Integration of duplicated vertices and vertex packets in mesh motion vector coding

Abstract

A method and apparatus, the apparatus comprising computer code configured to cause one or more processors to: obtain a grid of encoded volume data representing at least one three-dimensional (3D) visual content from a coded bitstream; determining a spatial packet syntax that signals a coding order of vertices obtained using the encoded volume data, where at least two of the vertices are within a threshold distance from each other and are not edge-connected to each other; the encoded volume data is decoded by predicting at least two of the vertices as a group based on a spatial packet syntax.

Description

Cross - Reference to Related Applications

[0001] This application claims the benefit of priority of U.S. Provisional Application No. 63 / 437,971, filed on January 9, 2023, and U.S. Application No. 18 / 405,330, filed on January 5, 2024, the entire contents of which are hereby incorporated by reference into this application. Background Art 1. Technical Field

[0002] This disclosure relates to a collection of advanced video coding techniques including vertex grouping in mesh motion vector coding. 2. Description of the Related Art

[0003] Advances in 3D capture, modeling, and rendering have contributed to the prevalence of 3D content on several platforms and devices. Today, a baby's first steps can be captured on one continent and made available for grandparents on another continent to view (and perhaps also interact) and enjoy a fully immersive experience with the child. However, to achieve such realism, the models are becoming increasingly complex, and a large amount of data is associated with the creation and consumption of these models. 3D meshes are widely used to represent such immersive content.

[0004] Dynamic mesh sequences may require a large amount of data because they may include a large amount of information that changes over time. Therefore, efficient compression techniques are needed to store and transmit such content. The mesh compression standards IC, MESHGRID, FAMC were previously developed by MPEG to handle dynamic meshes with constant connectivity and time - varying geometry and vertex attributes. However, these standards do not consider time - varying attribute maps and connectivity information. DCC (Digital Content Creation) tools typically generate such dynamic meshes. Correspondingly, for volumetric acquisition techniques, generating dynamic meshes with constant connectivity, especially under real - time constraints, is challenging. Existing standards do not support this type of content. MPEG plans to develop a new mesh compression standard to directly handle dynamic meshes with time - varying connectivity information and optionally time - varying attribute maps. This standard targets lossy and lossless compression for various applications such as real - time communication, storage, free - viewpoint video, AR, and VR. Features such as random access and scalable / progressive coding are also considered. Therefore, for any of these reasons, a technical solution to these problems arising in video coding techniques is needed. Summary of the Invention

[0005] Including a method and an apparatus, the apparatus includes: a memory configured to store computer program code; and one or more processors configured to access the computer program code and operate in accordance with what is indicated by the computer program code. The computer program is configured to cause the processor to implement the following code: an obtaining code configured to cause at least one processor to implement obtaining code, the obtaining code being configured to cause at least one processor to obtain, from a decoded bitstream, a mesh of encoded volume data representing at least one three-dimensional (3D) visual content; a determining code configured to cause at least one processor to determine a spatial grouping syntax that signals a decoding order of vertices obtained using the encoded volume data, wherein at least two of the vertices are within a threshold distance of each other and are not edge-connected to each other; and a decoding code configured to cause at least one processor to decode the encoded volume data by predicting at least two of the vertices as a group based on the spatial grouping syntax.

[0006] A third vertex in the group may be within a threshold distance of any of at least two of the vertices.

[0007] The third vertex may be edge-connected to one of at least two of the vertices.

[0008] The third vertex may not be edge-connected to any of at least two of the vertices.

[0009] Decoding the encoded volume data may include: predicting multiple groups of vertices other than the group, and at least one vertex of each of the multiple groups is not edge-connected to other vertices of the vertices of each of the multiple groups.

[0010] Each vertex of the vertices of each of the multiple groups may be within a threshold distance of each other of each of the multiple groups.

[0011] The spatial grouping syntax may be a base mesh inter-frame sub-mesh data unit syntax.

[0012] The group may include an integer K vertices, and the base mesh inter-frame sub-mesh data unit syntax may be obtained using the encoded volume data and signals the integer K.

[0013] The integer K may be 16.

[0014] The value of the spatial grouping syntax may be based on whether a first decoding cost for decoding motion vectors of all vertices of the group is determined to be less than or equal to a second decoding cost for decoding estimated residuals of all vertices of the group. Description of the Drawings

[0015] Other features, properties, and various advantages of the disclosed subject matter will become more apparent from the following detailed description and the accompanying drawings, in which:

[0016] Figure 1 is a schematic illustration of a figure according to an embodiment;

[0017] Figure 2 is a simplified block diagram according to an embodiment;

[0018] Figure 3 is a simplified illustration according to an embodiment;

[0019] Figure 4 is a simplified illustration according to an embodiment;

[0020] Figure 5 is a simplified illustration according to an embodiment;

[0021] Figure 6 is a simplified illustration according to an embodiment;

[0022] Figure 7 is a simplified illustration according to an embodiment;

[0023] Figure 8 is a simplified illustration according to an embodiment;

[0024] Figure 9 is a simplified illustration according to an embodiment;

[0025] Figure 10 is a simplified flowchart according to an embodiment;

[0026] Figure 11 is a simplified flowchart according to an embodiment;

[0027] Figure 12 is a simplified flowchart according to an embodiment;

[0028] Figure 13 is a simplified illustration according to an embodiment;

[0029] Figure 14 is a simplified illustration according to an embodiment;

[0030] Figure 15 is a simplified illustration according to an embodiment;

[0031] Figure 16 is a simplified illustration according to an embodiment;

[0032] Figure 17 is a simplified illustration according to an embodiment;

[0033] Figure 18 is a simplified illustration according to an embodiment;

[0034] Figure 19 is a simplified illustration according to an embodiment; and

[0035] Figure 20 is a simplified illustration according to an embodiment. Detailed Embodiments

[0036] The proposed features discussed below can be used alone or in any combination. In addition, embodiments can be implemented by processing circuitry (e.g., one or more processors or one or more integrated circuits). In one example, one or more processors execute a program stored in a non-transitory computer-readable medium.

[0037] Figure 1 FIG. shows a simplified block diagram of a communication system 100 according to an embodiment of the present disclosure. The communication system 100 can include at least two terminals 102 and 103 interconnected via a network 105. For unidirectional data transmission, the first terminal 103 can decode video data at a local location for transmission via the network 105 to another terminal 102. The second terminal 102 can receive the decoded video data of another terminal from the network 105, decode the decoded data, and display the restored video data. Unidirectional data transmission may be common in media service applications and the like.

[0038] Figure 1 FIG. shows a second pair of terminals 101 and 104 configured to support bidirectional transmission of decoded video that may occur, for example, during a video conference. For bidirectional data transmission, each terminal 101 and 104 can decode video data captured at a local location for transmission via the network 105 to another terminal. Each terminal 101 and 104 can also receive the decoded video data sent by another terminal, can decode the decoded data, and can display the restored video data at a local display device.

[0039] In Figure 1Among them, the terminals 101, 102, 103, and 104 may be shown as servers, personal computers, and smart phones, but the principles of the present disclosure are not limited thereto. Embodiments of the present disclosure are applicable to laptop computers, tablet computers, media players, and / or dedicated video conferencing devices. The network 105 represents any number of networks for transmitting decoded video data among the terminals 101, 102, 103, and 104, including, for example, wired and / or wireless communication networks. The communication network 105 may exchange data in circuit-switched channels 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, unless otherwise stated below, the architecture and topology of the network 105 may be immaterial to the operation of the present disclosure.

[0040] Figure 2 The placement of video encoders and video decoders in a streaming environment is shown as an example of an application of the disclosed subject matter. The disclosed subject matter may be equally applicable to other video-enabled applications, including, for example, video conferencing, digital TV, storing compressed video on digital media including CD (Compact Disc), DVD (Digital Versatile Disc), memory sticks, etc.

[0041] A streaming system may include a capture subsystem 203, which may include a video source 201, such as a digital camera device, that creates a stream of, for example, uncompressed video samples 213. The sample stream 213 may be emphasized as a high volume of data when compared to an encoded video bitstream and may be processed by an encoder 202 coupled to the video source 201, which may be, for example, a camera device as discussed above. The encoder 202 may include hardware, software, or a combination thereof to implement or carry out aspects of the disclosed subject matter described in more detail below. The encoded video bitstream 204 may be emphasized as a lower volume of data when compared to the sample stream, and the encoded video bitstream 204 may be stored on a streaming server 205 for future use. One or more streaming clients 212 and 207 may access the streaming server 205 to retrieve copies 208 and 206 of the encoded video bitstream 204. The client 212 may include a video decoder 211 that decodes an incoming copy of the encoded video bitstream 208 and creates an outgoing video sample stream 210 that can be rendered on a display 209 or other rendering device (not shown). In some streaming systems, the video bitstreams 204, 206, and 208 may be encoded according to certain video decoding / compression standards. Examples of these standards are mentioned above and further described herein.

[0042] Figure 3 It may be a functional block diagram of a video decoder 300 according to an embodiment of the present invention.

[0043] The receiver 302 may receive one or more coded video sequences to be decoded by the decoder 300; in the same or another embodiment, one decoded video sequence is received at a time, wherein the decoding of each decoded video sequence is independent of other decoded video sequences. The decoded video sequence may be received from a channel 301, which may be a hardware / software link to a storage device storing the encoded video data. The receiver 302 may receive the encoded video data as well as other data, such as decoded audio data and / or auxiliary data streams, which may be forwarded to their respective using entities (not depicted). The receiver 302 may separate the decoded video sequence from other data. To prevent network jitter, a buffer memory 303 may be coupled between the receiver 302 and the entropy decoder / parser 304 (hereinafter referred to as "parser"). When the receiver 302 is receiving data from a storage / forward device with sufficient bandwidth and controllability or from an isochronous network, the buffer 303 may not be required or the buffer 303 may be small. For use on a best-effort packet network such as the Internet, the buffer 303 may be required, and the buffer 303 may be relatively large and may advantageously have an adaptive size.

[0044] Video decoder 300 may include a parser 304 to reconstruct symbols 313 from an entropy-coded video sequence. The categories of these symbols include: information for managing the operation of decoder 300; and information potentially for controlling a rendering device such as display 312, which is not part of the decoder but may be coupled to the decoder. The control information for the rendering device may be in the form of Supplementary Enhancement Information (SEI) messages or Video Usability Information (VUI) parameter set segments (not depicted). The parser 304 may parse / entropy-decode the received entropy-coded video sequence. The decoding of the entropy-coded video sequence may be performed according to video coding techniques or standards and may follow principles well-known to those skilled in the art, including: variable length decoding, Huffman coding, arithmetic decoding with or without context sensitivity, etc. The parser 304 may extract subgroup parameter sets from the entropy-coded video sequence for at least one subgroup among at least one subgroup of pixels in the video decoder based on at least one parameter corresponding to the subgroup. The subgroup may include Group of Picture (GOP), picture, tile, slice, macroblock, Coding Unit (CU), block, Transform Unit (TU), Prediction Unit (PU), etc. The entropy decoder / parser may also extract information such as transform coefficients, quantizer parameter values, motion vectors, etc. from the entropy-coded video sequence.

[0045] The parser 304 may perform entropy decoding / parsing operations on the video sequence received from buffer 303 to create symbols 313. The parser 304 may receive the encoded data and selectively decode specific symbols 313. Additionally, the parser 304 may determine whether to provide a specific symbol 313 to the motion compensation prediction unit 306, the scaler / inverse transform unit 305, the intra prediction unit 307, or the loop filter 311.

[0046] Depending on the type of the decoded video picture or its part (e.g., inter picture and intra picture, inter block and intra block) and other factors, the reconstruction of symbols 313 may involve multiple different units. Which units are involved and the way they are involved may be controlled by subgroup control information parsed by the parser 304 from the entropy-coded video sequence. For simplicity, this subgroup control information flow between the parser 304 and the multiple units below is not depicted.

[0047] In addition to the functional blocks already mentioned, decoder 300 can conceptually be subdivided into a number of functional units as described below. In a practical implementation operating under commercial constraints, many of these units interact closely with each other and can be at least partially integrated with each other. However, for the purpose of describing the disclosed subject matter, it is appropriate to conceptually subdivide into the following functional units.

[0048] The first unit is the scaler / inverse transform unit 305. The scaler / inverse transform unit 305 receives, from parser 304, quantized transform coefficients as symbols 313 and control information, including which transform to use, block size, quantization factor, quantization scaling matrix, etc. The scaler / inverse transform unit 305 can output a block including sample values, which can be input into aggregator 310.

[0049] In some cases, the output samples of the scaler / inverse transform 305 can belong to an intra-coded block; that is: a block that does not use predictive information from a previously reconstructed picture, but can use predictive information from a previously reconstructed part of the current picture. Such predictive information can be provided by the intra picture prediction unit 307. In some cases, the intra picture prediction unit 307 uses the surrounding already reconstructed information extracted from the current (partially reconstructed) picture 309 to generate a block of the same size and shape as the block being reconstructed. In some cases, aggregator 310 adds the predictive information already generated by the intra prediction unit 307 to the output sample information provided by the scaler / inverse transform unit 305 on a per-sample basis.

[0050] In other cases, the output samples of the scaler / inverse transform unit 305 can belong to an inter-coded and possibly motion-compensated block. In this case, the motion compensation prediction unit 306 can access the reference picture memory 308 to extract samples for prediction. After motion compensating the extracted samples according to the symbols 313 belonging to the block, these samples can be added by aggregator 310 to the output of the scaler / inverse transform unit (referred to as residual samples or residual signal in this case) to generate output sample information. The address in the reference picture memory from which the motion compensation unit extracts the prediction samples can be controlled by a motion vector, which is available to the motion compensation unit in the form of symbols 313, which can have, for example, an X component, a Y component, and a reference picture component. Motion compensation can also include interpolation of sample values extracted from the reference picture memory when using sub-sample accurate motion vectors, a motion vector prediction mechanism, etc.

[0051] The output samples of aggregator 310 can undergo various loop filtering techniques in loop filter unit 311. Video compression techniques can include in-loop filter techniques that are controlled by parameters included in the decoded video bitstream and available to loop filter unit 311 as symbols 313 from parser 304, but video compression techniques can also respond to meta information obtained during the decoding of previous (in decoding order) portions of the decoded picture or decoded video sequence, and to previously reconstructed and loop-filtered sample values.

[0052] The output of loop filter unit 311 can be a sample stream that can be output to rendering device 312 and stored in reference picture memory 557 for future inter-picture prediction.

[0053] Once fully reconstructed, some decoded pictures can be used as reference pictures for future prediction. Once a decoded picture has been fully reconstructed and the decoded picture has been identified as a reference picture (e.g., by parser 304), then the current reference picture 309 can become part of reference picture buffer 308, and a new current picture memory can be reallocated before starting to reconstruct subsequent decoded pictures.

[0054] Video decoder 300 can perform decoding operations according to predetermined video compression techniques that can be recorded in standards such as ITU-T Recommendation H.265. In the sense that the decoded video sequence follows the syntax of the video compression technique or standard, the decoded video sequence can conform to the syntax specified by the video compression technique or standard being used, as specified in the video compression technique document or standard and explicitly in the profile document therein. For compliance, it is also required that the complexity of the decoded video sequence be within the range defined by the level of the video compression technique or standard. In some cases, the level limits the maximum picture size, maximum frame rate, maximum reconstructed sample rate (measured in, for example, megasamples per second), maximum reference picture size, etc. In some cases, the limits set by the level can be further restricted by the Hypothetical Reference Decoder (HRD) specification and the metadata of HRD buffer management signaled in the decoded video sequence.

[0055] In an embodiment, the receiver 302 may receive additional (redundant) data along with the encoded video. The additional data may be included as part of the (one or more) decoded video sequences. The additional data may be used by the video decoder 300 to properly decode the data and / or more accurately reconstruct the original video data. The additional data may be in the form of, for example, temporal, spatial, or signal-to-noise ratio (SNR) enhancement layers, redundant slices, redundant pictures, forward error correction codes, and the like.

[0056] Figure 4 may be a functional block diagram of a video encoder 400 according to an embodiment of the present disclosure.

[0057] The encoder 400 may receive video samples from a video source 401 (which is not part of the encoder), and the video source 401 may capture video images to be decoded by the encoder 400.

[0058] The video source 401 may provide a source video sequence in the form of a digital video sample stream to be decoded by the encoder (303), and the digital video sample stream may have any suitable bit depth (e.g., 8 bits, 10 bits, 12 bits,...), any color space (e.g., BT.601 YCrCb, RGB,...), and any suitable sampling structure (e.g., Y CrCb 4:2:0, Y CrCb 4:4:4). In a media service system, the video source 401 may be a storage device storing previously prepared videos. In a video conferencing system, the video source 401 may be a camera device that captures local image information as a video sequence. The video data may be provided as a plurality of individual pictures that are given motion when viewed in sequence. The pictures themselves may be organized as a spatial pixel array, where each pixel may include one or more samples depending on the sampling structure, color space, etc. used. Those skilled in the art can easily understand the relationship between pixels and samples. The following description focuses on samples.

[0059] According to an embodiment, the encoder 400 can decode and compress the pictures of the source video sequence into a decoded video sequence 410 in real time or according to any other time constraints required by the application. Implementing an appropriate decoding speed is a function of the controller 402. The controller controls other functional units described below and is functionally coupled to these units. For clarity, the coupling is not depicted. The parameters set by the controller may include: rate control related parameters (picture skipping, quantizer, lambda value of rate distortion optimization technology, ...), picture size, picture group (Group Of Picture, GOP) layout, maximum motion vector search range, etc. Those skilled in the art can easily identify other functions of the controller 402, because these functions may belong to the video encoder 400 optimized for a specific system design.

[0060] Some video encoders operate in a manner that is readily recognizable to those skilled in the art as a "decoding loop". As an overly simplified description, the decoding loop may include: an encoding portion of an encoder 400 (hereinafter "source decoder") (responsible for creating symbols based on the input picture to be encoded and the reference picture); and a (local) decoder 406 embedded in the encoder 400, which reconstructs the symbols to create sample data that the (remote) decoder will also create (because in the video compression techniques considered in the disclosed subject matter, any compression between the symbols and the decoded video bitstream is lossless). This reconstructed sample stream is input to a reference picture memory 405. Since decoding the symbol stream results in a bit-accurate result that is independent of the decoder location (local or remote), the reference picture buffer contents are also bit-accurate between the local encoder and the remote encoder. In other words, the reference picture samples "seen" by the prediction portion of the encoder are exactly the same sample values ​​that the decoder will "see" when using prediction during decoding. The basic principle of this reference picture synchronization (and the resulting drift if synchronization cannot be maintained, for example due to channel errors) is well known to those skilled in the art.

[0061] The operation of the "local" decoder 406 can be combined with the above Figure 3 The operation of the "remote" decoder 300 described in detail is the same. However, reference is also briefly made to Figure 4 , when symbols are available and the entropy decoder 408 and the parser 304 can losslessly encode / decode the symbols into a decoded video sequence, the entropy decoding part of the decoder 300 including the channel 301, the receiver 302, the buffer 303 and the parser 304 may not be fully implemented in the local decoder 406.

[0062] What can be observed at this time is that any decoder technology other than parsing / entropy decoding existing in the decoder must also exist in the corresponding encoder in substantially the same functional form. Since the encoder technology is inverse to the decoder technology that has been fully described, the description of the encoder technology can be simplified. Only more detailed descriptions will be needed and provided in some places below.

[0063] As part of its operation, the source decoder 403 can perform motion-compensated predictive decoding, which predicts and decodes an input frame by referring to one or more previously decoded frames designated as "reference frames" in the video sequence. In this way, the decoding engine 407 decodes the difference between a pixel block of the input frame and a pixel block of the reference frame, and the reference frame can be selected as the prediction reference for the input frame.

[0064] The local video decoder 406 can decode the decoded video data of the frame that can be designated as a reference frame based on the symbols created by the source decoder 403. The operation of the decoding engine 407 can advantageously be a lossy process. When the decoded video data can be decoded at a video decoder ( Figure 4 not shown), the reconstructed video sequence can generally be a copy of the source video sequence with some errors. The local video decoder 406 replicates the decoding process that the video decoder performs on the reference frame and can store the reconstructed reference frame in a reference picture memory 405 that can be, for example, a cache memory. In this way, the encoder 400 can locally store a copy of the reconstructed reference frame, which has the same content (without transmission errors) as the reconstructed reference frame to be obtained by the remote video decoder.

[0065] The predictor 404 can perform a prediction search for the decoding engine 407. That is, for a new frame to be decoded, the predictor 404 can search the reference picture memory 405 for sample data (as candidate reference pixel blocks) or some metadata such as reference picture motion vectors, block shapes, etc. that can be used as an appropriate prediction reference for the new picture. The predictor 404 can operate on a per-pixel basis for sample blocks to find an appropriate prediction reference. In some cases, as determined by the search results obtained by the predictor 404, the input picture can have prediction references extracted from multiple reference pictures stored in the reference picture memory 405.

[0066] The controller 402 can manage the decoding operation of the source decoder 403, which can be, for example, a video decoder, including, for example, setting parameters and subgroup parameters for encoding video data.

[0067] The outputs of all the above-mentioned functional units can be entropy-coded in an entropy coder 408. The entropy coder converts these symbols into a coded video sequence by losslessly compressing the symbols generated by the various functional units according to techniques known to those skilled in the art, such as Huffman coding, variable length coding, arithmetic coding, etc.

[0068] The transmitter 409 can buffer the coded video sequence(s) created by the entropy coder 408 in preparation for transmission via a communication channel 411, which can be a hardware / software link to a storage device that will store the encoded video data. The transmitter 409 can merge the coded video data from the source coder 403 with other data to be transmitted, such as coded audio data and / or auxiliary data streams (source not shown).

[0069] The controller 402 can manage the operation of the encoder 400. During coding, the controller 402 can assign a certain coded picture type to each coded picture, which may affect the coding techniques that can be applied to the corresponding picture. For example, pictures can generally be assigned to one of the following frame types:

[0070] Intra pictures (I pictures), which can be pictures that can be coded and decoded without using any other frames in the sequence as a prediction source. Some video codecs allow different types of intra pictures, including, for example, independent decoder refresh pictures. Those skilled in the art are aware of these variations of I pictures and their corresponding applications and characteristics.

[0071] Predictive pictures (P pictures), which can be pictures that can be coded and decoded using intra prediction or inter prediction that can predict the sample values of each block using at most one motion vector and a reference index.

[0072] Bi-directional predictive pictures (B pictures), which can be pictures that can be coded and decoded using intra prediction or inter prediction that can predict the sample values of each block using at most two motion vectors and a reference index. Similarly, multiple predictive pictures can use more than two reference pictures and associated metadata for reconstructing a single block.

[0073] Source pictures can typically be spatially subdivided into multiple sample blocks (e.g., blocks of 4×4, 8×8, 4×8, or 16×16 samples respectively), and decoded on a block-by-block basis. These blocks can be predictively decoded with reference to other (already decoded) blocks, which are determined by the decoding assignments applied to the corresponding pictures of the blocks. For example, blocks of an I picture can be non-predictively decoded, or can be predictively decoded (spatial prediction or intra prediction) with reference to already decoded blocks of the same picture. Pixel blocks of a P picture can be non-predictively decoded with reference to a previous already decoded reference picture via spatial prediction or via temporal prediction. Blocks of a B picture can be non-predictively decoded with reference to one or two previous already decoded reference pictures via spatial prediction or via temporal prediction.

[0074] An encoder 400, which can be, for example, a video decoder, can perform decoding operations according to a predetermined video decoding technique or standard such as ITU-T Recommendation H.265. In the operation of the encoder 400, the encoder 400 can perform various compression operations, including predictive decoding operations that exploit the temporal redundancy and spatial redundancy in the input video sequence. Thus, the decoded video data can conform to the syntax specified by the video decoding technique or standard used.

[0075] In an embodiment, the transmitter 409 can transmit additional data together with the encoded video. The source decoder 403 can include such data as part of the decoded video sequence. The additional data can include temporal / spatial / SNR enhancement layers, other forms of redundant data such as redundant pictures and slices, Supplementary Enhancement Information (SEI) messages, Visual Usability Information (VUI) parameter set fragments, and the like.

[0076] Figure 5 A simplified block-type flowchart 500 of exemplary viewport-related processing in the Omnidirectional Media Application Format (OMAF) is shown, which can enable 360-degree Virtual Reality (VR360) streaming as described in OMAF.

[0077] At an acquisition block 501, video data A is acquired, such as data of multiple images and audio at the same time instance in a case where the image data can represent a scene in VR360. At a processing block 503, an image B at the same time instance is processed by one or more of the following i: Stitching; mapping onto a projected picture with respect to one or more virtual reality (VR) angles or other angles / viewpoints; and packing region by region. Additionally, metadata can be created to indicate any information in such processed information and other information to assist in delivery and rendering processing.

[0078] With respect to data D, at the image encoding block 505, the projected picture is encoded as data E i and combined into a media file in viewport-independent streaming, and at the video encoding block 504, the video picture is encoded as data E such as a single-layer bitstream v , and with respect to data B a , the audio data can also be encoded as data E at the audio encoding block 502 a .

[0079] Data E a , E v and E i , the entire decoded bitstream F i and / or F can be stored at a (Content Delivery Network (CDN) / cloud) server and can generally be fully transmitted to the OMAF player 520, for example, at the delivery block 507 or otherwise, and can be fully decoded by a decoder such that at the display block 516, at least one region corresponding to the current viewport of the decoded picture is presented to the user with respect to various metadata, file playback, and orientation / viewport metadata from the head / eye tracking block 508, where the orientation / viewport metadata is, for example, the angle at which the user can view through the device relative to the viewport specifications of the VR image device. A significant feature of VR360 is that only the viewport can be displayed at any particular moment, and such a feature can be used to improve the performance of the omnidirectional video system by selective delivery according to the user's viewport (or any other criteria, such as recommended viewport timing metadata). For example, according to an exemplary embodiment, viewport-related delivery can be achieved through tile-based video coding.

[0080] Similar to the above encoding blocks, the OMAF player 520 according to an exemplary embodiment can similarly reverse one or more aspects of such encoding with respect to the file / segment de-encapsulation of one or more of data F' and / or F' i and metadata, decode the audio data E' at the audio decoding block 510 i , decode the video data E' at the video decoding block 513 v , and decode the image data E' at the image decoding block 514 i to continue to process the data B' at the audio rendering block 511 aPerform audio rendering and perform image rendering on data D' at the image rendering block 515, so as to output display data A' in the VR360 format according to various data such as orientation / viewport metadata at the display block 516 i and output audio data A' at the speaker / headphone block 512 s . Depending on various tracks, languages, qualities, views that can be selected by the user of the OMAF player 520 or selected for the user, various metadata may affect the processing in data decoding and rendering processing, and it should be understood that the processing order described herein is presented for exemplary embodiments and can be implemented in other orders according to other exemplary embodiments.

[0081] Figure 6 FIG. 600 shows a simplified block-type content stream processing diagram for (decoded) point cloud data, in which view position and angle-related processing (referred to herein as "V-PCC") is performed on the point cloud data for 6-degree-of-freedom media of capture / generation / (de)coding / rendering / display. It should be understood that according to exemplary embodiments, the described features can be used alone or in any combination, and for example, elements for encoding and decoding and other elements shown can be implemented by processing circuitry (e.g., one or more processors or one or more integrated circuits), and one or more processors can execute a program stored in a non-transitory computer-readable medium.

[0082] FIG. 600 shows an exemplary embodiment for streaming decoded point cloud data according to V-PCC.

[0083] At the volume data acquisition block 601, a real-world visual scene or a computer-generated visual scene (or a combination thereof) can be captured by a set of imaging devices or synthesized into volume data by a computer, and the volume data, which can have any format, can be converted into (quantized) point cloud data format through image processing at the conversion to point cloud block 602. For example, according to an exemplary embodiment, data from the volume data can be converted region-by-region data into points in the point cloud by extracting one or more values from the values of the volume data and any associated data described below into a desired point cloud format. According to an exemplary embodiment, the volume data can be a 3D data set of 2D images, such as slices of 2D projections from which the 3D data set can be projected. According to an exemplary embodiment, the point cloud data format includes a representation of data points in one or more various spaces and can be used to represent the volume data and can provide improvements in sampling and data compression, such as improvements in temporal redundancy, and, for example, the point cloud data in the x, y, z format represents color values (e.g., RGB, etc.), luminance, intensity, etc. at each of the multiple points of the cloud data and can be used in conjunction with progressive decoding, polygon meshing, direct rendering, octree 3D representation of 2D quadtree data.

[0084] At the project onto image block 603, the acquired point cloud data can be projected onto a 2D image and encoded into an image / video picture using Video-based Point Cloud Coding (V-PCC). The projected point cloud data can include attributes, geometry, occupancy maps, and other metadata for point cloud data reconstruction, such as using the painter's algorithm, ray casting algorithm, three-dimensional (3D) binary space partitioning algorithm, etc.

[0085] On the other hand, at the scene generator block 609, the scene generator can generate some metadata, for example, according to the director's intention or the user's preference, for rendering and displaying 6 Degrees-of-Freedom (DoF) media. Such 6DoF media can include 360VR, such as in addition to allowing movement forward / backward, up / down, and left / right within or at least according to the point cloud decoded data relative to the virtual experience, a 3D viewing of the scene is also performed according to rotational changes on the 3D axes X, Y, Z. The scene description metadata defines one or more scenes composed of the decoded point cloud data and other media data including VR360, light field, audio, etc., and can be provided to one or more cloud servers and / or file / segment encapsulation / de-encapsulation processing as indicated by the relevant description. Figure 6 and the file / segment encapsulation / de-encapsulation processing as indicated by the relevant description.

[0086] After video encoding block 604 and image encoding block 605 similar to the above-described video and image encoding (and as will be appreciated, audio encoding may also be provided as described above), file / segment encapsulation block 606 processes such that the decoded point cloud data is combined into a media file for file playback or a series of initialization segments and media segments for streaming according to a specific media container file format such as one or more video container formats, and may be used, for example, with respect to DASH and the like described below when such a description represents an exemplary embodiment. The file container may also include scene description metadata such as from scene generator block 1109 in the file or segment.

[0087] According to an exemplary embodiment, the file is encapsulated according to scene description metadata to include at least one view position in 6DoF media and at least one or more angular views at that view position / these view positions at one or more moments, such that such a file can be transmitted on demand according to user or creator input. Additionally, according to an exemplary embodiment, segments of such a file may include one or more portions of such a file, for example, a portion of the 6DoF media indicating a single viewpoint and the angles at that viewpoint at one or more moments; however, these are only exemplary embodiments and may vary according to various conditions such as network, user, creator capabilities, and input.

[0088] According to an exemplary embodiment, the point cloud data is segmented into a plurality of 2D / 3D regions, which are independently decoded, for example, at one or more of video encoding block 604 and image encoding block 605. Then, each independently decoded segmentation of the point cloud data can be encapsulated as a track in the file and / or segment at file / segment encapsulation block 606. According to an exemplary embodiment, each point cloud track and / or metadata track may include some useful metadata for view position / angle-related processing.

[0089] According to an exemplary embodiment, metadata useful for processing related to view position / angle, for example, includes one or more of the following in metadata included in a file and / or segment encapsulated in a file / segment encapsulation block: layout information of a 2D / 3D segmentation with an index; (dynamic) mapping information associating a 3D volume segmentation with one or more 2D segmentations (e.g., any one of tiles / tile groups / slices / sub-pictures); 3D positions of each 3D segmentation on a 6DoF coordinate system; a list of representative view positions / angles; a list of selected view positions / angles corresponding to the 3D volume segmentation; indices of 2D / 3D segmentations corresponding to the selected view positions / angles; quality (grade) information of each 2D / 3D segmentation; and rendering information of each 2D / 3D segmentation depending on, for example, each view position / angle. Invoking such metadata when, for example, requested by a user of a V-PCC player or according to an instruction from a content creator for the user of the V-PCC player can enable more efficient processing for a specific part of 6DoF media expected with respect to such metadata, such that the V-PCC player can deliver an image of a focused part of 6DoF media with higher quality than other parts, rather than delivering unused parts of the media.

[0090] A file or one or more segments of a file can be directly delivered from the file / segment encapsulation block 606 to either the V-PCC player 625 or a cloud server, such as the cloud server in the cloud server block 607, using a delivery mechanism (e.g., via HTTP-based Dynamic Adaptive Streaming over HTTP (DASH)). At the cloud server block 607, the cloud server can extract one or more tracks and / or one or more specific 2D / 3D segmentations from the file and can merge multiple decoded point cloud data into one data.

[0091] According to data, for example, regarding the position / viewing angle tracking block 608, if the current viewing position and angle are defined on a 6DoF coordinate system at the client system, view position / angle metadata can be delivered from the file / segment encapsulation block 606 or otherwise processed based on the file or segment at the cloud server at the cloud server block 607, such that the cloud server can extract appropriate segmentations from the stored file and merge the segmentations (if necessary) according to metadata, for example, from the client system having the V-PCC player 625, and the extracted data can be delivered to the client as a file or segment.

[0092] Regarding such data, at the file / segment de-encapsulation block 615, the file de-encapsulator processes the file or the received segment, extracts the decoded bitstream and parses the metadata, and at the video decoding block 610 and the image decoding block 611, the decoded point cloud data is then decoded into decoded point cloud data, and at the point cloud reconstruction block 612 the decoded point cloud data is reconstructed into point cloud data, and the reconstructed point cloud data can be displayed at the display block 614 and / or can first be synthesized at the scene synthesis block 613 according to one or more various scene descriptions with respect to the scene description data from the scene generator block 609.

[0093] In view of the above, such an exemplary V-PCC stream represents advantages over the V-PCC standard, including one or more of the following: the described segmentation ability for multiple 2D / 3D regions; the ability to combine compressed-domain decoded 2D / 3D segmentations into a single compliant decoded video bitstream; and the ability to extract the decoded 2D / 3D bitstream of decoded pictures into a compliant decoded bitstream, where such a V-PCC system support is further improved by forming a container including a VVC (Versatile Video Coding, VVC) bitstream to support a mechanism for carrying metadata including one or more of the above metadata.

[0094] In view of this and according to the exemplary embodiments described further below, the term "mesh" indicates a composition of one or more polygons that describe the surface of a volumetric object. Each polygon is defined by its vertices in 3D space and information on how the vertices are connected (referred to as connectivity information). Optionally, vertex attributes such as color, normal, etc. can be associated with the mesh vertices. Attributes can also be associated with the surface of the mesh by using mapping information that parameterizes the mesh with a 2D attribute map. Such a mapping can be described by a set of parametric coordinates, referred to as UV coordinates or texture coordinates, associated with the mesh vertices. The 2D attribute map is used to store high-resolution attribute information such as texture, normal, displacement, etc. According to the exemplary embodiments, such information can be used for various purposes, such as texture mapping and shading.

[0095] However, a dynamic mesh sequence may require a large amount of data because it may include a large amount of information that changes over time. For example, contrary to a "static mesh" or "static mesh sequence" in which the information of the mesh may not change from one frame to another, a "dynamic mesh" or "dynamic mesh sequence" indicates the movement of which vertices represented by the mesh change from one frame to another. Therefore, efficient compression techniques are needed to store and transmit such content. The mesh compression standards IC, MESHGRID, and FAMC were previously developed by MPEG to handle dynamic meshes with constant connectivity as well as time-varying geometry and vertex attributes. However, these standards do not consider time-varying attribute maps and connectivity information. DCC (Digital Content Creation) tools typically generate such dynamic meshes. Correspondingly, for volume acquisition techniques, it is challenging to generate dynamic meshes with constant connectivity, especially under real-time constraints. Existing standards do not support this type of content. According to the exemplary embodiments herein, aspects of a new mesh compression standard for directly handling dynamic meshes with time-varying connectivity information and optionally time-varying attribute maps are described, which is for lossy and lossless compression for various applications such as real-time communication, storage, free viewpoint video, AR, and VR. Functions such as random access and scalable / progressive decoding are also considered.

[0096] Figure 7 An example framework 700 for a dynamic mesh compression for a method based on 2D atlas sampling, for example, is shown. Each frame of the input mesh 701 can be preprocessed through a series of operations (e.g., tracking, remeshing, parameterization, voxelization). Note that these operations can be encoder-only, which means these operations may not be part of the decoding process, and this possibility can be signaled in the metadata through a flag: for example, for encoder-only, the flag indicates 0 and for others, the flag indicates 1. Thereafter, a mesh 702 with a 2D UV atlas can be obtained, where each vertex of the mesh has one or more associated UV coordinates on the 2D atlas. Then, by sampling the 2D atlas, the mesh can be converted into multiple maps, including a geometry map and an attribute map. Then, these 2D maps can be decoded by a video / image codec such as HEVC, VVC, AV1, AVS3, etc. On the decoder 703 side, the mesh can be reconstructed from the decoded 2D maps. Any post-processing and filtering can also be applied to the reconstructed mesh 704. Note that for the purpose of 3D mesh reconstruction, other metadata can be signaled to the decoder side. Note that the chart boundary information including uv coordinates and xyz coordinates of the boundary vertices can be predicted, quantized, and entropy-coded in the bitstream. The quantization step size can be configured on the encoder side to trade off quality and bitrate.

[0097] In some implementations, a 3D mesh can be segmented into a number of segments (or patches / charts). According to an exemplary embodiment, one or more 3D mesh segments can be regarded as a "3D mesh". Each segment can consist of a set of connected vertices associated with its geometry, attributes, and connectivity information. As Figure 8 shown in the example 800 of volumetric data in, the UV parameterization process 802 that maps from a 3D mesh segment to a 2D chart, for example, to the blocks of the 2D UV atlas 702 mentioned above, maps one or more mesh segments 801 to the 2D chart 803 in the 2D UV atlas 804. Each vertex (v n ) in the mesh segment will be assigned 2D UV coordinates in the 2D UV atlas. Note that the vertices (v n ) in the 2D chart form a connected component that is the 3D counterpart thereof. The geometry, attributes, and connectivity information of each vertex can also be inherited from its 3D counterpart. For example, information indicating that vertex v4 is directly connected to vertices v0, v5, v1, and v3 can be indicated, and similarly, similar information for each of the other vertices can also be indicated. In addition, according to an exemplary embodiment, such a 2D texture mesh will further indicate information such as color information on a per-patch basis, and such per-patch is, for example, for each triangle patch, for example, v2, v5, v3 as one "patch".

[0098] For example, regarding Figure 8 the features of the example 800 of, refer to Figure 9 the example 900 of, where the 3D mesh segment 801 can also be mapped to multiple separate 2D charts 901 and 902. In this case, a vertex in 3D can correspond to multiple vertices in the 2D UV atlas. As Figure 9 shown, the same 3D mesh segment is mapped to multiple 2D charts in the 2D UV atlas, rather than a single chart as in Figure 8 . For example, 3D vertices v1 and v4 each have two 2D correspondences v1, v 1' and v4, v 4' . Therefore, the general 2D UV atlas of the 3D mesh can include multiple charts as shown in Figure 14 , where each chart can contain multiple (usually more than or equal to 3) vertices associated with its 3D geometry, attributes, and connectivity information.

[0099] Figure 9Example 903 is shown, which shows a triangulation derived from a graph having boundary vertices B0, B1, B2, B3, B4, B5, B6, B7. When such information is provided, any triangulation method can be applied to create connections between vertices (including boundary vertices and sampled vertices). For example, for each vertex, find the two closest vertices. Or for all vertices, continuously generate triangles until the minimum number of triangles is reached after a set number of attempts. As shown in Example 903, there are various regularly shaped, repeating triangles and various oddly shaped triangles, and these oddly shaped triangles are usually closest to the boundary vertices and have their own unique dimensions, which may or may not be shared with any other triangles in the triangle. The connectivity information can also be reconstructed by explicit signaling. If the polygon cannot be recovered by implicit rules, then according to an exemplary embodiment, the encoder can signal the connectivity information in the bitstream.

[0100] Define boundary vertices B0, B1, B2, B3, B4, B5, B6, B7 in 2D UV space. The boundary edges can be determined by checking whether an edge appears in only one triangle. According to an exemplary embodiment, the following information of the boundary vertices is important and should be signaled in the bitstream: geometric information, for example, 3D XYZ coordinates, even if currently in 2D UV parameter form; and 2D UV coordinates.

[0101] For the case where the boundary vertices in 3D as Figure 9 shown correspond to multiple vertices in a 2D UV atlas, the mapping from 3D XUZ to 2D UV can be one-to-many. Therefore, a UV-to-XYZ (or referred to as UV2XYZ) index can be signaled to indicate the mapping function. UV2XYZ can be a 1D array of indices that map each 2D UV vertex to a 3D XYZ vertex.

[0102] According to an exemplary embodiment, in order to efficiently represent the mesh signal, a subset of the mesh vertices along with their connectivity information between them can be decoded first. In the original mesh, the connections between these vertices may not exist because these vertices are subsampled from the original mesh. There are different ways to signal the connectivity information between vertices, and thus such a subset is called a base mesh or base vertices.

[0103] According to an exemplary embodiment, multiple methods are implemented for dynamic mesh compression, and the multiple methods are part of the edge-based vertex prediction framework mentioned above, where the base mesh is decoded first, and then more additional vertices are predicted based on the connectivity information of the edges from the base mesh. Note that these methods can be applied individually or in any form of combination.

[0104] For example, consider Figure 10 the vertex grouping of the exemplary flowchart 1001 of the prediction pattern. At S101, vertices inside the grid can be obtained, and at S102, the vertices can be divided into different groups for prediction purposes. For example, see Figure 9 . In one example, patch / map segmentation is used for the division at S104. In another example, the division is performed under each patch / map S105. The decision S103 of whether to proceed to S104 or S105 can be signaled by a flag or the like. In the case of S105, several vertices of the same patch / map form a prediction group and will share the same prediction pattern, while several other vertices of the same patch / map can use another prediction pattern. Herein, a "prediction pattern" can be regarded as a specific pattern used by a decoder for predicting video content including patches. The prediction pattern can be classified into an intra prediction pattern and an inter prediction pattern, and within each category, there can be different specific patterns from which the decoder selects. According to an exemplary embodiment, each group, a "prediction group", can share the same specific pattern (e.g., an angular pattern at a specific angle) or the same classified prediction pattern (e.g., all intra prediction patterns, but can be predicted at different angles) according to an exemplary embodiment. This grouping at S106 can be assigned at different levels by determining the corresponding number of vertices involved in each group. For example, according to an exemplary embodiment, every 64, 32, or 16 vertices following the scan order within a patch / map will be assigned the same prediction pattern, while other vertices can be assigned differently. For each group, the prediction pattern can be an intra prediction pattern or an inter prediction pattern. This can be signaled or assigned. According to the exemplary flowchart 1000, if it is determined at S107 that the grid frame or grid slice is of the intra type, for example, by checking whether the flag of the grid frame or the grid slice indicates the intra type, then all the vertices of all the groups within the grid frame or grid slice should use the intra prediction pattern; otherwise, at S108, the intra prediction pattern or the inter prediction pattern can be selected for all the vertices in each group.

[0105] In addition, for a group of grid vertices using the intra prediction pattern, its vertices can be predicted only by using the previously decoded vertices within the same sub - division of the current grid. According to an exemplary embodiment, sometimes the sub - division can be the current grid itself, and according to an exemplary embodiment, for a group of grid vertices using the inter prediction pattern, its vertices can be predicted only by using the previously decoded vertices from another grid frame. Each of the above - mentioned information can be determined and signaled by a flag or the like. The prediction feature can occur at S110, and the result of the prediction and signaling can occur at S111

[0106] According to an exemplary embodiment, for each vertex in a set of vertices in the example flowchart 1000 and the flowchart 1100 described below, after prediction, the residual will be a 3D displacement vector indicating the offset from the current vertex to its predictor. The residuals of a set of vertices need to be further compressed. In one example, before entropy coding, the transform at S111 along with its signaling can be applied to the residuals of the set of vertices. The following methods can be implemented to handle the coding of a set of displacement vectors. For example, in one method, the cases where a set of displacement vectors, some displacement vectors, or their components have only zero values are signaled appropriately. In another embodiment, for each displacement vector, a flag indicating whether the vector has any non-zero components is signaled, and if not, the coding of all components of the displacement vector can be skipped. Further, in another embodiment, for each set of displacement vectors, a flag indicating whether the set has any non-zero vectors is signaled, and if not, the coding of all displacement vectors in the set can be skipped. Additionally, in another embodiment, for each component of a set of displacement vectors, a flag indicating whether the component of the set has any non-zero vectors is signaled, and if not, the coding of that component of all displacement vectors in the set can be skipped. Moreover, in another embodiment, there may be cases where it is signaled that a set of displacement vectors or the components of the set of displacement vectors need to be transformed, and if not, the transformation can be skipped, and quantization / entropy coding can be directly applied to the set or the set of components. Further, in another embodiment, for each set of displacement vectors, a flag indicating whether the set needs to undergo transformation is signaled, and if not, the transform coding of all displacement vectors in the set can be skipped. Additionally, in another embodiment, for each component of a set of displacement vectors, a flag indicating whether the component of the set needs to undergo transformation is signaled, and if not, the transform coding of that component of all displacement vectors in the set can be skipped. The above embodiments regarding the processing of vertex prediction residuals in this paragraph can also be implemented separately for different patch combinations and in parallel.

[0107] Figure 11An example flowchart 1100 is shown, where at S121, a mesh frame decoded as an entire data unit can be obtained, which means that all vertices or attributes of the mesh frame can have correlations among them. Alternatively, according to the determination at S122, the mesh frame can be divided into smaller independent sub-divisions at S123, which conceptually is similar to slices or tiles in 2D video or images. At S124, a prediction type can be assigned to the decoded mesh frame or the decoded mesh sub-division. Possible prediction types include intra-frame decoding type and inter-frame decoding type. For the intra-frame decoding type, at S125, only prediction from the reconstructed parts of the same frame or slice is allowed. On the other hand, at S125, in addition to in-mesh-frame prediction, the inter-frame prediction type will allow prediction from previously decoded mesh frames. Furthermore, the inter-frame prediction type can be classified using more subtypes such as P type or B type. In the P type, only one predictor can be used for prediction purposes, while in the B type, two predictors from two previously decoded mesh frames can be used to generate a predictor. A weighted average of the two predictors can be an example. When the mesh frame is decoded as a whole, the frame can be regarded as an intra-frame or inter-frame decoded mesh frame. In the case of an inter-frame mesh frame, the P type or B type can be further identified via signaling. Alternatively, if the mesh frame is decoded in the case of further intra-frame division, at S124, the assignment of prediction types occurs for each sub-division in the sub-divisions. Each of the above information can be determined and signaled through flags, etc., and similar to Figure 10 S110 and S111, the prediction feature can occur at S126, and the result of the prediction and signaling can occur at S127.

[0108] Therefore, although a dynamic mesh sequence may require a large amount of data, because it may include a large amount of information that changes over time, an efficient compression technique is needed to store and transmit such content, and the features described herein represent this improved efficiency by enabling at least an improvement in the prediction of the 3D positions of mesh vertices by using (intra-frame prediction) in the same mesh frame or (inter-frame prediction) previously decoded vertices from previously decoded mesh frames.

[0109] In addition, an exemplary embodiment can generate a displacement vector for the third layer 1303 of the mesh based on one or more reconstructed vertices of the previous layers such as the second layer 1302 and the first layer 1301 of the third layer 1303. Assuming the index of the second layer 1302 is T, a predictor for the vertices in the third layer 1303 T+1 is generated based on at least the reconstructed vertices of the current layer or the second layer 1302. An example of such a layer-based prediction structure is as shown in Figure 13 example 1300 in Figure 13Shows vertex prediction based on reconstruction: Progressive vertex prediction is performed using edge-based interpolation, where the predictor is generated based on previously decoded vertices rather than predictor vertices. The first layer 1301 can be a mesh bounded by a first polygon 1340 that has decoded vertices as its vertices at its boundary and has interpolated vertices along lines among the vertices of these decoded vertices. As progressive decoding proceeds from the first layer 1301 to the second layer 1302, an additional polygon 1341 can be formed by displacement vectors from the interpolated vertices in the first layer to the additional vertices of the second layer 1302, and thus, the total number of vertices in the second layer 1302 can be greater than the total number of vertices in the first layer 1301. Similarly, proceeding to the third layer 1303, the additional vertices of the second layer 1302 together with the decoded vertices from the first layer 1301 can then serve the decoding in a manner similar to the decoded vertices served in proceeding from the first layer 1301 to the second layer 1303; i.e., multiple additional polygons can be formed. It should be noted that referring to Figure 14 Example 1400 in Figure 14 shows such progressive decoding, where, different from Figure 13 Example 1400 shows that in proceeding from the first layer 1401 to the second layer 1403 and then to the third layer 1403, each of the additionally formed polygons can be entirely within the polygon formed by the boundary of the first layer 1401.

[0110] For such examples 1300 and / or 1400, according to an exemplary embodiment, referring to Figure 12 Example flowchart 1200, where, since the interpolated vertices on the current layer are predicted values, such values need to be reconstructed before being used in the predictor for generating vertices on the next layer. This is done as follows: Decode the base mesh at S131; perform vertex prediction at S132; then add the decoded displacement vectors of the current layer to the vertex predictor at S133, such as the vertex predictor of layer 1302. Then, the reconstructed vertices of this layer together with all the decoded vertices of the previous layer - such as checking the additional vertex values of such a layer at S134 - can be used to generate the predictor vertices of the next layer 1303 at S135 and signal the predictor vertices. This process can also be summarized as follows: Assume P[t](Vi) represents the predictor of vertex Vi on layer t; assume R[t](Vi) represents the reconstructed vertex Vi on layer t; assume D[t](Vi) represents the displacement vector of vertex Vi on layer t; assume f(*) represents the predictor generator, which can particularly be the average of two existing vertices. Then, for each layer t, according to an exemplary embodiment, there is the following: R[t](Vi) = f(R[s|s<t](Vj), R[m|m<t](Vk)), where, Vj and Vk are vertices reconstructed from a previous layer R[t](Vi) = P[t](Vi) + D[t](Vi) - Equation (1)

[0111] Then, for all vertices in a mesh frame, the vertices are partitioned into layer 0 (base mesh), layer 1, layer 2, …, etc. Then, the reconstruction of vertices on one layer depends on the reconstruction of vertices on the previous layer. Herein, each of P, R, and D represents a 3D vector in the context of a 3D mesh representation. D is the decoded displacement vector, and quantization may or may not be applied to this vector.

[0112] According to an exemplary embodiment, vertex prediction using reconstructed vertices may be applied only to certain layers. For example, layer 0 and layer 1. For other layers, vertex prediction may still use neighboring predictor vertices without adding a displacement vector to the vertices for reconstruction. Such that these other layers can be processed simultaneously without waiting for the previous layer to be reconstructed. According to an exemplary embodiment, for each layer, it may be signaled whether to select vertex prediction based on reconstructed vertices or select vertex prediction based on predictors, or it may be signaled that the layer (and subsequent layers) do not use vertex prediction based on reconstruction.

[0113] For the displacement vector whose vertex predictor is generated from reconstructed vertices, quantization may be applied thereto without further transformation, such as wavelet transformation, etc. For the displacement vector whose vertex predictor is generated from other predictor vertices, transformation may be required, and quantization may be applied to the transformation coefficients of these displacement vectors.

[0114] Therefore, a dynamic mesh sequence may require a large amount of data because the dynamic mesh sequence may include a large amount of information that changes over time. Therefore, efficient compression techniques are needed to store and transmit such content. In the framework of the above-described interpolation-based vertex prediction method, an important process is to compress the displacement vector, and this occupies a major part in the decoded bitstream, and the focus and features of the present disclosure alleviate this problem by providing such compression.

[0115] In addition, similar to the other examples above, even in the case of those embodiments, a dynamic mesh sequence may require a large amount of data because the dynamic mesh sequence may include a large amount of information that changes over time, and thus, efficient compression techniques are needed to store and transmit such content. In the framework of the above-described 2D atlas sampling method, an important advantage can be achieved by inferring connectivity information at the decoder side based on the sampled vertices plus boundary vertices. This is a major part in the decoding process and is the focus of other examples described below.

[0116] According to an exemplary embodiment, the connectivity information of the base mesh can be inferred (derived) based on the decoded boundary vertices and sampled vertices for each graph on both the encoder side and the decoder side.

[0117] Similarly as described above, any triangulation method can be applied to create connections between vertices (including boundary vertices and sampled vertices). According to an exemplary embodiment, the connectivity type can be signaled in a high-level syntax such as a sequence header, a slice header.

[0118] As mentioned above, for example, for an irregular-shaped triangular mesh, the connectivity information can also be reconstructed by explicit signaling. That is, if it is determined that the polygon cannot be recovered by implicit rules, the encoder can signal the connectivity information in the bitstream. And according to an exemplary embodiment, the overhead of such explicit signaling can be reduced based on the boundary of the polygon.

[0119] According to an embodiment, only the connectivity information between the boundary vertices and the sampled positions is determined to be signaled, while the connectivity information between the sampled positions themselves is inferred.

[0120] Furthermore, in any embodiment of the embodiments, the connectivity information can be signaled by prediction, such that only the difference in the inferred connectivity (as a prediction) from one mesh to another mesh can be signaled in the bitstream.

[0121] It should be noted that according to an exemplary embodiment, the orientation of the inferred triangles (e.g., each triangle is inferred in a clockwise or counterclockwise manner) can be signaled in a high-level syntax such as a sequence header, a slice header, etc. for all graphs, or the orientation can be fixed (assumed) by the encoder and the decoder. The orientation of the inferred triangles can also be signaled differently for each graph.

[0122] As a further note, any reconstructed mesh can have a different connectivity from the original mesh. For example, the original mesh can be a triangular mesh, while the reconstructed mesh can be a polygon mesh (e.g., a quadrilateral mesh).

[0123] According to an exemplary embodiment, the connectivity information of any base vertices can be not signaled, but rather the same algorithm can be used on both the encoder side and the decoder side to derive the edges between the base vertices. And according to an exemplary embodiment, the interpolation of the predicted vertices of the additional mesh vertices can be based on the derived edges of the base mesh.

[0124] According to an exemplary embodiment, a flag can be used to signal whether to signal or derive the connectivity information of the base vertices, and such a flag can be signaled at different levels of the bitstream such as the sequence level, the frame level, etc.

[0125] According to an exemplary embodiment, first, the same algorithm is used on both the encoder side and the decoder side to obtain the edges between the base vertices. Then, by comparing with the original connectivity of the base mesh vertices, the difference between the obtained edges and the actual edges is signaled. Thus, after decoding the difference, the original connectivity of the base vertices can be restored.

[0126] In one example, for the obtained edges, if they are determined to be incorrect compared to the original edges, such information can be signaled in the bitstream (by indicating the vertex pairs forming the edges); and for the original edges, if they are not obtained, it can be signaled in the bitstream (by indicating the vertex pairs forming the edges). In addition, the connectivity on the boundary edges and the vertex interpolation involving the boundary edges can be performed separately from the internal vertices and edges.

[0127] Thus, through the exemplary embodiments described herein, the above technical problems can be advantageously improved by one or more of these technical solutions. For example, since a dynamic mesh sequence may require a large amount of data because the dynamic mesh sequence may include a large amount of information that changes over time, and thus, the exemplary embodiments described herein represent at least an efficient compression technique for storing and transmitting such content.

[0128] The above embodiments can be further applied to instance-based mesh decoding, where the instance can be a mesh of an object or a part of an object. For example, Figure 15 The illustrated example 1500 shows a mesh example 1501, where there are various instances 1502 (mesh representing a cup), 1503 (mesh representing a spoon), and 1504 (mesh representing a plate), and these instances can be separately separated and decoded. And each of the instances 1501, 1502, 1503, and 1504 is shown in the corresponding bounding boxes in the bounding boxes to be further described below. However, it should be noted that the instance 1501 can be considered to be shown as bounded by a "mesh-based bounding box", while each of the instances 1502, 1503, and 1504 can be considered to be shown as bounded by the corresponding bounding boxes in an "instance-based bounding box".

[0129] Viewing the example 1600 showing distance-based displacement decoding for a 3D mesh, in Figure 16 which, the displacement decoding is almost lossless, and in this context, this can be regarded as lossless. The 3D mesh is described according to an exemplary embodiment based on the selection of 3D decoding. For example, if it is determined that lossy decoding is not selected, the vertex z4 is predicted from the adjacent vertices in the base mesh: points z1, z2, z3. Similar to the 2D case of example 1601, if the distance h hGiven this, point z4 can be predicted from point z′4. On the other hand, point z′4 can be predicted from point z t with distance h s and h n or point z′ n (depending on rate and distortion cost). In summary, to signal point z4, the three distances h s , h t , h h will be used together with an index to indicate which edge is used for prediction. That is, points z1, z2, z3 can be base mesh vertices; point z4 can be a residual vertex; point z′4 can be a projected vertex; and points z n and z′ n can be derived neighbors.

[0130] Referring to Example 1603 showing mesh decoding based on subdivision and distance, such an exemplary implementation similarly introduces displacement decoding for a lossy 3D mesh selected at S2008 based on distance and face subdivision. That is, similar to Example 1602, in Example 1603, the projected vertex of point x4 on the base mesh face - point x′4 and distance d h are sufficient to encode point x4. In this implementation, the face is first subdivided at level L. The subdivision point closest to point x′4 is selected (which is x n in this example). Then, point h is derived at distance d n from point x point in the direction of the normal to the current triangle. Point n is considered a lossy version of point x4. Finally, the index of point x h and distance d 1 in the case of subdivision are encoded, and although triangle subdivision is shown in Example 1603, other polygon shapes as described herein can be used. That is, points x 2 , x 3 can be base mesh vertices; point x4 can be a residual vertex; point x′4 can be a projected vertex; point x n can be the closest subdivision; and point is the predicted vertex.

[0131] As described above for Example 1601, Example 1603 also represents an additional advantageous improvement because, compared to Example 1602, Example 1603 can simplify the computational complexity compared to the case where one of the values of point z4 and point z′4 may not be an integer value (for the purposes of this description, point z4 and point z′4 correspond to point x4 and point x′4 respectively). That is, by finding point x which is the point closest to point x4n (Among the vertices of the polygon regularly divided within the entire polygon formed by vertices x1, x2, x3), the point x n may be more likely to have an integer value than the point x′4, and thus as the point from which the vertex is predicted Similarly, it may have an integer value and thus reduces the computational complexity compared to the point x4 which is likely to have such an integer value conversely.

[0132] The mesh geometry information includes vertex connectivity information, 3D coordinates, 2D texture coordinates, etc., and the compression of vertex 3D coordinates (which are also called vertex positions) is very important because in most cases, it occupies a considerable part of the entire geometry-related data.

[0133] According to an embodiment, the dynamic mesh sequence M at time instance t can be represented as M(t). M(t) is called a position tracking frame. If there is a one-to-one mapping f from the vertex positions of M(t) to the vertex positions of another time instance M(t0) (where t and t0 are different time instances), then M(t0) can be represented as a reference frame, and the corresponding vertices in the reference frame are represented as reference vertices.

[0134] For a position tracking frame and its reference frame, according to an exemplary embodiment, the vertex position difference between the mapped vertices in the two frames can be represented by a motion vector (MV), and in MV decoding, the residual MV is derived from the prediction using the adjacent decoded MV.

[0135] Further improvement of motion vector decoding can be achieved as follows. First, since there are duplicate vertices in the decoded mesh of the reference frame, a pair of duplicate vertices (A, A') can be defined as two vertices in the decoded mesh frame that have the same position but different vertex indices, and assume that A is the vertex that is earlier than A' in the encoding / decoding order, and vertex A can be called the earlier vertex, and vertex A' can be called the later vertex. Second, according to an exemplary embodiment, in most cases, the MVs of the duplicate vertices A and A' are exactly the same.

[0136] Therefore, motion vector decoding based on integrating duplicate vertices can integrate the k-th pair of duplicate vertices (A k , A k ': k = 1,..., K) into a single vertex A k (called the integrated vertex), and update the connectivity in the decoded mesh of the reference frame.

[0137] Due to the integration of duplicate vertices, the implementation can further update the one-to-one mapping between an inter-frame and its reference frame at the encoder, which reduces the number of MVs. On the other hand, there are integrated vertices with multiple MVs after integrating the duplicate vertices. Therefore, the implementation can signal the total number of additional MVs and all indices from these multiple MVs. If the integrated vertex A k has N k (N k >1) MVs, the number and index of the additional MVs are (N k -1) and k, respectively. The total number of additional MVs may be Therefore, there are duplicate vertices and non-duplicate vertices in the decoded mesh before integration. After integration, the integrated vertices can have a single MV (the vast majority) or multiple MVs.

[0138] Therefore, the implementations herein can improve these features and enhance mesh motion vector decoding through vertex grouping.

[0139] According to an implementation, multiple methods and systems for mesh motion vector decoding are proposed. Note that these implementations can be applied individually or in any form of combination, such as the implementation in Example 1700 described below Figure 17 . For example, for a vertex V in the position tracking frame M(t), its neighbors are the vertices connected to V by edges, and these vertices are called the neighbor vertices of V.

[0140] For the position tracking frame M(t) and its reference frame M(t0), assume that the implementation of f is a mapping between the vertex positions of M(t) and M(t0). Considering the vertices in M(t) If there are decoded vertices in M(t) such that their reference vertices f(V) and have the same position value, the implementation regards V as a duplicate vertex. Decoded vertices mean whose decoding order is before V. Assuming that the subscripts x, y, z represent 3D coordinates in the xyz space, for the duplicate vertex V, the implementation has and

[0141] For the duplicate vertex V, if V and have the same position value, i.e., then the implementation regards V as a skippable duplicate; otherwise, the implementation regards V as a non-skippable duplicate. As Figure 17As shown, the vertex position compression method according to an embodiment in this document includes: repeatedly signaling feature 1701; grouping of vertex features 1702; calculation of position prediction features 1703; position prediction mode decoding feature 1704; and position prediction residual decoding feature 1705.

[0142] For example, repeatedly signaling feature 1701 includes: integrating a method for repeating vertices and signaling the repeated vertices. For the repeated vertices, repeatedly signaling feature 1701 further signals whether the repeated vertices are skippable repeats or non-skippable repeats.

[0143] Grouping of vertex features 1702 includes: dividing the vertices of the position-tracking frame M(t) into multiple groups, where each group contains K vertices, and K is a constant. For example, the vertices are divided into groups of 10 vertices, where K = 10. According to an embodiment, K = 16. For another example, if K = 1, each group contains one vertex. For another example, if K is equal to the number of vertices of frame M(t), all vertices are in the same group. In one embodiment, skippable repeats will be skipped during grouping. For example, for grouping of 10 vertices, if the first 12 vertices have 2 skippable repeats, the first group will include vertices from index 0 to index 11, excluding the 2 skippable repeats. In another embodiment, all vertices, including skippable repeats, will be considered during grouping.

[0144] According to an embodiment, by looking at Figure 19 Example 1900 of, vertex grouping follows a geometric structure. For example, the vertices can be divided into groups using octree decomposition via geometric tree structures 1901, 1902, 1903, 1904, where each of the above geometric tree structures is a group of vertices, structure 1903 is a group of vertices decomposed from the group of vertices of structure 1902, and structure 1904 is a group of vertices decomposed from one of the groups of vertices of structure 1903. That is, Figure 19 shows that the vertices can be divided into groups using octree decomposition, and each octree can be a group.

[0145] According to an embodiment, the vertices can be divided into multiple groups in the following predefined order. According to an embodiment, the order is from front to back or from right to left, etc., but it is not necessarily required that the grouped vertices are edge-connected. According to an embodiment, the vertices are divided into multiple groups in a traversal order such as the traversal order in the Edgebreaker algorithm. In addition, according to an embodiment, the vertices can be divided into multiple groups in Morton order. Through Edgebreaker, at least some of the vertices in the group are not edge-connected to each other. For example, by looking at Figure 9When, v1 and v2 are edge - connected and can be grouped with vertices (e.g., outside the edges in Figure 9 ), from another non - edge - connected mesh) (e.g., other vertices in Figure 15 ), by Edgebreaker, and / or according to an embodiment, v1 and v3 can be grouped into one group, and v2 and other vertices can be grouped into another group, like other vertices among the illustrated vertices. By Morton, there is grouping by considering the mesh coordinate system. For example, if a vertex is closer or has a smaller distance on the x - axis than on the y or z - axis, or if the distance on the x - axis is less than a threshold, the vertex can be grouped by its x - dimension, and according to an embodiment, such a feature is similarly applied to the y - axis and / or z - axis.

[0146] These grouping embodiments achieve a technical improvement because grouping reduces prediction error due to the increased likelihood that grouped vertices are closer in space.

[0147] The calculation of the position prediction feature 1703 includes such a feature that for a vertex V in a group G of a position tracking frame M(t), its position can be estimated by referring to the position of a reference vertex f(V) in a reference frame, where f is the mapping between M(t) and the reference frame. The motion vector E is the difference between the positions of V and f(V), such that E = V – f(V).

[0148] Since each vertex has 3D coordinates, the above formula calculates each coordinate component, that is, E x = V x -(f(V)) x ; Ey = V y -(f(V)) y ; E z = V z -(f(V)) z .

[0149] According to an embodiment, the motion vector E can be predicted based on the neighbors of the vertex V. According to an embodiment, the neighbors of a vertex can be, for example, the vertices connected to the edges of vertex V in a mesh or sub - mesh. For a neighbor vertex of V, if it has been decoded, the embodiment can use the motion vector of the neighbor vertex to predict E.

[0150] The embodiment can assume that V has N neighbor vertices V1, V2,..., V N that have been decoded and can be used for prediction. For a neighbor vertex V i , its motion vector is E i = V i –f(V i), where i = 1, 2, …, N. And the embodiment can define the average value of these motion vectors E0 as E0 = (E1 + E2 + … + E N ) / N. In addition, for group G, the encoder can estimate the decoding costs of the following two methods: The first method is C0: decoding the motion vectors E of all vertices; The second method is C1: decoding the estimated residuals (E - E0) of all vertices.

[0151] If the encoding cost of C0 is less than or equal to C1, then for group G, its prediction mode is 0, and the prediction residual is set to the motion vectors E of all vertices. If the decoding cost of C0 is greater than C1, then for group G, its prediction mode is 1, and according to this embodiment, the prediction residual is set to the estimated residuals (E - E0) of all vertices. According to the embodiments herein, the cost can be determined by the bit length (e.g., the bit length result of C0 being greater than or less than C1).

[0152] The position prediction mode decoding feature 1704 can consider that the prediction mode of group G (which is a binary digit 0 or 1) can be decoded. In one embodiment, entropy decoding is used to decode the prediction mode. In one embodiment, arithmetic decoding is used to decode the prediction mode.

[0153] In one embodiment of the position prediction mode decoding feature 1704, context-based arithmetic decoding is used to decode the prediction mode. In one embodiment, spatially context-based arithmetic decoding is used to decode the prediction mode, where the context is conditioned on the previously decoded groups in the same frame.

[0154] When the prediction modes in the reference frame have been decoded and are available, time context can be used to decode the prediction modes of the groups in frame M(t). Since each vertex has a reference vertex, there is also a one-to-one association between the groups in the position tracking frame and their reference frames. The embodiment can consider the associated groups in the reference frame as reference groups.

[0155] In one embodiment of the position prediction mode decoding feature 1704, the exclusive OR (XOR) of the prediction mode of group G and the prediction mode of the reference group is decoded. Thus, if group G and the reference group have the same prediction mode, their XOR (i.e., 0) is decoded. If group G and the reference group have different prediction modes, their XOR (i.e., 1) is decoded.

[0156] In another embodiment of the position prediction mode decoding feature 1704, a binary flag (either 0 or 1) indicating whether the group G and its reference group have the same prediction mode is decoded. Thus, if the group G and the reference group have the same prediction mode, the binary digit 1 is decoded. If the group G and the reference group have different prediction modes, the binary digit 0 is decoded.

[0157] In another embodiment of the position prediction mode decoding feature 1704, the prediction mode of the group G in the position tracking frame M(t) is decoded using arithmetic decoding based on temporal context, where the context is the prediction mode of the reference group.

[0158] The position prediction residual decoding feature 1705 may include considering decoding the prediction residuals. According to an embodiment, fixed-length decoding, exponential Golomb decoding, arithmetic decoding, etc. may be used to decode the prediction residuals. The prediction residuals undergo a compression transform, such as Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), Discrete Wavelet Transform (DWT), etc., and according to an exemplary embodiment, fixed-length decoding, exponential Golomb decoding, arithmetic decoding, etc. are used to decode the output from the compression transform. The embodiments described herein are also applicable to the motion field.

[0159] The following problems can be solved by the embodiments in this document. In V-Grid TM v1.0, motion field decoding is used for the inter-frame mode of the base grid. For a vertex v in the base grid m(i), the motion field f(i,v) is calculated by subtracting the quantized position Pos(i,v) of the vertex v in m(i) from the position Pos(j,v) of the vertex v in the reconstructed and quantized reference base grid m’(j): f(i,v) = Pos(i,v) - Pos(j,v). And during motion field decoding, for each vertex v, a flag indicating whether to predict the motion field f(i,v) based on the adjacent vertices of v is signaled. In addition, a skip mode for improving motion prediction in mesh decoding is proposed. For the inter-frame mode base grid m(i), all vertices are classified into two categories, namely, one category is the repeated vertices, and the other category is the non-repeated vertices. The repeated vertices are further classified into two subcategories, namely, skippable and non-skippable. The skippable repeated vertices can be perfectly reconstructed at the decoder and thus will not be decoded at the encoder. To help the decoder identify the skippable repeated vertices, the indices of all non-skippable repeated vertices will be signaled during encoding. And the embodiments in this document further enhance the motion field decoding by grouping the vertices in the motion field decoding. The vertices in a group will share the same pattern regarding whether to predict the motion field based on their adjacent vertices.

[0160] That is, according to the embodiment, for the inter-frame mode base grid m(i), the embodiment classifies the vertices into two categories, namely, one category is the class D of repeated vertices, and the other category is the class N of non-repeated vertices. For class D, it is further classified into two subcategories, namely, the subcategory S of skippable repeated vertices and the subcategory K of non-skippable repeated vertices. The indices of all vertices in subcategory K are decoded.

[0161] The motion fields of all vertices in the subcategory S of skippable repeated vertices can be perfectly reconstructed at the decoder and thus they will not be decoded at the encoder. Next, the embodiment decodes the motion fields of the remaining vertices, that is, the vertices in the class N of non-repeated vertices and the vertices in the subcategory K of non-skippable repeated vertices.

[0162] For the remaining vertices, the embodiment divides them into vertex groups. For example, the embodiment can divide them into groups of 16 vertices.

[0163] The embodiment can signal at the group level instead of signaling for each vertex regarding the pattern of whether to predict the motion field based on its adjacent vertices.

[0164] For example, for each group, the implementation estimates the decoding cost of directly decoding the motion field and the decoding cost of predicting the motion field based on its adjacent vertices, and selects the one with the lower decoding cost. Signals at the group level regarding the mode of whether to predict the motion field based on its adjacent vertices.

[0165] The decoding efficiency of the solution according to the implementation in this article was verified through experimental results. For example, the vertices were divided into groups of 16, and the proposed solution was evaluated against V-Mesh TM v1. The bitrate savings of the motion field decoding are listed in Tables 1, 2, 3, and 4 below. Table 1: Bit length and bitrate savings Table 2: Bit length and bitrate savings Table 3: Bit length and bitrate savings Table 4: Bit length and bitrate savings

[0166] On average, compared to V-Mesh TM v1.0, the bitrate savings of the motion field decoding of the implementation is 6.86%.

[0167] In addition, the motion field decoding enhancement of the implementation in this article is compatible with and combines two enhancements of edgebreaker-based base mesh compression: uv coordinate compression and position compression according to the implementation in this article. Using the combination of these two enhancements, the BD rate savings of the total bitstream (compared to V-Mesh TM v1.0) are listed in Table 5 below.

[0168] During the encoder / decoder runtime, integrating the combination of the motion field decoding enhancement and the Draco enhancement has no impact on V-Mesh TM v1.0.

[0169] Therefore, the implementation in this article provides an enhancement of the motion field decoding in mesh compression. It is reported that the implementation in this article can achieve bitrate savings relative to V-Mesh TM v1.0, and in addition, the implementation in this article represents a lossless improvement to the motion field decoding. Compared to V-Mesh TM v1.0, the decoded mesh according to the implementation in this article is the same as the anchor.

[0170] The base grid inter - sub - grid data unit syntax or the spatial grouping syntax of the embodiments described herein can be expressed as follows (bold indicates signaled explicitly):

[0171] According to an exemplary embodiment, sismu_integrate_mv_byte[subMeshID] indicates whether there are integrated vertices in the current sub - mesh and how many integrated vertices have multiple motion vectors, where the sub - mesh ID is equal to subMeshID. When sismu_integrate_mv_byte is equal to 128 or 255, there are no integrated vertices with multiple motion vectors. Otherwise, sismu_integrate_mv_byte specifies the number of integrated vertices with multiple motion vectors. The value of sismu_integrate_mv_byte should be in the range of 0 to 255. If sismu_integrate_mv_byte does not exist, it should be inferred to be equal to 0. An integrated vertex is an output vertex in H.11.4 that integrates at least two vertices with the same geometric position.

[0172] According to an exemplary embodiment, sismu_multi_mv_idx[subMeshID][i] specifies the index in the paired duplicate vertices with multiple motion vectors in the current sub - mesh, where the sub - mesh ID is equal to subMeshID. The default value is 0. The value of sismu_multi_mv_idx[i] should be in the range of 0 to 255. If sismu_multi_mv_idx[i] does not exist, sismu_multi_mv_idx[i] is inferred to be equal to 0. In the reconstructed base grid of the reference frame, the duplicate vertices have the same geometric position.

[0173] According to an exemplary embodiment, sismu_mv_pred_mode_group[subMeshID][g] specifies the method for predicting the motion vector associated with the vertices in the group with the index g of the current sub - mesh and the sub - mesh ID equal to subMeshID.

[0174] According to an exemplary embodiment, sismu_mv_residual_abs_gt0[subMeshID][g][k] indicates whether the k - th component of the motion vector prediction residual associated with the vertex with the index g in the current sub - mesh and the sub - mesh ID equal to subMeshID has an absolute value greater than zero (when it is 1) or an absolute value not greater than zero (when it is 0).

[0175] According to an exemplary embodiment, sismu_mv_residual_sign[subMeshID][g][k] indicates whether the k-th component of the motion vector prediction residual associated with the vertex with sub-mesh ID equal to subMeshID and having the index g of the current sub-mesh has a positive sign (when it is 1) or a negative sign (when it is 0). If sismu_mv_residual_sign[v][k] does not exist, sismu_mv_residual_sign[v][k] should be inferred to be equal to 1.

[0176] According to an exemplary embodiment, sismu_mv_residual_abs_gt1[subMeshID][k] indicates whether the k-th component of the motion vector prediction residual associated with the vertex with sub-mesh ID equal to subMeshID and having the index v of the current sub-mesh has an absolute value greater than 1 (when it is 1) or an absolute value not greater than 1 (when it is 0). If sismu_mv_residual_abs_gt1[v][k] does not exist, sismu_mv_residual_abs_gt1[v][k] should be inferred to be equal to 0.

[0177] According to an exemplary embodiment, sismu_mv_residual_abs_rem[subMeshID][v][k] indicates the absolute value of the k-th component of the motion vector prediction residual associated with the vertex with sub-mesh ID equal to subMeshID and having the index v of the current sub-mesh minus 2. If sismu_mv_residual_abs_rem[v][k] does not exist, sismu_mv_residual_abs_rem[v][k] should be inferred to be equal to 0.

[0178] According to an exemplary embodiment, the k-th component of the motion vector prediction residual VertexMotionVectorResiduals[v][k] associated with the vertex with sub-mesh ID equal to subMeshID and having the index v of the current sub-mesh is calculated as follows: VertexMotionVectorResiduals[v][k] = sismu_mv_residual_sign[v][k]? 1 : -1) * (sismu_mv_residua1_abs_gt0[v][k] + sismu_mv_residual_abs_gt1[v][k] + sismu_mv_residua|1_abs_rem[v][k])

[0179] Figure 18 An example 1800 of block partitioning by using a Quad Tree Binary Tree (QTBT) 1801 and a corresponding tree representation 1802 is shown. Solid lines indicate quadtree partitioning, and dashed lines indicate binary tree partitioning. In each partitioning (i.e., non-leaf) node of the binary tree, a flag is signaled to indicate which partitioning type (i.e., horizontal or vertical) is used, where 0 indicates horizontal partitioning and 1 indicates vertical partitioning. For quadtree partitioning, there is no need to indicate the partitioning type because the quadtree always partitions a block horizontally and vertically to produce 4 sub-blocks of equal size.

[0180] A Coding Tree Unit (CTU) is partitioned into Coding Units (CUs) by using a quadtree structure represented as a decoding tree to adapt to various local characteristics. A decision on whether to use inter-picture (temporal) prediction or intra-picture (spatial) prediction to decode a picture region is made at the CU level. Each CU can be further partitioned into one, two, or four Prediction Units (PUs) according to the PU partitioning type. Inside a PU, the same prediction process is applied, and relevant information is transmitted to the decoder based on the PU. After obtaining a residual block by applying the prediction process based on the PU partitioning type, the CU can be split into Transform Units (TUs) according to another quadtree structure such as the decoding tree of the CU.

[0181] According to an exemplary embodiment, there are lossless mesh decoding techniques and lossy mesh decoding techniques. A base mesh can be extracted as a subset of the original mesh, and the remaining vertices are encoded according to distance-based predictive displacement decoding.

[0182] The proposed methods can be used alone or in any combination in any order. The proposed methods can be used for any polygon mesh, but even so, only triangular meshes can be used for the demonstration of various embodiments. As described above, it will be assumed that the input mesh can contain one or more instances, a sub-mesh is a part of the input mesh with one or more instances, and multiple instances can be grouped to form a sub-mesh.

[0183] The above techniques can be implemented as computer software using computer-readable instructions and physically stored in one or more computer-readable media, or implemented by one or more specially configured hardware processors. For example, Figure 20 A computer system 2000 suitable for implementing certain embodiments of the disclosed subject matter is shown.

[0184] Computer software can be decoded using any suitable machine code or computer language, which can be subject to mechanisms such as assembly, compilation, linking, etc. to create code including instructions that can be directly executed by a computer central processing unit (CPU), Graphics Processing Unit (GPU), etc., or executed through interpretation, microcode execution, etc.

[0185] The instructions can be executed on various types of computers or their components, including, for example, personal computers, tablet computers, servers, smart phones, gaming devices, Internet of Things devices, etc.

[0186] Figure 20 The components shown for the computer system 2000 are exemplary in nature and are not intended to impose any limitations on the scope of use or functionality of the computer software implementing the present disclosure. The configuration of the components should also not be construed as having any dependencies or requirements related to any one component or combination of components shown in the exemplary embodiments of the computer system 2000.

[0187] The computer system 2000 may include certain human-machine interface input devices. Such human-machine interface input devices can respond to inputs made by one or more human users through, for example, tactile inputs (e.g., keystrokes, swipes, data glove movements), audio inputs (e.g., voice, taps), visual inputs (e.g., gestures), olfactory inputs (not depicted). The human-machine interface devices can also be used to capture certain media not necessarily directly related to conscious input by humans, such as audio (e.g., voice, music, ambient sound), images (e.g., scanned images, photographic images obtained from still image cameras), videos (e.g., two-dimensional videos, three-dimensional videos including stereoscopic videos).

[0188] The input human-machine interface devices may include one or more of the following (only one of each is depicted): keyboard 2001, mouse 2002, touchpad 2003, touch screen 2010, joystick 2005, microphone 2006, scanner 2008, camera device 2007.

[0189] The computer system 2000 may also include certain human-machine interface output devices. Such human-machine interface output devices can stimulate the senses of one or more human users through, for example, tactile output, sound, light, and smell / taste. Such human-machine interface output devices may include: tactile output devices (e.g., tactile feedback through the touch screen 2010, or joystick 2005, but there may also be tactile feedback devices that do not serve as input devices); audio output devices (e.g., speakers 2009, headphones (not depicted)); visual output devices (e.g., screen 2010, including CRT (Cathode Ray Tube) screens, LCD (Liquid Crystal Display) screens, plasma screens, OLED (Organic Light Emitting Diode) screens, each with or without touch screen input capabilities, each with or without tactile feedback capabilities - some of which may be able to output two-dimensional visual output or more than three-dimensional output through means such as stereoscopic image output; virtual reality glasses (not depicted); holographic displays and smoke cans (not depicted)); and printers (not depicted).

[0190] The computer system 2000 may also include human-accessible storage devices and their associated media, such as optical media including CD / DVD ROM (Read Only Memory) / RW 2020 with media such as CD / DVD 2011, thumb drives 2022, removable hard disk drives or solid state drives 2023, traditional magnetic media such as tapes and floppy disks (not depicted), devices based on dedicated ROM / ASIC (Application Specific Integrated Circuit) / PLD (Programmable Logic Device) such as security dongles (not depicted), etc.

[0191] Those skilled in the art should also understand that the term "computer-readable medium" used in connection with the currently disclosed subject matter does not include transmission media, carrier waves, or other transient signals.

[0192] The computer system 2000 may also include an interface 2099 to one or more communication networks 2098. The network 2098 may be, for example, wireless, wired, or optical. The network 2098 may also be local area, wide area, metropolitan area, vehicle and industrial, real-time, delay-tolerant, etc. Examples of the network 2098 include: local area networks such as Ethernet; wireless LAN (Local Area Network, LAN); cellular networks including GSM (Global System for Mobile Communications, GSM), 3G (the Third Generation, 3G), 4G (the Fourth Generation, 4G), 5G (the Fifth Generation, 5G), LTE (Long Term Evolution, LTE), etc.; TV wired or wireless wide area digital networks including cable TV, satellite TV, and terrestrial broadcast TV; vehicle and industrial networks including CANBus (Controller Area Network Bus, CANBus), etc. Certain networks 2098 typically require an external network interface adapter attached to certain common data ports or peripheral buses (2050 and 2051) (such as, for example, the USB (Universal Serial Bus, USB) port of the computer system 2000); other networks are typically integrated into the core of the computer system 2000 by attaching to the system bus as described below (for example, an Ethernet interface in a PC computer system or a cellular network interface in a smart phone computer system). Using any of these networks 2098, the computer system 2000 can communicate with other entities. Such communication can be unidirectional receive-only (e.g., broadcast TV), unidirectional transmit-only (e.g., CANbus to certain CANbus devices), or bidirectional, for example, to other computer systems using local area digital networks or wide area digital networks. Certain protocols and protocol stacks can be used on each of these networks and network interfaces as described above.

[0193] The above-mentioned human-machine interface devices, human-accessible storage devices, and network interfaces can be attached to the core 2040 of the computer system 2000.

[0194] The core 2040 may include one or more central processing units (CPUs) 2041, a graphics processing unit (GPU) 2042, a graphics adapter 2017, a dedicated programmable processing unit in the form of field programmable gate areas (FPGAs) 2043, a hardware accelerator 2044 for certain tasks, etc. These devices, together with a read-only memory (ROM) 2045, a random access memory 2046, and an internal mass storage device such as an internal hard disk drive that is not accessible to users, a solid-state drive (SSD), etc. 2047, can be connected via a system bus 2048. In some computer systems, the system bus 2048 may be accessible in the form of one or more physical plugs to allow expansion by attaching additional CPUs, GPUs, etc. Peripheral devices can be attached directly or via a peripheral bus 2049 to the system bus 2048 of the core. The architecture of the peripheral bus includes PCI (Peripheral Component Interconnect / Interface, PCI), USB, etc.

[0195] The CPU 2041, GPU 2042, FPGA 2043, and accelerator 2044 can execute certain instructions that, when combined, can constitute the computer code mentioned above. The computer code can be stored in the ROM 2045 or a random access memory (RAM) 2046. Transient data can also be stored in the RAM 2046, while permanent data can be stored in, for example, the internal mass storage device 2047. Fast storage and retrieval of any storage device in the memory device can be achieved by using a cache memory that can be closely associated with one or more CPUs 2041, GPUs 2042, the mass storage device 2047, the ROM 2045, the RAM 2046, etc.

[0196] A computer-readable medium can have computer code thereon for performing various computer-implemented operations. The medium and the computer code can be media and computer code that are specially designed and constructed for the purposes of this disclosure, or the medium and the computer code can be of the types that are known and available to those skilled in the art of computer software.

[0197] By way of example and not limitation, a computer system having architecture 2000 and in particular core 2040 can provide functionality due to software executed by a processor (including a CPU, GPU, FPGA, accelerator, etc.) included in one or more tangible computer-readable media. Such computer-readable media can be media associated with a user-accessible mass storage device as introduced above, as well as certain storage devices of core 2040 having a non-transitory nature such as on-core mass storage 2047 or ROM 2045. The software implementing various embodiments of the present disclosure can be stored in such devices and executed by core 2040. Depending on specific needs, the computer-readable media can include one or more memory devices or chips. The software can cause core 2040 and in particular the processors therein (including CPU, GPU, FPGA, etc.) to perform specific processes or specific portions of specific processes described herein, including defining data structures stored in RAM 2046 and modifying such data structures according to processes defined by the software. Additionally or alternatively, the computer system can provide functionality due to being logically hardwired or otherwise implemented in circuitry (e.g., accelerator 2044), which can operate in place of or in conjunction with the software to perform specific processes or specific portions of specific processes described herein. In appropriate instances, references to software can include logic, and references to logic can also include software. In appropriate instances, references to computer-readable media can include circuitry (e.g., an integrated circuit (IC)) storing software for execution, circuitry implementing logic for execution, or both. The present disclosure encompasses any suitable combination of hardware and software.

[0198] Although the present disclosure has described several exemplary embodiments, there are changes, permutations, and various alternative equivalents that fall within the scope of the present disclosure. Accordingly, it will be recognized that those skilled in the art will be able to envision many systems and methods that, although not explicitly shown or described herein, embody the principles of the present disclosure and are thus within the spirit and scope of the present disclosure.

Claims

1. A method for video decoding, the method being performed by at least one processor and comprising: obtaining a grid of encoded volumetric data representing at least one three-dimensional (3D) visual content from the decoded bitstream; determining a spatial grouping syntax that signals a decoding order of vertices obtained using the encoded volume data, wherein at least two of the vertices are within a threshold distance of each other and are not edge-connected to each other; as well as The encoded volume data is decoded by predicting the at least two of the vertices as a group based on the spatial grouping syntax.

2. The method according to claim 1, in, A third vertex in the group is within a threshold distance from any of the at least two of the vertices.

3. The method according to claim 2, in, The third vertex edge is connected to one vertex among the at least two of the vertices.

4. The method according to claim 2, in, The third vertex is not edge-connected to any vertex of the at least two of the vertices.

5. The method according to claim 1, in, Decoding the encoded volume data includes predicting a plurality of groups of vertices other than the group, and Wherein, at least one vertex in each of the plurality of groups is not connected to other vertices in each of the plurality of groups by an edge.

6. The method according to claim 5, in, Each of the vertices in each of the plurality of groups is within a threshold distance of each other in each of the plurality of groups.

7. The method according to claim 1, in, The spatial grouping syntax is a base grid inter-frame sub-grid data unit syntax.

8. The method according to claim 7, in, The set includes an integer number K of vertices, and Wherein, the base grid inter-frame sub-grid data unit syntax is obtained using the encoded volume data, and the integer K is notified by a signal.

9. The method according to claim 3, in, The integer K is 16.

10. The method according to claim 1, in, The value of the spatial grouping syntax is based on whether a first coding cost of coding the motion vectors of all vertices of the group is determined to be less than or equal to a second coding cost of coding the estimated residuals of all vertices of the group.

11. A device for video decoding, the device comprising: at least one memory configured to store computer program code; at least one processor configured to access the computer program code and to operate as directed by the computer program code, the computer program code comprising: obtaining code configured to cause the at least one processor to obtain a grid of encoded volumetric data representing at least one three-dimensional (3D) visual content from a decoded bitstream; determining code configured to cause the at least one processor to determine a spatial grouping syntax that signals a decoding order of vertices obtained using the encoded volume data, wherein at least two of the vertices are within a threshold distance of each other and are not edge-connected to each other; and A decoding code is configured to cause the at least one processor to decode the encoded volume data by predicting the at least two of the vertices as a group based on the spatial grouping grammar.

12. The device according to claim 11, in, A third vertex in the group is within a threshold distance from any of the at least two of the vertices.

13. The device according to claim 12, in, The third vertex edge is connected to one vertex among the at least two of the vertices.

14. The device according to claim 12, in, The third vertex is not edge-connected to any vertex of the at least two of the vertices.

15. The device according to claim 11, in, Decoding the encoded volume data includes predicting a plurality of groups of vertices other than the group, and Wherein, at least one vertex in each of the plurality of groups is not connected to other vertices in each of the plurality of groups by an edge.

16. The device according to claim 15, in, Each of the vertices in each of the plurality of groups is within a threshold distance of each other in each of the plurality of groups.

17. The device according to claim 11, in, The spatial grouping syntax is a base grid inter-frame sub-grid data unit syntax.

18. The device according to claim 17, in, The set includes an integer number K of vertices, and Wherein, the base grid inter-frame sub-grid data unit syntax is obtained using the encoded volume data, and the integer K is notified by a signal.

19. The device according to claim 3, in, The integer K is 16.

20. A non-transitory computer readable medium storing a program, wherein the program causes a computer to perform the following operations: obtaining a grid of encoded volumetric data representing at least one three-dimensional (3D) visual content from the decoded bitstream; determining a spatial grouping syntax that signals a decoding order of vertices obtained using the encoded volume data, wherein At least two of the vertices are within a threshold distance of each other and are not edge-connected to each other; as well as The encoded volume data is decoded by predicting the at least two of the vertices as a group based on the spatial grouping syntax.

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