WO2021002562A1 - Point cloud data transmission device, point cloud data transmission method, point cloud data reception device, and point cloud data reception method - Google Patents

Abstract

A point cloud data transmission method according to embodiments can comprise the steps of: encoding point cloud data; and/or transmitting a bitstream including the point cloud data. A point cloud data reception method according to embodiments can comprise the steps of: receiving a bitstream including point cloud data; decoding the point cloud data; and/or rendering the point cloud data.

Description

Point cloud data transmission device, point cloud data transmission method, point cloud data reception device, and point cloud data reception method

Embodiments provide Point Cloud content to provide users with various services such as VR (Virtual Reality, Virtual Reality), AR (Augmented Reality, Augmented Reality), MR (Mixed Reality, Mixed Reality), and autonomous driving service. Provide a solution.

A point cloud is a set of points in 3D space. There is a problem that it is difficult to generate point cloud data because the amount of points in 3D space is large.

Point cloud data may be divided into a tile or slice unit in order to meet the demand for transmission, encoding, decoding, and rendering processing in real time and low latency.

The technical problem according to the embodiments is to provide a point cloud data transmission apparatus, a transmission method, a point cloud data reception apparatus, and a reception method for efficiently transmitting and receiving point clouds in order to solve the above-described problems.

A technical problem according to embodiments is to provide a point cloud data transmission device, a transmission method, a point cloud data reception device and a reception method for solving latency and encoding/decoding complexity.

The technical problem according to the embodiments is to improve the compression performance of the point cloud by improving the encoding technology of attribute information of geometry-point cloud compression (G-PCC).

However, it is not limited only to the above-described technical problem, and the scope of the rights of the embodiments may be extended to other technical problems that can be inferred by those skilled in the art based on the entire contents of this document.

In order to achieve the technical problem, the point cloud data transmission method according to the embodiments may include encoding the point cloud data and/or transmitting a bitstream including the point cloud data.

Further, according to embodiments, the encoding may include encoding geometric information of the point cloud data and/or encoding attribute information of the point cloud data. In addition, the encoding may be performed in units of a slice or a tile including one or more slices.

Furthermore, according to embodiments, the bitstream may include a sequence parameter set for indicating a sequence of point cloud data. According to embodiments, the sequence parameter set includes first information indicating whether geometry information is encoded based on a plurality of types and second information indicating whether attribute information is encoded based on a plurality of types. Can include.

Additionally, according to embodiments, the encoding may be performed in units of slices, and the bitstream includes one or more slices including attribute information of the encoded point cloud data, and point clouds within the slices. It may further include a geometry parameter set and an attribute parameter set for indicating information about data. In addition, when the attribute information is encoded based on a plurality of types, the slice may include an attribute slice header including information related to a method of encoding the attribute information in the slice.

Furthermore, in the encoding step according to embodiments, encoding may be performed in units of tiles including one or more slices, and the bitstream may be applied to one or more tiles and point cloud data A tile parameter set for indicating related information may be further included.

Further, a tile according to embodiments may include one or more slices, a geometry parameter set and an attribute parameter set for indicating information about data in one or more slices, and the attribute parameter set is It may include information related to a method of encoding attribute information.

In addition, a tile may include one or more slices, and a slice may include a geometry parameter set and an attribute parameter set for indicating information about data in the slice, and the attribute parameter set encodes attribute information in the slice It may contain information related to how to do it.

In order to achieve the technical problem, the method of receiving point cloud data according to embodiments may include receiving a bitstream including point cloud data, decoding point cloud data, and/or rendering point cloud data. I can.

Further, according to embodiments, the bitstream may include a sequence parameter set including information on a sequence of point cloud data, and the sequence parameter set includes a plurality of types of geometry information of the point cloud data ( type) and second information indicating whether attribute information of the point cloud data is encoded based on a plurality of types. Further, the decoding may include decoding geometric information based on the first information and decoding attribute information based on the second information.

Furthermore, the bitstream may further include one or more tiles, and a tile parameter set including information on one or more tiles. In addition, the tile may further include a geometry parameter set and an attribute parameter set for indicating information about data in one or more slices and one or more slices. have. In addition, decoding the attribute information may decode point cloud data based on information on tiles included in the tile parameter set and information on slices included in the attribute parameter set.

A point cloud data transmission method, a transmission device, a point cloud data reception method, and a reception device according to the embodiments may provide a point cloud service with high quality.

The point cloud data transmission method, the transmission device, the point cloud data reception method, and the reception device according to the embodiments may achieve various video codec methods.

A point cloud data transmission method, a transmission device, a point cloud data reception method, and a reception device according to embodiments may provide general-purpose point cloud content such as an autonomous driving service.

A method and apparatus for transmitting and receiving point cloud data according to embodiments provides an effect of improving coding performance of a point cloud by performing a brick tiling splitting method and signaling data necessary for this.

The method and apparatus for transmitting and receiving point cloud data according to embodiments may provide improved parallel processing and scalability by performing spatial adaptive division for independent encoding and decoding of point cloud data.

The drawings are included to further understand the embodiments, and the drawings represent embodiments together with a description related to the embodiments. For a better understanding of the various embodiments described below, reference should be made to the description of the following embodiments with reference to the following drawings in which like reference numerals include corresponding parts throughout the following drawings.

1 shows an example of a point cloud content providing system according to embodiments.

2 is a block diagram illustrating an operation of providing point cloud content according to embodiments.

3 shows an example of a point cloud video capture process according to embodiments.

4 shows an example of a point cloud encoder according to embodiments.

5 shows an example of a voxel according to embodiments.

6 shows an example of an octree and an occupancy code according to embodiments.

7 shows an example of a neighbor node pattern according to embodiments.

8 shows an example of a point configuration for each LOD according to embodiments.

9 shows an example of a point configuration for each LOD according to embodiments.

10 shows an example of a point cloud decoder according to embodiments.

11 shows an example of a point cloud decoder according to embodiments.

12 is an example of a transmission device according to embodiments.

13 is an example of a reception device according to embodiments.

14 illustrates an architecture for G-PCC-based point cloud content streaming according to embodiments.

15 shows an example of a transmission device according to embodiments.

16 shows an example of a receiving device according to embodiments.

17 shows an example of a structure capable of interworking with a method/device for transmitting and receiving point cloud data according to embodiments.

18 shows a point cloud encoder according to embodiments.

19 illustrates an example of a bitstream structure of point cloud data according to embodiments.

20 illustrates a connection relationship between an example of a bitstream structure of point cloud data and a configuration within the bitstream according to embodiments.

21 illustrates a Sequence Parameter Set (SPS), a Tile Parameter Set (TPS), and a Geometry Parameter Set (GPS) according to embodiments.

22 shows an attribute parameter set (APS) according to embodiments.

23 illustrates a geometry slice header (GSH) and an attribute slice header (ASH) according to embodiments.

24 shows a point cloud encoder according to embodiments.

25 shows another embodiment of a sequence parameter set (SPS) according to the embodiments.

26 illustrates another embodiment of an APS (Attribute Parameter Set) according to the embodiments.

27 illustrates another embodiment of an ASH (Attribute Slice Header) according to the embodiments.

28 illustrates another example of a bitstream structure of point cloud data according to embodiments.

29 illustrates another example of a bitstream structure of point cloud data according to embodiments.

30 shows another embodiment of a sequence parameter set (SPS) according to the embodiments.

31 shows an embodiment of a Tile Parameter Set (TPS) according to the embodiments.

32 shows another embodiment of a GPS (Geometry Parameter Set) according to the embodiments.

33 illustrates another embodiment of an APS (Attribute Parameter Set) according to the embodiments.

34 illustrates another embodiment of a Geometry Slice Header (GSH) and an Attribute Slice Header (ASH) according to the embodiments.

35 shows a point cloud decoder 35000 according to embodiments.

36 shows a point cloud decoder according to embodiments.

37 shows a method of transmitting point cloud data according to embodiments.

38 illustrates a method of receiving point cloud data according to embodiments.

The preferred embodiments of the embodiments will be described in detail, examples of which are shown in the accompanying drawings. The detailed description below with reference to the accompanying drawings is intended to describe preferred embodiments of the embodiments, rather than showing only embodiments that can be implemented according to the embodiments of the embodiments. The following detailed description includes details to provide a thorough understanding of the embodiments. However, it is apparent to those skilled in the art that the embodiments may be practiced without these details.

Most terms used in the embodiments are selected from general ones widely used in the relevant field, but some terms are arbitrarily selected by the applicant, and their meanings will be described in detail in the following description as necessary. Accordingly, the embodiments should be understood based on the intended meaning of the term, not the simple name or meaning of the term.

1 shows an example of a point cloud content providing system according to embodiments.

The point cloud content providing system illustrated in FIG. 1 may include a transmission device 10000 and a reception device 10004. The transmission device 10000 and the reception device 10004 are capable of wired or wireless communication to transmit and receive point cloud data.

. The transmission device 10000 according to the embodiments may secure, process, and transmit point cloud video (or point cloud content). According to embodiments, the transmission device 10000 is a fixed station, a base transceiver system (BTS), a network, an artificial intelligence (AI) device and/or system, a robot, an AR/VR/XR device and/or server. And the like. In addition, according to embodiments, the transmission device 10000 uses a radio access technology (eg, 5G NR (New RAT), LTE (Long Term Evolution)) to communicate with a base station and/or other wireless devices, Robots, vehicles, AR/VR/XR devices, portable devices, home appliances, Internet of Thing (IoT) devices, AI devices/servers, etc. may be included.

The transmission device 10000 according to embodiments includes a point cloud video acquisition unit (Point Cloud Video Acquisition, 10001), a point cloud video encoder (Point Cloud Video Encoder, 10002) and/or a transmitter (Transmitter (or Communication module), 10003). Include)

The point cloud video acquisition unit 10001 according to the embodiments acquires a point cloud video through a process such as capture, synthesis, or generation. The point cloud video is point cloud content expressed as a point cloud, which is a set of points located in a three-dimensional space, and may be referred to as point cloud video data. A point cloud video according to embodiments may include one or more frames. One frame represents a still image/picture. Accordingly, the point cloud video may include a point cloud image/frame/picture, and may be referred to as any one of a point cloud image, a frame, and a picture.

The point cloud video encoder 10002 according to embodiments encodes the secured point cloud video data. The point cloud video encoder 10002 may encode point cloud video data based on Point Cloud Compression coding. Point cloud compression coding according to embodiments may include Geometry-based Point Cloud Compression (G-PCC) coding and/or Video based Point Cloud Compression (V-PCC) coding or next-generation coding. In addition, point cloud compression coding according to the embodiments is not limited to the above-described embodiments. The point cloud video encoder 10002 may output a bitstream including encoded point cloud video data. The bitstream may include not only the encoded point cloud video data, but also signaling information related to encoding of the point cloud video data.

The transmitter 10003 according to the embodiments transmits a bitstream including encoded point cloud video data. The bitstream according to the embodiments is encapsulated into a file or segment (for example, a streaming segment) and transmitted through various networks such as a broadcasting network and/or a broadband network. Although not shown in the drawing, the transmission device 10000 may include an encapsulation unit (or an encapsulation module) that performs an encapsulation operation. Also, according to embodiments, the encapsulation unit may be included in the transmitter 10003. According to embodiments, a file or segment may be transmitted to the receiving device 10004 through a network or stored in a digital storage medium (eg, USB, SD, CD, DVD, Blu-ray, HDD, SSD, etc.). The transmitter 10003 according to the embodiments may perform wired/wireless communication with the reception device 10004 (or a receiver 10005) through a network such as 4G, 5G, or 6G. In addition, the transmitter 10003 may perform necessary data processing operations according to a network system (for example, a communication network system such as 4G, 5G, or 6G). In addition, the transmission device 10000 may transmit encapsulated data according to an on demand method.

The reception device 10004 according to the embodiments includes a receiver 10005, a point cloud video decoder 10006, and/or a renderer 10007. According to embodiments, the receiving device 10004 uses a wireless access technology (eg, 5G NR (New RAT), LTE (Long Term Evolution)) to communicate with a base station and/or other wireless devices, a robot , Vehicles, AR/VR/XR devices, portable devices, home appliances, Internet of Thing (IoT) devices, AI devices/servers, and the like.

The receiver 10005 according to embodiments receives a bitstream including point cloud video data or a file/segment in which the bitstream is encapsulated from a network or a storage medium. The receiver 10005 may perform necessary data processing operations according to a network system (for example, a communication network system such as 4G, 5G, or 6G). The receiver 10005 according to the embodiments may decapsulate the received file/segment and output a bitstream. In addition, according to embodiments, the receiver 10005 may include a decapsulation unit (or a decapsulation module) for performing a decapsulation operation. In addition, the decapsulation unit may be implemented as an element (or component) separate from the receiver 10005.

The point cloud video decoder 10006 decodes a bitstream including point cloud video data. The point cloud video decoder 10006 may decode the point cloud video data according to the encoding method (for example, a reverse process of the operation of the point cloud video encoder 10002). Accordingly, the point cloud video decoder 10006 may decode the point cloud video data by performing point cloud decompression coding, which is a reverse process of the point cloud compression. Point cloud decompression coding includes G-PCC coding.

The renderer 10007 renders the decoded point cloud video data. The renderer 10007 may output point cloud content by rendering audio data as well as point cloud video data. According to embodiments, the renderer 10007 may include a display for displaying point cloud content. According to embodiments, the display is not included in the renderer 10007 and may be implemented as a separate device or component.

An arrow indicated by a dotted line in the drawing indicates a transmission path of feedback information acquired by the receiving device 10004. The feedback information is information for reflecting an interaction ratio with a user who consumes point cloud content, and includes user information (eg, head orientation information, viewport information, etc.). In particular, when the point cloud content is content for a service that requires interaction with a user (for example, an autonomous driving service, etc.), the feedback information is the content sending side (for example, the transmission device 10000) and/or a service provider. Can be delivered to According to embodiments, the feedback information may be used not only in the transmitting device 10000 but also in the receiving device 10004, and may not be provided.

Head orientation information according to embodiments is information on a position, direction, angle, and movement of a user's head. The receiving device 10004 according to the embodiments may calculate viewport information based on the head orientation information. The viewport information is information on the area of the point cloud video that the user is viewing. A viewpoint is a point at which the user is watching a point cloud video, and may mean a center point of a viewport area. That is, the viewport is an area centered on a viewpoint, and the size and shape of the area may be determined by a field of view (FOV). Accordingly, the receiving device 10004 may extract viewport information based on a vertical or horizontal FOV supported by the device in addition to the head orientation information. In addition, the receiving device 10004 performs a gaze analysis and the like to check the point cloud consumption method of the user, the point cloud video area that the user gazes, and the gaze time. According to embodiments, the receiving device 10004 may transmit feedback information including the result of gaze analysis to the transmitting device 10000. Feedback information according to embodiments may be obtained during rendering and/or display. Feedback information according to embodiments may be secured by one or more sensors included in the receiving device 10004. Also, according to embodiments, the feedback information may be secured by the renderer 10007 or a separate external element (or device, component, etc.). A dotted line in FIG. 1 shows a process of transmitting feedback information secured by the renderer 10007. The point cloud content providing system may process (encode/decode) point cloud data based on feedback information. Accordingly, the point cloud video data decoder 10006 may perform a decoding operation based on the feedback information. Also, the receiving device 10004 may transmit feedback information to the transmitting device 10000. The transmission device 10000 (or the point cloud video data encoder 10002) may perform an encoding operation based on feedback information. Therefore, the point cloud content providing system does not process (encode/decode) all point cloud data, but efficiently processes necessary data (e.g., point cloud data corresponding to the user's head position) based on feedback information. Point cloud content can be provided to users.

According to embodiments, the transmission device 10000 may be referred to as an encoder, a transmission device, a transmitter, and the like, and the reception device 10004 may be referred to as a decoder, a reception device, a receiver, or the like.

Point cloud data (processed in a series of acquisition/encoding/transmission/decoding/rendering) processed in the point cloud content providing system of FIG. 1 according to embodiments may be referred to as point cloud content data or point cloud video data. I can. According to embodiments, the point cloud content data may be used as a concept including metadata or signaling information related to the point cloud data.

Elements of the point cloud content providing system shown in FIG. 1 may be implemented by hardware, software, processor, and/or a combination thereof.

2 is a block diagram illustrating an operation of providing point cloud content according to embodiments.

The block diagram of FIG. 2 shows the operation of the point cloud content providing system described in FIG. 1. As described above, the point cloud content providing system may process point cloud data based on point cloud compression coding (eg, G-PCC).

A point cloud content providing system according to embodiments (for example, the point cloud transmission apparatus 10000 or the point cloud video acquisition unit 10001) may acquire a point cloud video (20000). The point cloud video is expressed as a point cloud belonging to a coordinate system representing a three-dimensional space. A point cloud video according to embodiments may include a Ply (Polygon File format or the Stanford Triangle format) file. When the point cloud video has one or more frames, the acquired point cloud video may include one or more Ply files. Ply files contain point cloud data such as the geometry and/or attributes of the point. The geometry includes the positions of the points. The position of each point may be expressed by parameters (eg, values of each of the X-axis, Y-axis, and Z-axis) representing a three-dimensional coordinate system (eg, a coordinate system composed of XYZ axes). Attributes include attributes of points (eg, texture information of each point, color (YCbCr or RGB), reflectance (r), transparency, etc.). A point has one or more attributes (or attributes). For example, one point may have an attribute of one color, or two attributes of a color and reflectance. Depending on embodiments, geometry may be referred to as positions, geometry information, geometry data, and the like, and attributes may be referred to as attributes, attribute information, attribute data, and the like. In addition, the point cloud content providing system (for example, the point cloud transmission device 10000 or the point cloud video acquisition unit 10001) provides points from information related to the acquisition process of the point cloud video (eg, depth information, color information, etc.). Cloud data can be secured.

The point cloud content providing system (for example, the transmission device 10000 or the point cloud video encoder 10002) according to the embodiments may encode point cloud data (20001). The point cloud content providing system may encode point cloud data based on point cloud compression coding. As described above, the point cloud data may include the geometry and attributes of the point. Accordingly, the point cloud content providing system may output a geometry bitstream by performing geometry encoding for encoding geometry. The point cloud content providing system may output an attribute bitstream by performing attribute encoding for encoding the attribute. According to embodiments, the point cloud content providing system may perform attribute encoding based on geometry encoding. The geometry bitstream and the attribute bitstream according to the embodiments may be multiplexed and output as one bitstream. The bitstream according to embodiments may further include signaling information related to geometry encoding and attribute encoding.

The point cloud content providing system according to embodiments (for example, the transmission device 10000 or the transmitter 10003) may transmit encoded point cloud data (20002). As described in FIG. 1, the encoded point cloud data may be expressed as a geometry bitstream and an attribute bitstream. In addition, the encoded point cloud data may be transmitted in the form of a bitstream together with signaling information related to encoding of the point cloud data (eg, signaling information related to geometry encoding and attribute encoding). In addition, the point cloud content providing system may encapsulate the bitstream for transmitting the encoded point cloud data and transmit it in the form of a file or segment.

The point cloud content providing system according to the embodiments (for example, the receiving device 10004 or the receiver 10005) may receive a bitstream including encoded point cloud data. In addition, the point cloud content providing system (for example, the receiving device 10004 or the receiver 10005) may demultiplex the bitstream.

The point cloud content providing system (e.g., the receiving device 10004 or the point cloud video decoder 10005) can decode the encoded point cloud data (e.g., geometry bitstream, attribute bitstream) transmitted as a bitstream. have. The point cloud content providing system (for example, the receiving device 10004 or the point cloud video decoder 10005) can decode the point cloud video data based on signaling information related to encoding of the point cloud video data included in the bitstream. have. The point cloud content providing system (for example, the receiving device 10004 or the point cloud video decoder 10005) may restore positions (geometry) of points by decoding a geometry bitstream. The point cloud content providing system may restore the attributes of points by decoding an attribute bitstream based on the restored geometry. The point cloud content providing system (for example, the receiving device 10004 or the point cloud video decoder 10005) may restore the point cloud video based on the decoded attributes and positions according to the restored geometry.

The point cloud content providing system according to the embodiments (for example, the receiving device 10004 or the renderer 10007) may render the decoded point cloud data (20004 ). The point cloud content providing system (for example, the receiving device 10004 or the renderer 10007) may render geometry and attributes decoded through a decoding process according to a rendering method according to various rendering methods. Points of the point cloud content may be rendered as a vertex having a certain thickness, a cube having a specific minimum size centered on the vertex position, or a circle centered on the vertex position. All or part of the rendered point cloud content is provided to the user through a display (eg VR/AR display, general display, etc.).

The point cloud content providing system according to the embodiments (for example, the receiving device 10004) may secure feedback information (20005). The point cloud content providing system may encode and/or decode point cloud data based on feedback information. Since the operation of the feedback information and point cloud content providing system according to the embodiments is the same as the feedback information and operation described in FIG. 1, a detailed description will be omitted.

3 shows an example of a point cloud video capture process according to embodiments.

3 shows an example of a point cloud video capture process in the point cloud content providing system described in FIGS. 1 to 2.

The point cloud content is an object located in various three-dimensional spaces (for example, a three-dimensional space representing a real environment, a three-dimensional space representing a virtual environment, etc.) and/or a point cloud video (images and/or Videos). Therefore, the point cloud content providing system according to the embodiments includes one or more cameras (eg, an infrared camera capable of securing depth information, color information corresponding to the depth information) to generate the point cloud content. You can capture a point cloud video using an RGB camera that can extract the image), a projector (for example, an infrared pattern projector to secure depth information), and LiDAR. The point cloud content providing system according to the embodiments may obtain point cloud data by extracting a shape of a geometry composed of points in a 3D space from depth information, and extracting an attribute of each point from color information. An image and/or an image according to the embodiments may be captured based on at least one or more of an inward-facing method and an outward-facing method.

The left side of Fig. 3 shows an inword-facing scheme. The inword-facing method refers to a method in which one or more cameras (or camera sensors) located surrounding a central object capture a central object. The in-word-facing method provides point cloud content that provides users with 360-degree images of key objects (e.g., provides users with 360-degree images of objects (eg, key objects such as characters, players, objects, actors, etc.) VR/AR content).

The right side of Fig. 3 shows the outword-pacing scheme. The outward-facing method refers to a method in which one or more cameras (or camera sensors) located surrounding the central object capture the environment of the central object other than the central object. The outward-pacing method may be used to generate point cloud content (for example, content representing an external environment that may be provided to a user of a self-driving vehicle) to provide an environment that appears from a user's point of view.

As shown in the figure, the point cloud content may be generated based on the capture operation of one or more cameras. In this case, since the coordinate system of each camera may be different, the point cloud content providing system may calibrate one or more cameras to set a global coordinate system before the capture operation. In addition, the point cloud content providing system may generate point cloud content by synthesizing an image and/or image captured by the above-described capture method with an arbitrary image and/or image. In addition, the point cloud content providing system may not perform the capture operation described in FIG. 3 when generating point cloud content representing a virtual space. The point cloud content providing system according to embodiments may perform post-processing on the captured image and/or image. In other words, the point cloud content providing system removes an unwanted area (e.g., background), recognizes the space where captured images and/or images are connected, and performs an operation to fill in a spatial hole if there is. I can.

In addition, the point cloud content providing system may generate one point cloud content by performing coordinate system transformation on points of the point cloud video acquired from each camera. The point cloud content providing system may perform a coordinate system transformation of points based on the position coordinates of each camera. Accordingly, the point cloud content providing system may generate content representing a wide range, or may generate point cloud content having a high density of points.

4 shows an example of a point cloud encoder according to embodiments.

4 shows an example of the point cloud video encoder 10002 of FIG. 1. The point cloud encoder uses point cloud data (for example, positions and/or positions of points) to adjust the quality of the point cloud content (for example, lossless-lossless, loss-lossy, near-lossless) according to network conditions or applications. Attributes) and perform an encoding operation. When the total size of the point cloud content is large (for example, a point cloud content of 60 Gbps in the case of 30 fps), the point cloud content providing system may not be able to stream the content in real time. Therefore, the point cloud content providing system can reconstruct the point cloud content based on the maximum target bitrate in order to provide it according to the network environment.

As described in FIGS. 1 to 2, the point cloud encoder may perform geometry encoding and attribute encoding. Geometry encoding is performed before attribute encoding.

Point cloud encoders according to embodiments include a coordinate system transform unit (Transformation Coordinates, 40000), a quantization unit (Quantize and Remove Points (Voxelize), 40001), an octree analysis unit (Analyze Octree, 40002), and a surface aproximation analysis unit ( Analyze Surface Approximation, 40003), Arithmetic Encode (40004), Reconstruct Geometry (40005), Transform Colors (40006), Transfer Attributes (40007), RAHT Transformation A unit 40008, an LOD generation unit (Generated LOD) 40009, a lifting transform unit (Lifting) 40010, a coefficient quantization unit (Quantize Coefficients, 40011), and/or an Arithmetic Encode (40012).

The coordinate system transform unit 40000, the quantization unit 40001, the octree analysis unit 40002, the surface aproximation analysis unit 40003, the arithmetic encoder 40004, and the geometry reconstruction unit 40005 perform geometry encoding. can do. Geometry encoding according to embodiments may include octree geometry coding, direct coding, trisoup geometry encoding, and entropy encoding. Direct coding and trisoup geometry encoding are applied selectively or in combination. Also, geometry encoding is not limited to the above example.

As shown in the drawing, the coordinate system conversion unit 40000 according to the embodiments receives positions and converts them into a coordinate system. For example, positions may be converted into position information in a three-dimensional space (eg, a three-dimensional space represented by an XYZ coordinate system). The location information of the 3D space according to embodiments may be referred to as geometry information.

The quantization unit 40001 according to embodiments quantizes geometry. For example, the quantization unit 40001 may quantize points based on the minimum position values of all points (eg, minimum values on each axis with respect to the X-axis, Y-axis, and Z-axis). The quantization unit 40001 multiplies the difference between the minimum position value and the position value of each point by a preset quantum scale value, and then performs a quantization operation to find the nearest integer value by performing a rounding or a rounding. Thus, one or more points may have the same quantized position (or position value). The quantization unit 40001 according to embodiments performs voxelization based on the quantized positions to reconstruct the quantized points. The minimum unit including the 2D image/video information is a pixel, and points of the point cloud content (or 3D point cloud video) according to the embodiments may be included in one or more voxels. have. Voxel is a combination of volume and pixel, and the three-dimensional space is a unit (unit=1.0) based on the axes representing the three-dimensional space (for example, X-axis, Y-axis, Z-axis). It refers to a three-dimensional cubic space that occurs when divided by. The quantization unit 40001 may match groups of points in a 3D space with voxels. According to embodiments, one voxel may include only one point. According to embodiments, one voxel may include one or more points. In addition, in order to express one voxel as one point, a position of a center point (ceter) of a corresponding voxel may be set based on positions of one or more points included in one voxel. In this case, attributes of all positions included in one voxel may be combined and assigned to a corresponding voxel.

The octree analysis unit 40002 according to the embodiments performs octree geometry coding (or octree coding) to represent voxels in an octree structure. The octree structure represents points matched to voxels based on an octal tree structure.

The surface aproxiation analysis unit 40003 according to the embodiments may analyze and approximate the octree. The octree analysis and approximation according to the embodiments is a process of analyzing to voxelize a region including a plurality of points in order to efficiently provide octree and voxelization.

The arithmetic encoder 40004 according to embodiments entropy encodes the octree and/or the approximated octree. For example, the encoding method includes an Arithmetic encoding method. As a result of encoding, a geometry bitstream is generated.

Color conversion unit 40006, attribute conversion unit 40007, RAHT conversion unit 40008, LOD generation unit 40009, lifting conversion unit 40010, coefficient quantization unit 40011 and/or Arismatic encoder 40012 Performs attribute encoding. As described above, one point may have one or more attributes. Attribute encoding according to embodiments is applied equally to attributes of one point. However, when one attribute (eg, color) includes one or more elements, independent attribute encoding is applied to each element. Attribute encoding according to embodiments includes color transform coding, attribute transform coding, Region Adaptive Hierarchial Transform (RAHT) coding, Interpolaration-based hierarchical nearest-neighbor prediction-Prediction Transform coding, and interpolation-based hierarchical nearest -Neighbor prediction with an update/lifting step (Lifting Transform)) coding may be included. Depending on the point cloud content, the aforementioned RAHT coding, predictive transform coding, and lifting transform coding may be selectively used, or a combination of one or more codings may be used. In addition, attribute encoding according to embodiments is not limited to the above-described example.

The color conversion unit 40006 according to embodiments performs color conversion coding for converting color values (or textures) included in attributes. For example, the color conversion unit 40006 may convert the format of color information (eg, convert from RGB to YCbCr). The operation of the color conversion unit 40006 according to the embodiments may be selectively applied according to color values included in attributes.

The geometry reconstruction unit 40005 according to embodiments reconstructs (decompresses) an octree and/or an approximated octree. The geometry reconstruction unit 40005 reconstructs an octree/voxel based on a result of analyzing the distribution of points. The reconstructed octree/voxel may be referred to as reconstructed geometry (or reconstructed geometry).

The attribute conversion unit 40007 according to the embodiments performs attribute conversion for converting attributes based on the reconstructed geometry and/or positions for which geometry encoding has not been performed. As described above, since attributes are dependent on geometry, the attribute conversion unit 40007 may transform the attributes based on the reconstructed geometry information. For example, the attribute conversion unit 40007 may convert an attribute of the point of the position based on the position value of the point included in the voxel. As described above, when a position of a center point of a corresponding voxel is set based on positions of one or more points included in one voxel, the attribute conversion unit 40007 converts attributes of one or more points. When tri-soup geometry encoding is performed, the attribute conversion unit 40007 may convert attributes based on trisoup geometry encoding.

The attribute conversion unit 40007 is an average value of attributes or attribute values (for example, the color of each point or reflectance) of points neighboring within a specific position/radius from the position (or position value) of the center point of each voxel. Attribute conversion can be performed by calculating. The attribute conversion unit 40007 may apply a weight according to a distance from a central point to each point when calculating an average value. Thus, each voxel has a position and a calculated attribute (or attribute value).

The attribute conversion unit 40007 may search for neighboring points existing within a specific position/radius from the position of the center point of each voxel based on a K-D tree or a Molton code. The K-D tree is a binary search tree and supports a data structure that can manage points based on location so that the Nearest Neighbor Search (NNS) can be quickly performed. The Molton code represents a coordinate value (for example, (x, y, z)) representing a three-dimensional position of all points as a bit value, and is generated by mixing the bits. For example, if the coordinate value indicating the position of the point is (5, 9, 1), the bit value of the coordinate value is (0101, 1001, 0001). If the bit values are mixed according to the bit index in the order of z, y, x, it is 010001000111. If this value is expressed as a decimal number, it becomes 1095. That is, the Molton code value of the point whose coordinate value is (5, 9, 1) is 1095. The attribute conversion unit 40007 may sort points based on a Morton code value and perform a shortest neighbor search (NNS) through a depth-first traversal process. After the attribute transformation operation, when the shortest neighbor search (NNS) is required in another transformation process for attribute coding, a K-D tree or a Molton code is used.

As shown in the figure, the converted attributes are input to the RAHT conversion unit 40008 and/or the LOD generation unit 40009.

The RAHT conversion unit 40008 according to embodiments performs RAHT coding for predicting attribute information based on the reconstructed geometry information. For example, the RAHT conversion unit 40008 may predict attribute information of a node at a higher level of the octree based on attribute information associated with a node at a lower level of the octree.

The LOD generation unit 40009 according to embodiments generates a level of detail (LOD) to perform predictive transform coding. The LOD according to the embodiments is a degree representing the detail of the point cloud content, and a smaller LOD value indicates that the detail of the point cloud content decreases, and a larger LOD value indicates that the detail of the point cloud content is high. Points can be classified according to LOD.

The lifting transform unit 40010 according to embodiments performs lifting transform coding that transforms attributes of a point cloud based on weights. As described above, the lifting transform coding can be selectively applied.

The coefficient quantization unit 40011 according to embodiments quantizes attribute-coded attributes based on coefficients.

Arismatic encoder 40012 according to embodiments encodes quantized attributes based on Arismatic coding.

The elements of the point cloud encoder of FIG. 4 are not shown in the drawing, but hardware including one or more processors or integrated circuits configured to communicate with one or more memories included in the point cloud providing apparatus. , Software, firmware, or a combination thereof. One or more processors may perform at least one or more of the operations and/or functions of the elements of the point cloud encoder of FIG. 4 described above. Further, one or more processors may operate or execute a set of software programs and/or instructions for performing operations and/or functions of the elements of the point cloud encoder of FIG. 4. One or more memories according to embodiments may include high speed random access memory, and nonvolatile memory (e.g., one or more magnetic disk storage devices, flash memory devices, or other nonvolatile solid state Memory devices (solid-state memory devices, etc.).

5 shows an example of a voxel according to embodiments.

5 shows voxels located in a three-dimensional space represented by a coordinate system composed of three axes of the X-axis, Y-axis, and Z-axis. As described with reference to FIG. 4, a point cloud encoder (eg, quantization unit 40001) may perform voxelization. The voxel refers to a three-dimensional cubic space generated when a three-dimensional space is divided into units (unit = 1.0) based on axes (eg, X-axis, Y-axis, and Z-axis) representing the three-dimensional space. FIG. 5 is an octree structure recursively subdividing a cubical axis-aligned bounding box defined by two poles (0,0,0) and (2 ^d , 2 ^d , 2 ^d ) Shows an example of a voxel generated through. One voxel includes at least one or more points. The voxel can estimate spatial coordinates from the positional relationship with the voxel group. As described above, voxels have attributes (color or reflectance, etc.) like pixels of a 2D image/video. A detailed description of the voxel is the same as that described with reference to FIG. 4 and thus is omitted.

6 shows an example of an octree and an occupancy code according to embodiments.

As described in FIGS. 1 to 4, a point cloud content providing system (point cloud video encoder 10002) or a point cloud encoder (for example, octree analysis unit 40002) efficiently manages the area and/or position of the voxel. To do this, octree geometry coding (or octree coding) based on an octree structure is performed.

The upper part of FIG. 6 shows an octree structure. The three-dimensional space of the point cloud content according to the embodiments is represented by axes of a coordinate system (eg, X-axis, Y-axis, Z-axis). The octree structure is created by recursive subdividing of a cubical axis-aligned bounding box defined by two poles (0,0,0) and (2 ^d , 2 ^d , 2 ^d ). . 2d may be set to a value constituting the smallest bounding box surrounding all points of the point cloud content (or point cloud video). d represents the depth of the octree. The d value is determined according to the following equation. In the following equation, (x ^int _n , y ^int _n , z ^int _n ) represents positions (or position values) of quantized points.

As shown in the middle of the upper portion of FIG. 6, the entire 3D space may be divided into eight spaces according to the division. Each divided space is represented by a cube with 6 faces. As shown on the right side of the upper part of FIG. 6, each of the eight spaces is divided again based on the axes of the coordinate system (eg, X axis, Y axis, Z axis). Thus, each space is further divided into eight smaller spaces. The divided small space is also represented as a cube with 6 faces. This division method is applied until a leaf node of an octree becomes a voxel.

The lower part of FIG. 6 shows the octree ocupancy code. The octree's ocupancy code is generated to indicate whether each of the eight divided spaces generated by dividing one space includes at least one point. Therefore, one Okufanshi code is represented by 8 child nodes. Each child node represents the occupancy of the divided space, and the child node has a value of 1 bit. Therefore, the Ocufanshi code is expressed as an 8-bit code. That is, if at least one point is included in the space corresponding to the child node, the node has a value of 1. If the point is not included in the space corresponding to the child node (empty), the node has a value of 0. Since the ocupancy code shown in FIG. 6 is 00100001, it indicates that the spaces corresponding to the 3rd child node and the 8th child node among 8 child nodes each include at least one point. As shown in the figure, the 3rd child node and the 8th child node each have 8 child nodes, and each child node is represented by an 8-bit ocupancy code. The drawing shows that the occupancy code of the third child node is 10000111, and the ocupancy code of the eighth child node is 01001111. The point cloud encoder (for example, the Arismatic encoder 40004) according to embodiments may entropy encode an ocupancy code. In addition, in order to increase the compression efficiency, the point cloud encoder can intra/inter code the ocupancy code. The reception device (for example, the reception device 10004 or the point cloud video decoder 10006) according to the embodiments reconstructs an octree based on an ocupancy code.

A point cloud encoder according to embodiments (for example, the point cloud encoder of FIG. 4 or the octree analyzer 40002) may perform voxelization and octree coding to store positions of points. However, since points in the 3D space are not always evenly distributed, there may be a specific area where there are not many points. Therefore, it is inefficient to perform voxelization over the entire 3D space. For example, if there are almost no points in a specific area, it is not necessary to perform voxelization to the corresponding area.

Therefore, the point cloud encoder according to the embodiments does not perform voxelization for the above-described specific region (or nodes other than the leaf nodes of the octree), but directly codes the positions of points included in the specific region. ) Can be performed. Coordinates of a direct coding point according to embodiments are referred to as a direct coding mode (DCM). In addition, the point cloud encoder according to embodiments may perform trisoup geometry encoding in which positions of points within a specific region (or node) are reconstructed based on voxels based on a surface model. Trisoup geometry encoding is a geometry encoding that expresses the representation of an object as a series of triangle meshes. Therefore, the point cloud decoder can generate a point cloud from the mesh surface. Direct coding and trisoup geometry encoding according to embodiments may be selectively performed. In addition, direct coding and trisoup geometry encoding according to embodiments may be performed in combination with octree geometry coding (or octree coding).

In order to perform direct coding, the option to use direct mode to apply direct coding must be activated, and the node to which direct coding is applied is not a leaf node, but below the threshold within a specific node. There must be points of. In addition, the number of all points subject to direct coding must not exceed a preset limit. When the above condition is satisfied, the point cloud encoder (or the arithmetic encoder 40004) according to the embodiments may entropy-code the positions (or position values) of the points.

The point cloud encoder according to the embodiments (for example, the surface aproximation analysis unit 40003) determines a specific level of the octree (if the level is less than the depth d of the octree), and from that level, the node Trisoup geometry encoding that reconstructs the position of a point in the region based on voxels can be performed (tri-soup mode). A point cloud encoder according to embodiments may designate a level to which trisoup geometry encoding is applied. For example, if the specified level is equal to the depth of the octree, the point cloud encoder does not operate in the try-soup mode. That is, the point cloud encoder according to the embodiments may operate in the try-soup mode only when the specified level is less than the depth value of the octree. A three-dimensional cube area of nodes of a designated level according to the embodiments is referred to as a block. One block may include one or more voxels. The block or voxel may correspond to a brick. Within each block, the geometry is represented by a surface. The surface according to embodiments may intersect each edge (edge) of the block at most once.

Since one block has 12 edges, there are at least 12 intersection points within one block. Each intersection is called a vertex (vertex, or vertex). A vertex existing along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge. An occupied voxel according to embodiments refers to a voxel including a point. The position of the vertex detected along the edge is the average position along the edge of all voxels among all blocks sharing the edge.

When a vertex is detected, the point cloud encoder according to the embodiments entropycodes the starting point (x, y, z) of the edge, the direction vector of the edge (Δx, Δy, Δz), and vertex position values (relative position values within the edge). I can. When trisoup geometry encoding is applied, the point cloud encoder (e.g., the geometry reconstruction unit 40005) according to embodiments performs a triangle reconstruction, up-sampling, and voxelization process. By doing so, you can create reconstructed geometry (reconstructed geometry).

The vertices located at the edge of the block determine the surface that passes through the block. The surface according to the embodiments is a non-planar polygon. The triangle reconstruction process reconstructs the surface represented by a triangle based on the starting point of the edge, the direction vector of the edge, and the position value of the vertex. The triangle reconstruction process is as follows. ① Calculate the centroid value of each vertex, ② calculate the squared values of the values subtracted from each vertex value by subtracting the center value, and calculate the sum of all the values.

Calculate the minimum value of the added value, and perform a projection process along the axis with the minimum value. For example, if the x element is the minimum, each vertex is projected on the x-axis based on the center of the block, and projected on the (y, z) plane. If the projected value on the (y, z) plane is (ai, bi), θ is obtained through atan2(bi, ai), and vertices are aligned based on the θ value. The table below shows a combination of vertices for generating a triangle according to the number of vertices. Vertices are ordered from 1 to n. The table below shows that for four vertices, two triangles may be formed according to a combination of vertices. The first triangle may be composed of 1st, 2nd, and 3rd vertices among the aligned vertices, and the second triangle may be composed of 3rd, 4th, and 1st vertices among the aligned vertices. .

table. Triangles formed from vertices ordered 1,...,n

n	Triangles
3	(1,2,3)
4	(1,2,3), (3,4,1)
5	(1,2,3), (3,4,5), (5,1,3)
6	(1,2,3), (3,4,5), (5,6,1), (1,3,5)
7	(1,2,3), (3,4,5), (5,6,7), (7,1,3), (3,5,7)
8	(1,2,3), (3,4,5), (5,6,7), (7,8,1), (1,3,5), (5,7,1)
9	(1,2,3), (3,4,5), (5,6,7), (7,8,9), (9,1,3), (3,5,7), (7 ,9,3)
10	(1,2,3), (3,4,5), (5,6,7), (7,8,9), (9,10,1), (1,3,5), (5 ,7,9), (9,1,5)
11	(1,2,3), (3,4,5), (5,6,7), (7,8,9), (9,10,11), (11,1,3), (3 ,5,7), (7,9,11), (11,3,7)
12	(1,2,3), (3,4,5), (5,6,7), (7,8,9), (9,10,11), (11,12,1), (1 ,3,5), (5,7,9), (9,11,1), (1,5,9)

The upsampling process is performed to voxelize by adding points in the middle along the edge of the triangle. Additional points are created based on the upsampling factor and the width of the block. The additional point is called a refined vertice. The point cloud encoder according to embodiments may voxelize refined vertices. In addition, the point cloud encoder may perform attribute encoding based on the voxelized position (or position value).

7 shows an example of a neighbor node pattern according to embodiments.

In order to increase the compression efficiency of the point cloud video, the point cloud encoder according to the embodiments may perform entropy coding based on context adaptive arithmetic coding.

As described in FIGS. 1 to 6, a point cloud content providing system or a point cloud encoder (for example, a point cloud video encoder 10002, a point cloud encoder or an Arismatic encoder 40004 of FIG. 4) directly converts the Ocufanshi code. Entropy coding is possible. In addition, the point cloud content providing system or point cloud encoder performs entropy encoding (intra encoding) based on the ocupancy code of the current node and the ocupancy of neighboring nodes, or entropy encoding (inter encoding) based on the ocupancy code of the previous frame. ) Can be performed. A frame according to embodiments means a set of point cloud videos generated at the same time. The compression efficiency of intra-encoding/inter-encoding according to embodiments may vary depending on the number of referenced neighbor nodes. The larger the bit, the more complicated it is, but it can be skewed to one side, increasing compression efficiency. For example, if you have a 3-bit context, you have to code in 8 ways. The divided coding part affects the complexity of the implementation. Therefore, it is necessary to match the appropriate level of compression efficiency and complexity.

7 shows a process of obtaining an ocupancy pattern based on the ocupancy of neighboring nodes. A point cloud encoder according to embodiments determines occupancy of neighboring nodes of each node of an octree and obtains a value of a neighbor pattern. The neighboring node pattern is used to infer the occupancy pattern of the corresponding node. The left side of FIG. 7 shows a cube corresponding to a node (centered cube) and six cubes (neighbor nodes) that share at least one surface with the cube. Nodes shown in the figure are nodes of the same depth (depth). Numbers shown in the figure indicate weights (1, 2, 4, 8, 16, 32, etc.) associated with each of the six nodes. Each weight is sequentially assigned according to the positions of neighboring nodes.

The right side of FIG. 7 shows neighboring node pattern values. The neighbor node pattern value is the sum of values multiplied by weights of the occupied neighbor nodes (neighbor nodes having points). Therefore, the neighbor node pattern value has a value from 0 to 63. When the neighbor node pattern value is 0, it indicates that no node (occupied node) has a point among neighboring nodes of the corresponding node. If the neighboring node pattern value is 63, it indicates that all neighboring nodes are occupied nodes. As shown in the figure, since neighboring nodes to which weights 1, 2, 4, and 8 are assigned are occupied nodes, the neighboring node pattern value is 15, which is the sum of 1, 2, 4, and 8. The point cloud encoder may perform coding according to the neighboring node pattern value (for example, if the neighboring node pattern value is 63, 64 codings are performed). According to embodiments, the point cloud encoder may reduce coding complexity by changing a neighbor node pattern value (for example, based on a table changing 64 to 10 or 6).

8 shows an example of a point configuration for each LOD according to embodiments.

As described with reference to FIGS. 1 through 7, the encoded geometry is reconstructed (decompressed) before attribute encoding is performed. When direct coding is applied, the geometry reconstruction operation may include changing the placement of the direct coded points (eg, placing the direct coded points in front of the point cloud data). When trisoup geometry encoding is applied, the geometry reconstruction process is triangular reconstruction, upsampling, voxelization, and the attribute is dependent on geometry, so the attribute encoding is performed based on the reconstructed geometry.

The point cloud encoder (for example, the LOD generator 40009) may reorganize points for each LOD. The figure shows point cloud content corresponding to the LOD. The left side of the figure shows the original point cloud content. The second figure from the left of the figure shows the distribution of the lowest LOD points, and the rightmost figure in the figure shows the distribution of the highest LOD points. That is, the points of the lowest LOD are sparsely distributed, and the points of the highest LOD are densely distributed. That is, as the LOD increases according to the direction of the arrow indicated at the bottom of the drawing, the spacing (or distance) between points becomes shorter.

9 shows an example of a point configuration for each LOD according to embodiments.

As described in FIGS. 1 to 8, a point cloud content providing system or a point cloud encoder (for example, a point cloud video encoder 10002, a point cloud encoder in FIG. 4, or an LOD generator 40009) generates an LOD. can do. The LOD is generated by reorganizing the points into a set of refinement levels according to a set LOD distance value (or a set of Euclidean distance). The LOD generation process is performed not only in the point cloud encoder but also in the point cloud decoder.

The upper part of FIG. 9 shows examples (P0 to P9) of points of point cloud content distributed in a three-dimensional space. The original order of FIG. 9 represents the order of points P0 to P9 before LOD generation. The LOD based order of FIG. 9 represents the order of points according to LOD generation. Points are rearranged by LOD. Also, the high LOD includes points belonging to the low LOD. As shown in FIG. 9, LOD0 includes P0, P5, P4 and P2. LOD1 includes the points of LOD0 and P1, P6 and P3. LOD2 includes points of LOD0, points of LOD1 and P9, P8 and P7.

As described with reference to FIG. 4, the point cloud encoder according to embodiments may selectively or combine predictive transform coding, lifting transform coding, and RAHT transform coding.

The point cloud encoder according to embodiments may generate a predictor for points and perform predictive transform coding to set a predicted attribute (or predicted attribute value) of each point. That is, N predictors may be generated for N points. The predictor according to the embodiments may calculate a weight (=1/distance) value based on the LOD value of each point, indexing information about neighboring points existing within the distance set for each LOD, and the distance value to the neighboring points. I can.

The predicted attribute (or attribute value) according to the embodiments is a weight calculated based on the distance to each neighboring point to the attributes (or attribute values, for example, color, reflectance, etc.) of neighboring points set in the predictor of each point. It is set as the average value multiplied by (or weight value). A point cloud encoder according to embodiments (e.g., the coefficient quantization unit 40011) subtracts a predicted attribute (attribute value) from an attribute (attribute value) of each point, residuals (residuals, residual attributes, residual attribute values, attributes) It can be called a prediction residual value, etc.) can be quantized and inverse quantized The quantization process is as shown in the following table.

Attribute prediction residuals quantization pseudo code

int PCCQuantization(int value, int quantStep) {

if( value >= 0) {

return floor(value / quantStep + 1.0 / 3.0);

} else {

return -floor(-value / quantStep + 1.0 / 3.0);

}

}

Attribute prediction residuals inverse quantization pseudo code

int PCCInverseQuantization(int value, int quantStep) {

if( quantStep ==0) {

return value;

} else {

return value * quantStep;

}

}

The point cloud encoder (for example, the arithmetic encoder 40012) according to the embodiments may entropy-code the quantized and dequantized residual values as described above when there are points adjacent to the predictors of each point. The point cloud encoder according to embodiments (for example, the arithmetic encoder 40012) may entropy-code attributes of the corresponding point without performing the above-described process if there are no points adjacent to the predictor of each point.

The point cloud encoder (for example, the lifting transform unit 40010) according to the embodiments generates a predictor of each point, sets the calculated LOD to the predictor, registers neighboring points, and increases the distance to the neighboring points. Lifting transform coding can be performed by setting weights. Lifting transform coding according to embodiments is similar to the above-described predictive transform coding, but differs in that a weight is accumulated and applied to an attribute value. A process of cumulatively applying a weight to an attribute value according to embodiments is as follows.

1) Create an array QW (Quantization Wieght) that stores the weight value of each point. The initial value of all elements of QW is 1.0. The QW value of the predictor index of the neighboring node registered in the predictor is multiplied by the weight of the predictor of the current point.

2) Lift prediction process: In order to calculate the predicted attribute value, the value obtained by multiplying the attribute value of the point by the weight is subtracted from the existing attribute value.

3) Create temporary arrays called updateweight and update, and initialize temporary arrays to 0.

4) The weights calculated by additionally multiplying the weights calculated for all predictors by the weights stored in the QW corresponding to the predictor indexes are cumulatively added to the update weight array by the indexes of neighboring nodes. In the update array, the value obtained by multiplying the calculated weight by the attribute value of the index of the neighboring node is accumulated and summed.

5) Lift update process: For all predictors, the attribute value of the update array is divided by the weight value of the update weight array of the predictor index, and the existing attribute value is added to the divided value.

6) For all predictors, the predicted attribute value is calculated by additionally multiplying the attribute value updated through the lift update process by the weight updated through the lift prediction process (stored in QW). A point cloud encoder (for example, the coefficient quantization unit 40011) according to embodiments quantizes a predicted attribute value. In addition, the point cloud encoder (for example, the Arismatic encoder 40012) entropy-codes the quantized attribute values.

The point cloud encoder (for example, the RAHT transform unit 40008) according to the embodiments may perform RAHT transform coding that estimates the attributes of higher-level nodes by using an attribute associated with a node at a lower level of the octree. . RAHT transform coding is an example of attribute intra coding through octree backward scan. The point cloud encoder according to the embodiments scans from voxels to the entire area, and repeats the merging process up to the root node while merging the voxels into larger blocks in each step. The merging process according to the embodiments is performed only for an occupied node. The merging process is not performed for the empty node, and the merging process is performed for the node immediately above the empty node.

The following equation represents the RAHT transformation matrix.

Denotes the average attribute value of voxels at level l.

Is

Wow

Can be calculated from

Wow

Weight of

and

to be.

Is a low-pass value and is used in the merging process at the next higher level.

Is high-pass coefficients, and the high-pass coefficients in each step are quantized and entropy-coded (for example, encoding of the arithmetic encoder 400012). Weight is

Is calculated as Root node is the last

and

It is created as follows:

The gDC value is also quantized and entropy coded like the high pass coefficient.

10 shows an example of a point cloud decoder according to embodiments.

The point cloud decoder illustrated in FIG. 10 is an example of the point cloud video decoder 10006 described in FIG. 1, and may perform the same or similar operation as that of the point cloud video decoder 10006 described in FIG. 1. As shown in the figure, the point cloud decoder may receive a geometry bitstream and an attribute bitstream included in one or more bitstreams. The point cloud decoder includes a geometry decoder and an attribute decoder. The geometry decoder performs geometry decoding on the geometry bitstream and outputs decoded geometry. The attribute decoder outputs decoded attributes by performing attribute decoding on the basis of the decoded geometry and the attribute bitstream. The decoded geometry and decoded attributes are used to reconstruct the point cloud content.

11 shows an example of a point cloud decoder according to embodiments.

The point cloud decoder illustrated in FIG. 11 is an example of the point cloud decoder described in FIG. 10, and may perform a decoding operation that is a reverse process of the encoding operation of the point cloud encoder described in FIGS. 1 to 9.

As described in FIGS. 1 and 10, the point cloud decoder may perform geometry decoding and attribute decoding. Geometry decoding is performed prior to attribute decoding.

The point cloud decoder according to the embodiments includes an arithmetic decoder (11000), an octree synthesis unit (synthesize octree, 11001), a surface optimization synthesis unit (synthesize surface approximation, 11002), and a geometry reconstruction unit (reconstruct geometry). , 11003), inverse transform coordinates (11004), arithmetic decode (11005), inverse quantize (11006), RAHT transform unit (11007), LOD generator (generate LOD, 11008) ), Inverse lifting (11009), and/or inverse transform colors (11010).

The arithmetic decoder 11000, the octree synthesis unit 11001, the surface opoxidation synthesis unit 11002, the geometry reconstruction unit 11003, and the coordinate system inverse transform unit 11004 may perform geometry decoding. Geometry decoding according to embodiments may include direct coding and trisoup geometry decoding. Direct coding and trisoup geometry decoding are optionally applied. Further, the geometry decoding is not limited to the above example, and is performed in the reverse process of the geometry encoding described in FIGS. 1 to 9.

The Arismatic decoder 11000 according to embodiments decodes the received geometry bitstream based on Arismatic coding. The operation of the Arismatic decoder 11000 corresponds to the reverse process of the Arismatic encoder 40004.

The octree synthesizer 11001 according to the embodiments may generate an octree by obtaining an ocupancy code from a decoded geometry bitstream (or information on a geometry obtained as a result of decoding). A detailed description of the OQFancy code is as described in FIGS. 1 to 9.

When trisoup geometry encoding is applied, the surface opoxidation synthesizer 11002 according to embodiments may synthesize a surface based on the decoded geometry and/or the generated octree.

The geometry reconstruction unit 11003 according to the embodiments may regenerate the geometry based on the surface and/or the decoded geometry. 1 to 9, direct coding and trisoup geometry encoding are selectively applied. Accordingly, the geometry reconstruction unit 11003 directly imports and adds position information of points to which direct coding is applied. In addition, when trisoup geometry encoding is applied, the geometry reconstruction unit 11003 performs a reconstruction operation of the geometry reconstruction unit 40005, such as triangle reconstruction, up-sampling, and voxelization, to restore the geometry. have. Details are the same as those described in FIG. 6 and thus will be omitted. The reconstructed geometry may include a point cloud picture or frame that does not include attributes.

The coordinate system inverse transform unit 11004 according to embodiments may acquire positions of points by transforming a coordinate system based on the restored geometry.

Arithmetic decoder 11005, inverse quantization unit 11006, RAHT conversion unit 11007, LOD generation unit 11008, inverse lifting unit 11009, and/or color inverse conversion unit 11010 are attributes described in FIG. Decoding can be performed. Attribute decoding according to embodiments includes Region Adaptive Hierarchial Transform (RAHT) decoding, Interpolaration-based hierarchical nearest-neighbor prediction-Prediction Transform decoding, and interpolation-based hierarchical nearest-neighbor prediction with an update/lifting. step (Lifting Transform)) decoding may be included. The above three decodings may be used selectively, or a combination of one or more decodings may be used. In addition, attribute decoding according to embodiments is not limited to the above-described example.

The Arismatic decoder 11005 according to the embodiments decodes the attribute bitstream by arithmetic coding.

The inverse quantization unit 11006 according to embodiments inverse quantizes information on the decoded attribute bitstream or the attribute obtained as a result of decoding, and outputs inverse quantized attributes (or attribute values). Inverse quantization may be selectively applied based on the attribute encoding of the point cloud encoder.

According to embodiments, the RAHT conversion unit 11007, the LOD generation unit 11008 and/or the inverse lifting unit 11009 may process reconstructed geometry and inverse quantized attributes. As described above, the RAHT conversion unit 11007, the LOD generation unit 11008, and/or the inverse lifting unit 11009 may selectively perform a decoding operation corresponding thereto according to the encoding of the point cloud encoder.

The inverse color transform unit 11010 according to embodiments performs inverse transform coding for inverse transforming a color value (or texture) included in the decoded attributes. The operation of the color inverse transform unit 11010 may be selectively performed based on the operation of the color transform unit 40006 of the point cloud encoder.

Although elements of the point cloud decoder of FIG. 11 are not shown in the drawing, hardware including one or more processors or integrated circuits configured to communicate with one or more memories included in the point cloud providing apparatus , Software, firmware, or a combination thereof. One or more processors may perform at least one or more of the operations and/or functions of the elements of the point cloud decoder of FIG. 11 described above. Further, one or more processors may operate or execute a set of software programs and/or instructions for performing operations and/or functions of elements of the point cloud decoder of FIG. 11.

12 is an example of a transmission device according to embodiments.

The transmission device shown in FIG. 12 is an example of the transmission device 10000 of FIG. 1 (or a point cloud encoder of FIG. 4 ). The transmission device illustrated in FIG. 12 may perform at least one or more of the same or similar operations and methods as the operations and encoding methods of the point cloud encoder described in FIGS. 1 to 9. The transmission apparatus according to the embodiments includes a data input unit 12000, a quantization processing unit 12001, a voxelization processing unit 12002, an octree occupancy code generation unit 12003, a surface model processing unit 12004, an intra/ Inter-coding processing unit (12005), Arithmetic coder (12006), metadata processing unit (12007), color conversion processing unit (12008), attribute transformation processing unit (or attribute transformation processing unit) (12009), prediction/lifting/RAHT transformation A processing unit 12010, an Arithmetic coder 12011, and/or a transmission processing unit 12012 may be included.

The data input unit 12000 according to the embodiments receives or acquires point cloud data. The data input unit 12000 may perform the same or similar operation and/or an acquisition method to the operation and/or acquisition method of the point cloud video acquisition unit 10001 (or the acquisition process 20000 described in FIG. 2 ).

Data input unit 12000, quantization processing unit 12001, voxelization processing unit 12002, Occupancy code generation unit 12003, surface model processing unit 12004, intra/inter coding processing unit 12005, Arithmetic The coder 12006 performs geometry encoding. The geometry encoding according to the embodiments is the same as or similar to the geometry encoding described in FIGS. 1 to 9, so a detailed description thereof will be omitted.

The quantization processing unit 12001 according to embodiments quantizes geometry (eg, a position value or position value of points). The operation and/or quantization of the quantization processor 12001 is the same as or similar to the operation and/or quantization of the quantization unit 40001 described in FIG. 4. Detailed descriptions are the same as those described in FIGS. 1 to 9.

The voxelization processor 12002 according to embodiments voxelsizes the position values of the quantized points. The voxelization processor 120002 may perform the same or similar operation and/or process as the operation and/or the voxelization process of the quantization unit 40001 described in FIG. 4. Detailed descriptions are the same as those described in FIGS. 1 to 9.

The octree occupancy code generation unit 12003 according to embodiments performs octree coding on positions of voxelized points based on an octree structure. The octree ocupancy code generation unit 12003 may generate an ocupancy code. The octree occupancy code generation unit 12003 may perform the same or similar operation and/or method as the operation and/or method of the point cloud encoder (or octree analysis unit 40002) described in FIGS. 4 and 6. Detailed descriptions are the same as those described in FIGS. 1 to 9.

The surface model processing unit 12004 according to embodiments may perform trisoup geometry encoding to reconstruct positions of points within a specific area (or node) based on a voxel based on a surface model. The face model processing unit 12004 may perform the same or similar operation and/or method as the operation and/or method of the point cloud encoder (eg, the surface aproxiation analysis unit 40003) described in FIG. 4. Detailed descriptions are the same as those described in FIGS. 1 to 9.

The intra/inter coding processor 12005 according to embodiments may intra/inter code point cloud data. The intra/inter coding processing unit 12005 may perform the same or similar coding as the intra/inter coding described in FIG. 7. The detailed description is the same as described in FIG. 7. According to embodiments, the intra/inter coding processing unit 12005 may be included in the arithmetic coder 12006.

The arithmetic coder 12006 according to embodiments entropy encodes an octree and/or an approximated octree of point cloud data. For example, the encoding method includes an Arithmetic encoding method. . The arithmetic coder 12006 performs the same or similar operation and/or method to the operation and/or method of the arithmetic encoder 40004.

The metadata processing unit 12007 according to embodiments processes metadata related to point cloud data, for example, a set value, and provides it to a necessary processing such as geometry encoding and/or attribute encoding. In addition, the metadata processing unit 12007 according to embodiments may generate and/or process signaling information related to geometry encoding and/or attribute encoding. Signaling information according to embodiments may be encoded separately from geometry encoding and/or attribute encoding. In addition, signaling information according to embodiments may be interleaved.

The color conversion processing unit 12008, the attribute conversion processing unit 12009, the prediction/lifting/RAHT conversion processing unit 12010, and the Arithmetic coder 12011 perform attribute encoding. Attribute encoding according to embodiments is the same as or similar to the attribute encoding described in FIGS. 1 to 9, and thus a detailed description thereof will be omitted.

The color conversion processing unit 12008 according to embodiments performs color conversion coding that converts color values included in attributes. The color conversion processing unit 12008 may perform color conversion coding based on the reconstructed geometry. Description of the reconstructed geometry is the same as described in FIGS. 1 to 9. In addition, the same or similar operation and/or method to the operation and/or method of the color conversion unit 40006 described in FIG. 4 is performed. Detailed description will be omitted.

The attribute conversion processing unit 12009 according to embodiments performs attribute conversion for converting attributes based on the reconstructed geometry and/or positions for which geometry encoding has not been performed. The attribute conversion processing unit 12009 performs the same or similar operation and/or method to the operation and/or method of the attribute conversion unit 40007 described in FIG. 4. Detailed description will be omitted. The prediction/lifting/RAHT transform processing unit 12010 according to embodiments may code transformed attributes by using any one or a combination of RAHT coding, predictive transform coding, and lifting transform coding. The prediction/lifting/RAHT conversion processing unit 12010 performs at least one of the same or similar operations as the RAHT conversion unit 40008, LOD generation unit 40009, and lifting conversion unit 40010 described in FIG. 4. do. In addition, descriptions of predictive transform coding, lifting transform coding, and RAHT transform coding are the same as those described in FIGS.

The Arismatic coder 12011 according to embodiments may encode coded attributes based on Arismatic coding. The Arismatic coder 12011 performs the same or similar operation and/or method to the operation and/or method of the Arismatic encoder 400012.

The transmission processor 12012 according to the embodiments transmits each bitstream including the encoded geometry and/or the encoded attribute, and metadata information, or transmits the encoded geometry and/or the encoded attribute, and the metadata information in one piece. It can be configured as a bitstream and transmitted. When the encoded geometry and/or encoded attribute and metadata information according to the embodiments are configured as one bitstream, the bitstream may include one or more sub-bitstreams. The bitstream according to the embodiments is a sequence parameter set (SPS) for signaling of a sequence level, a geometry parameter set (GPS) for signaling of geometry information coding, an attribute parameter set (APS) for signaling of attribute information coding, and a tile. It may include signaling information including TPS (Tile Parameter Set) for level signaling and slice data. Slice data may include information on one or more slices. One slice according to embodiments may include one geometry bitstream (Geom0 ⁰ ) and one or more attribute bitstreams (Attr0 ⁰ and Attr1 ⁰ ). The TPS according to the embodiments may include information about each tile (eg, coordinate value information and height/size information of a bounding box) for one or more tiles. The geometry bitstream may include a header and a payload. The header of the geometry bitstream according to embodiments may include identification information of a parameter set included in GPS (geom_ parameter_set_id), a tile identifier (geom_tile_id), a slice identifier (geom_slice_id), and information about data included in the payload. I can. As described above, the metadata processing unit 12007 according to the embodiments may generate and/or process signaling information and transmit the generated signaling information to the transmission processing unit 12012. Depending on embodiments, elements that perform geometry encoding and elements that perform attribute encoding may share data/information with each other as dotted line processing. The transmission processing unit 12012 according to the embodiments may perform the same or similar operation and/or transmission method as the operation and/or transmission method of the transmitter 10003. Detailed descriptions are the same as those described in FIGS. 1 to 2 and thus will be omitted.

13 is an example of a reception device according to embodiments.

The receiving device illustrated in FIG. 13 is an example of the receiving device 10004 of FIG. 1 (or the point cloud decoder of FIGS. 10 and 11 ). The receiving device illustrated in FIG. 13 may perform at least one or more of the same or similar operations and methods as the operations and decoding methods of the point cloud decoder described in FIGS. 1 to 11.

The receiving apparatus according to the embodiments includes a receiving unit 13000, a receiving processing unit 13001, an arithmetic decoder 13002, an octree reconstruction processing unit 13003 based on an Occupancy code, and a surface model processing unit (triangle reconstruction). , Up-sampling, voxelization) (13004), inverse quantization processing unit (13005), metadata parser (13006), arithmetic decoder (13007), inverse quantization processing unit (13008), prediction A /lifting/RAHT inverse transformation processing unit 13009, a color inverse transformation processing unit 13010, and/or a renderer 13011 may be included. Each component of decoding according to the embodiments may perform a reverse process of the component of encoding according to the embodiments.

The receiving unit 13000 according to the embodiments receives point cloud data. The receiving unit 13000 may perform the same or similar operation and/or a receiving method as the operation and/or receiving method of the receiver 10005 of FIG. 1. Detailed description will be omitted.

The reception processing unit 13001 according to embodiments may obtain a geometry bitstream and/or an attribute bitstream from received data. The reception processing unit 13001 may be included in the reception unit 13000.

The arithmetic decoder 13002, the ocupancy code-based octree reconstruction processing unit 13003, the surface model processing unit 13004, and the inverse quantization processing unit 13005 may perform geometry decoding. Since the geometry decoding according to the embodiments is the same as or similar to the geometry decoding described in FIGS. 1 to 10, a detailed description will be omitted.

The Arismatic decoder 13002 according to embodiments may decode a geometry bitstream based on Arismatic coding. The Arismatic decoder 13002 performs the same or similar operation and/or coding as the operation and/or coding of the Arismatic decoder 11000.

The ocupancy code-based octree reconstruction processing unit 13003 according to the embodiments may obtain an ocupancy code from a decoded geometry bitstream (or information on a geometry obtained as a result of decoding) to reconstruct the octree. The ocupancy code-based octree reconstruction processing unit 13003 performs the same or similar operation and/or method as the operation and/or the octree generation method of the octree synthesis unit 11001. When the trisoup geometry encoding is applied, the surface model processing unit 13004 according to the embodiments decodes the trisoup geometry based on the surface model method and reconstructs the related geometry (e.g., triangle reconstruction, up-sampling, voxelization). Can be done. The surface model processing unit 13004 performs an operation identical or similar to that of the surface opoxidation synthesis unit 11002 and/or the geometry reconstruction unit 11003.

The inverse quantization processing unit 13005 according to embodiments may inverse quantize the decoded geometry.

The metadata parser 13006 according to embodiments may parse metadata included in the received point cloud data, for example, a setting value. The metadata parser 13006 may pass metadata to geometry decoding and/or attribute decoding. The detailed description of the metadata is the same as that described in FIG. 12 and thus will be omitted.

The arithmetic decoder 13007, the inverse quantization processing unit 13008, the prediction/lifting/RAHT inverse transformation processing unit 13009, and the color inverse transformation processing unit 13010 perform attribute decoding. Since the attribute decoding is the same as or similar to the attribute decoding described in FIGS. 1 to 10, a detailed description will be omitted.

The Arismatic decoder 13007 according to the embodiments may decode the attribute bitstream through Arismatic coding. The arithmetic decoder 13007 may perform decoding of the attribute bitstream based on the reconstructed geometry. The Arismatic decoder 13007 performs the same or similar operation and/or coding as the operation and/or coding of the Arismatic decoder 11005.

The inverse quantization processing unit 13008 according to embodiments may inverse quantize the decoded attribute bitstream. The inverse quantization processing unit 13008 performs the same or similar operation and/or method as the operation and/or the inverse quantization method of the inverse quantization unit 11006.

The prediction/lifting/RAHT inverse transform processing unit 13009 according to embodiments may process reconstructed geometry and inverse quantized attributes. The prediction/lifting/RAHT inverse transform processing unit 13009 is the same or similar to the operations and/or decodings of the RAHT transform unit 11007, the LOD generator 11008 and/or the inverse lifting unit 11009, and/or At least one or more of the decodings is performed. The color inverse transform processing unit 13010 according to embodiments performs inverse transform coding for inverse transforming a color value (or texture) included in the decoded attributes. The color inverse transform processing unit 13010 performs the same or similar operation and/or inverse transform coding as the operation and/or inverse transform coding of the color inverse transform unit 11010. The renderer 13011 according to embodiments may render point cloud data.

14 illustrates an architecture for G-PCC-based point cloud content streaming according to embodiments.

The upper part of FIG. 14 shows a process in which the transmission device (for example, the transmission device 10000, the transmission device of FIG. 12, etc.) described in FIGS. 1 to 13 processes and transmits the point cloud content.

As described with reference to FIGS. 1 to 13, the transmission device may obtain audio Ba of the point cloud content (Audio Acquisition), encode the acquired audio, and output audio bitstreams Ea. In addition, the transmission device acquires a point cloud (Bv) (or point cloud video) of the point cloud content (Point Acqusition), performs point cloud encoding on the acquired point cloud, and performs a point cloud video bitstream ( Eb) can be output. The point cloud encoding of the transmission device is the same as or similar to the point cloud encoding described in FIGS. 1 to 13 (for example, encoding of the point cloud encoder of FIG. 4, etc.), so a detailed description thereof will be omitted.

The transmission device may encapsulate the generated audio bitstreams and video bitstreams into files and/or segments (File/segment encapsulation). The encapsulated file and/or segment (Fs, File) may include a file of a file format such as ISOBMFF or a DASH segment. Point cloud-related metadata according to embodiments may be included in an encapsulated file format and/or segment. Meta data may be included in boxes of various levels in the ISOBMFF file format or may be included in separate tracks in the file. According to an embodiment, the transmission device may encapsulate the metadata itself as a separate file. The transmission device according to the embodiments may deliver an encapsulated file format and/or segment through a network. Since the encapsulation and transmission processing method of the transmission device is the same as those described in FIGS. 1 to 13 (for example, the transmitter 10003, the transmission step 20002 of FIG. 2, etc.), detailed descriptions are omitted.

The bottom of FIG. 14 shows a process of processing and outputting point cloud content by the receiving device (for example, the receiving device 10004, the receiving device of FIG. 13, etc.) described in FIGS. 1 to 13.

According to embodiments, the receiving device includes a device that outputs final audio data and final video data (e.g., loudspeakers, headphones, display), and a point cloud player that processes point cloud content ( Point Cloud Player). The final data output device and the point cloud player may be configured as separate physical devices. The point cloud player according to the embodiments may perform Geometry-based Point Cloud Compression (G-PCC) coding and/or Video based Point Cloud Compression (V-PCC) coding and/or next-generation coding.

The receiving device according to the embodiments secures a file and/or segment (F', Fs') included in the received data (for example, a broadcast signal, a signal transmitted through a network, etc.) and decapsulation (File/ segment decapsulation). Since the reception and decapsulation method of the reception device is the same as that described in FIGS. 1 to 13 (for example, the receiver 10005, the reception unit 13000, the reception processing unit 13001, etc.), a detailed description will be omitted.

The receiving device according to the embodiments secures an audio bitstream E'a and a video bitstream E'v included in a file and/or segment. As shown in the drawing, the receiving device outputs the decoded audio data B'a by performing audio decoding on the audio bitstream, and rendering the decoded audio data to final audio data. (A'a) is output through speakers or headphones.

In addition, the receiving device outputs decoded video data B'v by performing point cloud decoding on the video bitstream E'v. Since the point cloud decoding according to the embodiments is the same as or similar to the point cloud decoding described in FIGS. 1 to 13 (for example, decoding of the point cloud decoder of FIG. 11 ), a detailed description will be omitted. The receiving device may render the decoded video data and output the final video data through the display.

The receiving device according to the embodiments may perform at least one of decapsulation, audio decoding, audio rendering, point cloud decoding, and rendering operations based on metadata transmitted together. The description of the metadata is the same as that described with reference to FIGS. 12 to 13 and thus will be omitted.

As shown in the dotted line shown in the drawing, the receiving device according to the embodiments (for example, a point cloud player or a sensing/tracking unit (sensing/tracking) in a point cloud flare) may generate feedback information (orientation, viewport). . The feedback information according to the embodiments may be used in a decapsulation process, a point cloud decoding process and/or a rendering process of a receiving device, or may be transmitted to a transmitting device. The description of the feedback information is the same as that described with reference to FIGS. 1 to 13 and thus will be omitted.

15 shows an example of a transmission device according to embodiments.

The transmission device of FIG. 15 is a device that transmits point cloud content, and the transmission device described in FIGS. 1 to 14 (for example, the transmission device 10000 of FIG. 1, the point cloud encoder of FIG. 4, the transmission device of FIG. 12, 14). Accordingly, the transmission device of FIG. 15 performs the same or similar operation to that of the transmission device described in FIGS. 1 to 14.

The transmission device according to embodiments may perform at least one or more of point cloud acquisition, point cloud encoding, file/segment encapsulation, and delivery. Can be done.

Since the operation of acquiring and transmitting the point cloud illustrated in the drawing is the same as described in FIGS. 1 to 14, detailed descriptions will be omitted.

As described with reference to FIGS. 1 to 14, the transmission device according to embodiments may perform geometry encoding and attribute encoding. Geometry encoding according to embodiments may be referred to as geometry compression, and attribute encoding may be referred to as attribute compression. As described above, one point may have one geometry and one or more attributes. Therefore, the transmission device performs attribute encoding for each attribute. The drawing shows an example in which a transmission device has performed one or more attribute compressions (attribute #1 compression, ...attribute #N compression). In addition, the transmission apparatus according to the embodiments may perform auxiliary compression. Additional compression is performed on the metadata. Description of the meta data is the same as that described with reference to FIGS. 1 to 14 and thus will be omitted. In addition, the transmission device may perform mesh data compression. Mesh data compression according to embodiments may include the trisoup geometry encoding described in FIGS. 1 to 14.

The transmission device according to the embodiments may encapsulate bitstreams (eg, point cloud streams) output according to point cloud encoding into files and/or segments. According to embodiments, a transmission device performs media track encapsulation for carrying data other than metadata (for example, media data), and metadata tracak for carrying meta data. encapsulation) can be performed. According to embodiments, metadata may be encapsulated as a media track.

1 to 14, the transmitting device receives feedback information (orientation/viewport metadata) from the receiving device, and based on the received feedback information, at least one of point cloud encoding, file/segment encapsulation, and transmission operations. Any one or more can be performed. Detailed descriptions are the same as those described with reference to FIGS.

16 shows an example of a receiving device according to embodiments.

The receiving device of FIG. 16 is a device that receives point cloud content, and the receiving device described in FIGS. 1 to 14 (for example, the receiving device 10004 of FIG. 1, the point cloud decoder of FIG. 11, the receiving device of FIG. 13, 14). Accordingly, the receiving device of FIG. 16 performs the same or similar operation to that of the receiving device described in FIGS. 1 to 14. In addition, the receiving device of FIG. 16 may receive a signal transmitted from the transmitting device of FIG. 15, and may perform a reverse process of the operation of the transmitting device of FIG. 15.

The receiving device according to embodiments may perform at least one or more of delivery, file/segement decapsulation, point cloud decoding, and point cloud rendering. Can be done.

Since the point cloud reception and point cloud rendering operations shown in the drawings are the same as those described in FIGS. 1 to 14, detailed descriptions are omitted.

As described with reference to FIGS. 1 to 14, the reception device according to the embodiments performs decapsulation on a file and/or segment acquired from a network or a storage device. According to embodiments, the receiving device performs media track decapsulation carrying data other than meta data (for example, media data), and metadata track decapsulation carrying meta data. decapsulation) can be performed. According to embodiments, when metadata is encapsulated into a media track, the metadata track decapsulation is omitted.

As described with reference to FIGS. 1 to 14, the receiving device may perform geometry decoding and attribute decoding on bitstreams (eg, point cloud streams) secured through decapsulation. Geometry decoding according to embodiments may be referred to as geometry decompression, and attribute decoding may be referred to as attribute decompression. As described above, a point may have one geometry and one or more attributes, and are each encoded. Therefore, the receiving device performs attribute decoding for each attribute. The drawing shows an example in which the receiving device performs one or more attribute decompressions (attribute #1 decompression, ...attribute #N decompression). In addition, the receiving device according to the embodiments may perform auxiliary decompression. Additional decompression is performed on the metadata. Description of the meta data is the same as that described with reference to FIGS. 1 to 14 and thus will be omitted. Additionally, the receiving device may perform mesh data decompression. The mesh data decompression according to embodiments may include decoding the trisoup geometry described in FIGS. 1 to 14. The receiving device according to the embodiments may render the output point cloud data according to the point cloud decoding.

As described in FIGS. 1 to 14, the receiving device secures orientation/viewport metadata using a separate sensing/tracking element, etc., and transmits feedback information including the same to a transmission device (for example, the transmission device of FIG. 15). Can be transmitted. In addition, the receiving device may perform at least one or more of a receiving operation, file/segment decapsulation, and point cloud decoding based on the feedback information. Detailed descriptions are the same as those described with reference to FIGS.

17 shows an example of a structure capable of interworking with a method/device for transmitting and receiving point cloud data according to embodiments.

The structure of FIG. 17 includes at least one of a server 1760, a robot 1710, an autonomous vehicle 1720, an XR device 1730, a smartphone 1740, a home appliance 1750, and/or an HMD 1770. A configuration connected to the cloud network 1710 is shown. The robot 1710, the autonomous vehicle 1720, the XR device 1730, the smartphone 1740, the home appliance 1750, and the like are referred to as devices. In addition, the XR device 1730 may correspond to a point cloud data (PCC) device according to embodiments or may be interlocked with a PCC device.

The cloud network 1700 may constitute a part of a cloud computing infrastructure or may mean a network that exists in the cloud computing infrastructure. Here, the cloud network 1700 may be configured using a 3G network, a 4G or long term evolution (LTE) network, or a 5G network.

The server 1760 includes at least one of a robot 1710, an autonomous vehicle 1720, an XR device 1730, a smartphone 1740, a home appliance 1750, and/or an HMD 1770, and a cloud network 1700. The connected devices 1710 to 1770 may be connected through, and may help at least part of the processing of the connected devices.

The HMD (Head-Mount Display) 1770 represents one of types in which an XR device and/or a PCC device according to embodiments may be implemented. The HMD type device according to the embodiments includes a communication unit, a control unit, a memory unit, an I/O unit, a sensor unit, and a power supply unit.

Hereinafter, various embodiments of the devices 1710 to 1750 to which the above-described technology is applied will be described. Here, the devices 1710 to 1750 shown in FIG. 17 may be interlocked/coupled with the point cloud data transmission/reception apparatus according to the above-described embodiments.

<PCC+XR>

The XR/PCC device 1730 is applied with PCC and/or XR (AR+VR) technology to provide a head-mount display (HMD), a head-up display (HUD) provided in a vehicle, television, mobile phone, smart phone It may be implemented as a computer, wearable device, home appliance, digital signage, vehicle, fixed robot or mobile robot.

The XR/PCC device 1730 analyzes 3D point cloud data or image data acquired through various sensors or from an external device to generate position data and attribute data for 3D points, thereby Information can be obtained, and the XR object to be output can be rendered and output. For example, the XR/PCC device 1730 may output an XR object including additional information on the recognized object in correspondence with the recognized object.

<PCC+Autonomous Driving+XR>

The autonomous vehicle 1720 may be implemented as a mobile robot, a vehicle, or an unmanned aerial vehicle by applying PCC technology and XR technology.

The autonomous driving vehicle 1720 to which the XR/PCC technology is applied may refer to an autonomous driving vehicle having a means for providing an XR image, an autonomous driving vehicle that is an object of control/interaction within the XR image. In particular, the autonomous vehicle 1720, which is the object of control/interaction in the XR image, is distinguished from the XR device 1730 and may be interlocked with each other.

The autonomous vehicle 1720 having a means for providing an XR/PCC image may acquire sensor information from sensors including a camera, and may output an XR/PCC image generated based on the acquired sensor information. For example, the autonomous vehicle 1720 may provide an XR/PCC object corresponding to a real object or an object in a screen to the occupant by outputting an XR/PCC image with a HUD.

In this case, when the XR/PCC object is output to the HUD, at least a part of the XR/PCC object may be output to overlap the actual object facing the occupant's gaze. On the other hand, when the XR/PCC object is output on a display provided inside the autonomous vehicle, at least a part of the XR/PCC object may be output to overlap the object in the screen. For example, the autonomous vehicle 1220 may output XR/PCC objects corresponding to objects such as lanes, other vehicles, traffic lights, traffic signs, motorcycles, pedestrians, and buildings.

VR (Virtual Reality) technology, AR (Augmented Reality) technology, MR (Mixed Reality) technology and/or PCC (Point Cloud Compression) technology according to the embodiments can be applied to various devices.

That is, VR technology is a display technology that provides objects or backgrounds in the real world only as CG images. On the other hand, AR technology refers to a technology that shows a virtually created CG image on a real object image. Furthermore, MR technology is similar to the AR technology described above in that virtual objects are mixed and combined in the real world. However, in AR technology, the distinction between real objects and virtual objects made from CG images is clear, and virtual objects are used in a form that complements the real objects, whereas in MR technology, the virtual objects are regarded as having the same characteristics as the real objects. It is distinct from technology. More specifically, for example, it is a hologram service to which the aforementioned MR technology is applied.

However, recently, VR, AR, and MR technologies are sometimes referred to as XR (extended reality) technology rather than clearly distinguishing between them. Therefore, embodiments of the present invention are applicable to all of VR, AR, MR, and XR technologies. This technology can be applied to encoding/decoding based on PCC, V-PCC, and G-PCC technology.

The PCC method/apparatus according to the embodiments may be applied to a vehicle providing an autonomous driving service.

Vehicles providing autonomous driving service are connected to PCC devices to enable wired/wireless communication.

When the point cloud data (PCC) transmission and reception device according to the embodiments is connected to enable wired/wireless communication with the vehicle, the vehicle receives/processes AR/VR/PCC service related content data that can be provided together with the autonomous driving service. Can be transferred to. In addition, when the point cloud data transmission/reception device is mounted on a vehicle, the point cloud transmission/reception device may receive/process AR/VR/PCC service related content data according to a user input signal input through the user interface device and provide it to the user. The vehicle or user interface device according to the embodiments may receive a user input signal. The user input signal according to the embodiments may include a signal indicating an autonomous driving service.

The method/device according to the embodiments may refer to a point cloud data transmission/reception method and/or a point cloud data transmission/reception apparatus. According to embodiments, geometry information may be referred to as geometric information, and attribute information may be referred to as attribute information.

The encoder according to the embodiments may be referred to as a point cloud data encoder, a point cloud encoder, and a point cloud encoder according to the embodiments. The decoder according to the embodiments may be referred to as a point cloud data decoder, a point cloud decoder, and a point cloud decoder according to the embodiments.

18 shows a point cloud encoder according to embodiments.

The point cloud encoder 18000 according to the embodiments receives point cloud data (PCC data, 18000a) and encodes them. The point cloud encoder according to the embodiments outputs a geometric information bitstream 18000b and an attribute information bitstream 18000c. The point cloud encoder 18000 according to the embodiments may include a spatial division unit 18001, a geometric information encoding unit 18002, and/or an attribute information encoding unit 18003.

The spatial division unit 18001 may receive the point cloud data (PCC data, 18000a) from the point cloud encoder, and divide the point cloud data into one or more three-dimensional spaces. The spatial divider 18001 may receive point cloud data and spatially divide the point cloud data into 3D blocks. The point cloud data may include geometric information and/or attribute information of a point (or points). The spatial divider 18001 may spatially divide point cloud data (PCC data) based on a bounding box and/or a sub-bounding box. The method/apparatus according to the embodiments may perform encoding/decoding based on a divided unit (box).

The space division unit 18001 is a part of the operation of the Point Cloud Acquisition (10001) of FIG. 1, the acquisition (20000) of FIG. 2, the operation of FIGS. 3 to 5, and the data input unit 12000 of FIG. 12 /Can do all.

The geometric information encoding unit 18002 receives geometry information of point cloud data (PCC data) according to embodiments and encodes them. The geometry information may mean location information of points included in the point cloud data. The geometry information encoder 18002 encodes geometry information and outputs a geometry information bitstream. The geometric information encoder 18002 may reconstruct the location information of the points and output the reconstructed geometric information 18002a. The geometric information encoding unit 18002 may transmit the reconstructed geometric information to the attribute information encoding unit 18002.

The geometric information encoding unit 18002 is a point cloud video encoder 10002 of FIG. 1, an encoding 20001 of FIG. 2, a coordinate system transforming unit 40000 of FIG. 4, a quantization 40001, an octree analysis unit. (40002), a surface aproximation analysis unit (40003), an Arismatic encoder (40004), a geometry reconstruction unit (40005), a quantization processing unit (12001) of FIG. 12, a voxelization processing unit (12002), an octree occupancy Some/all of the operations of the code generation unit 12003, the surface model processing unit 12004, the intra/inter coding processing unit 12005, and/or the arithmetic coder 12006 may be performed.

The attribute information encoding unit 18003 may receive attribute information of the point cloud data according to embodiments, and may encode the attribute information using the reconstructed geometric information received from the geometric information encoder 18003. The attribute information encoding unit 18003 encodes attribute information and outputs an attribute information bitstream 18000c. The attribute information encoder 18003 may, for example, perform prediction transform, lifting transform, and/or region adaptive hierarchical transform (RAHT) transform according to embodiments. The attribute information encoding unit 18003 may, for example, perform prediction lifting (or predictive lifting) transformation. The prediction lifting transformation may mean a combination of some or all of the detailed operations of the predictive transformation and/or the lifting transformation according to embodiments.

The point cloud encoder according to the embodiments encodes some, all and/or a combination of prediction transform, lifting transform, and/or Region Adaptive Hierarchical Transform (RAHT) transform according to the embodiments. Can be done.

The attribute information encoding unit 18003 includes a point cloud video encoder 10002 of FIG. 1, an encoding 20001 of FIG. 2, a color converter 40006 of FIG. 4, an attribute converter 40007, and a RATH converter 40008. , LOD generation unit 40009, Lifting transform unit 40010, coefficient quantization unit 40011 and/or operation of Arismatic encoding unit 40012, color conversion processing unit 12008 of FIG. 12, attribute conversion processing unit 12009 , All/some operations of the prediction/lifting/RAHT conversion processor 12010 and the Arismatic coder 12011 may be performed.

Here, the reconstructed geometric information 18002c may mean an octree reconstructed by the Reconstruct Geometry 40005 described in FIG. 4 and/or an approximated octree. The restored geometric information may refer to the occupancy code described in FIG. 6 or may refer to an octree structure. The restored geometric information may refer to an octree occupancy code generated by the octree occupancy code generator 12003 described in FIG. 12.

The attribute information encoder 18003 may encode attribute information of point cloud data according to embodiments. Here, the encoder 18003 according to the embodiments may encode attribute information by using reconstructed geometric information (or reconstructed geometric information) according to the embodiments. The attribute information encoder 18003 may generate a bitstream including attribute information (or attribute information) by encoding the received data.

The attribute information encoding unit 18003 according to the embodiments includes a color conversion unit 40006, an attribute transmission unit 40007, a RAHT conversion unit 40008, an LOD generation unit 40009, a lifting unit 40010, and A quantization unit 40011 and/or an arithmetic encoding unit 400012 may be included.

Point cloud data according to embodiments may be classified into category 1 and category 3 according to the characteristics of the data. Category 1 data may be static data and may be data composed of one frame. Category 3 data is dynamic data and may be data composed of N frames. A ply file, which is a file format of point cloud data, may be composed of a number of points according to a data acquisition method.

The point cloud data transmission method according to embodiments may include encoding point cloud data and/or transmitting a bitstream including point cloud data.

According to embodiments, the encoding may include encoding geometric information of the point cloud data and/or encoding attribute information of the point cloud data. In addition, the encoding may be performed in units of a slice or a tile including one or more slices.

Point cloud data according to embodiments may be classified into category 1 and category 3 according to the characteristics of the data. Category 1 data may be static data and may be data composed of one frame. Category 3 data is dynamic data and may be data composed of N frames. A ply file, which is a file format of point cloud data, may be composed of a number of points according to a data acquisition method.

A point according to embodiments may include attribute information (attribute information) including location information (geometry information) and color information, reflectivity information, time information, and normal vector information of the corresponding point. Points according to embodiments may include various information according to a condition to be expressed. Category 1 and Category 3 data consisting of points may include a frame including a large amount of points. However, when the point cloud data transmission apparatus according to the embodiments receives and encodes a frame including these points, there is a problem that a lot of delay time and unnecessary resources are used.

Accordingly, the point cloud data transmission apparatus according to the embodiments includes point cloud data in order to perform a transmission operation of point cloud data, an encoding operation, a decoding operation of the receiving device, and a rendering processing operation of the receiving device in real time and at the same time to be processed with low latency. Can be divided into a plurality of regions. The point cloud data transmission apparatus according to embodiments may divide a frame of point cloud data into a tile and a slice unit.

A tile may mean a partial area of a 3D space occupied by point cloud data according to embodiments. A tile according to embodiments may include one or more slices. The tile according to the embodiments is divided into one or more slices, so that the point cloud data encoder may encode the point cloud data in parallel. The point cloud data encoder may perform quantization and/or transformation differently according to the characteristics of data for each of one or more slices of a tile according to embodiments.

A slice may mean a unit of data that the device for transmitting and receiving point cloud data according to the embodiments performs encoding and decoding. A slice may mean a set of data in a 3D space occupied by point cloud data, or may mean a set of some data among point cloud data. A slice may mean an area of points or a set of points included in a tile according to embodiments. A tile according to embodiments may be divided into one or more slices based on the number of points included in one tile. For example, one tile may mean a set of points divided by the number of points. A tile according to embodiments may divide a slice based on the number of points, and some data may be split or merged during the segmentation process.

The point cloud data transmission apparatus according to the embodiments divides the point cloud data and encodes them independently or non-independently, thereby performing random access and parallel encoding in a three-dimensional space occupied by the point cloud data. Provides an effect that makes it possible.

The point cloud data transmission apparatus and reception apparatus according to the embodiments may prevent errors accumulated in the encoding and decoding process by performing encoding and decoding independently or non-independently in a slice unit.

19 illustrates an example of a bitstream structure of point cloud data according to embodiments.

The point cloud data transmission apparatus according to the embodiments may transmit a bitstream 19000 having a bitstream structure as illustrated in FIG. 31. The bitstream 19000 of the point cloud data is SPS (Sequential Parameter Set, 19001), GPS (Geometry Parameter Set, 19002), APS (Attribute Parameter Set, 19003), TPS (Tile Parameter Set, 19004), and one or more It may include slices (slice 0, slice 1… slice n, 19004). The bitstream 19000 of the point cloud data may include one or more tiles. A tile according to embodiments may be a group of slices including one or more slices.

The bitstream 19000 according to the embodiments provides a tile or slice so that point cloud data can be divided and processed by regions. Each region of the bitstream 19000 according to the embodiments may have a different importance. Accordingly, when the point cloud data is divided into tiles, different filters (coding methods) and different filter units may be applied for each tile. When the point cloud is divided into slices, different filters and different filter units may be applied for each slice.

The transmission/reception apparatus according to the embodiments may transmit and receive a bitstream according to a high-level syntax structure for selective transmission of attribute information within a divided region when the point cloud is divided and compressed.

The present invention proposes a high-level syntax structure to support a structure for selectively processing location information and multiple attribute information in an encoding/decoding process. The syntax in the present invention refers to an upper set of syntax of a bitstream, and if there is an additional constraint on the syntax, it can be specified directly or indirectly in another lower syntax. The parameter set defined in the present invention includes information that is expected not to be changed.

The point cloud data transmission apparatus according to the embodiments transmits the point cloud data according to the structure of the bitstream 19000 as shown in FIG. 31, so that different encoding operations can be applied according to the importance, and the quality is improved. It can provide a way to use a good coding method in an important area. In addition, it can support efficient encoding/decoding and transmission according to the characteristics of the point cloud, and provide attribute values according to user requirements.

In the point cloud data receiving apparatus according to the embodiments, instead of using a complex decoding (filtering) method for the entire point cloud data according to the processing capacity of the receiving apparatus, each area (area divided into tiles or divided into slices) By allowing different filtering (decoding methods) to be applied, it is possible to ensure better image quality in areas important to the user and appropriate latency to the system.

The point cloud data transmission apparatus and reception apparatus according to the embodiments may independently or non-independently perform encoding and decoding on a tile and/or slice unit, thereby preventing an error accumulated in the encoding and decoding process. Can be prevented.

SPS (Sequence Parameter Set, 19001) is applied to all zero or more CVSs determined by the content of the syntax element in the PPS referenced by the syntax element in each slice segment header. It is a syntax structure that includes syntax elements that are used. (A syntax structure containing syntax elements that apply to zero or more entire CVSs as determined by the content of a syntax element found in the PPS referred to by a syntax element found in each slice segment header.) SPS is a point according to embodiments It may include sequence information of the cloud data bitstream.

The GPS (Geometry Parameter Set, 19002) may mean a syntax structure including syntax elements to which zero or more total geometry (or encoded geometry) is applied. The GPS 19002 according to embodiments may include information about a method of encoding attribute (attribute) information of point cloud data included in one or more slices 19005. The GPS 19002 may include SPS identifier information indicating which geometry parameter associated with the SPS 19001 according to embodiments, and GPS identifier information for identifying the corresponding GPS.

The APS (Attribute Parameter Set, 19003) may mean a syntax structure including syntax elements to which zero or more all attributes (or encoded attributes) are applied. The APS 19003 according to the embodiments may include information on a method of encoding attribute (attribute) information of point cloud data included in one or more slices 19005. The APS 19003 may include SPS identifier information indicating which geometry parameter associated with the SPS 19001 according to embodiments, and GPS identifier information for identifying the corresponding APS.

The Tile Parameter Set (TPS) 19004 may mean a syntax structure including syntax elements to which zero or more total tiles (or encoded tiles) are applied. The tile inventory includes information on zero or more tiles included in the point cloud data bitstream according to embodiments. The tile inventory may be referred to as a tile parameter set (TPS) according to embodiments.

The TPS (Tile Parameter Set) 19004 may include identifier information for identifying one or more tiles and information indicating a range of one or more tiles (ie, a bounding box of a tile). Information indicating a range of one or more tiles (ie, a bounding box of a tile) is coordinate information of a point that is a reference of a bounding box represented by a corresponding tile (eg, Tile(n).tile_bounding_box_xyz0) and Information about the width, height, and depth of the corresponding bounding box (eg, Tile(n).tile_boudning_box_whd) may be included. When a plurality of tiles exist, the tile inventory (Tile Inventory, 19004) may include information indicating a bounding box for each of the tiles. For example, when each tile is represented by 0 to n by the identifier information of the tiles, the information indicating the bounding box of each tile is Tile(0).tile_bounding_box_xyz0, Tile(0).tile_bounding_box_whd, Tile(1).tile_bounding_box_xyz0 , Tile(1).tile_bounding_box_whd… It can be expressed as such.

A slice 19005 may mean a unit for encoding point cloud data by a device for transmitting point cloud data according to embodiments. A slice 19004 according to embodiments may refer to a unit including one geometry bitstream (Geom00, 19005a) and one or more attribute bitstreams (Attr00, Attr10, 19005b, 19005c).

A slice (19005) is a geometry slice (Geometry, 19005a) representing the geometry information of the point cloud data included in the slice, and one or more attribute slices representing the attribute information of the point cloud data included in the slice. (Attribute Slice, Attr, 19005b, 19005c) may be included.

A geometry slice (Geometry Slice, Geom, 19005a) includes geometry slice data (Geometry Slice Data, Geom_slice_data, 19005a-2) including geometry information of point cloud data, and a geometry slice header including information about the geometry slice data. Header, Geom_slice_header, GSH, 19005a-1).

The geometry slice header 19005a-1 includes information about the geometry slice data 19005a-2 in the slice. For example, the geometry slice header 19005a-1 is a geometry parameter set identifier (geom_geom_parameter_set_id) for identifying which GPS 19002 represents the geometry information of the corresponding slice, and a geometry slice identifier for identifying the corresponding geometry slice. (geom_slice_id), geometry box origin information indicating the box origin of the corresponding geometry slice data (geomBoxOrigin), information indicating the lock scale of the geometry slice (geom_box_log2_scale), information related to the number of points in the corresponding geometry slice (geom_num_points), etc. I can.

When the point cloud data bitstream according to the embodiments includes one or more tiles, the header of the geometry bitstream according to the embodiments is information for identifying a tile including the geometry bitstream (geom_tile_id ) May be further included.

Attribute Slice (Attr, 19005b) includes attribute slice data (Attribute Slice Data, Attr_slice_data, 19005b-2) including attribute information of point cloud data and an attribute slice header including information about attribute slice data. Header, Attr_slice_header, ASH, 19005b-1).

According to embodiments, parameters necessary for encoding a point cloud may be newly defined as parameter set and header information of a point cloud. For example, attribute parameter set RBSP syntax can be added when encoding attribute information, and tile_header syntax can be added when tile-based encoding is performed.

The point cloud data transmission/reception method according to the embodiments provides such a bitstream structure, so that the receiver can improve the decoding performance of attribute information of the point cloud data.

20 illustrates a connection relationship between an example of a bitstream structure of point cloud data and a configuration within the bitstream according to embodiments.

20 shows the relationship between a parameter of all syntax structure information and a bitstream. 20 shows a structure of a point cloud data bitstream according to embodiments. The point cloud data bitstream structure shown in FIG. 20 may mean the point cloud data bitstream structure shown in FIG. 19.

The point cloud data bitstream shown in FIG. 20 is a sequence parameter set (SPS), one or more geometry parameter sets (GPS), one or more attribute parameter sets (APS), and one or more slices according to embodiments. It may include (slice) or tiles.

The GPS and APS according to the embodiments include an identifier indicating an active SPS to which the corresponding GPS and APS belong.

For example, the GPS according to the embodiments is a GPS identifier indicating the identifier of the corresponding GPS (eg, gps_id or gps_geom_parameter_set_id in FIG. 21) and/or an SPS identifier (eg, sps_id or FIG. 21) for referring to the SPS. Gps_seq_parameter_set_id). The SPS identifier for referring to the SPS refers to information for identifying which SPS the corresponding GPS belongs to.

For example, the APS according to the embodiments is an APS identifier (e.g., aps_id or aps_geom_parameter_set_id of FIG. 22) indicating an identifier of the corresponding APS and/or an SPS identifier (e.g., sps_id or FIG. 22) for referring to the SPS. Aps_seq_parameter_set_id). The SPS identifier for referencing the SPS means information for identifying which SPS the corresponding APS belongs to.

The geometry data Geom according to embodiments includes an identifier indicating an active GPS to which the geometry data Geom belongs. For example, the Geometry Slice Header (GSH) of the geometry data Geo according to the embodiments includes information indicating the identifier of the geometry data Geo. The information indicating the identifier of the corresponding geometry data (Geom) may include an identifier of a tile to which the corresponding Geom belongs and/or an identifier of a slice (eg, gsh_tile_id and/or gsh_slice_id of FIG. 23 ). The GSH (Geometry Slice Header) of the geometry data (Geom) according to the embodiments includes a GPS identifier (for example, gps_id or gsh_geometry_parameter_set_id of FIG. 23) for referring to GPS related to a corresponding slice or tile. The GPS identifier for referring to the GPS refers to information for identifying which GPS the corresponding Geom belongs to or is signaled by which GPS.

The attribute data Attr according to embodiments includes an identifier indicating an active APS to which the corresponding attribute data Attr belongs. For example, an ASH (Attribute Slice Header) of the attribute data Attr according to embodiments includes information indicating an identifier of the corresponding attribute data Attr. Information indicating the identifier of the corresponding attribute data Attr may include the identifier of the SPS to which the corresponding Attr belongs (eg, ash_attr_sps_attr_idx in FIG. 23 ). The ASH (Attribute Slice Header) of the attribute data (Attr) according to the embodiments includes an APS identifier (eg, aps_id or ash_attribute_parameter_set_id of FIG. 23) for referencing an APS related to a corresponding slice or tile. The APS identifier for referencing the APS means information for identifying which APS the corresponding Attr belongs to or which APS is signaled by.

The Attribute Slice Header (ASH) of the attribute data Attr according to the embodiments refers to a geometry data identifier (eg, geometry_id or FIG. 23) for referencing the geometry data Geom corresponding to the corresponding attribute data Attr. ash_attr_geom_slice_id) may be further included.

21 illustrates a Sequence Parameter Set (SPS), a Tile Parameter Set (TPS), and a Geometry Parameter Set (GPS) according to embodiments.

The bitstream (or bitstream received by the point cloud data receiving device) transmitted by the point cloud data transmission device according to the embodiments is SPS (Sequence Parameter Set, 21000), one or more TPS (Tile Parameter Set, 21001) And/or one or more GPS (Geometry Parameter Set, 21002). The SPS according to the embodiments means the SPS of FIGS. 19 and 20. TPS according to the embodiments means the TPS of FIGS. 19 and 20. The GPS according to embodiments refers to the GPS of FIGS. 19 and 20.

SPS (21000) in accordance with the embodiments include, for example, profile_idc, profile_compatibility_flags, sps_bounding_box_present_flag, sps_bounding_box_offset_x, sps_bounding_box_offset_y, sps_bounding_box_offset_z, sps_bounding_box_scale_factor, sps_bounding_box_size_width, sps_bounding_box_size_height, sps_bounding_box_size_depth, sps_source_scale_factor, sps_seq_parameter_set_id, sps_num_attribute_sets, attribute_dimension [i], attribute_instance_id [i], attribute_bitdepth[ i ], attribute_cicp_colour_primaries[ i ], attribute_cicp_transfer_characteristics[ i ], attribute_cicp_matrix_coeffs[ i ], attribute_cicp_video_full_range_flag[ i ], known_attribute_label_flag[ i ], known_attribute_label_flag[ i ], known_attribute_label_flag[i], known_attribute_label_flag[i], attribute_extens_label_flag, attribute_data_extens_flag

profile_idc may mean information indicating a profile of a bitstream that can satisfy Annex A of the H.264 standard document. Other values of profile_idc may be used later by ISO/IEC. (indicates a profile to which the bitstream conforms as specified in Annex A. Bitstreams shall not contain values of profile_idc other than those specified in Annex A. Other values of profile_idc are reserved for future use by ISO/IEC.)

If profile_compatibility_flags is 1, it may indicate that the corresponding bitstream satisfies a profile whose profile_idc is j according to Annex A. The value of profile_compatibility_flag[ j] may be 0 when j is not a value defined according to Annex A. (equal to 1, indicates that the bitstream conforms to the profile indicated by profile_idc equal to j as specified in Annex A. The value of profile_compatibility_flag[ j] shall be equal to 0 for any value of j that is not specified as an allowed value of profile_idc in Annex A.)

level_idc represents the level of a bitstream that can satisfy Annex A of the H.264 standard document. The bitstream is different from the information defined in Annex A of the H.264 standard document and does not have a value of level_idc. Other values of Level_idc are reserved for later by ISO/IEC. (indicates a level to which the bitstream conforms as specified in Annex A. Bitstreams may not contain values of level_idc other than those specified in Annex A. Other values of level_idc are reserved for future use by ISO/IEC.)

sps_bounding_box_present_flag may be 1 when bounding box offset and size information are signaled. (equal to 1 specifies the bounding box offset and size information is signalled.sps_bounding_box_present_flag equal to 0 specifies)

sps_bounding_box_offset_x represents the x offset of the original bounding box in the Cartesian coordinate system. If the information does not exist, the value of this parameter may be 0. (indicates the x offset of the source bounding box in the cartesian coordinates.When not present, the value of sps_bounding_box_offset_x is inferred to be 0.)

sps_bounding_box_offset_y represents the y offset of the original bounding box in the Cartesian coordinate system. If the information does not exist, the value of this parameter may be 0. (indicates indicates the y offset of the source bounding box in the cartesian coordinates.When not present, the value of sps_bounding_box_offset_y is inferred to be 0.)

sps_bounding_box_offset_z represents the z offset of the original bounding box in the Cartesian coordinate system. If the information does not exist, the value of this parameter may be 0. (indicates indicates the z offset of the source bounding box in the Cartesian coordinates.When not present, the value of sps_bounding_box_offset_z is inferred to be 0.)

sps_bounding_box_scale_factor represents the scale factor of the original bounding box in the Cartesian coordinate system. If the corresponding information does not exist, the value of this parameter may be 1 or 0. (indicates the scale factor the source bounding box in the Cartesian coordinates.When not present, the value of sps_bounding_box_scale_factor is inferred to be 1. Indicates.When not present, the value of sps_bounding_box_scale_factor is inferred to be 0.)

sps_bounding_box_size_width represents the width of the original bounding box in the Cartesian coordinate system. When the corresponding information does not exist, the value of sps_bounding_box_size_width may be a specific value such as 10. (indicates the width of the source bounding box in the Cartesian coordinates.... When not present, the value of sps_bounding_box_size_width is inferred to be a specific value (such as 10).)

sps_bounding_box_size_height represents the height of the original bounding box in the Cartesian coordinate system. If the corresponding information does not exist, the value of sps_bounding_box_size_height may be 1 or 0. (indicates the height of the source bounding box in the Cartesian coordinates.When not present, the value of sps_bounding_box_size_height is inferred to be 1.When not present, the value of sps_bounding_box_size_hieght is inferred to be 0.)

sps_bounding_box_size_depth represents the depth of the original bounding box in the Cartesian coordinate system. If the corresponding information does not exist, the value of sps_bounding_box_size_height may be 1 or 0. (indicates the depth of the source bounding box in the Cartesian coordinates.When not present, the value of sps_bounding_box_size_depth is inferred to be 1.When not present, the value of sps_bounding_box_size_depth is inferred to be 0.)

sps_source_scale_factor represents the scale factor of the original point cloud. (indicates the scale factor of the source point cloud.)

sps_seq_parameter_set_id represents id information on SPS referenced by other syntax elements. sps_seq_parameter_set_id may be set to a value from 0 to 15 within a range that satisfies conditions in the specification of the corresponding version. As information other than 0, sps_seq_parameter_set_id may be used later by ISO/IEC. (provides an identifier for the SPS for reference by other syntax elements.In The value of sps_seq_parameter_set_id may be in the range of 0 to 15, inclusive in bitstreams conforming to this version of this Specification.. The value other than 0 for sps_seq_parameter_set_id is reserved for future use by ISO/IEC.)

sps_num_attribute_sets represents the number of coded attributes in the bitstream. sps_seq_parameter_set_id can range from 0 to 64. (indicates the number of coded attributes in the bitstream.The value of sps_num_attribute_sets may be in the range of 0 to 64.)

attribute_dimension[ i] represents the number of components of the i-th attribute. (specifies the number of components of the i-th attribute.)

attribute_instance_id[ i] represents the attribute instance id. (specifies attribute instance id.)

attribute_bitdepth[i] represents bitdepth information of the i-th attribute signal(s). (specifies the bitdepth of the i-th attribute signal(s).)

attribute_cicp_colour_primaries[ i] represents the chromaticity of the color attribute source primary. (indicates the chromaticity coordinates of the color attribute source primaries.)

attribute_cicp_transfer_characteristics[ i] represents the reference optoelectronic transfer characteristic function of a color attribute, consisting of Lc, the original input linear optical intensity, and a nominal real-value between 0 and 1. Alternatively, this parameter may represent the inverse of a reference optoelectronic transfer characteristic function, consisting of a nominal real-value ranging from 0 to 1, Lo, which is an output linear optical intensity. (either indicates the reference opto-electronic transfer characteristic function of the color attribute as a function of a source input linear optical intensity Lc with a nominal real-valued range of 0 to 1 or indicates the inverse of the reference electro-optical transfer characteristic function as a function of an output linear optical intensity Lo with a nominal real-valued range of 0 to 1.)

attribute_cicp_matrix_coeffs[i] represents the luma and chroma signals matrix coefficients of green, blue, and red (or three primary colors of Y, Z, and X). (describes the matrix coefficients used in deriving luma and chroma signals from the green, blue, and red, or Y, Z, and X primaries.)

attribute_cicp_video_full_range_flag[i] represents the range of black level and luma and saturation signals derived from E'Y, E'PB and E'PR or E'R, E'G and E'B real-value component signals. (specifies indicates the black level and range of the luma and chroma signals as derived from E'Y, E'PB, and E'PR or E'R, E'G, and E'B real-valued component signals.)

When known_attribute_label_flag[i] is 1, it indicates that know_attribute_label is signaled for the i-th attribute. When the corresponding parameter is 0, it indicates that attribute_label_four_bytes is signaled for the i-th attribute. (equal to 1 specifies know_attribute_label is signalled for the i-th attribute. known_attribute_label_flag[ i] equal to 0 specifies attribute_label_four_bytes is signaled for the i-th attribute.)

If known_attribute_label[i] is 0, it indicates that the attribute is a color. When the parameter is 1, the attribute indicates reflectance. When the corresponding parameter is 2, the attribute indicates a frame index. (equal to 0 specifies the attribute is colour. known_attribute_label[ i] equal to 1 specifies the attribute is reflectance. known_attribute_label[ i] equal to 2 specifies the attribute is farme index.)

When sps_extension_present_flag is 1, it indicates that sps_extension_data exists in the SPS RBSP syntax structure. If the parameter is 0, it indicates that the corresponding syntax structure does not exist. If not present, a value of sps_extension_present_flag may be 0. (equal to 1 specifies that the sps_extension_data syntax structure is present in the SPS RBSP syntax structure. sps_extension_present_flag equal to 0 specifies that this syntax structure is not present.When not present, the value of sps_extension_present_flag is inferred to be equal to 0.)

sps_extension_data_flag can have any value. The presence of this parameter does not affect the behavior of the profile presented in Annex A of the corresponding standard document of the decoder. (may have any value. Its presence and value do not affect decoder conformance to profiles specified in Annex A Decoders conforming to a profile specified in Annex A.)

TPS 21001 according to embodiments may be, for example, num_tiles, tile_bounding_box_offset_x[ i ], tile_bounding_box_offset_y[ i ], tile_bounding_box_offset_z[ i ], tile_bounding_box_scale_factor[ i ], tile_bounding_box_size_width_box_size_box_height_box_size[i_deight_box] It may include.

num_tiles represents the number of tiles existing in the corresponding bitstream. (Represents the number of tiles signaled for the bitstream). If no tiles exist in the corresponding bitstream, num_tiles may be signaled as 0. (When not present, num_tiles is inferred to be 0)

tile_bounding_box_offset_x[i] indicates the x offset of the i-th tile in the cartesian coordinates. If the corresponding x offset does not exist, the value of tile_bounding_box_offset_x[ 0] may be sps_bounding_box_offset_x. (When not present, the value of tile_bounding_box_offset_x[ 0] is inferred to be sps_bounding_box_offset_x.)

tile_bounding_box_offset_y[i] indicates the y offset of the i-th tile in the cartesian coordinates. If the corresponding y offset does not exist, the value of tile_bounding_box_offset_y[ 0] may be sps_bounding_box_offset_y. (When not present, the value of tile_bounding_box_offset_y[ 0] is inferred to be sps_bounding_box_offset_y.)

tile_bounding_box_offset_z[i] represents the z offset of the i-th tile in the Cartesian coordinate system. (indicates indicates the z offset of the i-th tile in the Cartesian coordinates.) If the corresponding z offset does not exist, the value of tile_bounding_box_offset_z[ 0] may be sps_bounding_box_offset_z. (When not present, the value of tile_bounding_box_offset_z[ 0] is inferred to be sps_bounding_box_offset_z.)

tile_bounding_box_scale_factor[i] represents a scale factor related to the i-th tile in the Cartesian coordinate system. (indicates the scale factor the i-th tile in the Cartesian coordinates.) If the corresponding scale factor does not exist, tile_bounding_box_scale_factor[ 0] may be sps_bounding_box_scale_factor. (When not present, the value of tile_bounding_box_scale_factor[ 0] is inferred to be sps_bounding_box_scale_factor.)

tile_bounding_box_size_width[ i] represents the width of the i-th tile in the Cartesian coordinate system. (indicates the width of the i-th tile in the Cartesian coordinates.) If the width value does not exist, tile_bounding_box_size_width[ 0] may be sps_bounding_box_size_width. (When not present, the value of tile_bounding_box_size_width[ 0] is inferred to be sps_bounding_box_size_width.)

tile_bounding_box_size_height[ i] represents the height of the i-th tile in the Cartesian coordinate system. (indicates the height of the i-th tile in the Cartesian coordinates.) If the height value does not exist, tile_bounding_box_size_height[ 0] may be sps_bounding_box_size_height. (When not present, the value of tile_bounding_box_size_height[ 0] is inferred to be sps_bounding_box_size_height.)

tile_bounding_box_size_depth[i] represents the depth of the i-th tile in the Cartesian coordinate system. (indicates the depth of the i-th tile in the Cartesian coordinates.) If the height value does not exist, tile_bounding_box_size_depth[ 0] may be sps_bounding_box_size_depth. (When not present, the value of tile_bounding_box_size_depth[ 0] is inferred to be sps_bounding_box_size_depth.)

GPS (21002) according to the embodiments is an example, gps_geom_parameter_set_id, gps_seq_parameter_set_id, geometry_coding_type, gps_box_present_flag, unique_geometry_points_flag, neighbour_context_restriction_flag, inferred_direct_coding_mode_enabled_flag, bitwise_occupancy_coding_flag, child_neighbours_enabled_flagfalse_neighbour_removal_enabled_flag, adjacent_child_contextualisation_enabled_flag, geom_occupancy_ctx_reduction_factor, log2_neighbour_avail_boundary, log2_intra_pred_max_node_size, log2_trisoup_node_size, trisoup_depth, trisoup_triangle_level, gps_extension_present_flag, gps_extension_data_flag Can include.

gps_geom_parameter_set_id represents the identifier of the GPS referenced by other syntax elements. The value of this parameter may be 0 to 15. (provides an identifier for the GPS for reference by other syntax elements.The value of gps_seq_parameter_set_id may be in the range of 0 to 15, inclusive.)

gps_seq_parameter_set_id represents the value of sps_seq_parameter_set_id for the active SPS. The corresponding value may be 0 to 15. (specifies the value of sps_seq_parameter_set_id for the active SPS.The value of gps_seq_parameter_set_id shall be in the range of 0 to 15, inclusive.)

geometry_coding_type may mean a coding type for geometry information. The value of the parameter may be 0 to 1, and other values may be used later by ISO/IEC. The decoder can ignore if the parameter has a different value. For example, if the parameter is 0, it may indicate an octree, and if it is 1, it may indicate a triangle soup (trisoup). (indicates that the coding type for the geometry in Table 7 1 Table 7 1 for the given value of geometry_coding_type. The value of geometry_coding_type shall be equal to 0 or 1 in bitstreams conforming to this version of this Specification.Other values of geometry_coding_type are reserved for future use by ISO/IEC.Decoders conforming to this version of this Specification may ignore reserved values of geometry_coding_type. 0= Octree, 1=Triangle Soup (Trisoup))

gps_box_present_flag may be 1 when additional bounding box information is provided in a geometry header within a corresponding GPS. This parameter may represent 0 when additional bounding box information is not provided in the geometry header. (equal to 1 specifies an additional bounding box information is provided in a geometry header that references the current GPS. gps_bounding_box_present_flag equal to 0 specifies that additional bounding box information is not signalled in the geometry header.)

unique_geometry_points_flag may be 1 when all the output points have unique positions. This parameter may be 0 when the output points exist at the same location. (equal to 1 indicates that all output points have unique positions. unique_geometry_points_flag equal to 0 indicates that the output points may have same positions.)

When neighbor_context_restriction_flag is 0, it indicates that octree occupancy coding uses contexts determined based on six neighboring nodes. If 1, it indicates that octree occupancy coding uses contexts determined based only on sibling nodes. (equal to 0 indicates that octree occupancy coding uses contexts determined from six neighboring parent nodes.neighbour_context_restriction_flag equal to 1 indicates that octree coding uses contexts determined from sibling nodes only.)

When inferred_direct_coding_mode_enabled_flag is 0, it indicates that octree coding uses inferred_direct_coding_mode. If 1, it indicates that octree coding is performed using a plurality of contexts determined from sibling neighbor nodes. (equal to 0 indicates the octree coding uses inferred_direct_coding_mode. inferred_direct_coding_mode_enabled_flag equal to 1 indicates the octree coding uses multiple context determined from sibling neighboring nodes.)

log2_neighbour_avail_boundary represents the value of NeighbAvailBoundary used by the decoding process as follows. (specifies the value of the variable NeighbAvailBoundary that is used in the decoding process as follows:)

NeighbAvailBoundary = 2log2_neighbour_avail_boundary

When neighbour_context_restriction_flag is 1, neighbour_context_restriction_flag may be 13. (When neighbor_context_restriction_flag is equal to 1, NeighbAvailabilityMask is set equal to 13.) When neighbor_context_restriction_flag is 0, NeighbAvailabilityMask can be determined as follows. (Otherwise, neighbor_context_restriction_flag equal to 0, NeighbAvailabilityMask is set equal to)

(1 << log2_neighbour_avail_boundary).

log2_trisoup_node_size represents TrisoupNodeSize as the size of triangle nodes determined as follows. (specifies the variable TrisoupNodeSize as the size of the triangle nodes as follows.)

TrisoupNodeSize = 2log2_trisoup_node_size

The value of log2_trisoup_node_size can be greater than 0. When the size of log2_trisoup_node_size is 0, it may indicate that the geometry bitstream includes only octree coding syntax. (The value of log2_trisoup_node_size may be equal to or greater than 0.When log2_trisoup_node_size is equal to 0, the geometry bitstream includes only the octree coding syntax.)

trisoup_depth represents the number of bits used to represent each component of point coordinates. trisoup_depth can have a value from 2 to 21. (specifies the number of bits used to represent each component of a point coordinate. The value of trisoup_depth may be in the range of 2 to 21. [Ed(df): 21 should perhaps be a level limit].)

trisoup_triangle_level represents the level at which the octree is pruned. trisoup_triangle_level can have a value of 1 to trisoup_depth-1. (specifies the level at which the octree is pruned.The value of trisoup_triangle_level may be in the range of 1 to trisoup_depth-1.)

If gps_extension_present_flag is 1, it indicates that the gps_extension_data syntax structure exists in the GPS RBSP syntax structure. If 0, it indicates that the corresponding syntax structure does not exist. (equal to 1 specifies that the gps_extension_data syntax structure is present in the GPS RBSP syntax structure. gps_extension_present_flag equal to 0 specifies that this syntax structure is not present.When not present, the value of gps_ extension_present_flag is inferred to be equal to 0.)

gps_extension_data_flag can have any value. If the value is present, the value does not affect the decoder. (may have any value. Its presence and value do not affect decoder conformance to profiles specified in Annex A. Decoders conforming to a profile specified in Annex A.)

22 shows an attribute parameter set (APS) according to embodiments.

The bitstream (or bitstream received by the point cloud data receiving device) transmitted by the point cloud data transmission device according to the embodiments includes one or more Attribute Parameter Sets (APS). APS according to embodiments means the APS of FIGS. 19 and 20.

APS according to the embodiments may include, for example, aps_attr_parameter_set_id, aps_seq_parameter_set_id, attr_coding_type, num_pred_nearest_neighbours, max_num_direct_predictors, lifting_search_range lifting_quant_step_size, lifting_quant_step_size_chroma, lod_binary_tree_enabled_flag, sampling_distance_squared [idx], adaptive_prediction_threshold, raht_depth, raht_binarylevel_threshold, raht_quant_step_size, aps_extension_present_flag, aps_extension_data_flag.

aps_attr_parameter_set_id represents the identifier (id) of the APS for reference by other syntax elements. This parameter may have a value of 0 to 15. (provides an identifier for the APS for reference by other syntax elements.The value of aps_attr_parameter_set_id may be in the range of 0 to 15, inclusive.)

aps_seq_parameter_set_id represents the value of sps_seq_parameter_set_id for the currently active SPS. aps_seq_parameter_set_id may have a value of 0 to 15. (specifies the value of sps_seq_parameter_set_id for the active SPS.The value of aps_seq_parameter_set_id may be in the range of 0 to 15, inclusive.)

attr_coding_type represents the coding type for an attribute. The value of the parameter may be 0, 1, or 2. Other values of this parameter may be used later by ISO/IEC. For example, if attr_coding_type=0, a coding type based on the prediction weight lifting method, if attr_coding_type=1, a coding type based on a Region Adaptive Hierarchical Transform (RAHT) method, and if attr_coding_type=2, a fixed weight lifting ( Fixed weight lifting) method based coding type. (indicates that the coding type for the attribute in Table 7 2 Table 7 2 for the given value of attr_coding_type. The value of attr_coding_type shall be equal to 0, 1, or 2 in bitstreams conforming to this version of this Specification.Other values of attr_coding_type. are reserved for future use by ISO/IEC.Decoders conforming to this version of this Specification shall ignore reserved values of attr_coding_type. 0 = Predicting weight lifting, 1 = Region Adaptive Hierarchical Transferm (RAHT), 2= Fixed weight lifting)

num_pred_nearest_neighbours represents information on the maximum value of the number of near-list neighbors used to perform prediction. The value of numberOfNearestNeighboursInPrediction may have a value of 1 to xx. (specifies the maximum number of nearest neighbors to be used for prediction.The value of numberOfNearestNeighboursInPrediction may be in the range of 1 to xx.)

max_num_direct_predictors represents information on the maximum value of the number of predictors used for direct prediction. max_num_direct_predictors may have a value of 0 to num_pred_nearest_neighbours. The value of the variable MaxNumPredictors used in the point cloud data decoding process according to the embodiments may be expressed as follows. (specifies the maximum number of predictor to be used for direct prediction. The value of max_num_direct_predictors shall be range of 0 to num_pred_nearest_neighbours. The value of the variable MaxNumPredictors that is used in the decoding process as follows:)

MaxNumPredictors = max_num_direct_predicots + 1

lifting_search_range represents the search range for lifting. (specifies search range for the lifting.)

lifting_quant_step_size represents the quantization step size for the first component of the attribute. The corresponding value may have a value of 1 to xx. (specifies the quantization step size for the 1st component of the attribute.The value of quant_step_size may be in the range of 1 to xx.)

lifting_quant_step_size_chroma represents the quantization step size for the chroma component of the attribute when the attribute is color. The value of quant_step_size_chroma may be 1 to xx. (specifies the quantization step size for the chroma component of the attribute when the attribute is colour.The value of quant_step_size_chroma may be in the range of 1 to xx.)

lod_binary_tree_enabled_flag indicates whether or not the binary tree is enabled for log generation. (specifies whether binary tree is enable or not for the log generation.)

num_detail_levels_minus1 represents the number of level-of-detail (LOD) for attribute coding. The value of num_detail_levels_minus1 may be 0 to xx. (specifies the number of levels of detail for the attribute coding.The value of num_detail_levels_minus1 may be in the range of 0 to xx.)

sampling_distance_squared [idx] represents the square of the sampling distance for idx. The value of sampling_distance_squared may be 0 to xx. (specifies the square of the sampling distance for idx.The value of sampling_distance_squared may be in the range of 0 to xx.)

adaptive_prediction_threshold represents the prediction threshold. (specifies the threshold of prediction.)

raht_depth represents the number of levels of RAHT. depthRAHT may have a value of 1 to xx. (specifies the number of levels of detail for RAHT.The value of depthRAHT may be in the range of 1 to xx.)

raht_binarylevel_threshold represents levels of details to cut out the RAHT coefficient. The value of binaryLevelThresholdRAHT may have a value of 0 to xx. (specifies the levels of detail to cut out the RAHT coefficient.The value of binaryLevelThresholdRAHT shall be in the range of 0 to xx.)

raht_quant_step_size represents the quantization step size for the first component of the attribute. The corresponding value may be 1 to xx. (specifies the quantization step size for the 1st component of the attribute.The value of quant_step_size may be in the range of 1to xx.)

When aps_extension_present_flag is 1, it indicates that the aps_extension_data syntax structure exists in the APS RBSP syntax structure. If 0, it indicates that the corresponding syntax structure does not exist. If not present, aps_extension_present_flag may be 0. (equal to 1 specifies that the aps_extension_data syntax structure is present in the APS RBSP syntax structure. aps_extension_present_flag equal to 0 specifies that this syntax structure is not present.When not present, the value of aps_ extension_present_flag is inferred to be equal to 0.)

aps_extension_data_flag can have any value. If the value is present, the value does not affect the decoder. (may have any value. Its presence and value do not affect decoder conformance to profiles specified in Annex A. Decoders conforming to a profile specified in Annex A.)

23 illustrates a geometry slice header (GSH) and an attribute slice header (ASH) according to embodiments.

The bitstream (or bitstream received by the point cloud data receiving device) transmitted by the point cloud data transmission device according to the embodiments may include one or more slices. The slice may include a geometry slice and an attribute slice. The geometry slice includes a geometry slice header (GSH). The attribute slice includes an attribute slice header (ASH). The geometry slice header 23000 according to the embodiments may mean the geometry slice header 19005a-1 of FIG. 19.

The geometry slice header (GSH, Geometry Slice Header, 23000) can include gsh_geometry_parameter_set_id, gsh_tile_id, gsh_slice_id, gsh_box_log2_scale, gsh_box_origin_x, gsh_box_origin_y, gsh_box_origin_z, gsh_box_origin_z, gsh_log2_max_number, and gsh_log2_max.

gsh_geometry_parameter_set_id represents the value of gps_geom_parameter_set_id of active GPS. (specifies the value of the gps_geom_parameter_set_id of the active GPS.)

gsh_tile_id represents the id of a tile. (specifies id of tile.)

gsh_slice_id represents the id of a slice. (specifies id of slice.)

gsh_box_log2_scale represents the scale value. (specifies scale value.)

gsh_box_origin_x represents x coordinate information of the source bounding box in the Cartesian coordinate system. (specifies the x of the source bounding box in the cartesian coordinates.)

gsh_box_origin_y represents y coordinate information of the source bounding box in the Cartesian coordinate system. (specifies the y of the source bounding box in the cartesian coordinates.)

gsh_box_origin_z represents z coordinate information of the source bounding box in the Cartesian coordinate system. (specifies the z of the source bounding box in the cartesian coordinates.)

gsh_log2_max_nodesize represents the value of MaxNodeSize at which the decoding process is performed as follows. (specifies the value of the variable MaxNodeSize that is used in the decoding process as follows:)

MaxNodeSize = 2 (gbh_log2_max_nodesize)

gbh_points_number represents the number of coded points in a slice. (specifies the number of coded points in the slice.)

The attribute slice header (ASH, Attribute Slice Header, 23001) may include abh_attr_parameter_set_id, abh_attr_sps_attr_idx, abh_attr_geom_slice_id.

abh_attr_parameter_set_id represents the value of aps_attr_parameter_set_id of the current active APS. (specifies the value of the aps_attr_parameter_set_id of the active APS.)

abh_attr_sps_attr_idx represents an attribute set in the currently active SPS. A value of abh_attr_sps_attr_idx may range from 0 to a value of sps_num_attribute_setsd of the current active SPS. (specifies the attribute set in the active SPS. The value of abh_attr_sps_attr_idx may be in the range of 0 to sps_num_attribute_sets in the active SPS.)

abh_attr_geom_slice_id represents the value of the geometry slice id. (specifies the value of geom slice id.)

The point cloud data transmission apparatus according to embodiments may transmit point cloud data a bitstream having a bitstream structure shown in FIGS. 19 to 23. Point cloud data can be divided into Category 1 and Category 3 according to the characteristics of the data. Category 1 data is static data and is composed of one frame. Category 3 data is dynamic data and is composed of N frames.

A point according to embodiments may include attribute information (attribute information) including location information (geometry information) and color information, reflectivity information, time information, and normal vector information of the corresponding point. Points according to embodiments may include various information according to a condition to be expressed. Category 1 and Category 3 data consisting of points may include a frame including a large amount of points. However, when the point cloud data transmission apparatus according to the embodiments receives and encodes a frame including these points, there is a problem that a lot of delay time and unnecessary resources are used.

Accordingly, the point cloud data transmission apparatus according to the embodiments includes point cloud data in order to perform a transmission operation of point cloud data, an encoding operation, a decoding operation of the receiving device, and a rendering processing operation of the receiving device in real time and at the same time to be processed with low latency May be divided into a plurality of coding units.

The point cloud data transmission apparatus according to embodiments may divide a frame of point cloud data into a tile, a slice, or the like as coding units. The point cloud data transmission apparatus according to embodiments may perform encoding in units of divided tiles and/or slices. Accordingly, when the point cloud data is divided into tiles and slices, information related to encoding is independently or non-independently provided for each of the divided tiles and/or slices. It needs to be signaled. Accordingly, the bitstream transmitted by the point cloud data transmission apparatus according to the embodiments may be structured by various methods.

The bitstream transmitted by the point cloud data transmission device includes a first structure for independently or non-independently performing encoding by dividing point cloud data into one or more slices, and one or more point cloud data. Divided into more than one tile, and the tile may be configured according to a second structure and a third structure divided into one or more slices. The first to third structures will be described later in FIGS. 24 to 34.

The point cloud data transmission apparatus and reception apparatus according to the embodiments may prevent errors accumulated in the encoding and decoding process by performing encoding and decoding independently or non-independently in a slice unit.

24 shows a point cloud encoder according to embodiments.

The point cloud encoder according to the embodiments includes a data characteristic investigation unit 24000, a brick tiling unit 24001, a divided data input unit 24002, a coordinate conversion unit 24003, a quantization/voxelization processing unit 24004, and an octree occupan. City code generation unit 24005, surface model processing unit 24006, first Arithmetic coder 24007, geometry reconstruction unit 2408, color conversion processing unit 2409, attribute conversion processing unit 24010, prediction/lifting/RAHT A transform processing unit 24011, a coefficient quantization processing unit 24012, a second arithmetic coder 24013, and/or a bitstream combiner 24014 may be included.

The point cloud data encoder according to the embodiments shows an example of the point cloud data encoder 18000 according to the embodiments of FIG. 18. An encoder and an encoder according to embodiments may be referred to as an encoder, and a decoder, and a decoder may be referred to as a decoder.

The data characteristic survey unit 24000 receives point cloud data according to embodiments and examines the characteristics of the received point cloud data.

The brick tiling unit 24001 receives point cloud data according to embodiments, and stores the received point cloud data with one or more tiles, one or more slices, or one or more bricks. ). That is, the brick tiling unit 19001 may divide the point cloud data into tiles, slices, or bricks. The brick tiling unit 19001 outputs point cloud data divided in units of tiles, slices, or bricks.

A tile may mean a partial area of a 3D space occupied by point cloud data according to embodiments. A tile according to embodiments may include one or more slices. The tile according to the embodiments is divided into one or more slices, so that the point cloud data encoder may encode the point cloud data in parallel. The point cloud data encoder may perform quantization and/or transformation differently according to the characteristics of data for each of one or more slices of a tile according to embodiments.

A slice may mean a unit of data that the device for transmitting and receiving point cloud data according to the embodiments performs encoding and decoding. A slice may mean a set of data in a 3D space occupied by point cloud data, or may mean a set of some data among point cloud data. A slice may mean an area of points or a set of points included in a tile according to embodiments. A tile according to embodiments may be divided into one or more slices based on the number of points included in one tile. For example, one tile may mean a set of points divided by the number of points. A tile according to embodiments may divide a slice based on the number of points, and some data may be split or merged during the segmentation process.

Brick may mean a block or slice according to embodiments. That is, a brick may mean a set or region of points for dividing slice or point cloud data. According to embodiments, a brick may be referred to as an area.

According to embodiments, the point cloud data transmission apparatus may perform the brick tiling unit when the brick_tiling_filter is turned on after processing the data characteristic investigation unit. Each data unit divided into bricks may exist as N bricks in the divided data input unit, and encoding is performed by being divided into position values and attribute values. After the encoding process is performed in N bricks, a process of combining into one bitstream in a bitstream combiner may be performed.

According to embodiments, the point cloud data transmission apparatus may perform the brick tiling unit when the brick_tiling_filter is turned on after processing the data characteristic investigation unit. Each data unit divided into bricks may exist as N bricks in the divided data input unit, and encoding is performed by being divided into position values and attribute values. After the encoding process is performed in N bricks, a process of combining into one bitstream in a bitstream combiner may be performed.

According to embodiments, the point cloud data may be divided into a plurality of slices. There may be several methods of dividing the point cloud data into a plurality of slices. Point cloud data included in a slice according to embodiments may be independently encoded. The point cloud data transmission device and the reception device according to the embodiments may independently or non-independently perform encoding and decoding in units such as slices and tiles, thereby reducing errors accumulated in the encoding and decoding process. Can be prevented.

A slice may mean a unit for dividing a point cloud frame in point cloud data for encoding. The point cloud data may be divided into a plurality of slices according to a slice-partitioning scheme.

According to embodiments of a method of dividing point cloud data into a plurality of slices, there may be a method of dividing based on variance information of color information in order to ensure color continuity. For example, if distribution information of color information in a specific point cloud or area of point cloud data is greater than the first threshold value, the data or area is regarded as a non-smooth block, and the entire point cloud data If the weight of the non-smooth block is greater than the second threshold value, blocks corresponding to the non-smooth block (or some points included in the non-smooth block) can be extracted and separated into a first slice, The remaining unseparated cloud data may be divided into a second slice. According to embodiments, dispersion information of color information may be calculated to separate the first slice and the second slice, and kd-tree may be used as the dispersion information of the color information.

A k-d tree (kd tree) according to embodiments is a type of binary tree and represents a hierarchy for partitioning a k-dimensional space. The Kd-tree scheme refers to a method of performing geometry-adaptive division of point cloud data into slices.

According to embodiments, a slice may be referred to in various terms such as a brick, a block, a macroblock, and/or a tile. According to embodiments, one or more slices may be included in one tile.

The divided data input unit 24002 receives the divided point cloud data output by the brick tiling unit 24001. The divided data input unit 24002 outputs location information (geometry information) and attribute information (attribute information) of points in each of the bricks (or slices or tiles). The divided data input unit 24002 transfers the location information of points in brick units (or in slices or tiles) to the coordinate conversion unit 24003, and transfers attribute information of the points to the color conversion processing unit 24009.

The data characteristic investigation unit 24000, the brick tiling unit 24001, and/or the divided data input unit 24002 according to the embodiments may be included in the spatial division unit 18001 of FIG. 18.

The coordinate conversion unit 24003 may receive location information (geometry information) of points according to embodiments, and may convert coordinate information thereof. The coordinate conversion unit 24003 may transfer the converted coordinate information to the quantization/voxelization processing unit 24004. The coordinate conversion unit 24003 may perform operations of the coordinate conversion unit 40000 of FIG. 4 and the quantization processing unit 24001 of FIG. 12.

The quantization/voxelization processing unit 24004 may perform quantization and/or voxelization on the location information of points by the coordinate conversion unit 24003.

Quantize is to determine a value for matching geometric information (position information) of points according to embodiments to a voxel. The quantization/voxelization processing unit 24004 may perform quantization as described with reference to FIGS. 4 to 6.

Voxelize refers to mapping geometry information (position information) of points according to embodiments into a voxel. The voxel refers to a three-dimensional cubic space generated when a three-dimensional space is divided into units (unit = 1.0) based on axes (eg, X-axis, Y-axis, and Z-axis) representing the three-dimensional space. The quantization/voxelization processing unit 24004 may perform voxelization as described with reference to FIGS. 4 to 6.

The point cloud data transmission method/apparatus (or quantization/voxelization processing unit 24004) according to embodiments converts point cloud data divided by a brick tiling unit 24001, or a spatial division unit, into a brick or a tile ( Quantization and/or voxelization may be independently performed based on tile) or slice (slice).

The quantization/voxelization processor 24004 may transmit position information (geometry information) of points on which quantization and/or voxelization is performed to the octree occupancy code generator 24005. The quantization/voxelization processing unit 24004 may perform operations of the quantization and voxelization processing unit 40001 of FIG. 4 and the voxelization processing unit 12002 of FIG. 12.

The octree occupancy code generation unit 24005 may receive quantized and/or voxelized geometry information and generate an octree occupancy code based on the quantized and/or voxelized geometry information.

An octree is a set of geometric information of points according to embodiments, and is a data structure indicating occupied positions of points in a bounding box according to embodiments. The octree is a data structure representing geometric information (location information) of points included in a bounding box. The octree occupancy code may mean a data sequence in which an octree is represented by a binary code or the like. The octree and octree occupancy codes are described in FIGS. 4 to 7.

The point cloud data transmission method/apparatus (or octree occupancy code generation unit 24005) according to the embodiments may block point cloud data divided by a brick tiling unit 24001, or a spatial division unit, Quantization and/or voxelization may be independently performed based on a tile or a slice.

The octree occupancy code may include a data structure representing location information of points according to embodiments. The octree occupancy code generation unit 24005 may transmit the octree occupancy code to the first arithmetic coder 24007, the surface model processing unit 24006 and/or the geometry reconstruction unit 2408. The octree occupancy code generation unit 24005 may perform operations of the octree analysis unit 40002 of FIG. 4 and the octree occupancy code generation unit 12003 of FIG. 12.

The surface model processing unit 24006 may receive the octree occupancy code according to the embodiments and process the surface model. The surface model processing unit 24006 may output the surface model-processed geometry information and transmit it to the first arithmetic coder 24007. The surface model processing unit 24006 may perform operations of the surface aproxiation analysis unit 40003 of FIG. 4 and the surface model processing unit 12004 of FIG. 12.

The first arithmetic coder 24007 may receive an octree occupancy code according to embodiments and/or an octree occupancy code on which surface model processing has been performed, and encode them. The first arithmetic coder 24007 may output a geometry bitstream. The first arithmetic coder 24007 may transmit the geometry bitstream to the bitstream combiner. The first arithmetic coder 24007 may perform an arithmetic encoding 40004 of FIG. 4 and an arithmetic coder 12006 of FIG. 12.

The first arithmetic coder 24007 may transmit information related to whether encoding of geometry information for a corresponding brick (or slice or tile) is performed to the divided data input unit 24002.

The geometry reconstruction unit 2408 receives an octree occupancy code and/or an octree occupancy code that has been subjected to surface model processing according to embodiments, and reconstructs geometry information based on these. The geometry reconstruction unit 2408 may generate Molton codes according to embodiments, and may reconstruct geometry information based on them. The geometry reconstruction unit 2408 may perform an operation of the geometry reconstruction unit 40005 of FIG. 4.

The color conversion processor 2409 may receive attribute information of points according to embodiments and may convert color information of the attribute information. The color conversion processing unit may output the converted attribute information and transmit them to the attribute conversion processing unit 24010. The color conversion processing unit 2409 may perform operations of the color conversion unit 40006 of FIG. 4 and the color conversion processing unit 12008 of FIG. 12.

The attribute conversion processing unit 24010 includes position information of points according to embodiments, attribute information processed by color conversion by the color conversion processing unit 24009 according to embodiments, and/or reconstructed by the geometry reconstruction unit 24008. By mapping geometry information, attribute conversion processing can be performed. The attribute conversion processing unit 24010 may perform operations of the attribute transfer unit 40007 of FIG. 4 and the attribute conversion processing unit 12009 of 12.

The prediction/lifting/RAHT conversion processing unit 24011 may perform prediction, lifting, and/or transformation according to the RAHT method on the attribute information transformed by the attribute transformation processing unit 24010. The prediction/lifting/RAHT transformation processing unit 24011 may output attribute information transformed according to a prediction, lifting, and/or RAHT method, and may transmit them to the coefficient quantization processing unit 24012. The prediction/lifting/RAHT conversion processing unit 24011 performs an operation of the RAHT 40008, LOD generation unit 40009 and/or lifting 40010 of FIG. 4, and the prediction/lifting/RAHT conversion processing unit 12010 of FIG. can do.

The coefficient quantization processing unit 24012 may receive attribute information transformed by the prediction/lifting/RAHT transform processing unit 24011 and quantize them. The coefficient quantization processor 24012 may transmit the quantized attribute information to the second arithmetic coder 24013. The coefficient quantization processor 24012 may perform the operation of the coefficient quantization unit 40011 of FIG. 4.

The second arithmetic coder 24013 may receive attribute information quantized by the coefficient quantization processor 24012 and encode them. The second arithmetic coder 24013 may output an attribute bitstream including encoded attribute information. The second arithmetic coder 24013 may output attribute bitstreams and transmit them to the bitstream combiner 24014.

The second arithmetic coder 24013 may transmit information related to whether to perform encoding of attribute information for a corresponding brick (or slice or tile) to the divided data input unit 24002. The second arithmetic coder 24013 may perform operations of the arithmetic encoding unit 40012 of FIG. 4 and the arithmetic coder 12011 of FIG. 12.

The bitstream combiner 24014 may combine a geometry bitstream and/or an attribute information bitstream according to embodiments. The bitstream combiner 24014 may combine a geometry bitstream and an attribute bitstream in units of bricks (or slices or tiles) according to embodiments. The bitstream combiner 24014 may output a bitstream in which the geometry bitstream and the attribute bitstream are combined.

The point cloud data transmission apparatus according to the embodiments may include a data characteristic investigation unit 24000, a brick tiling unit 24001, a divided data input unit 24002, and a bitstream combining unit 24014. Point cloud data according to the embodiments is divided into N bricks by the brick tiling unit 24001 and input to the divided data input unit 24002. For each of the divided N bricks, point cloud data in each of the bricks is divided into position information of points and attribute information of points and encoded. When an encoding process is performed for each of the N bricks, position information of points and attribute information of points encoded by the bitstream combiner 24014 according to embodiments may be combined into one bitstream.

The point cloud data transmission apparatus according to the embodiments divides the point cloud data into one or more tiles using the brick tiling unit 24001, and encodes each region by performing encoding in the divided tile units. In this case, it is possible to efficiently perform encoding by dividing data of a region required for the point cloud data receiving apparatus according to the embodiments and a region of less importance. Accordingly, the point cloud data transmission apparatus can increase encoding efficiency due to this configuration.

The point cloud data transmission apparatus may provide an encoding method optimized for data characteristics by dividing the point cloud data into units of one or more tiles and performing encoding in units of the divided tiles. For example, in the case of point cloud data including points densely distributed in a specific area, an error that may occur during encoding may be reduced by dividing and encoding a densely distributed area of the points.

The point cloud data transmission device and the reception device according to the embodiments perform encoding and decoding independently or non-independently in a slice, tile, or brick unit, thereby accumulating in the encoding and decoding process. This can prevent errors.

According to embodiments, a bitstream in which a geometry bitstream and an attribute bitstream are combined requires information related to how data included in each tile and/or each slice is encoded.

However, when information related to how data included in each tile and/or each slice is encoded is signaled by a sequence parameter set (SPS) or an attribute parameter set (APS), each slice The encoding method cannot be signaled for each of them. In addition, since the SPS and APS include signaling information on point cloud data included in the bitstream, when the amount of data of the SPS and APS increases, it may be a heavy burden for the receiver to decode them. Particularly, when each tile and/or each slice is different from each other in the attribute coding method or related parameter information, the SPS or APS must include information on each of the slides.

Therefore, in the point cloud data transmission apparatus according to the embodiments, when each tile and/or each slice is separately included in the attribute coding method or related parameter information, the APS and/or the SPS Parameters may be included in each slice or tile.

Accordingly, the bitstream transmitted by the point cloud data transmission apparatus is the bitstream of the first structure for independently or non-independently performing encoding by dividing the point cloud data into one or more slices. To FIG. 27, a bitstream of a second structure and a bitstream of a third structure in which point cloud data is divided into one or more tiles, and a tile is divided into one or more slices. The bitstream is described in FIGS. 28 to 34.

25 shows another embodiment of a sequence parameter set (SPS) according to the embodiments.

FIG. 25 shows a sequence parameter set (SPS) 25000 of a bitstream structure including parameters shown in FIG. 25. The bitstream structure including the parameters shown in FIG. 25 may mean the bitstream structure of FIG. 19 and the bitstream of the first structure of FIG. 23.

The bitstream transmitted by the point cloud data transmission apparatus according to the embodiments may include one or more slices. One or more slices according to embodiments may be point cloud data encoded by different methods. Accordingly, the point cloud data transmission apparatus according to embodiments needs to signal information on how data included in each slice is encoded.

Accordingly, a sequence parameter set (SPS) 25000 according to embodiments may include information indicating whether data included in each slice are encoded based on the same encoding type. Thus, for example, the SPS according to the embodiments may include sps_variable_geometry_coding_type, sps_variable_attribute_type, sps_variable_geometry_flag, sps_variable_atribute_flag (25000a, 25000b).

sps_variable_geometry_coding_type may mean information defining a type for variably encoding (or decoding) geometric information (geometry information). For example, sps_variable_geometry_coding_type is A value of 0 indicates that it is coded based on octree geometric coding, if it is 1, trisoup geometric coding, and if it is 2, other geometric coding methods are used.

sps_variable_attribute_type may mean information defining a type for variably encoding (or decoding) attribute information (attribute information). For example, if sps_variable_attribute_type is 0, the attribute information is based on a color conversion, a property conversion of 1, a prediction conversion of 2, a lifting conversion of 3, a RAHT conversion of 4, and a conversion method other than 5. Indicates that it has been encoded.

sps_variable_geometry_flag is information indicating that geometry information has been variably encoded (or decoded) based on a multiplex method. For example, when sps_variable_geometry_flag is 0, it indicates that geometry information is encoded by a geometry single coding method, and when 1 is a geometry multiple coding method.

In the geometry multicoding method according to embodiments, when one frame is divided into one or more unit units (eg, slices or tiles), geometry coding (eg, octree coding, trisoup coding, etc.) is performed, respectively. It means performing the same or differently for each unit. The geometry single coding method indicates that when one frame is divided into one or more unit units (eg, slices or tiles), all of the unit units are geometry coded by the same geometry coding method.

sps_variable_atribute_flag : This is information indicating that attribute information has been variably encoded (or decoded) based on multiple methods. For example, when sps_variable_atribute_flag is 0, it indicates that the geometry information is encoded by an attribute single coding method, and when it is 1, it indicates that geometry information is encoded by an attribute multiple coding method.

In the attribute multicoding method according to embodiments, when one frame is divided into one or more unit units (eg, slices or tiles), attribute coding (eg, color transformation, attribute transformation, prediction transformation, lifting) is performed. Transformation, RAHT transformation, etc.) are performed in the same or different manner for each unit unit. The attribute single coding method indicates that when one frame is divided into one or more unit units (eg, slices or tiles), all unit units are attribute coded by the same attribute coding method.

The point cloud transmission apparatus according to the embodiments includes information 25000a defining a type for variably encoding geometry information and attribute information, information 25000a indicating that the geometry information is variably encoded based on a multiple method, and attribute information. Information 25000b indicating that is variably encoded based on a multi-method may be transmitted through the SPS 25000.

According to embodiments, when the point cloud transmission apparatus encodes point cloud data based on a multi-coding method (eg, a multi-geometry coding method and/or a multi-attribute coding method), the corresponding SPS 25000 indicates Information related to geometry and attribute coding of the point cloud data may be transmitted into each following slice or as an attribute parameter set (APS) according to embodiments.

According to embodiments, when geometry information is encoded by a point cloud transmission device based on a single geometry coding method (ie, sps_variable_geometry_coding_type==0), the point cloud transmission device according to the embodiments includes an SPS (25000). Information on the bounding box occupied by point cloud data (eg, sps_bounding_box_offset_x, sps_bounding_box_offset_y, sps_bounding_box_offset_z, sps_bounding_box_scale_factor, sps_bounding_box_scale_width, sps_bounding_box_scale_height, sps_bounding_box_scale_height, etc.) When the geometry information is encoded by the point cloud transmission device based on a multi-geometry coding method, the above-described parameters may not be transmitted, but may be defined in another syntax.

According to embodiments, when attribute information is encoded by a point cloud transmission device based on a single method (i.e., sps_variable_atribute_coding_type = = 0), attribute coding of all points of point cloud data indicated by the corresponding SPS (25000) the parameters associated with the method (e.g., sps_num_attribute_sets, attribute_dimension [i], attribute_instance_id [i], attribute_bitdepth [i], attribute_cicp_colour_primaries [i], attribute_cicp_transfer_characteristics [i], attribute_cicp_matrix_coeffs [i], attribute_cicp_video_full_range_flag [i], known_attribute_label_flag [i ], known_attribute_label[　i　], attribute_label_four_bytes[　i　], etc.) can be transmitted through the SPS. (25000b) When the attribute information is encoded based on the multi-attribute coding method by the point cloud transmission device, the above-described parameter is not transmitted, and can be defined in another syntax (e.g., Attr in a slice). I can.

According to embodiments, the bitstream may include a sequence parameter set for indicating a sequence of point cloud data. According to embodiments, the sequence parameter set includes first information indicating whether geometry information is encoded based on a plurality of types and second information indicating whether attribute information is encoded based on a plurality of types. Can include.

The point cloud data transmission apparatus according to the embodiments transmits the sps_variable_geometry_coding_type and sps_variable_attribute_type parameters to the point cloud data receiving apparatus, so that the point cloud data can be geometrically coded and attribute coded in any way by parsing only the SPS part of the bitstream You can determine if it has been performed.

In the case of encoding based on a multi-coding method, the point cloud data transmission apparatus according to the embodiments transmits information related to the geometry and attribute coding of the point cloud data into each corresponding slice, so that parameters included in the SPS The amount of can be reduced. That is, when the point cloud data is divided into one or more slices, and the divided slices are encoded based on information related to different encoding methods, the SPS does not separately signal the encoding method of each slice. Instead, it is possible to reduce the amount of transmission data of the SPS by signaling in each slice.

The point cloud data receiving apparatus according to the embodiments may rapidly parse a bitstream including point cloud data by receiving an SPS having a reduced data amount. Accordingly, as soon as the receiving device receives the slice, it can perform decoding of the corresponding slice, thereby maximizing the decoding efficiency.

26 illustrates another embodiment of an APS (Attribute Parameter Set) according to the embodiments.

FIG. 26 may mean an APS (Attribute Parameter Set, 26000) following the SPS 19001 of FIG. 19 or the SPS 25000 of FIG. 25. The APS 26000 may include some or all of the parameters included in FIG. 22 (eg, aps_attr_parameter_set_id, aps_seq_parameter_set_id, attr_coding_type, aps_attr_initial_qp, aps_attr_chroma_qp_offset, aps_slice_qp_delta_present_flag, etc.).

The APS 26000 according to embodiments may include information (eg, sps_variable_atribute_flag of FIG. 25) indicating that attribute information is variably encoded (or decoded) based on multiple methods. According to embodiments, when attribute information is encoded by a point cloud transmission device based on a single method (i.e., sps_variable_atribute_coding_type==0), attribute coding of all points of point cloud data indicated by the corresponding APS (26000) the parameters associated with the method (e.g., attr_coding_type, aps_attr_initial_qp, aps_attr_chroma_qp_offset, aps_slice_qp_delta_present_flag, isLifting, ifting_num_pred_nearest_neighbours, lifting_max_num_direct_predictors, lifting_search_range, lifting_lod_regular_sampling_enabled_flag, lifting_num_detail_levels_minus1, lifting_lod_decimation_enabled_flag, lifting_sampling_period [idx], lifting_sampling_distance_squared [idx], lifting_adaptive_prediction_threshold, lifting_intra_lod_prediction_num_layers, raht_depth, raht_binary_level_th, Some or all of aps_extension_present_flag, etc.) may be transmitted through the APS 26000.

According to embodiments, when attribute information is encoded by a point cloud transmission device based on a multi-attribute coding method, parameters related to the above-described attribute coding method are not transmitted, and within another syntax (e.g., a slice ) In Attr, etc.).

According to embodiments, the encoding step may be performed on a slice basis, and the bitstream includes one or more slices including attribute information of the encoded point cloud data, and points cloud data in the slices. It may further include a geometry parameter set and an attribute parameter set for indicating information. In addition, when the attribute information is encoded based on a plurality of types, the slice may include an attribute slice header including information related to a method of encoding the attribute information in the slice.

The point cloud data transmission apparatus according to the embodiments transmits information related to the geometry and attribute coding of the point cloud data into each corresponding slice when it is encoded based on a multiple coding method, so that the parameters included in the APS The amount of can be reduced. That is, when the point cloud data is divided into one or more slices, and the divided slices are encoded based on information related to each other encoding method, the APS does not separately signal the encoding method of each slice. Instead, it is possible to reduce the amount of data transmitted in the APS by signaling in each slice.

The point cloud data receiving apparatus according to embodiments may quickly parse a bitstream including point cloud data by receiving an APS having a reduced data amount. Accordingly, as soon as the receiving device receives the slice, it can perform decoding of the corresponding slice, thereby maximizing the decoding efficiency.

27 illustrates another embodiment of an ASH (Attribute Slice Header) according to the embodiments.

27 shows an attribute slice header 27000. The attribute slice header 27000 of FIG. 27 may be represented by the syntax of the attribute slice header 19005b-1 of the attribute slice Attr 19005b included in the slice 19005 of FIG. 19. A slice including the parameters shown in FIG. 27 may mean a slice 19005 of FIG. 19, and a slice following the SPS 25000 and APS 26000 shown in FIGS. 25 and 26 It can mean.

The APS 26000 according to embodiments may include information (eg, sps_variable_atribute_flag of FIG. 25) indicating that attribute information is variably encoded (or decoded) based on multiple methods.

According to embodiments, when attribute information is encoded based on a single method by a point cloud transmission device (i.e., sps_variable_atribute_coding_type==0), an SPS preceding the attribute slice header 27000 (e.g., FIG. 25 SPS (25000)) and parameters related to the attribute coding method of all points of the point cloud data in the APS (e.g., APS 26000 of FIG. 26) (e.g., sps_num_attribute_sets, attribute_dimension [　i ], the attribute_instance_id [i], attribute_bitdepth [i], attribute_cicp_colour_primaries [i], attribute_cicp_transfer_characteristics [i], attribute_cicp_matrix_coeffs [i], attribute_cicp_video_full_range_flag [i], known_attribute_label_flag [i], known_attribute_label [i], attribute_label_four_bytes [i] and 26 attr_coding_type, aps_attr_initial_qp, aps_attr_chroma_qp_offset, aps_slice_qp_delta_present_flag, isLifting, ifting_num_pred_nearest_neighbours, lifting_max_num_direct_predictors, lifting_search_range, lifting_lod_regular_sampling_enabled_flag, lifting_num_detail_levels_minus1, lifting_lod_decimation_enabled_flag, lifting_sampling_period [idx], lifting_sampling_distance_squ ared[　idx　], lifting_adaptive_prediction_threshold, lifting_intra_lod_prediction_num_layers, raht_depth, raht_binary_level_th, aps_extension_present_flag, etc.) can be signaled by the preceding SPS and APS. That is, when encoding is performed based on a single coding method, information related to encoding may be included in the SPS and APS signaling all of one or more slices.

According to embodiments, when attribute information is encoded by a point cloud transmission device based on a multi-method (ie, sps_variable_atribute_coding_type==1), parameters related to the attribute coding method of all points of the point cloud data are each It can be signaled within a slice. Accordingly, in this case, the attribute slice header 27000 may include the above-described parameters (27001).

According to embodiments, the encoding step may be performed on a slice basis, and the bitstream includes one or more slices including attribute information of the encoded point cloud data, and points cloud data in the slices. It may further include a geometry parameter set and an attribute parameter set for indicating information. In addition, when the attribute information is encoded based on a plurality of types, the slice may include an attribute slice header including information related to a method of encoding the attribute information in the slice.

The point cloud data transmission apparatus according to the embodiments transmits (27000) information related to the geometry and attribute coding of the point cloud data into each corresponding slice when it is encoded based on a multiple coding method, so that the APS It is possible to reduce the amount of parameters to be included. That is, when the point cloud data is divided into one or more slices, and the divided slices are encoded based on information related to each other encoding method, the APS does not separately signal the encoding method of each slice. Instead, it is possible to reduce the amount of data transmitted in the APS by signaling in each slice.

The point cloud data receiving apparatus according to embodiments may quickly parse a bitstream including point cloud data by receiving an APS having a reduced data amount. Accordingly, as soon as the receiving device receives the slice, it can perform decoding of the corresponding slice, thereby maximizing the decoding efficiency.

28 illustrates another example of a bitstream structure of point cloud data according to embodiments.

FIG. 28 illustrates performing multi-geometric coding (eg, octree coding, trisoup coding, etc.) and multi-attribute coding when one bitstream (frame) is divided into one or a tile unit. It shows the situation for. In order to support multiple encoding of slice-based geometric information and attribute information, the same parameters and additional parameters of the existing SPS, TPS, GPS, APS, Geometry Slice header, and Attribute Slice header can be used.

A bitstream of point cloud data according to embodiments may include a sequence parameter set (SPS), a tile parameter set (TPS), and one or more tiles (tile, 28002).

SPS 28000 represents information on a sequence of subsequent point cloud data. The syntax of the SPS according to the bitstream structure described in FIG. 28 may be expressed according to FIG. 30.

The TPS 28001 includes information on one or more tiles included in the bitstream. One or more tiles 2802 according to embodiments may be signaled by TPS.

The tile 2802 is a GPS (Geometry Parameter Set, 28002a) including parameters related to geometry information of point cloud data included in the tile, and APS (Geometry Parameter Set, 28002a) including parameters related to attribute information of point cloud data included in the tile ( Attribute Parameter Set, 28002b) and one or more slices (slice, 28003) may be included. A plurality of slices included in one tile may refer to point cloud data encoded based on the same geometry coding and attribute coding method. How the plurality of slices are encoded may be signaled by the GPS 2802a and APS 2802b included in the tile.

The slice 28003 includes a geometry slice (Geom, 28003a) including geometry information of point cloud data included in the slice, and an attribute slice (Attr, 28003b) including one or more attribute information. The attribute slice (Attr, 28003) includes an attribute slice header (ASH, 28003b-1) and attribute slice data (Attribute Slice Data, 28003b-2).

The attribute slice header 28803b-1 may include parameter information on attribute information included in a corresponding attribute slice.

Accordingly, the point cloud data transmission apparatus according to embodiments may signal information on one or more tiles composed of one or more slices of the point cloud data to the TPS 28001. In addition, information on the slice (slice 28003) included in each tile may be signaled to the GPS (28002a) and APS (28002b) included in the tile (28002).

When a separate encoding method exists for each of one or more slices or a different encoding method exists, the method is applied to the geometry slice header (28003a-1) and attribute slice header (28003b-1) within the slice. Can be signaled by

Each nth tile has GPS and APS, and n slices share GPS and APS. The slice may sequentially include Geom (Geom slice header, Geom slice data), Attr0, and Attr1. The entire bitstream structure may include one or more slices within a tile unit. That is, the bitstream according to the embodiments may be structured based on n tiles and n slices. The multi-encoding method of slice-based geometric information and attribute information shown in FIG. 28 may be sps_variable_geometry_coding_type = 1 in a sequence syntax structure, and may mean a bitstream structure when sps_variable_attribute_type = 1.

In the encoding step according to embodiments, encoding may be performed in units of a tile including one or more slices, and the bitstream includes information about one or more tiles and point cloud data in the tiles. It may further include a tile parameter set for indicating.

A tile according to embodiments may include one or more slices, a geometry parameter set and an attribute parameter set for indicating information about data in one or more slices, and the attribute parameter set is attribute information in the slice. It may include information related to how to encode.

The point cloud data transmission apparatus according to the embodiments, when encoded based on a multi-coding method, includes information related to the geometry and attribute coding of the point cloud data into each corresponding tile and transmits the SPS 28000. The amount of parameters included in) can be reduced. In addition, information related to geometry and attribute coding of point cloud data is included in each corresponding tile and transmitted, so that multiple coding can be efficiently performed for each tile.

The point cloud data receiving apparatus according to the embodiments may rapidly parse a bitstream including point cloud data by receiving an SPS having a reduced data amount. Therefore, the receiving device can decode the tile as soon as it receives the tiles, and can maximize the decoding efficiency by performing the decoding for each slice based on the GPS and APS included in the tile for each tile. have.

29 illustrates another example of a bitstream structure of point cloud data according to embodiments.

FIG. 29 is for performing multi-geometric coding (eg, octree coding, trisoup coding, etc.) and multi-attribute coding when one bitstream (frame) is divided into one or more tile unit units. It shows the situation. In order to support multiple encoding of slice-based geometric information and attribute information, the same parameters and additional parameters of the existing SPS, TPS, GPS, APS, Geometry Slice header, and Attribute Slice header can be used.

A bitstream of point cloud data according to embodiments may include a sequence parameter set (SPS) 29000, a tile parameter set (TPS) 29001, and one or more tiles 29003.

SPS 29000 represents information on a sequence of subsequent point cloud data. The syntax of the SPS according to the bitstream structure described in FIG. 28 may be expressed according to FIG. 30.

The TPS 29001 includes information on one or more tiles included in the bitstream. One or more tiles 2802 according to embodiments may be signaled by TPS.

Tile 29003 includes one or more slices 29004. The slice 29004 is a GPS (Geometry Parameter Set, 29004a) including parameters related to geometry information of the point cloud data included in the corresponding slice, and APS including parameters related to attribute information of the point cloud data included in the tile ( Attribute Parameter Set, 29004b) may be included.

A plurality of slices included in one tile may refer to point cloud data encoded based on the same geometry coding and the same or different attribute coding methods. How a plurality of slices are encoded may be signaled by the GPS 29004a and APS 29004b included in the corresponding slice.

For example, referring to FIG. 29, a bitstream includes an SPS 29000, a TPS 29001, and one or more tiles (tile, 29003, for example, tile 0 and tile 1). Among one or more tiles, an X-th tile (tile X) may include a slice Y and a slice Y+1. Slice Y represents GPS (e.g., GPS_X^Y(29004a)) representing the geometry encoding method of point cloud data in the slice, APS representing the attribute encoding method (e.g. APS_X^Y (29004b)), and geometry information. It includes a geometry slice (eg, Geom_0^Y), and one or more attribute slices (eg, Attr_0^Y) representing attribute information.

The slice 28003 includes a geometry slice (Geom, 28003a) including geometry information of point cloud data included in the slice, and an attribute slice (Attr, 28003b) including one or more attribute information. The attribute slice (Attr, 28003) includes an attribute slice header (ASH, 28003b-1) and attribute slice data (Attribute Slice Data, 28003b-2).

The GPS 29004a includes information indicating a geometry encoding method of point cloud data included in a corresponding slice within a corresponding tile. Since the GPS 29004 is applied in units of slices, it may exist for each slice.

The APS 29004b includes information indicating a method of encoding an attribute of point cloud data included in a corresponding slice within a corresponding tile. Since the APS 29004b is applied in units of slices, it may exist for each slice.

Accordingly, the point cloud data transmission apparatus according to embodiments may signal information on one or more tiles composed of one or more slices of the point cloud data to the TPS 29001. In addition, information on a slice 28003 included in each tile may be signaled to the GPS 29004a and APS 29004b included in each slice 29004.

When a separate encoding method exists for each of one or more slices or a different encoding method exists, the corresponding method includes GPS (29004a), APS (29004b), and geometry slice header (28003a-) included in the corresponding slice. 1) and the attribute slice header 2803b-1.

In the encoding step according to embodiments, encoding may be performed in units of a tile including one or more slices, and the bitstream includes information about one or more tiles and point cloud data in the tiles. It may further include a tile parameter set for indicating.

A tile may include one or more slices, and the slice may include a geometry parameter set and an attribute parameter set for indicating information about data in the slice, and the attribute parameter set is a method of encoding attribute information in a slice. It may include information related to.

The point cloud data transmission apparatus according to the embodiments, when encoded based on a multi-coding method, includes information related to geometry and attribute coding of the point cloud data into each corresponding tile and transmits the SPS 29000. The amount of parameters included in) can be reduced. In addition, information related to geometry and attribute coding of point cloud data is included in each corresponding tile and transmitted, so that multiple coding can be efficiently performed for each tile.

The point cloud data receiving apparatus according to the embodiments may rapidly parse a bitstream including point cloud data by receiving an SPS having a reduced data amount. Accordingly, the receiving device may decode the tile as soon as it receives the tiles, and perform decoding for each slice based on the GPS, APS, geometry slice header, and attribute slice header included in the tile for each tile. By doing this, the decoding efficiency can be maximized.

30 shows another embodiment of a sequence parameter set (SPS) according to the embodiments.

30 shows a sequence parameter set (SPS) 30000 of a bitstream structure. The bitstream structure including the parameters shown in FIG. 30 may mean the bitstream structure of FIG. 19, the bitstream structure of FIG. 28, or the bitstream structure of FIG. 29.

The bitstream transmitted by the point cloud data transmission apparatus according to the embodiments may include one or more tiles including one or more slices. One or more slices and tiles according to embodiments may be point cloud data encoded by the same or different methods, respectively. Accordingly, the point cloud data transmission apparatus according to embodiments needs to signal information on how data included in each slice and each tile is encoded.

Accordingly, a sequence parameter set (SPS) 30000 according to embodiments may include information indicating whether data included in each slice are encoded based on the same encoding type. Thus, for example, the SPS according to the embodiments may include sps_variable_geometry_coding_type, sps_variable_attribute_type, sps_variable_geometry_flag, sps_variable_atribute_flag (25000a, 25000b). In addition, the SPS 30000 may also include information on tiles following the SPS. For example, the SPS may further include information about the number of tiles that follow (eg, sps_tileNum).

sps_tileNum represents the number of tiles to divide the sequence of point cloud data indicated by the corresponding SPS. That is, sps_tileNum represents information on the number of tiles following the SPS.

The SPS 30000 according to the embodiments may further include sps_variable_geometry_coding_type, sps_variable_attribute_type, sps_variable_geometry_flag, sps_variable_atribute_flag (25000a, 25000b) as described above in FIG. 25 (30001, 30002).

As described in FIG. 25, the SPS 30000 according to the embodiments includes information on the bounding box occupied by the point cloud data based on the sps_variable_geometry_flag and sps_variable_atribute_flag parameters, and parameters related to the attribute coding method of all points of the point cloud data. Can be included or omitted.

31 shows an embodiment of a Tile Parameter Set (TPS) according to the embodiments.

31 shows a tile parameter set (TPS) following a sequence parameter set (SPS) of a bitstream structure. The bitstream structure including the parameters shown in FIG. 31 may mean the bitstream structure of FIG. 19, the bitstream structure of FIG. 28, or the bitstream structure of FIG. 29. That is, the TPS 31000 shown in FIG. 31 may follow the SPS 30000 shown in FIG. 30.

The bitstream transmitted by the point cloud data transmission apparatus according to the embodiments may include one or more tiles including one or more slices. One or more slices and tiles according to embodiments may be point cloud data encoded by the same or different methods, respectively. Accordingly, the point cloud data transmission apparatus according to embodiments needs to signal information on how data included in each slice and each tile is encoded.

The TPS 31000 according to the embodiments may include information on tiles and/or information on slices following the TPS 31000. For example, the TPS according to the embodiments may include information indicating the number of tiles included in the corresponding active SPS and the number of slices included in each of the tiles.

The TPS 31000 according to the embodiments may further include information indicating the number of slices included in each of the tiles. By signaling the number of slices included in each tile to the TPS following the SPS, the point cloud data receiving apparatus according to the embodiments can quickly check the number of slices, and information for parallel decoding Can be quickly parsed.

For example, the TPS 31000 may include num_tiles information indicating the number of tiles that follow, and num_slices information 31001 indicating the number of slices included in each tile.

The TPS 31000 according to the embodiments may further include information on spaces each occupied by subsequent tiles. For example, the TPS 31000 according to embodiments may further include tile_bounding_box_offset_x, tile_bounding_box_offset_y, tile_bounding_box_offset_z, tile_bounding_box_scale_factor, tile_bounding_box_size_width, tile_bounding_box_size_height information for each tile. The tile_bounding_box_offset_x, tile_bounding_box_offset_y, tile_bounding_box_offset_z, tile_bounding_box_scale_factor, tile_bounding_box_size_width, tile_bounding_box_size_height information described in FIG.

In the encoding step according to embodiments, encoding may be performed in units of a tile including one or more slices, and the bitstream includes information about one or more tiles and point cloud data in the tiles. It may further include a tile parameter set for indicating.

Since the TPS 31000 according to the embodiments includes num_tiles and/or num_slices, the point cloud data transmission apparatus according to the embodiments may efficiently compress redundant information. In addition, the point cloud data receiving apparatus according to the embodiments can quickly parse the number of tiles and the number of slices due to this structure, so that parallel decoding can be efficiently performed.

32 shows another embodiment of a GPS (Geometry Parameter Set) according to the embodiments.

FIG. 32 shows a Geometry Parameter Set (GPS) 32000 included in tiles following a tile parameter set (TPS) of a bitstream structure. The bitstream structure including the parameters shown in FIG. 32 may mean the bitstream structure of FIG. 19, the bitstream structure of FIG. 28, or the bitstream structure of FIG. 29. That is, the GPS 32000 shown in FIG. 32 may follow the SPS 30000 of FIG. 30 and/or the TPS 31000 of FIG. 31.

The parameters of the GPS 32000 according to the embodiments may be included in a tile according to the embodiments, or may be included in each slice included in the tile.

For example, as shown in FIG. 28, only one GPS 32000 may exist in one tile. That is, one tile (eg, tile 0) may include one GPS (eg, GPS0), one APS (eg, APS0), and/or one or more slices. have. In this case, the GPS 32000 may be information signaling geometry information of point cloud data of one or more slices that follow.

Further, for example, the GPS 32000 may be information included in each of one or more slices 29004 included in one tile, as shown in FIG. 29. That is, when n slices are included in one tile (eg, tile 0), GPS (eg, GPS00, GPS01, GPS02, …, GPS0n) may be included in each of the n slices. In this case, the GPS 32000 may be information individually signaling geometric information of point cloud data included in each slice.

GPS in accordance with embodiments (32000) is, gps_geom_parameter_set_id, gps_seq_parameter_set_id, geometry_coding_type, gps_box_present_flag, unique_geometry_points_flag, neighbour_context_restriction_flag, inferred_direct_coding_mode_enabled_flag, bitwise_occupancy_coding_flag, child_neighbours_enabled_flagfalse_neighbour_removal_enabled_flag, adjacent_child_contextualisation_enabled_flag, geom_occupancy_ctx_reduction_factor, log2_neighbour_avail_boundary, log2_intra_pred_max_node_size, log2_trisoup_node_size, trisoup_depth, trisoup_triangle_level, gps_extension_present_flag, can include gps_extension_data_flag have. Corresponding parameters are as described in FIG. 21.

The GPS 32000 according to embodiments may further include gps_tileid information indicating identifier information of a tile in which the corresponding GPS is included. gps_tileId refers to information on the number of tiles in a sequence in sps_tileNum according to embodiments. In this case, gps_tileId may be generated as many as the number of sps_tileNums, and the id of the for statement of FIG. 32 may be allocated to gps_tileId.

Due to the structure of the bitstream, the point cloud data transmission apparatus according to embodiments can efficiently compress redundant information. In addition, the point cloud data receiving apparatus according to the embodiments can quickly parse the number of tiles and the number of slices due to this structure, so that parallel decoding can be efficiently performed.

33 illustrates another embodiment of an APS (Attribute Parameter Set) according to the embodiments.

33 shows a Geometry Parameter Set (APS) 33000 included in tiles following a tile parameter set (TPS) of a bitstream structure. The bitstream structure including the parameters shown in FIG. 33 may mean the bitstream structure of FIG. 19, the bitstream structure of FIG. 28, or the bitstream structure of FIG. 29. That is, the APS 33000 shown in FIG. 33 may follow the SPS 30000 of FIG. 30 and/or the TPS 31000 of FIG. 31.

APS (33000) according to the embodiments may include aps_attr_parameter_set_id, aps_seq_parameter_set_id, attr_coding_type, num_pred_nearest_neighbours, max_num_direct_predictors, lifting_search_range lifting_quant_step_size, lifting_quant_step_size_chroma, lod_binary_tree_enabled_flag, sampling_distance_squared [idx], adaptive_prediction_threshold, raht_depth, raht_binarylevel_threshold, raht_quant_step_size, aps_extension_present_flag, aps_extension_data_flag. Corresponding parameters are as described in FIG. 22.

The parameters of the APS 33000 according to the embodiments may be included in a tile according to the embodiments, or may be included in each slice included in the tile.

Further, for example, the GPS 32000 may be information included in each of one or more slices 29004 included in one tile, as shown in FIG. 29. That is, when n slices are included in one tile (eg, tile 0), GPS (eg, GPS00, GPS01, GPS02, …, GPS0n) may be included in each of the n slices. In this case, the GPS 32000 may be information individually signaling geometric information of point cloud data included in each slice.

In the APS 32000 according to the embodiments, when the bitstream structure exists in each slice included in one tile as shown in FIG. 29, the point cloud data included in each of the slices is It may include attribute information and related signaling information.

As illustrated in FIG. 28, only one APS 32000 according to embodiments may exist in one tile. That is, one tile (eg, tile 0) may include one APS (eg, GPS0), one APS (eg, APS0), and/or one or more slices. have. In this case, the APS 33000 may be information signaling geometry information of point cloud data of one or more slices that follow.

In the case where only one bitstream structure exists in one tile as shown in FIG. 28, the APS 32000 according to the embodiments may include all or part of attribute information and related signaling information of each of subsequent slices. I can. For example, the APS 32000 may include all or part of the parameters described in FIG. 22.

Accordingly, the APS 32000 according to the embodiments may include aps_sps_sliceNum information indicating the number of subsequent slices and/or a tile identifier indicating which tile the corresponding APS 32000 is included, that is, aps_gps_tileId. Yes (33001). The APS 32000 according to embodiments may signal all or part of attribute information and related signaling information (eg, information shown in FIG. 28) corresponding to each subsequent slice (33001).

aps_sps_tileNum may be information indicating the number of tiles to divide the sequence into.

aps_gps_tileId represents an identifier of a tile defined by GPS according to embodiments.

sps_variable_geometry_coding_type represents a coding type of geometry information defined in SPS according to embodiments.

Due to the structure of the bitstream, the point cloud data transmission apparatus according to embodiments can efficiently compress redundant information. In addition, the point cloud data receiving apparatus according to the embodiments can quickly parse the number of tiles and the number of slices due to this structure, so that parallel decoding can be efficiently performed.

34 illustrates another embodiment of a Geometry Slice Header (GSH) and an Attribute Slice Header (ASH) according to the embodiments.

34 shows GSH (Geometry Slice Header) and ASH (Attribute Slice Header) included in a slice of a bitstream structure. The bitstream structure including parameters shown in FIG. 34 may mean the bitstream structure of FIG. 19, the bitstream structure of FIG. 28, or the bitstream structure of FIG. 29. That is, GSH and ASH shown in FIG. 33 may mean Attr_slice_header (28003b-1) and Geom_slice_header (28003a-1) shown in FIG. 28.

GSH (Geometry Slice Header, Geometry Slice Header) according to the embodiments may include gsh_geometry_parameter_set_id, gsh_tile_id, gsh_slice_id, gsh_box_log2_scale, gsh_box_origin_x, gsh_box_origin_y, gsh_box_origin_z, gsh_box_origin_z, gsh_log2_number, and gsh_log2_number. Corresponding parameters are as described in FIG. 23.

ASH (Attribute Slice Header, attribute slice header) according to embodiments may include abh_attr_parameter_set_id, abh_attr_sps_attr_idx, abh_attr_geom_slice_id. Corresponding parameters are as described in FIG. 23.

gsh_id_tile represents the identifier of the tile including the corresponding GSH. The gsh_id_tile according to embodiments may be within the range of sps_tileNum.

gsh_id_slice represents the identifier of the slice containing the GSH. The gsh_id_slice according to embodiments may be within the range of tps_numSlices.

ash_gsh_tile_id represents the identifier of the tile including the corresponding ASH. The number defined in sps_tileNum is received as id_tile and defined as ash_gsh_tile_id.

ash_gsh_slice_id represents the identifier of the slice including the corresponding ASH. The number defined in tps_numSlices is received as id_slice and defined as ash_gsh_slice_id. .

Due to the structure of the bitstream, the point cloud data transmission apparatus according to embodiments can efficiently compress redundant information. In addition, the point cloud data receiving apparatus according to the embodiments can quickly parse the number of tiles and the number of slices due to this structure, so that parallel decoding can be efficiently performed.

35 shows a point cloud decoder 35000 according to embodiments.

The point cloud decoder 35000 according to the embodiments may include a geometric information decoding unit 35001 and/or an attribute information decoding unit 35002. According to embodiments, the point cloud decoder may be referred to as a PCC decoder, a PCC decoder, a point cloud decoder, a point cloud decoder, a PCC decoder, or the like.

The geometric information decoding unit 35001 receives a geometric information bitstream 35000a of point cloud data. The geometric information decoding unit 35001 may decode (decode) the geometric information bitstream 35000a of the point cloud data and output geometry information of the restored point cloud data 35000c. The geometric information decoding unit 35001 may reconstruct the geometric information bitstream into geometric information and output the reconstructed geometric information 35001b. The geometry information bitstream 35000a may mean a geometry information bitstream and a geometry bitstream of FIGS. 18 to 26. The attribute information bitstream 35000b may mean an attribute information bitstream and an attribute bitstream of FIGS. 18 to 34.

The geometric information decoding unit 35001 restores the geometric information by decoding the received geometric information bitstream. The restored geometric information may be input to the attribute information decoding unit. The attribute information decoding unit 35002 receives the received attribute information bitstream and the restored geometric information received from the geometry information decoding unit and restores the attribute information. The reconstructed geometric information may mean a geometry reconstructed by a geometry reconstructing unit 11003 described in FIG. 11. The restored geometric information may mean an octree occupancy code reconstructed by the occupancy code-based octree reconstruction processing unit 13003 described in FIG. 13.

The geometry information decoding unit 35001 receives the geometry information bitstream received by the reception device according to the embodiments. The geometry information decoding unit 35001 may decode a geometry information bitstream.

The geometric information decoding unit 35001 includes the operation of the point cloud video decoder of Fig. 1, the decoding 20003 of Fig. 2, the operation of the geometry decoder of Fig. 10, the arithmetic decoder 11000 described in Fig. 11, and the octree synthesis unit 11001. ), the surface opoxidation synthesis unit 11002, the geometry reconstruction unit 11003, and/or the coordinate system inverse transform unit 11004 may perform all/part of the operations.

The attribute information decoding unit 35002 receives the attribute information bitstream 35000b of point cloud data. The attribute information decoding unit 35002 may decode (decode) the attribute information bitstream 35000b of the point cloud data and output attribute information of the restored point cloud data 35000c. The attribute information decoding unit 35002 may decode (decode) the attribute information bitstream based on the restored geometric information 35001a generated by the geometry information decoding unit 35001.

The attribute information decoding unit 35002 receives the attribute information bitstream received by the reception device according to the embodiments. The attribute information decoding unit may decode attribute information of the attribute information bitstream based on the restored geometric information. Geometric information and/or attribute information included in the point cloud data may be decoded and restored PCC data.

The attribute information decoding unit 35002 includes the point cloud video decoder of FIG. 1, the operation of the decoding 20003 of FIG. 2, the operation of the attribute decoder described in FIG. 10, the inverse quantization unit 11006 of FIG. 11, and RAHT. (11007), LOD generation unit (11008), inverse lifting unit (11009), and/or color inverse transform unit (11010) operation, the Arismatic decoder (13007) described in FIG. 13, inverse quantization processing unit (13008), prediction/lifting Some or all of the operations of the /RAHT inverse transform processing unit 13009, the color inverse transform processing unit 13010, and/or the renderer 13011 may be performed.

A method of receiving point cloud data according to embodiments may include receiving a bitstream including point cloud data, decoding point cloud data, and/or rendering point cloud data.

The bitstream may include a sequence parameter set including information on a sequence of point cloud data, and the sequence parameter set is encoded based on a plurality of types of geometry information of the point cloud data. It may include first information indicating whether or not, and second information indicating whether attribute information of the point cloud data is encoded based on a plurality of types. Further, the decoding may include decoding geometric information based on the first information and decoding attribute information based on the second information.

By signaling the number of slices included in each tile to the TPS following the SPS, the point cloud data receiving apparatus according to the embodiments can quickly check the number of slices, and information for parallel decoding Can be quickly parsed.

The point cloud data receiving apparatus according to the embodiments may rapidly parse a bitstream including point cloud data by receiving an SPS having a reduced data amount. Therefore, the receiving device can decode the tile as soon as it receives the tiles, and can maximize the decoding efficiency by performing the decoding for each slice based on the GPS and APS included in the tile for each tile. have.

36 shows a point cloud decoder according to embodiments.

A point cloud decoder according to embodiments includes one or more geometry decoders and/or one or more attribute decoders. The point cloud decoder according to the embodiments receives a point cloud data bitstream according to the embodiments. The point cloud decoder according to the embodiments decodes the point cloud data bitstream according to the embodiments for each tile and outputs the decoded point cloud data.

The point cloud data bitstream (receive bitstream) received by the point cloud decoder according to the embodiments may be configured in the bitstream structure shown in FIGS. 18 to 35. That is, a received bitstream according to embodiments may include one or more tiles, and each tile may include one or more slices.

The point cloud receiving apparatus (point cloud decoder) according to the embodiments may decode a received bitstream for each tile. For example, when the received bitstream includes n tiles, point cloud data included in each tile may be independently or non-independently decoded. For example, if there are n tiles in the received bitstream according to the embodiments, the point cloud data receiving apparatus (decoder) includes at most n geometry decoders and/or at most n attribute decoders. (attribute decoder) may be included.

For example, point cloud data included in tile 0 among n tiles of a received bitstream is decoded by a 0th geometry decoder and/or a 0th attribute decoder included in the point cloud data receiving device. Can be. Point cloud data included in a k-th tile (tile k) among n tiles of the received bitstream may be decoded by a k-th geometry decoder and/or a k-th attribute decoder included in the point cloud data receiving apparatus.

For example, a geometry bitstream of point cloud data included in tile 0 among n tiles of the received bitstream may be geometrically decoded by the 0th geometry decoder. The 0th geometry decoder may geometrically decode a geometry bitstream of point cloud data included in the 0th tile 0 and output the 0th decoded geometry information. The 0th attribute decoder may attribute-decode the attribute bitstream of point cloud data included in the 0th tile based on the 0th decoded geometry information. The 0th attribute decoder may decode the attribute bitstream and output decoded attribute information. In this case, the 0th geometry decoder and/or the 0th attribute decoder according to the embodiments may perform decoding in units of slices included in the corresponding tile. The point cloud data decoder according to embodiments may combine the 0th decoded geometry information and/or the 0th decoded attribute information to output the 0th decoded point cloud data.

The point cloud data decoder according to the embodiments may decode the point cloud data included in each tile based on information on a tile, included in a sequence parameter set (SPS) according to the embodiments. I can. For example, the point cloud data decoder according to the embodiments may check the parameters included in sps_tileNum included in the SPS according to the embodiments, and perform decoding in parallel by the number of tiles indicated by sps_tileNum. I can.

The point cloud data decoder according to embodiments may perform attribute decoding and/or geometry decoding of point cloud data according to embodiments based on sps_variable_geometry_coding_type and sps_variable_attribute_coding_type included in the SPS according to the embodiments.

The point cloud data decoder according to the embodiments includes information indicating the number of tiles included in the TPS (Tile Parameter Set) according to the embodiments and/or information on a slice included in each tile. Based on this, point cloud data included in each tile and/or each slice may be decoded.

The point cloud data decoder according to the embodiments, based on the information included in the GPS (Geometry Parameter Set) and / or GSH (Geometry Parameter Set) according to the embodiments, each tile (tile) and / or each slice ( slice) can be geometrically decoded. The point cloud data decoder according to the embodiments, based on the information included in the APS (Geometry Parameter Set) and/or ASH (Attribute Slice Header) according to the embodiments, each tile and/or each slice ( slice) can be attribute-decoded.

For example, it is assumed that the bitstream received by the point cloud data receiving apparatus according to the embodiments is a bitstream according to the structure shown in FIG. 19. The point cloud data receiving apparatus according to the embodiments includes parameters included in the SPS according to the embodiments shown in FIG. 21, parameters included in the TPS according to the embodiments shown in FIG. 21, and embodiments shown in FIG. 21 Geometry decoding and/or attribute decoding based on parameters included in GPS according to, parameters included in APS according to the embodiments shown in FIG. 22, GSH and/or ASH according to the embodiments shown in FIG. 23 Can be done.

For example, it is assumed that the bitstream received by the point cloud data receiving apparatus according to the embodiments is a bitstream according to the structure shown in FIG. 28. The point cloud data receiving apparatus according to the embodiments may first check the SPS 28000 shown in FIG. 28. The SPS 28000 shown in FIG. 28 includes information on a corresponding sequence. In this case, the SPS may include some or all of the parameters of the SPS shown in FIG. 30. The point cloud data receiving apparatus according to embodiments includes information on the number of tiles (eg, num_tiles) included in a subsequent TPS 28001 and/or of a slice included in each tile. Number information (eg, num_slices) can be checked. The TPS 28001 according to the embodiments may be the TPS shown in FIG. 31. The point cloud data receiving apparatus according to the embodiments may perform parallel decoding of point cloud data included in each tile or a slice included in each tile based on num_tiles and/or num_slices information. The point cloud data receiving apparatus according to embodiments may perform decoding based on information on a space occupied by each tile included in the TPS 28001 (eg, tile_bounding_box_offset_x[　i　], etc.). The point cloud data decoder according to embodiments may include a geometry decoder and/or an attribute decoder as many as the maximum number of tiles (num_tiles). Each geometry decoder may decode point cloud data corresponding to a tile received by each geometry decoder. Each geometry decoder may receive a bitstream corresponding to the received tile and check the GPS 2802a according to embodiments included in the tile. Each geometry decoder may geometry decode point cloud data included in slices 2803 included in the received tile based on parameters included in the GPS 2802a. Each attribute decoder may attribute decode point cloud data corresponding to a tile received by each attribute decoder. Each attribute decoder may receive a bitstream corresponding to the received tile, and may check the APS 2802b according to embodiments included in the tile. Each attribute decoder may attribute decode point cloud data included in slices 2803 included in the received tile, based on parameters included in the APS 2802b. Each attribute decoder and/or each geometry decoder according to the embodiments may independently or non-independently perform decoding on a slice basis. In this case, each attribute decoder and/or each geometry decoder may perform decoding based on the GSH 28003a-1 and/or ASH 28003b-1 included in each slice.

For example, assume that the bitstream received by the point cloud data receiving apparatus according to the embodiments is a bitstream according to the structure shown in FIG. 29. The point cloud data receiving apparatus according to the embodiments may first check the SPS 29000 shown in FIG. 29. The SPS 29000 shown in FIG. 29 includes information on a corresponding sequence. In this case, the SPS may include some or all of the parameters of the SPS shown in FIG. 30. The point cloud data receiving apparatus according to the embodiments includes information on the number of tiles (eg, num_tiles) included in a subsequent TPS 29001 and/or of a slice included in each tile. Number information (eg, num_slices) can be checked. The TPS 29001 according to the embodiments may be the TPS shown in FIG. 31. The point cloud data receiving apparatus according to the embodiments may perform parallel decoding of point cloud data included in each tile or a slice included in each tile based on num_tiles and/or num_slices information. The point cloud data receiving apparatus according to embodiments may perform decoding based on information on a space occupied by each tile included in the TPS 29001 (eg, tile_bounding_box_offset_x[　i　], etc.). The point cloud data decoder according to embodiments may include a geometry decoder and/or an attribute decoder as many as the maximum number of tiles (num_tiles). Each geometry decoder may decode point cloud data corresponding to a tile received by each geometry decoder. Each geometry decoder may receive a bitstream corresponding to the received tile, and may geometrically decode point cloud data included in the tile for each slice. In this case, when geometry decoding is performed for each slice, each geometry decoder decodes geometry based on the GPS 29003a and/or GSH 29003c-1 according to embodiments included in the corresponding slice. Can be done. When attribute decoding is performed for each slice, each attribute decoder performs attribute decoding based on the APS 29004b and/or ASH 29004d-1 according to the embodiments included in the corresponding slice. I can.

A method of receiving point cloud data according to embodiments may include receiving a bitstream including point cloud data, decoding point cloud data, and/or rendering point cloud data.

The bitstream may further include one or more tiles, and a tile parameter set including information on one or more tiles. In addition, the tile may further include a geometry parameter set and an attribute parameter set for indicating information about data in one or more slices and one or more slices. have. In addition, decoding the attribute information may decode point cloud data based on information on tiles included in the tile parameter set and information on slices included in the attribute parameter set.

According to embodiments, by signaling the number of slices included in each tile to a TPS following the SPS, the point cloud data receiving apparatus according to the embodiments can quickly check the number of slices, Information for parallel decoding can be quickly parsed.

The point cloud data receiving apparatus according to the embodiments may rapidly parse a bitstream including point cloud data by receiving an SPS having a reduced data amount. Therefore, the receiving device can decode the tile as soon as it receives the tiles, and can maximize the decoding efficiency by performing the decoding for each slice based on the GPS and APS included in the tile for each tile. have.

37 shows a method of transmitting point cloud data according to embodiments.

The point cloud data transmission method according to the embodiments may mean encoding the point cloud data (37001) and/or transmitting the bitstream including the encoded point cloud data and/or signaling information (37002). have.

The step 37001 of encoding point cloud data may refer to an step of encoding point cloud data according to embodiments. In the step of encoding the point cloud data (37001), the point cloud video encoder 10002 of FIG. 1, the encoding 20001 of FIG. 2, some/all of the operations shown in FIG. can do.

Encoding point cloud data 37001 according to embodiments may include encoding geometry information of the point cloud data and/or encoding attribute information of the point cloud data. In this case, in the encoding step according to embodiments, encoding may be performed in units of a slice or a tile including one or more slices.

Transmitting a bitstream including encoded point cloud data and/or signaling information (37002) refers to a step of transmitting encoded point cloud data and/or signaling information in the form of a bitstream according to embodiments. The step 37002 of transmitting the bitstream including the encoded point cloud data and/or signaling information according to the embodiments may be performed in the transmitter 10003 of FIG. 1, and the transmission 20002 of FIG. This may mean, and may mean the step of the transmission processing unit 12012 of FIG. 12.

A bitstream according to embodiments may be configured in a bitstream structure as described with reference to FIGS. 19, 20, 28, and 29. A bitstream according to embodiments may include parameters shown in FIGS. 21 to 23, 25 to 27, and/or 30 to 33.

According to embodiments, a sequence parameter set for indicating a sequence of point cloud data may be included. The sequence parameter set according to the embodiments includes first information indicating whether or not geometry information is encoded based on a plurality of types (for example, sps_variable_geometry_flag according to the embodiments) and/or attribute information. It may include second information (eg, sps_variable_atribute_flag) indicating whether encoding is performed based on types.

According to embodiments, the step 37001 of encoding the point cloud data may mean encoding in a slice unit. In this case, the bitstream is one or more slices including attribute information of the encoded point cloud data, a geometry parameter set and/or an attribute parameter for indicating information about point cloud data in the slices. A set (Attribute Parameter Set) may be further included. In this case, when the attribute information is encoded based on a plurality of types, the slice may include an attribute slice header including information related to a method of encoding attribute information in the slice.

According to embodiments, the encoding of the point cloud data 37001 may perform encoding in a tile unit including one or more slices. In this case, the bitstream may further include a tile parameter set for indicating information on one or more tiles and/or point cloud data in the tiles. A tile according to embodiments includes one or more slices, a geometry parameter set and an attribute parameter set for indicating information about data in one or more slices, and the attribute parameter set encodes attribute information in the slice. It may contain information related to how to do it.

According to embodiments, the encoding of the point cloud data 37001 may perform encoding in a tile unit including one or more slices. In this case, the bitstream may further include a tile parameter set for indicating information on one or more tiles and/or point cloud data in the tiles. In this case, the tile may include one or more slices, and the slice may include a geometry parameter set and an attribute parameter set for indicating information about data in the slice. In addition, the attribute parameter set may include information related to a method of encoding attribute information in a slice.

38 illustrates a method of receiving point cloud data according to embodiments.

The method of receiving point cloud data according to embodiments includes receiving a bitstream including point cloud data and/or signaling information (38000), decoding the point cloud data (38001), and/or decoded point cloud data. It may include the step of rendering (38002).

In step 38000 of receiving a bitstream including point cloud data and/or signaling information, a point cloud data bitstream according to embodiments may be received. It may be performed by the receiver 10007 of FIG. 1, and may include operations of the trajectory 20002 of FIG. 2 and the reception unit 13000 of FIG. 13.

The bitstream according to embodiments may include a sequence parameter set including information on a sequence of point cloud data. In the sequence parameter set, first information ( sps_variable_geometry_flag) indicating whether geometry information of point cloud data is encoded based on a plurality of types and/or attribute information of point cloud data is encoded based on a plurality of types. It may include second information ( sps_variable_atribute_flag ) indicating whether or not.

The bitstream according to embodiments may further include a tile parameter set including information on one or more tiles and/or one or more tiles. The tile according to the embodiments is a geometry parameter set and/or an attribute parameter set for representing information about data in one or more slices and/or one or more slices. Parameter Set) may be further included.

A bitstream according to embodiments may be configured in a bitstream structure as described with reference to FIGS. 19, 20, 28, and 29. A bitstream according to embodiments may include parameters shown in FIGS. 21 to 23, 25 to 27, and/or 30 to 33.

According to embodiments, a sequence parameter set for indicating a sequence of point cloud data may be included. The sequence parameter set according to the embodiments includes first information indicating whether or not geometry information is encoded based on a plurality of types (eg, sps_variable_geometry_flag according to the embodiments) and/or attribute information. It may include second information (eg, sps_variable_atribute_flag) indicating whether encoding is performed based on types.

The bitstream according to embodiments includes one or more slices including attribute information of encoded point cloud data, a geometry parameter set for indicating information on point cloud data in the slices, and/or It may further include an attribute parameter set. In this case, when the attribute information is encoded based on a plurality of types, the slice may include an attribute slice header including information related to a method of encoding attribute information in the slice.

The bitstream according to embodiments may further include a tile parameter set for indicating information on one or more tiles and/or point cloud data in the tiles. A tile according to embodiments includes one or more slices, a geometry parameter set and an attribute parameter set for indicating information about data in one or more slices, and the attribute parameter set encodes attribute information in the slice. It may contain information related to how to do it.

The bitstream according to embodiments may further include a tile parameter set for indicating information on one or more tiles and/or point cloud data in the tiles. In this case, the tile may include one or more slices, and the slice may include a geometry parameter set and an attribute parameter set for indicating information about data in the slice. In addition, the attribute parameter set may include information related to a method of encoding attribute information in a slice.

The step of decoding the point cloud data 38001 includes decoding geometric information based on first information according to embodiments and/or decoding attribute information based on second information according to embodiments. can do. The decoding of attribute information according to embodiments may decode point cloud data based on information on tiles included in the tile parameter set and information on slices included in the attribute parameter set.

Each of the above-described parts, modules or units may be software, processor, or hardware parts that execute successive processes stored in a memory (or storage unit). Each of the steps described in the above-described embodiment may be performed by processor, software, and hardware parts. Each module/block/unit described in the above-described embodiment may operate as a processor, software, or hardware. In addition, the methods suggested by the embodiments may be executed as code. This code can be written to a storage medium that can be read by the processor, and thus can be read by a processor provided by the apparatus.

For convenience of explanation, each drawing has been described separately, but it is also possible to design a new embodiment by merging the embodiments described in each drawing. In addition, designing a computer-readable recording medium in which a program for executing the previously described embodiments is recorded is also within the scope of the rights of the embodiments according to the needs of the skilled person.

The apparatus and method according to the embodiments are not limitedly applicable to the configuration and method of the described embodiments as described above, but the above-described embodiments are all or part of each of the embodiments so that various modifications can be made. It may be configured in combination.

On the other hand, it is possible to implement the method proposed by the embodiments as a code readable by the processor on a recording medium readable by the processor provided in the network device. The processor-readable recording medium includes all types of recording devices that store data that can be read by the processor. Examples of recording media that can be read by the processor include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, etc., and also include those implemented in the form of carrier waves such as transmission through the Internet. . In addition, the processor-readable recording medium is distributed over a computer system connected through a network, so that the processor-readable code can be stored and executed in a distributed manner.

In addition, although preferred embodiments of the embodiments have been illustrated and described above, the embodiments are not limited to the specific embodiments described above, and the technical field to which the present invention belongs without departing from the gist of the embodiments claimed in the claims. In addition, various modifications can be implemented by those of ordinary skill in the art, and these modifications should not be understood individually from the technical idea or prospect of the embodiments.

It is understood by those skilled in the art that various changes and modifications are possible in the embodiments without departing from the spirit or scope of the embodiments. Accordingly, the embodiments are intended to cover variations and modifications of the embodiments provided within the appended claims and their equivalents.

In the present specification, both apparatus and method inventions are mentioned, and descriptions of both apparatus and method inventions may be applied to complement each other.

In this document, “/” and “,” are interpreted as “and/or”. For example, “A/B” is interpreted as “A and/or B”, and “A, B” is interpreted as “A and/or B”. Additionally, “A/B/C” means “at least one of A, B and/or C”. In addition, “A, B, C” also means “at least one of A, B and/or C”. (In this document, the term “/” and “,” should be interpreted to indicate “and/or.” For instance, the expression “A/B” may mean “A and/or B.” Further, “A, B” may mean “A and/or B.” Further, “A/B/C” may mean “at least one of A, B, and/or C.” Also, “A/B/C” may mean “ at least one of A, B, and/or C.”)

Additionally, in this document “or” is to be interpreted as “and/or”. For example, “A or B” may mean 1) only “A”, 2) only “B”, or 3) “A and B”. In other words, “or” in this document may mean “additionally or alternatively”. (Further, in the document, the term “or” should be interpreted to indicate “and/or.” For instance, the expression “A or B” may comprise 1) only A, 2) only B, and/or 3) both A and B. In other words, the term “or” in this document should be interpreted to indicate “additionally or alternatively.”)

Various elements of the embodiments may be performed by hardware, software, firmware, or a combination thereof. Various elements of the embodiments may be implemented on a single chip such as a hardware circuit. Depending on the embodiments, the embodiments may optionally be performed on individual needles. Depending on the embodiments, at least one of the elements of the embodiments may be executed in one or more processors including instructions for performing operations according to the embodiments.

Terms such as first and second are used to describe various elements of the embodiments. These terms do not limit the interpretation of the elements of the embodiments. These terms are used to distinguish between one element and another. For example, a first user input signal may be referred to as a second user input signal. Similarly, the second user input signal may be referred to as a first user input signal. These terms can be interpreted within the scope of the embodiments. Both the first user input signal and the second user input signal are user input signals, and do not mean the same user input signals unless clearly indicated in context.

The terms used to describe the embodiments are used for the purpose of describing specific embodiments, and are not intended to limit the embodiments. As used in the description of the embodiments and in the claims, the singular is intended to include the plural unless the context clearly indicates. And/or the expression is used in a sense including all possible combinations between terms. The include expression describes the existence of features, numbers, steps, elements, and/or components, and does not imply that no additional features, numbers, steps, elements, and/or components are included. .

Conditional expressions such as when, when, and when used to describe the embodiments are not limited to an optional case. When a specific condition is satisfied, it is intended to perform a related operation in response to a specific condition or to interpret the related definition.

It has been described in detail in the best mode for carrying out the invention.

It is apparent to those skilled in the art that various changes and modifications are possible in the present invention without departing from the spirit or scope of the present invention. Accordingly, the present invention is intended to cover modifications and variations of the present invention provided within the appended claims and their equivalents.

Claims (20)

1. Encoding the point cloud data; And

   Transmitting a bitstream including the point cloud data; Containing,

   Point cloud data transmission method.
2. The method of claim 1, wherein the encoding step,

   Dividing geometry information of the point cloud data and attribute information of the point cloud data based on a slice or a tile including one or more slices;

   Encoding geometry information of the point cloud data and attribute information of the point cloud data in units of the slice or the tile; And

   Combining the encoded point cloud data in units of the slice or the tile; Included,

   Point cloud data transmission method.
3. The method of claim 2,

   The bitstream includes a sequence parameter set for indicating a sequence of the point cloud data,

   The sequence parameter set includes first information indicating whether the geometry information is encoded based on a plurality of types and second information indicating whether the attribute information is encoded based on a plurality of types. ,

   Point cloud data transmission method.
4. The method of claim 3, wherein when the encoding step is performed in a slice unit,

   The bitstream includes one or more slices including attribute information of the encoded point cloud data, a geometry parameter set for indicating information on point cloud data in the slices, and the attribute parameter set It further includes (Attribute Parameter Set),

   When the attribute information is encoded based on a plurality of types, the slice includes an attribute slice header including information related to a method of encoding attribute information in the slice,

   Point cloud data transmission method.
5. The method of claim 3,

   When the encoding step is performed in units of tiles including one or more slices,

   The bitstream further comprises a tile parameter set for indicating information on one or more tiles and point cloud data in the tiles,

   Point cloud data transmission method.
6. The method of claim 5,

   The tile includes one or more slices, a geometry parameter set and an attribute parameter set for representing information about data in the one or more slices,

   The attribute parameter set includes information related to a method of encoding attribute information in the slice,

   Point cloud data transmission method.
7. The method of claim 5,

   The tile includes one or more slices,

   The slice includes a geometry parameter set and an attribute parameter set for representing information about data in the slice,

   The attribute parameter set includes information related to a method of encoding attribute information in the slice,

   Point cloud data transmission method.
8. An encoder for encoding point cloud data; And

   A transmitter for transmitting a bitstream including the point cloud data; Containing,

   Point cloud data transmission device.
9. The method of claim 8, wherein the encoder,

   Dividing geometry information of the point cloud data and attribute information of the point cloud data based on a slice or a tile including one or more slices;

   Encoding geometry information of the point cloud data and attribute information of the point cloud data in units of the slice or the tile; And

   Combining the encoded point cloud data in units of the slice or the tile; To do,

   Point cloud data transmission device.
10. The method of claim 9,

    The bitstream includes a sequence parameter set for indicating a sequence of the point cloud data,

    The sequence parameter set includes first information indicating whether the geometry information is encoded based on a plurality of types, and second information indicating whether the attribute information is encoded based on a plurality of types. ,

    Point cloud data transmission device.
11. The method of claim 10, wherein when the encoder is performed in a slice unit,

    The bitstream includes one or more slices including attribute information of the encoded point cloud data, a geometry parameter set and the attribute parameter set for indicating information on point cloud data in the slices It further includes (Attribute Parameter Set),

    When the attribute information is encoded based on a plurality of types, the slice includes an attribute slice header including information related to a method of encoding attribute information in the slice,

    Point cloud data transmission device.
12. The method of claim 10,

    When the encoder is performed in a tile unit including one or more slices,

    The bitstream further comprises a tile parameter set for indicating information on one or more tiles and point cloud data in the tiles,

    Point cloud data transmission device.
13. The method of claim 12,

    The tile includes one or more slices, a geometry parameter set and an attribute parameter set for representing information about data in the one or more slices,

    The attribute parameter set includes information related to a method of encoding attribute information in the slice,

    Point cloud data transmission device.
14. The method of claim 12,

    The tile includes one or more slices,

    The slice includes a geometry parameter set and an attribute parameter set for representing information about data in the slice,

    The attribute parameter set includes information related to a method of encoding attribute information in the slice,

    Point cloud data transmission device.
15. Receiving a bitstream including point cloud data;

    Decoding the point cloud data; And

    Rendering the point cloud data; Containing,

    How to receive point cloud data.
16. The method of claim 15,

    The bitstream includes a sequence parameter set including information on a sequence of the point cloud data,

    The sequence parameter set includes first information indicating whether geometry information of the point cloud data is encoded based on a plurality of types, and whether attribute information of the point cloud data is encoded based on a plurality of types. Including second information indicating,

    The decoding step comprises decoding the geometry information based on the first information and decoding the attribute information based on the second information,

    How to receive point cloud data.
17. The method of claim 16, wherein the bitstream further comprises one or more tiles and a tile parameter set including information on the one or more tiles,

    The tile further includes a geometry parameter set and an attribute parameter set for representing information about data in one or more slices and the one or more slices, and ,

    The decoding of the attribute information comprises decoding the point cloud data based on information on tiles included in the tile parameter set and information on slices included in the attribute parameter set,

    How to receive point cloud data.
18. A receiving unit receiving a bitstream including point cloud data;

    A decoder for decoding the point cloud data; And

    A renderer for rendering the point cloud data; Containing,

    Point cloud data receiving device.
19. The method of claim 18,

    The bitstream includes a sequence parameter set including information on a sequence of the point cloud data,

    The sequence parameter set includes first information indicating whether geometry information of the point cloud data is encoded based on a plurality of types, and whether attribute information of the point cloud data is encoded based on a plurality of types. Including second information indicating,

    The decoder comprises a geometry decoder for decoding the geometry information based on the first information and an attribute decoder for decoding the attribute information based on the second information,

    Point cloud data receiving device.
20. The method of claim 16, wherein the bitstream further comprises one or more tiles and a tile parameter set including information on the one or more tiles,

    The tile further includes a geometry parameter set and an attribute parameter set for representing information about data in one or more slices and the one or more slices, and ,

    The attribute decoder decodes the point cloud data based on information on tiles included in the tile parameter set and information on slices included in the attribute parameter set,

    Point cloud data receiving device.

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