If the first parameter is equal to the second parameter, skip decoding the repeated point information of the i-th non-zero child node.
The method according to any one of claims 4 to 18, characterized in that the determining whether to decode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter comprises:

If the first parameter is greater than the second parameter, and the i-th non-zero child node is the last voxel node of the octree, skip decoding the repeated point information of the i-th non-zero child node, and determine the difference between the first parameter and the second parameter as the number of repeated points included in the i-th non-zero child node.
The method according to any one of claims 4 to 18, characterized in that the determining whether to decode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter comprises:

If the first parameter is greater than the second parameter, and the i-th non-zero child node is not the last voxel node of the octree, the repeated point information of the i-th non-zero child node is decoded.
The method according to claim 1, characterized in that the determining the first parameter corresponding to the current node comprises:

For the i-th non-zero child node in the current node, determine the total number of decoded repeated points corresponding to the i-th non-zero child node, where i is a positive integer;

The total number of decoded repeated points corresponding to the i-th non-zero child node is determined as the first parameter.
The method according to claim 22, characterized in that the determining the total number of decoded repeated points corresponding to the i-th non-zero child node comprises:

Determine the sum of the numbers of third decoded repeated points included in each non-zero child node located before the i-th non-zero child node in the octree;

Based on the sum of the third number of decoded repeated points, the total number of decoded repeated points corresponding to the i-th non-zero child node is determined.
The method according to claim 23, characterized in that if the point cloud adopts a prediction tree encoding method, then determining the total number of decoded repeated points corresponding to the i-th non-zero child node based on the sum of the third number of decoded repeated points includes:

Determine the sum of the number of fourth decoded repeated points included in the first node of the octree using the prediction tree encoding method;

Based on the sum of the third number of decoded repeated points and the sum of the fourth number of decoded repeated points, the total number of decoded repeated points corresponding to the i-th non-zero child node is determined.
The method according to claim 24, characterized in that if the point cloud adopts the inferred direct coding mode IDCM, then determining the total number of decoded repeated points corresponding to the i-th non-zero child node based on the sum of the third number of decoded repeated points and the sum of the fourth number of decoded repeated points comprises:

Determine the sum of the number of fifth decoded repeated points included in the second node using IDCM in the octree;

The sum of the third number of decoded repeated points, the sum of the fourth number of decoded repeated points, and the sum of the fifth number of decoded repeated points are added together to obtain the total number of decoded repeated points corresponding to the i-th non-zero child node.
The method according to any one of claims 22 to 25, characterized in that the step of geometrically decoding the current node based on the first parameter comprises:

Determining a total number of duplicate points of the point cloud;

Based on the total number of repeated points in the point cloud and the total number of decoded repeated points corresponding to the i-th non-zero child node, it is determined whether to decode the repeated point information of the i-th non-zero child node.
The method according to claim 26, characterized in that determining the total number of repeated points in the point cloud comprises:

Determine the total number of points in the point cloud and the total number of non-zero voxel nodes in the octree;

The difference between the total number of points of the point cloud and the total number of non-zero voxel nodes of the octree is determined as the total number of repeated points of the point cloud.
The method according to claim 27, characterized in that the determining whether to decode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of decoded duplicate points corresponding to the i-th non-zero child node comprises:

If the total number of decoded repeated points corresponding to the i-th non-zero child node is equal to the total number of repeated points of the point cloud, then decoding of the repeated point information of the i-th non-zero child node is skipped.
The method according to claim 27, characterized in that the determining whether to decode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of decoded duplicate points corresponding to the i-th non-zero child node comprises:

If the total number of decoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points of the point cloud, and the i-th non-zero child node is the last voxel node of the octree, then the decoding of the duplicate point information of the i-th non-zero child node is skipped, and the difference between the total number of duplicate points of the point cloud and the total number of decoded duplicate points corresponding to the i-th non-zero child node is determined as the number of duplicate points included in the i-th non-zero child node.
The method according to claim 27, characterized in that the determining whether to decode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of decoded duplicate points corresponding to the i-th non-zero child node comprises:

If the total number of decoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points in the point cloud, and the i-th non-zero child node is not the last voxel node of the octree, the duplicate point information of the i-th non-zero child node is decoded.
The method according to any one of claims 1-18 is characterized in that the repeated point information includes the number of repeated points.
The method according to claim 2 or 27, characterized in that determining the total number of points in the point cloud comprises:

Decode the geometric code stream of the point cloud to obtain the total number of points of the point cloud.
The method according to claim 32, characterized in that the decoding of the geometric code stream of the point cloud to obtain the total number of points of the point cloud comprises:

Decode the geometric unit header of the point cloud to obtain the total number of points of the point cloud.
The method according to claim 33, characterized in that decoding the geometric unit header to obtain the total number of points in the point cloud comprises:

Decoding the geometry unit header to obtain a low-order portion of points contained in a slice corresponding to the point cloud and a high-order portion of points contained in the slice;

The total number of points in the point cloud is obtained based on the low-order part of the number of points in the slice and the high-order part of the number of points in the slice.
The method according to claim 12, characterized in that the determining the number of non-zero child nodes of the current node comprises:

Decoding the geometric code stream of the point cloud to obtain the placeholder information of the current node;

Based on the placeholder information, the number of non-zero child nodes included in the current node is obtained.
A point cloud encoding method, characterized by comprising:

Determine a first parameter corresponding to a current node, where the first parameter is used to determine whether at least one child node of the current node includes a duplicate point, where the current node is a non-zero node in the N-1th layer of an octree of the point cloud, where the octree is obtained by node division of the point cloud, where N is the total number of layers of the octree, and where N is a positive integer greater than 1;

Based on the first parameter, geometric encoding is performed on the current node.
The method according to claim 36, characterized in that the determining the first parameter corresponding to the current node comprises:

Determine the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer;

The first parameter is determined based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer.
The method according to claim 37, characterized in that the determining the first parameter based on the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer comprises:

The difference between the total number of points in the point cloud and the number of non-zero nodes in the N-1th layer is determined as the first parameter.
The method according to claim 38, characterized in that the geometric encoding of the current node based on the first parameter comprises:

For the i-th non-zero child node of the current node, determine a second parameter corresponding to the i-th non-zero child node, where the second parameter is used to indicate the number of points whose geometric positions in the point cloud have been encoded when encoding the i-th non-zero child node;

Based on the first parameter and the second parameter, determine whether to encode the repeated point information of the i-th non-zero child node.
The method according to claim 39, characterized in that the determining the second parameter corresponding to the i-th non-zero child node comprises:

Determine the number of first encoded points corresponding to the i-th non-zero child node in the point cloud;

Based on the number of first encoded points corresponding to the ith non-zero child node in the point cloud, a second parameter corresponding to the ith non-zero child node is determined.
The method according to claim 40, characterized in that if the point cloud adopts a prediction tree encoding method, the determining the second parameter corresponding to the i-th non-zero child node based on the number of first encoded points corresponding to the i-th non-zero child node in the point cloud comprises:

The number of first encoded points corresponding to the i-th non-zero child node in the point cloud is determined as the second parameter.
The method according to claim 40, characterized in that, if the point cloud does not adopt the prediction tree encoding method, the determining the second parameter corresponding to the i-th non-zero child node based on the number of first encoded points corresponding to the i-th non-zero child node in the point cloud comprises:

Obtaining the number of second encoded points included in a first encoding unit encoded by a prediction tree in an encoding unit of the point cloud, wherein the encoding unit is a non-zero node obtained by dividing a bounding box of the point cloud by a preset number of times;

The sum of the first number of encoded points and the second number of encoded points is determined as the second parameter.
The method according to claim 40, characterized in that the determining the number of first encoded points corresponding to the i-th non-zero child node in the point cloud comprises:

Determine the number of third encoded points corresponding to the i-th non-zero child node;

Based on the third number of encoded points, the first number of encoded points is determined.
The method according to claim 43, characterized in that determining the number of third encoded points corresponding to the i-th non-zero child node comprises:

If the current node is the first non-zero node in the N-1th layer, determining the number of non-zero child nodes of the current node;

The third number of encoded points is determined based on the number of non-zero child nodes of the current node.
The method according to claim 43, characterized in that the determining the third number of encoded points based on the number of non-zero child nodes of the current node comprises:

If the i-th non-zero child node is the first non-zero child node of the current node, the number of non-zero child nodes included in the current node is reduced by 1 to determine the third number of encoded points.
The method according to claim 43, characterized in that the determining the third number of encoded points based on the number of non-zero child nodes of the current node comprises:

If the i-th non-zero child node is not the first non-zero child node of the current node, then obtaining the sum of the first number of repeated points included in the child nodes before the i-th non-zero child node among the non-zero child nodes of the current node;

The number of non-zero child nodes included in the current node is subtracted by 1, and then added to the sum of the first number of repeated points to obtain the third number of encoded points.
The method according to claim 43, characterized in that the determining the number of third encoded points corresponding to the i-th non-zero child node in the point cloud comprises:

If the current node is not the first non-zero node in the N-1th layer, determining the number of encoded points corresponding to each non-zero node in the N-1th layer before the current node;

Determine the number of non-zero child nodes of the current node;

The third number of encoded points is determined based on the number of encoded points corresponding to each non-zero node located before the current node in the N-1th layer and the number of non-zero child nodes of the current node.
The method according to claim 47, characterized in that the determining the number of encoded points corresponding to each non-zero node located before the current node in the N-1th layer comprises:

For any non-zero node among the non-zero nodes, obtain the number of non-zero child nodes of the non-zero node and the sum of the number of second repeated points included in the non-zero child nodes of the non-zero node;

The number of non-zero child nodes of the non-zero node is subtracted by 1, and then added to the sum of the second number of repeated points to obtain the number of encoded points corresponding to the non-zero node.
The method according to claim 47, characterized in that the determining the third number of coded points based on the number of coded points corresponding to each non-zero node located before the current node in the N-1th layer and the number of non-zero child nodes of the current node comprises:

Adding the numbers of encoded points corresponding to the non-zero nodes before the current node in the N-1th layer to obtain a first sum;

The third number of encoded points is determined based on the first sum value and the current number of non-zero child nodes.
The method according to claim 49, characterized in that the determining the third number of encoded points based on the first sum value and the number of non-zero child nodes of the current node comprises:

If the i-th non-zero child node is the first non-zero child node of the current node, then the first sum value is added to the number of non-zero child nodes included in the current node to obtain a second sum value;

Subtract 1 from the second sum to obtain the third number of encoded points.
The method according to claim 49, characterized in that the determining the number of third encoded points corresponding to the i-th non-zero child node based on the first sum value and the number of non-zero child nodes of the current node comprises:

If the i-th non-zero child node is not the first non-zero child node of the current node, then adding the first sum value to the number of non-zero child nodes included in the current node to obtain a second sum value;

Subtract 1 from the second sum to obtain a third sum;

Obtain the sum of the first number of repeated points included in the non-zero child nodes located before the i-th non-zero child node in the current node, and add the third sum value to the sum of the first number of repeated points to obtain the third number of encoded points.
The method according to claim 43, characterized in that if the point cloud does not adopt an inferred direct coding mode IDCM, then determining the first number of encoded points based on the third number of encoded points comprises:

The third number of encoded points is determined as the first number of encoded points.
The method according to claim 43, characterized in that if the point cloud adopts an inferred direct coding mode IDCM, then determining the first number of encoded points based on the third number of encoded points comprises:

Determine the number of points included in the second node of the octree using IDCM;

The sum of the number of encoded points corresponding to the i-th non-zero child node and the number of points included in the second node is determined as the first number of encoded points.
The method according to any one of claims 39 to 53, characterized in that the determining whether to encode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter comprises:

If the first parameter is equal to the second parameter, skip encoding the repeated point information of the i-th non-zero child node.
The method according to any one of claims 39 to 53, characterized in that the determining whether to encode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter comprises:

If the first parameter is greater than the second parameter, and the i-th non-zero child node is the last voxel node of the octree, skip encoding the repeated point information of the i-th non-zero child node, and determine the difference between the first parameter and the second parameter as the number of repeated points included in the i-th non-zero child node.
The method according to any one of claims 39 to 53, characterized in that the determining whether to encode the repeated point information of the i-th non-zero child node based on the first parameter and the second parameter comprises:

If the first parameter is greater than the second parameter, and the i-th non-zero child node is not the last voxel node of the octree, then the duplicate point information of the i-th non-zero child node is encoded.
The method according to claim 36, characterized in that the determining the first parameter corresponding to the current node comprises:

For the i-th non-zero child node in the current node, determine the total number of encoded repeated points corresponding to the i-th non-zero child node, where i is a positive integer;

The total number of encoded repeated points corresponding to the i-th non-zero child node is determined as the first parameter.
The method according to claim 57, characterized in that the determining the total number of encoded repeated points corresponding to the i-th non-zero child node comprises:

Determine the sum of the numbers of third encoded repeated points included in each non-zero child node located before the i-th non-zero child node in the octree;

Based on the sum of the third number of encoded repeated points, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined.
The method according to claim 58, characterized in that if the point cloud adopts a prediction tree encoding method, then determining the total number of encoded repeated points corresponding to the i-th non-zero child node based on the sum of the third number of encoded repeated points includes:

Determine the sum of the number of fourth encoded repeated points included in the first node of the octree using the prediction tree encoding method;

Based on the sum of the third number of encoded repeated points and the sum of the fourth number of encoded repeated points, the total number of encoded repeated points corresponding to the i-th non-zero child node is determined.
The method according to claim 59, characterized in that if the point cloud adopts the inferred direct coding mode IDCM, then based on the sum of the third number of encoded repeated points and the sum of the fourth number of encoded repeated points, determining the total number of encoded repeated points corresponding to the i-th non-zero child node comprises:

Determine the sum of the number of fifth coded repeated points included in the second node using IDCM in the octree;

The sum of the third number of encoded repeated points, the sum of the fourth number of encoded repeated points, and the sum of the fifth number of encoded repeated points are added to obtain the total number of encoded repeated points corresponding to the i-th non-zero child node.
The method according to any one of claims 57 to 60, characterized in that the step of geometrically encoding the current node based on the first parameter comprises:

Determining a total number of duplicate points of the point cloud;

Based on the total number of repeated points in the point cloud and the total number of encoded repeated points corresponding to the i-th non-zero child node, it is determined whether to encode the repeated point information of the i-th non-zero child node.
The method of claim 61, wherein determining the total number of duplicate points in the point cloud comprises:

Determine the total number of points in the point cloud and the total number of non-zero voxel nodes in the octree;

The difference between the total number of points of the point cloud and the total number of non-zero voxel nodes of the octree is determined as the total number of repeated points of the point cloud.
The method according to claim 61, characterized in that the determining whether to encode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of encoded duplicate points corresponding to the i-th non-zero child node comprises:

If the total number of encoded repeated points corresponding to the i-th non-zero child node is equal to the total number of repeated points in the point cloud, then the encoding of the repeated point information of the i-th non-zero child node is skipped.
The method according to claim 61, characterized in that the determining whether to encode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of encoded duplicate points corresponding to the i-th non-zero child node comprises:

If the total number of encoded repeated points corresponding to the i-th non-zero child node is less than the total number of repeated points of the point cloud, and the i-th non-zero child node is the last voxel node of the octree, then the encoding of the repeated point information of the i-th non-zero child node is skipped, and the difference between the total number of repeated points of the point cloud and the total number of encoded repeated points corresponding to the i-th non-zero child node is determined as the number of repeated points included in the i-th non-zero child node.
The method according to claim 61, characterized in that the determining whether to encode the duplicate point information of the i-th non-zero child node based on the total number of duplicate points in the point cloud and the total number of encoded duplicate points corresponding to the i-th non-zero child node comprises:

If the total number of encoded duplicate points corresponding to the i-th non-zero child node is less than the total number of duplicate points in the point cloud, and the i-th non-zero child node is not the last voxel node of the octree, the duplicate point information of the i-th non-zero child node is encoded.
The method according to any one of claims 36-53 is characterized in that the repeated point information includes the number of repeated points.
The method according to claim 37 or 62, characterized in that the method further comprises:

The total number of points of the point cloud is written into the geometric code stream of the point cloud.
The method according to claim 67, characterized in that writing the total number of points of the point cloud into the geometric code stream of the point cloud comprises:

The total number of points of the point cloud is written into the geometric unit header of the point cloud.
The method according to claim 68, characterized in that the step of writing the total number of points of the point cloud into a geometric unit header of the point cloud comprises:

Based on the total number of points in the point cloud, determine the low-order part of the points contained in the slice corresponding to the point cloud and the high-order part of the points contained in the slice;

The low-order part of the number of points contained in the slice and the high-order part of the number of points contained in the slice are written into the geometry unit header.
A point cloud decoding device, characterized by comprising:

a determining unit, configured to determine a first parameter corresponding to a current node, wherein the first parameter is used to determine whether at least one non-zero child node of the current node includes a duplicate point, wherein the current node is a non-zero node in the N-1th layer of the octree of the point cloud, wherein the octree is obtained by node division of the point cloud, and N is a total number of layers of the octree, and N is a positive integer greater than 1;

A decoding unit is used to perform geometric decoding on the current node based on the first parameter.
A point cloud encoding device, characterized in that it comprises:

a determining unit, configured to determine a first parameter corresponding to a current node, wherein the first parameter is used to determine whether at least one non-zero child node of the current node includes a duplicate point, wherein the current node is a non-zero node in the N-1th layer of the octree of the point cloud, wherein the octree is obtained by node division of the point cloud, and N is a total number of layers of the octree, and N is a positive integer greater than 1;

A coding unit, configured to perform geometric coding on the current node based on the first parameter.
An electronic device, characterized in that it comprises: a processor and a memory;

The memory is used to store computer programs;

The processor is used to call and run the computer program stored in the memory to execute the method according to any one of claims 1 to 35 or 36 to 69.
A computer-readable storage medium, characterized in that it is used to store a computer program, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 35 or 36 to 69.