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

Abstract

A decoding method according to embodiments may comprise the steps of: receiving a bitstream including point cloud data; and decoding the point cloud data. An encoding method according to embodiments may comprise the steps of: encoding point cloud data; and transmitting a bitstream including the point cloud data.

Description

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

[0001] Embodiments relate to a method and apparatus for processing point cloud content.

[0002] Point cloud content is represented as a point cloud, a collection of points within a coordinate system representing three-dimensional space. Point cloud content can represent three-dimensional media and is used to provide various services such as VR (Virtual Reality), AR (Augmented Reality), MR (Mixed Reality), and autonomous driving services. However, representing point cloud content requires tens to hundreds of thousands of point data. Therefore, a method for efficiently processing massive amounts of point data is required.

[0003] Embodiments provide devices and methods for efficiently processing point cloud data. Embodiments provide methods and devices for processing point cloud data to address latency and encoding / decoding complexity.

[0004] However, the scope of the embodiments is not limited to the technical tasks described above, 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 described content.

[0005] A method for transmitting point cloud data according to embodiments may include a step of encoding point cloud data and a step of transmitting a bitstream including the point cloud data. A method for receiving point cloud data according to embodiments may include a step of receiving a bitstream including point cloud data and a step of decoding the point cloud data.

[0006] The device and method according to the embodiments can process point cloud data with high efficiency.

[0007] The device and method according to the embodiments can provide a high quality point cloud service.

[0008] The device and method according to the embodiments can provide point cloud content for providing general services such as VR services and autonomous driving services.

[0009] 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.

[0010] Figure 1 illustrates an example of a point cloud content provision system according to embodiments.

[0011] FIG. 2 is a block diagram illustrating a point cloud content provision operation according to embodiments.

[0012] FIG. 3 illustrates an example of a point cloud encoder according to embodiments.

[0013] Figure 4 illustrates examples of octree and occupancy codes according to embodiments.

[0014] Figure 5 shows an example of a point configuration by LOD according to embodiments.

[0015] Figure 6 shows an example of a point configuration by LOD according to embodiments.

[0016] Fig. 7 illustrates an example of a point cloud decoder according to embodiments.

[0017] Figure 8 is an example of a transmission device according to embodiments.

[0018] Fig. 9 is an example of a receiving device according to embodiments.

[0019] Fig. 10 shows an example of a structure that can be linked with a point cloud data transmission / reception method / device according to embodiments.

[0020] Figure 11 illustrates the encoding, transmission, and decoding processes of point cloud data according to embodiments.

[0021] Figure 12 illustrates a layer-based point cloud data configuration according to embodiments.

[0022] Figure 13 illustrates a geometry and attribute bitstream structure according to embodiments.

[0023] Figure 14 shows a bitstream configuration according to embodiments and a bitstream alignment method according to embodiments.

[0024] Figure 15 illustrates a bitstream alignment method according to embodiments.

[0025] Figure 16 illustrates a bitstream alignment method according to embodiments.

[0026] Figure 17 illustrates a method for selecting geometry data and attribute data according to embodiments.

[0027] Figure 18 shows a bitstream selection method according to embodiments.

[0028] FIG. 19 illustrates a method for constructing a slice including point cloud data according to embodiments.

[0029] Figure 20 illustrates single-slice and segmented-slice based geometry tree structures according to embodiments.

[0030] FIG. 21 illustrates a layer group structure of a geometry coding tree and an aligned layer group structure of an attribute coding tree according to embodiments.

[0031] Figure 22 illustrates the layer group and subgroup structure according to embodiments.

[0032] Figure 23 illustrates an example of context references between layer groups according to embodiments.

[0033] Figure 24 illustrates an example of context reference between groups according to embodiments.

[0034] Figure 25 illustrates an example of context buffer management according to embodiments.

[0035] Figure 26 illustrates an example of context buffer management according to embodiments.

[0036] Figure 27 illustrates an example of context buffer management according to embodiments.

[0037] Figure 28 shows a table comparing context memory usage of context buffers according to embodiments.

[0038] Figure 29 shows a table comparing context memory usage of context buffers according to embodiments.

[0039] Figure 30 is a table showing the results of context buffer management according to embodiments.

[0040] Figure 31 is a table showing the results of context buffer management according to embodiments.

[0041] Figure 32 illustrates a context buffer release method according to embodiments.

[0042] Figure 33 illustrates a context buffer release method according to embodiments.

[0043] Figure 34 illustrates a context memory management method according to embodiments.

[0044] Figure 35 shows a bitstream including point cloud data according to embodiments.

[0045] Figure 36 shows a sequence parameter set of a bitstream according to embodiments.

[0046] Figure 37 illustrates a dependent geometry data unit header of a bitstream according to embodiments.

[0047] Figure 38 shows a dependent attribute data unit header of a bitstream according to embodiments.

[0048] Figures 39 a and 39b illustrate layer group structure inventories according to embodiments.

[0049] Fig. 40 illustrates a point cloud data transmission device / method according to embodiments.

[0050] Fig. 41 illustrates a point cloud data receiving device / method according to embodiments.

[0051] Figure 42 illustrates a method for receiving point cloud data according to embodiments.

[0052] Fig. 43 illustrates a layer group-based point cloud data encoding method according to embodiments.

[0053] Figure 44 illustrates a layer group-based point cloud data decryption method according to embodiments.

[0054] Figure 45 illustrates a context buffer management method according to embodiments.

[0055] Figure 46 illustrates a context buffer management method according to embodiments.

[0056] Figure 47 illustrates a context buffer management method according to embodiments.

[0057] Figure 48 shows a geometry data unit header syntax according to embodiments.

[0058] Figure 49 illustrates a dependent geometry data unit header syntax according to embodiments.

[0059] Figure 50 illustrates attribute data unit header syntax according to embodiments.

[0060] Figure 51 illustrates a dependent attribute data unit header syntax according to embodiments.

[0061] Figure 52 shows the effects according to embodiments.

[0062] Figure 53 shows the effects according to embodiments.

[0063] Figure 54 shows the sequence parameter set syntax according to embodiments.

[0064] Figure 55 illustrates a geometry data unit header syntax according to embodiments.

[0065] Figure 56 illustrates a dependent geometry data unit header syntax according to embodiments.

[0066] Figure 57 illustrates attribute data unit header syntax according to embodiments.

[0067] Figure 58 illustrates a dependent attribute data unit header syntax according to embodiments.

[0068] Figure 59 illustrates a context buffer management method according to embodiments.

[0069] Figure 60 illustrates a context buffer management method according to embodiments.

[0070] Figure 61 shows the sequence parameter set syntax according to embodiments.

[0071] Figure 62 illustrates a geometry data unit header syntax according to embodiments.

[0072] Figure 63 illustrates a dependent geometry data unit header syntax according to embodiments.

[0073] Figures 64 and 65 illustrate point cloud data transmission and reception devices / methods according to embodiments.

[0074] Fig. 66 shows a point cloud data transmission / reception device / method according to embodiments.

[0075] Fig. 67 shows a point cloud data transmission / reception device / method according to embodiments.

[0076] Figure 68 shows an encoding method according to embodiments.

[0077] Figure 69 shows a decryption method according to embodiments.

[0078] 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.

[0079] 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.

[0080] Figure 1 illustrates an example of a point cloud content provision system according to embodiments.

[0081] The point cloud content provision system illustrated in FIG. 1 may include a transmission device (10000) and a reception device (10004). The transmission device (10000) and the reception device (10004) are capable of wired and wireless communication to transmit and receive point cloud data.

[0082] A transmission device (10000) according to embodiments can secure, process, and transmit a point cloud video (or point cloud content). According to embodiments, the transmission device (10000) can include a fixed station, a base transceiver system (BTS), a network, an Artificial Intelligence (AI) device and / or system, a robot, an AR / VR / XR device and / or a server, etc. In addition, according to embodiments, the transmission device (10000) can include a device that performs communication with a base station and / or other wireless devices using a wireless access technology (e.g., 5G NR (New RAT), LTE (Long Term Evolution)), a robot, a vehicle, an AR / VR / XR device, a portable device, a home appliance, an IoT (Internet of Things) device, an AI device / server, etc.

[0083] A transmission device (10000) according to embodiments includes a point cloud video acquisition unit (Point Cloud Video Acquisition, 10001), a point cloud video encoder (Point Cloud Video Encoder, 10002), and / or a transmitter (or communication module, 10003).

[0084] A point cloud video acquisition unit (10001) according to embodiments acquires a point cloud video through a processing process such as capture, synthesis, or generation. The point cloud video is point cloud content expressed as a point cloud, which is a collection of points located in a three-dimensional space, and may be referred to as point cloud video data, etc. The point cloud video according to embodiments may include one or more frames. One frame represents a still image / picture. Therefore, the point cloud video may include a point cloud image / frame / picture, and may be referred to as any one of a point cloud image, a frame, and a picture.

[0085] A point cloud video encoder (10002) according to embodiments encodes acquired point cloud video data. The point cloud video encoder (10002) may encode point cloud video data based on point cloud compression coding. The point cloud compression coding according to embodiments may include G-PCC (Geometry-based Point Cloud Compression) coding and / or V-PCC (Video-based Point Cloud Compression) coding or next-generation coding. In addition, the point cloud compression coding according to embodiments is not limited to the above-described embodiment. The point cloud video encoder (10002) may output a bitstream including encoded point cloud video data. The bitstream may include not only encoded point cloud video data but also signaling information related to encoding of the point cloud video data.

[0086] A transmitter (10003) according to embodiments transmits a bitstream including encoded point cloud video data. The bitstream according to embodiments is encapsulated into a file or segment (e.g., streaming segment) and transmitted through various networks such as a broadcast network and / or a broadband network. Although not shown in the drawing, the transmission device (10000) may include an encapsulation unit (or an encapsulation module) that performs an encapsulation operation. In addition, the encapsulation unit may be included in the transmitter (10003) according to embodiments. According to embodiments, the file or segment may be transmitted to a receiving device (10004) through a network or may be stored in a digital storage medium (e.g., USB, SD, CD, DVD, Blu-ray, HDD, SSD, etc.). The transmitter (10003) according to embodiments may communicate with the receiving device (10004) (or receiver (10005)) via a network such as 4G, 5G, or 6G via wired / wireless communication. Additionally, the transmitter (10003) can perform data processing operations required according to a network system (e.g., a communication network system such as 4G, 5G, or 6G). Additionally, the transmission device (10000) can transmit encapsulated data in an on-demand manner.

[0087] A receiving device (10004) according to embodiments includes a receiver (Receiver) 10005, a point cloud video decoder (Point Cloud Decoder) 10006, and / or a renderer (Renderer) 10007. According to embodiments, the receiving device (10004) may include a device, robot, vehicle, AR / VR / XR device, mobile device, home appliance, IoT (Internet of Things) device, AI device / server, etc. that performs communication with a base station and / or other wireless devices using a wireless access technology (e.g., 5G NR (New RAT), LTE (Long Term Evolution)).

[0088] A receiver (10005) according to embodiments receives a bitstream containing point cloud video data or a file / segment in which the bitstream is encapsulated, from a network or a storage medium. The receiver (10005) may perform data processing operations required according to a network system (e.g., a communication network system such as 4G, 5G, or 6G). The receiver (10005) according to embodiments may decapsulate the received file / segment and output a bitstream. In addition, the receiver (10005) according to embodiments may include a decapsulation unit (or decapsulation module) for performing the decapsulation operation. In addition, the decapsulation unit may be implemented as a separate element (or component) from the receiver (10005).

[0089] A point cloud video decoder (10006) decodes a bitstream containing point cloud video data. The point cloud video decoder (10006) can decode the point cloud video data according to how it is encoded (e.g., the reverse process of the operation of the point cloud video encoder (10002)). Accordingly, the point cloud video decoder (10006) can decode the point cloud video data by performing point cloud decompression coding, which is the reverse process of point cloud compression. The point cloud decompression coding includes G-PCC coding.

[0090] The renderer (10007) renders decoded point cloud video data. The renderer (10007) can output point cloud content by rendering not only point cloud video data but also audio data. According to embodiments, the renderer (10007) may include a display for displaying the point cloud content. According to embodiments, the display may not be included in the renderer (10007) but may be implemented as a separate device or component.

[0091] The dotted arrows in the drawing indicate the transmission path of feedback information acquired from the receiving device (10004). The feedback information is information for reflecting the interaction with the user consuming the point cloud content, and includes information about the user (e.g., head orientation information, viewport information, etc.). In particular, when the point cloud content is content for a service requiring interaction with the user (e.g., autonomous driving service, etc.), the feedback information may be transmitted to the content transmitter (e.g., the transmitting device (10000)) and / or the service provider. Depending on the embodiments, the feedback information may be used by the receiving device (10004) as well as the transmitting device (10000), or may not be provided.

[0092] Head orientation information according to embodiments is information about the position, direction, angle, movement, etc. of the user's head. The receiving device (10004) according to embodiments can calculate viewport information based on the head orientation information. The viewport information is information about the area of ​​the point cloud video that the user is looking at. The viewpoint is the point where the user is looking at the point cloud video, and may mean the exact center point of the viewport area. In other words, the viewport is an area centered on the viewpoint, and the size, shape, etc. of the area can be determined by the FOV (Field Of View). Therefore, the receiving device (10004) can extract viewport information based on the vertical or horizontal FOV supported by the device in addition to the head orientation information. In addition, the receiving device (10004) performs gaze analysis, etc. to check the user's point cloud consumption method, the area of ​​the point cloud video that the user is looking at, the gaze time, etc. According to embodiments, the receiving device (10004) may transmit feedback information including gaze analysis results to the transmitting device (10000). The feedback information according to embodiments may be acquired during a rendering and / or display process. The feedback information according to embodiments may be acquired by one or more sensors included in the receiving device (10004). Additionally, according to embodiments, the feedback information may be acquired by a renderer (10007) or a separate external element (or device, component, etc.). The dotted line in Fig. 1 represents a transmission process of feedback information acquired by the renderer (10007). The point cloud content providing system may process (encode / decode) point cloud data based on the feedback information. Therefore, the point cloud video data decoder (10006) may perform a decoding operation based on the feedback information.Additionally, the receiving device (10004) can transmit feedback information to the transmitting device (10000). The transmitting device (10000) (or point cloud video data encoder (10002)) can perform an encoding operation based on the feedback information. Therefore, the point cloud content providing system can efficiently process necessary data (e.g., point cloud data corresponding to the user's head position) based on the feedback information without processing (encoding / decoding) all point cloud data, and provide point cloud content to the user.

[0093] According to embodiments, the transmitting device (10000) may be referred to as an encoder, a transmitting device, a transmitter, etc., and the receiving device (10004) may be referred to as a decoder, a receiving device, a receiver, etc.

[0094] Point cloud data processed (processed through a series of processes of acquisition / encoding / transmission / decoding / rendering) in the point cloud content providing system of FIG. 1 according to embodiments may be referred to as point cloud content data or point cloud video data. According to embodiments, point cloud content data may be used as a concept including metadata or signaling information related to point cloud data.

[0095] The elements of the point cloud content provision system illustrated in FIG. 1 may be implemented by hardware, software, a processor, and / or a combination thereof.

[0096] FIG. 2 is a block diagram illustrating a point cloud content provision operation according to embodiments.

[0097] The block diagram of Fig. 2 illustrates the operation of the point cloud content provision system described in Fig. 1. As described above, the point cloud content provision system can process point cloud data based on point cloud compression coding (e.g., G-PCC).

[0098] A point cloud content providing system according to embodiments (e.g., a point cloud transmission device (10000) or a point cloud video acquisition unit (10001)) can acquire a point cloud video (20000). The point cloud video is expressed as a point cloud belonging to a coordinate system representing a three-dimensional space. The point cloud video according to embodiments can include a Ply (Polygon File format or the Stanford Triangle format) file. If the point cloud video has one or more frames, the acquired point cloud video can include one or more Ply files. The Ply file includes point cloud data such as the geometry and / or attributes of points. The geometry includes the positions of points. The position of each point can be expressed as parameters (e.g., values ​​of each of the X-axis, Y-axis, and Z-axis) representing a three-dimensional coordinate system (e.g., a coordinate system composed of XYZ axes). Attributes include attributes of points (e.g., texture information of each point, color (YCbCr or RGB), reflectance (r), transparency, etc.). A point has one or more attributes (or properties). For example, a point may have one attribute, color, or two attributes, color and reflectance. According to embodiments, geometry may be referred to as positions, geometry information, geometry data, etc., and attributes may be referred to as attributes, attribute information, attribute data, etc.Additionally, a point cloud content provision system (e.g., a point cloud transmission device (10000) or a point cloud video acquisition unit (10001)) can obtain point cloud data from information related to the acquisition process of a point cloud video (e.g., depth information, color information, etc.).

[0099] A point cloud content providing system according to embodiments (e.g., a transmission device (10000) or a point cloud video encoder (10002)) can encode point cloud data (20001). The point cloud content providing system can encode point cloud data based on point cloud compression coding. As described above, point cloud data can include geometry and attributes of points. Therefore, the point cloud content providing system can perform geometry encoding to encode geometry and output a geometry bitstream. The point cloud content providing system can perform attribute encoding to encode attributes and output an attribute bitstream. According to embodiments, the point cloud content providing system can perform attribute encoding based on geometry encoding. The geometry bitstream and the attribute bitstream according to embodiments can be multiplexed and output as a single bitstream. A bitstream according to embodiments may further include signaling information related to geometry encoding and attribute encoding.

[0100] A point cloud content providing system according to embodiments (e.g., a transmission device (10000) or a transmitter (10003)) can transmit encoded point cloud data (20002). As described in FIG. 1, the encoded point cloud data can be expressed as a geometry bitstream and an attribute bitstream. In addition, the encoded point cloud data can be transmitted in the form of a bitstream together with signaling information related to encoding of the point cloud data (e.g., signaling information related to geometry encoding and attribute encoding). In addition, the point cloud content providing system can encapsulate a bitstream that transmits the encoded point cloud data and transmit it in the form of a file or segment.

[0101] A point cloud content providing system according to embodiments (e.g., a receiving device (10004) or a receiver (10005)) can receive a bitstream including encoded point cloud data. In addition, the point cloud content providing system (e.g., a receiving device (10004) or a receiver (10005)) can demultiplex the bitstream.

[0102] A point cloud content providing system (e.g., a receiving device (10004) or a point cloud video decoder (10005)) can decode encoded point cloud data (e.g., a geometry bitstream, an attribute bitstream) transmitted as a bitstream. The point cloud content providing system (e.g., a receiving device (10004) or a point cloud video decoder (10005)) can decode the point cloud video data based on signaling information related to encoding of the point cloud video data included in the bitstream. The point cloud content providing system (e.g., a receiving device (10004) or a point cloud video decoder (10005)) can decode the geometry bitstream to restore positions (geometry) of points. The point cloud content providing system can decode the attribute bitstream based on the restored geometry to restore attributes of points. A point cloud content provision system (e.g., a receiving device (10004) or a point cloud video decoder (10005)) can reconstruct a point cloud video based on positions and decoded attributes according to the reconstructed geometry.

[0103] A point cloud content providing system (e.g., a receiving device (10004) or a renderer (10007)) according to embodiments can render decoded point cloud data (20004). The point cloud content providing system (e.g., a receiving device (10004) or a renderer (10007)) can render the decoded geometry and attributes through a decoding process according to various rendering methods. Points of the point cloud content may be rendered as vertices having a certain thickness, cubes having a certain minimum size centered on the vertex position, or circles centered on the vertex position. All or a portion of the rendered point cloud content is provided to a user through a display (e.g., a VR / AR display, a general display, etc.).

[0104] A point cloud content provision system according to embodiments (e.g., a receiving device (10004)) can obtain feedback information (20005). The point cloud content provision system can encode and / or decode point cloud data based on the feedback information. The feedback information and the operation of the point cloud content provision system according to embodiments are identical to the feedback information and operation described in FIG. 1, and therefore, a detailed description thereof will be omitted.

[0105] FIG. 3 illustrates an example of a point cloud encoder according to embodiments.

[0106] FIG. 3 illustrates an example of a point cloud video encoder (10002) of FIG. 1. The point cloud encoder reconstructs point cloud data (e.g., positions and / or attributes of points) and performs an encoding operation to adjust the quality of point cloud content (e.g., lossless, lossy, near-lossless) depending on network conditions or applications. If the total size of the point cloud content is large (e.g., point cloud content of 60 Gbps at 30 fps), the point cloud content provision system may not be able to stream the content in real time. Therefore, the point cloud content provision system can reconstruct the point cloud content based on the maximum target bitrate in order to provide it according to the network environment, etc.

[0107] As described in FIGS. 1 and 2, the point cloud encoder can perform geometry encoding and attribute encoding. Geometry encoding is performed before attribute encoding.

[0108] The point cloud encoder according to the embodiments includes a coordinate system transformation unit (Transformation Coordinates, 30000), a quantization unit (Quantize and Remove Points (Voxelize), 30001), an octree analysis unit (Analyze Octree, 30002), a surface approximation analysis unit (Analyze Surface Approximation, 30003), an arithmetic encoder (Arithmetic Encode, 30004), a geometry reconstruction unit (Reconstruct Geometry, 30005), a color transformation unit (Transform Colors, 30006), an attribute transformation unit (Transfer Attributes, 30007), a RAHT transformation unit (30008), a LOD generation unit (Generated LOD, 30009), a lifting transformation unit (Lifting) (30010), and a coefficient quantization unit (Quantize Coefficients, 30011) and / or an arithmetic encoder (30012).

[0109] The coordinate system transformation unit (30000), the quantization unit (30001), the octree analysis unit (30002), the surface approximation analysis unit (30003), the arithmetic encoder (30004), and the geometry reconstruction unit (30005) can perform geometry encoding. The geometry encoding according to the embodiments can include octree geometry coding, direct coding, trisoup geometry encoding, and entropy encoding. Direct coding and trisoup geometry encoding are applied selectively or in combination. In addition, the geometry encoding is not limited to the above examples.

[0110] As illustrated in the drawing, a coordinate system conversion unit (30000) according to embodiments receives positions and converts them into coordinates. For example, the positions may be converted into location information of a three-dimensional space (e.g., a three-dimensional space expressed in an XYZ coordinate system, etc.). The location information of the three-dimensional space according to embodiments may be referred to as geometry information.

[0111] A quantization unit (30001) according to embodiments quantizes geometry. For example, the quantization unit (30001) may quantize points based on the minimum position value of all points (e.g., the minimum value on each axis for the X-axis, Y-axis, and Z-axis). The quantization unit (30001) performs a quantization operation of multiplying the difference between the minimum position value and the position value of each point by a preset quantization scale value, and then rounding down or up to find the closest integer value. Accordingly, one or more points may have the same quantized position (or position value). The quantization unit (30001) according to embodiments performs voxelization based on the quantized positions to reconstruct the quantized points. The minimum unit containing two-dimensional image / video information is a pixel, and points of point cloud content (or three-dimensional point cloud video) according to embodiments may be included in one or more voxels. A voxel is a combination of a volume and a pixel, and refers to a three-dimensional cubic space generated when a three-dimensional space is divided into units (unit=1.0) based on axes representing the three-dimensional space (e.g., X-axis, Y-axis, Z-axis). The quantization unit (40001) may match groups of points in the three-dimensional space to voxels. According to embodiments, one voxel may include only one point. According to embodiments, one voxel may include one or more points. In addition, in order to express one voxel as one point, the position of the center of the voxel may be set based on the positions of one or more points included in one voxel. In this case, the attributes of all positions contained in one voxel can be combined and assigned to the voxel.

[0112] The octree analysis unit (30002) according to the embodiments performs octree geometry coding (or octree coding) to represent voxels in an octree structure. The octree structure represents points matched to voxels based on an octree structure.

[0113] The surface approximation analysis unit (30003) according to the embodiments can analyze and approximate an octree. The octree analysis and approximation according to the embodiments is a process of analyzing and voxelizing an area including a large number of points to efficiently provide an octree and voxelization.

[0114] An arithmetic encoder (30004) according to embodiments entropy encodes an octree and / or an approximated octree. For example, the encoding method includes an arithmetic encoding method. The encoding results in a geometry bitstream.

[0115] The color conversion unit (30006), the attribute conversion unit (30007), the RAHT conversion unit (30008), the LOD generation unit (30009), the lifting conversion unit (30010), the coefficient quantization unit (30011) and / or the arithmetic encoder (30012) perform attribute encoding. As described above, one point may have one or more attributes. Attribute encoding according to embodiments is applied equally to the attributes of one point. However, when one attribute (e.g., color) includes one or more elements, independent attribute encoding is applied to each element. Attribute encoding according to embodiments may include color transform coding, attribute transform coding, RAHT (Region Adaptive Hierarchial Transform) coding, Interpolarization-based hierarchical nearest-neighbor prediction-Prediction Transform) coding, and lifting transform (interpolation-based hierarchical nearest-neighbor prediction with an update / lifting step (Lifting Transform)) coding. Depending on the point cloud content, the above-described RAHT coding, prediction transform coding, and lifting transform coding may be selectively used, or a combination of one or more codings may be used. In addition, attribute encoding according to embodiments is not limited to the above-described examples.

[0116] The color conversion unit (30006) according to the embodiments performs color conversion coding to convert color values ​​(or textures) included in attributes. For example, the color conversion unit (30006) may convert the format of color information (e.g., convert from RGB to YCbCr). The operation of the color conversion unit (30006) according to the embodiments may be optionally applied depending on the color values ​​included in the attributes.

[0117] The geometry reconstruction unit (30005) according to the embodiments reconstructs (decompresses) an octree and / or an approximated octree. The geometry reconstruction unit (30005) reconstructs an octree / voxel based on the results of analyzing the distribution of points. The reconstructed octree / voxel may be referred to as a reconstructed geometry (or restored geometry).

[0118] The attribute conversion unit (30007) according to the embodiments performs attribute conversion that converts attributes based on positions for which geometry encoding has not been performed and / or reconstructed geometry. As described above, since the attributes are dependent on the geometry, the attribute conversion unit (30007) can convert the attributes based on the reconstructed geometry information. For example, the attribute conversion unit (30007) can convert the attribute of a point at a position based on the position value of the point included in the voxel. As described above, when the position of the center point of a voxel is set based on the positions of one or more points included in the voxel, the attribute conversion unit (30007) converts the attributes of one or more points. When try-soup geometry encoding is performed, the attribute conversion unit (30007) can convert attributes based on the try-soup geometry encoding.

[0119] The attribute transformation unit (30007) can perform attribute transformation by calculating the average value of the attributes or attribute values ​​(e.g., the color or reflectance of each point) of neighboring points within a specific position / radius from the position (or position value) of the center point of each voxel. The attribute transformation unit (30007) can apply a weight according to the distance from the center point to each point when calculating the average value. Accordingly, each voxel has a position and a calculated attribute (or attribute value).

[0120] The attribute transformation unit (30007) can search for neighboring points within a specific position / radius from the position of the center point of each voxel based on the KD tree or the Moulton code. The KD tree is a binary search tree that supports a data structure that can manage points based on their positions to enable fast nearest neighbor search (NNS). The Moulton code represents the coordinate values ​​(e.g. (x, y, z)) indicating the 3D positions of all points as bit values ​​and is generated by mixing the bits. For example, if the coordinate values ​​indicating the position of a point are (5, 9, 1), the bit values ​​of the coordinate values ​​are (0101, 1001, 0001). If the bit values ​​are mixed in the order of z, y, and x according to the bit index, it is 010001000111. If this value is expressed in decimal, it becomes 1095. That is, the Moulton code value of the point with coordinate values ​​(5, 9, 1) is 1095. The attribute transformation unit (30007) can sort points based on the Moulton code value and perform nearest neighbor search (NNS) through a depth-first traversal process. After the attribute transformation operation, if nearest neighbor search (NNS) is also required in other transformation processes for attribute coding, a KD tree or Moulton code is utilized.

[0121] As shown in the drawing, the converted attributes are input to the RAHT conversion unit (30008) and / or the LOD generation unit (30009).

[0122] The RAHT transform unit (30008) according to the embodiments performs RAHT coding to predict attribute information based on reconstructed geometry information. For example, the RAHT transform unit (30008) can predict attribute information of a node at an upper level of an octree based on attribute information associated with a node at a lower level of the octree.

[0123] The LOD generation unit (30009) according to the embodiments generates a LOD (Level of Detail) to perform predictive transformation coding. The LOD according to the embodiments represents the level of detail of point cloud content. A smaller LOD value indicates lower detail of point cloud content, and a larger LOD value indicates higher detail of point cloud content. Points can be classified according to LOD.

[0124] The lifting transformation unit (30010) according to the embodiments performs lifting transformation coding that transforms attributes of a point cloud based on weights. As described above, lifting transformation coding may be applied selectively.

[0125] A coefficient quantization unit (30011) according to embodiments quantizes attribute-coded attributes based on coefficients.

[0126] An arithmetic encoder (30012) according to embodiments encodes quantized attributes based on arithmetic coding.

[0127] The elements of the point cloud encoder of FIG. 3 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 included in the point cloud providing device, although not shown in the drawing. The one or more processors may perform at least one or more of the operations and / or functions of the elements of the point cloud encoder of FIG. 3 described above. Furthermore, the 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 point cloud encoder of FIG. 3. The one or more memories according to embodiments may include high-speed random access memory, or may include non-volatile memory (e.g., one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices).

[0128] Figure 4 illustrates examples of octree and occupancy codes according to embodiments.

[0129] As described in FIGS. 1 to 3, the point cloud content provision system (point cloud video encoder (10002)) or point cloud encoder (e.g., octree analysis unit (30002)) performs octree geometry coding (or octree coding) based on an octree structure to efficiently manage the area and / or position of a voxel.

[0130] The top of Fig. 4 shows the octree structure. The three-dimensional space of the point cloud content according to the embodiments is expressed by the axes of the coordinate system (e.g., X-axis, Y-axis, Z-axis). The octree structure has two poles (0,0,0) and (2 d , 2 d , 2 d ) is generated by recursively subdividing the cubical axis-aligned bounding box defined by . 2d can be set to a value that constitutes the smallest bounding box that encloses all points of the point cloud content (or point cloud video). d represents the depth of the octree. The value of d is determined by the following equation. In the equation below, (x int n , y int n , z int n ) represents the positions (or position values) of quantized points.

[0131] d =Ceil(Log2(Max(x_n^int,y_n^int,z_n^int,n=1,…,N)+1))

[0132] As shown in the middle of the upper part of Fig. 4, the entire three-dimensional space can be divided into eight spaces according to the division. Each divided space is expressed as a cube with six faces. As shown in the upper right of Fig. 4, each of the eight spaces is again divided based on the axes of the coordinate system (e.g., X-axis, Y-axis, Z-axis). Therefore, each space is again divided into eight smaller spaces. The divided smaller spaces are also expressed as cubes with six faces. This division method is applied until the leaf nodes of the octree become voxels.

[0133] The bottom of Fig. 4 shows the occupancy code of the octree. The occupancy code of the octree is generated to indicate whether each of the eight partitioned spaces generated by partitioning one space contains at least one point. Therefore, one occupancy code is expressed by eight child nodes. Each child node represents the occupancy of the partitioned space, and each child node has a value of 1 bit. Therefore, the occupancy code is expressed as an 8-bit code. That is, if the space corresponding to the child node contains at least one point, the node has a value of 1. If the space corresponding to the child node does not contain a point (empty), the node has a value of 0. Since the occupancy code illustrated in Fig. 4 is 00100001, it indicates that the spaces corresponding to the third and eighth child nodes among the eight child nodes each contain at least one point. As shown in the drawing, the third child node and the eighth child node each have eight child nodes, and each child node is expressed by an 8-bit occupancy code. The drawing shows that the occupancy code of the third child node is 10000111, and the occupancy code of the eighth child node is 01001111. A point cloud encoder according to embodiments (e.g., an arithmetic encoder (30004)) can entropy encode the occupancy code. In addition, the point cloud encoder can intra / inter code the occupancy code to increase compression efficiency. A receiving device according to embodiments (e.g., a receiving device (10004) or a point cloud video decoder (10006)) reconstructs an octree based on the occupancy code.

[0134] A point cloud encoder according to embodiments (e.g., the point cloud encoder of FIG. 3, or the octree analysis unit (30002)) can perform voxelization and octree coding to store the positions of points. However, points within a 3D space are not always evenly distributed, and thus, there may be specific areas where there are not many points. Therefore, performing voxelization on the entire 3D space is inefficient. For example, if there are few points in a specific area, there is no need to perform voxelization up to that area.

[0135] Therefore, the point cloud encoder according to the embodiments can perform direct coding that directly codes the positions of points included in the specific region (or nodes excluding leaf nodes of the octree) without performing voxelization for the specific region described above. The coordinates of the direct coded points according to the embodiments are referred to as a direct coding mode (DCM). In addition, the point cloud encoder according to the embodiments can perform trisoup geometry encoding that reconstructs the positions of points within the specific region (or node) on a voxel basis based on a surface model. Trisoup geometry encoding is a geometry encoding that expresses the representation of an object as a series of triangle meshes. Therefore, the point cloud decoder can generate a point cloud from the mesh surface. Direct coding and trisoup geometry encoding according to the embodiments can be selectively performed. Additionally, direct coding and tri-subtractive geometry encoding according to embodiments may be performed in combination with octree geometry coding (or octree coding).

[0136] In order to perform direct coding, the option to use direct mode for applying direct coding must be activated, the node to which direct coding is to be applied must not be a leaf node, and there must be points below a threshold within a specific node. In addition, the total number of points subject to direct coding must not exceed a preset threshold. If the above conditions are satisfied, the point cloud encoder (or arithmetic encoder (30004)) according to the embodiments can entropy code the positions (or position values) of the points.

[0137] A point cloud encoder according to embodiments (e.g., surface approximation analysis unit (30003)) can determine a specific level of an octree (when the level is smaller than the depth d of the octree) and, starting from that level, perform tri-subject geometry encoding to reconstruct the positions of points within a node region on a voxel basis using a surface model (tri-subject mode). A point cloud encoder according to embodiments can specify a level to which tri-subject geometry encoding is to be applied. For example, when the specified level is equal to the depth of the octree, the point cloud encoder does not operate in tri-subject mode. That is, a point cloud encoder according to embodiments can operate in tri-subject mode only when the specified level is smaller than the depth value of the octree. A three-dimensional cubic area of ​​nodes at a specified level according to embodiments is called a block. One block may include one or more voxels. A block or a voxel may correspond to a brick. Within each block, geometry is represented by a surface. According to embodiments, a surface may intersect each edge of the block at most once.

[0138] Since one block has 12 edges, there are at least 12 intersections within one block. Each intersection is called a vertex. A vertex existing along an edge is detected if there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge. An occupied voxel according to embodiments means a voxel containing a point. The position of a vertex detected along an edge is the average position along the edge of all voxels adjacent to the edge among all blocks sharing the edge.

[0139] When a vertex is detected, the point cloud encoder according to the embodiments can entropy code the starting point (x, y, z) of the edge, the direction vector (Δx, Δy, Δz) of the edge, and the vertex position value (relative position value within the edge). When the tri-substructure geometry encoding is applied, the point cloud encoder according to the embodiments (e.g., the geometry reconstruction unit (30005)) can perform triangle reconstruction, up-sampling, and voxelization processes to generate restored geometry (reconstructed geometry).

[0140] The vertices located at the edge of a block determine the surface passing through the block. According to the embodiments, the surface is a non-planar polygon. The triangle reconstruction process reconstructs the surface represented by a triangle based on the starting point of the edge, the direction vector of the edge, and the position value of the vertex. The triangle reconstruction process is as follows. ① Calculate the centroid value of each vertex, ② Subtract the centroid value from each vertex value, and ③ Square the values, and then add up all the values ​​to obtain the value.

[0141]

[0142] Find the minimum of the added values, and perform the projection process according to the axis with the minimum value. For example, if the x element is minimum, each vertex is projected to the x-axis based on the center of the block, and then projected onto the (y, z) plane. If the value output when projected onto the (y, z) plane is (ai, bi), the θ value is found through atan2(bi, ai), and the vertices are sorted based on the θ value. The table below shows the combination of vertices to create a triangle depending on the number of vertices. The vertices are sorted in order from 1 to n. The table below shows that two triangles can be formed depending on the combination of vertices for four vertices. The first triangle can be formed by the 1st, 2nd, and 3rd vertices among the sorted vertices, and the second triangle can be formed by the 3rd, 4th, and 1st vertices among the sorted vertices.

[0143] Table 2-1. Triangles formed from vertices ordered 1,… ,n

[0144] n triangles

[0145] 3 (1,2,3)

[0146] 4 (1,2,3), (3,4,1)

[0147] 5 (1,2,3), (3,4,5), (5,1,3)

[0148] 6 (1,2,3), (3,4,5), (5,6,1), (1,3,5)

[0149] 7 (1,2,3), (3,4,5), (5,6,7), (7,1,3), (3,5,7)

[0150] 8 (1,2,3), (3,4,5), (5,6,7), (7,8,1), (1,3,5), (5,7,1)

[0151] 9 (1,2,3), (3,4,5), (5,6,7), (7,8,9), (9,1,3), (3,5,7), (7,9,3)

[0152] 10 (1,2,3), (3,4,5), (5,6,7), (7,8,9), (9,10,1), (1,3,5), (5,7,9), (9,1,5)

[0153] 11 (1,2,3), (3,4,5), (5,6,7), (7,8,9), (9,10,11), (11,1,3), (3,5,7), (7,9,11), (11,3,7)

[0154] 12 (1,2,3), (3,4,5), (5,6,7), (7,8,9), (9,10,11), (11,12,1), (1,3,5), (5,7,9), (9,11,1), (1,5,9)

[0155] The upsampling process is performed to voxelize the triangle by adding points in the middle along the edges. Additional points are generated based on the upsampling factor and the width of the block. The additional points are called refined vertices. A point cloud encoder according to embodiments can voxelize the refined vertices. The point cloud encoder can also perform attribute encoding based on the voxelized positions (or position values).

[0156] Figure 5 shows an example of a point configuration by LOD according to embodiments.

[0157] As described in FIGS. 1 to 4, the encoded geometry is reconstructed (decompressed) before attribute encoding is performed. When direct coding is applied, the geometry reconstruction operation may include changing the arrangement of direct-coded points (e.g., placing the direct-coded points at the front of the point cloud data). When trysoup geometry encoding is applied, the geometry reconstruction process includes triangle reconstruction, upsampling, and voxelization. Since attributes depend on the geometry, attribute encoding is performed based on the reconstructed geometry.

[0158] A point cloud encoder (e.g., LOD generation unit (30009)) can reorganize points by LOD. The drawing shows point cloud content corresponding to LOD. The left side of the drawing shows the original point cloud content. The second figure from the left in the drawing shows the distribution of points of the lowest LOD, and the rightmost figure in the drawing shows the distribution of points of the highest LOD. That is, points of the lowest LOD are sparsely distributed, and points of the highest LOD are densely distributed. That is, as LOD increases in the direction of the arrow indicated at the bottom of the drawing, the interval (or distance) between points becomes shorter.

[0159] Figure 6 shows an example of a point configuration by LOD according to embodiments.

[0160] As described in FIGS. 1 to 5, a point cloud content providing system, or a point cloud encoder (e.g., a point cloud video encoder (10002), the point cloud encoder of FIG. 3, or a LOD generation unit (30009)) can generate a LOD. The LOD is generated by reorganizing points into a set of refinement levels according to a set LOD distance value (or a set of Euclidean distances). The LOD generation process is performed not only in the point cloud encoder but also in the point cloud decoder.

[0161] The upper part of Fig. 6 shows examples of points (P0 to P9) of point cloud content distributed in 3D space. The original order in Fig. 6 represents the order of points P0 to P9 before LOD generation. The LOD-based order in Fig. 6 represents the order of points according to LOD generation. The points are rearranged by LOD. Additionally, a higher LOD includes points belonging to a lower LOD. As shown in Fig. 6, LOD0 includes P0, P5, P4, and P2. LOD1 includes points of LOD0 and P1, P6, and P3. LOD2 includes points of LOD0, points of LOD1, and P9, P8, and P7.

[0162] As described in FIG. 3, the point cloud encoder according to the embodiments can selectively or in combination perform predictive transform coding, lifting transform coding, and RAHT transform coding.

[0163] A point cloud encoder according to embodiments can perform predictive transformation coding to generate a predictor for points and set a predicted attribute (or predicted attribute value) for each point. That is, N predictors can be generated for N points. The predictor according to embodiments can calculate a weight (= 1 / distance) value based on the LOD value of each point, indexing information for neighboring points existing within a distance set for each LOD, and distance values ​​to the neighboring points.

[0164] According to the embodiments, the predicted attribute (or attribute value) is set as the average value of the product of the attributes (or attribute values, for example, color, reflectance, etc.) of neighboring points set in the predictor of each point and the weight (or weight value) calculated based on the distance to each neighboring point. The point cloud encoder according to the embodiments (for example, the coefficient quantization unit (30011)) can quantize and inverse quantize the residual values ​​(which may be referred to as residual attributes, residual attribute values, attribute prediction residual values, etc.) obtained by subtracting the predicted attribute (attribute value) from the attribute (attribute value) of each point. The quantization process is as shown in the following table.

[0165] graph. Attribute prediction residuals quantization pseudo code

[0166] int PCCQuantization(int value, int quantStep) {

[0167] if( value >=0) {

[0168] return floor(value / quantStep + 1.0 / 3.0);

[0169] } else {

[0170] return -floor(-value / quantStep + 1.0 / 3.0);

[0171] }

[0172] }

[0173] graph. Attribute prediction residuals inverse quantization pseudo code

[0174] int PCCInverseQuantization(int value, int quantStep) {

[0175] if( quantStep ==0) {

[0176] return value;

[0177] } else {

[0178] return value * quantStep;

[0179] }

[0180] }

[0181] A point cloud encoder according to embodiments (e.g., an arithmetic encoder (30012)) can entropy code the quantized and dequantized residuals as described above when there are neighboring points to the predictor of each point. A point cloud encoder according to embodiments (e.g., an arithmetic encoder (30012)) can entropy code the attributes of the point without performing the above-described process when there are no neighboring points to the predictor of each point.

[0182] A point cloud encoder according to embodiments (e.g., lifting transformation unit (30010)) can perform lifting transformation coding by generating a predictor for each point, setting the LOD calculated in the predictor, registering neighboring points, and setting weights according to the distance to the neighboring points. Lifting transformation coding according to embodiments is similar to the above-described predictive transformation coding, but differs in that weights are cumulatively applied to attribute values. The process of cumulatively applying weights to attribute values ​​according to embodiments is as follows.

[0183] 1) Create an array QW (QuantizationWieght) that stores the weight values ​​of each point. The initial value of all elements in QW is 1.0. Add the value obtained by multiplying the weight of the current point's predictor by the QW value of the predictor index of the neighboring node registered in the predictor.

[0184] 2) Lift prediction process: To calculate the predicted attribute value, the weighted value of the point's attribute value is multiplied and subtracted from the existing attribute value.

[0185] 3) Create temporary arrays called updateweight and update and initialize them to 0.

[0186] 4) For each predictor, the calculated weights are multiplied by the weights stored in the QW corresponding to the predictor index, and the resulting weights are cumulatively added to the update weight array as the index of the neighboring node. The update array accumulates the values ​​obtained by multiplying the calculated weights by the attribute values ​​of the indexes of the neighboring nodes.

[0187] 5) Lift update process: For each predictor, the attribute values ​​in the update array are divided by the weight values ​​in the update weight array of the predictor index, and the existing attribute values ​​are added to the divided value.

[0188] 6) For all predictors, the predicted attribute values ​​are calculated by additionally multiplying the updated attribute values ​​through the lift update process by the weights (stored in QW) updated through the lift prediction process. The point cloud encoder according to the embodiments (e.g., coefficient quantization unit (30011)) quantizes the predicted attribute values. In addition, the point cloud encoder (e.g., arithmetic encoder (30012)) entropy-codes the quantized attribute values.

[0189] A point cloud encoder according to embodiments (e.g., RAHT transform unit (30008)) can perform RAHT transform coding that predicts attributes of upper-level nodes using attributes associated with nodes at lower levels of an octree. RAHT transform coding is an example of attribute intra coding through octree backward scan. A point cloud encoder according to embodiments scans from a voxel to the entire area, and repeats the merging process up to a root node while merging voxels into larger blocks at each step. The merging process according to embodiments is performed only for occupied nodes. The merging process is not performed for empty nodes, and the merging process is performed for the node immediately above the empty node.

[0190] The following equation represents the RAHT transformation matrix. g l x, y, z represents the average attribute value of voxels at level l. g l x, y, z can be calculated from gl+1 2x, y, z and gl+1 2x+1, y, z. The weights of gl 2x, y, z and gl 2x+1, y, z are w1=wl 2x, y, z and w2=wl 2x+1, y, z.

[0191]

[0192] gl-1 x, y, z are low-pass values, which are used in the merging process at the next higher level. hl-1 x, y, z are high-pass coefficients, and the high-pass coefficients at each step are quantized and entropy coded (e.g., encoding of an arithmetic encoder (400012)). The weights are computed as wl-1 x, y, z=wl 2x, y, z+wl 2x+1, y, z. The root node is the last g 1 0, 0, 0 and g 1 0, 0, 1 It is generated as follows:

[0193]

[0194] The gDC values ​​are also quantized and entropy coded, like the high-pass coefficients.

[0195] Fig. 7 illustrates an example of a point cloud decoder according to embodiments.

[0196] The point cloud decoder illustrated in FIG. 7 is an example of a point cloud decoder and can perform a decoding operation, which is the reverse process of the encoding operation of the point cloud encoder described in FIGS. 1 to 6.

[0197] As described in Figure 1, the point cloud decoder can perform geometry decoding and attribute decoding. Geometry decoding is performed before attribute decoding.

[0198] A point cloud decoder according to embodiments includes an arithmetic decoder (7000), an octree synthesizer (7001), a surface approximation synthesizer (7002), a geometry reconstructor (7003), an inverse transform coordinates (7004), an arithmetic decoder (7005), an inverse quantize (7006), a RAHT transform (7007), a LOD generator (7008), an inverse lifting (7009), and / or an inverse transform colors (7010).

[0199] The arithmetic decoder (7000), the octree synthesis unit (7001), the surface oproximation synthesis unit (7002), the geometry reconstruction unit (7003), and the coordinate system inversion unit (7004) can perform geometry decoding. Geometry decoding according to embodiments can include direct coding and trisoup geometry decoding. Direct coding and trisoup geometry decoding are applied selectively. In addition, geometry decoding is not limited to the above examples, and is performed by the reverse process of the geometry encoding described in FIGS. 1 to 6.

[0200] An arithmetic decoder (7000) according to embodiments decodes a received geometry bitstream based on arithmetic coding. The operation of the arithmetic decoder (7000) corresponds to the reverse process of the arithmetic encoder (30004).

[0201] The octree synthesis unit (7001) according to the embodiments can generate an octree by obtaining an occupancy code from a decoded geometry bitstream (or information about the geometry obtained as a result of decoding). A specific description of the occupancy code is as described in FIGS. 1 to 6.

[0202] The surface off-axis synthesis unit (7002) according to the embodiments can synthesize a surface based on the decoded geometry and / or the generated octree when the tri-sub geometry encoding is applied.

[0203] The geometry reconstruction unit (7003) according to the embodiments can regenerate geometry based on the surface and / or decoded geometry. As described in FIGS. 1 to 6, direct coding and try-soup geometry encoding are selectively applied. Therefore, the geometry reconstruction unit (7003) directly retrieves and adds position information of points to which direct coding is applied. In addition, when try-soup geometry encoding is applied, the geometry reconstruction unit (7003) can restore geometry by performing a reconstruction operation of the geometry reconstruction unit (30005), such as triangle reconstruction, up-sampling, and voxelization operations. The specific details are the same as described in FIG. 4 and are therefore omitted. The restored geometry may include a point cloud picture or frame that does not include attributes.

[0204] The coordinate system inverse transformation unit (7004) according to the embodiments can obtain the positions of points by transforming the coordinate system based on the restored geometry.

[0205] The arithmetic decoder (7005), the inverse quantization unit (7006), the RAHT transform unit (7007), the LOD generation unit (7008), the inverse lifting unit (7009), and / or the color inverse transform unit (7010) can perform the attribute decoding described in FIG. 10. The attribute decoding according to embodiments can include RAHT (Region Adaptive Hierarchial Transform) decoding, Interpolaration-based hierarchical nearest-neighbor prediction-Prediction Transform) decoding, and lifting transform (interpolation-based hierarchical nearest-neighbor prediction with an update / lifting step (Lifting Transform)) decoding. The three decodings described above can be used selectively, or a combination of one or more decodings can be used. Additionally, attribute decoding according to embodiments is not limited to the examples described above.

[0206] An arithmetic decoder (7005) according to embodiments decodes an attribute bitstream using arithmetic coding.

[0207] The inverse quantization unit (7006) according to the embodiments inverse quantizes information about the decoded attribute bitstream or the attributes obtained as a result of the decoding and outputs the inverse quantized attributes (or attribute values). The inverse quantization may be selectively applied based on the attribute encoding of the point cloud encoder.

[0208] According to embodiments, the RAHT transform unit (7007), the LOD generator (7008), and / or the inverse lifting unit (7009) may process the reconstructed geometry and the inverse quantized attributes. As described above, the RAHT transform unit (7007), the LOD generator (7008), and / or the inverse lifting unit (7009) may selectively perform a corresponding decoding operation according to the encoding of the point cloud encoder.

[0209] The color inverse transform unit (7010) according to the embodiments performs inverse transform coding to inversely transform the color values ​​(or textures) included in the decoded attributes. The operation of the color inverse transform unit (7010) may be selectively performed based on the operation of the color transform unit (30006) of the point cloud encoder.

[0210] The elements of the point cloud decoder of FIG. 7 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 included in a point cloud providing device, although not shown in the drawing. The one or more processors may perform at least one or more of the operations and / or functions of the elements of the point cloud decoder of FIG. 7 described above. Furthermore, the 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 point cloud decoder of FIG. 7.

[0211] Figure 8 is an example of a transmission device according to embodiments.

[0212] The transmission device illustrated in FIG. 8 is an example of the transmission device (10000) of FIG. 1 (or the point cloud encoder of FIG. 3). The transmission device illustrated in FIG. 8 can perform at least one or more of the same or similar operations and encoding methods as the operations and encoding methods of the point cloud encoder described in FIGS. 1 to 6. A transmission device according to embodiments may include a data input unit (8000), a quantization processing unit (8001), a voxelization processing unit (8002), an octree occupancy code generation unit (8003), a surface model processing unit (8004), an intra / inter coding processing unit (8005), an arithmetic coder (8006), a metadata processing unit (8007), a color conversion processing unit (8008), an attribute conversion processing unit (or a property conversion processing unit) (8009), a prediction / lifting / RAHT conversion processing unit (8010), an arithmetic coder (8011), and / or a transmission processing unit (8012).

[0213] The data input unit (8000) according to the embodiments receives or acquires point cloud data. The data input unit (8000) may perform operations and / or acquisition methods identical or similar to those of the point cloud video acquisition unit (10001) (or the acquisition process (20000) described in FIG. 2).

[0214] The data input unit (8000), quantization processing unit (8001), voxelization processing unit (8002), octree occupancy code generation unit (8003), surface model processing unit (8004), intra / inter coding processing unit (8005), and arithmetic coder (8006) perform geometry encoding. Since the geometry encoding according to the embodiments is the same or similar to the geometry encoding described in FIGS. 1 to 6, a detailed description thereof will be omitted.

[0215] The quantization processing unit (8001) according to the embodiments quantizes geometry (e.g., position values ​​of points or position values). The operation and / or quantization of the quantization processing unit (8001) is identical to or similar to the operation and / or quantization of the quantization unit (30001) described in FIG. 3. The specific description is the same as that described in FIGS. 1 to 6.

[0216] The voxelization processing unit (8002) according to the embodiments voxels the position values ​​of quantized points. The voxelization processing unit (80002) may perform operations and / or processes identical or similar to the operations and / or voxelization processes of the quantization unit (30001) described in FIG. 3. Specific descriptions are identical to those described in FIGS. 1 to 6.

[0217] The octree occupancy code generation unit (8003) according to the embodiments performs octree coding on the positions of voxelized points based on the octree structure. The octree occupancy code generation unit (8003) can generate an occupancy code. The octree occupancy code generation unit (8003) can perform operations and / or methods identical or similar to those of the point cloud encoder (or octree analysis unit (30002)) described in FIGS. 3 and 4. The specific description is the same as that described in FIGS. 1 to 6.

[0218] The surface model processing unit (8004) according to the embodiments can perform tri-subject geometry encoding to reconstruct the positions of points within a specific area (or node) on a voxel basis based on the surface model. The surface model processing unit (8004) can perform operations and / or methods identical or similar to those of the point cloud encoder (e.g., surface approximation analysis unit (30003)) described in FIG. 3. The specific description is the same as that described with reference to FIGS. 1 to 6.

[0219] The intra / inter coding processing unit (8005) according to embodiments can intra / inter code point cloud data. The intra / inter coding processing unit (8005) can perform coding identical to or similar to the intra / inter coding described in FIG. 7. The specific description is identical to that described in FIG. 7. According to embodiments, the intra / inter coding processing unit (8005) can be included in an arithmetic coder (8006).

[0220] An arithmetic coder (8006) according to embodiments entropy encodes an octree and / or an approximated octree of point cloud data. For example, the encoding method includes an arithmetic encoding method. The arithmetic coder (8006) performs operations and / or methods identical or similar to those of the arithmetic encoder (30004).

[0221] The metadata processing unit (8007) according to the embodiments processes metadata regarding point cloud data, such as setting values, and provides the metadata to a necessary processing step, such as geometry encoding and / or attribute encoding. In addition, the metadata processing unit (8007) according to the embodiments may generate and / or process signaling information related to geometry encoding and / or attribute encoding. The signaling information according to the embodiments may be encoded and processed separately from geometry encoding and / or attribute encoding. In addition, the signaling information according to the embodiments may be interleaved.

[0222] The color conversion processing unit (8008), the attribute conversion processing unit (8009), the prediction / lifting / RAHT conversion processing unit (8010), and the arithmetic coder (8011) perform attribute encoding. Since the attribute encoding according to the embodiments is the same as or similar to the attribute encoding described in FIGS. 1 to 6, a detailed description thereof will be omitted.

[0223] The color conversion processing unit (8008) according to the embodiments performs color conversion coding to convert the color values ​​included in the attributes. The color conversion processing unit (8008) can perform color conversion coding based on the reconstructed geometry. The description of the reconstructed geometry is the same as that described with reference to FIGS. 1 to 6. In addition, the color conversion processing unit (8008) performs the same or similar operation and / or method as that of the color conversion unit (30006) described with reference to FIG. 3. A detailed description thereof will be omitted.

[0224] The attribute transformation processing unit (8009) according to embodiments performs attribute transformation to transform attributes based on positions for which geometry encoding has not been performed and / or reconstructed geometry. The attribute transformation processing unit (8009) performs operations and / or methods that are the same as or similar to those of the attribute transformation unit (30007) described in FIG. 3. A detailed description thereof will be omitted. The prediction / lifting / RAHT transformation processing unit (8010) according to embodiments can code transformed attributes by using any one or a combination of RAHT coding, prediction transformation coding, and lifting transformation coding. The prediction / lifting / RAHT transformation processing unit (8010) performs at least one or more of operations that are the same as or similar to those of the RAHT transformation unit (30008), LOD generation unit (30009), and lifting transformation unit (30010) described in FIG. 3. In addition, the description of the prediction transformation coding, lifting transformation coding, and RAHT transformation coding is the same as that described in FIGS. 1 to 6, so a detailed description is omitted.

[0225] An arithmetic coder (8011) according to embodiments can encode coded attributes based on arithmetic coding. The arithmetic coder (8011) performs operations and / or methods identical or similar to those of the arithmetic encoder (300012).

[0226] The transmission processing unit (8012) according to embodiments may transmit each bitstream including encoded geometry and / or encoded attribute, metadata information, or may transmit the encoded geometry and / or encoded attribute, and metadata information as one bitstream. When the encoded geometry and / or encoded attribute, and metadata information according to embodiments are configured as one bitstream, the bitstream may include one or more sub-bitstreams. The bitstream according to embodiments may include signaling information including a Sequence Parameter Set (SPS) for sequence-level signaling, a Geometry Parameter Set (GPS) for signaling geometry information coding, an Attribute Parameter Set (APS) for signaling attribute information coding, and a Tile Parameter Set (TPS) for tile-level signaling, and slice data. The slice data may include information about one or more slices. One slice according to embodiments may include one geometry bitstream (Geom0). 0 ) and one or more attribute bitstreams (Attr0 0 , Attr1 0 ) may be included.

[0227] A slice is a series of syntax elements that represent all or part of a coded point cloud frame.

[0228] A TPS according to embodiments may include information about each tile (e.g., coordinate value information of a bounding box and height / size information, etc.) for one or more tiles. A geometry bitstream may include a header and a payload. The header of a geometry bitstream according to embodiments may include identification information of a parameter set included in GPS (geom_ parameter_set_id), a tile identifier (geom_tile_id), a slice identifier (geom_slice_id), and information about data included in the payload. As described above, a metadata processing unit (8007) according to embodiments may generate and / or process signaling information and transmit it to a transmission processing unit (8012). According to embodiments, elements that perform geometry encoding and elements that perform attribute encoding may share data / information with each other as indicated by a dotted line. The transmission processing unit (8012) according to the embodiments may perform operations and / or transmission methods identical or similar to those of the transmitter (10003). A detailed description thereof is omitted as it is the same as that described in FIGS. 1 and 2.

[0229] Fig. 9 is an example of a receiving device according to embodiments.

[0230] The receiving device illustrated in FIG. 9 is an example of the receiving device (10004) of FIG. 1 (or the point cloud decoder of FIGS. 10 and 11). The receiving device illustrated in FIG. 9 can perform at least one or more of the same or similar operations and decoding methods as the operations and decoding methods of the point cloud decoder described in FIGS. 1 to 11.

[0231] A receiving device according to embodiments may include a receiving unit (9000), a receiving processing unit (9001), an arithmetic decoder (9002), an occupancy code-based octree reconstruction processing unit (9003), a surface model processing unit (triangle reconstruction, up-sampling, voxelization) (9004), an inverse quantization processing unit (9005), a metadata parser (9006), an arithmetic decoder (9007), an inverse quantization processing unit (9008), a prediction / lifting / RAHT inverse transform processing unit (9009), a color inverse transform processing unit (9010), and / or a renderer (9011). Each component of the decoding according to embodiments may perform the reverse process of the component of the encoding according to embodiments.

[0232] The receiving unit (9000) according to the embodiments receives point cloud data. The receiving unit (9000) may perform operations and / or receiving methods identical or similar to those of the receiver (10005) of FIG. 1. A detailed description thereof will be omitted.

[0233] The receiving processing unit (9001) according to the embodiments can obtain a geometry bitstream and / or an attribute bitstream from the received data. The receiving processing unit (9001) can be included in the receiving unit (9000).

[0234] The arithmetic decoder (9002), the occupancy code-based octree reconstruction processing unit (9003), the surface model processing unit (9004), and the inverse quantization processing unit (9005) can perform geometry decoding. Since the geometry decoding according to the embodiments is the same or similar to the geometry decoding described in FIGS. 1 to 10, a detailed description thereof will be omitted.

[0235] An arithmetic decoder (9002) according to embodiments can decode a geometry bitstream based on arithmetic coding. The arithmetic decoder (9002) performs operations and / or coding identical to or similar to those of the arithmetic decoder (7000).

[0236] The occupancy code-based octree reconstruction processing unit (9003) according to embodiments can reconstruct an octree by obtaining an occupancy code from a decoded geometry bitstream (or information about the geometry obtained as a result of decoding). The occupancy code-based octree reconstruction processing unit (9003) performs the same or similar operations and / or methods as those of the octree synthesis unit (7001) and / or the octree generation method. The surface model processing unit (9004) according to embodiments can perform tri-sub geometry decoding and related geometry reconstructing (e.g., triangle reconstruction, up-sampling, voxelization) based on the surface model method when tri-sub geometry encoding is applied. The surface model processing unit (9004) performs the same or similar operations as those of the surface off-ratio synthesis unit (7002) and / or the geometry reconstructing unit (7003).

[0237] The inverse quantization processing unit (9005) according to the embodiments can inverse quantize the decoded geometry.

[0238] The metadata parser (9006) according to the embodiments can parse metadata, such as setting values, contained in the received point cloud data. The metadata parser (9006) can pass the metadata to geometry decoding and / or attribute decoding. A detailed description of the metadata is omitted as it is the same as described in FIG. 8.

[0239] The arithmetic decoder (9007), the inverse quantization processing unit (9008), the prediction / lifting / RAHT inverse transform processing unit (9009), and the color inverse transform processing unit (9010) perform attribute decoding. Since attribute decoding is the same or similar to the attribute decoding described in FIGS. 1 to 10, a detailed description thereof will be omitted.

[0240] An arithmetic decoder (9007) according to embodiments can decode an attribute bitstream using arithmetic coding. The arithmetic decoder (9007) can decode the attribute bitstream based on the reconstructed geometry. The arithmetic decoder (9007) performs operations and / or coding identical or similar to those of the arithmetic decoder (7005).

[0241] The inverse quantization processing unit (9008) according to the embodiments can inverse quantize the decoded attribute bitstream. The inverse quantization processing unit (9008) performs operations and / or methods identical or similar to the operations and / or inverse quantization methods of the inverse quantization unit (7006).

[0242] The prediction / lifting / RAHT inverse transform processing unit (9009) according to embodiments can process reconstructed geometry and inverse quantized attributes. The prediction / lifting / RAHT inverse transform processing unit (9009) performs at least one or more of operations and / or decodings that are identical or similar to the operations and / or decodings of the RAHT transform unit (7007), the LOD generation unit (7008), and / or the inverse lifting unit (7009). The color inverse transform processing unit (9010) according to embodiments performs inverse transform coding for inverse transforming the color value (or texture) included in the decoded attributes. The color inverse transform processing unit (9010) performs operations and / or inverse transform coding that are identical or similar to the operations and / or inverse transform coding of the color inverse transform unit (7010). A renderer (9011) according to embodiments can render point cloud data.

[0243] Fig. 10 shows an example of a structure that can be linked with a point cloud data transmission / reception method / device according to embodiments.

[0244] The structure of FIG. 10 represents a configuration in which at least one of a server (1060), a robot (1010), an autonomous vehicle (1020), an XR device (1030), a smartphone (1040), a home appliance (1050), and / or an HMD (1070) is connected to a cloud network (1010). The robot (1010), the autonomous vehicle (1020), the XR device (1030), the smartphone (1040), or the home appliance (1050) are referred to as devices. In addition, the XR device (1030) may correspond to or be linked with a point cloud data (PCC) device according to embodiments.

[0245] A cloud network (1000) may refer to a network that constitutes part of a cloud computing infrastructure or exists within the cloud computing infrastructure. Here, the cloud network (1000) may be configured using a 3G network, a 4G or LTE (Long Term Evolution) network, or a 5G network.

[0246] The server (1060) is connected to at least one of a robot (1010), an autonomous vehicle (1020), an XR device (1030), a smartphone (1040), a home appliance (1050), and / or an HMD (1070) through a cloud network (1000), and can assist in at least part of the processing of the connected devices (1010 to 1070).

[0247] The HMD (Head-Mount Display) (1070) represents one of the types in which the XR device and / or the PCC device according to the embodiments can be implemented. The HMD type device according to the embodiments includes a communication unit, a control unit, a memory unit, an I / O unit, a sensor unit, and a power supply unit.

[0248] Below, various embodiments of devices (1010 to 1050) to which the above-described technology is applied are described. Here, the devices (1010 to 1050) illustrated in FIG. 10 can be linked / combined with point cloud data transmission / reception devices according to the above-described embodiments.

[0249] <PCC+XR>

[0250] The XR / PCC device (1030) may be implemented as a HMD (Head-Mount Display), a HUD (Head-Up Display) equipped in a vehicle, a television, a mobile phone, a smart phone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a fixed robot, a mobile robot, etc., by applying PCC and / or XR (AR+VR) technology.

[0251] The XR / PCC device (1030) can obtain information about surrounding space or real objects by analyzing 3D point cloud data or image data acquired through various sensors or from external devices to generate location data and attribute data for 3D points, and can render and output an XR object to be output. For example, the XR / PCC device (1030) can output an XR object including additional information about a recognized object in correspondence with the recognized object.

[0252] <PCC+XR+모바일폰>

[0253] The XR / PCC device (1030) can be implemented as a mobile phone (1040) or the like by applying PCC technology.

[0254] The mobile phone (1040) can decode and display point cloud content based on PCC technology.

[0255] <PCC+자율주행+XR>

[0256] Autonomous vehicles (1020) can be implemented as mobile robots, vehicles, unmanned aerial vehicles, etc. by applying PCC technology and XR technology.

[0257] An autonomous vehicle (1020) to which XR / PCC technology is applied may refer to an autonomous vehicle equipped with a means for providing XR images, or an autonomous vehicle that is the subject of control / interaction within an XR image. In particular, an autonomous vehicle (1020) that is the subject of control / interaction within an XR image is distinct from an XR device (1030) and can be linked with each other.

[0258] An autonomous vehicle (1020) equipped with a means for providing XR / PCC images can obtain sensor information from sensors including cameras and output XR / PCC images generated based on the obtained sensor information. For example, the autonomous vehicle (1020) can be equipped with a HUD to output XR / PCC images, thereby providing passengers with XR / PCC objects corresponding to real objects or objects on a screen.

[0259] At this time, when the XR / PCC object is output to the HUD, at least a part of the XR / PCC object may be output so as to overlap with an actual object toward which the passenger's gaze is directed. On the other hand, when the XR / PCC object is output to a display provided inside the autonomous vehicle, at least a part of the XR / PCC object may be output so as to overlap with an object on the screen. For example, the autonomous vehicle (1220) may output XR / PCC objects corresponding to objects such as a lane, another vehicle, a traffic light, a traffic sign, a two-wheeled vehicle, a pedestrian, a building, etc.

[0260] VR (Virtual Reality) technology, AR (Augmented Reality) technology, MR (Mixed Reality) technology and / or PCC (Point Cloud Compression) technology according to the embodiments can be applied to various devices.

[0261] In other words, VR technology is a display technology that provides only CG images of objects or backgrounds in the real world. On the other hand, AR technology refers to a technology that shows a virtually created CG image on top of an image of an actual object. Furthermore, MR technology is similar to the aforementioned AR technology in that it mixes and combines virtual objects in the real world. However, in AR technology, the distinction between real objects and virtual objects created with CG images is clear, and virtual objects are used in a form that complements real objects, whereas in MR technology, virtual objects are considered to have the same characteristics as real objects. A more specific example is the hologram service, which is an application of the aforementioned MR technology.

[0262] However, recently, rather than clearly distinguishing between VR, AR, and MR technologies, they are often referred to as XR (extended reality) technologies. Therefore, embodiments of the present invention are applicable to all VR, AR, MR, and XR technologies. These technologies can be applied to encoding / decoding based on PCC, V-PCC, and G-PCC technologies.

[0263] The PCC method / device according to the embodiments can be applied to a vehicle providing an autonomous driving service.

[0264] Vehicles providing autonomous driving services are connected to PCC devices to enable wired / wireless communication.

[0265] A point cloud data (PCC) transmission and reception device according to embodiments, when connected to a vehicle to enable wired / wireless communication, can receive / process content data related to AR / VR / PCC services that can be provided together with autonomous driving services and transmit the same to the vehicle. In addition, when the point cloud data transmission and reception device is mounted on a vehicle, the point cloud transmission and reception device can receive / process content data related to AR / VR / PCC services and provide the same to a user according to a user input signal input through a user interface device. A vehicle or a user interface device according to embodiments can receive a user input signal. The user input signal according to embodiments can include a signal instructing an autonomous driving service.

[0266] The point cloud data transmission method / device according to the embodiments is interpreted as a term referring to the transmission device (10000) of FIG. 1, the point cloud video encoder (10002), the transmitter (10003), the acquisition-encoding-transmission (20000-20001-20002) of FIG. 2, the encoder of FIG. 11, the layer group-based encoding of FIGS. 12 to 22, the context buffer memory control of FIGS. 23 to 34, the bitstream / parameter generation of FIGS. 35 to 39a, and 39b, the encoder of FIG. 40, the encoding of FIG. 43, the context buffer memory control of FIGS. 45 to 47 and FIGS. 59 to 60, the parameter generation of FIGS. 48 to 51, FIGS. 54 to 58, and FIGS. 61 to 63, the encoder of FIGS. 64 to 67, the encoding method of FIG. 68, etc.

[0267] The point cloud data receiving method / device according to the embodiments refers to the receiving device (10004), the receiver (10005), the point cloud video decoder (10006) of FIG. 1, the transmission-decoding-rendering (20002-20003-20004) of FIG. 2, the decoder of FIG. 7, the receiving device of FIG. 9, the device of FIG. 10, the decoder of FIG. 11, the layer group-based decoding of FIGS. 12 to 22, the context buffer memory control of FIGS. 23 to 34, the bitstream / parameter parsing of FIGS. 35 to 39a, and 39b, the decoder of FIG. 41, the decoding of FIGS. 42 and 44, the context buffer control of FIGS. 45 to 47, the parameter generation decoder of FIGS. 48 to 51, 54 to 58, and 61 to 63, the context buffer control of FIGS. 59 to 60, the decoder of FIGS. 64 to 67, the decoding method of FIG. 69, etc. It is interpreted as a term.

[0268] Additionally, the point cloud data transmission / reception method / device according to the embodiments may be abbreviated as the method / device according to the embodiments.

[0269] According to embodiments, geometry data, geometry information, location information, etc., which constitute point cloud data, are interpreted as having the same meaning. Attribute data, attribute information, property information, etc., which constitute point cloud data, are interpreted as having the same meaning.

[0270] The method and device according to the embodiments may include and perform an improved context memory management method considering partial coding (improved context memory for multiple coding units with context continuation).

[0271] The embodiments include a method for efficiently supporting selective decoding of a portion of data when transmitting and receiving point cloud data due to receiver performance or transmission speed. The embodiments propose a method for selecting necessary information or removing unnecessary information from a bitstream unit by dividing geometry and attribute data, which are previously transmitted as data units, into semantic units such as geometry octree and LoD (Level of Detail).

[0272] Embodiments include operations for constructing a data structure composed of a point cloud. Specifically, a packing and signaling method for effectively transmitting PCC data constructed based on layers is described, and an operation for applying the same to a scalable PCC-based service is included. In particular, a method for constructing and transmitting / receiving slice segments to be more suitable for a scalable PCC service when a direct compression mode is used for position compression is included. In particular, a compression structure for efficient storage and transmission of large-capacity point cloud data with a wide distribution and a high point density is included.

[0273] Referring to FIGS. 3 and 7, referring to point cloud data transmission and reception devices (or encoders / decoders for short) according to embodiments, point cloud data is composed of the location (geometry: e.g., XYZ coordinates) and attributes (attributes: e.g., color, reflectance, intensity, grayscale, opacity, etc.) of each data. In point cloud compression (Point Cloud Compression: PCC), octree-based compression is performed to efficiently compress distribution characteristics that are unevenly distributed in a three-dimensional space, and attribute information is compressed based on this. The PCC transmission and reception devices illustrated in FIGS. 3 and 7 can process operation(s) according to embodiments through each component device.

[0274] Figure 11 illustrates the encoding, transmission, and decoding processes of point cloud data according to embodiments.

[0275] A point cloud encoder (15000) is a transmission device according to embodiments that performs a transmission method according to embodiments, and can scalably encode and transmit point cloud data.

[0276] A point cloud decoder (15010) is a receiving device according to embodiments that performs a receiving method according to embodiments and can scalably decode point cloud data.

[0277] The source data received by the encoder (15000) may include geometry data and / or attribute data.

[0278] The encoder (15000) does not scalably encode point cloud data to directly generate a partial PCC bitstream, but receives full geometry data and full attribute data, stores the data in storage connected to the encoder, and then transcodes the data for partial encoding to generate and transmit a partial PCC bitstream. The decoder (15010) receives and decodes the partial PCC bitstream to restore the partial geometry and / or partial attributes.

[0279] An encoder (15000) can receive full geometry and full attributes, store the data in storage connected to the encoder, and transcode the point cloud data with low QP (quantization parameter) to generate and transmit a full PCC bitstream. A decoder (15010) can receive and decode the full PCC bitstream to restore the full geometry and / or full attributes. The decoder (15010) can select partial geometry and / or partial attributes from the full PCC bitstream through data selection.

[0280] The method / device according to the embodiments divides the location information and feature information such as color / brightness / reflectivity of data points, which are point cloud data, into geometry and attribute information, and compresses and transmits them respectively. At this time, the PCC data can be configured according to an octree structure with layers or LoD (Level of Detail) depending on the level of detail. Based on this, scalable point cloud data coding and representation are possible. At this time, it is possible to decode or represent only a part of the point cloud data depending on the performance or transmission speed of the receiver.

[0281] The method / device according to the embodiments can remove unnecessary data in advance during this process. That is, when only a part of a scalable PCC bitstream needs to be transmitted (for example, when only some layers are decoded during scalable decoding), since only the necessary part cannot be selected and transmitted, 1) the necessary part must be re-encoded after decoding (15020) or 2) the entirety must be transmitted and then selectively applied at the receiving end (15030). However, in case 1), a delay may occur due to the time required for decoding and re-encoding (15020), and in case 2), bandwidth efficiency may decrease because unnecessary data is transmitted, and when a fixed bandwidth is used, data quality may have to be lowered during transmission (15030).

[0282] At this time, in the case of octree-based positional compression, entropy-based compression method and direct coding can be used together, in which case slice configuration is required to efficiently utilize scalability.

[0283] Additionally, for large point clouds with wide distribution and high point density, delay issues may occur due to the large number of bitstreams that must be processed to access the region of interest.

[0284] Layer-group slicing enables partial decoding, spatial random access, and progressive decoding. When using context continuation, context buffer management is required for efficient memory usage.

[0285] Embodiments include efficient context memory management methods and signaling (subsequent_subgroup_bbox_origin, subsequent_subgroup_bbox_size) in a partial coding situation for multiple slashes. Embodiments include a method for selecting a subgroup list related to a context buffer based on subsequent subgroup region information. Embodiments include a method for updating a decoded subgroup list related to each context based on the selected subsequent subgroup list. Embodiments include a method for early releasing a context buffer by comparing the selected subsequent subgroup list with the decoded subgroup list.

[0286] Figure 12 illustrates a layer-based point cloud data configuration according to embodiments.

[0287] The transmission method / device according to the embodiments can encode and decode point cloud data by configuring layer-based point cloud data as shown in FIG. 12.

[0288] Layering of point cloud data can have a layer structure in various perspectives such as SNR, spatial resolution, color, temporal frequency, bitdepth, etc. depending on the application field, and layers can be formed in the direction of increasing data density based on an octree structure or LoD structure.

[0289] Figure 13 illustrates a geometry and attribute bitstream structure according to embodiments.

[0290] The method / device according to the embodiments can construct, encode, and decode a geometry bitstream and an attribute bitstream as in FIG. 13 based on layering as in FIG. 12.

[0291] A bitstream obtained through point cloud compression of a transmitting device / encoder according to embodiments can be divided into a geometry data bitstream and an attribute data bitstream and transmitted according to the type of data.

[0292] Each bitstream according to the embodiments may be transmitted as a slice. Regardless of layer information or LoD information, a geometry data bitstream and an attribute data bitstream may each be transmitted as a slice. In this case, if only a part of a layer or LoD is to be used, the following steps must be taken: 1) a process of decoding the bitstream, 2) a process of selecting only the part to be used and removing unnecessary parts, and 3) a process of re-encoding based only on the necessary information.

[0293] Figure 14 shows a bitstream configuration according to embodiments and a bitstream alignment method according to embodiments.

[0294] The transmission method / device according to the embodiments can generate a bitstream as in FIG. 14, and the reception method / device according to the embodiments can decode point cloud data included in the bitstream as in FIG. 14.

[0295] Bitstream composition according to embodiments

[0296] Embodiments may apply a method of dividing the bitstream into layers (or LoDs) and transmitting them to avoid unnecessary intermediate processes.

[0297] For example, considering the LoD-based PCC technology, it has a structure where lower LoDs are included in higher LoDs. Information included in the current LoD but not in the previous LoD, i.e., newly included information for each LoD, can be referred to as R (Residual, Rest). As shown in Figure 13 and below, the initial LoD information and the newly included information R in each LoD can be divided into independent units and transmitted.

[0298] The transmission method / device according to the embodiments can encode geometry data and generate a geometry bitstream. The geometry bitstream can be configured by LOD or layer, and the geometry bitstream can include a header (geometry header) by LOD or layer configuration unit. The header can include reference information for the next LOD or the next layer. The current LOD (layer) can further include R information (geometry data) that is not included in the previous LOD (layer).

[0299] The receiving method / device according to the embodiments can encode attribute data and generate an attribute bitstream. The attribute bitstream can be configured by LOD or layer, and the attribute bitstream can include a header (attribute header) by LOD or layer. The header can include reference information for the next LOD or the next layer. The current LOD (layer) can further include R information (attribute data) that is not included in the previous LOD (layer).

[0300] The receiving method / device according to the embodiments can receive a bitstream composed of LODs or layers and efficiently decode only the data to be used without a complex intermediate process.

[0301] Figure 15 shows a bitstream alignment method according to embodiments.

[0302] The method / device according to the embodiments can align the bitstream of FIG. 14 as in FIG. 15.

[0303] Bitstream alignment method according to embodiments

[0304] The transmission method / device according to the embodiments can transmit geometry and attributes serially, as illustrated in FIG. 15, when transmitting a bitstream. At this time, depending on the type of data, the entire geometry information (geometry data) can be transmitted first, and then attribute information (attribute data) can be transmitted. In this case, there is an advantage in that the geometry information can be quickly restored based on the information in the transmitted bitstream.

[0305] For example, layers (LODs) containing geometry data may be positioned first in the bitstream, and layers (LODs) containing attribute data may be positioned after the geometry layer. Since attribute data is dependent on geometry data, the geometry layer may be positioned first. Furthermore, the position may vary depending on the embodiments. References between geometry headers are possible, and references between attribute headers and geometry headers are also possible.

[0306] Figure 16 illustrates a bitstream alignment method according to embodiments.

[0307] Figure 16 is an example of bitstream alignment according to embodiments.

[0308] Bitstreams that comprise the same layer, including geometry and attribute data, can also be aggregated and transmitted. In this case, using a compression technique that enables parallel decoding of geometry and attributes can reduce decoding time. In this case, information that needs to be processed first (small LoD, geometry before attributes) can be placed first.

[0309] The first layer (2000) includes geometry data and attribute data corresponding to the smallest LOD 0 (layer 0) along with each header, and the second layer (2010) includes LOD 0 (layer 0) and includes geometry data and attribute data of points for a new and more detailed layer 1 (LOD 1) not present in LOD 0 (layer 0) as R1 information. Similarly, a third layer (2020) may exist subsequently.

[0310] The transmission / reception method / device according to the embodiments can efficiently select a desired layer (or LoD) in an application field at the bitstream level when transmitting and receiving a bitstream. In the case of collecting and transmitting geometry information among the bitstream alignment methods according to the embodiments (Fig. 15), an empty part may appear in the middle after selecting the bitstream level, in which case the bitstream may need to be rearranged. In the case of transmitting geometry and attributes by bundling them according to the layer (Fig. 16), unnecessary information can be selectively removed as follows depending on the application field.

[0311] Figure 17 illustrates a method for selecting geometry data and attribute data according to embodiments.

[0312] Bitstream selection according to embodiments

[0313] As above, when a bitstream needs to be selected, the method / device according to the embodiments can select data at the bitstream level as shown in FIG. 17: 1) symmetric geometry and attribute selection, 2) asymmetric geometry and attribute selection, 3) or a combination of both methods.

[0314] 1) Selecting symmetric geometry attributes

[0315] Referring to Figure 17, this shows a case where only LoD1 is selected (LOD 0 +R1, 21000) and transmitted or decoded. Information corresponding to R2 (a new part of LOD 2) corresponding to the upper layer is removed (21010) and transmitted and decoded.

[0316] Figure 18 shows a bitstream selection method according to embodiments.

[0317] 2) Selecting asymmetric geometry and attributes

[0318] The method / device according to the embodiments can transmit geometry and attributes asymmetrically. Only the attribute of the upper layer can be removed (Attribute R2, 22000) and the entire geometry (from level 0 (root level) to level 7 (leaf level) of the triangular octree structure) can be selected and transmitted / decoded (22010).

[0319] Referring to Figure 12, when point cloud data is expressed in an octree structure and hierarchically divided by LOD (or lair), scalable encoding / decoding (scalability) can be supported.

[0320] Scalability features according to embodiments may include slice level scalability and / or octree level scalability.

[0321] A LoD (level of detail) according to embodiments may be used as a unit to represent a set of one or more octree layers. It may also have the meaning of a bundle of octree layers for configuring them into slice units.

[0322] LOD according to the embodiments is a unit that divides data into details by extending the meaning of LOD when encoding / decoding attributes, and can be used in a broad sense.

[0323] That is, spatial scalability by an actual octree layer (or scalable attribute layer) can be provided for each octree layer, but when configuring scalability at the slice level prior to bitstream parsing, it can be selected at the LoD level according to embodiments.

[0324] In an octree structure, LOD 0 can be from the root level to level 4, LOD 1 can be from the root level to level 5, and LOD 2 can be from the root level to level 7 of the leaf.

[0325] That is, as in Fig. 12, when utilizing scalability in slice units such as scalable transmission, the scalable stages provided are three stages of LoD0, LoD1, and LoD2, and the scalable stages that can be provided in the decoding stage by the octree structure are eight stages from the root to the leaf.

[0326] According to embodiments, for example, in FIG. 12, when LoD0 to LoD2 are each composed of slices, a transcoder (FIG. 11 15040) of a receiver or transmitter can select 1) only LoD0, 2) LoD0 and LoD1, or 3) LoD0, LoD1, and LoD2 for scalable processing.

[0327] Example 1) If only LoD0 is selected, the maximum octree level is 4, and one scalable layer among octree layers 0 to 4 can be selected during the decoding process. At this time, the receiver can consider the node size that can be obtained through the maximum octree depth as a leaf node, and the node size at this time can be transmitted as signaling information.

[0328] Example 2) When LoD0 and LoD1 are selected, layer 5 is added, so the maximum octree level becomes 5, and one scalable layer among octree layers 0 to 5 can be selected during the decoding process. At this time, the receiver can consider the node size that can be obtained through the maximum octree depth as a leaf node, and the node size at this time can be transmitted as signaling information.

[0329] According to embodiments, octree depth, octree layer, octree level, etc. refer to units for dividing data in detail.

[0330] Example 3) When selecting LoD0, LoD1, and LoD2, layers 6 and 7 are added, so that the maximum octree level becomes 7, and one scalable layer among octree layers 0 to 7 can be selected during the decoding process. At this time, the receiver can consider the node size that can be obtained through the maximum octree depth as a leaf node, and the node size at this time can be transmitted as signaling information.

[0331] FIG. 19 illustrates a method for constructing a slice including point cloud data according to embodiments.

[0332] Slice configuration according to embodiments

[0333] The transmission method / device / encoder according to the embodiments may be configured by dividing a G-PCC bit stream into a slice structure. A data unit for detailed data expression may be a slice.

[0334] For example, one or more octree layers can be matched to a single slice.

[0335] A transmission method / device according to embodiments, for example, an encoder, can construct a slice-based bitstream by scanning nodes (points) included in an octree in the scan order direction.

[0336] Figure 19(a): Some nodes of the octree layer may be included in one slice.

[0337] An octree layer (e.g., level 0 to level 4) can constitute one slice.

[0338] In an octree layer, for example, some data from level 5 can constitute each slice.

[0339] In an octree layer, for example, some data from level 6 can constitute each slice.

[0340] Figure 19(b)(c): When multiple octree layers are matched to a single slice, only a portion of the nodes in each layer may be included. In this way, when multiple slices form a single geometry / attribute frame, the information necessary to configure the layers for the receiver can be conveyed. This may include information about the layers contained in each slice and the nodes contained in each layer.

[0341] Figure 19(b): An octree layer, for example, can be configured to contain data from level 0 to level 3 and some data from level 4 as one slice.

[0342] An octree layer, for example, can be configured to contain some data from level 4 and some data from level 5 in one slice.

[0343] An octree layer, for example, can be configured to contain some data from level 5 and some data from level 6 as one slice.

[0344] An octree layer, for example, can organize some data at level 6 into one slice.

[0345] Figure 19(c): Octree layer, for example, data from level 0 to level 4 can be organized into one slice.

[0346] Some data from each of the octree layers levels 5, 6, and 7 can be configured as a single slice.

[0347] An encoder and a device corresponding to the encoder according to the embodiments can encode point cloud data and generate and transmit a bitstream further including parameter information about the encoded data and the point cloud data.

[0348] Furthermore, when generating a bitstream, the bitstream can be generated based on a bitstream structure according to embodiments (e.g., see FIG. 26, etc.). Accordingly, a receiving device, a decoder, a corresponding device, etc. according to embodiments can receive and parse a bitstream configured to suit a selective partial data decoding structure, thereby partially decoding point cloud data and efficiently providing it (see FIG. 11).

[0349] Scalable transmission according to embodiments

[0350] The point cloud data transmission method / device according to the embodiments can scalably transmit a bitstream including point cloud data, and the point cloud data reception method / device according to the embodiments can scalably receive and decode the bitstream.

[0351] When a bitstream according to embodiments such as Fig. 19 is used for scalable transmission, information for selecting a slice required by the receiver can be transmitted to the receiver. Scalable transmission may mean that only a portion of the bitstream is transmitted or decoded rather than decoding the entire bitstream, and the result may be low resolution point cloud data.

[0352] When applying scalable transmission to an octree-based geometry bitstream, it is necessary to be able to construct point cloud data using only information up to a specific octree layer for the bitstream of each octree layer (Fig. 12) from the root node to the leaf node.

[0353] To achieve this, the target octree layer must not depend on information in lower octree layers. This can be a common constraint for geometry / attribute coding.

[0354] In addition, it is necessary to convey a scalable structure for selecting a scalable layer at the transmitter / receiver during scalable transmission. Considering the octree structure according to the implementation, all octree layers may support scalable transmission, but scalable transmission can be enabled only for a specific octree layer or lower. If some octree layers are included, it is possible to determine whether the slice is necessary or not at the bitstream stage by indicating which scalable layer the slice is included in. In the example of Fig. 19(a), the yellow highlighted part starting from the root node does not support scalable transmission and configures a single scalable layer, and the octree layers below can be configured to have a one-to-one match with the scalable layer. In general, scalability can be supported for the part corresponding to the leaf node, and if multiple octree layers are included in a slice as in Fig. 19(c), the layers can be defined to configure a single scalable layer.

[0355] At this time, scalable transmission and scalable decoding can be distinguished and used depending on the purpose. Scalable transmission can be used for the purpose of selecting information up to a specific layer without going through a decoder at the transmitting and receiving end. Scalable decoding is for the purpose of selecting a specific layer during coding. In other words, scalable transmission can support the selection of required information without going through a decoder (at the bitstream stage) in a compressed state, so that it can be identified at the transmitting or receiving end. On the other hand, scalable decoding can be used in cases such as scalable representation by supporting cases where encoding / decoding is performed only up to the required part during the encoding / decoding process.

[0356] In this case, the layer configuration for scalable transmission and the layer configuration for scalable decoding may differ. For example, the three lower octree layers including leaf nodes may constitute one layer from the perspective of scalable transmission, but from the perspective of scalable decoding, if all layer information is included, scalable decoding may be possible for each of the leaf node layer, leaf node layer-1, and leaf node layer-2.

[0357] Figure 20 illustrates single-slice and segmented-slice based geometry tree structures according to embodiments.

[0358] The method / device according to the embodiments can configure a slice for transmitting point cloud data as shown in FIG. 20.

[0359] Figure 20 illustrates a geometry tree structure included in different slice structures. According to the G-PCC technology, the entire coded bitstream can be included in a single slice. Furthermore, for multiple slices, each slice can include sub-bitstreams. The order of the slices can be the same as the order of the sub-bitstreams. The bitstreams are accumulated in breadth-first order of the geometry tree, and each slice can be matched to a group of tree layers (Figure 20). The divided slices can inherit the layering structure of the G-PCC bitstream.

[0360] Just as higher layers in a geometry tree do not affect lower layers, following slices may not affect previous slices.

[0361] Segmented slices according to the embodiments are efficient in terms of error robustness, effective transmission, supporting region of interest, etc.

[0362] 1) Error resilience

[0363] Compared to a single-slice structure, a partitioned slice can be more error-resistant. If a slice contains the entire bitstream of a frame, data loss can affect the entire frame data. On the other hand, if the bitstream is partitioned into multiple slices, even if some slices are lost, some slices that are not affected by the loss can still be decoded.

[0364] 2) Scalable transmission

[0365] Consider supporting multiple decoders with different capabilities. If the coded data resides in a single slice, the LOD of the coded point cloud can be determined prior to encoding. Therefore, multiple pre-encoded bitstreams with different resolutions of the point cloud data can be delivered independently. This can be inefficient in terms of high bandwidth or storage space.

[0366] When a PCC bitstream is generated and included in segmented slices, a single bitstream can support different levels of decoders. From the decoder side, the receiver can select target layers and pass the partially selected bitstream to the decoder. Similarly, by using a single PCC bitstream without partitioning the entire bitstream, a partial PCC bitstream can be efficiently generated on the transmitter side.

[0367] 3) Region-based spatial scalability

[0368] In terms of the G-PCC requirements, region-based spatial scalability can be defined as follows: A compressed bitstream can be structured to have more than one layer. Certain regions of interest can have additional layers and higher density, and layers can be predicted from lower layers.

[0369] To support this requirement, it is necessary to support different detailed representations of regions. For example, in VR / AR applications, it is desirable to represent distant objects with low precision and nearby objects with high precision. Alternatively, the decoder can increase the resolution of a region of interest upon request. This can be implemented by using scalable structures of G-PCC, such as geometry octrees and scalable attribute coding schemes. Based on the current slice structure containing the entire geometry or attribute, decoders must access the entire bitstream. This can lead to bandwidth, memory, and decoder inefficiencies. On the other hand, if the bitstream is segmented into multiple slices, each slice containing sub-bitstreams according to scalable layers, the decoder according to embodiments can select a slice as needed before efficiently parsing the bitstream.

[0370] FIG. 21 illustrates a layer group structure of a geometry coding tree and an aligned layer group structure of an attribute coding tree according to embodiments.

[0371] FIG. 21 illustrates a layer group structure of a geometry coding tree and an aligned layer group structure of an attribute coding tree according to embodiments.

[0372] The method / device according to the embodiments can create a slice layer group using a hierarchical structure or tree structure of point cloud data as shown in FIG. 21.

[0373] The method / device according to the embodiments can apply segmentation of geometry and attribute bitstreams contained in different slices. In addition, the coding tree structure of each slice and geometry and attribute coding contained in partial tree information can be used from a tree depth perspective.

[0374] Referring to Fig. 21(a), an example of a geometry tree structure and a proposed slice segment is shown.

[0375] For example, if there are eight layers (layer 0 to layer 7) in an octree, five slices can be used to contain sub-bitstreams of one or more layers. A group represents a group of geometry tree layers. For example, group 1 consists of layer 0 to layer 4, group 2 includes layer 5, and group 3 includes layer 6 and layer 7. In addition, a group can be divided into three sub-groups. Parent and child pairs exist in each sub-group. Group 3-1 to group 3-3 are sub-groups of group 3. When scalable attribute coding is used, the tree structure is identical to the geometry tree structure. The same octree-to-slice mapping can be used to create attribute slice segments (Fig. 22(b)).

[0376] Layer group: Represents a group of layer structure units that occur in G-PCC coding, such as octree layers and LoD layers.

[0377] Sub-group: A layer group can be represented as a set of adjacent nodes based on location information. Alternatively, a group can be formed based on the lowest layer within the layer group (which may refer to the layer closest to the root direction, for example, layer 6 in the case of group 3 in Fig. 22), a group of adjacent nodes can be formed based on the Morton code order, a group of adjacent nodes based on distance, or a group of adjacent nodes based on coding order. Additionally, nodes in a parent-child relationship can be stipulated to exist within a single sub-group.

[0378] When defining a subgroup, a boundary occurs in the middle of the layer, and whether to have continuity at the boundary can be maintained by indicating whether entropy is used continuously, such as sps_entropy_continuation_enabled_flag, gsh_entropy_continuation_flag, and by indicating ref_slice_id.

[0379] The tree structure of the geometry according to the embodiments may be an octree structure, and the attribute layer structure or attribute tree structure according to the embodiments may include a structure of a level of detail (LOD). That is, the tree structure for point cloud data includes layers corresponding to depth or level, and the layers may be grouped.

[0380] The method / device according to the embodiments (e.g., the octree analysis unit (40002) or LOD generation unit (40009) of FIG. 4, the octree synthesis unit (11001) or LOD generation unit (11008) of FIG. 11) can generate an octree structure of geometry or an LOD tree structure of attributes. In addition, point cloud data can be grouped based on layers of the tree structure as shown in FIGS. 21 and 22.

[0381] Referring to Figure 21, multiple layers are grouped to form Groups 1 through 3. A group can be further divided within itself to form subgroups. Figure 21 illustrates Group 3 being divided into three subgroups.

[0382] The method / device according to the embodiments can generate geometry-based slices and attribute-based slice layers.

[0383] The attribute coding layer may have a different structure than the geometry coding tree.

[0384] To efficiently use the layering structure of G-PCC, it is possible to provide segmentation of slices paired with the geometry and attribute layering structure.

[0385] For a geometry slice segment, each slice segment may contain data coded from a layer group, where a layer group is defined as a group of contiguous tree layers, and the start and end depths of the tree layers may be a specific number within the tree depth, with the start being less than the end.

[0386] For attribute slice segments, each slice segment contains coded data from a group of layers, where the layers can be tree depths or LODs according to the attribute coding scheme.

[0387] The order of coded data within slice segments may be the same as the order of coded data within a single slice.

[0388] As parameter sets included in the bitstream, the following can be provided:

[0389] Figure 22 illustrates the layer group and subgroup structure according to embodiments.

[0390] Point cloud data and bitstream based on layer structure can represent a bounding box as shown in Fig. 22.

[0391] Figure 22 illustrates the subgroup structure and the bounding boxes corresponding to the subgroups. Layer groups 2 and 3 are divided into two subgroups (group2-1, group2-2) and four subgroups (group3-1, group3-2, group3-3, group3-4), which are included in different slices. Given slices of layer groups and subgroups with bounding box information, 1) the bounding box of each slice is compared with the ROI, 2) the slice whose subgroup bounding box correlates with the ROI is selected, and spatial access can be performed. Then, 3) the selected slices are decoded. Considering the ROI in region 3-3, slices 1, 3, and 6 are selected as the subgroup bounding boxes of layer group 1, subgroups 2-2, and 3-3, covering the ROI area. For efficient spatial access, it is assumed that there is no dependency between subgroups of the same layer group. For live streaming or low-latency use cases, selection and decoding of each slice segment can be performed as it is received, improving time efficiency.

[0392] The method / device according to the embodiments can express data as a layer tree (22000) by layers (which can be referred to as depths, levels, etc.) when encoding geometry and / or attributes. Point cloud data corresponding to each layer (depth / level) can be grouped into layer groups (or groups, 22001). Each layer group can be further divided (segmented) into subgroups (22002). Each subgroup can be configured as a slice to generate a bitstream. The receiving device according to the embodiments can receive the bitstream, select a specific slice, decode a subgroup included in the slice, and decode a bounding box corresponding to the subgroup. For example, if slice 1 is selected, a bounding box (22003) corresponding to group 1 can be decoded. Group 1 may be data corresponding to the largest area. If the user wants to additionally view the detailed area for group 1, the method / device according to the embodiments can partially hierarchically access the bounding boxes (point cloud data) of group 2-2 and / or group 3-3 for the detailed area included in the area of ​​group 1 by selecting slice 3 and / or slice 6.

[0393] Embodiments can select a slice based on subgroup bounding box information. For example, a slice matching an ROI is determined and selected based on subgroup bounding box information.

[0394] When dividing slices and delivering them in a way that proposes a compressed bitstream for the full coding layer, it is possible to support receivers with different performances. When selectively decoding slices based on ROI or receiver performance, the selection can be done directly at the receiver or at the transcoder. In the case of selection at the transcoder, information regarding the case of full decoding (e.g., total coding layer depth, total number of layer groups, total number of subgroups, etc.) is not available, and in this case, the receiver may need such information during the decoding process. In this case, the information can be directly delivered or inferred, such as the number of skipped layer groups (num_skipped_layer_groups) and the number of skipped layers (num_skipped_layers), can be delivered to the decoder.

[0395] Figure 23 illustrates an example of context references between layer groups according to embodiments.

[0396] Referring to FIG. 23, a fine-granularity slice (FGS) may represent a subgroup or slice, and the subgroup or slice may be a grouping of point cloud data according to embodiments.

[0397] In Fig. 23, FGS 1(1,0) represents subgroup 0 of layer group 1, and FGS 2(1,1) represents subgroup 1 of layer group 1. FGS N+1(2,0) represents subgroup 0 of layer group 2, and FGS N+2(2,1) represents subgroup 1 of layer group 2.

[0398] In Fig. 23, Save states indicates encoding or decoding the corresponding subgroup and saving context information, and Refer context indicates referencing the saved context information to encode or decode the corresponding subgroup.

[0399] Accordingly, in Fig. 23, it is exemplified that FGS 1 references the context information of FGS 0 (23001), and FGS N+1 (23003) references the context information of FGS 1 (23002). As in Fig. 23, a subgroup (or slice) belonging to layer group 2 can reference the context of a subgroup (or slice) belonging to layer group 1. In addition, a subgroup belonging to layer group 1 can be a parent subgroup of a subgroup belonging to layer group 2.

[0400] Context inheritance

[0401] Figure 23 illustrates a context reference structure of layer group slicing according to embodiments. In the figure, an FGS may correspond to a subgroup according to embodiments, and subgroups in the same row are considered to be in the same layer group. A subgroup may correspond to a slice. In the figure, an arrow pointing from one slice to another indicates a context reference relationship between the two slices. The context of the current slice may refer to a slice decoded before the current slice.

[0402] Considering the spatial random access (SRA) model, referencing parent subgroups can be a good choice for ensuring independence between subgroups. However, as the number of subgroups or layer groups increases, the number of context buffers can also increase. Considering the number of context buffers as the number of referenced slices, the number of context buffers can be the sum of all subgroups except those belonging to the first and last layer groups. This is formulated as follows, where N represents a number.

[0403] N_(context buffer)=1+N_subgroup×(N_(layer-group)-2)

[0404] Figure 24 illustrates an example of context reference between groups according to embodiments.

[0405] In Fig. 24, FGS 1 (24002) to FGS N, FGS N+1 (24003) to FGS 2N+1 refer to the context information of FGS 0 (24001). That is, all subgroups (or slices) except FGS 0 (24001) refer to FGS 0 (24001).

[0406] One way to mitigate the size of the context buffer according to embodiments may be to reduce the number of subgroups referenced by following slices. An extreme example of this method is to reference the root slice, as shown in Figure 24. This approach, based on the number of context buffers described above, results in a single context buffer because the number of subgroup slices referenced is zero.

[0407] N_(context buffer)=1

[0408] That is, all slices reference the first slice. Compared to the case of Figure 24, the number of saved context states is reduced to one, and all dependent slices reference the first slice.

[0409] Figure 25 illustrates an example of context buffer management according to embodiments.

[0410] Referring to (a) of FIG. 25, the transmitting and receiving device according to the embodiments processes FGS 0(0,0)(25001) and stores context information (25002) for the corresponding group (FGS 0) in the context buffer.

[0411] Referring to (b) of FIG. 25, the transceiver device according to the embodiments can load context information (25004) of FGS 0 stored in a context buffer to process (encode or decode) FGS 2(1,1)(25003) (load states), and can process FGS 2(1,1) and store context information of FGS 2(1,1) in the context buffer (Save states). At this time, the process of loading context information can be performed with reference to the ref_layer_group_id and ref_subgroup_id parameters.

[0412] Referring to (c) of FIG. 25, the transceiver device according to the embodiments can load context information (context states (1,1)) of FGS 2 (1,1) to process (encode or decode) FGS N+2 (2,1) (25005). Since FGS N+2 (2,1) belongs to the last layer group, context information is not stored in the context buffer.

[0413] Referring to FIG. 25, in the case of the parent subgroup reference method, the change of the context buffer is illustrated. When the bitstream of a slice is decoded, the context state is stored in the context buffer as shown in FIG. 25(a). If context inheritance is used, the context states of the following slices are initialized with one of the stored context states of the previous slices indicated by ref_layer_group_id and ref_subgroup_id (FIG. 25(b)). Therefore, the context state of the slice belonging to the last layer group is initialized with the stored context state of the previous slice as shown in FIG. 25(c). However, the receiving device (or decoder) according to the embodiments may decide not to store the context of FGS N+1 to 2N if there is a restriction that does not refer to a subgroup belonging to the same layer group. Based on the previous information, the smart decoder can save the context buffer.

[0414] Figure 26 illustrates an example of context buffer management according to embodiments.

[0415] Referring to (a) of FIG. 26, the transmitting and receiving device according to the embodiments processes FGS 0(0,0)(26001) and stores context information (26002) for the corresponding group (FGS 0) in the context buffer.

[0416] Referring to (b) of FIG. 26, the transceiver device according to the embodiments can load context information (26004) of FGS 0 stored in a context buffer to process (encode or decode) FGS 2(1,1)(26003) (load states), and process FGS 2(1,1) and store context information of FGS 2(1,1) in the context buffer (Save states). At this time, the process of loading context information can be performed with reference to the ref_layer_group_id and ref_subgroup_id parameters.

[0417] Referring to (c) of FIG. 26, the transmitting and receiving device according to the embodiments can load the context information (context states (0,0)) (26006) of FGS 0 (0,0) (26001) to process (encode or decode) FGS N+2 (2,1) (26005). Since FGS N+2 (2,1) (26005) belongs to the last layer group, the context information is not stored in the context buffer.

[0418] When flexible context references are allowed, there may be context states that are not used by following slices. For example, consider a root layer group reference, where all context states of dependent slices are initialized by the context state saved from the first slice. Decoders are unaware of the overall reference structure and may use the current context of following slices. However, as expected, the context states saved from (1,0) to (1,N-1) are not used by any slice. In this example, the inefficiency arises from the lack of information on the decoder side.

[0419] Figure 27 illustrates an example of context buffer management according to embodiments.

[0420] Referring to (b) of FIG. 27, the transmitting / receiving device / method according to the embodiments can retrieve context information (context states (0,0)) (27004) of FGS 0 (0,0) (27001) from the context buffer to process (encode or decode) FGS 2 (1,1) (27003). Then, the context information of FGS 2 (1,1) can be stored in the context buffer based on the context_reference_indication_flag information. That is, the context information of FGS 2 (1,1) may or may not be stored in the buffer depending on the context_reference_indication_flag information. The context_reference_indication_flag information can be generated and transmitted by the transmitting device / method according to the embodiments, and used in the receiving device / method according to the embodiments.

[0421] Referring to (c) of FIG. 27, the transmitting and receiving device / method according to the embodiments can retrieve context information (context states(0,0))(27006) of FGS 0(0,0)(27001) from the context buffer to process (encode or decode) FGS N+2(2,1)(27005).

[0422] Since the context buffer always stores only context information of FGS 0, the transmitting and receiving device according to the embodiments can efficiently use the memory of the buffer.

[0423] The transceiver according to the embodiments proposes a new signal to assist the decoder in indicating whether the current context of followed slices is used and deciding whether to store the context, in order to increase the efficiency of context buffer management.

[0424] A followed slice according to embodiments may represent a slice that is referenced by other slices. A following slice according to embodiments may represent a slice that references other slices.

[0425] To improve context buffer management on the decoder side, context reference information is proposed from the perspective of the current slice, i.e., context state reference indication by followed slices.

[0426] Figure 27 (b) illustrates a buffer management case of the proposed signal. Compared to previous cases without other information, storing the context state in the context buffer is determined by the context reference indicator (context_reference_indication_flag). If the context reference indicator is on, the decoder stores the current context state in the context buffer to allow context state usage by followed slices. On the other hand, if the context reference indicator is off, the decoder does not store the current context state in the context buffer to save context memory. Comparing Figure 27 (c) with Figure 27 (c), the context buffer of the root layer reference case only has one context compared to the context buffer of the parent subgroup reference case. The saved context memory size is N units, where N represents the number of subgroups.

[0427] Figure 28 shows a table comparing context memory usage of context buffers according to embodiments.

[0428] To investigate the effectiveness of utilizing flexible context inheritance according to embodiments, memory usage and compression loss were compared for fixed and flexible context reference approaches. The context reference of the parent subgroup, i.e., ref-parent, and the context reference of the root layer group, i.e., ref-root, are considered as representatives of the fixed and flexible context reference approaches.

[0429] For each method, the amount of memory used to store the GeometryOctreeContext was measured for each decoding process of the slices. In this experiment, Statue_Klimt_vox12.ply is used as input, and 10 subgroups are provided under the test conditions. Memory usage at each step is measured using tools in Visual Studio 15 2017.

[0430] Referring to Figure 28, the memory usage of each method is expressed in bytes and the number of contexts. The number of contexts is derived by using the fact that the size of one GeometryOctreeContext is 18,230 bytes. In the case of parent references, the number of stored contexts increases monotonically from slice 1 to slice 5. In slice 10, the expected number of contexts was 11 (= 1 + 10), but the number of contexts measured in actual size was 13, which is due to the compiler's memory allocation strategy. In addition, the size of the context storage memory did not change for the slices in the last layer group (i.e., slices 11 to 20). On the other hand, the number of context memories did not change in the root reference case. This means that only one context was used for all slices from slice 1 to 20.

[0431] Figure 29 shows a table comparing context memory usage of context buffers according to embodiments.

[0432] To examine memory usage across a growing number of slices, we performed the same memory check with the same content across an increasing number of layer groups. The layer group structure changes from 8-3-1 to 8-1-1-1-1. In the table in Fig. 29, the number of contexts referenced by ref-parent increases, except for slices 31 to 40 of layer group 4. On the other hand, for ref-root, context memory remains unchanged across all slices.

[0433] Referring to Figure 29, in the case of the parent group reference method (ref-parent), as the number of slices (or subgroups) increases, the number of stored contexts increases, and memory usage increases. On the other hand, in the case of the root group reference method (ref-root), the number of stored contexts remains constant at 1 even if the number of slices (or subgroups) increases.

[0434] Figure 30 is a table showing the results of context buffer management according to embodiments.

[0435] To investigate the compression loss due to context reference changes, the average bitrates of the two methods are compared. Referring to the table in Figure 30, the average compression loss is 0.1% for the C2 and CW conditions. In terms of time consumption, the root layer group reference shows 3% and 4% less decoding time than the parent subgroup reference.

[0436] Figure 31 is a table showing the results of context buffer management according to embodiments.

[0437] The receiver can use context, phiBuffer, Planar context, and buffer continuity between slices to prevent coding efficiency reduction caused by dividing slices, and the receiver can decide whether to store context, phiBuffer, and Planar context based on whether the context is reused.

[0438] if (_dep_gbh.context_reuse_flag) {

[0439] _refIdxToSavedArrayIdx[curLayerGroup][_dep_gbh.subgroup_id] = _ctxtMemSaved.size();

[0440] _ctxtMemSaved.push_back(cur_ctxtMem);

[0441]

[0442] if(_gps->geom_angular_mode_enabled_flag)

[0443] _phiBufferSaved.push_back(cur_phiBuffer);

[0444] if(_gps->geom_planar_mode_enabled_flag)

[0445] _planarSaved.push_back(cur_planar);

[0446] int idx = _refIdxToSavedArrayIdx[curLayerGroup][_dep_gbh.subgroup_id];

[0447] }

[0448] Figure 32 illustrates a context buffer release method according to embodiments.

[0449] A method according to embodiments includes a method for determining a decoder context release time.

[0450] When indicating whether a context is reusable, it indicates whether the context used in a specific slice should be stored in the context buffer. This allows for efficient use of context buffer memory by storing only the context needed when coding subsequent slices. However, in this case, the context is stored in the context buffer until the coding for that frame is completed, which can place a burden on the context buffer as the number of stored contexts increases. To utilize the context buffer more efficiently, a method can be used to delete stored contexts from the context buffer when they are no longer needed.

[0451] 1) List-based context memory management method

[0452] Figure 32 illustrates a method for managing a list of slices / subgroups using context information stored in a buffer as a method for effectively managing context memory. Figure 32 illustrates a method for managing context memory based on a list.

[0453] Fig. 32(a): Whether the context used to code the current slice is stored can be indicated through the context reference indication flag (context_reference_indication_flag). That is, if the context reference indication flag (context_reference_indication_flag) is 1, it can indicate that the context of the current slice / subgroup can be used in the slice / subgroup transmitted later, and can be stored in the context buffer. In order to use the context later, the index of the context can be made to have the same index as the subgroup index. At this time, if information about the slice / subgroup using the current context is given as a list, the target list can be stored and compared with the list for actual use cases. The list of slices / subgroups using the context can be investigated in advance by the encoder and transmitted, or the list can be generated by inferring the context reference relationship based on a predetermined layer group structure in the decoder. For example, if the context of the parent subgroup is fixed in a way that references it, the list of subgroups that are children of the current subgroup can be examined, which in this embodiment can be called list A.

[0454] Fig. 32(b): When a new slice / subgroup is passed, the context used to decode the slice / subgroup can be specified based on the context reference id. In the following example, the context corresponding to (0,0) is used, and the index (1,1) of the current slice / subgroup can be added to the list of used subgroups. In the coding process, the list of slices / subgroups that use a specific context is called List B. If the context reference indication flag (context_reference_indication_flag) is 1, it means that the context of the current slice / subgroup will be used later, so it can be stored in the context buffer, and List B (1,1) of the context buffer (1,1) can be initialized.

[0455] Fig. 32(c): If lists A and B are the same for a specific context buffer, memory can be managed by releasing the context buffer. As follows, if the context reference id is (1,1), the context state (1,1) can be used for coding in the context buffer. At this time, the index of the current slice / subgroup, (2,1), can be added to list B. At this time, since list B is the same as list A = ( (2,1) ), we can see that the context state (1,1) will not be used in the future. In this case, the memory of the context buffer can be effectively managed by releasing the memory that stored the context state (1,1).

[0456] The embodiments include a method for specifying a context index based on a layer group index and a subgroup index. If a unique slice index is assigned to each slice, a context buffer list can be managed based on the slice index.

[0457] Figure 33 illustrates a context buffer release method according to embodiments.

[0458] Embodiments include a method for managing context memory based on the number of references.

[0459] Context buffers can be efficiently utilized by managing unused context states in real time based on the number of times each context state is used. Embodiments can manage context buffers using target numbers and counters for each context state in the context buffer.

[0460] Fig. 33(a): The target number stores the number of times each context state is used, and the counter can update the number of times the context state is used. Fig. 33(a) shows the case of the first slice / subgroup, and if the context reference indication flag (context_reference_indication_flag) is 1 or layer-group slicing is used, the context state (0,0) can be stored in the context buffer. In addition, the number of times the context state is used, N, can be stored in the target number, and this can be specified as the same value as N, the number of subgroups belonging to layer-group 1, by using the case of using the context state of the parent subgroup as an example. In other words, the list of child subgroups of FGS 0 can be obtained as FGS 1 (1,0), FGS 2 (1,1), …, FGS N (1, N-1), and the number of elements N belonging to the list can be specified as the target number.

[0461] Fig. 33(b): When coding a new slice / subgroup, the context reference of the corresponding slice / subgroup can be found in the context buffer via the context reference id. The context state (0,0) will be used, and the counter number can be increased by 1. Since the context state (0,0) was already used to code FGS 1 (1,0), the counter can have the value 2. Also, since the context reference indication flag (context_reference_indication_flag) is 1, it means that it can be used as a context reference in the following slice / subgroup, so the context state of FGS 2 (1,1) can be stored in the context buffer. At this time, the number of child slices / subgroups that use the context state (1,1) can be stored in the target number.

[0462] Fig. 33(c): The memory usage of the context buffer can be managed through memory release for context states whose target number and counter managed in the context buffer are the same. The context state (1,1) corresponding to the context reference id of FGS N+2 can be used, and the counter (1,1) can be increased by 1. In this case, the target number and counter of the context state (1,1) become the same, which means that the context state (1,1) is no longer in use. Therefore, even if the context state (1,1) is deleted from the context buffer, it does not affect the coding of subsequent slices / subgroups. The memory usage of the context buffer can be minimized by deleting context states that are no longer used from the context buffer.

[0463] The following shows an example of decoder code implementation.

[0464] if (_dep_gbh.context_reference_indication_flag) {

[0465] _refIdxToSavedArrayIdx[curLayerGroup][_dep_gbh.subgroup_id] = _ctxtMemSaved.size();

[0466] _ctxtMemSaved.push_back(cur_ctxtMem);

[0467] _numSubsequentSubgroups.push_back(_dep_gbh.numSubsequentSubgroups);

[0468] if (_gps->geom_angular_mode_enabled_flag)

[0469] _phiBufferSaved.push_back(cur_phiBuffer);

[0470] if (_gps->geom_planar_mode_enabled_flag)

[0471] _planarSaved.push_back(cur_planar);

[0472] }

[0473] _numSubsequentSubgroups[refArrayIdx]--;

[0474] if (_numSubsequentSubgroups[refArrayIdx] == 0) {

[0475] _ctxtMemSaved[refArrayIdx].resetMap();

[0476] _ctxtMemSaved[refArrayIdx].reset();

[0477] }

[0478] The target number for each context state can be passed after examining the number of subsequent subgroups in the encoder. If necessary, a list of slices / subgroups used as context references can be additionally passed to verify the accuracy of the number of subsequent subgroups and determine whether to delete the context state.

[0479] Figure 34 illustrates a context memory management method according to embodiments.

[0480] Embodiments include a method for managing context memory based on a data unit coding structure.

[0481] Slices / subgroups can be delivered based on a certain order. Representative methods include breadth-first search and depth-first search. Breadth-first search is a method that codes subgroups within the same layer group before coding subgroups within child layer groups. In contrast, depth-first search is a method that first codes children within the same parent layer group after reaching the subgroup corresponding to the maximum depth.

[0482] If we consider each node as an FGS slice index, we can assume that layer group 0 belongs to slice 0, layer group 1 belongs to slices 1 and 2, and layer group 2 belongs to slices 3, 4, 5, and 6. In addition, we can assume that slices connected by solid lines represent slice pairs belonging to a parent-child relationship. If coding is based on breadth-first search, the order is 0, 1, 2, 3, 4, 5, 6, and if coding is based on depth-first search, the order is 0, 1, 3, 4, 2, 5, 6.

[0483] If the memory of the context buffer is managed based on the slice order, it can work as follows. At this time, it can be assumed that the parent context state is used as the reference context. If it is coded based on breadth-first search, the context state of the upper layer group is no longer used when the coding of the subgroup belonging to each layer group is finished. That is, context state 0 is used when coding slices 1 and 2, but context state 1 is no longer used when coding slice 2. In this case, when the layer group is switched (slice 2), the context state of the parent subgroup (the context state of slice 0) can be deleted from the context buffer.

[0484] If coding is based on depth-first search, the context state can be deleted at the point where the coding for the child subgroup is finished or when the layer group is switched (from the bottom to the root). After coding for slices 3 and 4 is finished, it moves on to slice 2. At this time, slices 3 and 4 belong to layer group 2, and slice 2 belongs to layer group 1. Slices 3 and 4 are coded using the context state of slice 1, and since context state 1 is no longer used, it can be deleted from the context buffer.

[0485] In this case, context memory can be used efficiently without additional information such as the list of subsequent subgroups or the number of subsequent subgroups.

[0486] Figure 35 shows a bitstream including point cloud data according to embodiments.

[0487] An encoder according to embodiments may encode point cloud data, generate related parameter information, and generate a bitstream. A decoder according to embodiments may receive the bitstream and decode the point cloud data based on the parameter information.

[0488] Information about separated slices can be defined in parameter sets and SEI messages as follows. It can be defined in Sequence Parameter Set (SPS), Geometry Parameter Set (GPS), Attribute Parameter Set (APS), Geometry Slice Header (GSH), and Attribute Slice Header (ASH). Depending on the application or system, it can be defined in a corresponding location or in a separate location to use different scopes, application methods, etc. That is, the signal can have different meanings depending on the location where it is transmitted. If it is defined in SPS, it can be applied equally to the entire sequence. If it is defined in GPS, it can indicate that it is used for position recovery. If it is defined in APS, it can indicate that it is applied to attribute recovery. If it is defined in TPS (Tile Parameter Set), it can indicate that the signaling is applied only to points within a tile. If it is transmitted in slice units, it can indicate that the signal is applied only to the corresponding slice. In addition, depending on the application or system, it can be defined in a corresponding location or in a separate location to use different scopes, application methods, etc. Additionally, if the syntax elements defined below can be applied to multiple p-point cloud data streams as well as the current point cloud data stream, they can be conveyed through a parameter set of a higher concept, etc.

[0489] Each abbreviation stands for the following. Each abbreviation may be referred to by other terms within the same meaning: SPS: Sequence Parameter Set, GPS: Geometry Parameter Set, APS: Attribute Parameter Set, TPS: Tile Parameter Set, Geom: Geometry bitstream = geometry slice header + geometry slice data, Attr: Attribute bitstream = attribute blick header + attribute brick data.

[0490] Embodiments can generate this information independently of the coding technique or in conjunction with the coding method. A tile parameter set can be defined to support regionally varying scalability. Alternatively, bitstreams can be selected at the system level by defining a Network Abstract Layer (NAL) unit and conveying relevant information, such as a layer ID (layer_id), that allows layer selection.

[0491] Hereinafter, parameters (which may be referred to in various ways, such as metadata, signaling information, etc.) according to the embodiments may be generated in the process of a transmitter according to the embodiments described below, and may be transmitted to a receiver according to the embodiments and used in the reconstruction process.

[0492] For example, parameters according to embodiments may be generated in a metadata processing unit (or metadata generator) of a transmitting device according to embodiments described below, and may be obtained in a metadata parser of a receiving device according to embodiments.

[0493] Figure 36 shows a sequence parameter set of a bitstream according to embodiments.

[0494] Figure 37 illustrates a dependent geometry data unit header of a bitstream according to embodiments.

[0495] Figure 38 shows a dependent attribute data unit header of a bitstream according to embodiments.

[0496] Figures 39a and 39b illustrate layer group structure inventories according to embodiments.

[0497] The definitions of information in Figures 36 to 39a and 39b are as follows:

[0498] When the layer group enable flag (layer_group_enabled_flag) is equal to 1, it indicates that the geometry and / or attribute bitstreams of a frame or tile are contained in multiple slices that match the coding layer group or its subgroups. When layer_group_enabled_flag is equal to 0, it indicates that the geometry bitstreams of a frame or tile are contained in a single slice.

[0499] The layer group slice order type (layer_group_slice_order_type) indicates the order type of the layer group slice. If layer_group_slice_order_type is 0, it indicates a breadth-first search order of the layer group slice. If layer_group_slice_order_type is 1, it indicates a depth-first search order of the layer group slice. A layer_group_slice_order_type of 2 indicates that no order type is specified.

[0500] If the context reference indication flag (context_reference_indication_flag) is 1, it indicates that the context state of the current dependent slice is inherited by one or more subsequent dependent slices. If context_reference_indication_flag is 0, it indicates that the context state of the current dependent slice is not inherited by subsequent dependent slices.

[0501] The decoder can manage the context buffer using context_reference_indication_flag. If context_reference_indication_flag is 1, the context state of the current dependent slice is saved in the context buffer when decoding is finished. If context_reference_indication_flag is 0, the context state of the current dependent slice is not saved in the context buffer.

[0502] The number of subsequent data units (num_subsequent_data_units) indicates the number of subsequent dependent data units that use the context state of the current data unit.

[0503] If the subsequent data unit list presence flag (subsequent_data_unit_list_present_flag) is 1, it indicates that a subsequent data unit list exists. If next_data_unit_list_present_flag is 0, it indicates that a subsequent data unit list does not exist.

[0504] The number_of_layer_groups indicates the number of layer groups in the subsequent data unit list.

[0505] The subsequent layer group id (subsequent_layer_group_id) indicates the layer group index of the subsequent data unit.

[0506] The number_of_subgroups indicates the number of subgroups in the layer group in the subsequent data unit list.

[0507] The subsequent subgroup id (subsequent_subgroup_id) indicates the subgroup index within the layer group of the subsequent data unit.

[0508] Layer Group Structure Inventory Syntax

[0509] Sequence parameter set id (lgsi_seq_parameter_set_id) indicates the sps_seq_parameter_set_id value. lgsi_seq_parameter_set_id being 0 is a requirement for bitstream conformance.

[0510] lgsi_frame_ctr_lsb_bits represents the length of the lgsi_frame_ctr_lsb syntax element in bits.

[0511] lgsi_frame_ctr_lsb represents the lgsi_frame_ctr_lsb_bits least significant bits of the FrameCtr for which the group structure inventory is valid. A layer group structure inventory remains valid until it is replaced by another layer group structure inventory.

[0512] Number of slices (lgsi_num_slice_ids_minus1): This value plus 1 represents the number of slices in the layer group structure inventory.

[0513] Slice id (gi_slice_id) represents the slice ID of the sid-th slice within the layer group structure inventory. It is a bitstream conformance requirement that all values ​​of lgsi_slice_id be unique within the layer group structure inventory.

[0514] The number of layer groups (lgsi_num_layer_groups_minus1) + 1 indicates the number of layer groups.

[0515] Layer group id (lgsi_layer_group_id) indicates the indicator of the layer group. The range of lgsi_layer_group_id is from 0 to lgsi_num_layer_groups_minus1.

[0516] The number of layers (lgsi_num_layers_minus1) + 1 represents the number of coded layers in the slice of the i-th layer group of the sid-th slice. The total number of coded layers required to decode the n-th layer group is equal to the sum of lgsi_num_layers_minus1[sid][i] + 1, where i is from 0 to n.

[0517] The number of subgroups (lgsi_num_subgroups_minus1) + 1 represents the number of subgroups in the i-th layer group of the sid-th slice.

[0518] The subgroup id (lgsi_subgroup_id) indicates the indicator of the layer group. The range of lgsi_subgroup_id is from 0 to lgsi_num_subgroups_minus1.

[0519] The parent subgroup id (lgsi_parent_subgroup_id) indicates the identifier of a subgroup within the layer group pointed to by lgsi_subgroup_id. The range of lgsi_parent_subgroup_id is from 0 to gi_num_subgroups_minus1 within the layer group pointed to by lgsi_subgroup_id.

[0520] The subgroup bounding box origin (lgsi_subgroup_bbox_origin) and subgroup bounding box size (lgsi_subgroup_bbox_size) represent the bounding box of the current subgroup.

[0521] The subgroup bounding box origin (lgsi_subgroup_bbox_origin) indicates the origin of the subgroup bounding box of the subgroup indicated by lgsi_subgroup_id among the layer groups indicated by lgsi_layer_group_id.

[0522] lgsi_subgroup_bbox_size indicates the size of the subgroup bounding box of the subgroup indicated by lgsi_subgroup_id among the layer groups indicated by lgsi_layer_group_id.

[0523] lgsi_origin_bits_minus + 1 represents the length of the lgsi_origin_xyz syntax element in bits.

[0524] The origin location (lgsi_origin_xyz) indicates the origin of all partitions. The value of lgsi_origin_xyz[ k ] is equal to sps_bounding_box_offset[ k ].

[0525] lgsi_origin_log2_scale represents a scaling factor for scaling the components of lgsi_origin_xyz. The value of lgsi_origin_log2_scale is equal to sps_bounding_box_offset_log2_scale.

[0526] Fig. 40 illustrates a point cloud data transmission device / method according to embodiments.

[0527] Each component of the device 40 corresponds to hardware, software, a processor, and / or a combination thereof.

[0528] Referring to Fig. 40, an embodiment of a detailed functional configuration for encoding / transmitting PCC data is shown. When point cloud data is input, the encoder can encode geometry information (e.g., XYZ coordinates, phi-theta coordinates, etc.) and attribute information (e.g., color, reflectance, intensity, grayscale, opacity, medium, material, glossiness, etc.) respectively. The compressed data is divided into units for transmission, and the required information can be selected from the bitstream units according to the layering structure information through a sub-bitstream generator (38010) and packed into appropriate units.

[0529] According to embodiments, when different types of bitstreams are included in one slice, the encoder can separate the generated bitstream (AEC bitstream or DC bitstream) according to the purpose. Then, each slice or adjacent information can be included in one slice according to layer group information. At this time, through the metadata generator (38006), information such as layer group information, layer information included in the layer group, number of nodes, layer depth information, number of nodes included in the sub-group, bitstream type, bitstream offset, bitstream length, and bitstream direction can be transmitted according to each slice ID.

[0530] When point cloud data is input to a transmitting device according to embodiments, a geometry encoder (40002) encodes location information (geometry data: e.g., XYZ coordinates, phi-theta coordinates, etc.), and an attribute encoder (40004) encodes attribute information (attribute data: e.g., color, reflectance, intensity, grayscale, opacity, medium, material, glossiness, etc.).

[0531] Compressed (encoded) data is divided into units for transmission, and the required information can be selected from the bitstream units according to layering structure information through the sub-bitstream generation unit (40010) and packed into appropriate units.

[0532] According to embodiments, an octree coded geometry bitstream is input to an octree coded geometry bitstream segmentation unit (octree coded geom bitstream segmentation, 40011), and a direct coded geometry bitstream is input to a direct coded geometry bitstream segmentation unit (direct coded geom bitstream segmentation, 40012).

[0533] An octree-coded geometry bitstream segmentation unit (40011) performs a process of dividing an octree-coded geometry bitstream into one or more groups and / or subgroups based on information about segmented (separated) slices generated in a layer-group structure generation unit (40014) and / or information related to direct coding.

[0534] Additionally, the direct coded geometry bitstream segmentation unit (40012) performs a process of dividing the direct coded geometry bitstream into one or more groups and / or subgroups based on information about segmented (separated) slices generated by the layer-group structure generation unit (40014) and / or information related to direct coding.

[0535] The output of the octree-coded geometry bitstream segmentation unit (40011) and the output of the direct-coded geometry bitstream segmentation unit (40012) are input to the geometry bitstream bonding unit (40013).

[0536] The geometry bitstream bonding unit (40013) performs a geometry bitstream bonding process based on information about segmented (separated) slices generated by the layer-group structure generation unit (40014) and / or information related to direct coding, and outputs sub-bitstreams to the segmented slice generation unit in units of layer groups. For example, the geometry bitstream bonding unit (40013) performs a process of bonding an AEC bitstream and a DC bitstream within one slice. The final slices are created in the geometry bitstream bonding unit.

[0537] The coded attribute bitstream segmentation unit (40015) performs a process of dividing the coded attribute bitstream into one or more groups and / or subgroups based on information about segmented (separated) slices generated by the layer-group structure generation unit (40014) and / or information related to direct coding. The one or more groups and / or subgroups of attribute information may be linked to one or more groups and / or subgroups for geometry information, or may be generated independently.

[0538] The segmented slice generation unit (40016) receives the geometry bitstream bonding unit (40013) and / or the coded attribute bitstream segmentation unit (40015) based on information about the segmented (separated) slice generated by the metadata generation unit (40006) and / or information related to direct coding, and performs a process of segmenting one slice into multiple slices. Each sub-bitstream is transmitted through each slice segment. At this time, the AEC bitstream and the DC bitstream may be transmitted through one slice or may be transmitted through different slices.

[0539] The multiplexer (40008) multiplexes the output of the segmented slice generation unit (40016) and the output of the metadata generation unit (40006) for each layer and outputs them to the transmitter (40009).

[0540] When different types of bitstreams (e.g., AEC bitstream and DC bitstream) are included in one slice, the geometry encoder (40002) can separate the generated bitstreams (e.g., AEC bitstream and DC bitstream) according to the purpose. Then, each slice or adjacent information can be included in one slice according to information about the segmented (separated) slices generated by the layer-group structure generation unit (40014) and / or the metadata generation unit (40006) and / or information related to direct coding (i.e., layer-group information). According to embodiments, information about segmented (separated) slices and / or information related to direct coding (e.g., layer-group information, layer information included in the layer-group, number of nodes, layer depth information, number of nodes included in the sub-group, along with information about bitstream type, bitstream_offset, bitstream_length, bitstream direction, etc., according to each slice id) may be transmitted through the metadata generation unit (40006). Information about segmented (separated) slices and / or information related to direct coding (e.g., layer-group information, layer information included in the layer-group, number of nodes, layer depth information, number of nodes included in the sub-group, along with information about bitstream type, bitstream_offset, bitstream_length, bitstream direction, etc., according to each slice id) may be signaled in an SPS, an APS, a GPS, a geometry data unit header, an attribute data unit header, or an SEI message.

[0541] Fig. 41 illustrates a point cloud data receiving device / method according to embodiments.

[0542] The receiving method of Fig. 41 can follow the reverse process of the transmitting method of Fig. 40. Each component of the Fig. 41 device corresponds to hardware, software, a processor, and / or a combination thereof.

[0543] Fig. 41 is an embodiment of a detailed functional configuration for receiving / decoding PCC data. When a bitstream is input, the receiving device according to the embodiments can process a bitstream for position information and a bitstream for attribute information by distinguishing between them. At this time, a sub-bitstream classifier (41010) can transmit the bitstream to an appropriate decoder based on information in the bitstream header. Alternatively, a layer required by the receiver can be selected during this process. The classified bitstream can be restored into geometry data and attribute data, respectively, by a geometry decoder (41006) and an attribute decoder (41008) according to the characteristics of the data, and then converted into a format for final output by a renderer (41009).

[0544] When different types of geometry bitstreams are included, each bitstream can be decoded separately through a bitstream splitter (41014) as shown below. In an embodiment of the present invention, an arithmetic entropy coded bitstream based on octree coding and a direct coded bitstream can be distinguished and processed in a geometry decoder. At this time, separation can be performed based on information about bitstream type, bitstream_offset, bitstream_length, and bitstream direction. A process of attaching (or connecting) bitstream segments of the same type for the separated bitstreams can be included. This can be included as a process for processing bitstreams separated by layer-group as a continuous bitstream, and bitstreams can be sorted in order based on layer-group information. If a bitstream can be processed in parallel, it can be processed in the decoder without a concatenation process.

[0545] The receiver (41002) can receive a bitstream.

[0546] The demultiplexer (41004) can output point cloud data and metadata (signaling information) included in the bitstream.

[0547] The sub-bitstream classifier (41010) can select slices, split the bitstream, and concatenate bitstream segments of the octree-coded geometry bitstream and the directly-coded geometry bitstream.

[0548] A metadata parser (41005) may provide information about slices and / or layer groups.

[0549] A slice selector (41012) can select one or more slices included in a bitstream.

[0550] The bitstream splitter (41014) can split a geometry bitstream. The geometry data can be encoded and / or directly coded based on an octree.

[0551] A bitstream segment concatenation (41016) can concatenate an octree-coded geometry bitstream and a direct-coded geometry bitstream according to their encoding types. For a layer group-based geometry bitstream, bitstream segments including multiple groups / subgroups related to a decoding area can be concatenated.

[0552] The geometry decoder (41006) can decode a geometry bitstream and output geometry data.

[0553] The attribute decoder (41008) can decode attribute data included in the selected slice.

[0554] The renderer (41009) can render point cloud data based on geometry data and / or attribute data.

[0555] Figure 42 illustrates a method for receiving point cloud data according to embodiments.

[0556] Figure 42 illustrates in more detail the operation of the sub-bitstream classifier (41010) illustrated in Figure 41.

[0557] The receiving device receives data in slice units, and the metadata parser transmits parameter set information such as SPS, GPS, APS, and TPS (e.g., information on segmented (separated) slices and / or information related to direct coding). Based on the transmitted information, it is possible to determine whether scalability is possible. If scalability is possible, the slice structure for scalable transmission is identified as shown in FIG. 42 (42011). First, the geometry slice structure can be identified based on information such as num_scalable_layers, scalable_layer_id, tree_depth_start, tree_depth_end, node_size, num_nodes, num_slices_in_scalable_layer, and slice_id transmitted via GPS.

[0558] If the value of the aligned_slice_structure_enabled_flag field is 1 (42017), the attribute slice structure can also be identified in the same way (for example, if the geometry is octree-based, the attribute is encoded based on scalable LoD or scalable RAHT, and the geometry / attribute slice pairs generated through the same slice partitioning have the same number of nodes for the same octree layer).

[0559] When the structure is the same, the range of geometry slice id is determined according to the target scalable layer, the range of attribute slice id is determined through slice_id_offset, and geometry / attribute slice is selected according to the determined range (42012-42014, 42018, 42019).

[0560] If aligned_slice_sturcutre_enabled_flag = 0, the attribute slice structure is separately identified based on information such as num_scalable_layers, scalable_layer_id, tree_depth_start, tree_depth_end, node_size, num_nodes, num_slices_in_scalable_layer, and slice_id transmitted through APS, and the range of attribute slice ids required according to the scalable purpose can be limited, and based on this, the required slice can be selected through each slice id before reconstruction (42020-42021, 42019). The geometry / attribute slice selected through the above process is transmitted as an input to the receiving device according to the embodiments.

[0561] The above explanation describes the decoding process according to the slice structure based on the scalable transmission or the scalable selection of the receiver. However, if scalable_transmission_enabled_flag is 0, the ranging geom / attr slice id process can be omitted and the entire slice can be selected, allowing it to be used in non-scalable processes as well. In this case, information about the preceding slice (e.g., a slice belonging to a higher layer or a slice specified via ref_slice_id) can be used through slice structure information conveyed through parameter sets such as SPS, GPS, APS, and TPS (e.g., information about segmented (separated) slices and / or information related to direct coding).

[0562] When different types of geometry bitstreams exist, all slices within the range for different bitstreams can be selected during the slice selection process. If different types of bitstreams are included in a single slice, each bitstream can be separated based on offset and length information, and the separated bitstreams can be rearranged according to the layer group order for decoding.

[0563] Fig. 43 illustrates a layer group-based point cloud data encoding method according to embodiments.

[0564] An encoder according to embodiments includes a flowchart in FIG. 43. When point cloud data is input, a layer group structure is constructed and related parameters are acquired. A reference relationship between subgroups is established based on the layer group structure (or already by external input). Encoding can be performed based on the layer group structure and the reference structure. For each subgroup / slice, whether it is used as a reference can be checked, and if so, context_reference_indication_flag can be set to 1. If not, context_reference_indication_flag can be set to 0. Whether it is used as a reference can be performed after encoding and can be obtained directly through the reference structure. If it is used as a reference, the number of times the slice / subgroup is used as a reference can be signaled as the number of subsequent data units (num_subsequenct_data_units). Additionally, if a slice / subgroup passes a specific list of slices / subgroups that are used as references, the subsequent subgroup list presence flag (subsequent_subgroup_list_present_flag) can be set to 1 and the subsequent data unit list can be passed as a layer-group index and a subgroup index. Parameters required for decoding can be included in the data unit header, and the encoded compressed bit stream can be included in the data unit to generate a bitstream for each slice, and this process can be performed for every data unit / slice / subgroup.

[0565] Figure 44 illustrates a layer group-based point cloud data decryption method according to embodiments.

[0566] The decryption method of Fig. 44 can follow the reverse process of the encoding method of Fig. 43.

[0567] The decoder can prepare for decoding by analyzing the data unit header for each slice. At this time, the context state used for decoding can be retrieved from the context buffer through the reference layer group ID (ref_layer_group_id) and reference subgroup ID (ref_subgroup_id). The decoder is initialized based on the retrieved context state and then decoding is performed. Whether to store the new context state generated during the decoding process can be determined by the context_reference_indication_flag included in the data unit header. If it is used in the decoding of subsequent slices / subgroups / data units, the context_reference_indication_flag is signaled as 1. In this case, the target number of subsequent data units can be set to the number of subsequent data units (num_subsequent_data_units) to manage the memory of the context state. Additionally, if subsequent_subgroup_list_present_flag = 1, the layer group index and subgroup index of subsequent data units can be stored in the list of subsequent data units.

[0568] For a used context state, the context state counter and the list of used data units can be updated. At this time, if the target number of subsequent data units of the context state and the counter are the same, or the number of subsequent data units in the given list (list of subsequent data units (list_given)) and the updated list of used data units in the updated list (updated list of used data units (lilst_updated)) are the same, the context state can be freed from the counter buffer.

[0569] The context buffer management method can be applied equally to both the decoder and the encoder. Furthermore, it can be applied not only to slices based on layer-group slicing, but also to cases where context buffers are referenced between slices within a regular frame or between frames.

[0570] Figure 45 illustrates a context buffer management method according to embodiments.

[0571] In Fine Granularity Slicing (FGS), context inheritance between slices is used to mitigate coding losses caused by discontinuities between adjacent nodes or coding layers. However, as the number of slices or layer groups increases, the number of context states in memory also increases. To help the decoder manage the context buffer, an indication of future use of the current context by subsequent slices is signaled.

[0572] Referring to Fig. 45, the context buffer management method of the current layer group slicing method is shown. When the bitstream of a slice is decoded and the context reference indication flag (context_reference_indication_flag) is enabled, the context state of the decoder output is stored in the context buffer as shown in Fig. 45(a). Using context inheritance, the context state of the next slice can be initialized with one of the stored context states of the previous subgroup indicated by the reference layer group ID (ref_layer_group_id) and the reference subgroup ID (ref_subgroup_id) (see Fig. 45(b)). In Fig. 45(c), the context state of the slice belonging to the last layer group is initialized by the stored context state of the upper slice. However, since the context_reference_indication_flag is disabled, the output context state is not stored in the context buffer.

[0573] Using the context_reference_indication_flag allows you to reduce the overall size of the context buffer by selecting context states known to be used in the next slice. However, this has the limitation that the decoder cannot know when each stored context will be released. Therefore, all context states must be stored in the buffer until all subgroups have been decoded.

[0574] Referring to Fig. 45(a), the first slice, FGS 0, represents subgroup 0 of layer group 0 of point cloud data. When encoding (or decoding) from FGS 0, the context state (0, 0) for FGS 0 is stored in the context buffer for subsequent FGSs.

[0575] Referring to Fig. 45(b), the third slice, FGS 2, can be sequentially encoded (or decoded). FGS 2 represents subgroup 1 of layer group 1 of point cloud data. FGS 2 may be a subgroup belonging to FGS 0 (parent-child relationship). Therefore, FGS 2 can be efficiently encoded (or decoded) by referencing the context state (0, 0) for FGS 0 from the context buffer. Then, the context state (1, 1) is stored in the context buffer for the subsequent slice FGS.

[0576] The method according to the embodiments can solve this problem as follows through a mechanism for releasing context state.

[0577] Figure 46 illustrates a context buffer management method according to embodiments.

[0578] The method according to the embodiments includes a method of indicating the number of subgroups that reference the current subgroup so that the decoder knows when to release the stored context state.

[0579] Figure 46 illustrates how to release the context buffer using the proposed signal. Compared to Figure 45, the context buffer has two additional columns: one for indicating the number of subsequent subgroups referencing the current subgroup, and one for calculating the number of subgroups that have already used the context state in subgroup decoding. When the context_reference_indication_flag is enabled, the number of subsequent subgroups (num_subsequent_subgroups) is signaled and the corresponding number is stored in the context state, as shown in Figure 46(a). As shown in Figure 46(b), three context states are stored in the context buffer, which are known to be referenced N or 1 times. The context state of FGS 0 (0, 0) is referenced twice by FGS 1 (1, 0) and FGS 2 (1, 1), so the counter value for context state (0, 0) is 2. As shown in Figure 46(c), the context state of (1, 1) is released after being used by FGS N+2 (2, 1). Context states (0, 0) and (1, 0) are released in advance because there are no subsequent subgroups referencing them. Releasing a context state means deleting the context state information from the context buffer memory.

[0580] Figure 47 illustrates a context buffer management method according to embodiments.

[0581] The proposed method can be equally effective when using different orders for FGS (which can be simply referred to as slices, sub-slices, etc.). Referring to Fig. 47, the method according to the embodiments is also applicable to the case of depth-first ordering. For comparison with the breadth-first order case of Fig. 46, the names of each slice are the same, and the transmission order is changed from FGS 0, FGS 1, FGS 2, FGS 3, ... to FGS 0, FGS 1, FGS N+1, FGS 2. As shown in Fig. 47(b), when the decoding of FGS2 is completed, the output context state (1, 0) is stored in the context buffer and the number of subsequent subgroups is stored. When the next slice FGS N+2 is decoded, the context state is initialized by the context state (1, 1) and the corresponding counter in the context buffer is increased by 1. If the number of subsequent subgroups is the same, the context state (1, 1) can be released from this point on. In this example, the maximum number of context states in the context buffer is 2, which is the number of layer groups minus 1.

[0582] At this time, the size of the context buffer can be predicted in advance at the receiver. For example, if there are N layer groups, and the size of the subgroup within the nth layer group is S[n], we can consider a case where the parent subgroup (or upper subgroup) is referenced.

[0583] In this case, the number of context states that need to be stored in memory can be estimated as follows. That is, since the maximum number (N-1) will not be referenced subsequently, the addition process is performed only up to N-2.

[0584]

[0585] As an extreme opposite case, if we consider the case where we reference the first slice / subgroup, then the number of context states that need to be stored in memory can be estimated as follows:

[0586] (number of subgroups in the root layer - group) = 1

[0587] For example, the number of subgroups within a root layer group can be 1.

[0588] For example, the number of subgroups within a root layer group can be 1.

[0589] The case where the parent subgroup is referenced may be the case where context state is most used, while the case where context state is least used may be the case where the first slice / subgroup is referenced. Therefore, when using layer group slicing with different reference relationships, it is possible to consider a position between the maximum and minimum values.

[0590] Using the method according to the embodiments may require space to store fewer context states than dynamically freeing memory. For example, if FGS generated by layer group slicing are generated and / or passed based on breadth-first order and only reference parent subgroups, the context states belonging to the parent layer group can be freed when coding for a layer group is completed. Therefore, the number of context states that need to be stored in memory can be estimated as follows.

[0591] MAX(S[0], S[1], ..., S[N-2])

[0592] If the FGS generated by layer group slicing is generated / transferred in depth-first order, the context memory of the parent subgroup can be released (deleted) when the coding of the child subgroup is completed by the method according to the embodiments. In this case, only the context of the parent subgroup with remaining children needs to be stored, and since leaf layer groups are excluded, the number of context states that need to be stored in memory can be estimated as follows.

[0593] N-1

[0594] If the receiver needs to estimate the memory size for storing the context buffer, it can pass related information (slice coding order type, depth first / breadth first, number of layer-groups, number of subgroups belonging to each layer-group, context reference method, parent reference / root reference, etc.) and estimate the number of context states as in the method presented above.

[0595] In the following, based on the context memory management mechanism according to the embodiments, new signaling information, the number of subsequent data units (num_subsequent_data_units), is generated in the geometry data unit header and the dependent geometry data unit header.

[0596] An encoder according to embodiments encodes point cloud data and generates related signaling information. It then generates and transmits a bitstream containing the encoded point cloud data and parameter information. In reverse, a decoder according to embodiments receives the bitstream, parses the parameter information contained in the bitstream, and decodes the point cloud data based on the parameter information. Figures 48 to 50 illustrate the syntax of parameter information contained in the bitstream.

[0597] Figure 48 shows a geometry data unit header syntax according to embodiments.

[0598] Figure 49 illustrates a dependent geometry data unit header syntax according to embodiments.

[0599] Figure 50 illustrates attribute data unit header syntax according to embodiments.

[0600] Figure 51 illustrates a dependent attribute data unit header syntax according to embodiments.

[0601] The number of subsequent data units (num_subsequent_data_units) indicates the number of subsequent dependent data units that reference the current data unit or dependent data unit. The data unit may be a slice. A slice may be an FGS for a subgroup within a layer group according to embodiments.

[0602] Geometry Parameter Set ID (dgsh_geometry_parameter_set_id): This is the geometry parameter set identifier. It may be information that identifies the parameter set for a dependent geometry data unit.

[0603] Slice ID (dgsh_slice_id): This is the slice identifier. It may be the slice identifier associated with a dependent geometry data unit.

[0604] Layer Group ID (layer_group_id): This is the layer group identifier. It can be the identifier of the layer group to which the dependent geometry data unit is associated.

[0605] Subgroup ID (subgroup_id): This is the subgroup identifier. It can be the identifier of a subgroup associated with a dependent geometry data unit.

[0606] Subgroup bounding box location (subgroup_bbox_origin[i]): Indicates the origin location of the subgroup bounding box.

[0607] Subgroup bounding box size (subgroup_bbox_size[i]): Indicates the size of the subgroup bounding box.

[0608] Reference Layer Group ID (ref_layer_group_id): This is the reference layer group identifier. It can be the identifier of the layer group referenced by the dependent geometry data unit.

[0609] Reference subgroup ID (ref_subgroup_id): This is the reference subgroup identifier. It can be the identifier of a subgroup referenced by the layer group for the layer group identifier.

[0610] context_reference_indication_flag: A flag indicating whether or not the context is referenced.

[0611] Number of references (num_referenced): Indicates the number of references.

[0612] Figure 52 shows the effects according to embodiments.

[0613] Figure 53 shows the effects according to embodiments.

[0614] The effects of embodiments on the breadth-first and depth-first ordering of fine-grained slices (FGS) by setting the encoder configuration "length1stSubgroupSearch" are as shown in Fig. 52.

[0615] As shown in Figures 52 and 53, additional signaling does not affect coding performance in terms of coding gain and computational complexity. When the decoder's Resident Set Size (RSS) is estimated, the average RSS for breadth-first ordering is reduced to 94% under both lossless and lossy conditions. Using depth-first ordering further reduces the decoder's RSS, resulting in a 90% RSS under both lossless and lossy conditions.

[0616] Embodiments include a method for managing a context buffer by freeing (deleting) context states no longer in use from the context buffer. To this end, the number of subsequent subgroups referencing the current subgroup is signaled. According to embodiments, this can effectively reduce memory usage.

[0617] The method and device according to the embodiments can control the context memory by considering partial decoding.

[0618] The context memory control method described in Fig. 45 can efficiently manage the context buffer in a situation where the entire slice is decoded for a bitstream composed of multiple slices. However, in the case of partial decoding (when only some slices are decoded when there is a region of interest or a resolution of interest), which is one of the main use cases of layer-group slicing, the reference count (num_subsequent_data_units) transmitted by the encoder may not be fully filled.

[0619] For example, given a layer group structure divided into three layer groups, the decoder may decide not to use the last layer group. In this case, knowing the number of references in the second layer group eliminates the need to store context in the context buffer for decoding the last layer group.

[0620] To achieve this, the decoder can release context memory after a specified number of times by signaling the number of times the context is used per data unit. The number of times the context is used for each data unit can have the following relationship with the number of times the entire context is used:

[0621] Subsequent layer-groups represent layer groups that contain subgroups that reference the context of the current data unit, and the number of subsequent data units within a layer group (num_sdu_per_layer_group) can represent the number of times the subgroups belonging to each layer group reference the context of the current subgroup.

[0622] num_subsquent_data_units= num_sud_per_layer_group[i]

[0623] Based on the above method, context memory can be early released in partial decoding situations through various methods as follows.

[0624] The method and device according to the embodiments can transmit the entire context reference structure as signaling information (parameter information, e.g., sequence parameter set (SPS)). Information about the layer group structure and the actual relationship that allows the decoder to identify the reference structure, such as the reference subgroup ID and the number of subsequent subgroups, can be transmitted from the encoder to the decoder as signaling information (parameter information, e.g., sequence parameter set (SPS). The decoder can early release (delete) the context from the memory in case of partial decoding based on the identified entire reference structure. However, in some cases, the SPS may become bloated and inefficient because the entire structure must be signaled.

[0625] The method and device according to the embodiments can directly transmit subsequent subgroup IDs as signaling information (e.g., information within a data unit header). The context reference structure can be transmitted on a per-data unit basis. The decoder can check whether a request is coming from the corresponding subgroup ID in the buffer, and if all the corresponding contexts are used in the subgroups used in partial decoding, it can early release (delete) them from memory.

[0626] The method and device according to the embodiments can divide the number of subsequent subgroups and transmit it from the encoder to the decoder as signaling information (e.g., information in the data unit header). For example, for the number of subsequent subgroups N, the number of subgroups referenced by each layer group can be divided and transmitted, such as N = N1 (the number referenced in layer-group 1) + N2 (the number referenced in layer-group 2). A receiver (decoder) that does not decode layer-group 2 can early release (delete) the context from the memory (buffer) when the context has been used N1 times. In the case of full decoding, the context can be released from the memory after it has been used N1 + N2 times.

[0627] Below, we describe how to convey the number of times each data unit is referenced within each layer group and the subgroup ID in the examples. When a parent subgroup contains multiple child subgroups, adding bounding box information for the referencing subgroups allows for more accurate conveyance of the number of context references for ROI-based partial decoding, enabling the decoder to release context memory at the correct time.

[0628] The encoding method / device according to the embodiments (the transmitting device (10000) of FIG. 1, the point cloud video encoder (10002), the transmitter (10003), the acquisition-encoding-transmission (20000-20001-20002) of FIG. 2, the encoder of FIG. 11, the layer group-based encoding of FIG. 12 to FIG. 22, the context buffer memory control of FIG. 23 to FIG. 34, the bitstream / parameter generation of FIG. 35 to FIG. 39a, FIG. 39b, the encoder of FIG. 40, the encoding of FIG. 43, the context buffer memory control of FIG. 45 to FIG. 47 and FIG. 59 to FIG. 60, the parameter generation of FIG. 48 to FIG. 51, FIG. 54 to FIG. 58, and FIG. 61 to FIG. 63, the encoder of FIG. 64 to FIG. 67, the encoding method of FIG. 68) can encode point cloud data, generate parameter information, and generate and transmit a bitstream including the syntax of FIG. 54 to FIG. 58 and FIG. 61 to FIG. 63. there is.

[0629] The decoding method and device according to the embodiments (receiving device (10004), receiver (10005), point cloud video decoder (10006) of FIG. 1, transmission-decoding-rendering (20002-20003-20004) of FIG. 2, decoder of FIG. 7, receiving device of FIG. 9, device of FIG. 10, decoder of FIG. 11, layer group-based decoding of FIGS. 12 to 22, context buffer memory control of FIGS. 23 to 34, bitstream / parameter parsing of FIGS. 35 to 39a, bitstream / parameter parsing of FIG. 39b, decoder of FIG. 41, decoding of FIG. 42, decoding of FIG. 44, context buffer control of FIGS. 45 to 47, parameter generation decoder of FIGS. 48 to 51, 54 to 58, and parameter generation decoder of FIGS. 59 to 60, context buffer control of FIGS. 64 to 67, decoder of FIG. 69 decoding method) are configured to: Point cloud data can be decoded based on the syntax of FIGS. 54 to 58 and FIGS. 61 to 63 included. Hereinafter, the syntax and semantics of the information included in the bitstream will be described with reference to each drawing.

[0630] Figure 54 shows the sequence parameter set syntax according to embodiments.

[0631] Layer Group Enabled Flag (layer_group_enabled_flag): If this value is 1, it indicates that the geometry bitstream of the slice is contained in multiple slices that match the coding layer group or subgroup. If layer_group_enabled_flag is 0, it indicates that the geometry bitstream is contained in a single slice.

[0632] Number of Layer Groups (num_layer_groups_minus1): Adding 1 to this value indicates the number of layer groups representing groups of contiguous tree layers (hierarchies) that are part of the geometry coding tree structure. num_layer_groups_minus1 ranges from 0 to the number of coding tree layers.

[0633] Layer Group ID (layer_group_id): Indicates the layer group indicator of the slice. The range of layer_group_id is 0 to num_layer_groups_minus1.

[0634] Number of layers (num_layers_minus1): Adding 1 to this value indicates the number of coding layers included in the ith layer group. The total number of layer groups can be derived by adding all (num_layers_minus1[i] + 1) to num_layer_groups_minus1 when i is 0.

[0635] If the subgroup enable flag (subgroup_enabled_flag) is 1, it indicates that the ith layer group is divided into two or more subgroups where the set of points in the subgroups of the layer group is the same as the set of points in the layer group. If the subgroup_enabled_flag of the ith layer group is 1, then the subgroup_enabled_flag of the jth layer group is equal to 1 when j is greater than or equal to i. If the subgroup_enabled_flag is 0, it indicates that the current layer group is not divided into multiple subgroups but is contained in a single slice.

[0636] Subgroup bounding box origin (subgroup_bbox_origin_bits_minus1): Adding 1 to this value indicates the bit length of the syntax element subgroup_bbox_origin.

[0637] Subgroup bounding box size (subgroup_bbox_size_bits_minus1): Adding 1 to this value gives the length in bits of the syntax element subgroup_bbox_size.

[0638] Number of subgroups (num_subgroups_minus1): Adding 1 to this value indicates the number of subgroups in the i-th layer group.

[0639] Number of subsequent data units (num_subsequent_data_units): Indicates the number of subsequent dependent data units that reference the ith data unit or the ith dependent data unit.

[0640] Subsequently_data_unit_id: Indicates the index (or ID) of the subsequent data unit referencing the data unit of the i-th layer group and the j-th subgroup.

[0641] Figure 55 illustrates a geometry data unit header syntax according to embodiments.

[0642] Number of subsequent data units (num_subsequent_data_units): Indicates the number of subsequent dependent data units that reference the current data unit or dependent data unit.

[0643] Number of subsequent data units per layer group present flag (num_sdu_per_layer_group_present_flag): If this value is 1, it indicates that each layer group has a number of subsequent data units. If num_sdu_per_layer_group_present_flag is 0, each layer group does not have a number of subsequent data units.

[0644] Successor Data Unit Presence Flag (sdu_present_flag): If this value is 1, it indicates that the successor data unit of the current data unit is in the ith layer group. If sdu_present_flag is 0, the successor data unit of the current data unit is not in the ith layer group.

[0645] Number of subsequent data units per layer group (num_sdu_per_layer_group): Indicates the number of subsequent dependent data units in the i-th layer group that references the current data unit or dependent data unit.

[0646] subsequent_data_unit_id: Indicates the index (or ID) of the subsequent data unit that references the current data unit or dependent data unit.

[0647] Figure 56 illustrates a dependent geometry data unit header syntax according to embodiments.

[0648] Figure 57 illustrates attribute data unit header syntax according to embodiments.

[0649] Figure 58 illustrates a dependent attribute data unit header syntax according to embodiments.

[0650] The definitions of the syntax elements included in FIGS. 56 to 58 also follow the definitions described above. In this way, information related to layer groups, subgroups, and / or subsequent data units within a bitstream can be transmitted at various locations.

[0651] Figure 59 illustrates a context buffer management method according to embodiments.

[0652] Fine granularity slicing (FGS) can mitigate coding loss caused by discontinuities between adjacent nodes or coding layers by leveraging context inheritance between slices. However, increasing the number of slices or layer groups can increase the number of context states in memory.

[0653] As shown in Figure 59, signaling information can be transmitted to enable the decoder to later use the current context in subsequent slices to help manage the context buffer. This can reduce the overall size of the context buffer by storing context states known to be used in subsequent slices.

[0654] Additionally, the stored context state can be released using the number of subgroups referencing the current subgroup. However, when a partial layer or partial region of the bitstream is decoded, the stored context may not be released because subsequent subgroups outside the region of interest (ROI) cannot be calculated. Consequently, the number of coded subsequent subgroups cannot reach the signaled subgroup.

[0655] Figure 60 illustrates a context buffer management method according to embodiments.

[0656] The method according to the embodiments can solve the aforementioned issue by managing a list of subsequent subgroups overlapping with the ROI for each layer group to consider the partial decoding case, as shown in FIG. 60.

[0657] The method according to the embodiments can release the context buffer using the method proposed in FIG. 60. Referring to FIG. 60, the context buffer contains two lists. The first list is a list of subsequent subgroups referencing the current subgroup, and the second list is a list of coded subgroups related to the context state of the current subgroup. The first list can be provided for each data unit, and the second list can be updated by the decoder.

[0658] When a ROI for partial region decoding is provided, the subgroup regions in the list are compared with the ROI, and subgroups with overlapping ROI regions are maintained in the list. Additionally, when the number of layer groups skipped in partial layer group decoding is set, a list of subsequent subgroups within the non-skipped layer groups is maintained in the list.

[0659] In Fig. 60(a), for example, the ROI is indicated by the line (6000) on the FGSs with one skipped layer group. Using this information, the FGS decoder decodes FGS 0 for layer group 0, FGS 1 and 2 for layer group 1, and decodes nothing for layer group 2. Based on this, a selected list of subsequent subgroups ('List A') is generated as a subset of the provided list of subsequent subgroups.

[0660] Referring to Fig. 60(b), when FGS 1 is decoded, the context state is initialized to the saved context state of FGS 0 (context state (0, 0)) and updated with the list of coded subsequent subgroups ('list B').

[0661] Referring to Fig. 60(c), when FGS 2 is decoded, list B is updated to FGS 2 (1, 1), and since list B and list A are identical, the context state (0, 0) can be released under the condition that the decoder does not decode the subgroup in the ROI.

[0662] The first list (List A) is a list of subsequent subgroups referencing the current subgroup, and the second list (List B) is a list of related coded subgroups using the context state of the current subgroup. While decoding the FGS within the layer group and subgroup related to the ROI for partial decoding, List B is updated according to the coded subgroup, and when the subsequent subgroup list (List A) and the updated List B are identical, partial decoding related to the ROI is completed, so there is no need to store the context state stored in the context buffer. Therefore, the decoder can efficiently control the context buffer by releasing the context buffer.

[0663] The encoding / decoding method according to the embodiments may store a context state in a buffer and store a list of subsequent subgroups in the buffer if the context reference indication flag (context_reference_indication_flag) is true. When encoding (or decoding) FGS 0, context (0, 0) is stored in the buffer, and subsequent subgroups (FGS (1, 0), FGS (1, 1) to FSG (1, N-1)) are stored in the buffer. When encoding (or decoding) FGS 1 (1, 0), if the reference layer group ID (ref_layer_group_id) is 0 and the reference subgroup ID (ref_subgroup_id) is 0, the context state (0, 0) stored in the context buffer is loaded. If the context reference indication flag (context_reference_inidcation_flag), ROI overlapping area, and skipped layer group are all true, the context state (1, 0) is not stored in the buffer. When encoding (or decoding) FGS 2(1, 1), if the reference layer group ID is 0 and the reference subgroup ID is 0, the context state (0, 0) stored in the buffer is loaded. If the context reference indication flag (context_reference_inidcation_flag), ROI overlapping region, and skipped layer group are all true, the context state (1, 1) is not stored in the buffer.

[0664] The encoding method according to the embodiments can generate subgroup indices and bounding box information for each layer group as signaling information (parameter information) in the data unit header based on the proposed context memory management mechanism, and transmit them by including them in the bitstream. The decoding method according to the embodiments can decode point cloud data based on parameter information related to context memory management.

[0665] Figure 61 shows the sequence parameter set syntax according to embodiments.

[0666] Figure 61 shows the parameter set syntax included in the bitstream.

[0667] If subsequently__subgroups_info_present_flag is 1, it indicates that additional information about subsequent subgroups is transmitted. If subsequently__subgroups_info_present_flag is 0, it indicates that additional information about subsequent subgroups is not transmitted.

[0668] Figure 62 illustrates a geometry data unit header syntax according to embodiments.

[0669] Figure 62 shows the geometry data unit header syntax included in the bitstream.

[0670] Number of subsequent subgroups (num_subsequent_subgroups): Indicates the number of subsequent dependent data units that reference the current data unit or dependent data unit.

[0671] subsequently_subgroup_id: Indicates the subgroup index of the subsequent dependent data unit of the i-th layer group that references the current data unit or dependent data unit.

[0672] subsequent_subgroup_bbox_origin: Indicates the origin of the subgroup bounding box of the subsequent subgroup that refers to the context state of the current subgroup.

[0673] subsequent_subgroup_bbox_size: Indicates the size of the subgroup bounding box of the subsequent subgroup that refers to the context state of the current subgroup.

[0674] Figure 63 illustrates a dependent geometry data unit header syntax according to embodiments.

[0675] Figure 63 shows the dependent geometry data unit header syntax included in the bitstream.

[0676] Geometry parameter set ID (dgsh_geometry_parameter_set_id): Indicates the geometry parameter set ID referenced by the dependent geometry data unit header.

[0677] Slice ID (dgsh_slice_id): Indicates the slice ID of the geometry data unit.

[0678] Layer group ID (layer_group_id): Indicates the layer group ID of the geometry data unit.

[0679] Subgroup ID (subgroup_id): Indicates the subgroup ID of the geometry data unit.

[0680] Subgroup bounding box origin (subgroup_bbox_origin[i]): Indicates the origin of the bounding box belonging to a subgroup of the geometry data unit.

[0681] Subgroup bounding box size (subgroup_bbox_size[i]): Indicates the size of the bounding box belonging to a subgroup of the geometry data unit.

[0682] Reference layer group ID (ref_layer_group_id): Indicates the ID of the layer group referenced by the geometry data unit.

[0683] Reference subgroup ID (ref_subgroup_id): Indicates the ID of the subgroup referenced by the geometry data unit.

[0684] context_reference_indication_flag: A flag indicating whether a context reference exists for the geometry data unit.

[0685] Number of subsequent subgroups (num_subsequent_subgroups): Indicates the number of subsequent dependent data units that reference the current data unit or dependent data unit.

[0686] subsequently_subgroup_id: Indicates the subgroup index of the subsequent dependent data unit of the i-th layer group that references the current data unit or dependent data unit.

[0687] subsequent_subgroup_bbox_origin: Indicates the origin of the subgroup bounding box of the subsequent subgroup that refers to the context state of the current subgroup.

[0688] subsequent_subgroup_bbox_size: Indicates the size of the subgroup bounding box of the subsequent subgroup that refers to the context state of the current subgroup.

[0689] Figures 64 and 65 illustrate point cloud data transmission and reception devices / methods according to embodiments.

[0690] The embodiments include a method for dividing and transmitting compressed data based on a standard for point cloud data. When layered coding is used, compressed data can be divided and transmitted according to layers, which increases the storage and transmission efficiency of the transmitter.

[0691] Fig. 64 illustrates an embodiment of a case where the geometry and attributes of point cloud data are compressed and provided as a service. In a PCC-based service, the compression ratio or the number of data can be adjusted and transmitted depending on the receiver performance or transmission environment. However, if point cloud data is bundled in units of one slice, and if the receiver performance or transmission environment changes, 1) a bitstream suitable for each environment is converted in advance and stored separately and selected at the time of transmission, or 2) a process of conversion (transcoding) is required prior to transmission. In this case, if the number of receiver environments to be supported increases or the transmission environment changes frequently, storage space issues or delays due to conversion may become a problem.

[0692] Referring to Figure 65, when compressed data is divided and transmitted according to layers, there is an advantage in that only the necessary portions of pre-compressed data can be selectively transmitted at the bitstream stage without a separate conversion process. This is efficient in terms of storage space, as only one storage space is required per stream, and efficient transmission is also possible in terms of bandwidth, as only the necessary layers are selectively transmitted before transmission (bitstream selector).

[0693] An encoder (4601) according to embodiments can select a required portion from a bitstream (Bitstream selector). Furthermore, the selected bitstream can be transmitted to a decoder (4602) according to embodiments. The decoder (4602) according to embodiments can restore partial geometry and partial attributes from the received bitstream.

[0694] Fig. 66 shows a point cloud data transmission / reception device / method according to embodiments.

[0695] The embodiments include a method for dividing compressed data for a point cloud and transmitting it according to certain criteria. Using layered coding, compressed data can be divided and transmitted according to each layer, increasing the efficiency of the receiver.

[0696] Figure 66 illustrates the operation of the transmitter and receiver when transmitting point cloud data composed of layers. When transmitting information capable of restoring the entire point cloud data, regardless of the receiver's performance, the receiver requires a process (data selection or sub-sampling) to restore the point cloud data through decoding and then select only the data corresponding to the required layers. In this case, since the transmitted bitstream has already been decoded, a receiver targeting low latency may experience delays or, depending on the receiver's performance, may not be able to decode.

[0697] In the embodiments, when the bitstream is divided into slice units and transmitted, the receiver can selectively transmit the bitstream to the decoder according to the decoder performance or the density of point cloud data to be represented according to the application field. In this case, since the selection is made before decoding, the decoder efficiency is increased, and there is an advantage in that decoders of various performances can be supported. That is, the transmission / reception device according to the embodiments can select and transmit / receive a bitstream, and support decoders of various performances by restoring the selected bitstream.

[0698] 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 individual 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.

[0699] The operations according to the embodiments described above may be performed by a transmitting device and / or a receiving device according to the embodiments. The transmitting / receiving device may include a transmitting / receiving unit for transmitting and receiving media data, a memory for storing instructions (program code, algorithm, flowchart, and / or data) for a process according to the embodiments, and a processor for controlling the operations of the transmitting / receiving device.

[0700] The processor may be referred to as a controller or the like, and may correspond to, for example, hardware, software, and / or a combination thereof. The operations according to the above-described embodiments may be performed by the processor. Furthermore, the processor may be implemented as an encoder / decoder or the like for the operations of the above-described embodiments.

[0701] Fig. 67 shows a point cloud data transmission / reception device / method according to embodiments.

[0702] Referring to Fig. 67, multi-resolution ROIs can be supported by the scalability and spatial accessibility of hierarchical slicing. In Fig. 67, the encoder (4801) can generate bitstream slices of spatial subgroups of each layer group or octree layer-groups. Upon request, a slice matching the ROI of each resolution is selected and transmitted. The overall bitstream size is reduced compared to a tile-based approach because the bitstream does not contain details other than the requested ROI. At the receiving end, the decoder (4802) can combine the slices to produce three outputs: 1) a high-level view output from layer group slice 1, 2) a mid-level view output from layer group slice 1 and selected subgroups of layer group 2, and 3) a low-level view output with good detail from layer group 1 and selected subgroups of layer groups 2 and 3. Since the outputs can be generated progressively, the receiver can provide a viewing experience such as zooming in which the resolution progressively increases from the high-level view to the low-level view.

[0703] The encoder (4801) is a point cloud encoder according to embodiments, and may correspond to a geometry encoder and an attribute encoder. The encoder may slice point cloud data based on a layer group (or groups). A layer may be referred to as a tree depth, a LOD level, etc. The depth of a geometry octree and / or the level of an attribute LOD layer may be divided into layer groups (or subgroups).

[0704] The slice selector, in conjunction with the encoder (4801), can select a split slice (or sub-slice) to selectively transmit partially, such as layer group 1 to layer group 3.

[0705] The decoder (4802) can decode point cloud data transmitted selectively and partially. For example, the high-level view can be decoded based on layer group 1 (high depth / layer / level or index 0, closer to the root). Thereafter, the mid-level view can be decoded based on layer group 1 and layer group 2, with a slightly higher depth / level index than layer group 1 alone. The low-level view can be decoded based on layer groups 1 to 3.

[0706] Figure 68 shows an encoding method according to embodiments.

[0707] The encoding method according to the embodiments includes the operations described in the transmitting device (10000) of FIG. 1, the point cloud video encoder (10002), the transmitter (10003), the acquisition-encoding-transmission (20000-20001-20002) of FIG. 2, the encoder of FIG. 11, the layer group-based encoding of FIGS. 12 to 22, the context buffer memory control of FIGS. 23 to 34, the bitstream / parameter generation of FIGS. 35 to 39a, and 39b, the encoder of FIG. 40, the encoding of FIG. 43, the context buffer memory control of FIGS. 45 to 47 and FIGS. 59 to 60, the parameter generation of FIGS. 48 to 51, FIGS. 54 to 58, and FIGS. 61 to 63, the encoder of FIGS. 64 to 67, etc.

[0708] The encoding method according to the embodiments may include a step of encoding point cloud data (S6800); and a step of transmitting a bitstream including point cloud data (S6810).

[0709] Referring to FIG. 1, an encoding method may be performed by an encoding device. The encoding device includes a memory; and at least one processor connected to the memory; and the at least one processor may be configured to: encode point cloud data; and transmit a bitstream including the point cloud data.

[0710] Embodiments further include a computer-readable storage medium storing a bitstream generated by the method of FIG. 68.

[0711] Embodiments further include a method comprising: obtaining a bitstream for point cloud data, the bitstream being generated based on a step of encoding geometry data of the point cloud data; and a step of encoding attribute data of the point cloud data; and transmitting data including the bitstream.

[0712] Figure 69 shows a decryption method according to embodiments.

[0713] The decoding method according to the embodiments includes the operations described in the receiving device (10004), the receiver (10005), the point cloud video decoder (10006) of FIG. 1, the transmission-decoding-rendering (20002-20003-20004) of FIG. 2, the decoder of FIG. 7, the receiving device of FIG. 9, the device of FIG. 10, the decoder of FIG. 11, the layer group-based decoding of FIGS. 12 to 22, the context buffer memory control of FIGS. 23 to 34, the bitstream / parameter parsing of FIGS. 35 to 39a, and 39b, the decoder of FIG. 41, the decoding of FIGS. 42 and 44, the context buffer control of FIGS. 45 to 47, the parameter generation decoder of FIGS. 48 to 51, 54 to 58, and 61 to 63, the context buffer control of FIGS. 59 to 60, the decoder of FIGS. 64 to 67, etc.

[0714] A decoding method according to embodiments may include a step of receiving a bitstream including point cloud data (S6900); and a step of decoding point cloud data (S6910).

[0715] Referring to FIG. 44 together, with respect to context-based decoding, the step of decoding point cloud data (S6910) includes: a step of decoding geometry data of point cloud data, a step of decoding attribute data of point cloud data, and the step of decoding geometry data further includes: decoding the geometry data included in the data unit based on a header of the data unit including the geometry data, and storing the context in a buffer based on context reference indication information included in a bitstream, and the step of decoding attribute data further includes: decoding the attribute data included in the data unit based on a header of the data unit including the attribute data, and storing the context in a buffer based on context reference indication information included in a bitstream.

[0716] Referring to FIG. 54 together, in relation to an SPS including layer_group_enabled_flag, num_layer_groups_minus1, layer_group_id, num_layers_minus1, subgroup_enabled_flag, num_subgroups_minus1, num_subsequent_data_units, etc., a bitstream may include a sequence parameter set, and the sequence parameter set may include at least one of information indicating whether the geometry data is included in a plurality of slices and matches a layer group or at least one subgroup of the layer group, information indicating the number of layer groups, information indicating an ID of the layer group, information indicating the number of layers in the layer group, information indicating whether the layer group is divided into a plurality of subgroups, information indicating the number of subgroups included in the layer group, information indicating the number of subsequent dependent data units referencing a data unit or a dependent data unit, or information indicating an ID of a subsequent data unit referencing a data unit of the layer group and a subgroup.

[0717] Referring to FIGS. 55 and 56 together, with respect to a geometry data unit header and a dependent geometry data unit header including num_subsequent_data_units, num_sdu_per_layer_group, subsequent_data_unit_id, etc., a bitstream includes a geometry data unit, and a header of a geometry data unit may include at least one of: information indicating the number of subsequent dependent data units referencing the data unit or the dependent data unit, information indicating the number of subsequent dependent data units within a layer group referencing the data unit or the dependent data unit, or information indicating an ID of a subsequent data unit referencing the data unit or the dependent data unit.

[0718] Referring to FIGS. 56, 57, and 58 together, with respect to a dependent geometry data unit header, an attribute data unit header, and a dependent attribute data unit header including num_subsequent_data_units, num_sdu_per_layer_group_present_flag, num_sdu_per_layer_group[i], subsequent_data_unit_id[i][j], etc., the bitstream further includes a dependent geometry data unit, an attribute data unit, or a dependent attribute data unit, and the header of the dependent geometry data unit, the header of the attribute data unit, or the header of the dependent attribute data unit may include at least one of: information indicating the number of subsequent dependent data units referencing the data unit or the dependent data unit, information indicating the number of subsequent dependent data units within the layer group referencing the data unit or the dependent data unit, or information indicating an ID of a subsequent data unit referencing the data unit or the dependent data unit.

[0719] Referring to FIGS. 21 and 59 together, in point cloud data encoded and decoded in the form of an FGS, with respect to a context buffer management scheme, a bitstream includes at least one FSG (Fine Granularity Slice) including point cloud data, and at least one FGS matches a layer group and a subgroup of the layer group, and the step of decoding the point cloud data includes: decoding a first FGS, storing a context for the first FGS in a buffer, storing the number of subgroups subsequent to the first FGS in the buffer, loading the context for the first FGS from the buffer when decoding a second FGS subsequent to the first FGS, increasing a value of a counter in the buffer, storing the number of subgroups subsequent to the second FGS in the buffer, loading the context for the second FGS from the buffer when decoding a third FGS subsequent to the second FGS, increasing a value of a counter in the buffer, and releasing the context memory of the buffer when the value of the counter is equal to the number of subgroups subsequent to the first FGS.

[0720] Referring also to FIG. 60, with respect to a method for managing a context buffer for partial encoding or partial decoding such as ROI, a bitstream includes at least one FSG (Fine Granularity Slice) including point cloud data, and at least one FGS matches a layer group and a subgroup of the layer group, and a step of decoding the point cloud data may include: when decoding a first FGS, a second FGS, and a third FGS related to partial decoding, decoding the first FGS, storing a context for the first FGS in a buffer, storing a list of subgroups subsequent to the first FGS in the buffer, decoding the second FGS based on the context for the first FGS, updating the list of decoded subgroups in the buffer without storing the context for the second FGS in the buffer, decoding the third FGS based on the context for the first FGS, updating the list of decoded subgroups in the buffer without storing the context for the third FGS in the buffer.

[0721] Referring to FIG. 61, with respect to an SPS further including subsequent_subgroups_info_present_flag, etc., the bitstream includes a sequence parameter set, and the sequence parameter set may further include information indicating whether additional information of subsequent subgroups exists.

[0722] Referring to FIGS. 62 and 63 together, with respect to num_subsequent_subgroups[i], subsequent_subgroup_id[i][j], subsequent_subgroup_bbox_origin[i][j][k], subsequent_subgroup_bbox_size[i][j][k]), the bitstream includes at least one of a geometry data unit or a dependent geometry data unit, and a header of the geometry data unit or at least one of the dependent geometry data units may include at least one of information indicating the number of subsequent subgroups, information indicating an ID of the subsequent subgroup, information indicating a position of a bounding box related to the subsequent subgroup, or information indicating a size of a bounding box related to the subsequent subgroup.

[0723] Referring to FIG. 1, a decryption method may be performed in a decryption device. The decryption device includes 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 point cloud data; and decode the point cloud data.

[0724] The processor is further configured to: decode geometry data of point cloud data; decode attribute data of point cloud data; and the processor is further configured to: decode the geometry data included in the data unit based on a header of the data unit including the geometry data, and store the context in a buffer based on context reference indication information included in the bitstream; and the processor may be further configured to: decode attribute data included in the data unit based on a header of the data unit including the attribute data, and store the context in a buffer based on context reference indication information included in the bitstream.

[0725] The method and device according to the embodiments provide the following technical effects.

[0726] The present invention can provide spatial random access and scalable coding effects while maintaining the compression ratio of point cloud data. Embodiments can scalably encode and decode point cloud data based on layer groups or subgroups. Embodiments can efficiently store context information in the buffer memory of the context used during encoding and decoding by utilizing the structure of the layer groups or subgroups, and can delete the memory. Embodiments can perform ROI-based partial encoding or partial decoding by utilizing the layer groups or subgroups.

[0727] The embodiments have been described in terms of methods and / or devices, and the descriptions of methods and devices may be applied complementarily.

[0728] For the convenience of explanation, each drawing has been described separately, but it is also possible to design a new embodiment by combining the embodiments described in each drawing. In addition, designing a computer-readable recording medium having a program recorded thereon for executing the previously described embodiments, as needed by a person skilled in the art, also falls within the scope of the embodiments. 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 the embodiments so that various modifications can be made. 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 can be made by a person skilled in the art to which the present invention pertains without departing from the gist of the embodiments claimed in the claims, and such modifications should not be understood individually from the technical idea or prospect of the embodiments.

[0729] 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. According to embodiments, the components according to the embodiments may be implemented by separate chips. According to embodiments, 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.

[0730] 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”.

[0731] Terms such as "first," "second," etc. may be used to describe various components of the embodiments. However, the various components according to the embodiments should not be interpreted as limited 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 mean the same user input signals unless the context clearly indicates otherwise.

[0732] 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 terms. The expression “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.

[0733] Additionally, the operations according to the embodiments described in this document may be performed by a transceiver device including a memory and / or a processor according to the embodiments. The memory may store programs for processing / controlling the operations according to the embodiments, and the processor may control various operations described in this document. The processor 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 the processor or in the memory.

[0734] Meanwhile, the operations according to the embodiments described above may be performed by a transmitting device and / or a receiving device according to the embodiments. The transmitting / receiving device may include a transmitting / receiving unit for transmitting and receiving media data, a memory for storing instructions (program code, algorithm, flowchart, and / or data) for a process according to the embodiments, and a processor for controlling the operations of the transmitting / receiving device.

[0735] The processor may be referred to as a controller or the like, and may correspond to, for example, hardware, software, and / or a combination thereof. The operations according to the above-described embodiments may be performed by the processor. Furthermore, the processor may be implemented as an encoder / decoder or the like for the operations of the above-described embodiments.

[0736] As described above, the relevant contents have been described in the best form for carrying out the embodiments.

[0737] As described above, the embodiments may be applied in whole or in part to a point cloud data transmission and reception device and system.

[0738] Those skilled in the art may make various changes or modifications to the embodiments within the scope of the embodiments.

[0739] Embodiments may include modifications / changes, which do not depart from the scope of the claims and their equivalents.

Claims

1. A step of receiving a bitstream containing point cloud data; and A step of decoding the above point cloud data; comprising; How to decrypt.

2. In paragraph 1, The steps for decoding the above point cloud data are: A step of decoding geometry data of the above point cloud data, A step of decoding attribute data of the above point cloud data, comprising: The steps for decoding the above geometry data are: Decoding the geometry data included in the data unit based on the header of the data unit including the geometry data, Further comprising storing context in a buffer based on context reference indication information included in the above bitstream, The steps to decode the above attribute data are: Decoding the attribute data included in the data unit based on the header of the data unit including the attribute data, Further comprising storing context in a buffer based on context reference indication information included in the bitstream. How to decrypt.

3. In paragraph 1, The above bitstream includes a set of sequence parameters, The sequence parameter set includes at least one of information indicating whether the geometry data is included in a plurality of slices and matches a layer group or at least one subgroup of the layer group, information indicating the number of layer groups, information indicating an ID of the layer group, information indicating the number of layers in the layer group, information indicating whether the layer group is divided into a plurality of subgroups, information indicating the number of subgroups included in the layer group, information indicating the number of subsequent dependent data units referencing a data unit or a dependent data unit, or information indicating an ID of a subsequent data unit referencing a data unit of the layer group and a subgroup. How to decrypt.

4. In paragraph 1 The above bitstream includes a geometry data unit, The header of the geometry data unit includes at least one of: information indicating the number of subsequent dependent data units referencing the data unit or dependent data unit, information indicating the number of subsequent dependent data units within the layer group referencing the data unit or dependent data unit, or information indicating the ID of the subsequent data unit referencing the data unit or dependent data unit. How to decrypt.

5. In paragraph 1, The above bitstream further includes a dependent geometry data unit, an attribute data unit, or a dependent attribute data unit, The header of the dependent geometry data unit, the header of the attribute data unit, or the header of the dependent attribute data unit includes at least one of: information indicating the number of subsequent dependent data units referencing the data unit or the dependent data unit, information indicating the number of subsequent dependent data units within the layer group referencing the data unit or the dependent data unit, or information indicating the ID of the subsequent data unit referencing the data unit or the dependent data unit. How to decrypt.

6. In paragraph 1, The bitstream comprises at least one FSG (Fine Granularity Slice) containing the point cloud data, and the at least one FGS matches a layer group and a subgroup of the layer group, The steps for decoding the above point cloud data are: Decode the first FGS, store the context for the first FGS in a buffer, and store the number of subgroups following the first FGS in the buffer, When decoding a second FGS following the first FGS, the context for the first FGS is loaded from the buffer, the value of the counter of the buffer is increased, and the number of subgroups following the second FGS is stored in the buffer. When decoding a third FGS following the second FGS, loading the context for the second FGS from the buffer, increasing the value of a counter of the buffer, and releasing the context memory of the buffer when the value of the counter is equal to the number of the subsequent subgroups. How to decrypt.

7. In paragraph 1, The bitstream comprises at least one FSG (Fine Granularity Slice) containing the point cloud data, and the at least one FGS matches a layer group and a subgroup of the layer group, The steps for decoding the above point cloud data are: When decoding the first FGS, the second FGS, and the third FGS related to partial decoding, decode the first FGS, store the context for the first FGS in a buffer, and store a list of subgroups following the first FGS in the buffer. Decoding the second FGS based on the context for the first FGS, and updating the list of decoded subgroups in the buffer without storing the context for the second FGS in the buffer, Decoding the third FGS based on the context for the first FGS, and updating the list of decoded subgroups in the buffer without storing the context for the third FGS in the buffer. How to decrypt.

8. In paragraph 1, The above bitstream includes a set of sequence parameters, The above sequence parameter set further includes information indicating whether additional information of subsequent subgroups exists, How to decrypt.

9. In paragraph 1, The bitstream includes at least one of a geometry data unit or a dependent geometry data unit, At least one of the header of the geometry data unit or the dependent geometry data unit includes at least one of information indicating the number of subsequent subgroups, information indicating an ID of the subsequent subgroup, information indicating a position of a bounding box related to the subsequent subgroup, or information indicating a size of a bounding box related to the subsequent subgroup. How to decrypt.

10. Memory; and At least one processor connected to the memory; wherein the at least one processor comprises: Receive a bitstream containing point cloud data; and configured to decode the above point cloud data; Decryption device.

11. In paragraph 10, The above processor: Decoding geometry data of the above point cloud data; It is further configured to decode attribute data of the above point cloud data; The above processor: Decoding the geometry data included in the data unit based on the header of the data unit including the geometry data, Further configured to store context in a buffer based on context reference indication information included in the above bitstream, The above processor: Decoding the attribute data included in the data unit based on the header of the data unit including the attribute data, Further configured to store context in a buffer based on context reference indication information included in the above bitstream, Decryption device.

12. Step of encoding point cloud data; and A step of transmitting a bitstream including the above point cloud data; Encoding method.

13. Memory; and At least one processor connected to the memory; wherein the at least one processor comprises: Encode point cloud data; and configured to transmit a bitstream including the above point cloud data; Encoding device.

14. A computer-readable storage medium storing a bitstream generated by the method according to Article 12.

15. Step of obtaining bitstream for point cloud data; The bitstream is generated based on the steps of encoding geometry data of the point cloud data; and encoding attribute data of the point cloud data; and A method comprising the step of transmitting data including the bitstream.

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