Mesh data transmission device, mesh data transmission method, mesh data reception device, and mesh data reception method

Abstract

A mesh data decoding device, according to embodiments, may comprise: a base mesh processing step for reconstructing a base mesh from a base mesh bitstream; a displacement information processing step for reconstructing displacement information from a displacement vector bitstream; a reconstruction step for reconstructing a mesh on the basis of the base mesh and the displacement information; and a texture map processing step for reconstructing a texture map from a texture map bitstream included in a bitstream.

Description

Mesh data transmission device, mesh data transmission method, mesh data reception device, and mesh data reception method

[0001] The embodiments provide a method for providing 3D content to provide users with various services such as VR (Virtual Reality), AR (Augmented Reality), MR (Mixed Reality), and autonomous driving services.

[0002] Among 3D content, point cloud data and mesh data are collections of points in 3D space. However, the sheer number of points in 3D space makes it difficult to generate point cloud or mesh data.

[0003] That is, there is a problem that a lot of processing is required to transmit and receive 3D data with a large amount of points, such as point cloud data or mesh data.

[0004] The technical problem according to the embodiments is to provide a device and method for efficiently transmitting and receiving mesh data in order to solve the problems described above.

[0005] The technical problem according to the embodiments is to provide a device and method for resolving latency and encoding / decoding complexity of mesh data.

[0006] The technical problem according to the embodiments is to provide a device and method for efficiently performing encoding and decoding of a displacement vector.

[0007] The technical problem according to the embodiments is to provide a device and method for performing an adaptive prediction and / or update process by using adaptive weights for each displacement vector component according to the characteristics of the displacement vector component when performing a displacement vector lifting transformation and inverse transformation process of a dynamic mesh.

[0008] However, the scope of the embodiments is not limited to the aforementioned technical tasks, and the scope of the embodiments may be expanded to other technical tasks that can be inferred by a person skilled in the art based on the entire contents of this document.

[0009] To achieve the above-described purpose and other advantages, a decoding method according to embodiments may include a step of receiving a bitstream including mesh data and a step of decoding the mesh data.

[0010] According to embodiments, the step of decoding the mesh data may include a base mesh processing step of restoring a base mesh from a base mesh bitstream included in the bitstream, a displacement information processing step of restoring displacement information from a displacement vector bitstream included in the bitstream, a restoration step of restoring a mesh based on the base mesh and the displacement information, and a texture map processing step of restoring a texture map from a texture map bitstream included in the bitstream.

[0011] According to embodiments, the displacement information processing step may include a step of decoding the displacement vector bitstream into displacement information, a step of dequantizing the decoded displacement information, and a step of inversely transforming the dequantized displacement information.

[0012] According to embodiments, the inverse transform step may include a step of inversely transforming the inverse quantized displacement information in a lifting manner.

[0013] According to embodiments, the step of performing inverse transformation in the lifting manner may include a step of performing a lifting inverse transformation update by applying an update weight to each component of the displacement information, and a step of performing a lifting inverse transformation prediction by applying a prediction weight to each component of the updated displacement information.

[0014] According to embodiments, the lifting inverse transformation update step may perform the lifting inverse transformation update based on valence information calculated from the base mesh.

[0015] According to embodiments, a decoding device may include a memory and at least one processor connected to the memory, wherein the at least one processor may be configured to receive a bitstream including mesh data and decode the mesh data.

[0016] According to embodiments, the at least one processor may include a base mesh processing unit that restores a base mesh from a base mesh bitstream included in the bitstream, a displacement information processing unit that restores displacement information from a displacement vector bitstream included in the bitstream, a restoration unit that restores a mesh based on the base mesh and the displacement information, and a texture map processing unit that restores a texture map from a texture map bitstream included in the bitstream.

[0017] According to embodiments, the displacement information processing unit may include a displacement information decoding unit that decodes the displacement vector bitstream into displacement information, an inverse quantization unit that inversely quantizes the decoded displacement information, and an inverse transformation unit that inversely transforms the inversely quantized displacement information.

[0018] According to embodiments, the inverse transformation unit may include a lifting inverse transformation update unit that performs lifting inverse transformation update by applying update weights to each component of the displacement information, and a lifting inverse transformation prediction unit that performs lifting inverse transformation prediction by applying prediction weights to each component of the updated displacement information.

[0019] According to embodiments, the lifting inverse transformation update unit can perform the lifting inverse transformation update based on valence information calculated from the base mesh.

[0020] According to embodiments, the encoding method may include the steps of encoding mesh data, and transmitting a bitstream including the encoded mesh data.

[0021] According to embodiments, the encoding step may include a base mesh processing step of generating a base mesh bitstream by encoding a base mesh generated by simplifying an original mesh, a displacement information processing step of generating a displacement vector bitstream by encoding displacement information generated based on the base mesh, a mesh restoration step of restoring a mesh based on the encoded base mesh and the encoded displacement information, and a texture map processing step of generating a texture map bitstream by encoding a texture map generated based on the original mesh and the restored mesh.

[0022] According to embodiments, the displacement information processing step may include a step of converting the displacement information, a step of quantizing the converted displacement information, and a step of encoding the quantized displacement information into a displacement vector bitstream.

[0023] According to embodiments, the converting step may include converting the displacement information into a lifting manner.

[0024] According to embodiments, the step of converting to the lifting method may include a step of performing lifting transformation prediction by applying prediction weights to each component of the displacement information, and a step of performing lifting inverse transformation update by applying update weights to each component of the displacement information for which the prediction was performed.

[0025] According to embodiments, the lifting transformation update step may perform the lifting transformation update based on valence information calculated from the base mesh.

[0026] According to embodiments, a computer program stored on a computer-readable recording medium can be combined with a computer, which is hardware, to perform the above method.

[0027] The mesh data transmission method, mesh data transmission device, mesh data reception method, and mesh data reception device according to the embodiments can provide a quality 3D service.

[0028] The mesh data transmission method, mesh data transmission device, mesh data reception method, and mesh data reception device according to the embodiments can achieve various video codec methods.

[0029] The mesh data transmission method, mesh data transmission device, mesh data reception method, and mesh data reception device according to the embodiments can provide general-purpose 3D content such as autonomous driving services.

[0030] The mesh data transmission method, mesh data transmission device, mesh data reception method, and mesh data reception device according to the embodiments can improve the accuracy of the prediction process by performing adaptive lifting transformation and inverse transformation prediction and / or update using adaptive weights according to displacement vector components, thereby reducing the bit amount of the displacement vector and improving encoding performance.

[0031] The drawings are included to further understand the embodiments, and the drawings illustrate the embodiments together with the description related to the embodiments. For a better understanding of the various embodiments described below, reference should be made to the following description of the embodiments in conjunction with the following drawings, in which like reference numerals correspond to corresponding parts throughout the drawings.

[0032] FIG. 1 illustrates a system for providing dynamic mesh content according to embodiments.

[0033] Figure 2 illustrates a V-MESH compression method according to embodiments.

[0034] Figure 3 illustrates pre-processing of V-MESH compression according to embodiments.

[0035] Figure 4 illustrates a mid-edge subdivision method according to embodiments.

[0036] Figure 5 illustrates a displacement generation process according to embodiments.

[0037] Figure 6 illustrates an intra-frame encoding process of V-MESH data according to embodiments.

[0038] Figure 7 illustrates an inter-frame encoding process of V-MESH data according to embodiments.

[0039] Figure 8 illustrates a lifting conversion process for displacement according to embodiments.

[0040] Figure 9 illustrates a process of packing transformation coefficients into a 2D image according to embodiments.

[0041] Figure 10 illustrates an attribute transfer process of a V-MESH compression method according to embodiments.

[0042] Figure 11 illustrates an intra-frame decoding process of V-MESH data according to embodiments.

[0043] Figure 12 shows an inter-frame decoding processor of V-MESH data.

[0044] Fig. 13 is a drawing showing an example of a transmitting device according to embodiments.

[0045] Fig. 14 is a drawing showing an example of a receiving device according to embodiments.

[0046] Fig. 15 is a drawing showing another example of a transmitting device according to embodiments.

[0047] FIG. 16 is a block diagram showing an example of a displacement vector encoder that encodes displacement vectors or quantized displacement vector transform coefficients according to the present disclosure based on a 2D video codec.

[0048] FIG. 17 is a block diagram showing an example of a displacement vector encoder that encodes a displacement vector or a quantized displacement vector transform coefficient based on a zero run length according to the present disclosure.

[0049] FIG. 18 is a block diagram showing an example of a displacement vector encoder that arithmetically encodes a displacement vector or a quantized displacement vector transform coefficient according to the present disclosure.

[0050] FIG. 19 is a block diagram showing another example of a displacement vector encoder that encodes a displacement vector or a quantized displacement vector transform coefficient based on a zero run length according to the present disclosure.

[0051] FIG. 20 is a block diagram illustrating another example of a displacement vector encoder that arithmetic-encodes a displacement vector or a quantized displacement vector transform coefficient according to the present disclosure.

[0052] Fig. 21 is a flowchart showing an example of a process for converting a displacement vector in a displacement vector conversion unit according to embodiments.

[0053] Fig. 22 is a drawing showing another example of a receiving device according to embodiments.

[0054] Fig. 23 is a detailed block diagram showing an example of a displacement vector coordinate system inverse transformation unit according to embodiments.

[0055] Fig. 24 is a detailed block diagram showing another example of a displacement vector coordinate system inverse transformation unit according to embodiments.

[0056] Fig. 25 is a detailed block diagram showing an example of a displacement vector decoder according to embodiments.

[0057] Fig. 26 is a flowchart showing an example of a process of inversely transforming a displacement vector in a displacement vector inverse transform unit according to embodiments.

[0058] FIG. 27 is a diagram showing an example of the syntax structure of the lifting transformation parameters of the present disclosure.

[0059] FIG. 28 and FIG. 29 are diagrams showing other examples of the syntax structure of the lifting transformation parameters of the present disclosure.

[0060] FIG. 30 and FIG. 31 are diagrams showing another example of the syntax structure of the lifting transformation parameters of the present disclosure.

[0061] Figure 32 is a flowchart showing an example of a transmission method according to embodiments.

[0062] Figure 33 is a flowchart showing an example of a receiving method according to embodiments.

[0063] Preferred embodiments of the embodiments are described in detail, examples of which are illustrated in the accompanying drawings. The following detailed description, with reference to the accompanying drawings, is intended to illustrate preferred embodiments of the embodiments, rather than merely show embodiments that can be implemented according to the embodiments. The following detailed description includes details to provide a thorough understanding of the embodiments. However, it will be apparent to those skilled in the art that the embodiments may be practiced without these details.

[0064] While most of the terms used in the examples are commonly used in the field, some terms were arbitrarily selected by the applicant, and their meanings are described in detail in the following descriptions as needed. Therefore, the examples should be understood based on the intended meaning of the terms, not simply their names or meanings.

[0065] With the recent development of 3D data modeling and rendering technology, research on creating and processing 3D data is being conducted in various fields such as Virtual Reality (VR), Augmented Reality (AR), autonomous driving, Computer-Aided Design (CAD) / Computer-Aided Manufacturing (CAM), and Geographic Information Systems (GIS). 3D data can be represented as point clouds, meshes, etc., depending on the format of expression. Among these, a mesh is composed of geometric information expressing the coordinate values ​​of each vertex (or point), connection information indicating the connection relationship between vertices, a texture map expressing the color information of the mesh surface as 2D image data, and texture coordinates indicating mapping information between the surface of the mesh and the texture map. In the present disclosure, a mesh is defined as a dynamic mesh if one or more of the elements constituting the mesh change over time, and a static mesh if they do not change. In other words, dynamic mesh data may refer to mesh data having an object or movement.

[0066] Because dynamic mesh data has a large amount of data for elements that constitute the mesh compared to two-dimensional image data, technologies have been developed to efficiently compress this large amount of mesh data to store and transmit it.

[0067] FIG. 1 illustrates a system for providing dynamic mesh content according to embodiments.

[0068] The system of FIG. 1 includes a transmitting device (100) and a receiving device (110) according to embodiments. The transmitting device (100) may include a mesh video acquisition unit (101), a mesh video encoder (102), a file / segment encapsulator (103), and a transmitter (104). The receiving device (110) may include a receiving unit (111), a file / segment decapsulator (112), a mesh video decoder (113), and a renderer (114). Each component of FIG. 1 may correspond to hardware, software, a processor, and / or a combination thereof. Hereinafter, the mesh data transmitting device according to embodiments may be interpreted as a term referring to a 3D data transmitting device or transmitting device (100), or a mesh video encoder (hereinafter, referred to as an encoder) (102). The mesh data receiving device according to the embodiments may be interpreted as a term referring to a 3D data receiving device or receiving device (110), or a mesh video decoder (hereinafter, decoder) (113).

[0069] The system of FIG. 1 can perform video-based dynamic mesh compression and decompression.

[0070] Advances in 3D capture, modeling, and rendering have enabled users to consume diverse forms of 3D content, such as AR, XR, metaverse, and holograms, across multiple platforms and devices. 3D content increasingly represents objects with greater precision and realism, enabling users to enjoy immersive experiences. To achieve this, the creation and use of 3D models requires a significant amount of data. Among various types of 3D content, 3D meshes are widely used for efficient data utilization and realistic object representation. Embodiments include a series of processing steps in a system that utilizes such mesh content.

[0071] First, the method of compressing dynamic mesh data starts from the V-PCC (Video-based point cloud compression) standard technology for point cloud data. Point cloud data is data that has color information at the coordinates (X, Y, Z) of a vertex (or point). In the present disclosure, the coordinates (i.e., position information) of a vertex are referred to as geometry information, the color information of a vertex is referred to as attribute information, and the geometry information and attribute information are referred to as vertex information or point cloud data. The vertex information to which connectivity information between vertices is added is referred to as mesh data. When creating content, it can be created in the form of mesh data from the beginning. Alternatively, it can be used by converting it into mesh data by adding connectivity information to point cloud data.

[0072] Currently, the MPEG standards body defines two types of dynamic mesh data: Category 1: Mesh data with texture maps as color information. Category 2: Mesh data with vertex colors as color information.

[0073] Mesh coding standards for Category 1 data are currently under development, and work on Category 2 data standards is also planned for the future. The overall process for providing mesh content services may include acquisition, encoding, transmission, decoding, rendering, and / or feedback, as shown in Figure 1.

[0074] To provide mesh content services, 3D data acquired through multiple cameras or specialized cameras can be processed into mesh data types through a series of processes and then converted into video. The generated mesh video is then transmitted through a series of processes, and the receiving end can then reprocess the received data into mesh video and render it. This allows mesh video to be presented to users, who can then interact with the mesh content according to their intended intent.

[0075] A mesh compression system may include a transmitting device (100) and a receiving device (110) as shown in FIG. 1. The transmitting device (100) may encode mesh video to output a bitstream, and transmit the bitstream to the receiving device (110) in the form of a file or streaming (streaming segment) via a digital storage medium or a network. The digital storage medium may include various storage media such as USB, SD, CD, DVD, Blu-ray, HDD, and SSD.

[0076] In the above transmitting device (100), the encoder may be called a mesh video / video / picture / frame encoding device, and in the receiving device (110), the decoder may be called a mesh video / video / picture / frame decoding device. The transmitter may be included in a mesh video encoder. The receiver may be included in a mesh video decoder. The renderer (114) may include a display unit, and the renderer and / or the display unit may be configured as separate devices or external components. The transmitting device (100) and the receiving device (110) may further include separate internal or external modules / units / components for a feedback process.

[0077] Mesh data represents the surface of an object as a number of polygons. Each polygon is defined by vertices in 3D space and connection information that describes how the vertices are connected. It can also contain vertex attributes such as vertex color and normal. Mapping information that allows the surface of the mesh to be mapped to a 2D planar area can also be included in the attributes of the mesh. The mapping can be described as a set of parameter coordinates, generally called UV coordinates or texture coordinates, associated with the mesh vertices. Meshes contain 2D attribute maps, which can be used to store high-resolution attribute information such as textures, normals, and displacement. Here, displacement can be used interchangeably with displacement, displacement information, or displacement vectors (i.e., displacement vectors).

[0078] The mesh video acquisition unit (101) may include processing 3D object data acquired through a camera, etc. into a mesh data type having the attributes described above through a series of processes and generating a video composed of such mesh data. The mesh video may have attributes of the mesh, such as vertices, polygons, connection information between vertices, colors, normals, etc., that may change over time. A mesh video having attributes and connection information that change over time in this way may be expressed as a dynamic mesh video.

[0079] A mesh video encoder (102) can encode an input mesh video into one or more video streams. One video can include multiple frames, and one frame can correspond to a still image / picture. In this document, a mesh video can include a mesh image / frame / picture, and a mesh video can be used interchangeably with a mesh image / frame / picture. The mesh video encoder (102) can perform a Video-based Dynamic Mesh (V-Mesh) Compression procedure. The mesh video encoder (102) can perform a series of procedures such as prediction, transformation, quantization, and entropy coding for compression and coding efficiency. The encoded data (encoded video / image information) can be output in the form of a bitstream.

[0080] The file / segment encapsulator (103) can encapsulate encoded mesh video data and / or mesh video-related metadata in the form of a file, etc. Here, the mesh video-related metadata may be received from a metadata processing unit, etc. The metadata processing unit may be included in the mesh video encoder (102) or may be configured as a separate component / module. The file / segment encapsulator (103) can encapsulate the corresponding data in a file format such as ISOBMFF, or process it in the form of other DASH segments, etc. The file / segment encapsulator (103) may include mesh video-related metadata in the file format according to an embodiment. The mesh video metadata may be included in boxes at various levels in the ISOBMFF file format, for example, or may be included as data in a separate track within the file. Depending on the embodiment, the file / segment encapsulator (103) may encapsulate the mesh video related metadata itself into a file.

[0081] The transmission processing unit can process encapsulated mesh video data for transmission according to the file format. The transmission processing unit can be included in the transmission unit (104) or can be configured as a separate component / module. The transmission processing unit can process mesh video data according to any transmission protocol. The processing for transmission can include processing for transmission through a broadcast network or processing for transmission through broadband. According to an embodiment, the transmission processing unit can receive not only mesh video data but also mesh video-related metadata from the metadata processing unit and process it for transmission.

[0082] The transmission unit (104) can transmit encoded video / image information or data output in the form of a bitstream to the reception unit (111) of the reception device (110) via a digital storage medium or network in the form of a file or streaming. The digital storage medium can include various storage media such as USB, SD, CD, DVD, Blu-ray, HDD, SSD, etc. The transmission unit (104) can include an element for generating a media file through a predetermined file format and can include an element for transmission via a broadcasting / communication network. The reception unit (111) can extract the bitstream and transmit it to a decoding device.

[0083] The receiving unit (111) can receive mesh video data transmitted by a mesh data transmission device. Depending on the channel through which it is transmitted, the receiving unit (111) can receive mesh video data through a broadcast network, through a broadband, or through a digital storage medium.

[0084] The receiving processing unit can perform processing according to the transmission protocol on the received mesh video data. The receiving processing unit can be included in the receiving unit (111) or can be configured as a separate component / module. In order to correspond to the processing performed for transmission on the transmitting side, the receiving processing unit can perform the reverse process of the aforementioned transmission processing unit. The receiving processing unit can transfer the acquired mesh video data to the file / segment decapsulator (112) and transfer the acquired mesh video-related metadata to the metadata parser. The mesh video-related metadata acquired by the receiving processing unit can be in the form of a signaling table.

[0085] The file / segment decapsulator (112) can decapsulate mesh video data in the form of a file received from a receiving processing unit. The file / segment decapsulator (112) can decapsulate files according to ISOBMFF, etc., to obtain a mesh video bitstream or mesh video-related metadata (metadata bitstream). The obtained mesh video bitstream can be transmitted to the mesh video decoder (113), and the obtained mesh video-related metadata (metadata bitstream) can be transmitted to the metadata processing unit. The mesh video bitstream may include metadata (metadata bitstream). The metadata processing unit may be included in the mesh video decoder (113) or may be configured as a separate component / module. The mesh video-related metadata obtained by the file / segment decapsulator (112) may be in the form of a box or track within a file format. The file / segment decapsulator (112) may receive metadata required for decapsulation from the metadata processing unit, if necessary. The mesh video related metadata may be passed to the mesh video decoder (113) and used in the mesh video decoding procedure, or may be passed to the renderer (114) and used in the mesh video rendering procedure.

[0086] The mesh video decoder (113) can receive a bitstream and perform a reverse operation corresponding to the operation of the mesh video encoder (102) to decode the video / image. The decoded mesh video / image can be displayed through the display unit of the renderer (114). The user can view all or part of the rendered result through a VR / AR display or a general display.

[0087] The feedback process may include a process of transmitting various feedback information that may be acquired during the rendering / display process to the transmitter or to the decoder on the receiver. Interactivity may be provided in mesh video consumption through the feedback process. Depending on the embodiment, head orientation information, viewport information indicating the area that the user is currently viewing, etc. may be transmitted during the feedback process. Depending on the embodiment, the user may interact with things implemented in the VR / AR / MR / autonomous driving environment, in which case information related to the interaction may be transmitted to the transmitter or the service provider during the feedback process. Depending on the embodiment, the feedback process may not be performed.

[0088] Head orientation information can refer to information about the user's head position, angle, and movement. Based on this information, information about the area the user is currently viewing within the mesh video, i.e. viewport information, can be calculated.

[0089] Viewport information can be information about the area the user is currently viewing in the mesh video. This can be used to perform gaze analysis to determine how the user consumes the mesh video, which area of ​​the mesh video they are gazing at, and for how long. Gaze analysis can be performed on the receiving side and transmitted to the transmitting side through a feedback channel. Devices such as VR / AR / MR displays can extract the viewport area based on the user's head position / orientation, the vertical or horizontal FOV supported by the device, etc.

[0090] Depending on the embodiment, the aforementioned feedback information may not only be transmitted to the transmitter but may also be consumed by the receiver. That is, the aforementioned feedback information may be utilized to perform decoding, rendering, and other processes on the receiver. For example, head orientation information and / or viewport information may be utilized to preferentially decode and render only the mesh video for the area currently being viewed by the user.

[0091] This document relates to embodiments of dynamic mesh video compression as described above. The method / embodiment disclosed in this document can be applied to the Video-based Dynamic Mesh Compression (V-Mesh) standard of the Moving Picture Experts Group (MPEG) or the next-generation video / image coding standard. Dynamic mesh video compression is a method for processing mesh connection information and attributes that change over time, and it can perform lossy and lossless compression for various applications such as real-time communication, storage, free-viewpoint video, and AR / VR.

[0092] The dynamic mesh video compression method described below is based on MPEG's V-Mesh method.

[0093] In this document, picture / frame can generally mean a unit representing one video of a specific time period.

[0094] A pixel or pel can refer to the smallest unit that constitutes a picture (or image). Additionally, the term "sample" can be used as a counterpart to a pixel. A sample can generally represent a pixel or a pixel value, and can represent only the pixel / pixel value of the luma component, only the pixel / pixel value of the chroma component, or only the pixel / pixel value of the depth component.

[0095] A unit may represent a basic unit of image processing. A unit may include at least one of a specific region of a picture and information related to the region. In some cases, the term "unit" may be used interchangeably with terms such as "block" or "area." In general, an MxN block may include a set (or array) of samples (or sample array) or transform coefficients consisting of M columns and N rows.

[0096] As described above, the encoding process of Fig. 1 is as follows.

[0097] That is, the video-based dynamic mesh compression (V-Mesh) compression method can provide a method of compressing dynamic mesh video data based on 2D video codecs such as HEVC (High Efficiency Video Coding) and VVC (Versatile Video Coding). The V-Mesh compression process receives the following data as input and performs compression.

[0098] Input mesh: Contains the 3D coordinates of the vertices that make up the mesh, normal information for each vertex, mapping information that maps the mesh surface to a 2D plane, and connection information between the vertices that make up the surface. The mesh surface can be expressed as triangles or more polygons, and connection information between the vertices that make up each surface is stored according to a set shape. The input mesh can be saved in the OBJ file format.

[0099] Attribute map: (Hereinafter, texture map is also used in the same meaning): Contains information about the attributes of the mesh (color, normal, displacement, etc.), and stores data in the form of a mapping of the surface of the mesh onto a 2D image. Mapping which part (surface or vertex) of the mesh each data of this attribute map corresponds to is based on the mapping information contained in the input mesh. Since the attribute map has data for each frame of the mesh video, it can also be expressed as an attribute map video. The attribute map in the V-Mesh compression method mainly contains the color information of the mesh, and is saved in an image file format (PNG, BMP, etc.).

[0100] Material Library File: Contains information about the material attributes used in a mesh, and in particular, information that links the input mesh to its corresponding attribute map. It is saved in the Wavefront Material Template Library (MTL) file format.

[0101] In the V-Mesh compression method, the following data and information can be generated through the compression process.

[0102] Base mesh: The input mesh is simplified (decimated) through a pre-processing process, thereby expressing the objects of the input mesh using the minimum number of vertices determined by the user's standards.

[0103] Displacement: Displacement information used to express the input mesh as similarly as possible to the base mesh, and is expressed in the form of 3D coordinates.

[0104] Atlas information: This is the metadata required to reconstruct a mesh using base mesh, displacement, and attribute map information. It can be created and utilized as sub-mesh units (such as patches) that make up the mesh.

[0105] Referring to FIGS. 2 to 7, a method for encoding mesh position information (or vertex position information) is described, and referring to FIGS. 6 to 10, etc., a method for encoding attribute information (attribute map) by restoring mesh position information is described.

[0106] Figure 2 illustrates a V-MESH compression method according to embodiments.

[0107] Fig. 2 illustrates the encoding process of Fig. 1, and the encoding process may include a pre-processing process and an encoding process. The mesh video encoder (102) of Fig. 1 may include a pre-processor (200) and an encoder (201) as in Fig. 2. In addition, the transmitting device of Fig. 1 may be broadly referred to as an encoder, and the mesh video encoder (102) of Fig. 1 may be referred to as an encoder. The V-Mesh compression method may include a pre-processing process (Pre-processing, 200) and an encoding process (Encoding, 201) as in Fig. 2. The pre-processor (200) of Fig. 2 may be located in front of the encoder (201) of Fig. 2. The pre-processor (200) and the encoder (201) of Fig. 2 may be referred to as a single encoder.

[0108] The pre-processor (200) can receive a static of a dynamic mesh (M(i)) and / or an attribute map (A(i)). The pre-processor (200) can generate a base mesh (m(i)) and / or a displacement (or displacement) (d(i)) through pre-processing. The pre-processor (200) can receive feedback information from the encoder (201) and generate the base mesh and / or the displacement based on the feedback information.

[0109] The encoder (201) can receive a base mesh (m(i)), a displacement (d(i)), a static of a dynamic mesh (M(i)), and / or an attribute map (A(i)). In the present disclosure, at least one of the base mesh (m(i)), the displacement (d(i)), the static of a dynamic mesh (M(i)), and / or the attribute map (A(i)) can be referred to as mesh-related data. The encoder (201) can encode the mesh-related data to generate a compressed bitstream.

[0110] Figure 3 illustrates a pre-processing process of V-MESH compression according to embodiments.

[0111] Fig. 3 illustrates the configuration and operation of the preprocessor of Fig. 2. In Fig. 3, the input mesh may include a static of a dynamic mesh (M(i)) and / or an attribute map (A(i)). In addition, the input mesh may include three-dimensional coordinates of vertices constituting the mesh, normal information of each vertex, mapping information for mapping the mesh surface to a 2D plane, connection information between vertices constituting the surface, etc.

[0112] Fig. 3 shows a process of performing pre-processing on an input mesh. The pre-processing process (200) may largely include four steps: 1) GoF (Group of Frame) generation, 2) Mesh Decimation, 3) UV parameterization, and 4) Fitting subdivision surface (300). According to embodiments, GoF generation may be referred to as a GoF generation process or a GoF generation unit, mesh simplification may be referred to as a mesh simplification process or a mesh simplification unit, UV parameterization may be referred to as a UV parameterization process or a UV parameterization unit, and the fitting subdivision surface may be referred to as a fitting subdivision surface process or a fitting subdivision surface unit. The pre-processor (200) can generate displacement and / or base meshes from the received input mesh and transmit them to the encoder (201). The pre-processor (200) can transmit GoF information associated with GoF generation to the encoder (201).

[0113] Below, each step of Fig. 3 is described.

[0114] GoF Generation: This is the process of generating a reference structure for mesh data. If the number of vertices, the number of texture coordinates, the vertex connection information, and the texture coordinate connection information of the mesh of the previous frame and the current mesh are all the same, the previous frame can be set as the reference frame. That is, if only the vertex coordinate values ​​are different between the current input mesh and the reference input mesh, the encoder (201) can perform inter frame encoding. Otherwise, intra frame encoding is performed for the corresponding frame.

[0115] Mesh Decimation: This process simplifies the input mesh to create a simplified mesh, or base mesh. Vertices to be removed from the original mesh are selected based on user-defined criteria, and the selected vertices and the triangles connected to them can be removed.

[0116] In the process of performing mesh simplification (Mesh decimation), the input mesh (voxelized), target triangle ratio (TTR), and minimum triangle component (CCCount) information are passed as input, and the simplified mesh (decimated mesh) can be obtained as output. In this process, connected triangle components smaller than the set minimum triangle component (CCCount) can be removed.

[0117] UV parameterization: This is the process of mapping a 3D surface of a decimated mesh into a texture domain. Parameterization can be performed using the UVAtlas tool. This process generates mapping information, which maps each vertex of the decimated mesh to a location on a 2D image. This mapping information is expressed and stored as texture coordinates, and through this process, the final base mesh is created.

[0118] Fitting subdivision surface (300): This is a process of performing subdivision on a decimated mesh (i.e., a simplified mesh having texture coordinates). The displacement and base mesh generated through this process are output to the encoder (201). A user-defined method, such as a mid-edge method, may be applied as the subdivision method. A fitting process is performed so that the input mesh and the mesh on which the subdivision has been performed become similar to each other. In the present disclosure, the mesh on which the fitting process has been performed is referred to as a fitted subdivision mesh (or fitted subdivision mesh).

[0119] Figure 4 illustrates a mid-edge subdivision method according to embodiments.

[0120] Figure 4 illustrates the mid-edge method of the fitting subdivision surface described in Figure 3. Referring to Figure 4, an original mesh containing four vertices is subdivided to generate a sub-mesh. A sub-mesh can be generated by creating a new vertex in the middle of the edge between the vertices. Then, a fitting process is performed so that the input mesh and the sub-mesh become similar to each other, thereby generating a fitted sub-division mesh.

[0121] When a fitted subdivided mesh (hereinafter referred to as a fitted subdivided mesh) is generated, displacement is calculated using this result and a pre-compressed and decoded base mesh (hereinafter referred to as a reconstructed base mesh). That is, the reconstructed base mesh is subdivided in the same way as the fitting subdivision surface. The difference in position of each vertex between this result and the fitted subdivided mesh is the displacement for each vertex. Since displacement represents the position difference in three-dimensional space, it is also expressed as a value in the (x, y, z) space of a Cartesian coordinate system. Depending on the user input parameters, the (x, y, z) coordinate values ​​can be converted to (normal, tangential, bi-tangential) coordinate values ​​of the local coordinate system.

[0122] Fig. 5 illustrates a displacement generation process according to embodiments. The displacement generation process of Fig. 5 may be performed in a pre-processor (200) or in an encoder (201).

[0123] FIG. 5 illustrates in detail the displacement calculation method of the fitting subdivision surface (300) as described in FIG. 4.

[0124] An encoder and / or pre-processor according to embodiments may include 1) a subdivision unit, 2) a local coordinate system calculation unit, and 3) a displacement calculation unit. The subdivision unit may perform subdivision on a reconstructed base mesh to generate a subdivided reconstructed base mesh. Here, the restoration of the base mesh may be performed in the pre-processor (200) or in the encoder (201). The local coordinate system calculation unit may receive a fitted subdivision mesh and a subdivided reconstructed base mesh, and may convert a coordinate system of the mesh into a local coordinate system based on the fitted subdivision mesh and the subdivided reconstructed base mesh. The local coordinate system calculation operation may be optional. The displacement calculation unit may calculate a positional difference between the fitted subdivision mesh and the subdivided reconstructed base mesh. For example, a positional difference value between vertices of two input meshes may be generated. The vertex positional difference value becomes a displacement.

[0125] The mesh data transmission method and device according to the embodiments can encode mesh data as follows. Mesh data is a term including point cloud data. Point cloud data (which may be referred to as point cloud for short) according to the embodiments can refer to data including vertex coordinates (or geometry information) and color information (or attribute information). In addition, geometry images, attribute images, occupancy maps, and additional information (or patch information) generated through patch generation and packing based on vertex coordinates and color information are also referred to as point cloud data. Therefore, point cloud data including connection information can be referred to as mesh data. In this document, point cloud and mesh data can be used interchangeably.

[0126] The V-Mesh compression (reconstruction) method according to the embodiments may include intra frame encoding (Fig. 6) and inter frame encoding (Fig. 7).

[0127] Based on the results of the GoF generation described above, intra-frame encoding or inter-frame encoding is performed. In the case of intra-encoding, the data to be compressed may be a base mesh, displacement, attribute map, etc. In the case of inter-encoding, the data to be compressed may be a displacement, attribute map, and a motion field between a reference base mesh and the current base mesh.

[0128] Fig. 6 illustrates an intra-frame encoding process of a V-MESH compression method according to embodiments. Each component for the intra-frame encoding process of Fig. 6 corresponds to hardware, software, a processor, and / or a combination thereof.

[0129] The encoding process of FIG. 6 details the encoding of the mesh video encoder (102) of FIG. 1. That is, it shows the configuration of the mesh video encoder (102) when the encoding of FIG. 1 is an intra-frame method. The encoder of FIG. 6 may include a pre-processor (200) and / or an encoder (201). The pre-processor (200) and encoder (201) of FIG. 6 may correspond to the pre-processor (200) and encoder (201) of FIG. 3.

[0130] The preprocessor (200) can receive an input mesh and perform the preprocessing described above. The preprocessing can generate a base mesh and / or a fitted subdivision mesh.

[0131] The quantizer (411) of the encoder (201) can quantize the base mesh and / or the fitted subdivided mesh. The static mesh encoder (412) can encode the static mesh (i.e., the quantized base mesh) and generate a bitstream (i.e., a compressed base mesh bitstream) including the encoded base mesh. The static mesh decoder (413) can decode the encoded static mesh (i.e., the encoded base mesh). The inverse quantizer (414) can inversely quantize the quantized static mesh (i.e., the base mesh) to output a reconstructed (or restored) base mesh. The displacement calculation unit (415) can generate displacements (or displacements) based on the reconstructed static mesh (i.e., the base mesh) and the fitted subdivided mesh. According to embodiments, the displacement calculation unit (415) calculates displacement, which is the position difference between each vertex of the subdivided base mesh and the fitted subdivided mesh after subdividing (or refining) the restored base mesh. In other words, the displacement is a displacement vector, which is the position difference between the vertices of the two meshes so that the fitted subdivided (or refining) mesh becomes similar to the original mesh. The forward linear lifting unit (416) can perform lifting transformation on the input displacement to generate lifting coefficients (or transform coefficients). The quantizer (417) can quantize the lifting coefficients. The image packing unit (418) can pack an image based on the quantized lifting coefficients. The video encoder (419) can encode the packed image. That is, the quantized lifting coefficients are packed into one frame as a 2D image by the image packing unit (418), compressed through the video encoder (419), and output as a displacement bitstream (i.e., compressed displacement bitstream).

[0132] A video decoder (420) decodes a compressed displacement bitstream. An image unpacking unit (421) can perform unpacking on the decoded displacement frame to output quantized lifting coefficients. A dequantizer (422) can dequantize the quantized lifting coefficients. An inverse linear lifting unit (423) applies inverse lifting to the inverse quantized lifting coefficients to generate restored displacement. A mesh restoration unit (424) reconstructs and deforms a mesh using the restored displacement output from the inverse linear lifting unit (423) and the restored base mesh (or subdivided restored base mesh) output from the inverse quantization unit (414). The present disclosure refers to the reconstructed and deformed mesh as a restored deformed mesh.

[0133] The attribute transfer (425) receives an input mesh and / or an input attribute map, and regenerates an attribute map based on the restored deformed mesh. The attribute map refers to a texture map corresponding to attribute information among mesh data components, and in the present disclosure, the attribute map and the texture map may be used interchangeably. The push-pull padding (426) may pad data in the attribute map based on the push-pull method. The color space conversion unit (427) may convert the space of the color component of the attribute map. For example, the attribute map may be converted from an RGB color space to a YUV color space. The video encoder (428) may encode the attribute map and output it as a compressed attribute bitstream.

[0134] A multiplexer (430) can generate a compressed bitstream by multiplexing a compressed base mesh bitstream, a compressed displacement bitstream, and a compressed attribute bitstream.

[0135] In Fig. 6, the displacement calculation unit (415) may be included in the pre-processor (200). In addition, at least one of the quantizer (411), the static mesh encoder (412), the static mesh decoder (413), and the inverse quantizer (414) may be included in the pre-processor (200).

[0136] As described in FIG. 6, the intra-frame encoding method includes base mesh encoding (also called static mesh encoding). That is, when performing intra-frame encoding on the current input mesh frame, the base mesh generated in the pre-processing process of the pre-processor (200) can be encoded using a static mesh compression technology in a static mesh encoder (412) after undergoing a quantization process in a quantizer (411). In the V-Mesh compression method, for example, Draco technology is applied to base mesh encoding, and vertex position information, mapping information (texture coordinates), vertex connection information, etc. of the base mesh become compression targets.

[0137] The encoder of Fig. 6 generates a bitstream by compressing the base mesh, displacement, and attributes within the frame, and the encoder of Fig. 7 generates a bitstream by compressing the motion, displacement, and attributes between the current frame and the reference frame.

[0138] Fig. 7 illustrates an inter-frame encoding process of a V-MESH compression method according to embodiments. Each component for the inter-frame encoding process of Fig. 7 corresponds to hardware, software, a processor, and / or a combination thereof.

[0139] The encoding process of Fig. 7 details the encoding of Fig. 1. That is, it shows the configuration of an encoder when the encoding of Fig. 1 is an inter-frame method. The encoder of Fig. 7 may include a pre-processor (200) and / or an encoder (201). The pre-processor (200) and encoder (201) of Fig. 7 may correspond to the pre-processor (200) and encoder (201) of Fig. 3.

[0140] For a description of the components corresponding to the encoding operation of FIG. 6 among the encoding operations of FIG. 7, refer to the description of FIG. 6. That is, the operation of the quantizer (511), displacement calculation unit (515), wavelet transformer (516), quantizer (517), image packing unit (518), video encoder (519), video decoder (520), image unpacking unit (521), inverse quantizer (522), inverse wavelet transformer (523), mesh restoration unit (524), attribute transfer (525), push-pull padding (526), ​​color space conversion unit (527), video encoder (528), and multiplexer (530) of FIG. 7 is similar to that of the quantizer (411), static mesh encoder (412), static mesh decoder (413), inverse quantizer (414), displacement calculation unit (415), forward linear lifting unit (416), quantizer (417), image Since the operations described in the packing unit (418), video encoder (419), video decoder (420), image unpacking unit (421), inverse quantizer (422), inverse linear lifting unit (423), mesh restoration unit (424), attribute transfer (425), push-pull padding (426), color space conversion unit (427), video encoder (428), and multiplexer (430) are the same or similar, a detailed description thereof is omitted in FIG. 7 to avoid redundant description.

[0141] In Fig. 7, for inter-frame based encoding, the motion encoder (512) can obtain a motion vector between the two base meshes based on the restored quantized reference base mesh and the quantized current base mesh, and then encode the motion vector to output a compressed motion bitstream. The motion encoder (512) can be referred to as a motion vector encoder. The base mesh restoration unit (513) can restore the base mesh based on the restored quantized reference base mesh and the encoded motion vector. The restored base mesh is dequantized in the dequantizer (514) and then output to the displacement calculation unit (515).

[0142] In Fig. 7, the displacement calculation unit (515) may be included in the pre-processor (200). In addition, at least one of the quantizer (511), the motion encoder (512), the base mesh restoration unit (513), and the inverse quantizer (514) may be included in the pre-processor (200).

[0143] As described in Fig. 7, the inter-frame encoding method may include motion field encoding (also called motion vector encoding). Inter-frame encoding may be performed when a one-to-one correspondence of vertices is established between a reference mesh and a current input mesh, and only the position information of the vertices is different. When performing inter-frame encoding, instead of compressing the base mesh, the difference between the vertices of the reference base mesh and the current base mesh, i.e., the motion field (also called motion vector), may be calculated and encoded to encode this information. The reference base mesh is the result of quantizing the already decoded base mesh data and is determined according to the reference frame index determined in the GoF generation. The motion field may also be encoded as a value. Alternatively, the predicted motion field can be calculated by averaging the motion fields of the restored vertices among the vertices connected to the current vertex, and the residual motion field, which is the difference between the predicted motion field value and the motion field value of the current vertex, can be encoded. This residual motion field value can be encoded using entropy coding.The process of encoding displacement and attribute maps, excluding the motion field encoding process of inter frame encoding, is the same as the structure of the intra frame encoding method except for the base mesh encoding.

[0144] Figure 8 illustrates a lifting conversion process for displacement according to embodiments.

[0145] Figure 9 illustrates a process of packing transformation coefficients (or lifting coefficients) according to embodiments into a 2D image.

[0146] Figures 8 and 9 illustrate the process of transforming displacement and packing transform coefficients of the encoding process of Figures 6 and 7, respectively.

[0147] The encoding method according to the embodiments includes displacement encoding.

[0148] After base mesh encoding and / or motion field encoding, a reconstructed base mesh is generated through restoration and dequantization, and the displacement between the result of performing subdivision on the reconstructed base mesh and the fitted subdivided mesh generated through the fitting subdivision surface can be calculated (see 415 in FIG. 6 or 515 in FIG. 7). For effective encoding, a data transform process such as wavelet transform can be applied to the displacement information (see 416 in FIG. 6 or 516 in FIG. 7).

[0149] FIG. 8 shows a process of transforming displacement information using a lifting transform in the forward linear lifting unit (416) of FIG. 6 or the wavelet transformer (516) of FIG. 7. For example, a linear wavelet-based lifting transform may be performed. The transform coefficients generated through the transform process are quantized in a quantizer (417 or 517) and then packed into a 2D image through an image packing unit (418 or 518) as in FIG. 9. The transform coefficients are configured as one block for every 256 (= 16×16) units, and each block can be packed in a z-scan order. The horizontal number of blocks is fixed to 16, but the vertical number of blocks can be determined according to the number of vertices of the subdivided base mesh. Transform coefficients can be packed by aligning them with Morton codes within a single block. The packed images generate displacement videos for each GoF unit, and these displacement videos can be encoded using a conventional video compression codec in a video encoder (419 or 519).

[0150] Referring to FIG. 8, the base mesh (original) may include vertices and edges for LoD0. A first subdivision mesh generated by dividing (or subdividing) the base mesh includes vertices generated by further dividing (or subdividing) edges of the base mesh. The first subdivision mesh includes vertices for LoD0 and vertices for LoD1. LoD1 includes the subdivided vertices and the vertices of the base mesh (LoD0). The first subdivision mesh may be further divided (or subdivided) to generate a second subdivision mesh. The second subdivision mesh includes LoD2. LoD2 includes base mesh vertices (LoD0), LoD1 including vertices further divided (or subdivided) from LoD0, and vertices further divided (or subdivided) from LoD1. LoD is a level of detail that indicates the degree of detail of mesh data content. As the level index increases, the distance between vertices becomes closer and the level of detail increases. In other words, the smaller the LoD value, the lower the detail of the mesh data content, and the larger the LoD value, the higher the detail of the mesh data content. LoD N contains the vertices included in the previous LoDN-1 as is. When a mesh (or vertex) is further divided through subdivision, the mesh can be encoded based on a prediction and / or update method by considering the previous vertices v1, v2 and the subdivided vertex v. Instead of directly encoding information about the current LoD N, a residual value between the previous LoD N-1 can be generated and the mesh can be encoded using the residual value to reduce the size of the bitstream. The prediction process means predicting the current vertex v using the previous vertices v1 and v2. Since adjacent subdivision meshes have similar data, efficient encoding can be achieved by utilizing this property.Current vertex position information is predicted as a residual of previous vertex position information, and the previous vertex position information is updated through the residual. In the present disclosure, vertex, apex, and point may be used with the same meaning. In addition, LoDs may be defined during the subdivision process of the base mesh. According to embodiments, the subdivision process of the base mesh may be performed in the pre-processor (200) or in a separate component / module.

[0151] Referring to FIG. 9, a vertex has a transform coefficient (also called a lifting coefficient) generated through a lifting transformation. The transform coefficient of a vertex related to a lifting transformation can be packed into an image by an image packing unit (418 or 518) and then encoded by a video encoder (419 or 519).

[0152] Figure 10 illustrates an attribute transfer process of a V-MESH compression method according to embodiments.

[0153] According to the embodiments, FIG. 10 shows the detailed operation of the attribute transfer (425 or 525) of the encoding of FIG. 6, FIG. 7, etc.

[0154] Encoding according to embodiments includes attribute map encoding. According to embodiments, attribute map encoding may be performed in the video encoder (428) of FIG. 6 or the video encoder (528) of FIG. 7.

[0155] According to embodiments, in the present disclosure, the encoder compresses information about the input mesh through base mesh encoding (i.e., intra encoding), motion field encoding (i.e., inter encoding), and displacement encoding. In the encoding process, the compressed input mesh is restored through base mesh decoding (intra frame), motion field decoding (inter frame), and displacement video decoding processes, and the restored result, the reconstructed deformed mesh (hereinafter referred to as Recon. deformed mesh), is used to compress the input attribute map as shown in FIGS. 6 and 7. The reconstructed deformed mesh (Recon. deformed mesh) has position information of vertices, texture coordinates, and corresponding connection information, but does not have color information corresponding to the texture coordinates. Therefore, as shown in Fig. 10, in the V-Mesh compression method, a new attribute map having color information corresponding to the texture coordinates of the reconstructed deformed mesh is regenerated through the attribute transfer process of attribute transfer (425 or 525).

[0156] According to embodiments, attribute transfer (425 or 525) first checks whether each point P(u, v) of a 2D texture domain belongs to a texture triangle of a reconstructed deformed mesh, and if it exists in a texture triangle T, the barycentric coordinate of P(u, v) according to the triangle T ( , , ) is calculated. And the 3D vertex positions of triangle T and ( , , ) is used to compute the 3D coordinates M(x, y, z) of P(u, v). Find the vertex coordinates M'(x', y', z') and the triangle T' containing this vertex that corresponds to the most similar position to the calculated M(x, y, z) in the input mesh domain. Then, the center of mass coordinates of M'(x', y', z') in this triangle T' ( ', ', ') is calculated. The texture coordinates corresponding to the three vertices of Triangle T' and ( ', ', ') is used to calculate the texture coordinates (u', v'), and the color information corresponding to these coordinates is found in the input attribute map. The color information found in this way is immediately assigned to the pixel location (u, v) of the new attribute map. If P(u, v) does not belong to any triangle, the pixel at that location in the new attribute map can be filled with a color value using a padding algorithm, such as the push-pull algorithm of push-pull padding (426 or 526).

[0157] The new attribute map generated through attribute transfer (425 or 525) is grouped into GoF units to form an attribute map video, which is compressed using the video codec of the video encoder (428 or 528).

[0158] Referring to Figure 10, the reference relationship between the input mesh, the input attribute map, the reconstructed deformed mesh, and the regenerated attribute map can be seen.

[0159] The decoding process of Fig. 1 can perform the reverse process of the corresponding process of the encoding process of Fig. 1. The specific decoding process is as follows.

[0160] FIG. 11 illustrates an intra-frame decoding (or intra-decoding) process of V-Mesh technology according to embodiments.

[0161] Fig. 11 illustrates the configuration and operation of the mesh video decoder (113) of the receiving device of Fig. 1. In addition, Fig. 11 can restore mesh data by performing the reverse process of the intra-frame encoding process of Fig. 6. Each component for the intra-frame decoding process of Fig. 11 corresponds to hardware, software, and / or a combination thereof.

[0162] First, the bitstream (i.e., compressed bitstream) received and input to the demultiplexer (611) of the intra frame decoding unit (610) can be separated into a mesh substream, a displacement substream, an attribute map substream, and a substream containing patch information of the mesh, such as V-PCC / V3C. The term V-PCC (Video-based Point Cloud Compression) used in this document can be used with the same meaning as V3C (Visual Volumetric Video-based Coding), and the two terms can be used interchangeably. Therefore, the term V-PCC in this document can be interpreted as the term V3C.

[0163] According to embodiments, the mesh sub-stream may be input to a static mesh decoder (612) and decoded, the displacement sub-stream may be input to a video decoder (613) and decoded, and the attribute map sub-stream may be input to a video decoder (617) and decoded.

[0164] According to embodiments, the mesh sub-stream is decoded through a decoder (612) of a static mesh codec used in encoding, such as Google Draco, and as a result, a reconstructed quantized base mesh, for example, connection information, vertex geometry information, vertex texture coordinates, etc. of the base mesh can be reconstructed.

[0165] According to embodiments, the displacement sub-stream is decoded into displacement video through a decoder (613) of a video compression codec used in encoding, and is restored as displacement information for each vertex (i.e., Recon. displacements) through an image unpacking process of an image unpacking unit (614), an inverse quantization process of an inverse quantizer (615), and an inverse transform process of an inverse linear lifting unit (616).

[0166] According to embodiments, the base mesh restored by the static mesh decoder (612) is inverse quantized by the inverse quantizer (620) and then output to the mesh restoration unit (630). The mesh restoration unit (630) reconstructs and restores the deformed mesh (i.e., decoded mesh) through the restored displacement output from the inverse linear lifting unit (616) and the restored base mesh output from the inverse quantizer (620). That is, the inverse quantized restored base mesh is combined with the restored displacement information to generate the final decoded mesh. In the present disclosure, the final decoded mesh is referred to as a reconstructed deformed mesh.

[0167] According to embodiments, an attribute map sub-stream is decoded through a decoder (617) corresponding to a video compression codec used in encoding, and then restored to a final attribute map (i.e., decoded attribute map) through a color conversion unit (640) through processes such as color format conversion and color space conversion.

[0168] According to embodiments, the restored decoded mesh and decoded attribute map can be utilized by the receiver as final mesh data that can be utilized by the user.

[0169] Referring to FIG. 11, the received compressed bitstream includes patch information, a mesh substream, a displacement substream, and an attribute map substream. A substream is interpreted as a term referring to a part of a bitstream included in a bitstream. The bitstream includes patch information (data), mesh information (data), displacement information (data), and attribute map information (data).

[0170] As described above, the decoder of FIG. 11 performs the following intra-frame decoding operations. The static mesh decoder (612) decodes the mesh sub-stream to generate a reconstructed quantized base mesh, and the inverse quantizer (620) applies the quantization parameters of the quantizer inversely to generate the reconstructed base mesh. The video decoder (613) decodes the displacement sub-stream, the image unpacking unit (614) unpacks the images of the decoded displacement video, and the inverse quantizer (615) inversely quantizes the quantized images. The inverse linear lifting unit (616) applies a lifting transform in the reverse process of the encoder to generate the reconstructed displacement. The mesh restoration unit (630) generates a reconstructed deformed mesh based on the reconstructed base mesh and the reconstructed displacement. The video decoder (617) decodes the attribute map sub-stream, and the color conversion unit (640) converts the color format and / or space of the decoded attribute map to generate a decoded attribute map.

[0171] Figure 12 illustrates the inter-frame decoding (or inter-decoding) process of V-Mesh technology.

[0172] Fig. 12 illustrates the configuration and operation of the mesh video decoder (113) of the receiving device of Fig. 1. In addition, Fig. 12 can restore mesh data by performing the reverse process of the inter-frame encoding process of Fig. 7. Each component for the inter-frame decoding process of Fig. 12 corresponds to hardware, software, and / or a combination thereof.

[0173] First, the bitstream received and input to the demultiplexer (711) of the intra frame decoding unit (710) can be separated into a motion sub-stream (also called a motion sub-stream or motion vector sub-stream), a displacement sub-stream, an attribute map sub-stream, and a sub-stream including patch information of a mesh such as V3C / V-PCC.

[0174] According to embodiments, a motion sub-stream may be input to a motion decoder (712) and decoded, a displacement sub-stream may be input to a video decoder (713) and decoded, and an attribute map sub-stream may be input to a video decoder (717) and decoded.

[0175] According to embodiments, a motion sub-stream is decoded through entropy decoding and inverse prediction processes in a motion decoder (712) and restored into motion information (or motion vector information). A base mesh restoration unit (718) combines the restored motion information with a reference base mesh that has already been restored and stored to generate a reconstructed quantized base mesh for the current frame. An inverse quantizer (720) applies inverse quantization to the restored quantized base mesh to generate a reconstructed base mesh. A video decoder (713) decodes a displacement sub-stream, an image unpacking unit (714) unpacks an image of the decoded displacement video, and an inverse quantizer (715) inversely quantizes a quantized image. The inverse linear lifting unit (716) applies a lifting transformation in the reverse process of the encoder to generate a restored displacement. The mesh restoration unit (730) generates a reconstructed deformed mesh, i.e., a final decoded mesh, based on the restored base mesh and the restored displacement.

[0176] According to embodiments, the video decoder (717) decodes the attribute map sub-stream in the same manner as intra decoding, and the color conversion unit (740) converts the color format and / or space of the decoded attribute map to generate a decoded attribute map. The decoded mesh and the decoded attribute map can be utilized by the receiver as final mesh data that can be utilized by the user.

[0177] Referring to Fig. 12, the bitstream includes motion information (also called motion vectors), displacement, and an attribute map. Since Fig. 12 performs inter-frame decoding, it further includes a process of decoding inter-frame motion information. The motion information is decoded, and a restored quantized base mesh for the motion information is generated based on the reference base mesh, thereby generating a restored base mesh. For a description of the operation of Fig. 12, which is identical to that of Fig. 11, refer to the description of Fig. 11.

[0178] Fig. 13 illustrates a mesh data transmission device according to embodiments.

[0179] FIG. 13 corresponds to the transmitting device (100) or mesh video encoder (102) of FIG. 1, the encoder (preprocessor and encoder) of FIG. 2, FIG. 6, or FIG. 7, and / or a transmitting encoding device corresponding thereto. Each component of FIG. 13 corresponds to hardware, software, a processor, and / or a combination thereof.

[0180] The operation process of a transmitter for compressing and transmitting dynamic mesh data using V-Mesh compression technology may be as shown in Fig. 13. The transmitter of Fig. 13 may perform an intra-frame encoding (or intra-encoding or intra-screen encoding) process and / or an inter-frame encoding (or inter-encoding or inter-screen encoding) process.

[0181] The pre-processor (811) receives the original mesh as input and generates a simplified mesh (decimated mesh) (or base mesh) and a fitted decimated mesh (or subdivision). Simplification can be performed based on the target number of vertices or target number of polygons that constitute the mesh. Parameterization, which generates texture coordinates and texture connection information per vertex, can be performed on the simplified mesh. For example, parameterization is a process of mapping a 3D surface to a texture domain for the decimated mesh. If parameterization is performed using the UVAtlas tool, mapping information is generated that can identify where each vertex of the decimated mesh can be mapped on a 2D image. The mapping information is expressed and stored as texture coordinates, and the final base mesh is generated through this process. In addition, the work of quantizing the mesh information in floating-point form into fixed-point form can be performed. This result can be output as a base mesh to a motion vector encoder (813) or a static mesh encoder (814) through a switching unit (812). The pre-processor (811) can perform mesh subdivision on the base mesh to generate additional vertices. Depending on the subdivision method, vertex connection information, texture coordinates, and texture coordinate connection information including the added vertices can be generated. The pre-processor (811) can generate a fitted subdivided mesh by adjusting the vertex positions so that the subdivided mesh becomes similar to the original mesh.

[0182] According to embodiments, the base mesh is output to a motion vector encoder (813) via a switching unit (812) when performing inter-encoding for the corresponding mesh frame, and is output to a static mesh encoder (814) via a switching unit (812) when performing intra-encoding for the corresponding mesh frame. The motion vector encoder (813) may be referred to as a motion encoder.

[0183] For example, when performing intra-encoding (or intra-frame encoding) on ​​the corresponding mesh frame, the base mesh can be compressed through a static mesh encoder (814). In this case, encoding can be performed on connection information, vertex geometry information, vertex texture information, normal information, etc. of the base mesh. The base mesh bitstream generated through encoding is transmitted to a multiplexer (823).

[0184] As another example, when performing inter-encoding (or inter-frame encoding) for the corresponding mesh frame, the motion vector encoder (813) can receive a base mesh and a reference reconstructed base mesh (or a reconstructed quantized reference base mesh) as input, calculate a motion vector between the two meshes, and encode the value. In addition, the motion vector encoder (813) can perform prediction based on connection information using a previously encoded / decoded motion vector as a predictor, and encode a residual motion vector obtained by subtracting the predicted motion vector from the current motion vector. The motion vector bitstream generated through encoding is transmitted to the multiplexer (823).

[0185] The base mesh restoration unit (815) can receive the base mesh encoded by the static mesh encoder (814) or the motion vector encoded by the motion vector encoder (813) and generate a reconstructed base mesh. For example, the base mesh restoration unit (815) can perform static mesh decoding on the base mesh encoded by the static mesh encoder (814) to restore the base mesh. At this time, quantization can be applied before the static mesh decoding, and inverse quantization can be applied after the static mesh decoding. As another example, the base mesh restoration unit (815) can restore the base mesh based on the reconstructed quantized reference base mesh and the motion vector encoded by the motion vector encoder (813). The reconstructed base mesh is output to the displacement calculation unit (816) and the mesh restoration unit (820).

[0186] The displacement calculation unit (816) can perform mesh refinement on the restored base mesh. The displacement calculation unit (816) can calculate a displacement vector, which is a difference value between the vertex positions of the restored base mesh and the fitted subdivision (or refined) mesh generated by the pre-processor (811). At this time, the displacement vector can be calculated as many times as the number of vertices of the refined mesh. The displacement calculation unit (816) can convert the displacement vector calculated in the 3D Cartesian coordinate system into a local coordinate system based on the normal vector of each vertex.

[0187] The displacement vector video generation unit (817) may include a linear lifting unit, a quantizer, and an image packing unit. That is, in the displacement vector video generation unit (817), the linear lifting unit may transform the displacement vector for effective encoding. The transformation may be performed by a lifting transformation, a wavelet transformation, etc., according to embodiments. In addition, quantization may be performed in a quantizer on the transformed displacement vector value, i.e., the transform coefficient. At this time, a different quantization parameter may be applied to each axis of the transform coefficient, and the quantization parameter may be derived according to an encoder / decoder agreement. The transformed and quantized displacement vector information may be packed into a 2D image in the image packing unit. The displacement vector video generation unit (817) may generate a displacement vector video by bundling packed 2D images for each frame, and the displacement vector video may be generated for each GoF (Group of Frame) unit of the input mesh.

[0188] The displacement vector video encoder (818) can encode the generated displacement vector video using a video compression codec. The generated displacement vector video bitstream is transmitted to a multiplexer (823).

[0189] The displacement vector restoration unit (819) may include a video decoder, an image unpacking unit, an inverse quantizer, and an inverse linear lifting unit. That is, the displacement vector restoration unit (819) performs decoding on an encoded displacement vector in the video decoder, performs image unpacking in the image unpacking unit, performs inverse quantization in the inverse quantizer, and then performs inverse transformation in the inverse linear lifting unit to restore the displacement vector. The restored displacement vector is output to the mesh restoration unit (820). The mesh restoration unit (820) restores a deformed mesh based on the base mesh restored by the base mesh restoration unit (815) and the displacement vector restored by the displacement vector restoration unit (819). The restored mesh (or referred to as a restored deformed mesh) has restored vertices, connection information between vertices, texture coordinates, and connection information between texture coordinates.

[0190] The texture map video generation unit (821) can regenerate a texture map based on the texture map (or attribute map) of the original mesh and the restored deformed mesh output from the mesh restoration unit (820). According to embodiments, the texture map video generation unit (821) can assign color information per vertex of the texture map of the original mesh to the texture coordinates of the restored deformed mesh. According to embodiments, the texture map video generation unit (821) can generate a texture map video by grouping the regenerated texture maps by GoF unit for each frame.

[0191] The generated texture map video can be encoded using a video compression codec of a texture map video encoder (822). The texture map video bitstream generated through encoding is transmitted to a multiplexer (823).

[0192] A multiplexer (823) multiplexes a motion vector bitstream (e.g., in case of inter encoding), a base mesh bitstream (e.g., in case of intra encoding), a displacement vector bitstream, and a texture map bitstream into a single bitstream. The single bitstream can be transmitted to a receiver via a transmitter (824). Alternatively, the motion vector bitstream, the base mesh bitstream, the displacement vector bitstream, and the texture map bitstream can be generated as a file with one or more track data or encapsulated into segments and transmitted to a receiver via the transmitter (824).

[0193] Referring to FIG. 13, a transmitting device (encoder) can encode a mesh in an intra-frame or inter-frame manner. A transmitting device according to intra-encoding can generate a base mesh, a displacement vector (or referred to as displacement), and a texture map (or referred to as attribute map). A transmitting device according to inter-encoding can generate a motion vector (or referred to as motion), a displacement vector (or referred to as displacement), and a texture map (or referred to as attribute map). The texture map obtained from the data input unit is generated and encoded based on the restored mesh. Displacement is generated and encoded through the difference in vertex positions between the base mesh and the divided (or subdivided or subdivided) mesh. More specifically, the displacement is the difference in position between the fitted sub-divided mesh and the sub-divided restored base mesh, i.e., the difference in vertex positions between the two meshes. In addition, the base mesh is generated by simplifying and encoding the original mesh through pre-processing. Motion is generated as motion vectors for the mesh of the current frame based on the reference base mesh of the previous frame.

[0194] Fig. 14 illustrates a mesh data receiving device according to embodiments.

[0195] Fig. 14 corresponds to the receiving device (110) or mesh video decoder (113) of Fig. 1, the decoder of Fig. 11 or Fig. 12, and / or the receiving decoding device corresponding thereto. Each component of Fig. 14 corresponds to hardware, software, a processor, and / or a combination thereof. The receiving (decoding) operation of Fig. 14 may follow the reverse process of the corresponding process of the transmitting (encoding) operation of Fig. 13.

[0196] The bitstream of the mesh data received by the receiver (910) is demultiplexed into a compressed motion vector bitstream (e.g., inter decoding) or a base mesh bitstream (e.g., intra decoding), a displacement vector bitstream, and a texture map bitstream after file / segment decapsulation in the demultiplexer (911). For example, if the current mesh has inter-screen encoding (i.e., inter encoding) applied, the motion vector bitstream is received, demultiplexed, and then output to the motion vector decoder (913) via the switching unit (912). As another example, if the current mesh has intra-screen encoding (i.e., intra encoding) applied, the base mesh bitstream is received, demultiplexed, and then output to the static mesh decoder (914) via the switching unit (912). Here, the motion vector decoder (913) may be referred to as a motion decoder.

[0197] According to embodiments, if the current mesh has inter-screen encoding applied according to frame header information, the motion vector decoder (913) can perform decoding on the motion vector bitstream. According to embodiments, the motion vector decoder (913) can reconstruct the final motion vector by adding the previously decoded motion vector as a predictor to the residual motion vector decoded from the bitstream.

[0198] According to embodiments, if the current mesh has been subjected to in-screen encoding according to frame header information, the static mesh decoder (914) can decode the base mesh bitstream to restore connection information, vertex geometry information, texture coordinates, normal information, etc. of the base mesh.

[0199] According to embodiments, the base mesh restoration unit (915) can restore the current base mesh based on the decoded motion vector or the decoded base mesh. For example, if the current mesh has inter-screen encoding applied, the base mesh restoration unit (915) can generate a restored base mesh by adding the decoded motion vector to the reference base mesh and then performing inverse quantization. As another example, if the current mesh has intra-screen encoding applied, the base mesh restoration unit (915) can generate a restored base mesh by performing inverse quantization on the base mesh decoded through the static mesh decoder (914).

[0200] According to embodiments, the displacement vector video decoder (917) can decode the displacement vector bitstream as a video bitstream using a video codec.

[0201] According to embodiments, the displacement vector restoration unit (918) extracts displacement vector transform coefficients from the decoded displacement vector video, and restores the displacement vector by applying inverse quantization and inverse transformation processes to the extracted displacement vector transform coefficients. To this end, the displacement vector restoration unit (918) may include an image unpacking unit, an inverse quantizer, and an inverse linear lifting unit. If the restored displacement vector is a value in a local coordinate system, a process of inversely transforming it into a Cartesian coordinate system may be performed.

[0202] The mesh restoration unit (916) can generate additional vertices by performing subdivision on the restored base mesh. Through subdivision, vertex connection information including the added vertices, texture coordinates, and texture coordinate connection information can be generated. At this time, the mesh restoration unit (916) can generate a final restored mesh (or a restored deformed mesh) by combining the subdivided restored base mesh with the restored displacement vector.

[0203] According to embodiments, the texture map video decoder (919) can decode the texture map bitstream as a video bitstream using a video codec to restore the texture map. The restored texture map has color information for each vertex contained in the restored mesh, and the color value of each vertex can be obtained from the texture map using the texture coordinates of each vertex.

[0204] According to embodiments, the mesh restored by the mesh restoration unit (916) and the texture map restored by the texture map video decoder (919) are shown to the user through a rendering process in the mesh data renderer (920).

[0205] Referring to FIG. 14, a receiving device (decoder) can decode a mesh in an intra-frame or inter-frame manner. A receiving device according to intra-decoding can receive a base mesh, a displacement vector (or referred to as displacement), a texture map (or referred to as attribute map), and render mesh data based on the restored mesh and the restored texture map. A receiving device according to inter-decoding can receive a motion vector (or referred to as motion), a displacement vector (or referred to as displacement), a texture map (or referred to as attribute map), and render mesh data based on the restored mesh and the restored texture map.

[0206] A mesh data transmission device and method according to embodiments may pre-process mesh data, encode the pre-processed mesh data, and transmit a bitstream including the encoded mesh data. A point mesh data reception device and method according to embodiments may receive a bitstream including mesh data and decode the mesh data. The mesh data transmission and reception method / device according to embodiments may be abbreviated as the method / device according to embodiments. The mesh data transmission and reception method / device according to embodiments may also be referred to as a 3D data transmission and reception method / device or a point cloud data transmission and reception method / device.

[0207] As described above, the V-Mesh method converts the displacement information generated during the encoding process into a video format and then compresses it using a conventional 2D video codec. Then, the compressed displacement information is restored by performing the reverse process of the 2D video codec. More specifically, the V-DMC encoder (or encoder or encoding device) calculates a displacement vector, which is the difference between the mesh restored from the base mesh and the mesh fitted in the pre-processing step, and converts the calculated displacement vector in the canonical coordinate system (i.e., in the form of x, y, z) into a displacement vector in the local coordinate system (i.e., in the form of normal, tangential, or bi-tangential), and then performs lifting transformation and quantization on the displacement vector in the local coordinate system to encode it into a displacement vector bitstream. In this case, the V-DMC decoder (or decoder or decoding device) performs the reverse process of the V-DMC encoder to restore the displacement vector. That is, rather than compressing the displacement vector information in the x, y, z form of the canonical coordinate system for efficient compression, it is converted to the normal, tangential, and bi-tangential forms of the local coordinate system, and then lifting transform and quantization are performed, and then encoded and transmitted in the form of simple displacement vector coefficients such as 0, 1, and 2.

[0208] Typically, for dynamic mesh encoders / decoders, the weights used for prediction and updating during displacement vector lifting and inverse transformations are shared among all displacement vector components. This can increase the bit rate of the displacement vector and degrade encoding performance.

[0209] The present disclosure proposes an improved method for lifting transformation between displacement vector coding of dynamic meshes and related syntax and semantics information. It also describes the operation of a transmitter and receiver employing the method.

[0210] More specifically, the present disclosure is to improve encoding performance by improving the accuracy of the prediction process by using adaptive weights for each displacement vector component when performing prediction and / or update in the lifting transformation and inverse transformation processes, taking into account the characteristics of the displacement vector components.

[0211] That is, the present disclosure proposes a method for performing an adaptive prediction and / or update process using adaptive weights for each displacement vector component according to the characteristics of the displacement vector component when performing a displacement vector lifting transformation and inverse transformation process of a dynamic mesh. In this way, the present disclosure can improve the accuracy of the prediction process by performing an adaptive lifting transformation and inverse transformation prediction and / or update using adaptive weights according to the displacement vector component, thereby reducing the bit amount of the displacement vector and improving the encoding performance.

[0212] In the present disclosure, geometric information (or referred to as geometry or geometric data) is one of the elements that constitute a mesh, and includes vertices (or points), edges, polygons, etc. Here, a vertex defines a position in 3D space, an edge represents connection information between vertices, and a polygon forms the surface of the mesh with a combination of edges and vertices. That is, each vertex that constitutes the mesh represents a position in 3D space, and is expressed, for example, by x, y, z coordinates (i.e., canonical coordinate system). And, a polygon may be a triangle or a square. That is, geometry forms the skeleton of a 3D model, thereby defining the shape of the model and visually expressing it when rendered.

[0213] In the present disclosure, vertex, apex, and point may be used interchangeably. That is, a vertex has coordinates in 3D space, and a triangular or quadrilateral polygon can be created through connections between multiple vertices. In addition, V-DMC referred to in the present disclosure may also be referred to as V-mesh, and the two terms are expressions used interchangeably.

[0214] In the present disclosure, displacement information can be obtained based on a refined mesh (or referred to as a sub-mesh). That is, a fitting process is performed to make the input mesh and the sub-mesh similar to each other, and the difference in the positions of each vertex of the fitted subdivision mesh and the refined restored base mesh is generated by performing refinement on the restored base mesh. The present disclosure refers to this vertex position difference value as a displacement vector. In the present disclosure, the displacement vector may be used interchangeably with the same meaning as displacement or displacement information. In addition, the displacement video may be used interchangeably with the same meaning as a displacement vector video or a displacement vector conversion coefficient video, and the displacement vector may be used interchangeably with the same meaning as a displacement vector conversion coefficient or a displacement vector coefficient.

[0215] Next, in the displacement vector coding process of a dynamic mesh, when performing lifting transformation and inverse transformation processes, the adaptive prediction and update process using adaptive weights for each component according to the characteristics of the components that constitute the displacement vector will be explained with reference to the drawing.

[0216] Fig. 15 illustrates a transmitting device according to embodiments. The transmitting device of Fig. 15 may be referred to as a mesh data transmitting device or an encoder or an encoder of a transmitting device or a V-Mesh encoder or a dynamic mesh encoder.

[0217] FIG. 15 corresponds to the transmitting device (100) or the mesh video encoder (102) of FIG. 1, the encoder (pre-processor and encoder) of FIG. 2, FIG. 6, or FIG. 7, the transmitting device of FIG. 13, and / or the transmitting encoding device corresponding thereto. Therefore, parts not described in FIG. 15 will refer to the description of the transmitting device (100) or the mesh video encoder (102) of FIG. 1, the encoder (pre-processor and encoder) of FIG. 2, FIG. 6, or FIG. 7, and the transmitting device of FIG. 13. The elements of the transmitting device illustrated in FIG. 15 may be implemented by hardware, software, a processor connected to a memory, and / or a combination thereof. That is, the elements of the transmitting device of FIG. 15 may be implemented by hardware, software, firmware, or a combination thereof, including one or more processors or integrated circuits configured to communicate with one or more memories, although not illustrated in the drawing. One or more processors may perform at least one of the operations and / or functions of the elements of the transmitting device of FIG. 15 described above. Furthermore, one or more processors may operate or execute a set of software programs and / or instructions for performing the operations and / or functions of the elements of the transmitting device of FIG. 15. The execution order of each block in FIG. 15 may be changed, some blocks may be omitted, and some blocks may be newly added.

[0218] In the present disclosure, the operation process of a transmitter for compressing and transmitting dynamic mesh data using V-Mesh compression technology may be as shown in FIG. 15. The transmitter of FIG. 15 may support both an intra-frame encoding (or intra-encoding or intra-screen encoding) process and / or an inter-frame encoding (or inter-encoding or inter-screen encoding) process.

[0219] In Fig. 15, the mesh simplification unit (11011) simplifies the input original mesh through a mesh simplification algorithm to generate a base mesh (or simplified base mesh or simplified mesh). At this time, mesh simplification can be performed based on the number of target vertices or target polygons constituting the mesh. For example, a method such as decimation can be used as a mesh simplification algorithm that simplifies the original mesh. That is, the decimation method can be a process of selecting vertices to be removed from the original mesh using a certain reference point, and then removing the selected vertices and the triangles connected to the selected vertices.

[0220] That is, the mesh simplification unit (11011) can simplify the input mesh by the target number of vertices or the target number of faces. At this time, the simplification process can be performed through various methods such as triangle collapse and edge collapse.

[0221] According to embodiments, the base mesh simplified in the mesh simplification unit (11011) is provided to the mesh parameterization unit (11012) and the mesh refinement unit (11018).

[0222] The mesh parameterization unit (11012) performs a process of mapping a 3D surface to a texture domain for a simplified mesh (decimated mesh). That is, the mesh parameterization unit (11012) generates texture coordinates and texture connection information of the input mesh. In one embodiment, the mesh parameterization unit (11012) may perform parameterization using a UV Atlas tool. Through this process, mapping information is generated regarding which location on a 2D image each vertex of the simplified mesh (decimated mesh) can be mapped to. The mapping information is expressed and stored as texture coordinates, and through this process, the final base mesh is generated. That is, the mesh parameterization unit (11012) performs parameterization to generate texture coordinates (UV coordinates) and texture connection information per vertex of the input mesh (i.e., simplified mesh or simplified base mesh).

[0223] The final base mesh (or base mesh with texture map) generated in the above parameterization unit (11012) is input to the mesh quantization unit (11013) and quantized.

[0224] According to embodiments, the mesh quantization unit (11013) may perform a task of quantizing floating-point type mesh information (e.g., geometry information (x, y, z) or / and texture coordinates (u, v), normal information (nx, ny, nz), etc.) into fixed-point type. That is, the mesh quantization unit (11013) may quantize vertex coordinates and texture coordinates of the base mesh. According to embodiments, quantization for specific components may be omitted.

[0225] The above mesh subdivision unit (11018) subdivides the base mesh simplified by the mesh simplification unit (11011). That is, the mesh subdivision unit (11018) can perform mesh subdivision on the base mesh to generate additional vertices. Depending on the subdivision method, vertex connection information, texture coordinates, and texture coordinate connection information including the added vertices can be generated. At this time, depending on the subdivision method, geometry information connection information, texture coordinate connection information, and texture coordinates can be implicitly derived and generated. According to embodiments, the mesh subdivision unit (11018) can perform subdivision through a method such as mid-edge, Loop, or Catmul&Clark.

[0226] More specifically, in the mesh refinement unit (11018), mesh refinement can be performed n times by user parameters or a promise of the encoder (i.e., transmitting device) / decoder (i.e., receiving device). According to embodiments, the vertices of the base mesh are vertices of level 0 (R0), the vertices newly generated by performing refinement once are vertices of level 1 (R1), … the vertices newly generated by performing refinement n times are vertices of level n (R n ) can be defined as vertices of level 0 (R0). For convenience of explanation, the present disclosure refers to vertices of level 0 (R0) as level 0 vertices, vertices of level 1 (R1) as level 1 vertices, …, level n (R n ) can be called level n vertices. Also, level 0 is called the 0th level (R0), level 1 is called the 1st level (R1), … level n is called the nth level (R n ) can be called.

[0227] According to embodiments, LoD0, LoD1, … LoDn can be defined as in the following mathematical expression 1.

[0228] [Mathematical Formula 1]

[0229] LoD0 = R0

[0230] LoD1 = R0+ R1= LoD0 + R1

[0231] …

[0232] LoDn = R0+ R1+, … + R n = LoDn-1 + R n

[0233] That is, the base mesh includes vertices for LoD0. And, the first subdivision mesh generated by subdividing the base mesh once includes vertices for LoD1. That is, LoD1 includes vertices of the base mesh (i.e., R0 vertices) and vertices of a newly generated level 1 by subdividing the base mesh (i.e., R1 vertices). In addition, the second subdivision mesh generated by subdividing the first subdivision mesh again includes vertices for LoD2. That is, LoD2 includes vertices of the base mesh (i.e., R0 vertices), vertices of a newly generated level 1 by subdividing the base mesh (i.e., R1 vertices), and vertices of a newly generated level 2 by subdividing the first subdivision mesh (i.e., R2 vertices).

[0234] In this way, LoD represents the level of detail of mesh data content, and as the LoD (or level) index increases, the distance between vertices becomes closer and the level of detail increases. In other words, the smaller the LoD value, the lower the detail of the mesh data content, and the larger the LoD value, the higher the detail of the mesh data content.

[0235] According to embodiments, the mesh fitting unit (11019) can perform fitting by adjusting vertex positions so that the mesh subdivided by the mesh subdivision unit (11018) becomes similar to the original mesh, thereby generating a fitted subdivided mesh.

[0236] According to embodiments, the mesh simplification unit (11011), the mesh parameterization unit (11012), the mesh refinement unit (11018), and the mesh fitting unit (11019) may be omitted, and when these processes are omitted, the original mesh may be applied as input to the mesh quantization unit (11013).

[0237] At this time, coordinate information of the original mesh can be applied as input to the displacement vector calculation unit (11020), and according to embodiments, the displacement vector encoding process (displacement vector calculation unit (11020), displacement vector coordinate system conversion unit (11021), and displacement vector encoder (11022)) can be omitted.

[0238] The present disclosure may be referred to as a pre-processor, including a mesh simplification unit (11011), a mesh parameterization unit (11012), a mesh refinement unit (11018), and a mesh fitting unit (11019). According to embodiments, the pre-processor may further include a displacement vector calculation unit (11020).

[0239] According to embodiments, the base mesh quantized in the mesh quantization unit (11013) may be output to a motion vector encoder (11015) or a static mesh encoder (11016) via a switching unit (11014). According to embodiments, the base mesh is output to the motion vector encoder (11015) via the switching unit (11014) when inter-encoding is performed on the corresponding mesh frame, and is output to the static mesh encoder (11016) via the switching unit (11014) when intra-encoding is performed on the corresponding mesh frame. The motion vector encoder (11015) may be referred to as a motion encoder.

[0240] For example, when performing intra encoding or intra frame encoding for the corresponding mesh frame, the base mesh can be compressed through a static mesh encoder (11016). In this case, encoding can be performed on connection information, vertex geometry information, vertex texture information, normal information, etc. of the base mesh. That is, vertex coordinates, vertex connection information, texture coordinates, texture connection information, etc. of the mesh can be encoded in the static mesh encoder (11016). The base mesh bitstream generated through encoding is transmitted to a multiplexer (not shown).

[0241] As another example, when performing inter-encoding (or inter-frame encoding) on ​​the corresponding mesh frame, the motion vector encoder (11015) may receive the current base mesh and the reference reconstructed base mesh (or the reconstructed quantized reference base mesh) as input, calculate a motion vector between the two meshes, and encode the value. In addition, the motion vector encoder (11015) may perform prediction based on connection information using a previously encoded / decoded motion vector as a predictor, and entropy-encode a differential motion vector (or residual motion vector) obtained by subtracting the predicted motion vector from the current motion vector. According to embodiments, the motion vector encoding may be performed on a vertex basis or a subgroup basis. The motion vector bitstream generated through the motion vector encoding is transmitted to a multiplexer (not shown) as a base mesh bitstream. That is, in the case of intra-frame encoding, the static mesh bitstream is input to the multiplexer as the base mesh bitstream, and in the case of inter-frame encoding, the motion vector bitstream is input to the multiplexer as the base mesh bitstream.

[0242] In FIG. 15, the base mesh decoder (11017) can receive a base mesh encoded by a static mesh encoder (11016) or a motion vector encoded by a motion vector encoder (11015) and generate a reconstructed base mesh. The base mesh decoder (11017) performs reconstructing the base mesh according to the encoding type (inter-screen encoding or intra-screen encoding) of the current mesh. For example, the base mesh decoder (11017) can perform static mesh decoding on the base mesh encoded by the static mesh encoder (11016) to reconstruct the base mesh. At this time, quantization can be applied before static mesh decoding, and inverse quantization can be applied after static mesh decoding. That is, when intra-screen encoding is performed, inverse quantization can be performed on the quantized base mesh through the mesh quantization unit (11013) to reconstruct the current base mesh. As another example, the base mesh decoder (11017) can reconstruct the base mesh based on the reconstructed quantized reference base mesh and the motion vector encoded by the motion vector encoder (11015). That is, when inter-screen encoding is performed, the current base mesh can be generated by decoding the motion vector by the motion vector decoding method and then applying (i.e., adding) the decoded motion vector to the reference reconstructed base mesh. At this time, when the motion vector is not quantized, the motion vector restoration process is omitted and the current base mesh can be restored using the motion vector calculated by the motion vector encoder (11015). The reconstructed base mesh is output to the displacement vector calculation unit (11020) and the mesh dequantization unit (11024).

[0243] According to embodiments, the displacement vector calculation unit (11020) can perform mesh refinement on the restored base mesh. In addition, the displacement vector calculation unit (11020) can calculate a displacement vector, which is a difference value of vertex positions between the restored base mesh that has been refined and the fitted subdivision (or refined) mesh generated by the mesh fitting unit (11019). At this time, the displacement vector can be calculated as many times as the number of vertices of the refined mesh. That is, the displacement vector of the number of vertices of the refined mesh can be calculated through the displacement vector calculation unit (11020).

[0244] According to embodiments, the displacement vector coordinate system transformation unit (11021) can transform a vertex displacement vector calculated in a 3D Cartesian coordinate system (i.e., (x, y, z) space) into a local coordinate system (i.e., normal, tangential, bi-tangential coordinate system) based on the normal vector of each vertex. At this time, the normal vector can be calculated for each subdivided vertex based on the geometry information and connection information of the surrounding vertices. According to embodiments, only the normal component among the (normal, tangential, bi-tangential) coordinate systems can be encoded. This means that when the coordinate system transformation is applied according to the agreement between the encoder / decoder, encoding of only the normal component is always performed, or the encoder can decide to signal a 1-bit flag (onlyNormFlag).

[0245] In the present disclosure, whether or not to perform displacement vector coordinate system transformation is determined by an agreement between the encoder / decoder, or whether or not to perform coordinate system transformation is determined by transmitting a coordinate system transformation status flag (applyLocalCoord) in units such as sequence, GOF (Group of frame), frame, and sub-mesh.

[0246] According to embodiments, the displacement vector encoder (11022) can perform encoding on the displacement vector or displacement vector transformation coefficient output from the displacement vector calculation unit (11020) or the displacement vector coordinate system transformation unit (11021). In the present disclosure, the displacement vector encoder (11022) can perform encoding through a video codec-based encoder, a zero run length encoder, an arithmetic encoder, or the like. For example, when the encoding method is video codec-based encoding, the displacement vector encoder (11022) can encode the displacement vector or the displacement vector transformation coefficient by packing it into a frame. That is, in the displacement vector encoder (11022), the displacement vector transform coefficients can be packed into a 2D image and then encoded using a 2D video codec (i.e., a video compression codec), or zero run-length encoded, or arithmetic encoded to generate a displacement vector video bitstream.

[0247] According to embodiments, a displacement vector video bitstream encoded and generated by a displacement vector encoder (11022) is transmitted to a multiplexer (not shown). According to embodiments, a method for selecting encoding of the displacement vector encoder (11022) may use a displacement vector encoder promised in an encoder (i.e., a transmitting side) / decoder (i.e., a receiving side), or may analyze the characteristics of a displacement vector in an encoder on the transmitting side and transmit the type of a selected displacement vector encoder to a decoder on the receiving side.

[0248] According to embodiments, the displacement vector restoration unit (11023) can restore the displacement vector by performing the reverse process of displacement vector encoding on the displacement vector or displacement vector transform coefficient encoded by the displacement vector encoder (11022). That is, the displacement vector restoration unit (11023) can perform displacement vector depacking depending on the method of encoding the displacement vector, for example, when encoding is based on a video codec. In other words, the bitstream encoded by the 2D video encoder (i.e., the video codec-based encoder) after being packed into a 2D image / video is decoded by the 2D video decoder and depacked. In addition, the displacement vector restoration unit (11023) can additionally perform inverse quantization, inverse transformation, etc. depending on whether quantization and transformation processes are performed during the displacement vector encoding process. For example, inverse quantization is performed on the quantized transform coefficients on which inverse packing has been performed, and inverse transformation is performed to calculate the restored displacement vector.

[0249] According to embodiments, the mesh dequantization unit (11024) can dequantize vertex coordinates or texture coordinates of the restored base mesh as a reverse process of quantization. More specifically, the mesh dequantization unit (11024) performs dequantization using inputs such as restored geometry information (x, y, z) and / or texture coordinates (u, v) and / or normal information (nx, ny, nz) of the restored base mesh. According to embodiments, dequantization for a specific component may be omitted. In addition, if the quantization process is omitted in the mesh quantization unit (11013), the dequantization process is also omitted in the mesh dequantization unit (11024).

[0250] According to embodiments, the mesh restoration unit (11025) can restore a mesh based on a restored displacement vector output from the displacement vector restoration unit (11023) and a restored base mesh (or a dequantized restored base mesh) output from the mesh dequantization unit (11024). More specifically, the mesh restoration unit (11025) can perform subdivision on the restored base mesh output from the mesh dequantization unit (11024) and add the restored displacement vector from the displacement vector restoration unit (11023) to generate a reconstructed deformed mesh. That is, the mesh restoration unit (11025) performs subdivision on the restored base mesh, which is restored by performing dequantization in the mesh dequantization unit (11024), to generate subdivided vertex position information, texture coordinates, and connection information. In addition, the mesh restoration unit generates restored vertex position information by adding a restored displacement vector to the subdivided vertex position information. The mesh restored by the mesh restoration unit (11025) (or referred to as restored mesh or restored deformed mesh) has restored vertices, connection information between vertices, texture coordinates, and connection information between texture coordinates. The restored mesh (or referred to as restored mesh or restored deformed mesh) generated by the mesh restoration unit (11025) is provided to the texture map generation unit (11026).

[0251] According to embodiments, the texture map generation unit (11026) can regenerate the texture map of the current mesh based on the texture map (or attribute map) of the original mesh and the mesh restored by the mesh restoration unit (11025). That is, the texture map generation unit (11026) can generate the texture map of the restored mesh through the relationship between the texture coordinates and connection information of the restored mesh and the original mesh and the texture map of the original mesh.

[0252] According to embodiments, the texture map generation unit (11026) can assign color information per vertex of the texture map of the original mesh to the texture coordinates of the restored base mesh (or the restored deformed mesh). According to embodiments, the texture map generation unit (11026) can generate a texture map (or texture map video) by grouping the regenerated texture maps by GoF unit for each frame.

[0253] The texture map generated in the texture map generation unit (11026) may be encoded in the texture map encoder (11027). For example, the texture map encoder (11027) may encode the texture map using a 2D video codec-based encoder, a zero run length encoder, an entropy coding-based arithmetic encoder, etc. That is, the texture map generated through the texture map generation unit (11026) is stacked in the frame order of the mesh to form a texture map video, and encoding is performed on the texture map video using the 2D video encoder. In addition, the texture map encoder (11027) may further perform color space conversion of the texture map. That is, when the color space of the texture map is RGB444, encoding may be performed after conversion to a color space such as YUV420 or YUV444. Then, the texture map substream (or texture map video bitstream) generated through the texture map encoding is transmitted to a multiplexer (not shown).

[0254] According to embodiments, the type of texture map encoder (11027) may include a video encoder (e.g., VVC, HEVC, etc.), an entropy coding-based encoder, etc. In addition, a method for selecting a texture map encoder (11027) may use a texture map encoder promised in an encoder (i.e., a transmitting side) / decoder (i.e., a receiving side), or may transmit the type of texture map encoder selected by the encoder on the transmitting side to the decoder on the receiving side.

[0255] According to embodiments, a multiplexer (not shown) may multiplex an input base mesh bitstream, a displacement vector bitstream, and a texture map bitstream into a single bitstream and then transmit the multiple bitstreams to a receiving device. Alternatively, the base mesh bitstream, the displacement vector bitstream, and the texture map bitstream may be encapsulated into a file / segment and transmitted to the receiving device.

[0256] According to embodiments, the bitstream multiplexed in the multiplexer may be transmitted over a network or stored in a digital storage medium. Here, the network may include a broadcasting network and / or a communication network, and the digital storage medium may include various storage media such as a USB, SD, CD, DVD, Blu-ray, HDD, or SSD.

[0257] The following describes in detail the process of encoding a displacement vector or displacement vector transform coefficient in a displacement vector encoder (11022).

[0258] That is, the displacement vector encoder (11022) can perform transformation and quantization on the displacement vector. In addition, the displacement vector encoder (11022) can encode the displacement vector or the quantized displacement vector transform coefficients through a 2D video codec-based encoding method, and / or a zero run length encoding method, and / or an arithmetic encoding method, etc. In this case, the displacement vector encoder (11022) can encode the displacement vector or the quantized displacement vector transform coefficients by selectively using only one of the 2D video codec-based encoding method, the zero run length encoding method, and the arithmetic encoding method, or by using one or more various combinations thereof.

[0259] FIGS. 16 to 20 are diagrams showing various examples of the displacement vector encoder (11022) of the present disclosure.

[0260] In the present disclosure, a displacement vector encoder (11022) may be referred to as a displacement vector transform coefficient encoder. Each component of FIGS. 16 to 20 corresponds to hardware, software, a processor, and / or a combination thereof. As in FIGS. 16 to 20, the execution order of each block may be changed, some blocks may be omitted, and some blocks may be newly added. FIG. 16 is a block diagram showing an example of a displacement vector encoder that encodes a displacement vector or a quantized displacement vector transform coefficient according to the present disclosure based on a 2D video codec. The displacement vector encoder (11022) of FIG. 16 may include a displacement vector transform unit, a displacement vector transform coefficient quantization unit, a displacement vector transform coefficient packing unit, and a displacement vector transform coefficient image / video encoding unit.

[0261] Fig. 17 is a block diagram showing an example of a displacement vector encoder that encodes a displacement vector or a quantized displacement vector transform coefficient based on a zero run length according to the present disclosure. The displacement vector encoder (11022) of Fig. 17 may include a displacement vector transform unit, a displacement vector transform coefficient quantization unit, a restored displacement vector transform coefficient level buffer, a displacement vector transform coefficient level prediction unit, and a displacement vector transform coefficient zero run length encoding unit.

[0262] Fig. 18 is a block diagram showing an example of a displacement vector encoder that arithmetic encodes a displacement vector or a quantized displacement vector transform coefficient according to the present disclosure. The displacement vector encoder (11022) of Fig. 18 may include a displacement vector transform unit, a displacement vector transform coefficient quantization unit, a restored displacement vector transform coefficient level buffer, a displacement vector transform coefficient level prediction unit, and a displacement vector transform coefficient arithmetic encoding unit.

[0263] Fig. 19 is a block diagram showing another example of a displacement vector encoder that encodes a displacement vector or a quantized displacement vector transform coefficient based on a zero run length according to the present disclosure. The displacement vector encoder (11022) of Fig. 19 may include a displacement vector transform unit, a restored displacement vector transform coefficient buffer, a displacement vector transform coefficient prediction unit, a displacement vector transform coefficient quantization unit, and a displacement vector transform coefficient zero run length encoding unit.

[0264] Fig. 20 is a block diagram illustrating another example of a displacement vector encoder that arithmetic encodes a displacement vector or a quantized displacement vector transform coefficient according to the present disclosure. The displacement vector encoder (11022) of Fig. 20 may include a displacement vector transform unit, a restored displacement vector transform coefficient buffer, a displacement vector transform coefficient prediction unit, a displacement vector transform coefficient quantization unit, and a displacement vector transform coefficient arithmetic encoding unit.

[0265] According to embodiments, the displacement vector encoder (11022) may perform displacement vector encoding through a 2D video encoder such as H.264, HEVC, VVC, etc. as in FIG. 16, or may perform displacement vector encoding through a zero run length encoder as in FIG. 17 or FIG. 19, or may perform displacement vector encoding through an arithmetic encoder as in FIG. 18 or FIG. 20.

[0266] According to embodiments, the displacement vector encoding method may be determined as a specific encoding method by an agreement between the encoder / decoder, or the encoding method determined by the encoder may be signaled as a flag or index (dispEncType) and transmitted to the receiving device.

[0267] In the present disclosure, the displacement vector encoding method may be various, and according to an embodiment, one of {video codec-based encoding method, zero run length encoding method}, {video codec-based encoding method, zero run length encoding method}, {video codec-based encoding method, arithmetic encoding method}, video codec-based encoding method, zero run length encoding method, and arithmetic encoding method may be determined through the dispEncType flag or index.

[0268] According to embodiments, a displacement vector encoding method can be determined according to a profile defined in an encoder / decoder, and an index (profileToolsetIdx) indicating profile information can be signaled and transmitted to a receiver, and a displacement vector decoding method can be determined according to profileToolsetIdx in a decoder of the receiver.

[0269] In FIGS. 16 to 20, the displacement vector transformation unit can perform transformation on the displacement vector of the (x, y, z) or (n, t, bt) coordinate system. Here, the transformation may be applied, for example, lifting transformation, wavelet transformation, etc., according to embodiments. In the (n, t, bt) coordinate system, n means normal, t means tangential, and bt means bi-tangential. For example, when lifting transformation is performed, the vertex R of the kth subdivision level k R as a predictor when performing prediction t(t <k 또는 t<=k)의 세분화 정점 변위 벡터를 통해 k번째 세분화 레벨의 변위 벡터 예측을 수행할 수 있다. 실시예들에 따라 변위 벡터의 예측 수행 시 현재 정점보다 세분화 레벨이 낮은 정점 중 연결정보를 기반으로 가까운 n개의 점을 평균 또는 거리 기반 가중평균예측을 수행할 수 있다. 실시예들에 따라 메쉬 세분화 단계에서 현재 정점을 생성하기 위해 사용한 n개의 정점의 변위 벡터를 기반으로 예측을 수행할 수 있다. 본 개시는 모두 인접 정점의 정보를 활용해 현재 정점의 값을 예측하고 보정하는 리프팅 변환 기법을 사용하며, 예측 가중치를 적용하는 방식이 사용될 수 있다.

[0270] And, when a lifting transformation is performed, a process of updating the displacement vector of the vertex used in the prediction can be performed through the residual signal generated by the prediction.

[0271] Taking Fig. 19 or Fig. 20 as an example, the restoration displacement vector transformation coefficient is stored in the restoration displacement vector transformation coefficient buffer according to the reference structure, and the displacement vector transformation coefficient prediction unit can perform prediction through the following mathematical expression 2 by using the restoration displacement vector transformation coefficient (refDispCoeff) of the reference mesh mapped to the current mesh vertex stored in the restoration displacement vector transformation coefficient buffer as a predictor of the current displacement vector transformation coefficient.

[0272] [Equation 2]

[0273] for(size t v = 0; v <N; v++){

[0274] for(size t v = 0; d <dim; d++){

[0275] dispCore[v][d] = curDispCoeff{v][d] - refDispCoeff[v][d]

[0276] }

[0277] }

[0278] And, the displacement vector transform coefficient quantization unit can perform quantization on the displacement vector value transformed by the displacement vector transform unit, i.e., the displacement vector or the displacement vector transform coefficient. According to embodiments, the displacement vector transform coefficient quantization unit can perform quantization on the differential displacement vector transform coefficient (dispCoeff) obtained by subtracting the predicted displacement vector transform coefficient (refDispCoeff) from the current displacement vector transform coefficient (curDispCodff).

[0279] Fig. 21 is a flowchart showing an example of a process for converting a displacement vector in a displacement vector conversion unit according to embodiments.

[0280] According to embodiments, a displacement vector in the (x,y,z) or (n,t,bt) coordinate system can be transformed through a displacement vector transformation unit.

[0281] According to embodiments, when coordinate system transformation into the (n, t, bt) coordinate system is performed in the displacement vector coordinate system transformation unit (11021), a 1D scalar displacement vector of the normal (n) component may be applied as an input to the displacement vector transformation unit of the displacement vector encoder (11022), and transformation, quantization, and encoding may be performed on the displacement value of the normal component.

[0282] At this time, the transformation may be performed by lifting transformation, wavelet transformation, etc. according to embodiments. If lifting transformation is performed, transformation of the displacement vector may be performed through the embodiment of FIG. 21.

[0283] The present disclosure can determine the number of lifting transformations using the number of mesh subdivision levels (lodCount). In the present disclosure, the lifting transformation process can be performed for each mesh subdivision level. Furthermore, a lifting transformation prediction unit and a lifting transformation update unit can be performed during the lifting transformation process.

[0284] In Fig. 21, the displacement vector transformation unit can perform lifting transformation prediction and lifting transformation update for each subdivision level.

[0285] In Fig. 21, the lifting transformation prediction part is the vertex R of the kth subdivision level. k When performing displacement vector prediction, t(t <k 또는 t≤k)번째 세분화 레벨의 정점 R t Displacement vector prediction of the kth subdivision level can be performed using the displacement vector as a predictor.

[0286] According to embodiments, when performing prediction of a displacement vector, the lifting transformation prediction unit may perform an average or distance-based weighted average prediction of n points near the current vertex based on connection information among vertices having a lower level of detail than the current vertex.

[0287] According to embodiments, the lifting transformation prediction unit can perform prediction based on displacement vectors of n vertices used to generate the current vertex in the mesh refinement step.

[0288] According to embodiments, the lifting transformation prediction unit can perform prediction with adaptive weights according to components of a displacement vector during the prediction process. According to embodiments, the components of the displacement vector can be expressed as three-dimensional components of x, y, and z in the (x, y, z) coordinate system, and as three-dimensional components of normal, tangential, and bi-tangential in the (normal, tangential, bi-tangential) coordinate system, depending on the coordinate system expressing the displacement vector.

[0289] According to embodiments, the lifting transformation prediction unit may perform adaptive prediction for each displacement vector component by using adaptive weights (predWeight[k]) or PredictionWeights[k]) for each displacement vector component when the displacement vector component is k-dimensional during the lifting transformation prediction process.

[0290] In the present disclosure, the adaptive prediction weights for each component may be derived by considering the distribution of each displacement vector component, or may be derived by considering the number or ratio of non-zero displacement vectors for each displacement vector component, or may be derived by considering the average size of displacement vectors for each component, or may be derived by quantization parameters for each displacement vector component, etc.

[0291] According to embodiments, when considering the distribution of each displacement vector component, the weight may be determined according to the size of the variance. In addition, when considering the number or ratio of non-zero displacement vectors for each displacement vector component, the weight may be determined according to the size of the number of non-zero displacement vectors or the ratio of non-zero displacement vectors among the entire displacement vector. In addition, when induced by the quantization parameter for each displacement vector component, the weight may be determined according to the size of the quantization parameter for each component or the difference between the quantization parameters for each component.

[0292] According to embodiments, the component-specific adaptive prediction weights may share displacement vector transformation prediction weights of tangential and bi-tangential components when expressed in (normal, tangential, bi-tangential) coordinate systems.

[0293] The following code illustrates an example of a conventional lifting transformation prediction process. That is, the code below illustrates an example in which all displacement vector components share the same weights when performing predictions during the displacement vector lifting transformation and inverse transformation processes.

[0294] for (int32_t v = vcount0; v < vcount1; ++v) {

[0295] const auto edge = edges[v];

[0296] const auto v1 = int32_t(edge ​​& 0xFFFFFFFF);

[0297] const auto v2 = int32_t((edge ​​>> 32) & 0xFFFFFFFF);

[0298] assert(v1 >= 0 && v1 <= vcount0);

[0299] assert(v2 >= 0 && v2 <= vcount0);

[0300] signal[v] -= predWeight * (signal[v1] + signal[v2]);

[0301] }

[0302] The following is a code showing an embodiment of an adaptive lifting transformation prediction process for each displacement vector component of the present disclosure. The code below is an example in which a for (int32_t k = 0; k < dispDimensions; k++) loop is additionally added to the code above to perform an independent prediction operation for each component of the displacement vector of each vertex. In other words, the code below is an example in which adaptive prediction is performed for each displacement vector component using an adaptive weight (predWeight[k]) for each displacement vector component when the displacement vector component is k-dimensional in the lifting transformation prediction process. In other words, the weight is applied independently to each component of the displacement vector to perform the prediction. dispDimensions represents the number of components of the displacement vector, and predWeight[k] is a prediction weight that is applied differently for each component (i.e., dimension).

[0303] for (int32_t k = 0; k < dispDimensions; k++) {

[0304] for (int32_t v = vcount0; v < vcount1; ++v) {

[0305] const auto edge = edges[v];

[0306] const auto v1 = int32_t(edge & 0xFFFFFFFF);

[0307] const auto v2 = int32_t((edge >> 32) & 0xFFFFFFFF);

[0308] assert(v1 >= 0 && v1 <= vcount0);

[0309] assert(v2 >= 0 && v2 <= vcount0);

[0310] signal[v][k] -= predWeight[k] * (signal[v1][k] + signal[v2][k]);

[0311] }

[0312] }

[0313] The following is a code showing another embodiment of the adaptive lifting transformation prediction process for each displacement vector component of the present disclosure. That is, the code below is an example of performing adaptive prediction according to LoD through an additional subdivision step loop. In the code below, PredictionWeights is an array representing prediction weights used in the lifting transformation prediction process, which may be one-dimensional, and the size of the array is DisplacementDim. SubdivisionIterationCount represents the number of subdivisions, and levelOfDetailVertexCounts is an array storing the number of vertices per LoD level. DisplacementDim represents the dimension of the displacement vector. Vcount0 represents the number of vertices in the i-th LoD, and Vcount1 represents the number of vertices in the i+1-th LoD. The verCoordEdges array represents edge information of vertices, and a and b represent vertices connected to the v-th edge, respectively. dispCoeffArray[v][d] represents the displacement vector transformation coefficient of the d-th component of the v-th vertex, and the initial value can be displacement vector data. The prediction process can be a process of subtracting the product of the sum of the displacement data of vertices a and b of the d-th component and the d-th prediction weight from the displacement data of vertex v of the d-th component.

[0314] for( i = 0; i < subdivisionIterationCount; i++ ) {

[0315] vcount0 = levelOfDetailVertexCounts[i]

[0316] vcount1 = levelOfDetailVertexCounts[i + 1]

[0317] for (v = vcount0; v < vcount1; ++v ) {

[0318] a = verCoordEdges[v][0]

[0319] b = verCoordEdges[v][1]

[0320] for( d = 0; d < DisplacementDim; d++ ) {

[0321] dispCoeffArray[v][d]-= PredictionWeights[d]*(dispCoeffArray[a][d]+dispCoeffArray[b][d])

[0322] }

[0323] }

[0324] }

[0325] As seen in the codes for the adaptive lifting transformation prediction process for each displacement vector component above, the lifting transformation prediction unit performs lifting transformation prediction by applying weights to each component (e.g., x, y, z, etc.) that makes up the displacement vector of each vertex. At this time, the prediction error (i.e., residual signal) is generated by subtracting the predicted value obtained by multiplying the values ​​of adjacent vertices by the weights from the value of each vertex. That is, signal[v][k] or dispCoeffArray[v][d] are variables that store the residual signal calculated by subtracting the predicted value obtained by multiplying the values ​​of adjacent vertices by the weights from the value of the current vertex.

[0326] In Fig. 21, the lifting transformation update unit performs a process of updating the displacement vector of the vertex used for prediction through the residual signal generated by the lifting transformation prediction unit.

[0327] According to embodiments, the lifting transformation update unit may perform an update using weights determined for each component of the displacement vector. According to embodiments, the components of the displacement vector may be expressed in an (x, y, z) coordinate system or a (normal, tangential, bi-tangential) coordinate system. When the displacement vector is k-dimensional, the lifting transformation update weight may transmit updateWeight[k] or updateWeights[k], and when transmitting LoD-based adaptive update weights, adaptiveUpdateWeightNr[lodCount - it - 2][k] and adaptiveUpdateWeightDr[lodCount - it - 2][k] may be transmitted.

[0328] At this time, the adaptive update weights for each component may be derived by considering the distribution of each displacement vector component, or may be derived by the number or ratio of non-zero displacement vectors for each displacement vector component, or may be derived by considering the average size of the displacement vectors for each component, or may be derived by the quantization parameter for each displacement vector component, etc. According to embodiments, when considering the distribution of each displacement vector component, the weights may be determined according to the size of the variance. According to embodiments, when considering the number or ratio of non-zero displacement vectors for each displacement vector component, the weights may be determined according to the size of the number of non-zero displacement vectors or the ratio of non-zero displacement vectors among the total displacement vectors. According to embodiments, when induced by the quantization parameter for each displacement vector component, the weights may be determined according to the size of the quantization parameter for each component or the difference between the quantization parameters for each component.

[0329] According to embodiments, when the adaptive update weights for each component are expressed in (normal, tangential, bi-tangential) coordinate systems, the displacement vector transformation update weights of the tangential and bi-tangential components can be shared with each other.

[0330] The following code shows an example of the existing lifting transformation update process.

[0331] for (int32_t v = vcount0; !skipUpdate && v < vcount1; ++v) {

[0332] const auto edge = edges[v];

[0333] const auto v1 = int32_t(edge ​​& 0xFFFFFFFF);

[0334] const auto v2 = int32_t((edge ​​>> 32) & 0xFFFFFFFF);

[0335] assert(v1 >= 0 && v1 <= vcount0);

[0336] assert(v2 >= 0 && v2 <= vcount0);

[0337] if (!adaptiveUpdateWeight) {

[0338] const auto d = updateWeight * signal[v];

[0339] signal[v1] += d;

[0340] signal[v2] += d;

[0341] } else {

[0342] const auto d = (double(adaptiveUpdateWeightNr[lodCount - it - 2])

[0343] / double(adaptiveUpdateWeightDr[lodCount - it - 2]))

[0344] * signal[v];

[0345] signal[v1] += d;

[0346] signal[v2] += d;

[0347] }

[0348] }

[0349] The following code illustrates an embodiment of an adaptive lifting transformation update process for each displacement vector component of the present disclosure, in which an adaptive weight is applied to each displacement vector component (i.e., dimension) to perform a lifting update. dispDimensions represents the dimension of the displacement vector. More specifically, the code below distributes update values ​​to adjacent basic vertices (vertices with signal indices between 0 and vcount0) for each component of the displacement vector during the update process of the lifting transformation. During the update process, the values ​​of the basic vertices are corrected using the residuals calculated in the previous prediction process (e.g., signal[v][k]). At this time, if adaptiveUpdateWeight is true, i.e., the adaptive update weights are applied, the adaptive weights apply different update rates depending on the current LOD or iteration (it) step. In addition, the update coefficient d is calculated in two different ways depending on the adaptiveUpdateWeight flag, and the calculated d is added to the signal of the adjacent vertices, thereby correcting the basic vertices to reflect the predicted residuals.

[0350] for (int32_t k = 0; k < dispDimensions; k++) {

[0351] for (int32_t v = vcount0; !skipUpdate && v < vcount1; ++v) {

[0352] const auto edge = edges[v];

[0353] const auto v1 = int32_t(edge & 0xFFFFFFFF);

[0354] const auto v2 = int32_t((edge >> 32) & 0xFFFFFFFF);

[0355] assert(v1 >= 0 && v1 <= vcount0);

[0356] assert(v2 >= 0 && v2 <= vcount0);

[0357] if (!adaptiveUpdateWeight) {

[0358] const auto d = updateWeight[k] * signal[v][k];

[0359] signal[v1][k] += d;

[0360] signal[v2][k] += d;

[0361] } else {

[0362] const auto d = (double(adaptiveUpdateWeightNr[lodCount - it - 2][k])

[0363] / double(adaptiveUpdateWeightDr[lodCount - it - 2][k]))

[0364] * signal[v][k];

[0365] signal[v1][k] += d;

[0366] signal[v2][k] += d;

[0367] }

[0368] }

[0369] }

[0370] The following is a code showing another embodiment of the adaptive lifting transformation update process for each displacement vector component of the present disclosure. In the code below, UpdateWeights is an array representing update weights used in the lifting transformation update process, which may be two-dimensional, and the size of the array is (subdivisionCount * DisplacementDim). UpdateWeights[i][d] represents the update weights of the d-th component of the i-th LoD. subdivisionIterationCount represents the number of subdivisions, and levelOfDetailVertexCounts is an array storing the number of vertices per LoD level. dispDimensions represents the dimension of the displacement vector, Vcount0 represents the number of vertices in the i-th LoD, and Vcount1 represents the number of vertices in the i+1th LoD. The skipUpdate flag is a flag indicating whether to skip the lifting update process, and the verCoordEdges array is an array representing edge information of vertices, where a and b represent vertices connected to the v-th edge, respectively. valenceUpdate is a flag indicating whether to use a method to determine update weights using valence information. That is, this valenceUpdate indicates whether to apply a balance-based update at each refinement step (i). Here, valence represents the number of connected neighbors of a base vertex. In other words, the valence () of a mesh vertex can be defined as the number of lines connected to the vertex or the number of other vertices connected to the vertex. For example, if the valenceUpdate flag is 1, the lifting transformation update unit can perform the update using the balance information calculated from the base mesh.dispCoeffArray[v][d] represents the displacement vector transformation coefficient of the d-th component of the v-th vertex, and is a value obtained by performing prediction of displacement vector data in the lifting transformation prediction unit. According to embodiments, the update process is a process of multiplying the v-th dispCoeffArray[v][d] by the update weight corresponding to the d-th component of the i-th LoD and adding the value to dispCoeffArray[a][d] and dispCoeffArray[b][d], respectively.

[0371] for(i = 0; i < subdivisionIterationCount; i++) {

[0372] vcount0 = levelOfDetailVertexCounts[i]

[0373] vcount1 = levelOfDetailVertexCounts[i + 1]

[0374] for (k = 0; k < dispDimensions; k++) {

[0375] for (v = vcount0; !skipUpdate && v < vcount1; ++v) {

[0376] a = verCoordEdges[v][0]

[0377] b = verCoordEdges[v][1]

[0378] for( d = 0; d < DisplacementDim; d++ ) {

[0379] if ( valenceUpdate[i] ) {

[0380] valenceA = (a < levelofDetailCounts[0]) ? valence[a]: 6

[0381] valenceB = (b < levelofDetailCounts[0]) ? valence[b]: 6

[0382] disp0 = updateWeights[i][d] * dispCoeffArray[v][d] / valenceA

[0383] disp1 = updateWeights[i][d] * dispCoeffArray[v][d] / valenceB

[0384] dispCoeffArray [a][d] += disp0

[0385] dispCoeffArray [b][d] += disp1

[0386] }

[0387] else {

[0388] disp = updateWeights[i][d] * dispCoeffArray[v][d]

[0389] dispCoeffArray[a][d] += disp

[0390] dispCoeffArray[b][d] += disp

[0391] }

[0392] }

[0393] }

[0394] }

[0395] The following is a detailed explanation of the behavior according to the value of valenceUpdate[i] in the above code.

[0396] If valenceUpdate[i] is true, the update value is adjusted based on the degree of connectivity of each vertex, taking into account the valence of the base vertex. When the valence (i.e., the number of connections) is high, the update value is relatively small, and when the valence is low, the update value is increased.

[0397] First, determine the valence (i.e., the number of connections) of vertices a and b as follows. That is, check whether each adjacent vertex a and b is a basic vertex. If it is a basic vertex, use the actual connection count, valences[a] or valences[b]; otherwise, use the default value of 6.

[0398] valenceA = (a < levelofDetailCounts[0]) ? valences[a] : 6

[0399] valenceB = (b < levelofDetailCounts[0]) ? valences[b] : 6

[0400] Then, the update value is calculated as follows. That is, the residual (or displacement coefficient to be updated) dispCoeffArray[v][d] of vertex v is multiplied by updateWeights[i][d], and then the update value is calculated by dividing it by valenceA for vertex a and by valenceB for vertex b.

[0401] disp0 = updateWeights[i][d] * dispCoeffArray[v][d] / valenceA

[0402] disp1 = updateWeights[i][d] * dispCoeffArray[v][d] / valenceB

[0403] Then, the adjacent vertices are updated as follows. That is, each adjacent vertex is updated by adding the calculated update values ​​disp0 and disp1 to the corresponding displacement coefficients of vertices a and b, respectively.

[0404] dispCoeffArray[a][d] += disp0

[0405] dispCoeffArray[b][d] += disp1

[0406] That is, if valenceUpdate[i] is true, the amount of update transmitted to each adjacent vertex is adjusted based on the actual connectivity (valence) of the base vertex. This allows each adjacent vertex to be updated differently based on its connectivity, resulting in a more balanced compensation during the restoration process on the receiving end.

[0407] If valenceUpdate[i] is false, the update value is calculated as follows. That is, the update value is simply multiplied by updateWeights[i][d] to obtain the residual (or displacement coefficient to be updated) dispCoeffArray[v][d] of vertex v.

[0408] disp = updateWeights[i][d] * dispCoeffArray[v][d]

[0409] Then, update the adjacent vertices as follows. That is, add the same update value disp to both vertices a and b.

[0410] dispCoeffArray[a][d] += disp

[0411] dispCoeffArray[b][d] += disp

[0412] That is, if valenceUpdate[i] is false, the update value is distributed equally to the two adjacent vertices without balance-based compensation. By doing so, the adjacent vertices receive the same update value of vertex v, and are compensated uniformly regardless of balance.

[0413] When valenceUpdate is true, the update value is divided and applied based on the balance of adjacent vertices, thereby adjusting the strength of the correction based on the degree of connectivity between vertices, resulting in a more adaptive update. Conversely, when valenceUpdate is false, the same update value is applied to all adjacent vertices, resulting in uniform correction regardless of balance.

[0414] In FIGS. 16 to 20, the displacement vector transform coefficient quantization unit performs quantization on the transform coefficients transformed through the displacement vector transform unit. According to embodiments, the transform coefficients may be quantized through different quantization parameters for each axis, and the quantization parameter or scaling parameter may be derived by an agreement between the encoder / decoder to determine the quantization rate for each LoD level.

[0415] Meanwhile, the transmitting device of FIG. 15 may further include an atlas encoder (not shown). According to embodiments, the atlas encoder may encode atlas information (or atlas data) into an atlas bitstream and transmit it to a receiving device. The atlas may be information required for a mesh reconstruction process and may refer to information such as tiles and patches. In addition, the atlas data may refer to data required for processes such as mesh decoding and mesh restoration and may include a segmentation method, a transformation method, a quantization method, the position and size of a patch within an atlas frame, and the like. Such atlas information may be encoded through Exp-Golomb coding of the atlas encoder, etc.

[0416] Fig. 22 illustrates a receiving device according to embodiments. In the present disclosure, the receiving device of Fig. 22 may be referred to as a mesh data receiving device or decoder or decoder of a receiving device or a V-Mesh decoder or a dynamic mesh decoder.

[0417] FIG. 22 corresponds to the receiving device (110) or mesh video decoder (113) of FIG. 1, the decoder of FIG. 11 or FIG. 12, the receiving device of FIG. 14, and / or the receiving decoding device corresponding thereto. Therefore, parts not described in FIG. 22 will refer to the description of the receiving device (110) or mesh video decoder (113) of FIG. 1, the decoder of FIG. 11 or FIG. 12, and the receiving device of FIG. 14. The elements of the receiving device illustrated in FIG. 22 may be implemented by hardware, software, a processor connected to a memory, and / or a combination thereof. That is, the elements of the receiving device of FIG. 22 may be implemented by hardware, software, firmware, or a combination thereof, including one or more processors or integrated circuits configured to be able to communicate with one or more memories, although not illustrated in the drawing. One or more processors may perform at least one of the operations and / or functions of the elements of the receiving device of FIG. 22 described above. Furthermore, one or more processors may operate or execute a set of software programs and / or instructions for performing the operations and / or functions of the elements of the receiving device of FIG. 22. The execution order of each block in FIG. 22 may be changed, some blocks may be omitted, and some blocks may be newly added.

[0418] FIG. 22 may largely include a base mesh decoding unit, a displacement information decoding unit, and a texture map decoding unit. According to embodiments, the base mesh decoding unit may include a switching unit (15011), a motion vector decoder (15012), a static mesh decoder (15013), a base mesh restoration unit (15014), a mesh refinement unit (15015), and a mesh restoration unit (15016). According to embodiments, the displacement information decoding unit may include a displacement vector decoder (15017) and a displacement vector coordinate system inverse transformation unit (15020). In addition, the receiving device of FIG. 22 may further include an atlas decoder (not shown).

[0419] According to embodiments, a bitstream of mesh data received by a receiver (not shown) may be demultiplexed into a base mesh bitstream, a displacement vector bitstream, a texture map bitstream, and / or an atlas bitstream after file / segment decapsulation in a demultiplexer (not shown). If the current mesh has inter-screen encoding (i.e., inter-encoding) applied, the base mesh bitstream may be a motion vector bitstream.

[0420] According to embodiments, a base mesh bitstream is provided to an atlas decoder. The atlas decoder can decode the atlas bitstream to restore atlas information. The restored atlas can be used in a mesh decoding process. According to embodiments, the process in which the atlas information is used may include a segmentation process, a displacement vector restoration process, etc., and may include information such as tiles and patches.

[0421] According to embodiments, the atlas bitstream may be decoded through an atlas decoder's Exp-Golomb coding process, etc. In this case, the atlas may be information required for a mesh reconstruction process, and may refer to information such as tiles and patches. In addition, the atlas data may refer to data required for processes such as mesh decoding and mesh reconstruction, and may include a segmentation method, a transformation method, a quantization method, the location and size of patches within an atlas frame, etc.

[0422] According to embodiments, the base mesh bitstream is provided to a motion vector decoder (15012) via a switching unit (15011) or to a static mesh decoder (15013).

[0423] For example, if the current mesh has inter-screen encoding (i.e., inter encoding) applied, the base mesh bitstream, i.e., the motion vector bitstream, is received, demultiplexed, and then output to the motion vector decoder (15012) through the switching unit (15011). As another example, if the current mesh has intra-screen encoding (i.e., intra encoding) applied, the base mesh bitstream is received, demultiplexed, and then output to the static mesh decoder (15013) through the switching unit (15011). Here, the motion vector decoder (15012) may be referred to as a motion decoder.

[0424] According to embodiments, the motion vector decoder (15012) can perform decoding on a motion vector bitstream on a vertex-by-vertex basis or a subgroup basis.

[0425] According to embodiments, the motion vector decoder (15012) can reconstruct a final motion vector by adding a differential motion vector (i.e., a residual motion vector) decoded from a bitstream using a previously decoded motion vector as a predictor. That is, the motion vector decoder (15012) can decode a differential motion vector (or a residual motion vector) in units of vertices or subgroups (or subblocks) through a motion vector bitstream, and perform prediction based on connection information using a previously decoded motion vector as a predictor to decode the motion vector by adding it to the residual motion vector.

[0426] According to embodiments, the static mesh decoder (15013) can decode the base mesh bitstream to restore connection information, vertex geometry information, texture coordinates (i.e., attribute geometry information), normal information, etc. of the base mesh.

[0427] According to embodiments, the base mesh restoration unit (15014) may restore the current base mesh based on the decoded motion vector or the decoded base mesh. For example, if the current mesh has inter-screen encoding applied, the base mesh restoration unit (15014) may add the decoded (or restored) motion vector to the reference base mesh and then perform inverse quantization to generate a restored base mesh (i.e., the current base mesh). As another example, if the current mesh has intra-screen encoding applied, the base mesh restoration unit (15014) may perform inverse quantization on the decoded (or restored) base mesh through the static mesh decoder (15012) to generate a restored base mesh (i.e., the current base mesh). According to embodiments, the inverse quantization unit may be omitted.

[0428] According to embodiments, the mesh subdivision unit (15015) can perform subdivision on the base mesh to generate additional vertices. The present disclosure can implicitly derive and generate geometry information connection information, texture coordinate connection information, and texture coordinates according to the subdivision method.

[0429] According to embodiments, the mesh refinement unit (15015) can perform refinement through methods such as mid-edge, Loop, and Catmul&Clark.

[0430] According to embodiments, mesh refinement in the mesh refinement unit (15015) may be performed n times by user parameters or encoder / decoder promises. According to embodiments, vertices of the base mesh are vertices of level 0 (R0), vertices newly generated by performing refinement once are vertices of level 1 (R1), … vertices newly generated by performing refinement n times are vertices of level n (R n ) can be defined as the vertices of the 0th level (R0), level 1 as the 1st level (R1), … level n as the nth level (R n ) can be called.

[0431] According to embodiments, LoD0, LoD1, … LoDn can be defined as in the following mathematical expression 3.

[0432] [Equation 3]

[0433] LoD0 = R0

[0434] LoD1 = R0+ R1= LoD0 + R1

[0435] …

[0436] LoDn = R0+ R1+, … + R n = LoDn-1 + R n

[0437] That is, the base mesh includes vertices for LoD0. And, the first subdivision mesh generated by subdividing the base mesh once includes vertices for LoD1. That is, LoD1 includes vertices of the base mesh (i.e., R0 vertices) and vertices of a newly generated level 1 by subdividing the base mesh (i.e., R1 vertices). In addition, the second subdivision mesh generated by subdividing the first subdivision mesh again includes vertices for LoD2. That is, LoD2 includes vertices of the base mesh (i.e., R0 vertices), vertices of a newly generated level 1 by subdividing the base mesh (i.e., R1 vertices), and vertices of a newly generated level 2 by subdividing the first subdivision mesh (i.e., R2 vertices).

[0438] According to embodiments, the displacement vector decoder (15017) may perform video codec-based decoding on the demultiplexed displacement vector bitstream as a video bitstream, or perform zero run-length decoding, or perform arithmetic decoding. In the present disclosure, the displacement vector decoder may be used interchangeably with the displacement vector transform decoder.

[0439] According to embodiments, the displacement vector decoder (15017) can restore the displacement vector by decoding the displacement vector in a reverse process of the displacement vector encoding method of the transmitting side.

[0440] According to embodiments, the displacement vector coordinate system inversion unit (15020) can perform a process of inverting the displacement vector decoded by the displacement vector decoder (15017) into a Cartesian (or canonical) coordinate system (x, y, z) if the displacement vector is a value of a local coordinate system (n, t, bt). The output of the displacement vector coordinate system inversion unit (15020) is provided to the mesh restoration unit (15016).

[0441] That is, in the encoder of the transmitting device, the vertex displacement vector calculated in the (x,y,z) space can be converted to a (normal, tangential, bi-tangential) coordinate system (or local coordinate system) based on the normal vector of each vertex. At this time, the normal vector can be calculated for each subdivided vertex based on the geometric information and connection information of the surrounding vertices.

[0442] Fig. 23 is a detailed block diagram showing an example of a displacement vector coordinate system inverse transformation unit (15020) according to embodiments.

[0443] Fig. 24 is a detailed block diagram showing another example of a displacement vector coordinate system inverse transformation unit (15020) according to embodiments.

[0444] More specifically, the displacement vector coordinate system inverse transformation unit (15020) parses the coordinate system transformation flag (applyLocalCoord or asps_vmc_ext_displacement_coordinate_system) included in the signaling information in units of sequences, GoFs (group of frames), frames, or sub-mesh, and if its value is 1, it can perform inverse transformation of the inverse quantized (or inversely transformed) restored displacement vector from the local coordinate system (n, t, b) to the canonical coordinate system (x, y, z).

[0445] In addition, a normal vector per vertex is calculated based on the restoration vertex position information of the restoration base mesh, and a normal value of a newly created vertex can be assigned by interpolating the vertex normal vector of the calculated restoration base mesh for the vertex additionally created through the subdivision process (see Fig. 23).

[0446] At this time, in the case of interpolation, interpolation can be performed by averaging or distance-based weighting the normal information of the base mesh used for subdivision. Alternatively, the normal information of the base mesh can be used as is for subdivided vertices on the same plane.

[0447] According to embodiments, after performing subdivision on the restored base mesh, normal vectors can be calculated for vertices generated through the mesh subdivision unit (15015) and vertices of the base mesh (see FIG. 24).

[0448] And, through the calculated normal vector per vertex, the tangential and bi-tangential vectors orthogonal to the normal vector can be calculated and the displacement vector coordinate system inverse transformation can be performed. The following mathematical expression 4 disp n (0), disp n (1), disp n (2) refers to the results of normal, tangential, and bitangential components obtained by performing inverse transformation and inverse quantization.

[0449] [Equation 4]

[0450]

[0451] In some embodiments, coordinate system inversion can always be performed without flag transmission.

[0452] According to embodiments, the mesh restoration unit (15016) restores the mesh based on the mesh refined in the mesh refinement unit (15015) and the restored displacement vector output from the displacement vector coordinate system inverse transformation unit (15020).

[0453] According to embodiments, the received and demultiplexed texture map bitstream is input to a texture map decoder (15021). According to embodiments, the texture map decoder (15021) can decode the texture map through a 2D scalable decoder. That is, the texture map decoder (15021) can restore the texture map by applying 2D scalable decoding to the texture map. In this way, the texture map decoder (15021) receives the texture map bitstream as input and performs a process of decoding the texture map. At this time, the type of texture map decoder may include a video decoder, a zero run length decoder, an arithmetic decoder, etc. According to embodiments, the texture map decoder (15021) can perform color space conversion of the texture map.

[0454] When the base mesh bitstream, displacement vector bitstream, texture map bitstream, and / or atlas bitstream encoded by the dynamic mesh encoder of the transmitting device are transmitted in this way, the decoder of the receiving device restores the mesh by decoding each bitstream. First, the base mesh is decoded by the motion vector or static mesh decoder depending on whether it is inter or intra frame, and the geometry information is restored along with the decoded displacement vector information through subdivision.

[0455] Fig. 25 is a detailed block diagram showing an example of a displacement vector decoder according to embodiments. The displacement vector decoder according to embodiments may include a displacement vector transform coefficient decoding unit, a displacement vector inverse quantization unit, and a displacement vector inverse transform unit. Each component of Fig. 25 corresponds to hardware, software, a processor, and / or a combination thereof. The execution order of each block in Fig. 25 may be changed, some blocks may be omitted, and some blocks may be newly added.

[0456] According to embodiments, the displacement vector transform coefficient decoding unit may perform displacement vector decoding through a 2D video decoder such as H.264, HEVC, VVC, etc., or may perform displacement vector decoding through a zero run length decoder or an arithmetic decoder, etc.

[0457] According to embodiments, in the displacement vector transform coefficient decoding unit, the displacement vector transform coefficient decoding method may be determined by a specific decoding method through an agreement between the encoder and the decoder, or may be determined by receiving an encoding method determined by the encoder as a flag or index (dispEncType).

[0458] In the present disclosure, the displacement vector transform coefficient decoding method may be various, and according to embodiments, one of {video codec-based decoding method, zero run length decoding method}, {video codec-based decoding method, zero run length decoding method}, {video codec-based decoding method, arithmetic decoding method}, video codec-based decoding method, zero run length decoding method, and arithmetic decoding method may be determined through the dispEncType flag or index.

[0459] According to embodiments, a displacement vector transformation coefficient decoding method can be determined according to a profile defined in an encoder / decoder, and an index (profileToolsetIdx) indicating profile information can be transmitted so that the decoder can determine a displacement vector decoding method according to profileToolsetIdx.

[0460] According to embodiments, a displacement vector inverse quantization unit may perform inverse quantization on a displacement vector. At this time, quantization of the transform coefficients may be performed through different quantization parameters for each axis, and a quantization rate may be determined for each LoD level by deriving a quantization parameter or a scaling parameter through an agreement between the encoder and the decoder.

[0461] According to embodiments, the displacement vector inverse transform unit performs an inverse transform of the transform performed in the encoder of the transmitting device on the inverse quantized displacement vector coefficients to output displacement vectors. According to embodiments, a lifting inverse transform, a wavelet inverse transform, etc. may be performed. If a lifting inverse transform is performed in the displacement vector inverse transform unit, a process of updating the displacement vector of a vertex used for prediction in the encoder may be performed through the parsed residual signal. That is, the displacement vector inverse transform unit performs an inverse transform of the inverse quantized displacement vector coefficients. At this time, a lifting inverse transform, a wavelet inverse transform, etc. may be applied as the inverse transform according to embodiments. Fig. 26 is a flowchart showing an example of a process of inverse transforming a displacement vector in the displacement vector inverse transform unit according to embodiments. That is, if a lifting inverse transform is performed in the displacement vector inverse transform unit, an inverse transform of a displacement vector may be performed through the embodiments of Fig. 26. At this time, the number of lifting inverse transformations can be determined using the number of mesh subdivision levels (lodCount). Furthermore, the lifting inverse transformation process can be performed for each mesh subdivision level. Furthermore, the lifting inverse transformation process can include a lifting inverse transformation prediction unit and a lifting inverse transformation update unit.

[0462] Figure 26 is an example of performing displacement vector inverse transformation for each LoD, and may include a lifting inverse transformation update unit and a lifting inverse transformation prediction unit.

[0463] In Fig. 26, the lifting inverse transformation prediction unit can perform inverse transformation prediction on a displacement vector for which lifting inverse transformation update has been performed in the lifting inverse transformation update unit.

[0464] According to the embodiments, the lifting inverse transform prediction unit performs the lifting inverse transform on the vertex R of the kth subdivision level. k R as a predictor when performing prediction t (t <k 또는 t<=k)의 세분화 정점 변위 벡터를 통해 k번째 세분화 레벨의 변위벡터 예측을 수행할 수 있다.

[0465] According to embodiments, when performing prediction of a displacement vector, an average or distance-based weighted average prediction can be performed on n points near the current vertex based on connection information among vertices with a lower level of detail than the current vertex.

[0466] According to embodiments, prediction can be performed based on the displacement vectors of n vertices used to generate the current vertex in the mesh refinement step.

[0467] Additionally, when the lifting inverse transformation is performed, the displacement vector of the vertex of the subdivision level can be restored through the sum between the predicted displacement vector and the parsed residual signal.

[0468] According to embodiments, the lifting inverse transform prediction unit can perform prediction with adaptive weights according to components of a displacement vector during the prediction process. According to embodiments, the components of the displacement vector can be expressed in an (x, y, z) coordinate system or a (normal, tangential, bi-tangential) coordinate system. When the displacement vector components are k-dimensional during the lifting inverse transform prediction process, adaptive prediction can be performed for each displacement vector component using adaptive weights (predWeight[k] or PredictionWeights[k]) for each displacement vector component. In the present disclosure, the lifting transform adaptive prediction weights can be transmitted from an encoder of a transmitting side and parsed.

[0469] The following code illustrates an example of an adaptive lifting inverse prediction process for each displacement vector component. The code below is an example in which an independent prediction operation is performed for each component of the displacement vector of each vertex. In other words, the code below is an example in which adaptive prediction is performed for each displacement vector component using an adaptive weight (predWeight[k]) for each displacement vector component when the displacement vector component is k-dimensional in the lifting inverse prediction process. In other words, the weight is applied independently to each component of the displacement vector to perform prediction. dispDimensions represents the number of components of the displacement vector, and predWeight[k] is a prediction weight that is applied differently for each component (i.e., dimension).

[0470] for (int32_t k = 0; k < dispDimensions; k++) {

[0471] for (int32_t v = vcount0; v < vcount1; ++v) {

[0472] const auto edge = edges[v];

[0473] const auto v1 = int32_t(edge ​​& 0xFFFFFFFF);

[0474] const auto v2 = int32_t((edge ​​>> 32) & 0xFFFFFFFF);

[0475] assert(v1 >= 0 && v1 <= vcount0);

[0476] assert(v2 >= 0 && v2 <= vcount0);

[0477] signal[v][k] -= predWeight[k] * (signal[v1][k] + signal[v2][k]);

[0478] }

[0479] }

[0480] The following is a code showing another embodiment of the adaptive lifting inverse prediction process for each displacement vector component of the present disclosure. That is, the code below is an example of performing adaptive prediction according to LoD through an additional subdivision step loop. In the code below, PredictionWeights is an array representing prediction weights used in the lifting inverse prediction process, which may be one-dimensional, and the size of the array is DisplacementDim. SubdivisionIterationCount represents the number of subdivisions, and levelOfDetailVertexCounts is an array storing the number of vertices per LoD level. DisplacementDim represents the dimension of the displacement vector. Vcount0 represents the number of vertices in the i-th LoD, and Vcount1 represents the number of vertices in the i+1-th LoD. The verCoordEdges array represents edge information of vertices, and a and b represent vertices connected to the v-th edge, respectively. dispCoeffArray[v][d] represents the displacement vector transformation coefficient of the d-th component of the v-th vertex, and the initial value can be displacement vector data. The prediction process can be a process of subtracting the product of the sum of the displacement data of vertices a and b of the d-th component and the d-th prediction weight from the displacement data of vertex v of the d-th component.

[0481] for( i = 0; i < subdivisionIterationCount; i++ ) {

[0482] vcount0 = levelOfDetailVertexCounts[ i ]

[0483] vcount1 = levelOfDetailVertexCounts[ i + 1 ]

[0484] for ( v = vcount0; v < vcount1; ++v ) {

[0485] a = verCoordEdges[ v ][ 0 ]

[0486] b = verCoordEdges[ v ][ 1 ]

[0487] for( d = 0; d < DisplacementDim; d++ ) {

[0488] dispCoeffArray[ v ][ d ] +=

[0489] PredictionWeights[d] * (dispCoeffArray[a][d] + dispCoeffArray[b][d])

[0490] }

[0491] }

[0492] }

[0493] In Fig. 26, the lifting inverse transformation update unit performs a process of updating the displacement vector of the vertex used for prediction through the parsed residual signal.

[0494] According to embodiments, the lifting inverse transformation update unit may perform an update using weights determined for each component of the displacement vector. According to embodiments, the components of the displacement vector may be expressed in an (x, y, z) coordinate system or a (normal, tangential, bi-tangential) coordinate system. In addition, when the displacement vector is k-dimensional, the inverse transformation update weight may be parsed as updateWeights[k], and when the LoD-based adaptive update weight is parsed, adaptiveUpdateWeightNr[lodCount - it - 2][k] and adaptiveUpdateWeightDr[lodCount - it - 2][k] may be parsed.

[0495] The following is a code showing an embodiment of an adaptive lifting inverse transformation update process for each displacement vector component of the present disclosure, in which an adaptive weight is applied to each displacement vector component (i.e., dimension) to perform a lifting update. In the code below, dispDimensions represents the dimension of the displacement vector. More specifically, the code below distributes the update value to adjacent basic vertices (vertices whose signal indices are between 0 and vcount0) for each component of the displacement vector during the update process of the lifting inverse transformation. During the update process, the values ​​of the basic vertices are corrected using the residual calculated in the previous prediction process (e.g., signal[v][k]). At this time, if adaptiveUpdateWeight is true, i.e., if the adaptive update weight is applied, the adaptive weight applies a different update ratio depending on the current LOD or iteration (it) step. Additionally, the update coefficient d is calculated in two different ways depending on the adaptiveUpdateWeight flag, and the calculated d is added to the signal of the adjacent vertices, thereby correcting the base vertices to reflect the prediction residual.

[0496] for (int32_t k = 0; k < dispDimensions; k++) {

[0497] for (int32_t v = vcount0; !skipUpdate && v < vcount1; ++v) {

[0498] const auto edge = edges[v];

[0499] const auto v1 = int32_t(edge ​​& 0xFFFFFFFF);

[0500] const auto v2 = int32_t((edge ​​>> 32) & 0xFFFFFFFF);

[0501] assert(v1 >= 0 && v1 <= vcount0);

[0502] assert(v2 >= 0 && v2 <= vcount0);

[0503] if (!adaptiveUpdateWeight) {

[0504] const auto d = updateWeight[k] * signal[v][k];

[0505] signal[v1][k] += d;

[0506] signal[v2][k] += d;

[0507] } else {

[0508] const auto d = (double(adaptiveUpdateWeightNr[lodCount - it - 2][k])

[0509] / double(adaptiveUpdateWeightDr[lodCount - it - 2][k])) * signal[v][k];

[0510] signal[v1][k] += d;

[0511] signal[v2][k] += d;

[0512] }

[0513] }

[0514] }

[0515] The following is a code showing another embodiment of the adaptive lifting inverse transformation update process for each displacement vector component of the present disclosure. In the code below, UpdateWeights is an array representing update weights used in the lifting inverse transformation update process, which may be two-dimensional, and the size of the array is (subdivisionCount * DisplacementDim). UpdateWeights[i][d] represents the update weights of the d-th component of the i-th LoD. subdivisionIterationCount represents the number of subdivisions, and levelOfDetailVertexCounts is an array storing the number of vertices per LoD level. dispDimensions represents the dimension of the displacement vector, Vcount0 represents the number of vertices in the i-th LoD, and Vcount1 represents the number of vertices in the i+1th LoD. The skipUpdate flag is a flag indicating whether to skip the lifting update process, and the verCoordEdges array is an array representing edge information of vertices, where a and b represent vertices connected to the v-th edge, respectively. valenceUpdate is a flag indicating whether to use a method of determining update weights using valence information. That is, this valenceUpdate indicates whether to apply a balance-based update at each refinement step (i). Here, valence represents the number of connected neighbors of the base vertex. For example, if the valenceUpdate flag is 1, the lifting transformation update unit can perform the update using the balance information calculated from the base mesh. dispCoeffArray[v][d] represents the displacement vector transformation coefficient of the d-th component of the v-th vertex, and is the value obtained by predicting the displacement vector data in the lifting transformation prediction unit.According to embodiments, the update process may be a process of multiplying the update weight corresponding to the d-th component of the i-th LoD by the v-th dispCoeffArray[v][d] and subtracting the value from dispCoeffArray[a][d] and dispCoeffArray[b][d], respectively.

[0516] for(i = 0; i < subdivisionIterationCount; i++ ) {

[0517] vcount0 = levelOfDetailVertexCounts[i]

[0518] vcount1 = levelOfDetailVertexCounts[i + 1]

[0519] for (k = 0; k < dispDimensions; k++) {

[0520] for (v = vcount0; !skipUpdate && v < vcount1; ++v) {

[0521] a = verCoordEdges[v][0]

[0522] b = verCoordEdges[v][1]

[0523] for( d = 0; d < DisplacementDim; d++ ) {

[0524] if ( valenceUpdate[i] ) {

[0525] valenceA = (a < levelofDetailCounts[0]) ? valence[a]: 6

[0526] valenceB = (b < levelofDetailCounts[0]) ? valence[b]: 6

[0527] disp0 = updateWeights[i][d] * dispCoeffArray[v][d] / valenceA

[0528] disp1 = updateWeights[i][d] * dispCoeffArray[v][d] / valenceB

[0529] dispCoeffArray [a][d] -= disp0

[0530] dispCoeffArray [b][d] -= disp1

[0531] }

[0532] else {

[0533] disp = updateWeights[i][d] * dispCoeffArray[v][d]

[0534] dispCoeffArray[a][d] -= disp

[0535] dispCoeffArray[b][d] -= disp

[0536] }

[0537] }

[0538] }

[0539] }

[0540] The following is a detailed explanation of the behavior according to the value of valenceUpdate[i] in the above code.

[0541] If valenceUpdate[i] is true, the update value is adjusted based on the degree of connectivity (valence) of each vertex, taking into account the valence of adjacent vertices. Vertices with a greater valence (i.e., greater number of connections) receive smaller updates from an edge, while vertices with fewer valences receive larger updates.

[0542] First, the valence (i.e., number of connections) of vertices a and b is determined as follows. That is, if each adjacent vertex a and b is a basic vertex (with an index less than levelofDetailCounts[0]), the actual number of connections, valences[a] or valences[b], is used; otherwise, the default value 6 is used.

[0543] valenceA = (a < levelofDetailCounts[0]) ? valences[a] : 6

[0544] valenceB = (b < levelofDetailCounts[0]) ? valences[b] : 6

[0545] Then, the update value is calculated as follows. That is, the residual (or displacement coefficient to be updated) dispCoeffArray[v][d] of vertex v is multiplied by updateWeights[i][d], and then the update value is calculated by dividing it by valenceA for vertex a and by valenceB for vertex b.

[0546] disp0 = updateWeights[i][d] * dispCoeffArray[v][d] / valenceA

[0547] disp1 = updateWeights[i][d] * dispCoeffArray[v][d] / valenceB

[0548] Then, the adjacent vertices are updated as follows. That is, each adjacent vertex is updated by subtracting the calculated update values ​​disp0 and disp1 from the dispCoeffArray of vertices a and b, respectively.

[0549] dispCoeffArray[a][d] -= disp0

[0550] dispCoeffArray[b][d] -= disp1

[0551] As shown above, when valenceUpdate[i] is true, each adjacent vertex receives a different update size based on its balance (i.e., the number of connections), resulting in a more fine-grained adjustment that reflects structural characteristics. That is, the update value is distributed based on the actual balance (or the default value of 6) of the adjacent vertices. Consequently, a higher number of connections results in a smaller update per edge, while a lower number results in a larger update.

[0552] If valenceUpdate[i] is false, the update value is calculated as follows. That is, the update value is simply multiplied by updateWeights[i][d] to obtain the residual (or displacement coefficient to be updated) dispCoeffArray[v][d] of vertex v.

[0553] disp = updateWeights[i][d] * dispCoeffArray[v][d]

[0554] Then, update the adjacent vertices as follows. That is, add the same update value disp to both vertices a and b.

[0555] dispCoeffArray[a][d] -= disp

[0556] dispCoeffArray[b][d] -= disp

[0557] That is, when valenceUpdate[i] is false, the update value is distributed to the two adjacent vertices in the same proportion without balance-based compensation. By doing so, the adjacent vertices receive the same update disp value of vertex v, and are compensated uniformly regardless of the balance. In other words, the update value disp calculated at vertex v is applied equally to the two adjacent base vertices a and b. In particular, the update value disp is subtracted from the displacement coefficients of the two vertices (e.g., disp value is subtracted from the dth displacement coefficient of vertex a and disp value is subtracted from the dth displacement coefficient of vertex b), and the residual separated from vertex v is reflected to the adjacent vertices. In this way, when valenceUpdate[i] is false, the update value is applied to all adjacent vertices in the same way, regardless of the balance. At this time, the adjacent vertices receive the same update value calculated at vertex v, and a uniform compensation is performed regardless of the balance.

[0558] According to embodiments, signaling information in a transmitting device (or an encoder of the transmitting device) may be generated by a metadata processing unit (not shown, may be referred to as a metadata generator, etc.) and provided to corresponding blocks in the transmitting device and / or a receiving device (or a decoder of the receiving device), and a metadata parser (not shown) of the receiving device may parse the received signaling information and provide it to the corresponding blocks. According to embodiments, each block of the receiving device may perform each operation based on the parsed signaling information.

[0559] In the present disclosure, a mesh data encoding method / device (such as a transmitting device (100) of FIG. 1, a mesh video encoder (102) of FIG. 1, an encoder of FIG. 2, a preprocessor of FIG. 3, a preprocessor of FIG. 5, an encoder of FIG. 6 and FIG. 7, an encoder of FIG. 13, an encoder of FIGS. 15 to 21, an encoding method of FIG. 32, etc.) can encode mesh data and generate and transmit a bitstream including encoded mesh data and parameter information related to the mesh data. In addition, a mesh data decoding method / device (such as a receiving device (110) of FIG. 1, a mesh video decoder (113) of FIGS. 11 and 12, a decoder of FIG. 14, a decoder of FIGS. 22 to 26, a decoding method of FIG. 33) according to embodiments can receive a bitstream and decode mesh data based on parameter information included in the bitstream.

[0560] A bitstream according to embodiments may include vdmc lifting transform parameters. In the present disclosure, vdmc lifting transform parameters may be used interchangeably with lifting transform parameters, with the same meaning.

[0561] Fig. 27 is a syntax structure illustrating an example of the lifting transformation parameters (vdmc_lifting_transform_parameters()) of the present disclosure. Fig. 27 is a syntax structure illustrating an embodiment for determining prediction and update weights differently depending on displacement vector components during lifting transformation.

[0562] Figures 28 and 29 are syntax structures illustrating other examples of the lifting transformation parameters (vdmc_lifting_transform_parameters()) of the present disclosure. Figures 28 and 29 are syntax structures illustrating an embodiment for selectively determining only some of the weights used in prediction or update during lifting transformation differently.

[0563] The vdmc_lifting_transform_parameters syntax structure of FIG. 27, FIG. 28, and FIG. 29 may be a syntax for parameters of a lifting transformation process used in V-DMC.

[0564] In the present disclosure, the lifting transformation parameters may be signaled in a syntax structure such as FIG. 27 and transmitted to the receiving device, or may be signaled in a syntax structure such as FIG. 28 and FIG. 29 and transmitted to the receiving device.

[0565] As mentioned above, applyLocalCoord is a flag indicating whether the displacement vector is transformed to the local coordinate system, i.e., a coordinate system transformation flag. For example, if this flag value is 0, it can indicate the (x,y,z) coordinate system, and if it is 1, it can indicate the (n,t,b) coordinate system. In other words, if this flag value is 1, the decoder of the receiving device can reverse transform the (n,t,b) coordinate system to the (x,y,z) coordinate system.

[0566] onlyNormFlag is a 1-bit flag indicating whether to encode the 1D displacement vector (normal component). If this flag value is 0, the decoder of the receiving device decodes the displacement vector of (n, t, b), and if it is 1, it decodes the 1D displacement value of the normal component.

[0567] dispEncType is a flag or index that determines the displacement vector encoding method. The decoder of the receiving device can perform displacement vector decoding through a 2D video codec, zero-run length decoding, or arithmetic decoding, depending on the parsed dispEncType.

[0568] A displacement vector decoding method can be determined through profileToolIdx. That is, a decoding method can be determined according to a profile defined in an encoder / decoder. According to embodiments, a decoder of a receiving device can perform displacement vector decoding through a 2D video codec, zero run length decoding, or arithmetic decoding, depending on profileToolIdx. If the displacement vector decoding method is determined through profileToolIdx, dispEncType can be omitted.

[0569] The following are examples of semantics related to displacement vector transform and inverse transform.

[0570] lodCount represents the number of mesh subdivision levels (if lodCount=3, the mesh contains subdivision levels 0, 1, and 2).

[0571] maxLOD represents the maximum mesh subdivision level (if lodCount=3, maxLOD has a value of 2).

[0572] currentLOD indicates the mesh subdivision level at which the lifting transformation / inverse transformation is currently being performed.

[0573] dispCoeff"[v]" represents the displacement vector value of vertex v.

[0574] resDispCoeff"[v]" represents the residual signal generated during the lifting transform prediction process.

[0575] vltp_log2_lifting_update_weight[ltpIndex][i][k] represents the weight coefficient value used as the update filter of the wavelet transform of the i-th LoD level for the displacement vector component of the k-th element. Here, ltpIndex may mean the index of the lifting transform parameter set.

[0576] vltp_log2_lifting_prediction_weight[ltpIndex][i][k] represents the weight coefficient value used as the prediction filter of the wavelet transform of the i-th LoD level for the displacement vector component of the k-th element. Here, ltpIndex may mean the index of the lifting transform parameter set.

[0577] vltp_component_adaptive_update_flag[ltpIndex] is a flag indicating whether adaptive weight updates are performed for each displacement vector component. For example, if the value of this flag is 1, the decoder of the receiving device can parse the weights used in the lifting transformation update process for each component of the displacement vector. If the value is 0, a single update weight can be shared among the components. Here, ltpIndex can mean the index of the lifting transformation parameter set.

[0578] vltp_component_adaptive_prediction_flag[ltpIndex] is a flag indicating whether adaptive weight prediction is performed for each displacement vector component. For example, if the value of this flag is 1, the decoder of the receiving device can parse the weights used in the lifting transformation prediction process for each component of the displacement vector, and if it is 0, a single prediction weight can be shared between components. Here, ltpIndex can mean the index of the lifting transformation parameter set. In addition, subdivisionCount (or subdivisionIterationCount) can indicate the number of subdivisions.

[0579] FIG. 30 and FIG. 31 are syntax structures showing another example of the lifting transform parameters (vdmc_lifting_transform_parameters()) of the present disclosure.

[0580] PredictionWeight can be an array representing the prediction weights used in the prediction of the lifting transformation. PredictionWeight can be two-dimensional, and the size of the array can be (ltpIndex * DisplacementDim).

[0581] UpdateWeight can be an array representing the update weights used in updating the lifting transformation. UpdateWeight can be three-dimensional, and the size of the array can be (ltpIndex * subdivisionCount * DisplacementDim).

[0582] And, depending on vltp_component_adaptive_update_flag, it is possible to determine whether to signal the update weight for each displacement vector component. For example, if the value of this flag (vltp_component_adaptive_update_flag) is 1, the update weight can be signaled for each displacement vector component, and if it is 0, only one update weight is signaled so that all displacement vector components use the same update weight, and the update weight of each component can be derived from the corresponding weight.

[0583] In addition, it is possible to determine whether to signal the prediction weight for each displacement vector component according to vltp_component_adaptive_prediction_flag. If the value of this flag (vltp_component_adaptive_prediction_flag) is 1, the prediction weight can be signaled for each displacement vector component. If it is 0, only one prediction weight is signaled so that all displacement vector components use the same prediction weight, and the prediction weight of each component can be derived from the corresponding weight.

[0584] As mentioned above, vltp_component_adaptive_update_flag[ltpIndex] represents a flag indicating whether adaptive weight update is performed for each displacement vector component. If the value of this flag is 1, the decoder of the receiving device can parse the weights used in the lifting transformation update process for each component of the displacement vector, and if it is 0, a single update weight can be shared among the components. Here, ltpIndex can mean the index of the lifting transformation parameter set.

[0585] vltp_component_adaptive_prediction_flag[ltpIndex] represents a flag indicating whether adaptive weight prediction is performed for each displacement vector component. If the value of this flag is 1, the decoder of the receiving device can parse the weights used in the lifting transformation prediction process for each component of the displacement vector. If the value is 0, a single prediction weight can be shared among the components. Here, ltpIndex can mean the index of the lifting transformation parameter set.

[0586] As described above, the present disclosure proposes a method for improving the lifting transformation of displacement vectors performed in existing V-DMCs. That is, in the case of existing dynamic mesh encoders / decoders, the same weights are used between displacement vector components during the prediction and update processes during the lifting transformation and inverse transformation calculation processes of displacement vectors.

[0587] In contrast, the present disclosure improves encoding performance by allowing different weights to be used for each component of the displacement vector in the prediction and / or update process for each component, taking into account the characteristics of each component of the displacement vector.

[0588] Furthermore, the present disclosure can improve the accuracy of the prediction process by applying adaptive prediction and / or adaptive update processes for each displacement vector component during the lifting transformation / inverse transformation process of the displacement vector. This can reduce the bit rate of the displacement vector and improve encoding performance.

[0589] Fig. 32 is a flowchart showing an example of a transmission method according to embodiments. The transmission method according to embodiments may include a step of encoding mesh data (S31011) and a step of transmitting a bitstream including the encoded mesh data (S31012). In one embodiment, the bitstream transmitted in step (S31012) includes a base mesh bitstream, a displacement vector bitstream, and a texture map bitstream.

[0590] According to embodiments, the step of encoding mesh data (S31011) may include a process of encoding a base mesh, a process of encoding displacement vectors or displacement vector transformation coefficients, and a process of encoding a texture map.

[0591] That is, in the process of encoding the base mesh, the original mesh to be transmitted is first simplified and mesh parameterized to generate a base mesh. The generated base mesh is quantized, and in the case of an inter-frame, the motion vector is calculated from the previously referenced restored base mesh and the motion vector is encoded. In the case of an intra-frame, it is encoded through static mesh encoding and transmitted as a base mesh bitstream.

[0592] And in the process of encoding the displacement vector (or displacement information), the displacement vector is calculated between the mesh data that has been simplified through mesh simplification, refined and fitted, and the mesh data restored from the previously encoded base mesh. In order to efficiently encode the calculated displacement vector, the displacement vector coordinate system is converted to a local coordinate system, and the displacement vector in the local coordinate system is converted and quantized into displacement vector coefficients, and then encoded into a displacement vector bitstream and transmitted.

[0593] The following describes the displacement vector conversion process during the displacement vector encoding process in more detail.

[0594] First, displacement vectors in the (x, y, z) or (n, t, bt) coordinate system can be converted into displacement vector coefficients by performing lifting transformation, wavelet transformation, etc. in the displacement vector transformation unit. When lifting transformation is performed, the number of lifting transformations can be determined using the number of mesh subdivision levels, the lifting transformation process can be performed in units of mesh subdivision levels, and lifting transformation prediction and lifting transformation update can be performed during the lifting transformation process.

[0595] The present disclosure can perform lifting transformation prediction with adaptive weights according to components of a displacement vector in a lifting transformation prediction process. According to an embodiment, the components of the displacement vector may be expressed as x, y, z three-dimensional components in the case of an (x, y, z) coordinate system according to a coordinate system expressing the displacement vector, or as normal, tangential, bi-tangential three-dimensional components in the case of a (normal, tangential, bi-tangential) coordinate system. In the lifting transformation prediction process, when the components of the displacement vector are k-dimensional, adaptive prediction can be performed for each displacement vector component using adaptive weights for each displacement vector component. At this time, the adaptive prediction weights for each component may be derived by considering a distribution for each displacement vector component, may be derived by the number or ratio of non-zero displacement vectors for each displacement vector component, may be derived by considering an average size of a displacement vector for each component, or may be derived by a quantization parameter for each displacement vector component. When considering the distribution of each displacement vector component, the weight may be determined according to the size of the variance depending on the embodiment. When considering the number or ratio of non-zero displacement vectors for each displacement vector component, the weight may be determined according to the size of the number of non-zero displacement vectors or the ratio of non-zero displacement vectors among the entire displacement vectors depending on the embodiment. When induced by the quantization parameter for each displacement vector component depending on the embodiment, the weight may be determined according to the size of the quantization parameter for each component or the difference between the quantization parameters for each component. In addition, when the adaptive prediction weight for each component is expressed in a (normal, tangential, bi-tangential) coordinate system, the displacement vector transformation prediction weights of the tangential and bi-tangential components may be shared with each other.

[0596] The present disclosure can perform a lifting transformation update using weights determined for each component of a displacement vector during a lifting transformation update process. Depending on the embodiment, the components of the displacement vector may be expressed in an (x, y, z) coordinate system or a (normal, tangential, bi-tangential) coordinate system. The adaptive update weights for each component may be derived by considering the distribution of each displacement vector component, may be derived by the number or ratio of non-zero displacement vectors for each displacement vector component, may be derived by considering the average size of the displacement vector for each component, or may be derived by a quantization parameter for each displacement vector component. When considering the distribution of each displacement vector component, the weights may be determined according to the size of the variance, depending on the embodiment. When considering the number or ratio of non-zero displacement vectors for each displacement vector component, the weights may be determined according to the size of the number of non-zero displacement vectors or the ratio of non-zero displacement vectors among all displacement vectors. In some embodiments, when the weights are determined based on the size of the quantization parameters for each component of the displacement vector or the difference between the quantization parameters for each component, the weights may be determined based on the size of the quantization parameters for each component or the difference between the quantization parameters for each component. In addition, when the adaptive update weights for each component are expressed in a (normal, tangential, bi-tangential) coordinate system, the displacement vector transformation update weights of the tangential and bi-tangential components may be shared with each other depending on the embodiment.

[0597] As described above, the displacement vector transform coefficients for which lifting transformation prediction and updating have been performed can be encoded after being quantized using a 2D video codec-based encoding method, and / or a zero-run length encoding method, and / or an arithmetic encoding method, etc. In this case, the quantized displacement vector transform coefficients can be encoded by selectively using only one of the 2D video codec-based encoding method, the zero-run length encoding method, and the arithmetic encoding method, or by using one or more various combinations thereof.

[0598] Finally, in the process of encoding the texture map, a new texture map having color information corresponding to the texture coordinates of the restored mesh is generated through a texture map generation unit (11026), and the generated texture map is encoded through a texture map encoder (i.e., a 2D video encoder) (11027) and transmitted as a texture bitstream.

[0599] In the step (S31012) of transmitting a bitstream including the above mesh data, the base mesh bitstream, displacement vector bitstream, and texture bitstream generated as described above in the step (S31011) of encoding the mesh data are multiplexed into a single bitstream, and transmitted to a receiving device through a transmitting device. At this time, signaling information including lifting transformation parameters such as those in FIGS. 27 to 30 and 31 may be transmitted to the receiving device for lifting inverse transformation prediction and update.

[0600] Fig. 33 is a flowchart showing an example of a receiving method according to embodiments. The receiving method according to embodiments may include a step (S32011) of receiving a bitstream including mesh data and a step (S32012) of decoding the mesh data included in the bitstream. In one embodiment, the step (S32011) of receiving the bitstream including mesh data receives a bitstream including a base mesh bitstream, a displacement vector bitstream, and a texture map bitstream. In addition, the step (S32011) of receiving the bitstream including mesh data also receives signaling information including lifting transformation parameters as in Figs. 27 to 31. At this time, the signaling information may be received while being included in the bitstream and may also be referred to as metadata.

[0601] According to embodiments, the step of decoding mesh data (S32012) may include a process of decoding a base mesh bitstream, a process of decoding a displacement vector bitstream, and a process of decoding a texture map bitstream.

[0602] That is, in the step (22011) of receiving a bitstream including mesh data, the received bitstream is demultiplexed into a base mesh bitstream, a displacement vector bitstream, and a texture map bitstream through a demultiplexing unit, and then a process of decoding each of them is performed.

[0603] First, in the process of decoding the base mesh bitstream, the base mesh bitstream is decoded through a motion vector encoder (15012) for inter-frames and a static mesh decoder (15013) for intra-frames. The decoded base mesh is then passed through a base mesh restoration unit (15014) to undergo mesh refinement.

[0604] In the process of decoding the displacement vector bitstream, the displacement vector bitstream decodes the displacement vector coefficients in the reverse order of encoding, performs inverse quantization and inverse transformation, and then is inversely transformed to the coordinate system, and then the mesh geometry information is restored together with the base mesh data.

[0605] Hereinafter, the displacement vector decoding process will be described in more detail. In the present disclosure, displacement vector decoding is performed based on signaling information transmitted and parsed from an encoder of a transmitting device. The signaling information of the present disclosure may include lifting transformation parameters such as those in FIGS. 27 to 31. In addition, the signaling information of the present disclosure may include one or more of a flag indicating whether to transform the displacement vector to a local coordinate system (applyLocalCoord), a flag indicating whether to encode a 1D displacement vector (normal component) (onlyNormFlag), a flag or index for determining a displacement vector decoding method (dispEncType), a profile tool index (profileToolIdx) for determining a displacement vector decoding method, the number of mesh refinement levels (lodCount), a maximum mesh refinement level (maxLOD), a mesh refinement level (currentLOD) on which lifting transformation / inverse transformation is currently being performed, a displacement vector value of vertex v (dispCoeff"[v]"), and a residual signal (resDispCoeff"[v]") generated in the lifting transformation prediction process.

[0606] In the present disclosure, displacement vector decoding may be performed through a 2D video decoder such as H.264, HEVC, or VVC, or through a zero-run length decoder or an arithmetic decoder. Furthermore, after decoding, the displacement vector may be inversely quantized and then subjected to inverse transformation. At this time, the inverse transformation may be performed by a lifting inverse transform, a wavelet inverse transform, or the like.

[0607] If a lifting inverse transform is performed, the number of lifting inverse transforms can be determined using the number of mesh subdivision levels (lodCount). Furthermore, the lifting inverse transform process can be performed on a mesh-by-mesh basis, and lifting inverse transform prediction and lifting inverse transform update can be performed during the lifting inverse transform process.

[0608] At this time, lifting inverse transformation prediction can be performed on the displacement vector for which lifting inverse transformation update has been performed. The present disclosure can perform lifting inverse transformation prediction with adaptive weights according to the components of the displacement vector. Depending on the embodiment, the components of the displacement vector can be expressed in the (x, y, z) coordinate system or can be expressed in the (normal, tangential, bi-tangential) coordinate system. In the lifting inverse transformation prediction process, when the displacement vector components are k-dimensional, adaptive prediction can be performed for each displacement vector component using adaptive weights for each displacement vector component. The lifting transformation adaptive prediction weights can be transmitted from the encoder of the transmitting device and parsed.

[0609] In the present disclosure, a process of updating the displacement vector of a vertex used for prediction using a parsed residual signal can be performed using a lifting inverse transformation. The present disclosure can perform the lifting inverse transformation update using weights determined for each component of the displacement vector. Depending on the embodiment, the components of the displacement vector may be expressed in the (x, y, z) coordinate system or in the (normal, tangential, bi-tangential) coordinate system.

[0610] As described above, when decoding, dequantization, and inverse transformation of a displacement vector are performed based on signaling information, the displacement vector coordinate system inverse transformation unit inversely transforms the displacement vector from the local coordinate system (n, t, b) to the canonical coordinate system (x, y, z) based on a flag (applyLocalCoord) indicating whether or not to transform the displacement vector into a local coordinate system.

[0611] In the mesh restoration unit (15016), the vertex geometry information of the restoration mesh is calculated by adding a restoration displacement vector to the vertices generated through the mesh refinement process, thereby restoring the final geometric information.

[0612] And, in the process of decoding the texture map bitstream, the received texture map bitstream is decoded through a texture map decoder (15021). The decoded texture map is used to generate a final restored mesh together with the restored geometry information in the mesh wall unit (15016).

[0613] Each of the parts, modules, or units described above may be software, processors, or hardware parts that execute sequential execution processes stored in memory (or storage units). Each of the steps described in the embodiments described above may be performed by processors, software, or hardware parts. Each of the modules / blocks / units described in the embodiments described above may operate as a processor, software, or hardware. In addition, the methods presented in the embodiments may be implemented as code. This code may be written on a processor-readable storage medium and thus may be read by a processor provided by an apparatus.

[0614] Furthermore, throughout the specification, when a part is said to "include" a component, this does not exclude other components, unless otherwise specifically stated, but rather implies the inclusion of other components. Furthermore, terms such as "part" described in the specification mean a unit that processes at least one function or operation, which may be implemented using hardware, software, or a combination of hardware and software.

[0615] For convenience of explanation, this specification has been described separately in each drawing. However, it is also possible to design new embodiments by combining the embodiments described in each drawing. Furthermore, designing a computer-readable recording medium containing a program for executing the previously described embodiments, as required by those skilled in the art, is also within the scope of the embodiments.

[0616] The devices and methods according to the embodiments are not limited to the configurations and methods of the embodiments described above, but the embodiments may be configured by selectively combining all or part of each embodiment so that various modifications can be made.

[0617] Although preferred embodiments of the embodiments have been illustrated and described, the embodiments are not limited to the specific embodiments described above, and various modifications may be made by those skilled in the art to which the present disclosure pertains without departing from the spirit or scope of the embodiments claimed in the claims, and such modifications should not be understood individually from the technical idea or prospect of the embodiments.

[0618] The various components of the devices of the embodiments may be implemented by hardware, software, firmware, or a combination thereof. The various components of the embodiments may be implemented by a single chip, for example, a single hardware circuit. The components according to the embodiments may be implemented by separate chips. At least one of the components of the devices of the embodiments may be configured with one or more processors capable of executing one or more programs, and the one or more programs may perform, or include instructions for performing, one or more of the operations / methods according to the embodiments. The executable instructions for performing the methods / operations of the devices of the embodiments may be stored in non-transitory CRMs or other computer program products configured to be executed by one or more processors, or may be stored in temporary CRMs or other computer program products configured to be executed by one or more processors. In addition, the memory according to the embodiments may be used as a concept including not only volatile memory (e.g., RAM, etc.), but also non-volatile memory, flash memory, PROM, etc. Additionally, it may include implementations in the form of carrier waves, such as transmissions via the Internet. Furthermore, processor-readable recording media may be distributed across network-connected computer systems, allowing processor-readable code to be stored and executed in a distributed manner.

[0619] In this document, " / " and "," are interpreted as "and / or". For example, "A / B" is interpreted as "A and / or B", and "A, B" is interpreted as "A and / or B". Additionally, "A / B / C" means "at least one of A, B, and / or C". Also, "A, B, C" means "at least one of A, B, and / or C". Additionally, "or" in this document is interpreted as "and / or". For example, "A or B" can mean 1) "A" only, 2) "B" only, or 3) "A and B". In other words, "or" in this document can mean "additionally or alternatively".

[0620] Various elements of the embodiments may be implemented by hardware, software, firmware, or a combination thereof. Various elements of the embodiments may be implemented on a single chip, such as a hardware circuit. In some embodiments, the embodiments may optionally be implemented on separate chips. In some embodiments, at least one of the elements of the embodiments may be implemented within one or more processors that include instructions for performing operations according to the embodiments.

[0621] Additionally, the operations according to the embodiments described in this document may be performed by a transceiver device including one or more memories and / or one or more processors according to the embodiments. One or more memories may store programs for processing / controlling the operations according to the embodiments, and one or more processors may control various operations described in this document. One or more processors may be referred to as a controller, etc. The operations according to the embodiments may be performed by firmware, software, and / or a combination thereof, and the firmware, software, and / or a combination thereof may be stored in a processor or a memory.

[0622] Terms such as "first" and "second" may be used to describe various components of the embodiments. However, the various components according to the embodiments should not be interpreted in a limited manner by these terms. These terms are merely used to distinguish one component from another. For example, a first user input signal may be referred to as a "second user input signal." Similarly, a second user input signal may be referred to as a "first user input signal." The use of these terms should be interpreted as not departing from the scope of the various embodiments. Although "first user input signal" and "second user input signal" are both user input signals, they do not necessarily mean the same user input signals unless the context clearly indicates otherwise.

[0623] The terminology used to describe the embodiments is for the purpose of describing particular embodiments and is not intended to be limiting of the embodiments. As used in the description of the embodiments and in the claims, the singular is intended to include the plural unless the context clearly dictates otherwise. The expressions “and / or” are used to mean all possible combinations of the terms. The expression “comprises” or “includes” describes the presence of features, numbers, steps, elements, and / or components, but does not mean that additional features, numbers, steps, elements, and / or components are not included. Conditional expressions such as “if” or “when” used to describe the embodiments are not intended to be limited to only optional cases. When a specific condition is satisfied, a related action is performed in response to a specific condition, or a related definition is intended to be interpreted.

[0624] As described above, the relevant contents have been described in the best form for carrying out the embodiments.

[0625] As described above, the embodiments may be applied in whole or in part to mesh data transmission and reception devices and systems. Those skilled in the art may variously modify or alter the embodiments within the scope of the embodiments. The embodiments may include modifications / alterations, and the modifications / alterations do not depart from the scope of the claims and their equivalents.

Claims

1. A step of receiving a bitstream containing mesh data; and A step of decoding the above mesh data; comprising: How to decode.

2. In the first paragraph, the step of decoding the mesh data A base mesh processing step for restoring a base mesh from a base mesh bitstream included in the above bitstream; A displacement information processing step for restoring displacement information from a displacement vector bitstream included in the above bitstream; A restoration step for restoring a mesh based on the base mesh and the displacement information; and A decoding method comprising a texture map processing step of restoring a texture map from a texture map bitstream included in the above bitstream.

3. In the second paragraph, the displacement information processing step A step of decoding the displacement vector bitstream into displacement information; a step of dequantizing the decoded displacement information; and A decoding method comprising a step of inversely transforming the above-described inverse quantized displacement information.

4. In paragraph 3, The above inverse transformation step includes a step of inversely transforming the inverse quantized displacement information in a lifting manner, The step of reversely converting to the above lifting method is: A step of performing a lifting inverse transformation update by applying an update weight to each component of the above displacement information, and A decoding method comprising a step of performing lifting inverse transformation prediction by applying prediction weights to each component of the updated displacement information.

5. In the fourth paragraph, the lifting inverse transformation update step A decoding method for performing the lifting inverse transformation update based on the valence information calculated from the above base mesh.

6. Memory; and At least one processor connected to the memory; At least one processor of the above: Receive a bitstream containing mesh data; and configured to decode the above mesh data; Decoding device.

7. In the 6th paragraph, the at least one processor A base mesh processing unit that restores a base mesh from a base mesh bitstream included in the above bitstream; A displacement information processing unit that restores displacement information from a displacement vector bitstream included in the above bitstream; A restoration unit that restores a mesh based on the base mesh and the displacement information; and A decoding device including a texture map processing unit that restores a texture map from a texture map bitstream included in the above bitstream.

8. In paragraph 7, the displacement information processing unit A displacement information decoding unit that decodes the displacement vector bitstream into displacement information; A dequantization unit that dequantizes the decoded displacement information; and A decoding device including an inverse transform unit that inversely transforms the above inverse quantized displacement information.

9. In the 8th paragraph, the reverse conversion unit A lifting inverse transformation update unit that performs lifting inverse transformation update by applying update weights to each component of the above displacement information; and A decoding device including a lifting inverse transform prediction unit that performs lifting inverse transform prediction by applying prediction weights to each component of the updated displacement information.

10. In the 9th paragraph, the lifting inverse transformation update unit A decoding device that performs the lifting inverse transformation update based on the valence information calculated from the base mesh.

11. Step of encoding mesh data; and A step of transmitting a bitstream including the encoded mesh data; comprising: Encoding method.

12. In the 11th paragraph, the encoding step A base mesh processing step for generating a base mesh bitstream by encoding a base mesh generated by simplifying the original mesh; A displacement information processing step of generating a displacement vector bitstream by encoding displacement information generated based on the above base mesh; A mesh restoration step for restoring a mesh based on the encoded base mesh and the encoded displacement information; and An encoding method comprising a texture map processing step of generating a texture map bitstream by encoding a texture map generated based on the original mesh and the restored mesh.

13. In the 12th paragraph, the displacement information processing step A step of converting the above displacement information; A step of quantizing the above-mentioned transformed displacement information; and An encoding method comprising a step of encoding the quantized displacement information into a displacement vector bitstream.

14. In paragraph 13, The above conversion step includes a step of converting the displacement information into a lifting method, The steps for converting to the above lifting method are: A step of performing lifting transformation prediction by applying prediction weights to each component of the above displacement information, and An encoding method comprising a step of performing a lifting transformation update by applying update weights to each component of displacement information for which the above prediction is performed.

15. In the 14th paragraph, the lifting transformation update step An encoding method for performing the lifting transformation update based on the valence information calculated from the base mesh.

Images