WO2023155794A1 - 编码、解码方法、装置及设备 - Google Patents

编码、解码方法、装置及设备 Download PDF

Info

Publication number
WO2023155794A1
WO2023155794A1 PCT/CN2023/076113 CN2023076113W WO2023155794A1 WO 2023155794 A1 WO2023155794 A1 WO 2023155794A1 CN 2023076113 W CN2023076113 W CN 2023076113W WO 2023155794 A1 WO2023155794 A1 WO 2023155794A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
precision
geometric
geometric information
target
Prior art date
Application number
PCT/CN2023/076113
Other languages
English (en)
French (fr)
Inventor
邹文杰
张伟
杨付正
吕卓逸
Original Assignee
维沃移动通信有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 维沃移动通信有限公司 filed Critical 维沃移动通信有限公司
Publication of WO2023155794A1 publication Critical patent/WO2023155794A1/zh

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/001—Model-based coding, e.g. wire frame
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G06T17/205—Re-meshing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks

Definitions

  • the present application belongs to the technical field of encoding and decoding, and in particular relates to an encoding and decoding method, device and equipment.
  • Three-dimensional mesh can be considered as the most popular representation method of three-dimensional model in the past years, and it plays an important role in many applications. Its representation is simple, so it is integrated into the Graphics Processing Unit (GPU) of computers, tablets and smartphones with a large number of hardware algorithms, dedicated to rendering 3D grids.
  • GPU Graphics Processing Unit
  • the 3D mesh geometry information can be compressed with point cloud compression algorithms.
  • the vertices of the 3D mesh have the characteristics of sparser and more uneven spatial distribution.
  • the point cloud compression algorithm is used to compress the geometric information of the 3D mesh model, and the compression efficiency is not high.
  • Embodiments of the present application provide an encoding and decoding method, device, and equipment, which can solve the problem of low compression efficiency in the prior art compression methods for three-dimensional grid geometric information.
  • an encoding method including:
  • the encoding end quantifies the geometric information of the target three-dimensional grid to obtain first information, and the first information includes at least one of the following: first-precision geometric information, second-precision geometric information, and supplementary point information;
  • the encoding end encodes the first information
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points It is the information of points that need additional processing generated during the quantization process.
  • an encoding device including:
  • the first acquisition module is used to quantify the geometric information of the target three-dimensional grid, and acquire the first information, the first information includes at least one of the following: first precision geometric information, second precision geometric information, and supplementary point information ;
  • an encoding module configured to encode the first information
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points It is the information of points that need additional processing generated during the quantization process.
  • a decoding method including:
  • the decoding end decomposes the obtained code stream to obtain first information, and the first information includes at least one of the following: first-precision geometric information, second-precision geometric information, and supplementary point information;
  • the decoding end performs inverse quantization according to the first information to obtain the target three-dimensional grid
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points It is the information of points that need additional processing generated during the quantization process.
  • a decoding device including:
  • the second acquisition module is configured to decompose the acquired code stream and acquire first information, where the first information includes at least one of the following items: first-precision geometric information, second-precision geometric information, and supplementary point information;
  • the third acquisition module is used to perform inverse quantization according to the first information, and acquire the target three-dimensional grid;
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points It is the information of points that need additional processing generated during the quantization process.
  • an encoding device including a processor and a memory
  • the memory stores programs or instructions that can run on the processor, and when the programs or instructions are executed by the processor, the first The steps of the method described in the aspect.
  • an encoding device including a processor and a communication interface, wherein the processor is used to quantify the geometric information of the target three-dimensional grid and obtain first information, and the first information includes at least one of the following Item: first-precision geometric information, second-precision geometric information, and supplementary point information; encode the first information;
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points for the quantification process Information about points that require additional processing generated in .
  • a decoding device including a processor and a memory
  • the memory stores programs or instructions that can run on the processor, and when the programs or instructions are executed by the processor, the third The steps of the method described in the aspect.
  • a decoding device including a processor and a communication interface, wherein the processor is configured to decompose the obtained code stream to obtain first information, and the first information includes at least one of the following: First-precision geometric information, second-precision geometric information, and supplementary point information; perform inverse quantization according to the first information to obtain a target three-dimensional grid;
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points It is the information of points that need additional processing generated during the quantization process.
  • a ninth aspect provides a communication system, including: an encoding device and a decoding device, the encoding device can be used to perform the steps of the method described in the first aspect, and the decoding device can be used to perform the steps of the method described in the third aspect steps of the method.
  • a readable storage medium is provided, and a program or an instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented, or the steps of the method as described in the first aspect are implemented, or the The steps of the method described in the third aspect.
  • a chip in an eleventh aspect, includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run a program or an instruction to implement the method described in the first aspect. method, or implement the method as described in the third aspect.
  • a computer program product is provided, the computer program product is stored in a storage medium, and the computer program product is executed by at least one processor to implement the steps of the method described in the first aspect, or Implement the method as described in the third aspect.
  • a communication device configured to execute the steps of the method described in the first aspect, or implement the method described in the third aspect.
  • the geometric information of the target three-dimensional grid by quantifying the geometric information of the target three-dimensional grid, at least one of the first-precision geometric information, the second-precision geometric information, and the supplementary point information is obtained, and the above-mentioned information is encoded, by The geometric information of the three-dimensional grid is quantified, so that the distance between vertices of the quantized three-dimensional mesh is reduced, and then the distance between two-dimensional vertices after projection is reduced, so as to improve the compression efficiency of the geometric information of the three-dimensional mesh.
  • FIG. 1 is a schematic flow chart of an encoding method in an embodiment of the present application
  • Fig. 2 is a schematic diagram of a grid-based fine division process
  • Fig. 3 is a schematic diagram of eight directions of sheet (Patch) arrangement
  • Fig. 4 is a schematic diagram of the encoding process of high-precision geometric information
  • Fig. 5 is a schematic diagram of an original film (raw patch).
  • Fig. 6 is a schematic diagram of a video-based three-dimensional mesh geometric information encoding framework
  • FIG. 7 is a block diagram of an encoding device according to an embodiment of the present application.
  • FIG. 8 is a schematic structural diagram of an encoding device according to an embodiment of the present application.
  • FIG. 9 is a schematic flowchart of a decoding method according to an embodiment of the present application.
  • Fig. 10 is a block diagram of geometric information reconstruction
  • Fig. 11 is a schematic diagram of a video-based three-dimensional mesh geometric information decoding framework
  • FIG. 12 is a block diagram of a decoding device according to an embodiment of the present application.
  • FIG. 13 is a schematic structural diagram of a communication device according to an embodiment of the present application.
  • first, second and the like in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific sequence or sequence. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application are capable of operation in sequences other than those illustrated or described herein and that "first" and “second” distinguish objects. It is usually one category, and the number of objects is not limited. For example, there may be one or more first objects.
  • “and/or” in the description and claims means at least one of the connected objects, and the character “/” generally means that the related objects are an "or” relationship.
  • LTE Long Term Evolution
  • LTE-Advanced LTE-Advanced
  • LTE-A Long Term Evolution-Advanced
  • CDMA Code Division Multiple Access
  • TDMA Time Division Multiple Access
  • FDMA Frequency Division Multiple Access
  • OFDMA Orthogonal Frequency Division Multiple Access
  • SC-FDMA Single-carrier Frequency Division Multiple Access
  • system and “network” in the embodiments of the present application are often used interchangeably, and the described technology can be used for the above-mentioned system and radio technology, and can also be used for other systems and radio technologies.
  • the following description describes the New Radio (New Radio, NR) system for the purpose of example, And NR terms are used in most of the following descriptions, but these technologies can also be applied to applications other than NR system applications, such as 6th Generation ( 6th Generation, 6G) communication systems.
  • 6th Generation 6th Generation
  • the embodiment of this application provides an encoding method, including:
  • Step 101 the encoding end quantifies the geometric information of the target three-dimensional grid to obtain the first information
  • the target 3D grid mentioned in this application can be understood as a 3D grid corresponding to any video frame, and the geometric information of the target 3D grid can be understood as the coordinates of vertices in the 3D grid, which are usually Refers to three-dimensional coordinates.
  • the first information includes at least one of the following:
  • the first-precision geometric information can be understood as low-precision geometric information, that is, the low-precision geometric information refers to the geometric information after quantization of the target 3D mesh, that is, the 3D geometry information of each vertex included in the quantized target 3D mesh. coordinate information.
  • the second-precision geometric information can be understood as high-precision geometric information, and the high-precision geometric information can be regarded as geometric information lost in the quantization process, that is, lost three-dimensional coordinate information.
  • the information of supplementary points refers to the information of points that need additional processing generated during the quantization process, that is, the supplementary points are points that require additional processing generated during the quantization process, for example, the coordinate positions overlap Repeated points, etc., by processing the repeated points, the vertices whose coordinate positions overlap during quantization can be restored to their original positions after dequantization.
  • the supplementary information includes at least one of the following:
  • the index it can be known which points in the quantized grid identify multiple points in the 3D grid before quantization, that is, multiple points in the 3D grid before quantization are being quantized After overlapping together, the low-precision geometric information of the supplementary point can be determined through the index of the vertex.
  • the third-precision geometric information can be understood as the low-precision geometric information of the supplementary point, that is, the quantized three-dimensional coordinate information of the supplementary point.
  • the fourth precision geometric information can be understood as the high-precision geometric information of the supplementary point, that is, the three-dimensional coordinate information of the supplementary point lost during quantization.
  • the quantized hidden points can be determined through A131 and A133 or through A132 and A133.
  • Step 102 the encoding end encodes the first information
  • the first information can be encoded to obtain the corresponding sub-code stream; the above solution, by quantizing the geometric information of the three-dimensional grid, makes the quantized three-dimensional grid The distance between the vertices is reduced, thereby reducing the distance between the two-dimensional vertices after projection, so as to improve the compression efficiency of the geometric information of the three-dimensional mesh.
  • step 101 is:
  • the encoding end quantizes each vertex in the target three-dimensional mesh according to the quantization parameter of each component, and acquires first-precision geometric information.
  • the quantization parameters of each component can be flexibly set according to the usage requirements; the quantization parameters mainly include the quantization parameters of the X-direction, Y-direction and Z-direction.
  • step 101 For quantization with low precision requirements, only low-precision geometric information can be retained after quantization; for quantization with high precision requirements, not only low-precision geometric information, but also high-precision geometric information needs to be recorded during quantization , so as to achieve accurate grid recovery during decoding, that is to say, the specific implementation of the above-mentioned step 101 should also include:
  • the encoding end acquires second-precision geometric information according to the first-precision geometric information and the quantization parameter of each component.
  • the f1 function in formula one to formula three is a quantization function
  • the input of the quantization function is the coordinate of a certain dimension and the quantization parameter of this dimension
  • the output is the coordinate value after quantization
  • the f2 function input in formula four to formula six It is the original coordinate value, the quantized coordinate value and the quantization parameter of this dimension, and the output is a high-precision coordinate value.
  • the f 1 function can be calculated in a variety of ways, and a more general calculation method is shown in formula 7 to formula 9, which is calculated by dividing the original coordinates of each dimension by the quantization parameter of this dimension.
  • / is a division operator, and the result of the division operation can be rounded in different ways, such as rounding, rounding down, rounding up, etc.
  • the f 1 function and the f 2 function can be implemented using bit operations, such as formula 13 to formula 18:
  • Formula 13: x l x>>log 2 QP x ;
  • Formula 14: y l y>>log 2 QP y ;
  • Formula fifteen: z l z >> log 2 QP z ;
  • Formula sixteen: x h x&(QP x -1);
  • Formula seventeen: y h y&(QP y -1);
  • Formula eighteen: z h z&(QP z -1);
  • the quantization parameters QP x , QP y and QP z can be flexibly set.
  • the quantization parameters of different components are not necessarily equal, and the correlation between the quantization parameters of different components can be used to establish the relationship between QP x , QP y and QP z , and set different quantization parameters for different components;
  • different spatial The quantization parameters of the regions are not necessarily equal, and the quantization parameters can be adaptively set according to the sparseness of the vertex distribution in the local region.
  • the high-precision geometric information includes detailed information of the outline of the three-dimensional mesh.
  • the high-precision geometric information (x h , y h , z h ) can be further processed.
  • the 3D mesh model the importance of high-precision geometric information of vertices in different regions is different. For areas where vertices are sparsely distributed, the distortion of high-precision geometric information will not have a great impact on the visual effect of the 3D mesh.
  • step 101 in the process of quantization, there may be multiple points that overlap to the same position after quantization, that is to say, in this case, the specific implementation of the above-mentioned step 101 should also include:
  • the encoding end determines supplementary point information according to the geometric information of the target three-dimensional grid and the first precision geometric information.
  • the points where the low-precision geometric information is repeated are used as supplementary points and encoded separately.
  • the geometric information of the supplementary points can also be divided into low-precision geometric information and high-precision geometric information. According to the requirements of the application for compression distortion, you can choose to keep all the supplementary points or only a part of them.
  • the high-precision geometric information of the supplementary points can also be further quantified, or only the high-precision geometric information of some points can be retained.
  • the first information needs to be encoded to obtain the final code stream.
  • the first The specific implementation process of information encoding includes:
  • Step 1021 the encoding end processes the first information to obtain second information, and the second information includes at least one of an occupancy map and a geometric map;
  • Step 1022 the encoding end encodes the second information.
  • step 1021 describes the implementation of step 1021 from the perspective of different information. The procedure is explained below.
  • the first information includes the first precision geometry information
  • step 1021 includes:
  • Step 10211 the encoder divides the first-precision geometric information into three-dimensional slices
  • the low-precision geometric information is mainly divided into patches (Patch) to obtain multiple 3D patches; the specific implementation of this step is: the encoding end determines each a projection plane of vertices; the encoding end slices the vertices contained in the first-precision geometric information according to the projection plane; the encoding end clusters the vertices contained in the first-precision geometric information to obtain After dividing each slice.
  • the process of patch division mainly includes: first estimate the normal vector of each vertex, and select the candidate projection plane with the smallest angle between the plane normal vector and the vertex normal vector as the projection plane of the vertex; then, according to the projection The plane initially divides the vertices, and forms the patch with the same and connected vertices on the projection plane; finally, the fine partition algorithm is used to optimize the clustering results to obtain the final 3D patch.
  • the tangent plane and its corresponding normal are defined based on each point's nearest neighbor vertex m at a predefined search distance.
  • the KD tree is used to separate the data and to find neighboring points near the point p i , the center of gravity of the set Used to define normals.
  • the calculation method of the center of gravity c is as follows: Formula nineteen:
  • the projection plane of each vertex is initially selected.
  • the normal vector of the candidate projection plane is Select the plane whose normal vector direction is closest to the vertex normal vector direction as the projection plane of the vertex.
  • the calculation process of plane selection is shown in formula 21: Formula twenty one:
  • the fine division process can use a grid-based algorithm to reduce the time complexity of the algorithm.
  • the grid-based fine division algorithm flow is shown in Figure 2, specifically including:
  • Step S201 divide the (x, y, z) geometric coordinate space into voxels.
  • Step S202 searching for a filled voxel, where a filled voxel refers to a voxel that contains at least one point in the grid.
  • Step S203 calculating the smoothing score of each filling voxel on each projection plane, denoted as voxScoreSmooth, the voxel smoothing score of a voxel on a certain projection plane is the number of points gathered to the projection plane through the initial segmentation process.
  • Step S204 use the KD-Tree partition to find adjacent filled voxels, denoted as nnFilledVoxels, that is, the nearest filled voxels of each filled voxel (within the search radius and/or limited to the maximum number of adjacent voxels).
  • Step S205 using the voxel smoothing scores of adjacent filling voxels on each projection plane to calculate the smoothing score (scoreSmooth) of each filling voxel, the calculation process is shown in formula 22:
  • Formula 22
  • Step S206 use the normal vector of the vertex and the normal vector of the candidate projection plane to calculate the normal score, which is recorded as scoreNormal, and the calculation process is shown in formula 23:
  • p is the index of the projection plane and i is the index of the vertex.
  • Step S207 using scoreSmooth and scoreNormal to calculate the final score of each voxel on each projection plane, the calculation process is shown in formula 24: Formula twenty-four:
  • i is the vertex index
  • p is the index of the projection plane
  • v is the voxel index where the vertex i is located.
  • Step S208 use the scores in step 207 to cluster the vertices to obtain finely divided patches.
  • Step 10212 the encoding end performs two-dimensional projection on the divided three-dimensional slices to obtain two-dimensional slices;
  • this process is to project the 3D patch onto a two-dimensional plane to obtain a two-dimensional patch (2D patch).
  • Step 10213 the encoder packs the two-dimensional slices to obtain two-dimensional image information
  • this step implements patch packing.
  • the purpose of patch packing is to arrange 2D patches on a two-dimensional image.
  • the basic principle of patch packing is to arrange patches on a two-dimensional image without overlapping or The non-pixel parts of the patch are partially overlapped and arranged on the two-dimensional image.
  • Through algorithms such as priority arrangement and time-domain consistent arrangement the patches are arranged more closely and have time-domain consistency to improve coding performance.
  • the minimum block size defining a patch arrangement is T, which specifies the minimum distance between different patches placed on this 2D grid.
  • each patch occupies an area consisting of an integer number of TxT blocks.
  • at least one TxT block distance is required between adjacent patches.
  • the patch can choose a variety of different arrangement directions.
  • eight different arrangement directions can be used, as shown in FIG. 3 , including 0 degree, 180 degree, 90 degree, 270 degree and mirror images of the first four directions.
  • a patch arrangement method with temporal consistency is adopted.
  • a group of frames Group of frame, GOF
  • all patches of the first frame are ordered from large to small in order of order.
  • the temporal consistency algorithm is used to adjust the arrangement order of the patches.
  • the patch information can be obtained according to the information in the process of obtaining the two-dimensional image information, and then the patch information can be encoded to obtain the patch information sub-stream;
  • the patch information records the operation information of each step in the process of obtaining a two-dimensional image , that is, the patch information includes: patch division information, patch projection plane information, and patch packing location information.
  • Step 10214 the encoding end obtains a first-precision occupancy map and a first-precision geometric map according to the two-dimensional image information
  • the main steps are: use the patch arrangement information obtained by patch packing, set the positions of vertices in the two-dimensional image to 1, and set the rest positions to 0 to obtain the occupancy map.
  • the process of obtaining the geometric map it is mainly: in the process of obtaining the 2D patch through projection, the distance from each vertex to the projection plane is saved. This distance is called depth.
  • the low-precision geometric map compression part is to convert each The depth value of the vertex is arranged to the position of the vertex in the occupancy map to obtain a low-precision geometry map.
  • the first information includes the second precision geometric information
  • step 1021 includes:
  • Step 10215 the encoding end obtains the arrangement order of the vertices contained in the first-precision geometric information
  • Step 10216 the encoder arranges the second-precision geometric information corresponding to the vertices included in the first-precision geometric information in the two-dimensional image, and generates a second-precision geometric map.
  • the high-precision geometric information adopts the arrangement of the original patch (raw patch), and the high-precision geometric information corresponding to the vertices in the low-precision geometric map is arranged in the two-dimensional image to obtain the raw patch, so as to generate high-precision Precision geometry. It is mainly divided into three steps, as shown in Figure 4, including:
  • Step 401 obtain the arrangement order of the vertices, scan the low-precision geometric graph from left to right row by row, and use the scanning order of each vertex as the arrangement order of the vertices in the raw patch.
  • Step 402 generate a raw patch.
  • the raw patch is a rectangular patch formed by arranging the three-dimensional coordinates of vertices line by line as shown in Figure 5. According to the arrangement order of the vertices obtained in the first step, arrange the high-precision geometric information of the vertices in order to obtain the high-precision geometric information raw patch.
  • Step 403 placing the high-precision geometric information in a two-dimensional image to generate a high-precision geometric map.
  • the encoding end when encoding the geometry sub-stream, will encode the first-precision geometry and the second-precision geometry to obtain the geometry sub-stream.
  • the first information includes supplementary information
  • step 1021 includes:
  • Step 10217 the encoding end arranges the third precision geometric information of the supplementary points into the first original slice
  • Step 10218 the encoding end, according to the same arrangement order as the first original slice, puts the first slice of the supplementary point Four-precision geometric information is arranged into a second original slice;
  • Step 10219 the encoding end compresses the first original slice and the second original slice, and obtains a geometric map of supplementary points.
  • the geometric information of the supplementary points is divided into low-precision parts and high-precision parts, respectively, and is encoded.
  • one method is to encode the values in the raw patch by run-length encoding, entropy encoding, etc.
  • the other method is to add the supplementary point low-precision raw patch to the blank area in the low-precision geometric map, and add the supplementary point high-precision
  • the raw patch adds blank areas in the high-precision geometry map to obtain a geometry map of supplementary points.
  • the 3D grid which may produce three parts: low-precision geometric information, high-precision geometric information and supplementary point information; for low-precision geometric Information, use the projection method to divide the patch, arrange the patch to generate the patch sequence compression information (patch division information), occupancy map and low-precision geometric map; for the possible high-precision geometric information, the raw patch arrangement can be used to generate High-precision geometric map (it should be explained here that high-precision geometric map can be separately encoded into one code stream, or high-precision geometric map can be filled into low-precision geometric map, and low-precision geometric map can be encoded to obtain one stream code stream); for the possible supplementary points, the geometric information of the supplementary points can be divided into low-precision parts and high-precision parts, and the raw patch is arranged separately, and encoded into a code stream separately, or the raw patch is added to the geometric map; Finally, encode the patch sequence compression information, occupancy map, and geometric map
  • this application provides an implementation method of how to encode the geometric information of the 3D grid. By quantizing the geometric information of the 3D grid and encoding the quantized information with different precisions, it can Improve the compression efficiency of 3D mesh geometry information.
  • the encoding method provided in the embodiment of the present application may be executed by an encoding device.
  • the encoding device provided in the embodiment of the present application is described by taking the encoding device executing the encoding method as an example.
  • an encoding device 700 including:
  • the first acquisition module 701 is configured to quantify the geometric information of the target three-dimensional grid, and acquire the first information, the first information including at least one of the following: first precision geometric information, second precision geometric information, supplementary points information;
  • An encoding module 702 configured to encode the first information
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points It is the information of points that need additional processing generated during the quantization process.
  • the first acquiring module 701 is configured to:
  • each vertex in the target 3D grid is quantized to obtain the first precise degree geometry information
  • the first acquiring module 701 is also configured to:
  • the first acquiring module 701 is also configured to:
  • the supplementary information includes at least one of the following:
  • the third precision geometric information of the supplementary point is the quantized three-dimensional coordinate information of the supplementary point;
  • the fourth precision geometric information of the supplementary point is the three-dimensional coordinate information lost during the quantization process of the supplementary point.
  • the encoding module 702 includes:
  • a first acquisition unit configured to process the first information and acquire second information, where the second information includes at least one of an occupancy map and a geometric map;
  • An encoding unit configured to encode the second information.
  • the first acquiring unit is configured to:
  • a first-precision occupancy map and a first-precision geometric map are acquired.
  • the first obtaining unit is further configured to:
  • the first acquiring unit is configured to:
  • the second-precision geometric information corresponding to the vertices included in the first-precision geometric information is arranged in the two-dimensional image to generate a second-precision geometric map.
  • the encoding unit is configured to:
  • the first acquiring unit is configured to:
  • This device embodiment corresponds to the above-mentioned encoding method embodiment, and each implementation process and implementation mode of the above-mentioned method embodiment can be applied to this device embodiment, and can achieve the same technical effect.
  • the embodiment of the present application also provides an encoding device.
  • the encoding device 800 includes: a processor 801 , a network interface 802 and a memory 803 .
  • the network interface 802 is, for example, a common public radio interface (Common Public Radio Interface, CPRI).
  • CPRI Common Public Radio Interface
  • the encoding device 800 of the embodiment of the present application also includes: instructions or programs stored in the memory 803 and operable on the processor 801, and the processor 801 calls the instructions or programs in the memory 803 to execute the modules shown in FIG. 7 To avoid duplication, the method of implementation and to achieve the same technical effect will not be repeated here.
  • the embodiment of the present application also provides a decoding method, including:
  • Step 901 the decoding end decomposes the obtained code stream to obtain the first information
  • the first information includes at least one of the following: first-precision geometric information, second-precision geometric information, and supplementary point information;
  • Step 902 the decoder performs inverse quantization according to the first information to obtain the target three-dimensional grid
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points It is the information of points that need additional processing generated during the quantization process.
  • step 901 includes:
  • the decoding end obtains a target sub-code stream according to the obtained code stream, and the target sub-code stream includes: a slice information sub-code stream, a placeholder image sub-code stream and a geometric graph sub-code stream;
  • the decoding end obtains second information according to the target sub-code stream, and the second information includes: at least one of a placeholder map and a geometric map;
  • the decoding end obtains the first information according to the second information.
  • the acquiring the first information according to the second information includes:
  • the decoding end obtains two-dimensional image information according to the occupancy map of the first precision and the geometric map of the first precision;
  • the decoding end obtains a two-dimensional slice according to the two-dimensional image information
  • the decoding end performs three-dimensional inverse projection on the two-dimensional slice according to the slice information corresponding to the slice information sub-stream to obtain a three-dimensional slice;
  • the decoding end obtains first-precision geometric information according to the 3D slice.
  • the acquiring the first information according to the second information includes:
  • the decoding end obtains the geometric information of the second precision according to the geometric map of the second precision.
  • the acquiring the first information according to the second information includes:
  • the decoding end determines the first primitive corresponding to the third-precision geometric information of the supplementary point according to the geometric map of the supplementary point The first slice and the second original slice corresponding to the fourth precision geometric information of the supplementary point;
  • the decoding end determines information of supplementary points according to the first original slice and the second original slice.
  • the geometric information of the supplementary points is divided into low-precision parts and high-precision parts, respectively, for decoding.
  • the geometry of the supplementary points is decompressed.
  • Various decompression methods can be used. Among them, one method is to perform run-length decoding and entropy decoding on the geometric graph, and the other method is to extract the low-precision raw patch of the supplementary point from the low-precision geometric graph, and extract the high-precision raw patch of the supplementary point from the high-precision Take it out of the geometry.
  • the specific order is decoding
  • the end obtains it by analyzing the code stream, that is, the order in which the encoding end uses to generate the supplementary low-precision raw patch and the supplementary high-precision raw patch will inform the decoding end through the code stream.
  • the performing inverse quantization according to the first information to obtain the target three-dimensional grid includes:
  • the decoding end determines the coordinates of each vertex in the first-precision geometric information according to the first-precision geometric information and the quantization parameters of each component.
  • the performing inverse quantization according to the first information to obtain the target three-dimensional grid further includes:
  • the decoding end determines the target 3D grid according to the coordinates of each vertex in the target 3D grid and the second precision geometric information.
  • the geometric information reconstruction process in the embodiment of the present application is a process of reconstructing a three-dimensional geometric model by using information such as patch information, occupancy maps, low-precision geometric maps, and high-precision geometric maps.
  • the specific process is shown in Figure 10, mainly including the following four steps:
  • Step 1001 obtain 2D patch
  • obtaining a 2D patch refers to segmenting the occupancy information and depth information of the 2D patch from the occupancy map and the geometry map by using the patch information.
  • the patch information contains the position and size of the bounding box of each 2D patch in the occupancy map and the low-precision geometry map.
  • the occupancy information and the size of the 2D patch can be directly obtained by using the patch information, occupancy map, and low-precision geometry map.
  • Low precision geometry information For high-precision geometric information, the high-precision geometric information in the high-precision raw patch is corresponding to the vertices of the low-precision geometric diagram by using the vertex scanning order of the low-precision geometric diagram, so as to obtain the high-precision geometric information of the 2D patch.
  • the geometric information of the supplementary point the low-precision raw patch and high-precision raw patch of the supplementary point can be directly decoded to obtain the low-precision geometric information and high-precision geometric information of the supplementary point.
  • Step 1002 rebuilding the 3D patch
  • reconstructing a 3D patch refers to reconstructing the vertices in the 2D patch into a low-precision 3D patch by using the occupancy information and low-precision geometric information in the 2D patch.
  • the occupancy information of the 2D patch contains the position of the vertex in the local coordinate system of the patch projection plane relative to the coordinate origin, and the depth information contains the depth value of the vertex in the normal direction of the projection plane. Therefore, the 2D patch can be reconstructed into a low-precision 3D patch in the local coordinate system by using the occupancy information and depth information.
  • Step 1003 rebuilding a low-precision geometric model
  • reconstructing a low-precision geometric model refers to reconstructing the entire low-precision 3D patch using the reconstructed low-precision 3D patch.
  • 3D geometric model The patch information includes the conversion relationship of the 3D patch from the local coordinate system to the global coordinate system of the 3D geometric model. Using the coordinate conversion relationship, all 3D patches are converted to the global coordinate system to obtain a low-precision 3D geometric model.
  • the geometric information in the low-precision raw patch is directly used to obtain the low-precision coordinate values of the supplementary points in the global coordinate system, thereby obtaining a complete low-precision 3D geometric model.
  • Step 1004 rebuilding a high-precision geometric model
  • Reconstructing a high-precision geometric model refers to the process of reconstructing a high-precision geometric model on the basis of a low-precision geometric model by using high-precision geometric information.
  • the high-precision geometric information and the low-precision geometric information are corresponded, and the high-precision three-dimensional coordinates of the vertex can be reconstructed according to the high-precision geometric information and the low-precision geometric information of the vertex.
  • y r (y l ⁇ log 2 QP y )
  • z r (z l ⁇ log 2 QP z )
  • the performing inverse quantization according to the first information to obtain the target three-dimensional grid further includes:
  • the decoding end uses the supplementary point information and the coordinates of each vertex in the first precision geometric information to determine the target three-dimensional mesh.
  • the supplementary information includes at least one of the following:
  • the third precision geometric information of the supplementary point is the quantized three-dimensional coordinate information of the supplementary point;
  • the fourth precision geometric information of the supplementary point is the three-dimensional coordinate information lost during the quantization process of the supplementary point.
  • the video-based 3D grid geometric information decoding framework of the embodiment of the present application is shown in Figure 11, and the overall decoding process is as follows:
  • the geometry sub-stream can include a code stream corresponding to low-precision geometry and a code stream corresponding to a high-precision geometric figure, or, the geometric figure sub-stream includes a code stream corresponding to a low-precision geometric figure filled with a high-precision geometric figure), and are decoded to obtain patch information and a placeholder image , geometric map; the geometric information of the low-precision grid can be reconstructed by using the occupancy map and the low-precision geometric map, and the geometric information of the high-precision mesh can be reconstructed by using the occupancy map, low-precision geometric map and high-precision geometric map; finally, use The reconstructed geometric information and the connection relationship obtained by other encoding and decoding methods are used to reconstruct the grid.
  • the embodiment of the present application is an embodiment of the opposite-end method corresponding to the above-mentioned embodiment of the encoding method, and the decoding process is an inverse process of encoding, and all the above-mentioned implementation methods on the encoding side are applicable to the embodiment of the decoding end. The same technical effect can also be achieved, and details will not be repeated here.
  • the embodiment of the present application also provides a decoding device 1200, including:
  • the second acquisition module 1201 is configured to decompose the acquired code stream, and acquire first information, where the first information includes at least one of the following: first-precision geometric information, second-precision geometric information, and supplementary point information;
  • the third acquiring module 1202 is configured to perform inverse quantization according to the first information, and acquire the target three-dimensional mesh;
  • the first precision geometric information is the geometric information after quantization of the target 3D grid
  • the second precision geometric information is the geometric information lost during the quantization process of the target 3D grid
  • the information of the supplementary points It is the information of points that need additional processing generated during the quantization process.
  • the second acquiring module 1201 includes:
  • the second obtaining unit is used to obtain a target sub-code stream according to the obtained code stream, and the target sub-code stream includes: a slice information sub-code stream, a placeholder image sub-code stream and a geometry sub-code stream;
  • a third acquiring unit configured to acquire second information according to the target sub-code stream, where the second information includes: at least one of a placeholder map and a geometric map;
  • the fourth obtaining unit is configured to obtain the first information according to the second information.
  • the fourth acquiring unit is configured to:
  • first-precision geometric information is obtained.
  • the fourth acquiring unit is configured to:
  • the fourth acquiring unit is configured to:
  • the geometric map of the supplementary point determine the first original slice corresponding to the third-precision geometric information of the supplementary point and the second original slice corresponding to the fourth-precision geometric information of the supplementary point;
  • the information of the supplementary point is determined according to the first original slice and the second original slice.
  • the third obtaining module 1202 is configured to:
  • the third acquiring module 1202 is also configured to:
  • the target three-dimensional grid is determined according to the coordinates of each vertex in the target three-dimensional grid and the second precision geometric information.
  • the third obtaining module 1202 is configured to:
  • the target three-dimensional mesh is determined by using the supplementary point information and the coordinates of each vertex in the first precision geometric information.
  • the supplementary information includes at least one of the following:
  • the third precision geometric information of the supplementary point is the quantized three-dimensional coordinate information of the supplementary point;
  • the fourth precision geometric information of the supplementary point is the three-dimensional coordinate information lost during the quantization process of the supplementary point.
  • this device embodiment is a device corresponding to the above-mentioned method, and all the implementation modes in the above-mentioned method embodiment are applicable to this device embodiment, and can also achieve the same technical effect, so details are not repeated here.
  • the embodiment of the present application also provides a decoding device, including a processor, a memory, and a program or instruction stored in the memory and operable on the processor.
  • a decoding device including a processor, a memory, and a program or instruction stored in the memory and operable on the processor.
  • the program or instruction is executed by the processor, the above-mentioned
  • the various processes of the decoding method embodiment can achieve the same technical effect, so in order to avoid repetition, details are not repeated here.
  • the embodiment of the present application also provides a readable storage medium.
  • the computer-readable storage medium stores programs or instructions.
  • the program or instructions are executed by the processor, the various processes of the above-mentioned decoding method embodiments can be achieved, and the same Technical effects, in order to avoid repetition, will not be repeated here.
  • the computer-readable storage medium is, for example, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and the like.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • magnetic disk or an optical disk and the like.
  • the embodiment of the present application also provides a decoding device, including a processor and a communication interface, wherein the communication interface is used to decompose the obtained code stream and obtain first information, and the first information includes at least one of the following : first-precision geometric information, second-precision geometric information, and supplementary point information; according to the first information, dequantization is performed to obtain a target three-dimensional grid.
  • a decoding device including a processor and a communication interface, wherein the communication interface is used to decompose the obtained code stream and obtain first information, and the first information includes at least one of the following : first-precision geometric information, second-precision geometric information, and supplementary point information; according to the first information, dequantization is performed to obtain a target three-dimensional grid.
  • the embodiment of the decoding device corresponds to the embodiment of the decoding method described above, and each implementation process and manner of the above method embodiment can be applied to the embodiment of the decoding device, and can achieve the same technical effect.
  • the embodiment of the present application also provides a decoding device.
  • the structure of the decoding device is shown in FIG. 8 , which will not be repeated here.
  • the decoding device in the embodiment of the present application further includes: instructions or programs stored in the memory and operable on the processor, the processor calls the instructions or programs in the memory to execute the method performed by each module shown in Figure 10, and To achieve the same technical effect, in order to avoid repetition, it is not repeated here.
  • the embodiment of the present application also provides a readable storage medium, on which programs or instructions are stored, the When the program or instruction is executed by the processor, each process of the above decoding method embodiment can be realized, and the same technical effect can be achieved. To avoid repetition, details are not repeated here.
  • the processor is the processor in the decoding device described in the foregoing embodiments.
  • the readable storage medium includes a computer-readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk, and the like.
  • this embodiment of the present application also provides a communication device 1300, including a processor 1301 and a memory 1302, and the memory 1302 stores programs or instructions that can run on the processor 1301, such as
  • the communication device 1300 is an encoding device
  • the program or instruction is executed by the processor 1301
  • each step of the above encoding method embodiment can be realized, and the same technical effect can be achieved.
  • the communication device 1300 is a decoding device
  • each step of the above decoding method embodiment can be achieved, and the same technical effect can be achieved. To avoid repetition, details are not repeated here.
  • the embodiment of the present application further provides a chip, the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the above encoding method or decoding method
  • the chip includes a processor and a communication interface
  • the communication interface is coupled to the processor
  • the processor is used to run programs or instructions to implement the above encoding method or decoding method
  • the chip mentioned in the embodiment of the present application may also be called a system-on-chip, a system-on-chip, a system-on-a-chip, or a system-on-a-chip.
  • the embodiment of the present application further provides a computer program product, the computer program product is stored in a storage medium, and the computer program product is executed by at least one processor to implement the various processes of the above encoding method or decoding method embodiment, And can achieve the same technical effect, in order to avoid repetition, no more details here.
  • the embodiment of the present application also provides a communication system, including at least: an encoding device and a decoding device, the encoding device can be used to perform the steps of the encoding method described above, and the decoding device can be used to perform the decoding method described above A step of. And can achieve the same technical effect, in order to avoid repetition, no more details here.
  • the embodiment of the present application also provides a communication device, the communication device is used to execute the steps of the above encoding method or decoding method, and can achieve the same technical effect, and to avoid repetition, details are not repeated here.
  • the term “comprising”, “comprising” or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article or apparatus comprising a set of elements includes not only those elements, It also includes other elements not expressly listed, or elements inherent in the process, method, article, or device. Without further limitations, an element defined by the phrase “comprising a " does not preclude the presence of additional identical elements in the process, method, article, or apparatus comprising that element.
  • the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved. Functions are performed, for example, the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
  • the methods of the above embodiments can be implemented by means of software plus a necessary general-purpose hardware platform, and of course also by hardware, but in many cases the former is a better implementation.
  • the technical solution of the present application can be embodied in the form of computer software products, which are stored in a storage medium (such as ROM/RAM, magnetic disk, etc.) , CD-ROM), including several instructions to make a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the methods described in the various embodiments of the present application.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Signal Processing (AREA)
  • Computer Graphics (AREA)
  • Geometry (AREA)
  • Software Systems (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Abstract

本申请公开了一种编码、解码方法、装置及设备，涉及编解码技术领域。该编码方法，包括：编码端对目标三维网格的几何信息进行量化，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；所述编码端对所述第一信息进行编码；其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。

Description

编码、解码方法、装置及设备
相关申请的交叉引用
本申请主张在2022年02月18日在中国提交的中国专利申请No.202210153277.2的优先权，其全部内容通过引用包含于此。
技术领域
本申请属于编解码技术领域，具体涉及一种编码、解码方法、装置及设备。
背景技术
三维网格(Mesh)可以被认为是过去多年来最流行的三维模型的表示方法，其在许多应用程序中扮演着重要的角色。它的表示简便，因此被大量以硬件算法集成到电脑、平板电脑和智能手机的图形处理单元(Graphics Processing Unit，GPU)中，专门用于渲染三维网格。
由于Mesh的顶点与点云都是空间中一组无规则分布的离散点集，具有相似的特点。因此，三维网格几何信息可以用点云压缩算法进行压缩。但相比于点云，三维网格的顶点具有空间分布更加稀疏，更加不均匀的特点。使用点云压缩算法来压缩三维网格模型的几何信息，压缩效率并不高。
发明内容
本申请实施例提供一种编码、解码方法、装置及设备，能够解决现有技术的对于三维网格几何信息的压缩方式，存在压缩效率不高的问题。
第一方面，提供了一种编码方法，包括：
编码端对目标三维网格的几何信息进行量化，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
所述编码端对所述第一信息进行编码；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
第二方面，提供了一种编码装置，包括：
第一获取模块，用于对目标三维网格的几何信息进行量化，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
编码模块，用于对所述第一信息进行编码；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
第三方面，提供了一种解码方法，包括：
解码端对获取的码流进行分解，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
所述解码端根据所述第一信息，进行反量化，获取目标三维网格；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
第四方面，提供了一种解码装置，包括：
第二获取模块，用于对获取的码流进行分解，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
第三获取模块，用于根据所述第一信息，进行反量化，获取目标三维网格；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
第五方面，提供了一种编码设备，包括处理器和存储器，所述存储器存储可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如第一方面所述的方法的步骤。
第六方面，提供了一种编码设备，包括处理器及通信接口，其中，所述处理器用于对目标三维网格的几何信息进行量化，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；对所述第一信息进行编码；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程 中产生的需要额外处理的点的信息。
第七方面，提供了一种解码设备，包括处理器和存储器，所述存储器存储可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如第三方面所述的方法的步骤。
第八方面，提供了一种解码设备，包括处理器及通信接口，其中，所述处理器用于对获取的码流进行分解，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；根据所述第一信息，进行反量化，获取目标三维网格；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
第九方面，提供了一种通信系统，包括：编码设备和解码设备，所述编码设备可用于执行如第一方面所述的方法的步骤，所述解码设备可用于执行如第三方面所述的方法的步骤。
第十方面，提供了一种可读存储介质，所述可读存储介质上存储程序或指令，所述程序或指令被处理器执行时实现如第一方面所述的方法的步骤，或者实现如第三方面所述的方法的步骤。
第十一方面，提供了一种芯片，所述芯片包括处理器和通信接口，所述通信接口和所述处理器耦合，所述处理器用于运行程序或指令，实现如第一方面所述的方法，或实现如第三方面所述的方法。
第十二方面，提供了一种计算机程序产品，所述计算机程序产品被存储在存储介质中，所述计算机程序产品被至少一个处理器执行以实现如第一方面所述的方法的步骤，或实现如第三方面所述的方法。
第十三方面，提供了一种通信设备，所述通信设备用于执行如第一方面所述的方法的步骤，或实现如第三方面所述的方法。
在本申请实施例中，通过对目标三维网格的几何信息进行量化，获取第一精度几何信息、第二精度几何信息和补充点的信息中的至少一项，并对上述信息进行编码，通过对三维网格的几何信息进行量化，使得量化后三维网格的顶点间距减少，进而减少投影后二维顶点的间距，以此提高三维网格的几何信息的压缩效率。
附图说明
图1是本申请实施例的编码方法的流程示意图；
图2是基于网格的精细划分过程示意图；
图3是片(Patch)排列的八种方向示意图；
图4是高精度几何信息的编码过程示意图；
图5是原始片(raw patch)示意图；
图6是基于视频的三维网格几何信息编码框架示意图；
图7是本申请实施例的编码装置的模块示意图；
图8是本申请实施例的编码设备的结构示意图；
图9是本申请实施例的解码方法的流程示意图；
图10是几何信息重建框图；
图11是基于视频的三维网格几何信息解码框架示意图；
图12是本申请实施例的解码装置的模块示意图；
图13是本申请实施例的通信设备的结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员所获得的所有其他实施例，都属于本申请保护的范围。
本申请的说明书和权利要求书中的术语“第一”、“第二”等是用于区别类似的对象，而不用于描述特定的顺序或先后次序。应该理解这样使用的术语在适当情况下可以互换，以便本申请的实施例能够以除了在这里图示或描述的那些以外的顺序实施，且“第一”、“第二”所区别的对象通常为一类，并不限定对象的个数，例如第一对象可以是一个，也可以是多个。此外，说明书以及权利要求中“和/或”表示所连接对象的至少其中之一，字符“/”一般表示前后关联对象是一种“或”的关系。
值得指出的是，本申请实施例所描述的技术不限于长期演进型(Long Term Evolution，LTE)/LTE的演进(LTE-Advanced，LTE-A)系统，还可用于其他无线通信系统，诸如码分多址(Code Division Multiple Access，CDMA)、时分多址(Time Division Multiple Access，TDMA)、频分多址(Frequency Division Multiple Access，FDMA)、正交频分多址(Orthogonal Frequency Division Multiple Access，OFDMA)、单载波频分多址(Single-carrier Frequency Division Multiple Access，SC-FDMA)和其他系统。本申请实施例中的术语“系统”和“网络”常被可互换地使用，所描述的技术既可用于以上提及的系统和无线电技术，也可用于其他系统和无线电技术。以下描述出于示例目的描述了新空口(New Radio，NR)系统， 并且在以下大部分描述中使用NR术语，但是这些技术也可应用于NR系统应用以外的应用，如第6代(6th Generation，6G)通信系统。
下面结合附图，通过一些实施例及其应用场景对本申请实施例提供的编码、解码方法、装置及设备进行详细地说明。
如图1所示，本申请实施例提供一种编码方法，包括：
步骤101，编码端对目标三维网格的几何信息进行量化，获取第一信息；
需要说明的是，本申请中所说的目标三维网格可以理解为任意视频帧对应的三维网格，该目标三维网格的几何信息可以理解为是三维网格中顶点的坐标，该坐标通常指的是三维坐标。
具体地，所述第一信息包括以下至少一项：
A11、第一精度几何信息；
需要说明的是，该第一精度几何信息可以理解为低精度几何信息，即低精度几何信息指的是目标三维网格量化后的几何信息，即量化后的目标三维网格包括的各顶点三维坐标信息。
A12、第二精度几何信息；
需要说明的是，该第二精度几何信息可以理解为高精度几何信息，高精度几何信息可以看作是量化过程中丢失的几何信息，即丢失的三维坐标信息。
A13、补充点的信息；
需要说明的是，补充点的信息是指量化过程中产生的需要额外处理的点的信息，也就是说，所述补充点为量化过程中产生的需要额外处理的点，例如，坐标位置出现重叠的重复点等，通过对重复点进行处理，可以使得在量化中坐标位置重叠的顶点在反量化后恢复到原来的位置。
可选地，该补充点的信息，包括以下至少一项：
A131、补充点对应的第一精度几何信息中顶点的索引；
需要说明的是，通过标识索引，便可知道量化后的网格中，哪些点标识的是量化前的三维网格中的多个点，即量化前的三维网格中的多个点在量化后重合到了一起，通过顶点的索引便可确定补充点的低精度几何信息。
A132、补充点的第三精度几何信息；
需要说明的是，该第三精度几何信息可以理解为补充点的低精度几何信息，即补充点被量化后的三维坐标信息。
A133、补充点的第四精度几何信息；
需要说明的是，该第四精度几何信息可以理解为补充点的高精度几何信息，即补充点在被量化过程中丢失的三维坐标信息。
这里需要说明的是，在具体使用时，通过A131和A133或者通过A132和A133便可确定得到量化后隐藏的点有哪些。
步骤102，所述编码端对所述第一信息进行编码；
需要说明的是，在得到第一信息后，便可以对这些第一信息进行编码，得到相应的子码流；上述方案，通过对三维网格的几何信息进行量化，使得量化后三维网格的顶点的间距减少，进而减少投影后二维顶点的间距，以此可以提高三维网格的几何信息的压缩效率。
可选地，上述的步骤101的具体实现方式为：
所述编码端根据每一分量的量化参数，对所述目标三维网格中的每一顶点进行量化，获取第一精度几何信息。
需要说明的是，每一分量的量化参数可以根据使用需求灵活设置；量化参数主要包括X向、Y向和Z向三个分量上的量化参数。
通常情况下，对于精度要求不高的量化，在量化后可以只保留低精度几何信息；而对于精度要求较高的量化，在量化时不仅要记录低精度几何信息，也需要记录高精度几何信息，以此在解码时能够实现精准的网格恢复，也就是说，上述的步骤101的具体实现方式还应当包括：
所述编码端根据所述第一精度几何信息以及所述每一分量的量化参数，获取第二精度几何信息。
例如，假设某顶点的三维坐标为(x,y,z)，量化参数为(QPx,QPy,QPz)，低精度几何信息(xl,yl,zl)和高精度几何信息(xh,yh,zh)的计算过程如公式一至公式六所示：
公式一：xl＝f1(x,QPx)；
公式二：yl＝f1(y,QPy)；
公式三：zl＝f1(z,QPz)；
公式四：xh＝f2(x,xl,QPx)；
公式五：yh＝f2(y,yl,QPy)；
公式六：zh＝f2(z,zl,QPz)；
其中，公式一至公式三中的f1函数是量化函数，量化函数的输入为某一维度的坐标和该维度的量化参数，输出为量化后的坐标值；公式四至公式六中的f2函数输入为原始坐标值、量化后的坐标值以及该维度的量化参数，输出为高精度的坐标值。
f1函数可以有多种计算方式，比较通用的一种计算方式如公式七至公式九所示，使用每个维度的原始坐标除以该维度的量化参数来计算。其中，/为除法运算符，对除法运算的结果可以采用不同的方式进行舍入，如四舍五入、向下取整、向上取整等。f2函数也存在多种计算方式，与公式七至公式九相对应的实现方式如公式十至公式十二所示，其中，*为乘法运算符。
公式七：xl＝x/QPx；
公式八：yl＝y/QPy；
公式九：zl＝z/QPz；
公式十：xh＝x-xl*QPx；
公式十一：yh＝y-yl*QPy；
公式十二：zh＝z-zl*QPz；
当量化参数为2的整数次幂时，f1函数和f2函数可以使用位运算实现，如公式十三至公式十八：
公式十三：xl＝x＞＞log2QPx；
公式十四：yl＝y＞＞log2QPy；
公式十五：zl＝z＞＞log2QPz；
公式十六：xh＝x&(QPx-1)；
公式十七：yh＝y&(QPy-1)；
公式十八：zh＝z&(QPz-1)；
值得注意的是，无论f1函数和f2函数采用哪种计算方式，量化参数QPx、QPy和QPz都可以灵活设置。首先，不同分量的量化参数并不一定相等，可以利用不同分量的量化参数的相关性，建立QPx、QPy和QPz之间的关系，为不同分量设置不同的量化参数；其次，不同空间区域的量化参数也不一定相等，可以根据局部区域顶点分布的稀疏程度自适应的设置量化参数。
需要说明的是，高精度几何信息包含的是三维网格的轮廓的细节信息。为了进一步提高压缩效率，可以对高精度几何信息(xh,yh,zh)进一步处理。在三维网格模型中，不同区域的顶点高精度几何信息的重要程度是不同的。对于顶点分布稀疏的区域，高精度几何信息的失真并不会对三维网格的视觉效果产生较大影响。这时为了提高压缩效率，可以选择对高精度几何信息进一步量化，或者只保留部分点的高精度几何信息。
可选地，在进行量化的过程中，可能会存在多个点量化完重合到同一个位置，也就是说，此种情况下，上述的步骤101的具体实现方式还应当包括：
所述编码端根据所述目标三维网格的几何信息和所述第一精度几何信息，确定补充点的信息。
也就是说，在得到所有顶点的低精度几何信息后，将低精度几何信息重复的点作为补充点，单独进行编码。补充点的几何信息同样可以分为低精度几何信息和高精度几何信息两部分，根据应用对压缩失真的要求，可以选择保留所有补充点或者只保留其中一部分补充点。对补充点的高精度几何信息，也可以进行进一步量化，或者只保留部分点的高精度几何信息。
需要说明的是，在对目标三维网格的几何信息进行量化得到第一信息之后，需要对第一信息进行编码得到最终的码流，可选地，本申请实施例中所说的对第一信息进行编码的具体实现过程包括：
步骤1021，所述编码端对所述第一信息进行处理，获取第二信息，所述第二信息包括占位图和几何图中的至少一项；
步骤1022，所述编码端对所述第二信息进行编码。
需要说明的是，因第一信息中包含的信息的种类不同，在对第一信息进行处理时，会分别对不同类的信息进行单独处理，下面分别从不同信息的角度，对步骤1021的实现过程说明如下。
一、所述第一信息包括第一精度几何信息
可选地，此种情况下，步骤1021的具体实现过程，包括：
步骤10211，所述编码端对所述第一精度几何信息进行三维片划分；
需要说明的是，此种情况下，主要是将低精度几何信息进行片(Patch)划分，得到多个三维片；此步骤的具体实现方式为：编码端确定第一精度几何信息中包含的每个顶点的投影平面；编码端根据所述投影平面对所述第一精度几何信息中所包含的顶点进行片划分；编码端对所述第一精度几何信息中所包含的顶点进行聚类，得到划分后的每一片。也就是说，对于Patch划分的过程主要包括：首先估计每个顶点的法向量，选择平面法向量与顶点法向量之间的夹角最小的候选投影平面作为该顶点的投影平面；然后，根据投影平面对顶点进行初始划分，将投影平面相同且连通的顶点组成patch；最后，使用精细划分算法优化聚类结果，得到最终的三维片(3D patch)。
下面对由第一精度几何信息得到三维片的过程的具体实现进行详细说明如下。
首先估计每个点的法向量。切线平面和它对应的法线是根据每个点的最近的邻居顶点m在一个预定义的搜索距离定义的。K-D树用于分离数据，并在点pi附近找到相邻点，该集合的重心用于定义法线。重心c的计算方法如下：
公式十九：
使用特征分解法估计顶点法向量，计算过程公式二十所示：
公式二十：
在初始划分阶段，初步选择每个顶点的投影平面。设顶点法向量的估计值为候选投影平面的法向量为选择法向量方向与顶点法向量方向最接近的平面作为该顶点的投影平面，平面选择的计算过程如公式二十一所示：
公式二十一：
精细划分过程可以采用基于网格的算法来降低算法的时间复杂度，基于网格的精细划分算法流程如图2所示，具体包括：
先设置循环次数(numlter)为0，判断循环次数是否小于最大循环次数(需要说明的是，该最大循环次数可以根据使用需求设置)，若小于则执行下述过程：
步骤S201，将(x,y,z)几何坐标空间划分为体素。
需要说明的是，此处的几何坐标空间指的是由量化得到的第一精度几何信息所构成的几何坐标空间。例如，对于使用体素大小为8的10位Mesh，每个坐标上的体素数量将是1024/8＝128，此坐标空间中的体素总数将是128×128×128。
步骤S202，查找填充体素，填充体素是指网格中包含至少有一个点的体素。
步骤S203，计算每个填充体素在每个投影平面上的平滑分数，记为voxScoreSmooth，体素在某投影平面的体素平滑分数是通过初始分割过程聚集到该投影平面的点的数量。
步骤S204，使用KD-Tree分区查找近邻填充体素，记为nnFilledVoxels，即每个填充体素(在搜索半径内和/或限制到最大数量的相邻体素)的最近的填充体素。
步骤S205，使用近邻填充体素在每个投影平面的体素平滑分数，计算每个填充体素的平滑分数(scoreSmooth)，计算过程如公式二十二所示：
公式二十二：
其中，p是投影平面的索引，v是近邻填充体素的索引。一个体素中所有点的scoreSmooth是相同的。
步骤S206，使用顶点的法向量与候选投影平面的法向量计算法向分数，记为scoreNormal，计算过程如公式二十三所示：
公式二十三：
其中，p是投影平面的索引，i是顶点的索引。
步骤S207，使用scoreSmooth和scoreNormal计算每个体素在各个投影平面上的最终分数，计算过程如公式二十四所示：
公式二十四：
其中，i为顶点索引，p为投影平面的索引，v是顶点i所在的体素索引。
步骤S208，使用步骤207中的分数对顶点进行聚类，得到精细划分的patch。
多次迭代上述过程，直到得到较为准确的patch。
步骤10212，所述编码端将划分的三维片进行二维投影，获取二维片；
需要说的是，此过程是将3D patch投影到二维平面得到二维片(2D patch)。
步骤10213，所述编码端将所述二维片进行打包，获取二维图像信息；
需要说明的是，此步骤实现的是片打包(Patch packing)，Patch packing的目的是将2D patch排列在一张二维图像上，Patch packing的基本原则是将patch不重叠的排列在二维图像上或者将patch的无像素部分进行部分重叠的排列在二维图像上，通过优先级排列、时域一致排列等算法，使patch排列的更加紧密，且具有时域一致性，提高编码性能。
假设，二维图像的分辨率为WxH，定义patch排列的最小块大小为T，它指定了放置在这个2D网格上的不同补丁之间的最小距离。
首先，patch按照不重叠的原则插入放置在2D网格上。每个patch占用由整数个TxT块组成的区域。此外，相邻patch之间要求至少有一个TxT块的距离。当没有足够的空间放置下一个patch时，图像的高度将变成原来的2倍，然后继续放置patch。
为了使patch排列的更加紧密，patch可以选择多种不同的排列方向。例如，可以采用八种不同的排列方向，如图3所示，包括0度、180度、90度、270度以及前四种方向的镜像。
为了获得更好的适应视频编码器帧间预测的特性，采用一种具有时域一致性的Patch排列方法。在一个一组帧(Group of frame，GOF)中，第一帧的所有patch按照从大到小 的顺序依次排列。对于GOF中的其他帧，使用时域一致性算法调整patch的排列顺序。
这里还需要说明的是，在得到二维图像信息后便能根据获取二维图像信息过程中的信息得到patch信息，之后便可以进行片信息的编码，获取片信息子码流；
这里需要说明的是，在进行二维图像信息过程中需要记录patch划分的信息、patch投影平面的信息以及patch packing位置的信息，所以patch信息记录的是获取二维图像过程中各步骤操作的信息，即patch信息包括：patch划分的信息、patch投影平面的信息以及patch packing位置的信息。
步骤10214，所述编码端根据所述二维图像信息，获取第一精度的占位图和第一精度的几何图；
需要说的是，对于获取占位图的过程，主要为：利用patch packing得到的patch排列信息，将二维图像中存在顶点的位置设为1，其余位置设为0，得到占位图。对于获取几何图的过程，主要为：在通过投影得到2D patch的过程中，保存了每个顶点到投影平面的距离，这个距离称为深度，低精度几何图压缩部分就是将2D patch中每个顶点的深度值，排列到该顶点在占位图中的位置上，得到低精度几何图。
二、所述第一信息包括第二精度几何信息
可选地，此种情况下，步骤1021的具体实现过程，包括：
步骤10215，所述编码端获取第一精度几何信息中所包含的顶点的排列顺序；
步骤10216，所述编码端将第一精度几何信息中所包含的顶点对应的第二精度几何信息排列在二维图像中，生成第二精度的几何图。
需要说明的是，高精度几何信息采用原始片(raw patch)的排列方式，将低精度几何图中的顶点对应的高精度几何信息排列在二维图像中，得到raw patch，以此便生成高精度几何图。主要分为三步，如图4所示，包括：
步骤401，获取顶点排列顺序，逐行从左向右扫描低精度几何图，将每个顶点的扫描顺序作为raw patch中顶点的排列顺序。
步骤402，生成raw patch。
需要说明的是，raw patch是将顶点的三维坐标按照如图5所示的方式逐行排列，形成的矩形patch。按照第一步中得到的顶点排列顺序，将顶点的高精度几何信息依次排列，得到高精度几何信息raw patch。
步骤403，将高精度几何信息放置在一张二维图像中，生成高精度几何图。
需要说明的是，在编码得到几何图子码流时，编码端是将对第一精度的几何图和第二精度的几何图进行编码，获取几何图子码流。
三、所述第一信息包括补充点的信息
可选地，此种情况下，步骤1021的具体实现过程，包括：
步骤10217、所述编码端将所述补充点的第三精度几何信息排列成第一原始片；
步骤10218、所述编码端按照与所述第一原始片相同的排列顺序，将所述补充点的第 四精度几何信息排列成第二原始片；
步骤10219、所述编码端对所述第一原始片和所述第二原始片进行压缩，获取补充点的几何图。
需要说明的是，本申请实施例中对于补充点的几何信息分为的低精度部分和高精度部分分别进行编码。首先，按照任意顺序将补充点的低精度几何信息排列成补充点低精度raw patch；然后，按照与补充点低精度raw patch相同的顺序将高精度几何信息排列成补充点高精度raw patch；最后，对补充点低精度raw patch和高精度raw patch进行压缩，可以采用多种压缩方法。其中，一种方法是对raw patch中的值进行游程编码、熵编码等方式编码，另一种方法是，将补充点低精度raw patch加入低精度几何图中的空白区域，将补充点高精度raw patch加入高精度几何图中的空白区域，得到补充点的几何图。
本申请实施例的基于视频的三维网格几何信息编码框架如图6所示，总体编码流程为：
首先，在量化之前可以选择是否对三维网格进行抽样简化；然后，对三维网格进行量化，由此可能会产生低精度几何信息、高精度几何信息和补充点信息三部分；对于低精度几何信息，采用投影的方式进行patch划分、patch排列生成patch序列压缩信息(patch的划分信息)、占位图和低精度几何图；对于可能存在的高精度几何信息可以采用raw patch的排列方式，生成高精度几何图(这里需要说明的是，可以对高精度几何图单独编码成一路码流，或者，也可以将高精度几何图填充进低精度几何图中，对低精度几何图进行编码得到一路码流)；对于可能存在的补充点，可以将补充点的几何信息分为低精度部分和高精度部分，分别进行raw patch排列，单独编码成一路码流，或者将raw patch加入几何图中；最后，编码patch序列压缩信息、占位图、几何图分别得到对应的子码流，并将多路子码流混流，得到最终输出码流。
需要说明的是，本申请给出了如何进行三维网格的几何信息进行编码的实现方式，通过将三维网格的几何信息进行量化，分别对量化后的不同精度的信息进行编码，以此能提高三维网格几何信息的压缩效率。
本申请实施例提供的编码方法，执行主体可以为编码装置。本申请实施例中以编码装置执行编码方法为例，说明本申请实施例提供的编码装置。
如图7所示，本申请实施例提供一种编码装置700，包括：
第一获取模块701，用于对目标三维网格的几何信息进行量化，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
编码模块702，用于对所述第一信息进行编码；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
可选地，所述第一获取模块701，用于：
根据每一分量的量化参数，对所述目标三维网格中的每一顶点进行量化，获取第一精 度几何信息；
可选地，所述第一获取模块701，还用于：
根据所述第一精度几何信息以及所述每一分量的量化参数，获取第二精度几何信息。
可选地，所述第一获取模块701，还用于：
根据所述目标三维网格的几何信息和所述第一精度几何信息，确定补充点的信息。
可选地，所述补充点的信息，包括以下至少一项：
补充点对应的第一精度几何信息中顶点的索引；
补充点的第三精度几何信息，所述第三精度几何信息为补充点被量化后的三维坐标信息；
补充点的第四精度几何信息，所述第四精度几何信息为补充点在被量化过程中丢失的三维坐标信息。
可选地，所述编码模块702，包括：
第一获取单元，用于对所述第一信息进行处理，获取第二信息，所述第二信息包括占位图和几何图中的至少一项；
编码单元，用于对所述第二信息进行编码。
可选地，在所述第一信息包括第一精度几何信息的情况下，所述第一获取单元，用于：
对所述第一精度几何信息进行三维片划分；
将划分的三维片进行二维投影，获取二维片；
将所述二维片进行打包，获取二维图像信息；
根据所述二维图像信息，获取第一精度的占位图和第一精度的几何图。
可选地，在所述将所述二维片进行打包，获取二维图像信息之后，所述第一获取单元，还用于：
根据获取二维图像信息过程中的信息，获取片信息；
对所述片信息进行编码，获取片信息子码流。
可选地，在所述第一信息包括第二精度几何信息的情况下，所述第一获取单元，用于：
获取第一精度几何信息中所包含的顶点的排列顺序；
将第一精度几何信息中所包含的顶点对应的第二精度几何信息排列在二维图像中，生成第二精度的几何图。
可选地，所述编码单元，用于：
对第一精度的几何图和第二精度的几何图进行编码，获取几何图子码流。
可选地，在所述第一信息包括补充点的信息的情况下，所述第一获取单元，用于：
将所述补充点的第三精度几何信息排列成第一原始片；
按照与所述第一原始片相同的排列顺序，将所述补充点的第四精度几何信息排列成第二原始片；
对所述第一原始片和所述第二原始片进行压缩，获取补充点的几何图。
该装置实施例与上述编码方法实施例对应，上述方法实施例的各个实施过程和实现方式均可适用于该装置实施例中，且能达到相同的技术效果。
具体地，本申请实施例还提供了一种编码设备，如图8所示，该编码设备800包括：处理器801、网络接口802和存储器803。其中，网络接口802例如为通用公共无线接口(Common Public Radio Interface，CPRI)。
具体地，本申请实施例的编码设备800还包括：存储在存储器803上并可在处理器801上运行的指令或程序，处理器801调用存储器803中的指令或程序执行图7所示各模块执行的方法，并达到相同的技术效果，为避免重复，故不在此赘述。
如图9所示，本申请实施例还提供一种解码方法，包括：
步骤901，解码端对获取的码流进行分解，获取第一信息；
需要说明的是，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
步骤902，所述解码端根据所述第一信息，进行反量化，获取目标三维网格；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
可选地，所述步骤901的具体实现方式，包括：
所述解码端根据获取的码流，获取目标子码流，所述目标子码流包括：片信息子码流、占位图子码流和几何图子码流；
所述解码端根据所述目标子码流，获取第二信息，所述第二信息包括：占位图和几何图中的至少一项；
所述解码端根据所述第二信息，获取第一信息。
可选地，在所述第一信息包括第一精度几何信息的情况下，所述根据所述第二信息，获取第一信息，包括：
所述解码端根据第一精度的占位图和第一精度的几何图，获取二维图像信息；
所述解码端根据所述二维图像信息，获取二维片；
所述解码端根据所述片信息子码流对应的片信息对所述二维片进行三维逆投影，获取三维片；
所述解码端根据所述三维片，获取第一精度几何信息。
可选地，在所述第一信息包括第二精度几何信息的情况下，所述根据所述第二信息，获取第一信息，包括：
所述解码端根据第二精度的几何图，获取第二精度几何信息。
可选地，在所述第一信息包括补充点的信息的情况下，所述根据所述第二信息，获取第一信息，包括：
所述解码端根据补充点的几何图，确定所述补充点的第三精度几何信息对应的第一原 始片以及所述补充点的第四精度几何信息对应的第二原始片；
所述解码端根据所述第一原始片和所述第二原始片，确定补充点的信息。
需要说明的是，本申请实施例中对于补充点的几何信息分为的低精度部分和高精度部分分别进行解码。首先，对补充点的几何图进行解压缩，可以采用多种解压缩方法。其中，一种方法是对几何图进行游程解码、熵解码等方式解码，另一种方法是，将补充点低精度raw patch从低精度几何图中取出，将补充点高精度raw patch从高精度几何图中取出。然后，按照特定顺序从补充点低精度raw patch中获取补充点的低精度几何信息，按照特定顺序从补充点高精度raw patch中获取高精度几何信息；这里需要说明的是，该特定顺序是解码端通过解析码流得到的，即编码端采用何种顺序生成补充点低精度raw patch和补充点高精度raw patch是会通过码流告知解码端的。
可选地，所述根据所述第一信息，进行反量化，获取目标三维网格，包括：
所述解码端根据所述第一精度几何信息以及每一分量的量化参数，确定所述第一精度几何信息中的每一顶点的坐标。可选地，所述根据所述第一信息，进行反量化，获取目标三维网格，还包括：
所述解码端根据所述目标三维网格中的每一顶点的坐标以及所述第二精度几何信息，确定所述目标三维网格。
需要说明的是，本申请实施例中的几何信息重建过程是利用patch信息、占位图、低精度几何图和高精度几何图等信息，重建三维几何模型的过程。具体过程如图10所示，主要包括以下四步：
步骤1001，获取2D patch；
需要说明的是，获取2D patch是指利用patch信息从占位图和几何图中分割出2D patch的占位信息和深度信息。Patch信息中包含了每个2D patch的包围盒在占位图和低精度几何图中的位置和大小，利用patch信息、占位图和低精度几何图可以直接获取到2D patch的占位信息和低精度几何信息。对于高精度几何信息，利用低精度几何图的顶点扫描顺序，将高精度raw patch中的高精度几何信息与低精度几何图顶点进行对应，从而得到2D patch的高精度几何信息。对于补充点的几何信息，直接解码补充点的低精度raw patch和高精度raw patch即可获得补充点的低精度几何信息和高精度几何信息。
步骤1002，重建3D patch；
需要说明的是，重建3D patch是指利用2D patch中的占位信息和低精度几何信息，将2D patch中的顶点重建为低精度3D patch。2D patch的占位信息中包含了顶点在patch投影平面局部坐标系中相对于坐标原点的位置，深度信息包含了顶点在投影平面法线方向上的深度值。因此，利用占位信息和深度信息可以在局部坐标系中将2D patch重建为低精度3D patch。
步骤1003，重建低精度几何模型；
需要说明的是，重建低精度几何模型是指利用重建的低精度3D patch，重建整个低精 度三维几何模型。Patch信息中包含了3D patch由局部坐标系转换成三维几何模型全局坐标系的转换关系，利用坐标转换关系将所有的3D patch转换到全局坐标系下，就得到了低精度三维几何模型。此外，对于补充点，直接利用低精度raw patch中的几何信息，得到补充点在全局坐标系下的低精度坐标值，从而得到完整的低精度三维几何模型。
步骤1004，重建高精度几何模型；
重建高精度几何模型是指在低精度几何模型的基础上，利用高精度几何信息，重建高精度几何模型的过程。在获取2D patch的过程中，将高精度几何信息与低精度几何信息进行了对应，根据顶点的高精度几何信息和低精度几何信息可以重建出顶点的高精度三维坐标。根据应用的要求，可以选择重建全部顶点的高精度三维坐标，也可以重建部分顶点的高精度三维坐标。高精度三维坐标(xr,yr,zr)的计算过程，如公式二十五至公式二十七所示：
公式二十五：xr＝f3(xl,xh,QPx)；
公式二十六：yr＝f3(yl,yh,QPy)；
公式二十七：zr＝f3(zl,zh,QPz)；
f3函数是重建函数，重建函数的计算过程与编码端量化函数的计算过程相对应，有多种实现方式。如果f1函数采用式公式七至公式十二的实现方式，则重建函数的实现方式如公式二十八至公式三十所示：
公式二十八：xr＝xl*QPx+xh；
公式二十九：yr＝yl*QPy+yh；
公式三十：zr＝zl*QPz+zh；
如果f1函数采用公式十三至公式十八的实现方式，则重建函数的实现方式如公式三十一至公式三十三所示：
公式三十一：xr＝(xl＜＜log2QPx)|xh；
公式三十二：yr＝(yl＜＜log2QPy)|yh；
公式三十三：zr＝(zl＜＜log2QPz)|zh。
可选地，所述根据所述第一信息，进行反量化，获取目标三维网格，还包括：
所述解码端将所述补充点的信息以及所述第一精度几何信息中的每一顶点的坐标，确定所述目标三维网格。
可选地，所述补充点的信息，包括以下至少一项：
补充点对应的第一精度几何信息中顶点的索引；
补充点的第三精度几何信息，所述第三精度几何信息为补充点被量化后的三维坐标信息；
补充点的第四精度几何信息，所述第四精度几何信息为补充点在被量化过程中丢失的三维坐标信息。
本申请实施例的基于视频的三维网格几何信息解码框架如图11所示，总体解码流程为：
首先，将码流分解成patch信息子码流、占位图子码流、几何图子码流(这里需要说明的是，该几何图子码流中可以包括低精度几何图对应的一路码流以及高精度几何图对应的一路码流，或者，该几何图子码流中包括填充有高精度几何图的低精度几何图对应的一路码流)，并分别进行解码得到patch信息、占位图、几何图；使用占位图、低精度几何图可以重建低精度网格的几何信息，使用占位图、低精度几何图以及高精度几何图可以重建高精度网格的几何信息；最终，使用重建的几何信息以及其他编解码方式得到的连接关系等信息重建网格。
需要说明的是，本申请实施例是与上述编码方法的实施例对应的对端的方法实施例，解码过程为编码的反过程，上述编码侧的所有实现方式均适用于该解码端的实施例中，也能达到与之相同的技术效果，在此不再赘述。
如图12所示，本申请实施例还提供一种解码装置1200，包括：
第二获取模块1201，用于对获取的码流进行分解，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
第三获取模块1202，用于根据所述第一信息，进行反量化，获取目标三维网格；
其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
可选地，所述第二获取模块1201，包括：
第二获取单元，用于根据获取的码流，获取目标子码流，所述目标子码流包括：片信息子码流、占位图子码流和几何图子码流；
第三获取单元，用于根据所述目标子码流，获取第二信息，所述第二信息包括：占位图和几何图中的至少一项；
第四获取单元，用于根据所述第二信息，获取第一信息。
可选地，在所述第一信息包括第一精度几何信息的情况下，所述第四获取单元，用于：
根据第一精度的占位图和第一精度的几何图，获取二维图像信息；
根据所述二维图像信息，获取二维片；
根据所述片信息子码流对应的片信息对所述二维片进行三维逆投影，获取三维片；
根据所述三维片，获取第一精度几何信息。
可选地，在所述第一信息包括第二精度几何信息的情况下，所述第四获取单元，用于：
根据第二精度的几何图，获取第二精度几何信息。
可选地，在所述第一信息包括补充点的信息的情况下，所述第四获取单元，用于：
根据补充点的几何图，确定所述补充点的第三精度几何信息对应的第一原始片以及所述补充点的第四精度几何信息对应的第二原始片；
根据所述第一原始片和所述第二原始片，确定补充点的信息。
可选地，所述第三获取模块1202，用于：
根据所述第一精度几何信息以及每一分量的量化参数，确定所述第一精度几何信息中的每一顶点的坐标。
可选地，所述第三获取模块1202，还用于：
根据所述目标三维网格中的每一顶点的坐标以及所述第二精度几何信息，确定所述目标三维网格。
可选地，所述第三获取模块1202，用于：
将所述补充点的信息以及所述第一精度几何信息中的每一顶点的坐标，确定所述目标三维网格。
可选地，所述补充点的信息，包括以下至少一项：
补充点对应的第一精度几何信息中顶点的索引；
补充点的第三精度几何信息，所述第三精度几何信息为补充点被量化后的三维坐标信息；
补充点的第四精度几何信息，所述第四精度几何信息为补充点在被量化过程中丢失的三维坐标信息。
需要说明的是，该装置实施例是与上述方法对应的装置，上述方法实施例中的所有实现方式均适用于该装置实施例中，也能达到相同的技术效果，在此不再赘述。
优选的，本申请实施例还提供一种解码设备，包括处理器，存储器，存储在存储器上并可在所述处理器上运行的程序或指令，该程序或指令被处理器执行时实现上述的解码方法实施例的各个过程，且能达到相同的技术效果，为避免重复，这里不再赘述。
本申请实施例还提供一种可读存储介质，计算机可读存储介质上存储有程序或指令，该程序或指令被处理器执行时实现上述的解码方法实施例的各个过程，且能达到相同的技术效果，为避免重复，这里不再赘述。
其中，所述的计算机可读存储介质，如只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等。
本申请实施例还提供了一种解码设备，包括处理器及通信接口，其中，所述通信接口用于对获取的码流进行分解，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；根据所述第一信息，进行反量化，获取目标三维网格。
该解码设备实施例是与上述解码方法实施例对应的，上述方法实施例的各个实施过程和实现方式均可适用于该解码设备实施例中，且能达到相同的技术效果。
具体地，本申请实施例还提供了一种解码设备。具体地，该解码设备的结构如图8所示，在此不再赘述。具体地，本申请实施例的解码设备还包括：存储在存储器上并可在处理器上运行的指令或程序，处理器调用存储器中的指令或程序执行图10所示各模块执行的方法，并达到相同的技术效果，为避免重复，故不在此赘述。
本申请实施例还提供一种可读存储介质，所述可读存储介质上存储有程序或指令，该 程序或指令被处理器执行时实现上述解码方法实施例的各个过程，且能达到相同的技术效果，为避免重复，这里不再赘述。
其中，所述处理器为上述实施例中所述的解码设备中的处理器。所述可读存储介质，包括计算机可读存储介质，如计算机只读存储器ROM、随机存取存储器RAM、磁碟或者光盘等。
可选地，如图13所示，本申请实施例还提供一种通信设备1300，包括处理器1301和存储器1302，存储器1302上存储有可在所述处理器1301上运行的程序或指令，例如，该通信设备1300为编码设备时，该程序或指令被处理器1301执行时实现上述编码方法实施例的各个步骤，且能达到相同的技术效果。该通信设备1300为解码设备时，该程序或指令被处理器1301执行时实现上述解码方法实施例的各个步骤，且能达到相同的技术效果，为避免重复，这里不再赘述。
本申请实施例另提供了一种芯片，所述芯片包括处理器和通信接口，所述通信接口和所述处理器耦合，所述处理器用于运行程序或指令，实现上述编码方法或解码方法实施例的各个过程，且能达到相同的技术效果，为避免重复，这里不再赘述。
应理解，本申请实施例提到的芯片还可以称为系统级芯片，系统芯片，芯片系统或片上系统芯片等。
本申请实施例另提供了一种计算机程序产品，所述计算机程序产品被存储在存储介质中，所述计算机程序产品被至少一个处理器执行以实现上述编码方法或解码方法实施例的各个过程，且能达到相同的技术效果，为避免重复，这里不再赘述。
本申请实施例还提供了一种通信系统，至少包括：编码设备和解码设备，所述编码设备可用于执行如上所述的编码方法的步骤，所述解码设备可用于执行如上所述的解码方法的步骤。且能达到相同的技术效果，为避免重复，这里不再赘述。
本申请实施例还提供了一种通信设备，所述通信设备用于执行上述编码方法或解码方法的步骤，且能达到相同的技术效果，为避免重复，这里不再赘述。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。此外，需要指出的是，本申请实施方式中的方法和装置的范围不限按示出或讨论的顺序来执行功能，还可包括根据所涉及的功能按基本同时的方式或按相反的顺序来执行功能，例如，可以按不同于所描述的次序来执行所描述的方法，并且还可以添加、省去、或组合各种步骤。另外，参照某些示例所描述的特征可在其他示例中被组合。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者 是更佳的实施方式。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分可以以计算机软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端(可以是手机，计算机，服务器，空调器，或者网络设备等)执行本申请各个实施例所述的方法。
上面结合附图对本申请的实施例进行了描述，但是本申请并不局限于上述的具体实施方式，上述的具体实施方式仅仅是示意性的，而不是限制性的，本领域的普通技术人员在本申请的启示下，在不脱离本申请宗旨和权利要求所保护的范围情况下，还可做出很多形式，均属于本申请的保护之内。

Claims (29)

  1. 一种编码方法，包括：
    编码端对目标三维网格的几何信息进行量化，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
    所述编码端对所述第一信息进行编码；
    其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
  2. 根据权利要求1所述的方法，其中，所述对目标三维网格的几何信息进行量化，获取第一信息，包括：
    所述编码端根据每一分量的量化参数，对所述目标三维网格中的每一顶点进行量化，获取第一精度几何信息。
  3. 根据权利要求2所述的方法，其中，所述对目标三维网格的几何信息进行量化，获取第一信息，还包括：
    所述编码端根据所述第一精度几何信息以及所述每一分量的量化参数，获取第二精度几何信息。
  4. 根据权利要求2所述的方法，其中，所述对目标三维网格的几何信息进行量化，获取第一信息，还包括：
    所述编码端根据所述目标三维网格的几何信息和所述第一精度几何信息，确定补充点的信息。
  5. 根据权利要求1-4任一项所述的方法，其中，所述补充点的信息，包括以下至少一项：
    补充点对应的第一精度几何信息中顶点的索引；
    补充点的第三精度几何信息，所述第三精度几何信息为补充点被量化后的三维坐标信息；
    补充点的第四精度几何信息，所述第四精度几何信息为补充点在被量化过程中丢失的三维坐标信息。
  6. 根据权利要求1所述的方法，其中，所述对所述第一信息进行编码，包括：
    所述编码端对所述第一信息进行处理，获取第二信息，所述第二信息包括占位图和几何图中的至少一项；
    所述编码端对所述第二信息进行编码。
  7. 根据权利要求6所述的方法，其中，在所述第一信息包括第一精度几何信息的情况下，所述对所述第一信息进行处理，获取第二信息，包括：
    所述编码端对所述第一精度几何信息进行三维片划分；
    所述编码端将划分的三维片进行二维投影，获取二维片；
    所述编码端将所述二维片进行打包，获取二维图像信息；
    所述编码端根据所述二维图像信息，获取第一精度的占位图和第一精度的几何图。
  8. 根据权利要求7所述的方法，其中，在所述将所述二维片进行打包，获取二维图像信息之后，还包括：
    所述编码端根据获取二维图像信息过程中的信息，获取片信息；
    所述编码端对所述片信息进行编码，获取片信息子码流。
  9. 根据权利要求6所述的方法，其中，在所述第一信息包括第二精度几何信息的情况下，所述对所述第一信息进行处理，获取第二信息，包括：
    所述编码端获取第一精度几何信息中所包含的顶点的排列顺序；
    所述编码端将第一精度几何信息中所包含的顶点对应的第二精度几何信息排列在二维图像中，生成第二精度的几何图。
  10. 根据权利要求6所述的方法，其中，所述编码端对所述第二信息进行编码，包括：
    所述编码端对第一精度的几何图和第二精度的几何图进行编码，获取几何图子码流。
  11. 根据权利要求6所述的方法，其中，在所述第一信息包括补充点的信息的情况下，所述对所述第一信息进行处理，获取第二信息，包括：
    所述编码端将所述补充点的第三精度几何信息排列成第一原始片；
    所述编码端按照与所述第一原始片相同的排列顺序，将所述补充点的第四精度几何信息排列成第二原始片；
    所述编码端对所述第一原始片和所述第二原始片进行压缩，获取补充点的几何图。
  12. 一种解码方法，包括：
    解码端对获取的码流进行分解，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
    所述解码端根据所述第一信息，进行反量化，获取目标三维网格；
    其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
  13. 根据权利要求12所述的方法，其中，所述对获取的码流进行分解，获取第一信息，包括：
    所述解码端根据获取的码流，获取目标子码流，所述目标子码流包括：片信息子码流、占位图子码流和几何图子码流；
    所述解码端根据所述目标子码流，获取第二信息，所述第二信息包括：占位图和几何图中的至少一项；
    所述解码端根据所述第二信息，获取所述第一信息。
  14. 根据权利要求13所述的方法，其中，在所述第一信息包括第一精度几何信息的情 况下，所述根据所述第二信息，获取第一信息，包括：
    所述解码端根据第一精度的占位图和第一精度的几何图，获取二维图像信息；
    所述解码端根据所述二维图像信息，获取二维片；
    所述解码端根据所述片信息子码流对应的片信息对所述二维片进行三维逆投影，获取三维片；
    所述解码端根据所述三维片，获取第一精度几何信息。
  15. 根据权利要求13所述的方法，其中，在所述第一信息包括第二精度几何信息的情况下，所述根据所述第二信息，获取第一信息，包括：
    所述解码端根据第二精度的几何图，获取第二精度几何信息。
  16. 根据权利要求13所述的方法，其中，在所述第一信息包括补充点的信息的情况下，所述根据所述第二信息，获取第一信息，包括：
    所述解码端根据补充点的几何图，确定所述补充点的第三精度几何信息对应的第一原始片以及所述补充点的第四精度几何信息对应的第二原始片；
    所述解码端根据所述第一原始片和所述第二原始片，确定补充点的信息。
  17. 根据权利要求12所述的方法，其中，所述根据所述第一信息，进行反量化，获取目标三维网格，包括：
    所述解码端根据所述第一精度几何信息以及每一分量的量化参数，确定所述第一精度几何信息中的每一顶点的坐标。
  18. 根据权利要求17所述的方法，其中，所述根据所述第一信息，进行反量化，获取目标三维网格，还包括：
    所述解码端根据所述目标三维网格中的每一顶点的坐标以及所述第二精度几何信息，确定所述目标三维网格。
  19. 根据权利要求17所述的方法，其中，所述根据所述第一信息，进行反量化，获取目标三维网格，还包括：
    所述解码端将所述补充点的信息以及所述第一精度几何信息中的每一顶点的坐标，确定所述目标三维网格。
  20. 根据权利要求17-19任一项所述的方法，其中，所述补充点的信息，包括以下至少一项：
    补充点对应的第一精度几何信息中顶点的索引；
    补充点的第三精度几何信息，所述第三精度几何信息为补充点被量化后的三维坐标信息；
    补充点的第四精度几何信息，所述第四精度几何信息为补充点在被量化过程中丢失的三维坐标信息。
  21. 一种编码装置，包括：
    第一获取模块，用于对目标三维网格的几何信息进行量化，获取第一信息，所述第一 信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
    编码模块，用于对所述第一信息进行编码；
    其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
  22. 根据权利要求21所述的装置，其中，所述第一获取模块，用于：
    根据每一分量的量化参数，对所述目标三维网格中的每一顶点进行量化，获取第一精度几何信息。
  23. 根据权利要求22所述的装置，其中，所述第一获取模块，还用于：
    根据所述第一精度几何信息以及所述每一分量的量化参数，获取第二精度几何信息。
  24. 根据权利要求22所述的装置，其中，所述第一获取模块，还用于：
    根据所述目标三维网格的几何信息和所述第一精度几何信息，确定补充点的信息。
  25. 根据权利要求21所述的装置，其中，所述编码模块，包括：
    第一获取单元，用于对所述第一信息进行处理，获取第二信息，所述第二信息包括占位图和几何图中的至少一项；
    编码单元，用于对所述第二信息进行编码。
  26. 一种编码设备，包括处理器和存储器，所述存储器存储可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如权利要求1至11任一项所述的编码方法的步骤。
  27. 一种解码装置，包括：
    第二获取模块，用于对获取的码流进行分解，获取第一信息，所述第一信息包括以下至少一项：第一精度几何信息、第二精度几何信息、补充点的信息；
    第三获取模块，用于根据所述第一信息，进行反量化，获取目标三维网格；
    其中，所述第一精度几何信息为所述目标三维网格量化后的几何信息，所述第二精度几何信息为所述目标三维网格量化过程中丢失的几何信息，所述补充点的信息为量化过程中产生的需要额外处理的点的信息。
  28. 一种解码设备，包括处理器和存储器，所述存储器存储可在所述处理器上运行的程序或指令，所述程序或指令被所述处理器执行时实现如权利要求12至20任一项所述的解码方法的步骤。
  29. 一种可读存储介质，所述可读存储介质上存储程序或指令，所述程序或指令被处理器执行时实现如权利要求1至11任一项所述的编码方法的步骤或如权利要求12至20任一项所述的解码方法的步骤。
PCT/CN2023/076113 2022-02-18 2023-02-15 编码、解码方法、装置及设备 WO2023155794A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202210153277.2A CN116664704A (zh) 2022-02-18 2022-02-18 编码、解码方法、装置及设备
CN202210153277.2 2022-02-18

Publications (1)

Publication Number Publication Date
WO2023155794A1 true WO2023155794A1 (zh) 2023-08-24

Family

ID=87577555

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2023/076113 WO2023155794A1 (zh) 2022-02-18 2023-02-15 编码、解码方法、装置及设备

Country Status (2)

Country Link
CN (1) CN116664704A (zh)
WO (1) WO2023155794A1 (zh)

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090184956A1 (en) * 2008-01-21 2009-07-23 Samsung Electronics Co., Ltd. Method, medium, and system for compressing and decoding mesh data in three-dimensional mesh model
CN102510497A (zh) * 2011-10-18 2012-06-20 清华大学 基于分级量化的质量可伸缩的三维网格编码方法及装置
CN104243958A (zh) * 2014-09-29 2014-12-24 联想(北京)有限公司 三维网格数据的编码、解码方法以及编码、解码装置
US20210090301A1 (en) * 2019-09-24 2021-03-25 Apple Inc. Three-Dimensional Mesh Compression Using a Video Encoder
US20220028119A1 (en) * 2018-12-13 2022-01-27 Samsung Electronics Co., Ltd. Method, device, and computer-readable recording medium for compressing 3d mesh content

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090184956A1 (en) * 2008-01-21 2009-07-23 Samsung Electronics Co., Ltd. Method, medium, and system for compressing and decoding mesh data in three-dimensional mesh model
CN102510497A (zh) * 2011-10-18 2012-06-20 清华大学 基于分级量化的质量可伸缩的三维网格编码方法及装置
CN104243958A (zh) * 2014-09-29 2014-12-24 联想(北京)有限公司 三维网格数据的编码、解码方法以及编码、解码装置
US20220028119A1 (en) * 2018-12-13 2022-01-27 Samsung Electronics Co., Ltd. Method, device, and computer-readable recording medium for compressing 3d mesh content
US20210090301A1 (en) * 2019-09-24 2021-03-25 Apple Inc. Three-Dimensional Mesh Compression Using a Video Encoder

Also Published As

Publication number Publication date
CN116664704A (zh) 2023-08-29

Similar Documents

Publication Publication Date Title
JP7084703B2 (ja) 物理的属性を表す信号の圧縮
Devillers et al. Geometric compression for interactive transmission
Morell et al. Geometric 3D point cloud compression
CN103927746B (zh) 一种三维网格序列的配准及压缩方法
WO2022121649A1 (zh) 点云数据编码方法、解码方法、点云数据处理方法及装置、电子设备、计算机程序产品及计算机可读存储介质
JP2012068881A (ja) ３次元動画像の圧縮に用いる基本単位及び当該基本単位の生成方法、当該基本単位を用いた３次元動画像の圧縮方法
Ponchio et al. Multiresolution and fast decompression for optimal web-based rendering
KR20230060534A (ko) 2차원 정규화 평면 투사에 기초한 포인트 클라우드 인코딩 및 디코딩 방법과 장치
Isenburg et al. Streaming compression of tetrahedral volume meshes
KR20120085134A (ko) 3차원 메쉬 부호화 장치 및 방법, 그리고 3차원 메쉬 복호화 장치 및 방법
WO2023155794A1 (zh) 编码、解码方法、装置及设备
TW202036483A (zh) 拼貼擴充方法、編碼器與解碼器
WO2023155778A1 (zh) 编码方法、装置及设备
WO2023174337A1 (zh) 编码、解码方法、装置及设备
WO2023179705A1 (zh) 编码、解码方法、装置及设备
Yusov Real-time deformable terrain rendering with DirectX 11
JP2023541271A (ja) 高密度メッシュ圧縮
WO2023174336A1 (zh) 编码、解码方法、装置及设备
WO2023174334A1 (zh) 编码、解码方法、装置及设备
WO2023197990A1 (zh) 编码方法、解码方法及终端
WO2023179706A1 (zh) 编码方法、解码方法及终端
WO2023179710A1 (zh) 编码方法及终端
CN116843771A (zh) 编码方法、解码方法及终端
Abderrahim et al. Progressive compression of 3D objects with an adaptive quantization
WO2023097694A1 (zh) 解码方法、编码方法、解码器以及编码器

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 23755796

Country of ref document: EP

Kind code of ref document: A1