RU2792020C1 - Method and device for encoding point cloud - Google Patents

Abstract

FIELD: information technology.

SUBSTANCE: invention relates to the field of encoding a point cloud. The first signal information is received from an encoded bit stream for a point cloud, which includes a set of points in a three-dimensional (3D) space. The first signal information indicates information about splitting the point cloud. The second signal information is determined based on the first signal information indicating the first value. The second signal information indicates a mode of splitting the set of points in the three-dimensional space. Next, the mode of splitting the set of points in the three-dimensional space is determined based on the second signal information. After that, the point cloud is restored based on the splitting mode.

EFFECT: provision of a possibility of compression of a point cloud without losses.

14 cl, 16 dwg, 5 tbl

Description

INCLUDING BY LINK

[0001] The present application claims priority under U.S. Patent Application No. 17/203,155, "METHOD AND APPARATUS FOR POINT CLOUD ENCODING", filed March 16, 2021, which claims priority priority of U.S. Provisional Application No. 63/004,304, "METHOD AND DEVICE FOR FLEXIBLE PARTITION OF QUAD-TREE AND BINARY-TREE FOR GEOMETRIC ENCODING”, filed April 2, 2020. The entire disclosures of prior applications are hereby incorporated by reference.

FIELD OF TECHNOLOGY

[0002] The present invention describes embodiments generally related to point cloud coding.

BACKGROUND OF THE INVENTION

[0003] The description of the prior art provided herein is intended to provide a general overview of the context of the invention. The work of the inventors, to the extent that it is described in this section on the prior art, as well as aspects of the description that cannot be considered prior art at the time of filing, are not expressly or impliedly recognized as prior art with respect to of the present invention.

[0004] Various technologies have been developed for capturing and representing the world, such as objects in the world, environments in the world, and the like, in three-dimensional (3D) space. Three-dimensional representations of the world can provide more immersive forms of interaction and communication. Point clouds can be used as a 3D representation of the world. A point cloud is a collection of points in 3D space, each of which has associated attributes, such as color, material properties, texture information, intensity attributes, reflectivity attributes, motion-related attributes, modality attributes, and/or various other attributes. Such point clouds can contain large amounts of data, and their storage and transmission can be time and cost intensive.

SUMMARY OF THE INVENTION

[0005] Aspects of the invention provide methods and apparatus for compressing and decompressing a point cloud. According to an aspect of the invention, a method for geometrically decoding a point cloud in a point cloud decoder is provided. In this method, the first signaling information may be obtained from an encoded bitstream for a point cloud that includes a set of points in three-dimensional (3D) space. The first signaling information may indicate partitioning information of the point cloud. The second signaling information may be determined based on the first signaling information indicating the first value. The second signaling information may indicate the mode of splitting the set of points in three-dimensional space. In addition, the splitting mode of the set of points in the three-dimensional space can be determined based on the second signal information. The point cloud can be subsequently reconstructed depending on the partitioning mode.

[0006] In some embodiments, the split mode may be determined as a predefined split of a Quad-tree and Binary-tree (QtBt) based on second signaling information indicating a second value.

[0007] The method may receive third signal information that indicates that the three-dimensional space is an asymmetric cuboid. The dimensions of the three-dimensional space that are communicated along the x, y, and z axes may be determined based on the third signal information indicating the first value.

[0008] In some embodiments, 3-bit signaling information may be determined for each of a plurality of split levels in a split mode based on the second signaling information indicating the first value. The 3-bit signaling information for each of the plurality of split levels may indicate split directions along the x, y, and z axes for the corresponding split level in the split mode.

[0009] In some embodiments, the implementation of the 3-bit signaling information may be determined based on the dimensions of the three-dimensional space.

[0010] In the method, a split mode may be determined based on a first signaling information indicating a second value, where the split mode may include a corresponding split of an octree in each of the plurality of split levels in the split mode.

[0011] According to an aspect of the invention, a method for geometrically decoding a point cloud in a point cloud decoder is provided. In this method, the first signaling information may be obtained from an encoded bitstream for a point cloud that includes a set of points in three-dimensional (3D) space. The first signaling information may indicate partitioning information of the point cloud. The partitioning mode of the set of points in the 3D space may be determined based on the first signal information, and the partitioning mode may include a plurality of partitioning levels. The point cloud can subsequently be reconstructed based on the mesh mode.

[0012] In some embodiments, the 3-bit signaling information for each of the multiple split levels in the split mode may be determined based on the first signaling information indicating the first value, where the 3-bit signaling information for each of the multiple split levels may indicate split directions. in the x, y, and z directions for the corresponding split level in split mode.

[0013] In some embodiments, the implementation of 3-bit signaling information may be determined based on the dimensions of the three-dimensional space.

[0014] In some embodiments, a split mode may be defined to include a corresponding split of the octree in each of the multiple split levels in the split mode based on the first signaling information indicating the second value.

[0015] In the method, the second signaling information may additionally be received from the encoded bitstream for the point cloud. The second signaling information may indicate that the 3D space is an asymmetric cuboid when the second signaling information is the first value, and the 3D space is a symmetrical cuboid when the second signaling information is the second value.

[0016] In some embodiments, based on the first signaling information indicating the second value and the second signaling information indicating the first value, the split mode may be determined to include a corresponding split of the octree in each of the first split levels in the split mode split level set. The split type and the split direction of the last split level from the multiple split levels of the split mode can be determined according to the following conditions:

where d _x , d _y , and d _z are log2 dimensions of three-dimensional space along the x, y, and z axes, respectively.

[0017] In the method, the second signaling information may be determined based on the first signaling information indicating the first value. The second signaling information may indicate that the 3D space is an asymmetric cuboid when the second signaling information indicates a first value, and the 3D space is a symmetrical cuboid when the second signaling information indicates a second value. In addition, the dimensions of the three-dimensional space that are communicated in the x, y, and z directions can be determined based on the second signal information indicating the first value.

[0018] In some examples, a point cloud data processing apparatus includes a receiving circuit and a processing circuit that are configured to perform one or more of the methods described above.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Additional features, nature and various advantages of the disclosed subject matter will be better understood from the following detailed description and the accompanying drawings, in which:

[0020] FIG. 1 is a schematic illustration of a simplified block diagram of a communication system in accordance with an embodiment;

[0021] FIG. 2 is a schematic illustration of a simplified block diagram of a streaming system according to an embodiment;

[0022] FIG. 3 shows a block diagram of an encoder for encoding point cloud frames, according to some embodiments;

[0023] FIG. 4 shows a block diagram of a decoder for decoding a compressed bitstream corresponding to point cloud frames, according to some embodiments;

[0024] FIG. 5 is a schematic illustration of a simplified block diagram of a video decoder according to an embodiment;

[0025] FIG. 6 is a schematic illustration of a simplified block diagram of a video encoder according to an embodiment;

[0026] FIG. 7 shows a block diagram of a decoder for decoding a compressed bitstream corresponding to point cloud frames, according to some embodiments;

[0027] FIG. 8 shows a block diagram of an encoder for encoding point cloud frames, according to some embodiments;

[0028] FIG. 9 shows a diagram illustrating cube partitioning based on an octree partitioning technique according to some embodiments of the present invention.

[0029] FIG. 10 shows an example of an octree split and an octree structure corresponding to the octree split, according to some embodiments of the invention.

[0030] FIG. 11 shows a point cloud with a bounding box shorter in the z-direction, in accordance with some embodiments of the invention.

[0031] FIG. 12 shows a diagram illustrating cube partitioning based on the x-y, x-z, and y-z octree partitioning technique, in accordance with some embodiments of the invention.

[0032] FIG. 13 shows a diagram illustrating cube partitions based on the x, y, and z binary partitioning method, in accordance with some embodiments of the invention.

[0033] FIG. 14 shows a first flowchart describing a first example of a process in accordance with some embodiments.

[0034] FIG. 15 shows a second flowchart describing a second process example in accordance with some embodiments.

[0035] FIG. 16 is a schematic illustration of a computer system in accordance with an embodiment.

DETAILED DESCRIPTION OF EMBODIMENTS

[0036] Enhanced 3D representations of the world enable more immersive forms of interaction and communication, and allow machines to understand, interpret, and navigate our world. Three-dimensional point clouds emerged as a way to represent such information. A number of use cases related to point cloud data have been identified and corresponding requirements have been developed for point cloud representation and compression. For example, a 3D point cloud can be used in autonomous driving to detect and localize objects. The 3D point cloud can also be used in geographic information systems (GIS) for mapping and used in cultural heritage to visualize and archive cultural heritage objects and collections.

[0037] A point cloud is generally a collection of points in three-dimensional space, each with attributes associated with it. The attributes may include color, material properties, texture information, intensity attributes, reflectivity attributes, motion-related attributes, modality attributes, and/or various other attributes. Point clouds can be used to recreate an object or scene as a composition of such points. The points may be captured using a variety of cameras, depth sensors and/or lidar in various settings and may include thousands to billions of points to realistically represent rendered scenes.

[0038] Compression techniques can reduce the amount of data needed to represent a point cloud for faster transmission or reduced memory footprint. Thus, technologies are needed to compress lossy point clouds for use in real-time communications and virtual reality with six degrees of freedom (6 DoF). In addition, lossless point cloud compression technology is required in the context of dynamic mapping for autonomous driving, cultural heritage applications, etc. Thus, ISO / IEC MPEG (JTC 1 / SC 29 / WG 11) began work on a standard to solve the compression problem geometry and attributes such as colors and reflectivity, scalable/progressive encoding, encoding of point cloud sequences acquired over time, and random access to point cloud subsets.

[0039] FIG. 1 illustrates a simplified block diagram of a communication system (100) according to an embodiment of the present invention. The communication system (100) includes a plurality of terminal devices that can communicate with each other, for example, via a network (150). For example, the communication system (100) includes a pair of terminals (110) and (120) interconnected via a network (150). In the example in FIG. 1, the first pair of terminals (110) and (120) may perform unidirectional transmission of point cloud data. For example, tag (110) may compress a point cloud (eg, points representing structure) that is captured by a sensor (105) connected to tag (110). The compressed point cloud may be transmitted, for example, in the form of a bit stream, to another terminal device (120) via the network (150). The terminal device (120) may receive the compressed point cloud from the network (150), decompress the bitstream to recover the point cloud, and display the recovered point cloud appropriately. One-way communication may be common in media serving applications and the like.

[0040] In the example of Figure 1, terminal devices (110) and (120) can be illustrated as servers and personal computers, but the principles of the present invention cannot be limited to this. Embodiments of the present invention find application in laptop computers, tablet computers, smartphones, game terminals, media players, and/or specialized three-dimensional (3D) equipment. Network (150) represents any number of networks that transmit compressed point cloud between terminals (110) and (120). Network (150) may include, for example, wired lines (wired) and/or wireless communication networks. The network (150) may communicate on circuit-switched and/or packet-switched channels. Representative networks include telecommunications networks, local area networks, wide area networks and/or the Internet. For the purposes of this discussion, the architecture and topology of the network (150) may not be essential to the operation of the present invention unless explained herein below.

[0041] FIG. 2 illustrates a simplified block diagram of a streaming system (200) in accordance with an embodiment. The example in FIG. 2 is an application for the disclosed subject matter to a point cloud. The disclosed subject matter may be equally applicable to other point cloud enabled applications such as a 3D telepresence application, a virtual reality application, and the like.

[0042] The streaming system (200) may include a capture subsystem (213). The capture subsystem (213) may include a source (201) of a point cloud, for example, light detection and ranging (LIDAR) systems, 3D cameras, 3D scanners, a graphics generation component that generates uncompressed a point cloud in software; and the like that generates, for example, point clouds (202) that are uncompressed. In an example, point clouds (202) include points captured by 3D cameras. The point clouds (202) are shown with a heavy line to emphasize the large amount of data compared to the compressed point clouds (204) (compressed point cloud bitstream). The compressed point clouds (204) may be generated by an electronic device (220) that includes an encoder (203) coupled to a point cloud source (201). The encoder (203) may include hardware, software, or a combination thereof for providing or implementing aspects of the disclosed subject matter, as described in more detail below. Compressed point clouds (204) (or bitstream of compressed point clouds (204)), depicted with a thin line to emphasize the smaller amount of data compared to the stream of point clouds (202), can be stored on the stream server (205) for future use. One or more streaming client subsystems, such as client subsystems (206) and (208) in FIG. 2 can access the streaming server (205) to extract copies (207) and (209) of the compressed point cloud (204). The client subsystem (206) may include a decoder (210), such as in an electronic device (230). The decoder (210) decodes the incoming copy (207) of the compressed point clouds and creates an outgoing stream of reconstructed point clouds (211) that can be rendered on the renderer (212).

[0043] It should be noted that electronic devices (220) and (230) may include other components (not shown). For example, electronic device (220) may include a decoder (not shown), and electronic device (230) may also include an encoder (not shown).

[0044] In some streaming systems, compressed point clouds (204), (207) and (209) (eg, compressed point cloud bitstreams) may be compressed in accordance with certain standards. In some examples, video coding standards are used when compressing point clouds. Examples of these standards include High Efficiency Video Coding (HEVC), Versatile Video Coding (VVC), and the like.

[0045] FIG. 3 shows a block diagram of a V-PCC encoder (300) for encoding point cloud frames, according to some embodiments. In some embodiments, a V-PCC encoder (300) may be used in a communication system (100) and a streaming system (200). For example, the encoder (203) may be configured and operate similarly to the encoder (300) V-PCC.

[0046] The V-PCC encoder (300) receives point cloud frames as uncompressed input and generates a bitstream corresponding to the compressed point cloud frames. In some embodiments, the V-PCC encoder (300) may receive point cloud frames from a point cloud source, such as a point cloud source (201) or the like.

[0047] In the example of FIG. 3, the V-PCC encoder (300) includes a patch generation module (306), a patch packing module (308), a geometric image generation module (310), a texture image generation module (312), a patch information module (304), occupancy map module (314), smoothing module (336), image filling modules (316) and (318), group extension module (320), video compression modules (322), (323) and (332), module (338) patch side information compression, an entropy compression module (334), and a multiplexer (324).

[0048] According to an aspect of the invention, the V-PCC encoder (300) converts 3D point cloud frames into an image-based representation along with some metadata (e.g., occupancy map and patch information) that is used to convert the compressed point cloud back to a decompressed cloud. points. In some examples, the V-PCC encoder (300) may convert 3D point cloud frames into geometry images, texture images, and occupancy maps, and then use video coding techniques to encode the geometry images, texture images, and occupancy maps into a bitstream. Typically, a geometry image is a two-dimensional image with pixels filled with geometric values associated with points projected onto the pixels, and a pixel filled with a geometry value may be referred to as a geometry reference. A texture image is a two-dimensional image with pixels filled with texture values associated with dots projected onto the pixels, and a pixel filled with a texture value may be referred to as a texture sample. An occupancy map is a 2D image with pixels filled with values that indicate they are occupied or not occupied by patches.

[0049] A patch (patch, "flap") can generally refer to a continuous subset of a surface described by a point cloud. In one example, the patch includes points with surface normal vectors that deviate from each other by less than a threshold amount. The patch generation module (306) segments the point cloud into a set of patches, which may or may not overlap, so that each patch can be described by a depth field with respect to a plane in two-dimensional space. In some embodiments, the patch generation module (306) aims to decompose the point cloud into a minimum number of patches with smooth boundaries, as well as to minimize the recovery error.

[0050] The patch information module (304) may collect patch information that indicates patch sizes and shapes. In some examples, patch information may be packed into an image frame and then encoded by patch side information compression module 338 to generate compressed patch side information.

[0051] The patch packing module (308) is configured to apply extracted patches to a two-dimensional (2D) grid, minimizing wasted space and ensuring that each MxM (eg, 16x16) grid block is associated with a unique patch. Efficient patch packing can directly affect compression efficiency, either by minimizing wasted space or by ensuring consistency over time.

[0052] The module (310) generating geometric images can generate two-dimensional geometric images associated with the geometry of the point cloud at the given patch locations. Module (312) generating texture images can generate two-dimensional texture images associated with the texture of the point cloud at the given patch locations. The module (310) generating geometric images and the module (312) generating texture images use the 3D to 2D transformation calculated during the packing process to save the geometry and texture of the point cloud as images. To better handle the case where multiple points are projected onto the same sample, each patch is projected onto two images called layers. In the example, the geometric image is represented by a WxH monochromatic frame in YUV420-8 bit format. To generate texture images, the texture generation procedure uses the reconstructed/smoothed geometry to calculate the colors to be associated with the resample points.

[0053] The occupancy map module (314) may generate an occupancy map that describes padding information in each block. For example, the busy image includes a binary map that indicates, for each grid cell, whether the cell belongs to empty space or a point cloud. In the example, the occupancy map uses binary information describing for each pixel whether the pixel is full or not. In another example, the occupancy map uses binary information describing, for each pixel block, whether the pixel block is full or not.

[0054] The occupancy map generated by the occupancy map module (314) may be compressed using lossless coding or lossy coding. When lossless coding is used, the entropy compression unit (334) is used to compress the occupancy map. When lossy coding is used, the video compression module (332) is used to compress the occupancy map.

[0055] It should be noted that the patch packing module (308) may leave some blank spaces between two-dimensional patches packed in an image frame. The image padding modules (316) and (318) may pad empty spaces (referred to as padding) to create an image frame that may be suitable for 2D video and image codecs. Image padding is also called background padding, which can fill unused space with redundant information. In some examples, good background padding minimally increases the bit rate and does not introduce significant coding distortion around patch boundaries.

[0056] The video compression modules (322), (323), and (332) can encode 2D images such as augmented geometry images, augmented texture images, and occupancy maps based on a suitable video coding standard such as HEVC, VVC, etc. similar. In one example, video compression modules (322), (323), and (332) are separate components that operate separately. It should be noted that modules (322), (323) and (332) video compression in another example can be implemented as one component.

[0057] In some examples, the smoothing module (336) is configured to create a smoothed image of the reconstructed geometric image. A smoothed image may be provided to generate 312 texture images. The texture image generation (312) can then adjust the generation of texture images based on the reconstructed geometric images. For example, when a patch shape (eg, geometry) is slightly distorted during encoding and decoding, the distortion can be taken into account when generating texture images to correct patch shape distortion.

[0058] In some embodiments, the group extension (320) is configured to fill pixels around object boundaries with redundant low frequency content to improve the encoding factor as well as the visual quality of the reconstructed point cloud.

[0059] The multiplexer (324) may multiplex the compressed geometric image, the compressed texture image, the compressed occupancy map, and/or the compressed patch side information into a compressed bitstream.

[0060] FIG. 4 shows a block diagram of a V-PCC decoder (400) for decoding a compressed bitstream corresponding to point cloud frames, according to some embodiments. In some embodiments, the V-PCC decoder (400) may be used in the communication system (100) and the streaming system (200). For example, decoder (210) may be configured to operate similarly to V-PCC decoder (400). The V-PCC decoder (400) receives the compressed bitstream and generates a reconstructed point cloud based on the compressed bitstream.

[0061] In the example of FIG. 4, the V-PCC decoder (400) includes a demultiplexer (432), video decompressors (434) and (436), a busy map decompressor (438), a side information decompressor (442) about patches, a geometry recovery module (444), an anti-aliasing module (446), a texture recovery module (448), and a color smoothing module (452).

[0062] The demultiplexer (432) may receive and separate the compressed bitstream into a compressed texture image, a compressed geometric image, a compressed occupancy map, and a compressed patch side information.

[0063] The video decompressing modules (434) and (436) can decode the compressed images according to an appropriate standard (eg, HEVC, VVC, etc.) and output the decompressed images. For example, the video decompressor (434) decodes the compressed texture images and outputs the decompressed texture images; and the video decompressor (436) decodes the compressed geometric images and outputs the decompressed geometric images.

[0064] The occupancy map decompressor (438) may decode the compressed occupancy maps according to an appropriate standard (eg, HEVC, VVC, etc.) and output the decompressed occupancy maps.

[0065] The patch side information decompressor 442 may decode the compressed patch side information according to an appropriate standard (eg, HEVC, VVC, etc.) and output the decompressed patch side information.

[0066] The geometry recovery module (444) may receive the decompressed geometry images and generate the reconstructed point cloud geometry based on the decompressed occupancy map and the decompressed patch assistance information.

[0067] The smoothing module (446) can smooth out inconsistencies at the edges of the patches. The smoothing procedure is aimed at eliminating potential inhomogeneities that may occur at patch boundaries due to compression artifacts. In some embodiments, an anti-aliasing filter may be applied to pixels located at patch boundaries to mitigate distortion that may be caused by compression/decompression.

[0068] The texture reconstruction module (448) may determine texture information for points in a point cloud based on decompressed texture images and anti-aliasing geometry.

[0069] The color smoothing module (452) can smooth out color inconsistencies. Non-adjacent patches in 3D space are often packed next to each other in 2D video. In some examples, pixel values from non-adjacent patches may be mixed by a block video codec. The purpose of color smoothing is to reduce visible artifacts that appear at patch boundaries.

[0070] FIG. 5 shows a block diagram of a video decoder (510) according to an embodiment of the present invention. The video decoder (510) may be used in the V-PCC decoder (400). For example, modules (434) and (436) video decompressing module (438) decompressing the busy map can be performed similarly to the video decoder (510).

[0071] The video decoder (510) may include a parser (520) for recovering symbols (521) from compressed images, such as an encoded video sequence. The categories of these symbols include information used to control the operation of the video decoder (510). The parser (520) may parse/entropy decode the received encoded video sequence. Encoding of the encoded video sequence may be in accordance with a video coding technology or standard, and may follow various principles including variable length coding, Huffman coding, arithmetic coding with or without context sensitivity, and so on. The parser (520) can extract from the encoded video sequence a set of subgroup parameters for at least one of the subgroups of pixels in the video decoder based on at least one parameter corresponding to the group. Subgroups may include groups of pictures (GOPs), pictures, tiles, slices, macroblocks, coding units (CUs), blocks (blocks), transform units (TUs), prediction units (PUs), and so on. The parser (520) may also extract information from the encoded video sequence, such as transform coefficients, quantizer parameter values, motion vectors, and so on.

[0072] The parser (520) may perform an entropy decoding/parsing operation on the video sequence received from the buffer memory to create symbols (521).

[0073] Symbol recovery (521) may involve using many different blocks depending on the type of encoded video image or parts thereof (eg, intra- and inter-picture, intra- and inter-block) and other factors. Which blocks are used and how can be controlled by the subgroup control information that has been parsed from the encoded video sequence by the parser (520). The flow of such subgroup control information between the parser (520) and the plurality of modules is not shown for simplicity.

[0074] In addition to the functional blocks already mentioned, the video decoder (510) can be conceptually subdivided into a number of functional blocks, as described below. In a practical implementation operating under commercial constraints, many of these devices interact closely with each other and can be at least partially integrated into one another. However, for purposes of describing the disclosed subject matter, the conceptual subdivision into functional blocks below is appropriate.

[0075] The first block is the scaling/inverse transform block (551). The scaling/inverse transform block (551) receives the quantized transform coefficient as well as control information, including which transform to use, block size, quantization factor, quantization scaling matrices, etc., in the form of symbol(s) (521 ) from the parser (520). Block (551) scaling / inverse transformation may output blocks containing the values of the samples that can be entered into the aggregator (555).

[0076] In some cases, the output samples of the block (551) scaling / inverse transformation may refer to the block with intra coding; that is, a block that does not use predictive information from previously restored images, but can use predictive information from previously restored portions of the current image. Such predictive information may be provided by an intra-picture predictor (552). In some cases, the intra-image prediction block (552) generates a block of the same size and shape as the reconstructed block, using the already reconstructed surrounding information retrieved from the current image buffer (558). The current picture buffer (558) buffers, for example, a partially restored current picture and/or a fully restored current picture. The aggregator (555) in some cases adds, for each sample, the prediction information generated by the intra prediction block (552) to the output sample information provided by the scaling/inverse transform block (551).

[0077] In other cases, the output samples of the scaling/inverse transform block (551) may refer to an inter-coded and potentially motion-compensated block. In such a case, the motion compensation prediction block (553) may access the reference picture memory (557) to retrieve samples used for prediction. After compensating for the movement of the selected samples according to the symbols (521) associated with the block, these samples can be added by the aggregator (555) to the output signal of the scaling/inverse transform block (551) (in this case called residual samples or residual signal) to generate output information. The addresses in the reference picture memory (557) from where the motion compensation prediction block (553) selects prediction samples may be controlled by the motion vectors available to the motion compensation prediction block (553) in the form of symbols (521), which may have, for example, X , Y and reference image components. Motion compensation may also include interpolation of sample values selected from the reference picture memory (557) when accurate sub-sample motion vectors are used, motion vector prediction mechanisms, and so on.

[0078] The output samples of the aggregator (555) may be subjected to various loop filtering methods in the loop filter block (556). The video compression technologies may include in-loop filtering technologies that are controlled by parameters included in the encoded video sequence (also referred to as the encoded video bitstream) and provided to the loop filtering block (556) as symbols (521) from the parser (520), but may also respond to meta-information received during decoding of the previous (in the order of decoding) parts of the encoded image or encoded video sequence, and also respond to the sample values previously restored and filtered by the contour filter.

[0079] The output of the loop filter block (556) may be a stream of samples that can be output to a renderer and also stored in reference picture memory (557) for use in future inter-picture prediction.

[0080] Some encoded pictures after full recovery can be used as reference pictures for future prediction. For example, after the encoded picture corresponding to the current picture has been completely reconstructed and the encoded picture has been identified as a reference picture (eg, by a parser (520)), the current picture buffer (558) may become part of the reference picture memory (557), and the fresh current picture buffer may be reallocated before starting the next encoded picture recovery.

[0081] The video decoder (510) may perform decoding operations according to a predetermined video compression technology in a standard such as ITU-T Rec. H.265. The encoded video sequence may conform to the syntax specified by the video compression technology or standard being used, in the sense that the encoded video sequence conforms to both the syntax of the video compression technology or standard and to the profiles documented in the video compression technology or standard. In particular, a profile may select certain tools as the only tools available for use in that profile, from among all the tools available in a video compression technology or standard. It may also be necessary for compliance that the complexity of the encoded video sequence be within limits defined by the level of technology or video compression standard. In some cases, levels limit the maximum image size, the maximum frame rate, the maximum recovery sampling rate (measured in megasamples (millions of samples) per second, for example), the maximum reference image size, and so on. The limits set by the layers may, in some cases, be further constrained by hypothetical reference decoder (HRD) specifications and metadata for managing the HRD buffer transmitted in the encoded video sequence.

[0082] FIG. 6 shows a block diagram of a video encoder (603) according to an embodiment of the present invention. A video encoder (603) may be used in a V-PCC encoder (300) that compresses point clouds. In the example, the video compression module (322) and (323) and the video compression module (332) are similar to the encoder (603).

[0083] The video encoder (603) may receive images, such as geometry augmented images, textured images, and the like, and generate compressed images.

[0084] According to an embodiment, the video encoder (603) may encode and compress images of the original video sequence (images) into an encoded video sequence (compressed images) in real time or with any other time constraints as required by the application. Providing an appropriate coding rate is one of the functions of the controller (650). In some embodiments, the controller (650) controls other functional blocks, as described below, and is operatively linked to other functional blocks. Communication is not shown for simplicity. Parameters set by the controller (650) may include parameters related to rate control (picture skip, quantizer, lambda value for rate-distortion optimization methods, ...), image size, group of pictures (GOP) layout, vector search maximum range movements and so on. The controller (650) may be configured to have other suitable functions that are related to the video encoder (603) optimized for a particular system design.

[0085] In some embodiments, video encoder (603) is configured to operate in a coding loop. As a simplified description, in an example, an encoding loop may include a source encoder (630) (eg, responsible for creating symbols, such as a stream of symbols, based on an input image to be encoded and reference image(s)), and a (local) decoder (633) embedded in the video encoder (603). The decoder (633) decompresses the symbols to create sample data, similar to how a (remote) decoder can do (because any compression between the symbols and the encoded video bitstream is lossless in the video compression technologies discussed in the disclosed subject matter). The reconstructed sample stream (sample data) is entered into the reference picture memory 634 . Since the decoding of the symbol stream produces bit-accurate results, regardless of the location of the decoder (local or remote), the contents of the reference picture memory (634) are also the same bit-for-bit for the local and remote encoders. In other words, the encoder's predictor "sees" as reference picture samples exactly the same sample values that the decoder "sees" when using prediction during decoding. This fundamental principle of reference picture synchronism (and the resulting drift if synchronism cannot be maintained due to, for example, channel errors) is also used in some related fields of technology.

[0086] The operation of the "local" decoder (633) may be the same as that of the "remote" decoder, such as the video decoder (510), which has already been described in detail above in connection with FIG. 5. Referring also briefly to FIG. 5, however, since the symbols are available and the entropy encoder (645) and parser (520) can be losslessly encoded/decoded into the encoded video sequence, the entropy decoding parts of the video decoder (510) including the parser (520) may not be fully implemented in the local decoder (633).

[0087] It may be noted here that any decoding technology other than syntactic/entropy decoding that is present in a decoder must also necessarily be present in a substantially identical functional form in a corresponding encoder. For this reason, the disclosed subject matter focuses on the operation of the decoder. The description of encoding technologies can be abbreviated as they are the inverse of fully described decoding technologies. Only in some areas a more detailed description is required, which is given below.

[0088] During operation, in some examples, source encoder (630) may perform motion-compensated predictive coding that predictively encodes an input picture with reference to one or more previously encoded pictures from a video sequence that have been labeled "reference pictures" . Thus, the encoding engine (632) encodes the differences between the pixel blocks of the input image and the pixel blocks of the reference image(s) that can be selected as the prediction reference(s) for the input image.

[0089] The local video decoder (633) may decode the encoded video data of pictures that can be marked as reference pictures based on the symbols generated by the source encoder (630). The operations of the encoding engine (632) provide the advantage that its operations can be lossy processes. When the encoded video data can be decoded in a video decoder (not shown in FIG. 6), the reconstructed video sequence can typically be a copy of the original video sequence with some errors. The local video decoder (633) replicates the decoding processes that may be performed by the video decoder on the reference pictures and may cause the recovered reference pictures to be stored in the reference picture cache (634). Thus, the video encoder (603) can locally store copies of the reconstructed reference pictures that share the same content as the reconstructed reference pictures to be received by the far-end video decoder (in the absence of transmission errors).

[0090] The predictor (635) may perform prediction searches for the encoding engine (632). That is, for a new picture to be encoded, the predictor (635) may search memory (634) for sample data reference pictures (as reference pixel block candidates) or certain metadata such as reference picture motion vectors, block shapes, etc. .d., which can serve as a suitable basis for predicting new images. The predictor (635) may operate on a sample-by-pixel basis to find appropriate references for prediction. In some cases, as determined by the search results obtained by the predictor (635), the input picture may have prediction references taken from a plurality of reference pictures stored in the reference picture memory (634).

[0091] The controller (650) may control the encoding operations of the source encoder (630), including, for example, setting parameters and subgroup parameters used to encode video data.

[0092] The output of all of the above functional blocks may be entropy encoded in an entropy encoder (645). An entropy encoder (645) converts symbols generated by various functional blocks into an encoded video sequence by lossless symbol compression to generate compressed images 643 in accordance with techniques such as Huffman coding, variable length coding, arithmetic coding, and so on.

[0093] The controller (650) may control the operation of the video encoder (603). During encoding, the controller (650) may assign to each encoded picture a certain type of encoded picture, which may affect the encoding methods that can be applied to the corresponding picture. For example, images can often be categorized as one of the following image types:

[0094] An Intra Picture (I-picture) may be one that can be encoded and decoded without using any other picture in the sequence as a prediction source. Some video codecs allow various types of intra-pictures, including, for example, independent decoder update ("IDR") pictures. Those skilled in the art are aware of these I-image variants and their respective applications and features.

[0095] A predictive picture (P-picture) may be one that can be encoded and decoded using intra prediction or inter prediction using at most one motion vector and a reference index to predict sample values of each block.

[0096] A bidirectional predictive picture (B-picture) may be one that can be encoded and decoded using intra-prediction or inter-prediction using at most two motion vectors and reference indices to predict sample values of each block. Similarly, multi-prediction images may use more than two reference images and associated metadata to reconstruct a single block.

[0097] Source images can typically be divided spatially into multiple blocks of samples (eg, blocks of 4x4, 8x8, 4x8, or 16x16 samples each) and encoded on a block-by-block basis. The blocks may be predictively encoded with reference to other (already encoded) blocks, as determined by the coding assignment applied to the corresponding block images. For example, blocks of I-pictures may be predictively encoded or they may be predictively encoded with reference to already encoded blocks of the same picture (spatial prediction or intra prediction). The pixel blocks of P-pictures may be predictively encoded, by spatial prediction, or by temporal prediction with reference to one previously encoded reference picture. The B-picture blocks may be predictively encoded, spatially predicted, or temporally predicted with reference to one or two previously encoded reference pictures.

[0098] The video encoder (603) may perform encoding operations according to a predetermined video coding technology or standard, such as ITU-T Rec. H.265. In operation, the video encoder (603) may perform various compression operations, including predictive coding operations that exploit temporal and spatial redundancy in the input video sequence. The encoded video data may therefore follow the syntax given by the video coding technology or standard being used.

[0099] The video may be in the form of a plurality of source frames (images) in time sequence. Intra-frame prediction (often abbreviated as intra-prediction) uses the spatial correlation in a given image, while inter-frame prediction uses (temporal or other) correlation between images. In the example, a particular image, when encoded/decoded, which is referred to as the current image, is divided into blocks. When a block in the current picture is similar to a reference block in a previously encoded and still buffered reference picture in a video, the block in the current picture may be encoded with a vector called a motion vector. The motion vector points to a reference block in the reference picture and may have a third dimension identifying the reference picture if multiple reference pictures are used.

[0100] In some embodiments, a dual prediction method may be used in inter-picture prediction. According to the dual prediction method, two reference pictures, such as the first reference picture and the second reference picture, both precede the current picture in the video in decoding order (but may be in the past and future, respectively, in the display order). A block in the current picture may be encoded with a first motion vector that points to a first reference block in a first reference picture and a second motion vector that points to a second reference block in a second reference picture. The block may be predicted by the combination of the first reference block and the second reference block.

[0101] In addition, the merge mode method can be used in inter-picture prediction to improve coding efficiency.

[0102] According to some embodiments of the invention, predictions, such as inter-picture predictions and intra-picture predictions, are performed in blocks. For example, according to the HEVC standard, an image in a video sequence is split into coding tree units (CTUs) for compression, CTUs in an image are the same size, such as 64x64 pixels, 32x32 pixels, or 16x16 pixels. In general, the CTU includes three coding tree units (CTBs), which are one luma CTB and two chrominance CTBs. Each CTU may be recursively divided in a quadtree into one or multiple coding units (CUs). For example, a CTU of 64x64 pixels can be divided into one CU of 64x64 pixels, or 4 CUs of 32x32 pixels, or 16 CUs of 16x16 pixels. In the example, each CU is parsed to determine a prediction type for the CU, such as an inter prediction type or an intra prediction type. The CU is divided into one or more prediction units (PUs) depending on temporal and/or spatial predictability. Typically, each PU includes a Luma PB and two Chroma PBs. In an embodiment, the encoding (encoding/decoding) prediction operation is performed in a prediction block. Using the luminance prediction block as an example of the prediction block, the prediction block includes a matrix of values (e.g., luminance values) for pixels such as 8x8 pixels, 16x16 pixels, 8x16 pixels, 16x8 pixels, etc. P.

[0103] The G-PCC model can separately compress geometric information and associated attributes such as color or reflectivity. The geometric information, which is the 3D coordinates of the point clouds, can be encoded by decomposing an octree of the occupancy information. On the other hand, attributes can be compressed based on the reconstructed geometry using prediction and lifting techniques. The splitting process of the octree is shown, for example, in FIG. 7-13.

[0104] FIG. 7 shows a block diagram of a G-PCC decoder (800) that is applied during a G-PCC decomposition process according to an embodiment. The decoder (800) may be configured to receive the compressed bitstream and decompress the point cloud data to decompress the bitstream to generate decoded point cloud data. In an embodiment, the decoder (800) may include an arithmetic decoding module (810), an inverse quantization module (820), an octree decoding module (830), a level of detail (LOD) generation module (840), a ) inverse quantization and a prediction module (860) based on inverse interpolation.

[0105] As shown, the compressed bit stream (801) may be received in the arithmetic decoding module (810). The arithmetic decoding module (810) is configured to decode the compressed bitstream (801) to obtain quantized prediction residuals (if generated) and point cloud busy codes (or symbols). The octree decoding module (830) is configured to generate quantized point positions in the point cloud in accordance with busy codes. The inverse quantization module (850) is configured to generate recovered point positions in the point cloud based on the quantized positions provided by the octree decoding module (830).

[0106] The LOD generation module (840) is configured to reorganize points into different LODs based on the recovered positions and ordering based on the LOD. The inverse quantization module (820) is configured to generate reconstructed prediction residuals based on the quantized prediction residuals received from the arithmetic decoding module (810). The inverse interpolation prediction module (860) is configured to perform an attribute prediction process to generate recovered point attributes in the point cloud based on the recovered prediction residuals received from the inverse quantization module (820) and an order based on the LOD obtained from the module (840). ) LOD generation.

[0107] In addition, the restored attributes generated by the inverse interpolation prediction module (860), together with the restored positions generated by the inverse quantization module (850), correspond to the decoded point cloud (802) (or reconstructed point cloud) that is output from decoder (800) in one example.

[0108] FIG. 8 shows a block diagram of a G-PPC encoder (700) according to an embodiment. The encoder (700) may be configured to receive point cloud data and compress the point cloud data to generate a bit stream carrying the compressed point cloud data. In an embodiment, the encoder (700) may include a position quantization module (710), a duplicate point removal module (712), an octree encoding module (730), an attribute transmission module (720), a level of detail (LOD) generation module (740) , an interpolation-based prediction module (750), a residual quantization module (760), and an arithmetic coding module (770).

[0109] As shown, the input point cloud (701) may be received at the encoder (700). The positions (eg, 3D coordinates) of the point cloud (701) are provided to the quantization module (710). The quantization module (710) is configured to quantize the coordinates to generate quantized positions. The duplicated point removal module (712) is configured to receive the quantized positions and perform a filtering process to identify and remove duplicated points. The octree encoding module (730) is configured to receive filtered positions from the duplicate point removal module (712) and perform an octree-based encoding process to generate a sequence of busy codes (or symbols) that describe a three-dimensional grid of voxels. The busy codes are passed to the arithmetic coding module (770).

[0110] The attribute transfer module (720) is configured to receive attributes of an input point cloud and perform an attribute transfer process to determine an attribute value for each voxel when a plurality of attribute values are associated with a corresponding voxel. The attribute transfer process may be performed on the reordered points output from the octree encoding module (730). Attributes after transmission operations are provided to the module (750) prediction based on interpolation. The LOD generation module (740) is configured to work with the reordered points output from the octree encoding module (730) and reorganize the points into different LODs. The LOD information is provided to the prediction module (750) based on the interpolation.

[0111] The interpolation-based prediction module (750) processes the points according to the LOD-based order indicated by the LOD information from the LOD generation module (740) and the transmitted attributes received from the attribute transmission module (720), and generates prediction residuals. The residual quantization module (760) is configured to receive prediction residuals from the interpolation-based prediction module (750) and perform quantization to generate quantized prediction residuals. The quantized prediction residuals are provided to an arithmetic encoding unit (770). Arithmetic encoding module (770) is configured to receive busy codes from octree encoding module (730), candidate indexes (if used), quantized prediction residuals from prediction module 750) based on interpolation and other information, and perform entropy encoding for further compression received values or information. As a result, a compressed bit stream (702) carrying compressed information can be generated. The bitstream (702) may be transmitted to or otherwise provided to a decoder that decodes the compressed bitstream, or may be stored in a storage device.

[0112] It should be noted that an interpolation-based prediction module (750) and an inverse-interpolation prediction module (860) configured to implement the attribute prediction methods disclosed herein may be included in other decoders or encoders, which may have similar or different structures compared to those shown in FIG. 7 and FIG. 8. In addition, the encoder (700) and decoder (800) in various examples may be included in the same device or separate devices.

[0113] In various embodiments, the encoder (300), decoder (400), encoder (700), and/or decoder (800) may be implemented in hardware, software, or a combination thereof. For example, the encoder (300), decoder (400), encoder (700), and/or decoder (800) may be implemented with a processing circuit, such as one or more integrated circuits (ICs), that operate with or without software. such as application specific integrated circuit (ASIC), field-programmable logic integrated circuit (FPGA), etc. In another example, the encoder (300), decoder (400), encoder (700), and/or decoder (800) may be implemented as software or firmware, including instructions stored on a non-volatile (or non-volatile) computer-readable storage medium. The instructions, when executed by a processing circuit, such as one or more processors, cause the processing circuit to perform the functions of an encoder (300), decoder (400), encoder (700), and/or decoder (800).

[0114] Splitting a point cloud that is defined by a 3D cube in a symmetrical manner along all axes (e.g., the x, y, and z axes) can result in eight sub-cubes, which is known as octree splitting (OT) in point cloud compression (PCC) . OT partitioning resembles binary tree (BT) partitioning in one-dimensional space and quadtree partitioning (QT) in two-dimensional space. The idea of partitioning OT can be illustrated by the example of Fig. 9, where the three-dimensional cube (900), shown in solid lines, can be broken into eight smaller cubes of the same size, shown in dashed lines. As shown in FIG. 9, the octree partitioning method allows the three-dimensional cube (900) to be divided into eight smaller cubes 0-7 of equal size.

[0115] In an octree partitioning method (eg, in TMC13), if an octree geometry codec is used, geometry encoding occurs as follows. First, the axis-aligned cubic bounding box B can be defined by two extreme points (0,0,0) and (2 ^d , 2 ^d , 2 ^d ), where 2 ^d defines the size of B's bounding box, and d can be encode to bitstream. Accordingly, all points within a given bounding box B can be compressed.

[0116] The octree structure can then be built by recursively splitting bounding box B. At each step, the cube can be split into 8 sub-cubes. The size of the sub-cube after iterative division k (k ≤d) times can be (2 ^dk , 2 ^dk , 2 ^dk ). An 8-bit code, such as a busy code, can then be generated by associating a 1-bit value with each sub-cube to indicate whether the corresponding sub-cube contains points (i.e., full and has a value of 1) or not (t .e. empty and has the value 0). Only complete sub-cubes larger than 1 (i.e. non-voxels) can be further split. The busy code for each cube can then be compressed using an arithmetic encoder.

[0117] The decoding process may begin by reading the dimensions of bounding box B from the bitstream. The same octree structure may then be built by splitting bounding box B according to the decoded busy codes. An example of a 2-level partition of a OT and the corresponding busy code is shown in FIG. 10, where the shaded cubes and nodes indicate that the cubes and nodes are occupied by dots.

[0118] FIG. 10 shows an example of an octree split (1010) and an octree structure (1020) corresponding to an octree split (1010) according to some embodiments of the invention. Fig. 10 shows two levels of splits in split (1010) of the octree. The octree structure (1020) includes a node (N0) corresponding to the octree partition (1010) cubic block. At the first level, the cube block is divided into 8 sub-cubic blocks, which are numbered from 0 to 7 according to the numbering method shown in FIG. 9. The occupancy code for splitting node N0 is "10000001" in binary, indicating that the first subcubic block represented by node N0-0 and the eighth subcubic block represented by node N0-7 include points in the point cloud, and the other subcubic blocks are empty.

[0119] Then, at the second partitioning level, the first subcubic block (represented by node N0-0) and the eighth subcubic block (represented by node N0-7), respectively, are further divided into eight octants. For example, the first subcubic block (represented by node N0-0) is split into 8 smaller subcubic blocks, which are numbered 0-7 in accordance with the numbering method shown in FIG. The busy code for splitting node N0-0 is "00011000" in binary, indicating that the fourth smaller subcubic block (represented by node N0-0-3) and the fifth smaller subcubic block (represented by node N0-0-4) include points in the point cloud, and the other smaller subcubic blocks are empty. At the second level, the seventh subcubic block (represented by node N0-7) is similarly divided into 8 smaller subcubic blocks, as shown in FIG. 10.

[0120] In the example of FIG. 10, nodes corresponding to a non-empty cubic space (eg, cubic block, subcubic blocks, smaller subcubic blocks, etc.) are shown in gray and are referred to as shaded nodes.

[0121] In the original structure of TMC13, for example, as described above, bounding box B may be a cube having the same size for all dimensions, and thus OT splitting may be performed for all subcubes at each node in which the subcubes are halved by all measurements. OT splitting can be performed recursively until the size of the subcubes reaches one. However, such partitioning may not be efficient in all cases, especially when the points are unevenly distributed in the 3D scene (or 3D space).

[0122] One extreme case may be a 2D plane in 3D space, in which all points may be located on the x-y plane in 3D space, and the z-axis deviation may be zero. In such a case, OT partitioning performed on cube B as the starting point may waste many bits in representing occupancy information in the z-direction, which is redundant and useless. In real applications this worst case may not be frequent. However, usually a point cloud has less deviation in one direction than in others. As shown in FIG. 11, the point cloud sequence referred to as "ford_01_vox1mm" in TMC13 may have principal components along the x and y axes. In fact, many point cloud data generated by a lidar system can have the same characteristics.

[0123] In quadtree and binary tree (QtBt) partitions, bounding box B may not be a cube, instead bounding box B may be a rectangular cuboid of arbitrary size to better fit the shape of the 3D scene or objects. When implemented, the size of B's bounding box can be represented as a power of two, for example,

[0124] Because bounding box B may not be a perfect cube, in some cases the node may (or may not) be split across the board. If the partition is performed in all three directions, then this is a typical OT partition. If the partition is performed in two directions out of three, then this partition is a partition of QT in 3D. If the split is only in one direction, then the split is a 3D BT split. Examples of QT and BT in 3D are shown in FIG. 12 and FIG. 13, respectively.

[0125] As shown in FIG. 12, the 3D cube 1201 may be partitioned along the x-y axes into 4 subcubes 0, 2, 4, and 6. The 3D cube 1202 may be partitioned along the x-z axes into 4 subcubes 0, 1, 4, and 5. The 3D cube 1203 can be split along the y-z axes into 4 subcubes 0, 1, 2 and 3. In FIG. 13, the 3D cube 1301 can be split along the x axis into 2 subcubes 0 and 4. 2 subcubes 0 and 2. The 3D cube 1303 can be split into 2 subcubes 0 and 1.

[0126] To define the conditions for implicit splits QT and BT in TMC13, two parameters (ie, K and M) can be applied. The first parameter K (0 ≤K ≤max(d _x , d _y , d _z ) - min(d _x , d _y , d _z )) can define the maximum number of implicit QT and BT splits that can be performed before OT splits. The second parameter M (0 ≤M ≤min(d _x , d _y , d _z )) can specify the minimum size of implicit splits QT and BT, indicating that implicit splits QT and BT are allowed only if all sizes are greater than M.

[0127] More specifically, the first K splits may follow the rules from Table I, and the splits following the first K splits may follow the rules from Table II. If none of the conditions listed in the tables are met, a OT split can be performed.

. Без потери общности, условия 0<d_x ≤d_y ≤d_z могут быть применены к ограничивающему боксу В. В зависимости от условий, на первых глубинах K (K ≤d_z-d_x), неявные разбиения ВТ могут выполняться по оси z, а неявные разбиения QT могут быть выполнены по осям y-z в соответствии с таблицей I. Размер подузлов тогда может стать

где значение δ_у и δ_z (δ_z ≥δ_у ≥0) может зависеть от значения K. Кроме того, разбиения ОТ могут выполняться d_x - М раз, так что оставшиеся подузлы могут иметь размер согласно таблице II, неявные разбиения ВТ могут выполняться по оси z δ_z - δ_у раз, а неявные разбиения QT могут затем выполняться по осям y-z δ_у раз. Таким образом, остальные узлы могут иметь размер 2^(M,M,M) Следовательно, разбиения ОТ могут быть выполнены М раз, чтобы охватить самые маленькие блоки.[0128] In an embodiment, bounding box B may be sized

. Without loss of generality, the conditions 0<d _x ≤d _y ≤d _z can be applied to the bounding box B. Depending on the conditions, at the first depths K (K ≤d _z -d _x ), implicit partitions of the BT can be performed along the z-axis , and implicit splits QT can be performed along the yz axes according to Table I. The size of the subnodes can then become

where the value of δ _y and δ _z (δ _z ≥δ _y ≥ 0) may depend on the value of K. In addition, OT splits may be performed d _x - M times, so that the remaining subnodes may have a size according to Table II, implicit BT splits may be performed along the z axis δ _z - δ _y times, and the implicit splits QT can then be performed along the yz δ _y times. Thus, the remaining nodes can be of size 2 ^(M,M,M). Therefore, OT partitions can be performed M times to cover the smallest blocks.

[0129] QtBt partitions use an implicit rule on how to apply partitioning of a given cuboid by switching between octree, quadtree, and binary tree at each node decomposition level. After the K levels of initial decomposition by partitioning QtBt according to a rule (eg Table I), another round of partitioning QtBt according to another rule (eg Table II) can be performed. If none of the rule conditions are met in the above processes, octree decomposition (or octree splitting) may be applied.

[0130] An implicit rule can affect the performance of QtBt in the following ways: (1) for point cloud data with a nearly symmetric cuboid bounding box in the x, y, and z axes, splitting QtBt does not show encoding advantages over a corresponding method (e.g., implicit splitting QtBt ), which performs Ot (octree) decomposition at all levels; and (2) for point cloud data with a highly asymmetric cuboid bounding box in the x, y, and z axes, QtBt partitioning shows the benefits of encoding by skipping sending unnecessary occupancy information during decomposition.

[0131] In the current partitions of QtBt, certain restrictions can be imposed as follows. First, QtBt partitions can always force the use of an asymmetric bounding box, which can be useless or even counterproductive when the point cloud has a nearly symmetrical bounding box. Second, the I table, together with the K parameter, can reduce larger dimensions according to the rule by forcing the use of Qt/Bt splits instead of Ot splits. However, the table I, together with the K parameter, may prevent splitting Qt or Bt at the beginning when the bounding box is symmetrical. Thirdly, Table II can be applied after the above K split times and takes effect when the minimum sub-block size reaches M. Thus, Table II can reduce larger dimensions according to the rule until all dimensions are equal. M. Fourth, the current implicit rule (or QtBt's implicit splits) may always dictate that the octree be decomposed after the first (up to) K levels, until the current QtBt splits reach the M level. In other words, the current QtBt splits may not allow arbitrary splits Qt / Bt / Ot were chosen between two level points.

[0132] The present invention provides for several methods. These techniques provide a simplification of the QtBt structure (eg, implicit splits of QtBt) in TMC 13 for a typical use case, eg based on the discussion above. These methods also allow for more flexible partitioning techniques, for example, by explicitly signaling the type of node decomposition at each level.

[0133] In an embodiment, a first partitioning method (or a simplified QtBt partitioning) may be proposed. The first way of splitting can be a special case of QtBt implicit splits, which can be applied to datasets with highly asymmetric bounding boxes by setting K=0 & M=0. The first way of splitting can simplify the structure of QtBt (e.g. QtBt splits) and still provide coding benefits for typical cases as above.

[0134] Compared to QtBt splits in TMC 13, the first split method may include the following features: (1) the implicit enable flag (eg, implicit_qtbt_enabled_flag) in QtBt splits in TMC 13 can be removed. (2) an asymmetric bounding box flag (eg, asymmetric_bbox_enabled_flag) may be introduced to enable the use of an asymmetric bounding box. In the example when the asymmetric bounding box flag is set to some value such as 0 (also referred to as the second value) for symmetrical or nearly symmetrical bounding box data, and to some value such as 1 (also referred to as the first value) for highly asymmetric bounding box data boxing. (3) If the asymmetric bounding box flag is the first value, the implicitQtBt (implicit QtBt) rule (eg Tables I and II) with K=0 & M=0 may be applied when the node decomposition level reaches 0 (or the last level). Otherwise, if the asymmetric bounding box flag is the second value, the first splitting method may perform octree decomposition (or octree splitting).

[0135] According to the first partitioning method, the implicitQtBt rule shown in Table II with M=0 can be applied to skip sending unnecessary busy information on some dimensions, for example, as shown in Table III.

[0136] In an embodiment, a second split method (or QtBt Explicit Split) can be proposed to send an explicit split decision signaling. Explicit signaling can be provided as an alternative to using a fixed implicit rule in the current QtBt partition.

[0137] The second partitioning method may include the following features: (1) a QtBt explicit enable flag (eg, explicit_qtbt_enabled_flag) may be introduced to enable/disable explicit split decision signaling, while the asymmetric bounding box flag from the first partitioning method may still be entered. (2) When the QtBt explicit enable flag is set to some value such as 0 (or a second value), the second partitioning method reverts to (or may be equal to) the first partitioning method described above. Thus, if the asymmetric bounding box flag (e.g., asymmetric_bbox_enabled_flag) is some value, such as 1 (or the first value), the implicitQtBt rule (e.g., tables I and II) with K=0 & M=0 may apply when the level node decomposition reaches 0 (or the last level). If the asymmetric bounding box flag is the second value, the second splitting method may perform octree decomposition (or octree splitting). In an embodiment, when the asymmetric bounding box flag is not used and the QtBt explicit enable flag is set to a second value (eg, 0), the second partitioning method may apply octree decomposition (or octree partitioning) for all levels. (4) When the QtBt explicit enable flag is set to the first value (e.g. 1), instead of always splitting the octree until the level reaches 0 (or the last level) as specified in the first splitting method, a 3-bit signal can be sent at each level of the octree to indicate whether to split along each of the x, y, and z axes. Thus, the 3-bit signal may indicate whether a Bt split, a Qt split, or an Ot split can be applied at each of the levels of the octree. In some embodiments, the implicitQtBt rule (eg, Tables I and II) in TMC 13 may be used to define a 3-bit signal at each of the octree levels.

[0138] It should be noted that since the Ot / Qt / Bt split is allowed arbitrarily in the process when the QtBt explicit enable flag is set to the first value in the second split method, the maximum possible total number of splits can be three times the difference between the maximum and minimum node depths.

[0139] In an embodiment, a third splitting method (or QtBt type 2 explicit splitting to send explicit split decision signaling can be provided. Explicit signaling can be provided as opposed to using a fixed implicit rule in the current QtBt splitting (e.g., in Tables I and II) A third splitting method may include the following features compared to the current QtBt splitting: (1) QtBt's explicit enable flag (eg, explicit_qtbt_enabled_flag) may replace the QtBt implicit enable flag (eg, implicit_qtbt_enabled_flag) in QtBt splits in TMC 13 to allow / disable explicit split decision signaling (2) An asymmetric bounding box flag (e.g. asymmetric_bbox_enabled_flag) can optionally be signaled only when QtBt's explicit enable flag has some value, such as 1 (or the first value), to enable/disable the use of an asymmetric bounding box. When the asymmetric bounding box flag is the first value, the asymmetric bounding box values (i.e. dimensions) along the x, y, and z axes may additionally be transmitted, as opposed to the maximum of the three. Accordingly, the asymmetric bounding box flag may be set to some value such as 0 (eg, a second value) for symmetrical or nearly symmetrical bounding box data, and to a first value (eg, 1) for highly asymmetric bounding box data. (3) When the QtBt Explicit Enable Flag is set to the first value, a 3-bit signal may be sent at each of the octree levels (or splitting levels of the octree) to indicate whether splitting should be performed on each of the x, y, and z axes. In an embodiment, the implicitQtBt rule (eg, Tables I and II) in TMC 13 may be used to define a 3-bit signal for each of the octree levels. In another embodiment, different partitioning rules may be applied to determine the 3-bit signal for each of the octree levels. Other partitioning rules may make it easier to encode the octree occupancy information and additionally take into account characteristics of the data (eg octree occupancy information) or a date derivation mechanism. (4) When QtBt's explicit permission flag is set to the second value (eg, 0), the third splitting method can apply octree decomposition (octree splitting) to all levels.

[0140] It should be noted that since the Ot / Qt / Bt split is allowed arbitrarily in the process when the QtBt explicit enable flag is set to the first value in the third split method, the maximum possible total number of splits can be three times the difference between the maximum and minimum node depths.

[0141] In an embodiment, a fourth partitioning method (or flexible QtBt partitioning) may be proposed to provide greater flexibility in the use of QtBt partitioning through additional signaling of the type of QtBt partitioning, explicit or implicit. Additional signaling may be provided as opposed to using a fixed implicit rule in the current partition of QtBt (eg, in Tables I and II).

[0142] The fourth split method may include the following: (1) a QtBt enable flag (eg, qtbt_enabled_flag) may be used to replace the QtBt implicit enable flag in the QtBt split in TMC 13 to indicate the use of QtBt split with more flexibility. (2) A QtBt type flag (eg, qtbt_type_flag) may optionally be transmitted when the QtBt enable flag is set to some value, such as 1. (3) If the QtBt type flag is set to some value, such as 0, the current implicit scheme may be applied. QtBt (eg tables I and II). In addition, an asymmetric bounding box flag (eg, asymmetric_bbox_enabled_flag) may optionally be transmitted to selectively enable/disable the use of an asymmetric bounding box. In an embodiment, when the asymmetric bounding box flag is set to some value, such as 1, the asymmetric bounding box values (i.e., dimensions) in the x, y, and z axes may be transmitted, as opposed to a maximum of three. In another embodiment, when the asymmetric bounding box flag is not transmitted, an asymmetric bounding box can always be used.

[0143] The fourth partitioning method may also include the following: (4) If the QtBt type flag is some value such as 1, a 3-bit signal may be sent to each of the octree levels to indicate whether splitting should be performed on each of the x, y, and z axes. In an embodiment, the implicitQtBt rule (eg, Tables I and II) in TMC 13 may be used to define a 3-bit signal for each of the octree levels. In another embodiment, different partitioning rules may be applied to determine the 3-bit signal for each of the octree levels. Other partitioning rules may make it easier to encode the octree occupancy information and additionally take into account characteristics of the data (eg octree occupancy information) or a date derivation mechanism. In an embodiment, an asymmetric bounding box flag may optionally be transmitted to selectively enable/disable the use of an asymmetric bounding box. When the asymmetric bounding box flag has some value, such as 1, the x, y, and z dimensions of the asymmetric bounding box may be transmitted, rather than a maximum of three. In another embodiment, the asymmetric bounding box flag may not be transmitted, and an asymmetric bounding box may always be used. levels.

[0144] It should be noted that since the Ot / Qt / Bt partition is allowed arbitrarily in the process when the QtBt explicit permission flag is set to some value such as 1, in the fourth partition method, the maximum possible total number of partitions can be three times the difference between the maximum and minimum node depths.

[0145] The above methods may be implemented in a video encoder or decoder adapted to compress/decompress a point cloud. The encoder/decoder may be implemented in hardware, software, or any combination thereof, and the software, if any, may be stored on one or more computer-readable media. For example, each of the methods (or embodiments), encoders, and decoders may be implemented by a processing circuit (eg, one or more processors or one or more integrated circuits). In one example, one or more processors execute a program that is stored on a computer-readable medium.

[0146] FIG. 14 and 15 show flowcharts describing process (1400) and process (1500) according to embodiments of the invention. Processes (1400) and (1500) may be used during point cloud decoding processes. In various embodiments, processes (1400) and (1500) may be performed by a processing circuit, such as a processing circuit in terminal devices (110), a processing circuit that performs the functions of an encoder (203) and/or a decoder (201), a processing circuit that acts as an encoder (300), decoder (400), encoder (700) and/or decoder (800), and the like. In some embodiments, processes (1400) and (1500) may be implemented in instructions, such that when the processing circuitry executes the instructions, the processing circuitry executes processes (1400) and (1500), respectively. [0147] As shown in FIG. 14, the process (1400) starts from (S1401) and proceeds to (S1410).

[0148] In (S1410), the first signaling information may be received from an encoded bitstream for a point cloud that includes a set of points in three-dimensional (3D) space. The first signaling information may indicate partitioning information of the point cloud.

[0149] In (S1420), the second signaling information may be determined based on the first signaling information indicating the first value. The second signaling information may indicate the mode of splitting the set of points in three-dimensional space.

[0150] In (S1430), the 3D dot set partition mode can be determined based on the second signal information. The process (1400) may then proceed to (S1440) where the point cloud may be reconstructed based on the split mode.

[0151] In some embodiments, the split mode may be determined as a predetermined quadtree and binary tree (QtBt) split based on the second signaling information being the second value.

[0152] In process (1400), third signal information may be received that indicates that the three-dimensional space is an asymmetric cuboid. The dimensions of the three-dimensional space that are transmitted in the x, y and z directions can be determined based on the third signal information being the first value.

[0153] In some embodiments, 3-bit signaling information may be determined for each of a plurality of split levels in a split mode based on the second signaling information being the first value. The 3-bit signaling information for each of the plurality of split levels may indicate split directions in the x, y, and z directions for the corresponding split level in the split mode.

[0154] In some embodiments, the implementation of the 3-bit signaling information may be determined based on the dimensions of the three-dimensional space.

[0155] In process (1400), the split mode may be determined based on the first signaling information being the second value, where the split mode may include a corresponding split of the octree in each of the plurality of split levels in the split mode.

[0156] As shown in FIG. 15, the process (1500) starts from (S1501) and proceeds to (S1510).

[0157] In (S1510), the first signaling information may be received from an encoded bitstream for a point cloud that includes a set of points in three-dimensional (3D) space. The first signaling information may indicate splitting information of the point cloud.

[0158] In (S1520), a partition mode of a set of points in 3D space may be determined based on the first signal information, where the partition mode may include a plurality of partition levels.

[0159] In (S1530), the point cloud can be reconstructed based on the split mode.

[0160] In some embodiments, the 3-bit signaling information for each of the multiple split levels in the split mode may be determined based on the first signaling information being the first value, where the 3-bit signaling information for each of the multiple split levels may indicate split directions. in the x, y, and z directions for the corresponding split level in split mode.

[0161] In some embodiments, the implementation of the 3-bit signaling information may be determined based on the dimensions of the three-dimensional space.

[0162] In some embodiments, a split mode may be defined to include a corresponding octree in each of the plurality of split levels in a split mode based on the first signaling information being the second value.

[0163] In process (1500), the second signaling information may be further received from the encoded bitstream for the point cloud. The second signaling information may indicate that the 3D space is an asymmetric cuboid when the second signaling information is the first value, and the 3D space is a symmetrical cuboid when the second signaling information is the second value.

[0164] In some embodiments, based on the first signaling information indicating the second value and the second signaling information indicating the first value, the split mode may be determined to include a corresponding split of the octree in each of the first split levels in the set of split levels of the split mode. The split type and the split direction of the last split level of the multiple split levels of the split mode can be determined according to the following table:

where d _x , d _y , and d _z are log2 dimensions of three-dimensional space along the x, y, and z axes, respectively.

[0165] In process (1500), the second signaling information may be determined based on the first signaling information indicating the first value. The second signaling information may indicate that the 3D space is an asymmetric cuboid when the second signaling information indicates a first value, and the 3D space is a symmetrical cuboid when the second signaling information indicates a second value. In addition, the dimensions of the three-dimensional space that are transmitted along the x, y, and z axes can be determined based on the second signal information indicating the first value.

[0166] As previously noted, the methods described above may be implemented in computer software using computer-readable instructions and physically stored on one or more computer-readable media. For example, FIG. 16 shows a computer system (1800) suitable for implementing certain embodiments of the disclosed subject matter.

[0167] Computer software may be coded using any suitable machine code or computer language, which may be the subject of assembly, compilation, linking, or similar mechanisms to produce code containing instructions that can be executed directly or through interpretation, execution of microcode, etc. .p., one or more central processing units (CPUs), graphics processing units (GPUs), and the like.

[0168] Instructions may be executed on various types of computers or components thereof, including, for example, personal computers, tablet computers, servers, smartphones, gaming devices, IoT devices, and the like.

[0169] The components shown in FIG. 16 for the computer system (1800) are exemplary in nature and are not intended to suggest any limitation as to the scope of use or functionality of the computer software implementing embodiments of the present invention. The configuration of the components is also not to be interpreted as having any dependency or requirement relating to any one or combination of the components illustrated in the exemplary embodiment of the computer system (1800).

[0170] The computer system (1800) may include certain human-machine input interfaces. Such a human-machine input interface may respond to input by one or more human users through, for example, tactile input (e.g., keystrokes, swipes, data glove movements), audio input (e.g., voice, handclaps), visual input ( for example, gestures), olfactory input (not shown). Human machine interfaces for input can also be used to capture certain media not necessarily directly related to conscious human input, such as audio (e.g. speech, music, ambient sound), images (e.g. scanned images, photographic images received from a camera for shooting still images), video (e.g. 2D video, 3D video including stereoscopic video).

[0171] Human-machine input interfaces may include one or more of the following (only one of them is shown): keyboard (1801), mouse (1802), trackpad (1803), touch screen (1810), data glove (not shown), joystick (1805), microphone (1806), scanner (1807), camera (1808).

[0172] The computer system (1800) may also include certain output human-machine interfaces. Such human-machine output interfaces may affect one or more human users through, for example, tactile output, sound, light, and smell/taste. Such human-machine output interfaces may include tactile output devices (e.g., tactile feedback from a touch screen (1810), a data glove (not shown) or a joystick (1805), but there may also be tactile feedback devices that are not serve as input devices), audio output devices (for example: speakers (1809), headphones (not shown)), image output devices (for example, screens (1810), including CRT screens, LCD screens, plasma screens, OLED- screens, each with or without touch screen input capability, each with or without haptic feedback capability - some of which can produce 2D visual output or more than 3D output by means such as stereographic output; virtual reality goggles (not shown), holographic displays and smoke tanks (not shown) and printers (not shown).

[0173] The computer system (1800) may also include human accessible storage devices and associated media such as optical media including CD/DVD ROM/RW (1820) with CD/DVD or similar media (1821), flash drive (1822), removable hard drive or solid state drive (1823), traditional magnetic media such as tape and floppy disk (not shown), specialized ROM/ASIC/PLD based devices such as security keys (not shown), and etc.

[0174] Those skilled in the art should also understand that the term "computer-readable medium" as used in connection with the currently disclosed subject matter does not encompass transmission media, carrier waves, or other transient signals.

[0175] The computer system (1800) may also include an interface to one or more communication networks. Networks can be, for example, wireless, wired, optical. In addition, networks can be local, wide area, metropolitan, automotive, industrial, real-time, latency tolerant, and so on. Examples of networks include local area networks such as Ethernet, wireless local area networks, cellular networks including GSM, 3G, 4G, 5G, LTE, etc., wired television or wireless digital wide area networks including cable television, satellite television and terrestrial broadcast television, automotive and industrial, including CANBus, etc. Some networks typically require external network interface adapters that are connected to certain general purpose data ports or peripheral buses (1849) (for example, computer system USB ports (1800)); others are typically integrated into the computer system core (1800) by being attached to a system bus as described below (eg, an Ethernet interface to a PC computer system or a cellular network interface to a smartphone computer system). Using any of these networks, the computer system (1800) can communicate with other entities. Such communication can be unidirectional, receive-only (for example, broadcast TV), unidirectional, send-only (for example, CANbus to certain CANbus devices), or bidirectional, for example, to other computer systems using a local or wide area digital network. Certain protocols and protocol stacks may be used on each of these networks and network interfaces, as described above.

[0176] The aforementioned human-machine interfaces, human-accessible storage devices, and network interfaces may be attached to the core (1840) of the computer system (1800).

[0177] The core (1840) may include one or more central processing units (CPU, CPU) (1841), graphics processors (GPU, GPU) (1842), specialized programmable processing units in the form of programmable logic integrated circuits (FPGA, FPGA ) (1843), hardware accelerators for certain tasks (1844), etc. These devices, along with Read Only Memory (ROM) (1845), Random Access Memory (1846), internal storage devices such as internal non-user hard drives, solid state drives, etc. (1847), can be connected via system bus (1848). In some computer systems, the system bus (1848) may be available as one or more physical connectors to allow expansion with additional processors, graphics processors, or the like. Peripherals can be connected either directly to the system bus (1848) of the kernel, or via a peripheral bus (1849). Peripheral bus architecture includes PCI, USB, etc.

[0178] The CPU (1841), GPU (1842), FPGA (1843), and accelerators (1844) may execute certain instructions, which in combination may constitute the aforementioned computer code. This computer code may be stored in ROM (1845) or RAM (1846). Transient data may also be stored in RAM (1846), while persistent data may be stored, for example, in internal storage (1847). Fast storage and retrieval to any of the storage devices can be accomplished through the use of cache memory, which can be tightly coupled to one or more CPU (1841), GPU (1842), mass storage device (1847), ROM (1845), RAM (1846), etc.

[0179] The computer-readable medium may contain computer code for performing various computer-implemented operations. The media and computer code may be specially designed and constructed for the purposes of the present invention, or they may be well known and available to those skilled in the art of computer software.

[0180] By way of example, and not limitation, a computer system having an architecture (1800), and in particular a core (1840), may provide functionality as a result of the processor(s) (including CPUs, GPUs) , FPGAs, accelerators, etc.) execute software embodied on one or more tangible machine-readable media. Such computer-readable media can be media associated with user-accessible mass storage as described above, as well as certain core stores (1840) that are non-volatile in nature, such as internal mass storage (1847) or ROM (1845). Software implementing various embodiments of the present invention may be stored on such devices and executed by the kernel (1840). The computer-readable medium may include one or more memory devices or microchips, as appropriate. The software may cause the core (1840), and in particular the processors within it (including CPUs, GPUs, FPGAs, and the like), to execute certain processes or certain portions of the specific processes described herein, including the definition of data structures stored in RAM (1846), and modifying such data structures according to processes defined by the software. In addition or alternatively, a computer system may provide functionality as a result of logic embedded in or otherwise embodied in hardware circuitry (e.g., an accelerator (1844)) that can operate in place of or in conjunction with software to perform certain processes or parts of particular processes described in this document. The link to the software may include logic and vice versa where appropriate. Reference to a computer-readable medium may encompass a circuit (eg, an integrated circuit (IC)) storing software to be executed, a circuit embodying logic to be executed, or both, where appropriate. The present invention encompasses any suitable combination of hardware and software.

[0181] Although several embodiments have been described, variations, permutations, and various substitute equivalents are possible within the scope of the invention. Thus, those skilled in the art will be able to develop numerous systems and methods that, although not explicitly shown or described herein, embody the principles of the invention and thus fall within its spirit and scope.

Claims (42)

1. A method for decoding the geometry of a point cloud in a point cloud decoder, including: receiving, by a processing circuit and from an encoded bitstream for a point cloud that includes a set of points in three-dimensional (3D) space, first signal information indicative of splitting information of the point cloud; determining, by the processing circuit and from the encoded bitstream for the point cloud, the second signaling information based on the first signaling information indicating the first value, the second signaling information indicating a splitting mode of the set of points in the three-dimensional space; determining, by means of the processing circuit, a mode of splitting the set of points in three-dimensional space based on the second signal information; And recovery, using a processing scheme, a point cloud based on the splitting mode. 2. The method of claim 1, wherein determining the split mode further includes: determining a split mode as a predetermined quadtree-binary tree (QtBt) split based on the second signal information indicating the second value. 3. The method of claim 1, further comprising: receiving third signal information that indicates that the three-dimensional space is an asymmetric cuboid; And determining the signaled dimensions of the three-dimensional space along the x, y, and z axes based on the third signal information indicating the first value. 4. The method of claim 1, wherein determining the split mode further includes: receiving 3-bit signaling information for each of the plurality of subdivision levels in a subdivision mode based on a second signaling information indicating a first value, wherein the 3-bit signaling information for each of the plurality of subdivision levels indicates the subdivision directions along the x, y, and z axes for the respective split level in split mode. 5. The method of claim 4, wherein the 3-bit signaling information is determined based on the dimensions of said three-dimensional space. 6. The method of claim 1, further comprising: determining a split mode based on the first signaling information indicating the second value, the split mode including a corresponding split of the octree in each of the plurality of split levels in the split mode. 7. A method for decoding the geometry of a point cloud in a point cloud decoder, including: receiving, by a processing circuit and from an encoded bitstream for a point cloud that includes a set of points in three-dimensional (3D) space, first signal information indicative of splitting information of the point cloud; determining, by means of the processing circuit, a partitioning mode of a set of points in 3D space based on the first signal information, the partitioning mode including a plurality of partitioning levels; And recovery, using a processing scheme, a point cloud based on the splitting mode. 8. The method of claim 7, wherein determining the split mode further includes: receiving 3-bit signaling information for each of the plurality of subdivision levels in a subdivision mode based on the first signaling information indicating the first value, wherein the 3-bit signaling information for each of the plurality of subdivision levels indicates the subdivision directions along the x, y, and z axes for the respective split level in split mode. 9. The method of claim 8, wherein the 3-bit signaling information is determined based on the dimensions of the three-dimensional space. 10. The method of claim 7, wherein determining the split mode further includes: determining a split mode that includes a corresponding split of the octree in each of the plurality of split levels in the split mode based on the first signaling information indicating the second value. 11. The method of claim 7, further comprising: receiving second signaling information from the encoded bitstream for the point cloud, wherein the second signaling information indicates that the 3D space is an asymmetric cuboid when the second signaling information is a first value, and the second signaling information indicates that the 3D space is a symmetric cuboid when the second signaling information is is the second value. 12. The method of claim 11, wherein determining the split mode further includes: based on the first signaling information indicating the second value and the second signaling information indicating the first value, determining a partition mode to include a corresponding partition of the octree in each of the first partition levels in the plurality of partition levels of the partition mode; And determining a partition type and a partition direction at the last partition level in the plurality of partition levels of the partition mode; in this case, the type of partition and the direction of partition at the last level of partition are: splitting Qt along the xy axes in the case d _z = 0 < d _x = d _y , splitting Qt along xz axes in case d _y = 0 < d _x = d _z , splitting Qt along the yz axes in the case d _x = 0 < d _y = d _z , splitting Bt along the x axis in case d _y =0 ≤ d _z < d _x or d _z = 0 ≤ d _y < d _x , splitting Bt along the y axis in case d _x =0 ≤ d _z < d _y or d _z = 0 ≤ d _x < d _y and splitting Bt along the z axis in case d _x =0 ≤ d _y < d _z or d _y = 0 ≤ d _x < d _z , where d _x , d _y , and d _z are log2 dimensions of three-dimensional space along the x, y, and z axes, respectively. 13. The method of claim 7, further comprising: determining the second signal information based on the first signal information indicating the first value, the second signal information indicating that the 3D space is an asymmetric cuboid when the second signal information indicates the first value, and the second signal information indicating that the 3D space is a symmetric cuboid when the second the signaling information indicates the second value; And determining the signaled dimensions of the three-dimensional space along the x, y, and z axes based on the second signal information indicating the first value. 14. A device for processing point cloud data, comprising: processing scheme, configured to implement the method according to any one of paragraphs. 1-13.

Images