Three-dimensional data processing method, three-dimensional data processing device, and three-dimensional data processing system

Abstract

To reduce a processing amount.SOLUTION: A three-dimensional data processing method processes three-dimensional data using a device including a processor and a memory. The processor acquires a plurality of three-dimensional data each corresponding to different time information, using the memory, combines the plurality of three-dimensional data, and generates the combined three-dimensional data. Each of the plurality of three-dimensional data includes a data set composed of three-dimensional position information and attribute information associated with the three-dimensional position information. The combined three-dimensional data includes the data set and meta data. The meta data includes information indicating an attribute type of the data set included in the combined three-dimensional data. The information indicating the attribute type indicates information where the attribute information of the data set included in the combined three-dimensional data is associated with the time information.SELECTED DRAWING: Figure 107

Description

[Technical Field]

[0001] The present disclosure relates to a three-dimensional data encoding method, a three-dimensional data decoding method, a three-dimensional data encoding device, and a three-dimensional data decoding device. [Background technology]

[0002] In the future, devices and services that utilize 3D data are expected to become widespread in a wide range of fields, including computer vision for autonomous operation of automobiles or robots, map information, surveillance, infrastructure inspection, video distribution, etc. 3D data can be acquired in a variety of ways, including distance sensors such as range finders, stereo cameras, or a combination of multiple monocular cameras.

[0003] One method of representing three-dimensional data is a point cloud, which represents the shape of a three-dimensional structure using a group of points in three-dimensional space. A point cloud stores the position and color of the points. Point clouds are expected to become the mainstream method of representing three-dimensional data, but point clouds require a very large amount of data. Therefore, when storing or transmitting three-dimensional data, data compression through encoding is essential, just as with two-dimensional video images (examples include MPEG-4 AVC or HEVC standardized by MPEG).

[0004] In addition, compression of point clouds is partially supported by public libraries that perform point cloud-related processing (Point Cloud Library).

[0005] Furthermore, a technique is known in which three-dimensional map data is used to search for and display facilities located around a vehicle (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0006] [Patent Document 1] International Publication No. 2014 / 020663 Summary of the Invention [Problem to be solved by the invention]

[0007] In encoding or decoding three-dimensional data, it is desirable to be able to reduce the amount of processing.

[0008] An object of the present disclosure is to provide a three-dimensional data encoding method, a three-dimensional data decoding method, a three-dimensional data encoding device, or a three-dimensional data decoding device that can reduce the amount of processing. [Means for solving the problem]

[0009] A three-dimensional data processing method according to one aspect of the present disclosure is a three-dimensional data processing method that processes three-dimensional data using an apparatus having a processor and a memory, wherein the processor uses the memory to acquire multiple three-dimensional data, each corresponding to different temporal information, and combines the multiple three-dimensional data to generate combined three-dimensional data, each of the multiple three-dimensional data including a dataset consisting of three-dimensional position information and attribute information associated with the three-dimensional position information, and the combined three-dimensional data includes the dataset and metadata, and the metadata includes information indicating the attribute type of the dataset included in the combined three-dimensional data, and the information indicating the attribute type indicates that the attribute information of the dataset included in the combined three-dimensional data is information related to the temporal information.

[0010] A three-dimensional data processing device according to one aspect of the present disclosure is a three-dimensional data processing device having a processor and a memory, wherein the processor uses the memory to acquire multiple three-dimensional data, each corresponding to different temporal information, and combines the multiple three-dimensional data to generate combined three-dimensional data, each of the multiple three-dimensional data including a dataset consisting of three-dimensional position information and attribute information associated with the three-dimensional position information, and the combined three-dimensional data includes the dataset and metadata, and the metadata includes information indicating the attribute type of the dataset included in the combined three-dimensional data, and the information indicating the attribute type indicates that the attribute information of the dataset included in the combined three-dimensional data is information related to the temporal information. [Effects of the Invention]

[0011] The present disclosure can provide a three-dimensional data encoding method, a three-dimensional data decoding method, a three-dimensional data encoding device, or a three-dimensional data decoding device that can reduce the amount of processing. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram showing a configuration of a three-dimensional data encoding / decoding system according to the first embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the configuration of point cloud data according to the first embodiment. [Figure 3] FIG. 3 is a diagram showing an example of the structure of a data file in which point cloud data information according to the first embodiment is described. [Figure 4] FIG. 4 is a diagram showing types of point cloud data according to the first embodiment. [Figure 5] FIG. 5 is a diagram showing a configuration of a first encoding unit according to the first embodiment. [Figure 6] FIG. 6 is a block diagram of a first encoding unit according to the first embodiment. [Figure 7] FIG. 7 is a diagram illustrating a configuration of a first decoding unit according to the first embodiment. [Figure 8]FIG. 8 is a block diagram of a first decoding unit according to the first embodiment. [Figure 9] FIG. 9 is a diagram showing a configuration of a second encoding unit according to the first embodiment. [Figure 10] FIG. 10 is a block diagram of a second encoding unit according to the first embodiment. [Figure 11] FIG. 11 is a diagram illustrating a configuration of a second decoding unit according to the first embodiment. [Figure 12] FIG. 12 is a block diagram of a second decoding unit according to the first embodiment. [Figure 13] FIG. 13 is a diagram showing a protocol stack related to PCC encoded data according to the first embodiment. [Figure 14] FIG. 14 is a diagram illustrating a basic structure of the ISOBMFF according to the second embodiment. [Figure 15] FIG. 15 is a diagram illustrating a protocol stack according to the second embodiment. [Figure 16] FIG. 16 is a diagram illustrating the configurations of an encoding unit and a multiplexing unit according to the third embodiment. [Figure 17] FIG. 17 is a diagram illustrating an example of a structure of coded data according to the third embodiment. [Figure 18] FIG. 18 is a diagram showing an example of the structure of coded data and NAL units according to the third embodiment. [Figure 19] FIG. 19 is a diagram illustrating an example of the semantics of pcc_nal_unit_type according to the third embodiment. [Figure 20] FIG. 20 is a diagram showing an example of the transmission order of NAL units according to the third embodiment. [Figure 21] FIG. 21 is a block diagram of a first encoding unit according to the fourth embodiment. [Figure 22] FIG. 22 is a block diagram of a first decoding unit according to the fourth embodiment. [Figure 23] FIG. 23 is a block diagram of a division unit according to the fourth embodiment. [Figure 24] FIG. 24 is a diagram showing an example of division into slices and tiles according to the fourth embodiment. [Figure 25] FIG. 25 is a diagram showing an example of a division pattern of slices and tiles according to the fourth embodiment. [Figure 26] FIG. 26 is a diagram illustrating an example of a dependency relationship according to the fourth embodiment. [Figure 27] FIG. 27 is a diagram showing an example of the decoding order of data according to the fourth embodiment. [Figure 28] FIG. 28 is a flowchart of the encoding process according to the fourth embodiment. [Figure 29] FIG. 29 is a block diagram of a coupling unit according to the fourth embodiment. [Figure 30] FIG. 30 is a diagram showing an example of the structure of coded data and NAL units according to the fourth embodiment. [Figure 31] FIG. 31 is a flowchart of the encoding process according to the fourth embodiment. [Figure 32] FIG. 32 is a flowchart of the decoding process according to the fourth embodiment. [Figure 33] FIG. 33 is a flowchart of the encoding process according to the fourth embodiment. [Figure 34] FIG. 34 is a flowchart of the decoding process according to the fourth embodiment. [Figure 35] FIG. 35 is a diagram showing an image of generating a tree structure and occupancy codes from point cloud data of multiple frames according to the fifth embodiment. [Figure 36] FIG. 36 is a diagram illustrating an example of frame combination according to the fifth embodiment. [Figure 37] FIG. 37 is a diagram showing an example of combining multiple frames according to the fifth embodiment. [Figure 38] FIG. 38 is a flowchart of three-dimensional data encoding processing according to the fifth embodiment. [Figure 39] FIG. 39 is a flowchart of the encoding process according to the fifth embodiment. [Figure 40] FIG. 40 is a flowchart of three-dimensional data decoding processing according to the fifth embodiment. [Figure 41]FIG. 41 is a flowchart of the decoding and division process according to the fifth embodiment. [Figure 42] FIG. 42 is a block diagram of an encoding unit according to the fifth embodiment. [Figure 43] FIG. 43 is a block diagram of a division unit according to the fifth embodiment. [Figure 44] FIG. 44 is a block diagram of a position information encoding unit according to the fifth embodiment. [Figure 45] FIG. 45 is a block diagram of an attribute information encoding unit according to the fifth embodiment. [Figure 46] FIG. 46 is a flowchart of the encoding process of point cloud data according to the fifth embodiment. [Figure 47] FIG. 47 is a flowchart of the encoding process according to the fifth embodiment. [Figure 48] FIG. 48 is a block diagram of a decoding unit according to the fifth embodiment. [Figure 49] FIG. 49 is a block diagram of a position information decoding unit according to the fifth embodiment. [Figure 50] FIG. 50 is a block diagram of an attribute information decoding unit according to the fifth embodiment. [Figure 51] FIG. 51 is a block diagram of a combining unit according to the fifth embodiment. [Figure 52] FIG. 52 is a flowchart of the decoding process of point cloud data according to the fifth embodiment. [Figure 53] FIG. 53 is a flowchart of the decoding process according to the fifth embodiment. [Figure 54] FIG. 54 is a diagram showing an example of a frame combining pattern according to the fifth embodiment. [Figure 55] FIG. 55 is a diagram illustrating an example of a configuration of a PCC frame according to the fifth embodiment. [Figure 56] FIG. 56 is a diagram showing the structure of the encoding position information according to the fifth embodiment. [Figure 57] FIG. 57 is a diagram illustrating an example of the syntax of the header of the encoding position information according to the fifth embodiment. [Figure 58]FIG. 58 is a diagram illustrating an example of the syntax of the payload of the encoded position information according to the fifth embodiment. [Figure 59] FIG. 59 is a diagram illustrating an example of leaf node information according to the fifth embodiment. [Figure 60] FIG. 60 is a diagram illustrating an example of leaf node information according to the fifth embodiment. [Figure 61] FIG. 61 is a diagram showing an example of bitmap information according to the fifth embodiment. [Figure 62] FIG. 62 is a diagram showing the structure of the encoding attribute information according to the fifth embodiment. [Figure 63] FIG. 63 is a diagram illustrating an example of the syntax of the header of the encoding attribute information according to the fifth embodiment. [Figure 64] FIG. 64 is a diagram illustrating an example of the syntax of the payload of the encoded attribute information according to the fifth embodiment. [Figure 65] FIG. 65 is a diagram showing a structure of coded data according to the fifth embodiment. [Figure 66] FIG. 66 is a diagram showing the data transmission order and data reference relationships according to the fifth embodiment. [Figure 67] FIG. 67 is a diagram showing the data transmission order and data reference relationships according to the fifth embodiment. [Figure 68] FIG. 68 is a diagram showing the data transmission order and data reference relationships according to the fifth embodiment. [Figure 69] FIG. 69 is a diagram showing an example of decoding some frames according to the fifth embodiment. [Figure 70] FIG. 70 is a diagram showing the data transmission order and data reference relationships according to the fifth embodiment. [Figure 71] FIG. 71 is a diagram showing the data transmission order and data reference relationships according to the fifth embodiment. [Figure 72] FIG. 72 is a diagram showing the data transmission order and data reference relationships according to the fifth embodiment. [Figure 73] FIG. 73 is a diagram showing the data transmission order and data reference relationships according to the fifth embodiment. [Figure 74] FIG. 74 is a flowchart of the encoding process according to the fifth embodiment. [Figure 75] FIG. 75 is a flowchart of the decoding process according to the fifth embodiment. [Figure 76] FIG. 76 is a diagram showing an example of three-dimensional points according to the sixth embodiment. [Figure 77] FIG. 77 is a diagram showing an example of setting LoD according to the sixth embodiment. [Figure 78] FIG. 78 is a diagram showing an example of threshold values ​​used for setting LoD according to the sixth embodiment. [Figure 79] FIG. 79 is a diagram showing an example of attribute information used for a predicted value according to the sixth embodiment. [Figure 80] FIG. 80 is a diagram illustrating an example of an exponential-Golomb code according to the sixth embodiment. [Figure 81] FIG. 81 is a diagram illustrating processing for exponential-Golomb coding according to the sixth embodiment. [Figure 82] FIG. 82 is a diagram illustrating an example of the syntax of an attribute header according to the sixth embodiment. [Figure 83] FIG. 83 is a diagram illustrating an example of the syntax of attribute data according to the sixth embodiment. [Figure 84] FIG. 84 is a flowchart of three-dimensional data encoding processing according to the sixth embodiment. [Figure 85] FIG. 85 is a flowchart of the attribute information encoding process according to the sixth embodiment. [Figure 86] FIG. 86 illustrates processing for exponential-Golomb coding according to the sixth embodiment. [Figure 87] FIG. 87 is a diagram showing an example of a reverse lookup table showing the relationship between the remaining codes and their values ​​according to the sixth embodiment. [Figure 88] FIG. 88 is a flowchart of three-dimensional data decoding processing according to the sixth embodiment. [Figure 89] FIG. 89 is a flowchart of the attribute information decoding process according to the sixth embodiment. [Figure 90]FIG. 90 is a block diagram of a three-dimensional data encoding device according to the sixth embodiment. [Figure 91] FIG. 91 is a block diagram of a three-dimensional data decoding device according to the sixth embodiment. [Figure 92] FIG. 92 is a diagram showing a configuration of attribute information according to the sixth embodiment. [Figure 93] FIG. 93 is a diagram illustrating coded data according to the sixth embodiment. In FIG. [Figure 94] FIG. 94 is a flowchart of three-dimensional data encoding processing according to the sixth embodiment. [Figure 95] FIG. 95 is a flowchart of three-dimensional data decoding processing according to the sixth embodiment. [Figure 96] FIG. 96 is a diagram showing an example of coded data according to the seventh embodiment. [Figure 97] FIG. 97 is a diagram showing an example of coded data according to the seventh embodiment. [Figure 98] FIG. 98 is a flowchart of three-dimensional data encoding processing according to the seventh embodiment. [Figure 99] FIG. 99 is a diagram showing an example of motion compensation and frame splicing according to the seventh embodiment. [Figure 100] FIG. 100 is a diagram showing an example of motion vector transmission according to the seventh embodiment. [Figure 101] FIG. 101 is a diagram showing an example of coded data according to the seventh embodiment. [Figure 102] FIG. 102 is a block diagram of a three-dimensional data decoding device according to the seventh embodiment. [Figure 103] FIG. 103 is a diagram showing an example of a method for calculating a motion vector according to the seventh embodiment. [Figure 104] FIG. 104 is a diagram showing an example of a method for calculating a motion vector according to the seventh embodiment. [Figure 105] FIG. 105 is a diagram showing an example of coded data according to the seventh embodiment. [Figure 106] FIG. 106 is a diagram showing an example of a tile to which motion compensation according to the seventh embodiment is applied. [Figure 107] FIG. 107 is a flowchart of the encoding process according to the seventh embodiment. [Figure 108] FIG. 108 is a flowchart of the decoding process according to the seventh embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013] A three-dimensional data encoding method according to one embodiment of the present disclosure generates encoded data by encoding third point cloud data that combines first point cloud data and second point cloud data, and generates a bit stream that includes the encoded data and control information, wherein the encoded data includes position information and multiple attribute information for each of multiple three-dimensional points included in the third point cloud data, one of the multiple attribute information includes first information indicating whether the corresponding three-dimensional point belongs to the first point cloud data or the second point cloud data, and the control information includes second information indicating which attribute information of the multiple attribute information includes the first information.

[0014] According to this, when the first information is included in any of a plurality of pieces of attribute information, a three-dimensional data decoding device that decodes a bitstream generated by the three-dimensional data encoding method can easily determine the attribute information that includes the first information by using the second information included in the control information. Therefore, the three-dimensional data encoding method can reduce the processing load of the three-dimensional data decoding device.

[0015] For example, the control information may be common to a plurality of frames.

[0016] For example, the attribute information including the first information may be encoded using a lossless encoding method.

[0017] For example, the quantization parameters may be set so that the lossless encoding method is used.

[0018] For example, the position of the point cloud included in the second point cloud data may be corrected using motion information indicating the motion between the first point cloud data and the second point cloud data, and the third point cloud data may be generated by integrating the first point cloud data and the corrected second point cloud data, and the encoded data may include the motion information.

[0019] According to this, the three-dimensional data encoding method can improve encoding efficiency because the positions of the connecting point groups can be brought closer together.

[0020] A three-dimensional data decoding method according to one embodiment of the present disclosure obtains, from a bit stream, encoded data including position information and multiple attribute information for each of multiple three-dimensional points included in third point cloud data formed by combining first point cloud data and second point cloud data, obtains, from control information included in the bit stream, second information indicating attribute information including first information indicating whether a corresponding three-dimensional point belongs to the first point cloud data or the second point cloud data, and obtains the first information using the second information.

[0021] According to this, when the first information is included in any of the plurality of pieces of attribute information, the three-dimensional data decoding method can easily determine the attribute information that includes the first information by using the second information included in the control information. Therefore, the three-dimensional data decoding method can reduce the amount of processing.

[0022] For example, the control information may be common to a plurality of frames.

[0023] For example, the attribute information including the first information may be encoded using a lossless encoding method.

[0024] For example, the quantization parameters may be set so that the lossless encoding method is used.

[0025] For example, the first information may be used to separate the first point cloud data and the second point cloud data from the third point cloud data.

[0026] For example, motion information indicating the motion between the first point cloud data and the second point cloud data may be obtained from the bitstream, and the motion information may be used to correct the positions of the points included in the second point cloud data.

[0027] According to this, the three-dimensional data decoding method can decode a bitstream with improved coding efficiency by bringing the positions of the connecting point groups closer together.

[0028] Furthermore, a three-dimensional data encoding device according to one embodiment of the present disclosure includes a processor and a memory, wherein the processor uses the memory to generate encoded data by encoding third point cloud data that is a combination of first point cloud data and second point cloud data, and generates a bit stream including the encoded data and control information, wherein the encoded data includes position information and multiple attribute information for each of multiple three-dimensional points included in the third point cloud data, one of the multiple attribute information includes first information indicating whether the corresponding three-dimensional point belongs to the first point cloud data or the second point cloud data, and the control information includes second information indicating which of the multiple attribute information includes the first information.

[0029] According to this, when the first information is included in any of a plurality of pieces of attribute information, a three-dimensional data decoding device that decodes a bitstream generated by the three-dimensional data encoding device can easily determine which piece of attribute information includes the first information by using the second information included in the control information. Therefore, the three-dimensional data encoding device can reduce the processing load of the three-dimensional data decoding device.

[0030] In addition, a three-dimensional data decoding device according to one embodiment of the present disclosure includes a processor and a memory, and the processor uses the memory to obtain, from a bitstream, encoded data including position information and multiple attribute information for each of multiple three-dimensional points included in third point cloud data formed by combining first point cloud data and second point cloud data, obtain, from control information included in the bitstream, second information indicating attribute information including first information indicating whether a corresponding three-dimensional point belongs to the first point cloud data or the second point cloud data, and obtain the first information using the second information.

[0031] According to this, when the first information is included in any of the plurality of pieces of attribute information, the three-dimensional data decoding device can easily determine the attribute information that includes the first information by using the second information included in the control information, thereby reducing the amount of processing required by the three-dimensional data decoding device.

[0032] These comprehensive or specific aspects may be realized as a system, a method, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM, or may be realized as any combination of a system, a method, an integrated circuit, a computer program, and a recording medium.

[0033] Hereinafter, the embodiments will be described in detail with reference to the drawings. Note that each of the embodiments described below represents a specific example of the present disclosure. The numerical values, shapes, materials, components, component placement and connection configurations, steps, and step order shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components not recited in independent claims will be described as optional components.

[0034] (Embodiment 1) When using encoded point cloud data in an actual device or service, it is desirable to transmit and receive the information required for the application in order to reduce network bandwidth. However, until now, such a function has not existed in the encoding structure of 3D data, and no encoding method for this purpose has existed.

[0035] In this embodiment, we will describe a three-dimensional data encoding method and a three-dimensional data encoding device that provide the function of transmitting and receiving information required for the purpose in encoded data of a three-dimensional point cloud, as well as a three-dimensional data decoding method and a three-dimensional data decoding device that decodes the encoded data, a three-dimensional data multiplexing method that multiplexes the encoded data, and a three-dimensional data transmission method that transmits the encoded data.

[0036] In particular, two encoding methods (encoding schemes) are currently being considered as encoding methods (encoding systems) for point cloud data; however, the structure of the encoded data and the method for storing the encoded data in a system format have not been defined, and as things stand, there is a problem that MUX processing (multiplexing) in the encoding unit, or transmission or storage, is not possible.

[0037] Furthermore, there has been no method to date that supports a format in which two codecs, a first encoding method and a second encoding method, are mixed, such as PCC (Point Cloud Compression).

[0038] In this embodiment, a description will be given of the structure of PCC encoded data in which two codecs, a first encoding method and a second encoding method, are mixed, and a method of storing the encoded data in a system format.

[0039] First, the configuration of a three-dimensional data (point cloud data) encoding / decoding system according to this embodiment will be described. Fig. 1 is a diagram showing an example of the configuration of a three-dimensional data encoding / decoding system according to this embodiment. As shown in Fig. 1, the three-dimensional data encoding / decoding system includes a three-dimensional data encoding system 4601, a three-dimensional data decoding system 4602, a sensor terminal 4603, and an external connection unit 4604.

[0040] The three-dimensional data encoding system 4601 generates encoded data or multiplexed data by encoding point cloud data, which is three-dimensional data. Note that the three-dimensional data encoding system 4601 may be a three-dimensional data encoding device realized by a single device, or may be a system realized by multiple devices. Furthermore, the three-dimensional data encoding device may include some of the multiple processing units included in the three-dimensional data encoding system 4601.

[0041] The three-dimensional data encoding system 4601 includes a point cloud data generation system 4611, a presentation unit 4612, an encoding unit 4613, a multiplexing unit 4614, an input / output unit 4615, and a control unit 4616. The point cloud data generation system 4611 includes a sensor information acquisition unit 4617 and a point cloud data generation unit 4618.

[0042] The sensor information acquisition unit 4617 acquires sensor information from the sensor terminal 4603 and outputs the sensor information to the point cloud data generation unit 4618. The point cloud data generation unit 4618 generates point cloud data from the sensor information and outputs the point cloud data to the encoding unit 4613.

[0043] The presentation unit 4612 presents the sensor information or point cloud data to the user. For example, the presentation unit 4612 displays information or an image based on the sensor information or point cloud data.

[0044] The encoding unit 4613 encodes (compresses) the point cloud data, and outputs the obtained encoded data, control information obtained in the encoding process, and other additional information to the multiplexing unit 4614. The additional information includes, for example, sensor information.

[0045] The multiplexing unit 4614 generates multiplexed data by multiplexing the coded data input from the coding unit 4613, the control information, and the additional information. The format of the multiplexed data is, for example, a file format for storage or a packet format for transmission.

[0046] The input / output unit 4615 (e.g., a communication unit or an interface) outputs the multiplexed data to the outside. Alternatively, the multiplexed data is stored in a storage unit such as an internal memory. The control unit 4616 (or application execution unit) controls each processing unit. In other words, the control unit 4616 controls encoding, multiplexing, etc.

[0047] The sensor information may be input to the encoding unit 4613 or the multiplexing unit 4614. The input / output unit 4615 may output the point cloud data or the encoded data directly to the outside.

[0048] The transmission signal (multiplexed data) output from the three-dimensional data encoding system 4601 is input to the three-dimensional data decoding system 4602 via the external connection unit 4604 .

[0049] The three-dimensional data decoding system 4602 generates point cloud data, which is three-dimensional data, by decoding the encoded data or multiplexed data. Note that the three-dimensional data decoding system 4602 may be a three-dimensional data decoding device realized by a single device, or may be a system realized by multiple devices. Furthermore, the three-dimensional data decoding device may include some of the multiple processing units included in the three-dimensional data decoding system 4602.

[0050] The three-dimensional data decoding system 4602 includes a sensor information acquisition unit 4621 , an input / output unit 4622 , a demultiplexing unit 4623 , a decoding unit 4624 , a presentation unit 4625 , a user interface 4626 , and a control unit 4627 .

[0051] The sensor information acquisition unit 4621 acquires sensor information from the sensor terminal 4603 .

[0052] The input / output unit 4622 acquires the transmission signal, decodes the multiplexed data (file format or packets) from the transmission signal, and outputs the multiplexed data to the demultiplexer 4623.

[0053] The demultiplexing unit 4623 obtains the coded data, control information, and additional information from the multiplexed data, and outputs the coded data, control information, and additional information to the decoding unit 4624.

[0054] The decoding unit 4624 reconstructs the point cloud data by decoding the encoded data.

[0055] The presentation unit 4625 presents the point cloud data to the user. For example, the presentation unit 4625 displays information or images based on the point cloud data. The user interface 4626 acquires instructions based on user operations. The control unit 4627 (or the application execution unit) controls each processing unit. In other words, the control unit 4627 controls demultiplexing, decoding, presentation, etc.

[0056] The input / output unit 4622 may acquire point cloud data or encoded data directly from the outside. The presentation unit 4625 may acquire additional information such as sensor information and present information based on the additional information. The presentation unit 4625 may perform presentation based on a user instruction acquired by the user interface 4626.

[0057] The sensor terminal 4603 generates sensor information, which is information obtained by a sensor. The sensor terminal 4603 is a terminal equipped with a sensor or a camera, and examples thereof include a moving body such as an automobile, a flying object such as an airplane, a mobile terminal, or a camera.

[0058] The sensor information that can be acquired by the sensor terminal 4603 includes, for example, (1) the distance between the sensor terminal 4603 and an object, or the reflectance of the object, obtained from a LIDAR, millimeter-wave radar, or infrared sensor, and (2) the distance between a camera and an object, or the reflectance of the object, obtained from multiple monocular camera images or stereo camera images. The sensor information may also include the attitude, direction, gyro (angular velocity), position (GPS information or altitude), speed, acceleration, etc. of the sensor. The sensor information may also include temperature, air pressure, humidity, magnetism, etc.

[0059] The external connection unit 4604 is realized by an integrated circuit (LSI or IC), an external storage unit, communication with a cloud server via the Internet, broadcasting, or the like.

[0060] Next, point cloud data will be described. Fig. 2 is a diagram showing the configuration of point cloud data. Fig. 3 is a diagram showing an example of the configuration of a data file in which information about point cloud data is written.

[0061] Point cloud data includes data on multiple points. The data on each point includes location information (three-dimensional coordinates) and attribute information for that location information. A collection of multiple points is called a point cloud. For example, a point cloud can represent the three-dimensional shape of an object.

[0062] Position information such as three-dimensional coordinates is sometimes called geometry. Data for each point may also include attribute information of multiple attribute types. Attribute types include, for example, color or reflectance.

[0063] One piece of attribute information may be associated with one piece of location information, or multiple pieces of attribute information with different attribute types may be associated with one piece of location information, or multiple pieces of attribute information of the same attribute type may be associated with one piece of location information.

[0064] The configuration example of the data file shown in FIG. 3 is an example in which there is a one-to-one correspondence between position information and attribute information, and shows the position information and attribute information of N points that make up the point cloud data.

[0065] The position information is, for example, information on the three axes x, y, and z. The attribute information is, for example, RGB color information. A typical data file is a ply file.

[0066] Next, the types of point cloud data will be explained. Fig. 4 is a diagram showing the types of point cloud data. As shown in Fig. 4, point cloud data includes static objects and dynamic objects.

[0067] A static object is 3D point cloud data at any time (a certain time). A dynamic object is 3D point cloud data that changes over time. Hereinafter, 3D point cloud data at a certain time will be referred to as a PCC frame, or simply a frame.

[0068] The object may be a point cloud with a certain area restriction, such as ordinary video data, or a large-scale point cloud with no area restriction, such as map information.

[0069] Furthermore, there may be point cloud data of various densities, such as sparse point cloud data and dense point cloud data.

[0070] Each processing unit will be described in detail below. Sensor information is acquired by various methods, such as a distance sensor such as a LIDAR or a range finder, a stereo camera, or a combination of multiple monocular cameras. The point cloud data generation unit 4618 generates point cloud data based on the sensor information acquired by the sensor information acquisition unit 4617. The point cloud data generation unit 4618 generates position information as point cloud data, and adds attribute information for the position information to the position information.

[0071] The point cloud data generation unit 4618 may process the point cloud data when generating position information or adding attribute information. For example, the point cloud data generation unit 4618 may reduce the amount of data by deleting point clouds with overlapping positions. In addition, the point cloud data generation unit 4618 may convert (position shift, rotation, normalization, etc.) the position information or render the attribute information.

[0072] In FIG. 1, the point cloud data generation system 4611 is included in the three-dimensional data encoding system 4601, but it may be provided independently outside the three-dimensional data encoding system 4601.

[0073] The encoding unit 4613 generates encoded data by encoding the point cloud data based on a predetermined encoding method. There are two main types of encoding methods: the first is an encoding method that uses position information, and this encoding method will be referred to as the first encoding method hereinafter; and the second is an encoding method that uses a video codec, and this encoding method will be referred to as the second encoding method hereinafter.

[0074] The decoding unit 4624 decodes the coded data based on a predetermined coding method to decode the point group data.

[0075] The multiplexing unit 4614 generates multiplexed data by multiplexing the encoded data using an existing multiplexing method. The generated multiplexed data is transmitted or stored. In addition to the PCC encoded data, the multiplexing unit 4614 multiplexes other media such as video, audio, subtitles, applications, and files, or reference time information. The multiplexing unit 4614 may also multiplex attribute information related to sensor information or point cloud data.

[0076] Multiplexing methods or file formats include ISOBMFF, MPEG-DASH, which is an ISOBMFF-based transmission method, MMT, MPEG-2 TS Systems, and RMP.

[0077] The demultiplexer 4623 extracts PCC encoded data, other media, time information, and the like from the multiplexed data.

[0078] The input / output unit 4615 transmits the multiplexed data using a method suited to the transmission medium or storage medium, such as broadcasting or communication. The input / output unit 4615 may communicate with other devices via the Internet, or may communicate with a storage unit such as a cloud server.

[0079] The communication protocol used may be http, ftp, TCP, UDP, etc. A PULL type communication method or a PUSH type communication method may be used.

[0080] Either wired or wireless transmission may be used. For wired transmission, Ethernet (registered trademark), USB, RS-232C, HDMI (registered trademark), coaxial cable, etc. are used. For wireless transmission, wireless LAN, Wi-Fi (registered trademark), Bluetooth (registered trademark), millimeter waves, etc. are used.

[0081] As a broadcasting system, for example, DVB-T2, DVB-S2, DVB-C2, ATSC3.0, or ISDB-S3 is used.

[0082] Fig. 5 is a diagram showing the configuration of a first encoding unit 4630, which is an example of the encoding unit 4613 that performs encoding using the first encoding method. Fig. 6 is a block diagram of the first encoding unit 4630. The first encoding unit 4630 generates encoded data (encoded stream) by encoding point cloud data using the first encoding method. This first encoding unit 4630 includes a position information encoding unit 4631, an attribute information encoding unit 4632, an additional information encoding unit 4633, and a multiplexing unit 4634.

[0083] The first encoding unit 4630 is characterized in that it performs encoding taking into consideration a three-dimensional structure. The first encoding unit 4630 is also characterized in that the attribute information encoding unit 4632 performs encoding using information obtained from the position information encoding unit 4631. The first encoding method is also called GPCC (Geometry based PCC).

[0084] The point cloud data is PCC point cloud data such as a PLY file, or PCC point cloud data generated from sensor information, and includes position information (Position), attribute information (Attribute), and other additional information (MetaData). The position information is input to a position information encoding unit 4631, the attribute information is input to an attribute information encoding unit 4632, and the additional information is input to an additional information encoding unit 4633.

[0085] The position information encoding unit 4631 encodes the position information to generate encoded position information (Compressed Geometry), which is encoded data. For example, the position information encoding unit 4631 encodes the position information using an N-ary tree structure such as an octree. Specifically, in an octree, the target space is divided into eight nodes (subspaces), and 8-bit information (occupancy code) indicating whether or not a point cloud is included in each node is generated. Furthermore, the node including the point cloud is further divided into eight nodes, and 8-bit information indicating whether or not a point cloud is included in each of the eight nodes is generated. This process is repeated until the number of point clouds included in a predetermined layer or node falls below a threshold.

[0086] The attribute information encoding unit 4632 generates encoded attribute information (Compressed Attribute) that is encoded data by encoding using the configuration information generated by the position information encoding unit 4631. For example, the attribute information encoding unit 4632 determines a reference point (reference node) to be referenced when encoding a target point (target node) to be processed, based on the octree structure generated by the position information encoding unit 4631. For example, the attribute information encoding unit 4632 references a peripheral node or adjacent node whose parent node in the octree is the same as that of the target node. Note that the method of determining the reference relationship is not limited to this.

[0087] Furthermore, the encoding process of the attribute information may include at least one of a quantization process, a prediction process, and an arithmetic coding process. In this case, the reference means using a reference node to calculate a predicted value of the attribute information, or using the state of the reference node (e.g., occupancy information indicating whether the reference node includes a point group) to determine an encoding parameter. For example, the encoding parameter is a quantization parameter in a quantization process, or a context in an arithmetic coding process.

[0088] The additional information encoding unit 4633 generates encoded additional information (Compressed MetaData) that is encoded data by encoding compressible data from the additional information.

[0089] The multiplexing unit 4634 multiplexes the encoding position information, the encoding attribute information, the encoding additional information, and other additional information to generate a compressed stream, which is encoded data. The generated compressed stream is output to a processing unit in a system layer (not shown).

[0090] Next, a first decoding unit 4640, which is an example of the decoding unit 4624 that performs decoding using the first encoding method, will be described. FIG. 7 is a diagram showing the configuration of the first decoding unit 4640. FIG. 8 is a block diagram of the first decoding unit 4640. The first decoding unit 4640 generates point cloud data by decoding, using the first encoding method, coded data (coded stream) coded using the first coding method. The first decoding unit 4640 includes a demultiplexing unit 4641, a position information decoding unit 4642, an attribute information decoding unit 4643, and an additional information decoding unit 4644.

[0091] A coded stream (compressed stream) that is coded data is input to the first decoding unit 4640 from a processing unit in a system layer (not shown).

[0092] The demultiplexer 4641 separates the encoded position information (Compressed Geometry), the encoded attribute information (Compressed Attribute), the encoded additional information (Compressed MetaData), and other additional information from the encoded data.

[0093] The position information decoding unit 4642 generates position information by decoding the encoded position information. For example, the position information decoding unit 4642 restores the position information of a point group represented by three-dimensional coordinates from the encoded position information represented by an N-ary tree structure such as an octree.

[0094] The attribute information decoding unit 4643 decodes the encoded attribute information based on the configuration information generated by the position information decoding unit 4642. For example, the attribute information decoding unit 4643 determines a reference point (reference node) to be referenced in decoding the target point (target node) to be processed based on the octree structure obtained by the position information decoding unit 4642. For example, the attribute information decoding unit 4643 references a peripheral node or adjacent node whose parent node in the octree is the same as that of the target node. Note that the method of determining the reference relationship is not limited to this.

[0095] Furthermore, the attribute information decoding process may include at least one of an inverse quantization process, a prediction process, and an arithmetic decoding process. In this case, the reference means using a reference node to calculate a predicted value of the attribute information, or using the state of the reference node (e.g., occupancy information indicating whether the reference node includes a point group) to determine a decoding parameter. For example, the decoding parameter is a quantization parameter in an inverse quantization process, or a context in an arithmetic decoding process.

[0096] The additional information decoding unit 4644 generates additional information by decoding the encoded additional information. The first decoding unit 4640 uses the additional information necessary for decoding the position information and attribute information during decoding, and outputs the additional information necessary for the application to the outside.

[0097] Next, a description will be given of second encoding unit 4650, which is an example of encoding unit 4613 that performs encoding using the second encoding method. Fig. 9 is a diagram showing the configuration of second encoding unit 4650. Fig. 10 is a block diagram of second encoding unit 4650.

[0098] The second encoding unit 4650 generates encoded data (encoded stream) by encoding the point cloud data using a second encoding method. The second encoding unit 4650 includes an additional information generation unit 4651, a position image generation unit 4652, an attribute image generation unit 4653, a video encoding unit 4654, an additional information encoding unit 4655, and a multiplexing unit 4656.

[0099] The second encoding unit 4650 has a feature of generating a position image and an attribute image by projecting a three-dimensional structure onto a two-dimensional image, and encoding the generated position image and attribute image using an existing video encoding method. The second encoding method is also called VPCC (Video based PCC).

[0100] The point cloud data is PCC point cloud data such as a PLY file or PCC point cloud data generated from sensor information, and includes position information (Position), attribute information (Attribute), and other additional information (MetaData).

[0101] The additional information generating unit 4651 generates map information of a plurality of two-dimensional images by projecting a three-dimensional structure onto the two-dimensional images.

[0102] The position image generation unit 4652 generates a position image (Geometry Image) based on the position information and the map information generated by the additional information generation unit 4651. This position image is, for example, a distance image in which distance (Depth) is indicated as a pixel value. Note that this distance image may be an image in which multiple point clouds are viewed from a single viewpoint (an image in which multiple point clouds are projected onto a single two-dimensional plane), or may be multiple images in which multiple point clouds are viewed from multiple viewpoints, or may be a single image in which these multiple images are integrated.

[0103] The attribute image generation unit 4653 generates an attribute image based on the attribute information and the map information generated by the additional information generation unit 4651. This attribute image is, for example, an image in which attribute information (for example, color (RGB)) is represented as pixel values. Note that this image may be an image in which multiple point clouds are viewed from one viewpoint (an image in which multiple point clouds are projected onto one two-dimensional plane), or multiple images in which multiple point clouds are viewed from multiple viewpoints, or a single image in which these multiple images are integrated.

[0104] The video encoding unit 4654 generates an encoded position image (Compressed Geometry Image) and an encoded attribute image (Compressed Attribute Image), which are encoded data, by encoding the position image and the attribute image using a video encoding method. Note that any known encoding method may be used as the video encoding method. For example, the video encoding method is AVC, HEVC, or the like.

[0105] The additional information encoding unit 4655 generates encoded additional information (Compressed MetaData) by encoding the additional information, map information, and the like included in the point cloud data.

[0106] The multiplexing unit 4656 multiplexes the encoding position image, the encoding attribute image, the encoding additional information, and other additional information to generate an encoded stream (Compressed Stream) that is encoded data. The generated encoded stream is output to a processing unit in a system layer (not shown).

[0107] Next, a second decoding unit 4660, which is an example of the decoding unit 4624 that performs decoding using the second encoding method, will be described. FIG. 11 is a diagram showing the configuration of the second decoding unit 4660. FIG. 12 is a block diagram of the second decoding unit 4660. The second decoding unit 4660 generates point cloud data by decoding, using the second encoding method, coded data (coded stream) coded using the second coding method. The second decoding unit 4660 includes a demultiplexing unit 4661, a video decoding unit 4662, an additional information decoding unit 4663, a position information generation unit 4664, and an attribute information generation unit 4665.

[0108] A coded stream (compressed stream) that is coded data is input to the second decoding unit 4660 from a processing unit in a system layer (not shown).

[0109] The demultiplexer 4661 separates the encoded position image (Compressed Geometry Image), the encoded attribute image (Compressed Attribute Image), the encoded additional information (Compressed MetaData), and other additional information from the encoded data.

[0110] The video decoding unit 4662 generates a position image and an attribute image by decoding the encoded position image and the encoded attribute image using a video encoding method. Note that any known encoding method may be used as the video encoding method. For example, the video encoding method is AVC or HEVC.

[0111] The additional information decoding unit 4663 decodes the encoded additional information to generate additional information including map information and the like.

[0112] The position information generating unit 4664 generates position information using the position image and map information. The attribute information generating unit 4665 generates attribute information using the attribute image and map information.

[0113] The second decoding unit 4660 uses the additional information necessary for decoding during decoding, and outputs the additional information necessary for the application to the outside.

[0114] The following describes the problems with the PCC encoding method. Fig. 13 is a diagram showing a protocol stack related to PCC encoded data. Fig. 13 shows an example in which other media data such as video (e.g., HEVC) or audio is multiplexed onto the PCC encoded data and transmitted or stored.

[0115] Multiplexing methods and file formats have the function of multiplexing various coded data and transmitting or storing them. To transmit or store coded data, the coded data must be converted into the format of the multiplexing method. For example, HEVC specifies a technology that stores coded data in a data structure called a NAL unit and stores the NAL unit in ISOBMFF.

[0116] On the other hand, currently, a first encoding method (Codec1) and a second encoding method (Codec2) are being considered as methods for encoding point cloud data, but the structure of the encoded data and the method for storing the encoded data in a system format have not been defined, which poses the problem that, as it stands, it is not possible to perform MUX processing (multiplexing) in the encoding unit, transmission, or storage.

[0117] In the following description, unless a specific encoding method is specified, it refers to either the first encoding method or the second encoding method.

[0118] (Embodiment 2) In this embodiment, a method for storing NAL units in an ISOBMFF file will be described.

[0119] ISOBMFF (ISO based media file format) is a file format standard defined in ISO / IEC 14496-12. ISOBMFF is a media-independent standard that defines a format that can store multiplexed media such as video, audio, and text.

[0120] This section explains the basic structure (file) of ISOBMFF. The basic unit in ISOBMFF is a box. A box consists of type, length, and data, and a file is a collection of boxes of various types.

[0121] 14 is a diagram showing the basic structure (file) of ISOBMFF. An ISOBMFF file mainly includes boxes such as ftyp, which indicates the brand of the file using 4CC (four-character code), moov, which stores metadata such as control information, and mdat, which stores data.

[0122] Storing methods for each media type in ISOBMFF files are specified separately. For example, storage methods for AVC video and HEVC video are specified in ISO / IEC 14496-15. While it is conceivable to extend and use the functions of ISOBMFF to store or transmit PCC encoded data, there are no regulations yet for storing PCC encoded data in ISOBMFF files. Therefore, in this embodiment, a method for storing PCC encoded data in an ISOBMFF file will be described.

[0123] 15 is a diagram showing a protocol stack when NAL units common to PCC codecs are stored in an ISOBMFF file. Here, NAL units common to PCC codecs are stored in an ISOBMFF file. Although NAL units are common to PCC codecs, multiple PCC codecs are stored in the NAL unit, so it is desirable to define a storage method (Carriage of Codec1, Carriage of Codec2) according to each codec.

[0124] (Embodiment 3) In this embodiment, the types of coded data (position information (Geometry), attribute information (Attribute), additional information (Metadata)) generated by the first coding unit 4630 or the second coding unit 4650 described above, a method for generating the additional information (Metadata), and multiplexing processing in the multiplexing unit will be described. Note that the additional information (Metadata) may also be referred to as a parameter set or control information.

[0125] In this embodiment, the dynamic object (three-dimensional point cloud data that changes over time) described in Figure 4 will be used as an example, but a similar method may also be used in the case of a static object (three-dimensional point cloud data at any time).

[0126] 16 is a diagram showing the configurations of an encoding unit 4801 and a multiplexing unit 4802 included in the three-dimensional data encoding device according to this embodiment. The encoding unit 4801 corresponds to, for example, the first encoding unit 4630 or the second encoding unit 4650 described above. The multiplexing unit 4802 corresponds to the multiplexing unit 4634 or 4656 described above.

[0127] The encoding unit 4801 encodes point cloud data of multiple PCC (Point Cloud Compression) frames, and generates encoded data (Multiple Compressed Data) of multiple pieces of position information, attribute information, and additional information.

[0128] The multiplexing unit 4802 converts data of multiple data types (position information, attribute information, and additional information) into NAL units, thereby converting the data into a data structure that takes into account data access in the decoding device.

[0129] 17 is a diagram showing an example of the structure of coded data generated by coding unit 4801. Arrows in the diagram indicate dependencies related to the decoding of coded data, with the source of the arrow depending on the data at the end of the arrow. In other words, the decoding device decodes the data at the end of the arrow and uses the decoded data to decode the data at the end of the arrow. In other words, dependency means that the data on which the dependency is based is referenced (used) in the processing (encoding, decoding, etc.) of the data on which the dependency is based.

[0130] First, the process of generating encoded data of position information will be described. The encoding unit 4801 generates encoded position data (compressed geometry data) for each frame by encoding the position information of each frame. The encoded position data is represented by G(i), where i indicates the frame number, the time of the frame, etc.

[0131] The encoding unit 4801 also generates a position parameter set (GPS(i)) corresponding to each frame. The position parameter set includes parameters that can be used to decode the encoded position data. The encoded position data for each frame depends on the corresponding position parameter set.

[0132] Furthermore, encoded position data consisting of multiple frames is defined as a position sequence (Geometry Sequence). The encoding unit 4801 generates a position sequence parameter set (Geometry Sequence PS: also referred to as position SPS) that stores parameters commonly used in decoding processes for multiple frames in the position sequence. The position sequence depends on the position SPS.

[0133] Next, the process of generating coded data of attribute information will be described. The coding unit 4801 generates coded attribute data (Compressed Attribute Data) for each frame by coding the attribute information of each frame. The coded attribute data is represented by A(i). Also, Fig. 17 shows an example in which attribute X and attribute Y exist, and the coded attribute data of attribute X is represented by AX(i) and the coded attribute data of attribute Y is represented by AY(i).

[0134] The encoding unit 4801 also generates an attribute parameter set (APS(i)) corresponding to each frame. The attribute parameter set for attribute X is represented as AXPS(i), and the attribute parameter set for attribute Y is represented as AYPS(i). The attribute parameter set includes parameters that can be used to decode encoded attribute information. The encoded attribute data depends on the corresponding attribute parameter set.

[0135] Furthermore, encoded attribute data consisting of multiple frames is defined as an attribute sequence. The encoding unit 4801 generates an attribute sequence parameter set (Attribute Sequence PS: also referred to as attribute SPS) that stores parameters commonly used in decoding processes for multiple frames in the attribute sequence. The attribute sequence depends on the attribute SPS.

[0136] Furthermore, in the first encoding method, the encoded attribute data depends on the encoded position data.

[0137] 17 shows an example in which two types of attribute information (attribute X and attribute Y) exist. When there are two types of attribute information, for example, two encoding units generate respective data and metadata. Also, for example, an attribute sequence is defined for each type of attribute information, and an attribute SPS is generated for each type of attribute information.

[0138] 17 shows an example in which there is one type of position information and two types of attribute information, but the present invention is not limited to this, and there may be one type of attribute information, or three or more types. In this case, encoded data can be generated using a similar method. Furthermore, in the case of point cloud data that does not have attribute information, the attribute information may not be necessary. In this case, the encoding unit 4801 does not need to generate a parameter set related to the attribute information.

[0139] Next, the process of generating additional information (metadata) will be described. The encoding unit 4801 generates a PCC Stream PS (also referred to as stream PS), which is a parameter set for the entire PCC stream. The encoding unit 4801 stores, in the stream PS, parameters that can be used in common for decoding processes for one or more position sequences and one or more attribute sequences. For example, the stream PS includes identification information indicating the codec for the point cloud data, information indicating the algorithm used for encoding, and the like. The position sequence and attribute sequence depend on the stream PS.

[0140] Next, the access unit and GOF will be explained. In this embodiment, the concepts of the access unit (AU) and GOF (Group of Frame) are newly introduced.

[0141] An access unit is a basic unit for accessing data during decoding, and is composed of one or more pieces of data and one or more pieces of metadata. For example, an access unit is composed of position information at the same time and one or more pieces of attribute information. A GOF is a random access unit and is composed of one or more access units.

[0142] The encoding unit 4801 generates an access unit header (AU Header) as identification information indicating the beginning of an access unit. The encoding unit 4801 stores parameters related to the access unit in the access unit header. For example, the access unit header includes the configuration or information of the coded data included in the access unit. The access unit header also includes parameters commonly used for the data included in the access unit, such as parameters related to decoding of the coded data.

[0143] Instead of an access unit header, the encoding unit 4801 may generate an access unit delimiter that does not include parameters related to the access unit. This access unit delimiter is used as identification information indicating the start of the access unit. The decoding device identifies the start of the access unit by detecting the access unit header or the access unit delimiter.

[0144] Next, the generation of identification information for the start of a GOF will be described. The encoding unit 4801 generates a GOF header as identification information that indicates the start of a GOF. The encoding unit 4801 stores parameters related to the GOF in the GOF header. For example, the GOF header includes the configuration or information of the coded data included in the GOF. The GOF header also includes parameters commonly used for the data included in the GOF, such as parameters related to the decoding of the coded data.

[0145] Instead of a GOF header, the encoding unit 4801 may generate a GOF delimiter that does not include parameters related to the GOF. This GOF delimiter is used as identification information that indicates the beginning of the GOF. The decoding device identifies the beginning of the GOF by detecting the GOF header or the GOF delimiter.

[0146] In PCC encoded data, for example, an access unit is defined as a PCC frame unit, and a decoding device accesses a PCC frame based on identification information at the beginning of the access unit.

[0147] Also, for example, GOF is defined as one random access unit. A decoding device accesses the random access unit based on the identification information at the beginning of the GOF. For example, if PCC frames are not dependent on each other and can be decoded independently, the PCC frames may be defined as the random access unit.

[0148] It should be noted that two or more PCC frames may be allocated to one access unit, and multiple random access units may be allocated to one GOF.

[0149] The encoding unit 4801 may also define and generate parameter sets or metadata other than those described above. For example, the encoding unit 4801 may generate SEI (Supplemental Enhancement Information) that stores parameters (optional parameters) that may not necessarily be used during decoding.

[0150] Next, the structure of coded data and the method of storing coded data in NAL units will be described.

[0151] For example, a data format is defined for each type of coded data. Figure 18 shows examples of coded data and NAL units.

[0152] For example, as shown in Fig. 18, the coded data includes a header and a payload. The coded data may include length information indicating the length (amount of data) of the coded data, the header, or the payload. The coded data may not include a header.

[0153] The header includes, for example, identification information for identifying the data, such as the data type or frame number.

[0154] The header includes, for example, identification information indicating a reference relationship. This identification information is stored in the header when, for example, there is a dependency relationship between data, and is information for referencing the reference destination from the reference source. For example, the header of the reference destination includes identification information for identifying the data. The header of the reference source includes identification information indicating the reference destination.

[0155] If the reference destination or the reference source can be identified or derived from other information, the identification information for specifying the data or the identification information indicating the reference relationship may be omitted.

[0156] The multiplexing unit 4802 stores the coded data in the payload of the NAL unit. The NAL unit header includes pcc_nal_unit_type, which is information identifying the coded data. Figure 19 shows an example of the semantics of pcc_nal_unit_type.

[0157] 19, when pcc_codec_type is codec 1 (Codec1: first encoding method), values ​​0 to 10 of pcc_nal_unit_type are assigned to the encoded position data (Geometry), encoded attribute X data (AttributeX), encoded attribute Y data (AttributeY), position PS (Geom.PS), attribute XPS (AttrX.PS), attribute YPS (AttrX.PS), position SPS (Geometry Sequence PS), attribute XSPS (AttributeX Sequence PS), attribute YSPS (AttributeY Sequence PS), AU header (AU Header), and GOF header (GOF Header) in codec 1. Values ​​11 and above are assigned as spares for codec 1.

[0158] When pcc_codec_type is Codec2 (Codec2: second encoding method), values ​​0 to 2 of pcc_nal_unit_type are assigned to codec data A (DataA), metadata A (MetaDataA), and metadata B (MetaDataB). Values ​​3 and above are assigned as spares for Codec2.

[0159] Next, the data transmission order will be explained. The following explains the restrictions on the transmission order of NAL units.

[0160] The multiplexing unit 4802 collectively transmits NAL units in units of GOF or AU. The multiplexing unit 4802 places a GOF header at the beginning of a GOF, and places an AU header at the beginning of an AU.

[0161] The multiplexing unit 4802 may allocate a sequence parameter set (SPS) for each AU so that the decoding device can decode from the next AU even if data is lost due to packet loss or the like.

[0162] If the coded data has a dependency relationship related to decoding, the decoding device decodes the referenced data first, and then decodes the referenced data. In order to enable the decoding device to decode the data in the order in which it was received without rearranging the data, the multiplexing unit 4802 sends the referenced data first.

[0163] 20 is a diagram showing examples of the transmission order of NAL units, and shows three examples: position information priority, parameter priority, and data integration.

[0164] The location information priority transmission order is an example in which information related to location information and information related to attribute information are transmitted together. In this transmission order, the transmission of information related to location information is completed earlier than the transmission of information related to attribute information.

[0165] For example, by using this transmission order, a decoding device that does not decode attribute information may be able to set a time during which it does not process the attribute information by ignoring the decoding of the attribute information. Also, for example, in the case of a decoding device that wants to decode position information quickly, it may be able to decode the position information more quickly by obtaining the encoded data of the position information early.

[0166] In FIG. 20, the attributes XSPS and YSPS are combined and written as the attribute SPS, but the attributes XSPS and YSPS may be arranged separately.

[0167] In the parameter set priority sending order, the parameter sets are sent first and the data is sent later.

[0168] As long as the NAL unit transmission order constraints are met as described above, the multiplexing unit 4802 may transmit NAL units in any order. For example, order identification information may be defined, and the multiplexing unit 4802 may have the function of transmitting NAL units in multiple order patterns. For example, the NAL unit order identification information may be stored in the stream PS.

[0169] The three-dimensional data decoding device may perform decoding based on the order identification information. The three-dimensional data decoding device may instruct the three-dimensional data encoding device on a desired transmission order, and the three-dimensional data encoding device (multiplexing unit 4802) may control the transmission order in accordance with the instructed transmission order.

[0170] The multiplexing unit 4802 may generate coded data that merges multiple functions, as long as the data transmission order is within the constraints of the transmission order, such as the transmission order of the integrated data. For example, as shown in Fig. 20, the GOF header and the AU header may be integrated, or the AXPS and the AYPS may be integrated. In this case, an identifier indicating that the data has multiple functions is defined in pcc_nal_unit_type.

[0171] A modified example of this embodiment will be described below. PS has levels, such as a frame-level PS, a sequence-level PS, and a PCC sequence-level PS, and if the PCC sequence level is the higher level and the frame level is the lower level, the following method may be used to store parameters.

[0172] The default PS value is indicated in the higher PS. Also, if the value of the lower PS differs from the value of the higher PS, the PS value is indicated in the lower PS. Alternatively, the PS value is not written in the higher PS, but written in the lower PS. Alternatively, information on whether the PS value is to be written in the lower PS, the higher PS, or both is written in either the lower PS or the higher PS, or both. Alternatively, the lower PS may be merged with the higher PS. Alternatively, if the lower PS and the higher PS overlap, the multiplexing unit 4802 may omit sending one of them.

[0173] The encoding unit 4801 or the multiplexing unit 4802 may divide the data into slices or tiles and transmit the divided data. The divided data includes information for identifying the divided data, and parameters used to decode the divided data are included in the parameter set. In this case, an identifier indicating that the data stores data or parameters related to tiles or slices is defined in pcc_nal_unit_type.

[0174] (Fourth embodiment) HEVC coding has data division tools such as slicing or tiling to enable parallel processing in a decoding device, but PCC (Point Cloud Compression) coding does not yet have such tools.

[0175] In PCC, various data division methods are possible depending on parallel processing, compression efficiency, and compression algorithms. This section explains the definitions of slices and tiles, the data structure, and transmission and reception methods.

[0176] 21 is a block diagram showing the configuration of a first encoding unit 4910 included in the three-dimensional data encoding device according to this embodiment. The first encoding unit 4910 generates encoded data (encoded stream) by encoding point cloud data using a first encoding method (GPCC (Geometry based PCC)). The first encoding unit 4910 includes a division unit 4911, multiple position information encoding units 4912, multiple attribute information encoding units 4913, an additional information encoding unit 4914, and a multiplexing unit 4915.

[0177] The dividing unit 4911 divides the point cloud data to generate a plurality of pieces of divided data. Specifically, the dividing unit 4911 divides the space of the point cloud data into a plurality of subspaces to generate a plurality of pieces of divided data. Here, a subspace is one of a tile and a slice, or a combination of a tile and a slice. More specifically, the point cloud data includes position information, attribute information, and additional information. The dividing unit 4911 divides the position information into a plurality of pieces of divided position information, and divides the attribute information into a plurality of pieces of divided attribute information. The dividing unit 4911 also generates additional information related to the division.

[0178] The position information encoding units 4912 encode the plurality of pieces of divided position information to generate a plurality of pieces of encoded position information. For example, the position information encoding units 4912 process the plurality of pieces of divided position information in parallel.

[0179] The attribute information encoding units 4913 encode the divided attribute information to generate the coded attribute information For example, the attribute information encoding units 4913 process the divided attribute information in parallel.

[0180] The additional information encoding unit 4914 generates encoded additional information by encoding the additional information included in the point cloud data and the additional information related to the data division generated by the division unit 4911 at the time of division.

[0181] The multiplexing unit 4915 multiplexes multiple pieces of encoding position information, multiple pieces of encoding attribute information, and encoded additional information to generate encoded data (encoded stream), and transmits the generated encoded data. The encoded additional information is also used during decoding.

[0182] 21 shows an example in which there are two position information encoders 4912 and two attribute information encoders 4913, but the number of position information encoders 4912 and two attribute information encoders 4913 may each be one, or three or more. Furthermore, multiple pieces of divided data may be processed in parallel within the same chip, like multiple cores within a CPU, or may be processed in parallel by cores on multiple chips, or may be processed in parallel by multiple cores on multiple chips.

[0183] 22 is a block diagram showing the configuration of the first decoding unit 4920. The first decoding unit 4920 restores the point cloud data by decoding coded data (coded stream) generated by coding the point cloud data using the first coding method (GPCC). The first decoding unit 4920 includes a demultiplexing unit 4921, multiple position information decoding units 4922, multiple attribute information decoding units 4923, an additional information decoding unit 4924, and a combining unit 4925.

[0184] The demultiplexing unit 4921 demultiplexes the coded data (coded stream) to generate a plurality of pieces of coding position information, a plurality of pieces of coding attribute information, and coded additional information.

[0185] The position information decoding units 4922 generate a plurality of pieces of divided position information by decoding the plurality of pieces of encoded position information. For example, the position information decoding units 4922 process the plurality of pieces of encoded position information in parallel.

[0186] The attribute information decoding units 4923 generate a plurality of pieces of divided attribute information by decoding the plurality of pieces of encoded attribute information. For example, the attribute information decoding units 4923 process the plurality of pieces of encoded attribute information in parallel.

[0187] The plurality of additional information decoders 4924 generate additional information by decoding the encoded additional information.

[0188] The combining unit 4925 generates position information by combining a plurality of pieces of divided position information using the additional information. The combining unit 4925 generates attribute information by combining a plurality of pieces of divided attribute information using the additional information.

[0189] 22 shows an example in which there are two position information decoding units 4922 and two attribute information decoding units 4923, but the number of position information decoding units 4922 and two attribute information decoding units 4923 may be one, or three or more. Furthermore, multiple pieces of divided data may be processed in parallel within the same chip, such as multiple cores within a CPU, or may be processed in parallel by cores on multiple chips, or may be processed in parallel by multiple cores on multiple chips.

[0190] Next, it will be described how the dividing unit 4911 has a configuration. Fig. 23 is a block diagram of the dividing unit 4911. The dividing unit 4911 includes a slice dividing unit 4931 (Slice Divider), a position information tile dividing unit 4932 (Geometry Tile Divider), and an attribute information tile dividing unit 4933 (Attribute Tile Divider).

[0191] The slice division unit 4931 generates a plurality of slice position information by dividing position information (Position (Geometry)) into slices. The slice division unit 4931 also generates a plurality of slice attribute information by dividing attribute information (Attribute) into slices. The slice division unit 4931 also outputs slice additional information (Slice MetaData) including information related to the slice division and information generated in the slice division.

[0192] The position information tile dividing unit 4932 divides a plurality of slice position information pieces into tiles to generate a plurality of pieces of divided position information pieces (a plurality of pieces of tile position information pieces). The position information tile dividing unit 4932 also outputs position tile additional information (Geometry Tile MetaData) including information related to the tile division of the position information pieces and information generated in the tile division of the position information pieces.

[0193] The attribute information tile dividing unit 4933 divides a plurality of slice attribute information pieces into tiles to generate a plurality of pieces of divided attribute information (a plurality of pieces of tile attribute information). The attribute information tile dividing unit 4933 also outputs attribute tile additional information (Attribute Tile MetaData) including information related to the tile division of the attribute information and information generated during the tile division of the attribute information.

[0194] The number of slices or tiles to be divided is equal to or greater than 1. In other words, division into slices or tiles does not have to be performed.

[0195] Although an example in which tile division is performed after slice division has been shown here, slice division may be performed after tile division. Furthermore, new division types may be defined in addition to slices and tiles, and division may be performed using three or more division types.

[0196] A method for dividing point cloud data will be described below. Fig. 24 is a diagram showing an example of division into slices and tiles.

[0197] First, the method of dividing into slices will be described. The dividing unit 4911 divides the three-dimensional point cloud data into arbitrary point clouds in slice units. In dividing into slices, the dividing unit 4911 does not divide the position information and attribute information that constitute a point, but divides the position information and attribute information together. In other words, the dividing unit 4911 divides into slices so that the position information and attribute information of an arbitrary point belong to the same slice. Note that, as long as this is followed, any number of divisions and any division method may be used. Furthermore, the minimum unit of division is a point. For example, the number of divisions for the position information and the attribute information is the same. For example, the three-dimensional point corresponding to the position information after dividing into slices and the three-dimensional point corresponding to the attribute information are included in the same slice.

[0198] Furthermore, the division unit 4911 generates slice additional information, which is additional information related to the number of divisions and the division method when dividing the slices. The slice additional information is the same for position information and attribute information. For example, the slice additional information includes information indicating the reference coordinate position, size, or side length of the bounding box after division. The slice additional information also includes information indicating the number of divisions, the division type, etc.

[0199] Next, a tile division method will be described. The division unit 4911 divides the data divided into slices into slice position information (G slices) and slice attribute information (A slices), and divides each of the slice position information and slice attribute information into tiles.

[0200] Although FIG. 24 shows an example of division using an octree structure, any number of divisions and any division method may be used.

[0201] Furthermore, the dividing unit 4911 may divide the position information and the attribute information using different division methods or the same division method. Furthermore, the dividing unit 4911 may divide a plurality of slices into tiles using different division methods or the same division method.

[0202] Furthermore, the dividing unit 4911 generates tile additional information related to the number of divisions and the division method when dividing tiles. The tile additional information (position tile additional information and attribute tile additional information) is independent of position information and attribute information. For example, the tile additional information includes information indicating the reference coordinate position, size, or side length of the bounding box after division. The tile additional information also includes information indicating the number of divisions, division type, etc.

[0203] Next, an example of a method for dividing point cloud data into slices or tiles will be described. The dividing unit 4911 may use a predetermined method as the method for dividing the point cloud data into slices or tiles, or may adaptively switch the method to be used depending on the point cloud data.

[0204] When dividing into slices, the dividing unit 4911 divides the three-dimensional space collectively based on the position information and attribute information. For example, the dividing unit 4911 determines the shape of an object and divides the three-dimensional space into slices according to the shape of the object. For example, the dividing unit 4911 extracts objects such as trees or buildings and divides the space into object units. For example, the dividing unit 4911 divides the space into slices so that one or more objects are entirely included in one slice. Alternatively, the dividing unit 4911 divides one object into multiple slices.

[0205] In this case, the encoding device may change the encoding method for each slice. For example, the encoding device may use a high-quality compression method for a specific object or a specific part of an object. In this case, the encoding device may store information indicating the encoding method for each slice in additional information (metadata).

[0206] Furthermore, the dividing unit 4911 may divide the image into slices based on map information or location information so that each slice corresponds to a predetermined coordinate space.

[0207] When dividing into tiles, the dividing unit 4911 divides the position information and the attribute information independently. For example, the dividing unit 4911 divides a slice into tiles according to the amount of data or the amount of processing. For example, the dividing unit 4911 determines whether the amount of data of a slice (for example, the number of three-dimensional points included in the slice) is greater than a predetermined threshold. If the amount of data of a slice is greater than the threshold, the dividing unit 4911 divides the slice into tiles. If the amount of data of a slice is less than the threshold, the dividing unit 4911 does not divide the slice into tiles.

[0208] For example, the dividing unit 4911 divides a slice into tiles so that the processing amount or processing time in the decoding device is within a certain range (a predetermined value or less). This makes the processing amount per tile in the decoding device constant, facilitating distributed processing in the decoding device.

[0209] Furthermore, when the processing amount differs between the position information and the attribute information, for example, when the processing amount of the position information is greater than the processing amount of the attribute information, the dividing unit 4911 divides the position information into a greater number of divisions than the attribute information.

[0210] Also, for example, depending on the content, if the decoding device may decode and display the position information quickly and decode and display the attribute information later slowly, the division unit 4911 may divide the position information into a larger number of parts than the attribute information. This allows the decoding device to process a larger number of pieces of position information in parallel, thereby making it possible to process the position information faster than the attribute information.

[0211] Note that the decoding device does not necessarily need to process sliced ​​or tiled data in parallel, and may determine whether to process them in parallel depending on the number or capabilities of the decoding processing units.

[0212] By dividing the data in the above manner, adaptive encoding according to the content or object can be realized. Also, parallel processing can be realized in the decoding process. This improves the flexibility of the point cloud encoding system or the point cloud decoding system.

[0213] 25 is a diagram showing examples of slice and tile division patterns. DU in the diagram is a data unit (DataUnit) and indicates tile or slice data. Each DU includes a slice index (SliceIndex) and a tile index (TileIndex). The number in the upper right corner of the DU in the diagram indicates the slice index, and the number in the lower left corner of the DU indicates the tile index.

[0214] In pattern 1, the number of divisions and the division method are the same for G slices and A slices in slice division. In tile division, the number of divisions and the division method for G slices are different from the number of divisions and the division method for A slices. Furthermore, the same number of divisions and the division method are used among multiple G slices. The same number of divisions and the division method are used among multiple A slices.

[0215] In pattern 2, the number of divisions and the division method are the same for G slices and A slices in slice division. The number of divisions and the division method for G slices are different from the number of divisions and the division method for A slices in tile division. Furthermore, the number of divisions and the division method differ between multiple G slices. The number of divisions and the division method differ between multiple A slices.

[0216] Next, a method for encoding divided data will be described. A three-dimensional data encoding device (first encoding unit 4910) encodes each of the divided data. When encoding attribute information, the three-dimensional data encoding device generates dependency information as additional information, which indicates which configuration information (position information, additional information, or other attribute information) was used for encoding. In other words, the dependency information indicates, for example, the configuration information of the reference destination (dependency destination). In this case, the three-dimensional data encoding device generates dependency information based on configuration information corresponding to the division shape of the attribute information. Note that the three-dimensional data encoding device may generate dependency information based on configuration information corresponding to a plurality of division shapes.

[0217] The dependency information may be generated by the three-dimensional data encoding device, and the generated dependency information may be sent to the three-dimensional data decoding device. Alternatively, the three-dimensional data decoding device may generate the dependency information, and the three-dimensional data encoding device may not send the dependency information. Furthermore, the dependency relationships used by the three-dimensional data encoding device may be determined in advance, and the three-dimensional data encoding device may not send the dependency information.

[0218] Figure 26 is a diagram showing an example of the dependency relationships of each data. The tip of the arrow in the diagram indicates the dependency destination, and the start of the arrow indicates the dependency source. The three-dimensional data decoding device decodes data in the order from the dependency destination to the dependency source. Furthermore, data shown by solid lines in the diagram is data that is actually sent, and data shown by dotted lines is data that is not sent.

[0219] In the figure, G indicates location information, and A indicates attribute information. s1 indicates the position information of slice number 1, and G s2 indicates the position information of slice number 2. G s1t1 indicates the position information of slice number 1 and tile number 1, and G s1t2 indicates the position information of slice number 1 and tile number 2, and G s2t1 indicates the position information of slice number 2 and tile number 1, and G s2t2 indicates the position information of slice number 2 and tile number 2. Similarly, A s1 indicates the attribute information of slice number 1, and A s2 indicates the attribute information of slice number 2. s1t1 indicates the attribute information of slice number 1 and tile number 1, and A s1t2 indicates the attribute information of slice number 1 and tile number 2, and A s2t1 indicates the attribute information of slice number 2 and tile number 1, and A s2t2 indicates attribute information of slice number 2 and tile number 2.

[0220] Mslice indicates slice additional information, MGtile indicates position tile additional information, and MAtile indicates attribute tile additional information. s1t1 is attribute information As1t1 D s2t1 is attribute information A s2t1 This shows dependency information for

[0221] Furthermore, the three-dimensional data encoding device may rearrange the data in decoding order so that rearrangement of the data is not required in the three-dimensional data decoding device. Note that the data may be rearranged in the three-dimensional data decoding device, or the data may be rearranged in both the three-dimensional data encoding device and the three-dimensional data decoding device.

[0222] FIG. 27 is a diagram showing an example of the data decoding order. In the example of FIG. 27, decoding is performed in order from the left data. When data has a dependency relationship, the three-dimensional data decoding device decodes the dependent data first. For example, the three-dimensional data encoding device rearranges the data in advance to achieve this order before sending it. Note that any order is acceptable as long as the dependent data comes first. The three-dimensional data encoding device may also send additional information and dependency information before the data.

[0223] 28 is a flowchart showing the flow of processing by the three-dimensional data encoding device. First, the three-dimensional data encoding device encodes data of multiple slices or tiles as described above (S4901). Next, the three-dimensional data encoding device rearranges the data so that the dependent data comes first, as shown in FIG. 27 (S4902). Next, the three-dimensional data encoding device multiplexes the rearranged data (into NAL units) (S4903).

[0224] Next, a description will be given of the configuration of the combining unit 4925 included in the first decoding unit 4920. Fig. 29 is a block diagram showing the configuration of the combining unit 4925. The combining unit 4925 includes a position information tile combining unit 4941 (geometry tile combiner), an attribute information tile combining unit 4942 (attribute tile combiner), and a slice combining unit (slice combiner).

[0225] The position information tile combining unit 4941 generates multiple slice position information pieces by combining multiple pieces of divided position information pieces using the position tile additional information. The attribute information tile combining unit 4942 generates multiple slice attribute information pieces by combining multiple pieces of divided attribute information pieces using the attribute tile additional information.

[0226] The slice combining unit 4943 generates position information by combining a plurality of slice position information pieces using the slice additional information. Also, the slice combining unit 4943 generates attribute information by combining a plurality of slice attribute information pieces using the slice additional information.

[0227] The number of slices or tiles to be divided is equal to or greater than 1. In other words, division into slices or tiles does not necessarily have to be performed.

[0228] Although an example in which tile division is performed after slice division has been shown here, slice division may be performed after tile division. Furthermore, new division types may be defined in addition to slices and tiles, and division may be performed using three or more division types.

[0229] Next, the structure of coded data divided into slices or tiles and a method of storing the coded data in NAL units (multiplexing method) will be described. Fig. 30 is a diagram showing the structure of coded data and a method of storing the coded data in NAL units.

[0230] The coded data (division position information and division attribute information) is stored in the payload of the NAL unit.

[0231] The encoded data includes a header and a payload. The header includes identification information for identifying the data included in the payload. This identification information includes, for example, the type of slice division or tile division (slice_type, tile_type), index information for identifying a slice or tile (slice_idx, tile_idx), position information of the data (slice or tile), or the address of the data. The index information for identifying a slice is also referred to as a slice index (SliceIndex). The index information for identifying a tile is also referred to as a tile index (TileIndex). The type of division may be, for example, a method based on the object shape as described above, a method based on map information or position information, or a method based on the amount of data or processing amount.

[0232] Note that all or part of the above information may be stored in either the header of the division position information or the header of the division attribute information, but not in the other. For example, if the same division method is used for the position information and the attribute information, the division type (slice_type, tile_type) and index information (slice_idx, tile_idx) are the same for the position information and the attribute information. Therefore, this information may be included in the header of either the position information or the attribute information. For example, if the attribute information depends on the position information, the position information is processed first. Therefore, this information may be included in the header of the position information, but not in the header of the attribute information. In this case, the three-dimensional data decoding device determines, for example, that the dependent attribute information belongs to the same slice or tile as the slice or tile of the dependent position information.

[0233] Furthermore, additional information related to slice division or tile division (slice additional information, position tile additional information, or attribute tile additional information), and dependency information indicating dependency relationships may be stored in an existing parameter set (GPS, APS, position SPS, attribute SPS, etc.) and transmitted. If the division method changes for each frame, information indicating the division method may be stored in a parameter set for each frame (GPS or APS, etc.). If the division method does not change within a sequence, information indicating the division method may be stored in a parameter set for each sequence (position SPS or attribute SPS). Furthermore, if the same division method is used for position information and attribute information, information indicating the division method may be stored in a parameter set of the PCC stream (stream PS).

[0234] The above information may be stored in any one of the above parameter sets, or in multiple parameter sets. Alternatively, a parameter set for tile division or slice division may be defined, and the above information may be stored in the parameter set. Alternatively, the information may be stored in a header of the encoded data.

[0235] Furthermore, the header of the encoded data includes identification information indicating a dependency relationship. That is, when there is a dependency relationship between data, the header includes identification information for referencing the dependency from the dependency source. For example, the header of the dependency data includes identification information for identifying the data. The header of the dependency source data includes identification information indicating the dependency. Note that, when the identification information for identifying data, the additional information related to slice division or tile division, and the identification information indicating the dependency relationship can be identified or derived from other information, these pieces of information may be omitted.

[0236] Next, the flow of the encoding process and decoding process of point cloud data according to this embodiment will be described. Fig. 31 is a flowchart of the encoding process of point cloud data according to this embodiment.

[0237] First, the three-dimensional data encoding device determines the division method to be used (S4911). This division method includes whether or not to perform slice division and whether or not to perform tile division. The division method may also include the number of divisions when performing slice division or tile division, and the type of division. The type of division may be a method based on the object shape as described above, a method based on map information or position information, or a method based on the amount of data or the amount of processing. The division method may be determined in advance.

[0238] If slice division is performed (Yes in S4912), the three-dimensional data encoding device generates a plurality of slice position information and a plurality of slice attribute information by dividing the position information and the attribute information together (S4913). The three-dimensional data encoding device also generates slice additional information related to the slice division. Note that the three-dimensional data encoding device may divide the position information and the attribute information independently.

[0239] If tile division is performed (Yes in S4914), the three-dimensional data encoding device generates multiple pieces of division position information and multiple pieces of division attribute information by independently dividing multiple pieces of slice position information and multiple pieces of slice attribute information (or position information and attribute information) (S4915). The three-dimensional data encoding device also generates position tile additional information and attribute tile additional information related to the tile division. Note that the three-dimensional data encoding device may divide the slice position information and slice attribute information together.

[0240] Next, the three-dimensional data encoding device generates a plurality of pieces of encoding position information and a plurality of pieces of encoding attribute information by encoding each of the plurality of pieces of division position information and the plurality of pieces of division attribute information (S4916). The three-dimensional data encoding device also generates dependency relationship information.

[0241] Next, the three-dimensional data encoding device generates encoded data (encoded stream) by grouping (multiplexing) the plurality of pieces of encoding position information, the plurality of pieces of encoding attribute information, and the additional information into NAL units (S4917).The three-dimensional data encoding device also transmits the generated encoded data.

[0242] 32 is a flowchart of a decoding process of point cloud data according to this embodiment. First, the three-dimensional data decoding device determines the division method by analyzing additional information related to the division method (slice additional information, position tile additional information, and attribute tile additional information) included in the coded data (coded stream) (S4921). This division method includes whether or not to perform slice division and whether or not to perform tile division. The division method may also include the number of divisions when performing slice division or tile division, the type of division, etc.

[0243] Next, the three-dimensional data decoding device generates split position information and split attribute information by decoding the multiple pieces of coded position information and multiple pieces of coded attribute information contained in the coded data using the dependency information contained in the coded data (S4922).

[0244] If the additional information indicates that tile division has been performed (Yes in S4923), the three-dimensional data decoding device generates a plurality of slice position information and a plurality of slice attribute information by combining the plurality of pieces of division position information and the plurality of pieces of division attribute information using respective methods based on the position tile additional information and the attribute tile additional information (S4924). Note that the three-dimensional data decoding device may combine the plurality of pieces of division position information and the plurality of pieces of division attribute information using the same method.

[0245] When the additional information indicates that slice division has been performed (Yes in S4925), the three-dimensional data decoding device generates position information and attribute information by combining, based on the slice additional information, a plurality of pieces of slice position information and a plurality of pieces of slice attribute information (a plurality of pieces of division position information and a plurality of pieces of division attribute information) in the same manner (S4926). Note that the three-dimensional data decoding device may combine, using different methods, a plurality of pieces of slice position information and a plurality of pieces of slice attribute information.

[0246] As described above, the three-dimensional data encoding device according to this embodiment performs the processing shown in Fig. 33. First, the three-dimensional data encoding device divides a target space containing a plurality of three-dimensional points into a plurality of divided data (e.g., tiles) contained in a plurality of divided subspaces (e.g., slices), each containing one or more three-dimensional points. Here, the divided data is one or more data aggregates contained in a subspace and containing one or more three-dimensional points. The divided data may also be a space, and may include a space that does not contain three-dimensional points. Furthermore, one subspace may contain multiple divided data, or one subspace may contain one divided data. Note that multiple subspaces may be set in the target space, or one subspace may be set in the target space.

[0247] Next, the three-dimensional data encoding device generates a plurality of coded data corresponding to each of the plurality of divided data by encoding each of the plurality of divided data (S4931). The three-dimensional data encoding device generates a bitstream including the plurality of coded data and a plurality of control information (e.g., the header shown in FIG. 30) for each of the plurality of coded data (S4932). Each of the plurality of control information stores a first identifier (e.g., slice_idx) indicating a subspace corresponding to the coded data corresponding to the control information, and a second identifier (e.g., tile_idx) indicating divided data corresponding to the coded data corresponding to the control information.

[0248] This allows a three-dimensional data decoding device that decodes a bitstream generated by a three-dimensional data encoding device to easily restore the target space by combining data from the plurality of divided data using the first identifier and the second identifier, thereby reducing the amount of processing required in the three-dimensional data decoding device.

[0249] For example, the three-dimensional data encoding device encodes position information and attribute information of three-dimensional points included in each of the plurality of pieces of divided data. Each of the plurality of pieces of coded data includes coded data for the position information and coded data for the attribute information. Each of the plurality of pieces of control information includes control information for the coded data for the position information and control information for the coded data for the attribute information. The first identifier and the second identifier are stored in the control information for the coded data for the position information.

[0250] For example, in a bitstream, each of the plurality of pieces of control information is placed before the coded data corresponding to that control information.

[0251] Furthermore, a three-dimensional data encoding device may be configured such that a target space containing a plurality of three-dimensional points is set to one or more subspaces, the subspaces contain one or more divided data each containing one or more three-dimensional points, and the device generates a plurality of coded data corresponding to each of the plurality of divided data by encoding each of the divided data, and generates a bit stream including the plurality of coded data and a plurality of control information for each of the plurality of coded data, and each of the plurality of control information stores a first identifier indicating the subspace corresponding to the coded data corresponding to the control information, and a second identifier indicating the divided data corresponding to the coded data corresponding to the control information.

[0252] For example, the three-dimensional data encoding device includes a processor and a memory, and the processor performs the above-mentioned processing using the memory.

[0253] Moreover, the three-dimensional data decoding device according to this embodiment performs the processing shown in FIG. 34. First, the three-dimensional data decoding device acquires, from a bitstream including a plurality of coded data pieces generated by encoding a plurality of divided data pieces (e.g., tiles) each including one or more three-dimensional points and included in a plurality of subspaces (e.g., slices) obtained by dividing a target space including a plurality of three-dimensional points, and a plurality of control information pieces (e.g., a header shown in FIG. 30) for each of the coded data pieces, a first identifier (e.g., slice_idx) indicating a subspace corresponding to the coded data piece corresponding to the control information piece, and a second identifier (e.g., tile_idx) indicating divided data piece corresponding to the coded data piece corresponding to the control information piece, both of which are stored in the plurality of control information pieces (S4941). Next, the three-dimensional data decoding device restores a plurality of divided data pieces by decoding the plurality of coded data pieces (S4942). Next, the three-dimensional data decoding device restores the target space by combining the plurality of divided data pieces using the first identifier and the second identifier (S4943). For example, the three-dimensional data encoding device uses the second identifier to combine multiple divided data to restore multiple subspaces, and uses the first identifier to combine multiple subspaces to restore the target space (multiple three-dimensional points). Note that the three-dimensional data decoding device may use at least one of the first identifier and the second identifier to obtain coded data of a desired subspace or divided data from the bitstream, and selectively decode or preferentially decode the obtained coded data.

[0254] This allows the three-dimensional data decoding device to easily restore the target space by combining the data of the plurality of divided data using the first identifier and the second identifier, thereby reducing the amount of processing in the three-dimensional data decoding device.

[0255] For example, each of the plurality of coded data is generated by encoding position information and attribute information of a three-dimensional point included in the corresponding divided data, and includes coded data of the position information and coded data of the attribute information. Each of the plurality of control information includes control information for the coded data of the position information and control information for the coded data of the attribute information. The first identifier and the second identifier are stored in the control information of the coded data of the position information.

[0256] For example, in the bitstream, control information precedes the corresponding coded data.

[0257] For example, the three-dimensional data decoding device includes a processor and a memory, and the processor performs the above processing using the memory.

[0258] (Embodiment 5) In position information encoding using neighbor dependency, the higher the density of the point cloud, the more likely it is that encoding efficiency will improve. In this embodiment, the three-dimensional data encoding device combines point cloud data of consecutive frames to collectively encode the point cloud data of consecutive frames. At this time, the three-dimensional data encoding device generates encoded data that includes information for identifying the frame to which each leaf node included in the combined point cloud data belongs.

[0259] Here, the point cloud data of consecutive frames is likely to be similar. Therefore, the upper level of the occupancy code is likely to be the same for consecutive frames. In other words, by encoding consecutive frames together, the upper level of the occupancy code can be shared.

[0260] Furthermore, the frame to which a point group belongs is distinguished at the leaf node by encoding the frame index.

[0261] Fig. 35 is a diagram showing an image of generating a tree structure and an occupancy code from point cloud data of N PCC (Point Cloud Compression) frames. In the figure, points inside the arrows indicate points belonging to each PCC frame. First, a frame index for identifying the frame is assigned to each point belonging to each PCC frame.

[0262] Next, the points belonging to the N frames are converted into a tree structure, and an occupancy code is generated. Specifically, for each point, it is determined which leaf node in the tree structure the point belongs to. In the figure, the tree structure represents a set of nodes. Starting from the top node, it is determined which node the point belongs to. The determination result for each node is encoded as an occupancy code. The occupancy code is common to the N frames.

[0263] A node may contain points from different frames with different frame indices. If the octree resolution is small, points from the same frame with the same frame index may also exist.

[0264] In the lowest level nodes (leaf nodes), points belonging to multiple frames may be mixed (overlapped).

[0265] In the tree structure and occupancy code, the higher level tree structure and occupancy code may be a common component in all frames, while the lower level tree structure and occupancy code may be an individual component for each frame, or a mixture of common and individual components.

[0266] For example, in the lowest level nodes such as leaf nodes, zero or more points with frame indexes are generated, and information indicating the number of points and information on the frame index for each point are generated. This information can also be said to be individual information in a frame.

[0267] Fig. 36 is a diagram showing an example of frame merging. As shown in Fig. 36(a), by combining multiple frames to generate a tree structure, the density of frame points included in the same node increases. Furthermore, by sharing the tree structure, the amount of data for the occupancy code can be reduced. These features may improve the coding rate.

[0268] Furthermore, as shown in FIG. 36(b), the individual components of the occupancy code in the tree structure become denser, which increases the effectiveness of arithmetic coding, and therefore may improve the coding rate.

[0269] The following description will be given using an example of combining multiple PCC frames that are temporally different, but it can also be applied to cases where there are not multiple frames, i.e., when frames are not combined (N=1). Furthermore, the multiple point cloud data to be combined is not limited to multiple frames, i.e., point cloud data of the same object at different times. In other words, the following method can also be applied to combining multiple point cloud data that are spatially or spatiotemporally different. Furthermore, the following method can also be applied to combining point cloud data or point cloud files with different content.

[0270] Fig. 37 is a diagram showing an example of combining multiple PCC frames that are different in time. Fig. 37 shows an example of acquiring point cloud data using a sensor such as LiDAR while a car is moving. The dotted lines indicate the sensor's acquisition range for each frame, i.e., the area of ​​the point cloud data. If the sensor's acquisition range is large, the range of the point cloud data will also be large.

[0271] The method of combining and encoding point cloud data is effective for point cloud data such as the following: For example, in the example shown in Figure 37, a car is moving and frames are identified by scanning 360° around the car. That is, the next frame, Frame 2, corresponds to another 360° scan after the car has moved in the X direction.

[0272] In this case, there is a possibility that frame 1 and frame 2 contain the same point cloud data because there are overlapping areas. Therefore, there is a possibility that encoding efficiency can be improved by combining and encoding frame 1 and frame 2. It is also possible to combine more frames. However, increasing the number of frames to be combined increases the number of bits required to encode the frame index added to the leaf node.

[0273] Furthermore, point cloud data may be acquired by sensors at different positions. Thus, each point cloud data acquired from each position may be used as a frame. That is, the multiple frames may be point cloud data acquired by a single sensor, or may be point cloud data acquired by multiple sensors. Furthermore, some or all of the objects may be the same or different between the multiple frames.

[0274] Next, the flow of three-dimensional data encoding processing according to this embodiment will be described. Fig. 38 is a flowchart of the three-dimensional data encoding processing. The three-dimensional data encoding device reads point cloud data of all N frames based on the number of frames to be combined, N, which is the number of frames to be combined.

[0275] First, the three-dimensional data encoding device determines the number of combined frames N (S5401). For example, this number of combined frames N is specified by the user.

[0276] Next, the three-dimensional data encoding device acquires point cloud data (S5402), and then records the frame index of the acquired point cloud data (S5403).

[0277] If N frames have not been processed (No in S5404), the three-dimensional data encoding device specifies the next point cloud data (S5405) and performs the processes from step S5402 onwards on the specified point cloud data.

[0278] On the other hand, if N frames have already been processed (Yes in S5404), the three-dimensional data encoding device combines the N frames and encodes the combined frame (S5406).

[0279] 39 is a flowchart of the encoding process (S5406). First, the three-dimensional data encoding device generates common information common to N frames (S5411). For example, the common information includes an occupancy code and information indicating the number N of combined frames.

[0280] Next, the three-dimensional data encoding device generates individual information, which is information individual to each frame (S5412). For example, the individual information includes the number of points included in the leaf node and the frame index of the points included in the leaf node.

[0281] Next, the three-dimensional data encoding device combines the common information and the individual information and encodes the combined information to generate encoded data (S5413). Next, the three-dimensional data encoding device generates additional information (metadata) related to the frame combination and encodes the generated additional information (S5414).

[0282] Next, the flow of the three-dimensional data decoding process according to this embodiment will be described with reference to Fig. 40, which is a flowchart of the three-dimensional data decoding process.

[0283] First, the three-dimensional data decoding device obtains the number of spliced ​​frames N from the bitstream (S5421). Next, the three-dimensional data encoding device obtains encoded data from the bitstream (S5422). Next, the three-dimensional data decoding device obtains point cloud data and frame indices by decoding the encoded data (S5423). Finally, the three-dimensional data decoding device divides the decoded point cloud data using the frame indices (S5424).

[0284] 41 is a flowchart of the decoding and division processing (S5423 and S5424). First, the three-dimensional data decoding device decodes (obtains) the common information and individual information from the coded data (bit stream) (S5431).

[0285] Next, the 3D data decoding device determines whether to decode a single frame or multiple frames (S5432). For example, whether to decode a single frame or multiple frames may be specified externally. Here, the multiple frames may be all of the combined frames or a portion of the frames. For example, the 3D data decoding device may determine to decode specific frames required by an application and not decode frames that are not required. Alternatively, if real-time decoding is required, the 3D data decoding device may determine to decode a single frame of the combined multiple frames.

[0286] When decoding a single frame (Yes in S5432), the three-dimensional data decoding device extracts individual information corresponding to the specified single frame index from the decoded individual information, and decodes the extracted individual information to restore the point cloud data of the frame corresponding to the specified frame index (S5433).

[0287] On the other hand, when decoding multiple frames (No in S5432), the three-dimensional data decoding device extracts individual information corresponding to the frame indexes of the specified multiple frames (or all frames) and decodes the extracted individual information to restore the point cloud data of the specified multiple frames (S5434). Next, the three-dimensional data decoding device divides the decoded point cloud data (individual information) based on the frame indexes (S5435). In other words, the three-dimensional data decoding device divides the decoded point cloud data into multiple frames.

[0288] The three-dimensional data decoding device may decode the data of all the combined frames at once and divide the decoded data into individual frames, or may decode any part of all the combined frames at once and divide the decoded data into individual frames. Furthermore, the three-dimensional data decoding device may independently decode a predetermined unit frame consisting of multiple frames.

[0289] The configuration of the three-dimensional data encoding device according to this embodiment will be described below. Fig. 42 is a block diagram showing the configuration of an encoding unit 5410 included in the three-dimensional data encoding device according to this embodiment. The encoding unit 5410 generates encoded data (encoded stream) by encoding point group data (point cloud). This encoding unit 5410 includes a division unit 5411, a plurality of position information encoding units 5412, a plurality of attribute information encoding units 5413, an additional information encoding unit 5414, and a multiplexing unit 5415.

[0290] The dividing unit 5411 divides point cloud data of multiple frames to generate multiple pieces of divided data for multiple frames. Specifically, the dividing unit 5411 divides the space of the point cloud data of each frame into multiple subspaces to generate multiple pieces of divided data. Here, a subspace is one of a tile and a slice, or a combination of a tile and a slice. More specifically, the point cloud data includes position information, attribute information (color, reflectance, etc.), and additional information. In addition, a frame number is input to the dividing unit 5411. The dividing unit 5411 divides the position information of each frame into multiple pieces of divided position information and divides the attribute information of each frame into multiple pieces of divided attribute information. In addition, the dividing unit 5411 generates additional information related to the division.

[0291] For example, the dividing unit 5411 first divides the point cloud into tiles, and then further divides the obtained tiles into slices.

[0292] The multiple position information encoding units 5412 encode the multiple pieces of divided position information to generate multiple pieces of encoded position information. For example, the position information encoding unit 5412 encodes the divided position information using an N-ary tree structure such as an octree. Specifically, in an octree, the target space is divided into eight nodes (subspaces), and 8-bit information (occupancy code) indicating whether or not a point cloud is included in each node is generated. Furthermore, the node including the point cloud is further divided into eight nodes, and 8-bit information indicating whether or not the point cloud is included in each of the eight nodes is generated. This process is repeated until the number of point clouds included in a predetermined layer or node falls below a threshold. For example, the multiple position information encoding units 5412 process the multiple pieces of divided position information in parallel.

[0293] The attribute information encoding unit 4632 generates encoded attribute information, which is encoded data, by encoding using the configuration information generated by the position information encoding unit 4631. For example, the attribute information encoding unit 4632 determines a reference point (reference node) to be referenced when encoding a target point (target node) to be processed, based on the octree structure generated by the position information encoding unit 4631. For example, the attribute information encoding unit 4632 references a peripheral node or adjacent node whose parent node in the octree is the same as that of the target node. Note that the method of determining the reference relationship is not limited to this.

[0294] Furthermore, the encoding process of the position information or attribute information may include at least one of a quantization process, a prediction process, and an arithmetic coding process. In this case, the reference means using a reference node to calculate a predicted value of the attribute information, or using the state of the reference node (e.g., occupancy information indicating whether the reference node includes a point group) to determine an encoding parameter. For example, the encoding parameter is a quantization parameter in a quantization process, or a context in an arithmetic coding process.

[0295] The attribute information encoding units 5413 encode the divided attribute information to generate the coded attribute information, for example, the attribute information encoding units 5413 process the divided attribute information in parallel.

[0296] The additional information encoding unit 5414 generates encoded additional information by encoding the additional information included in the point cloud data and the additional information related to the data division generated by the division unit 5411 at the time of division.

[0297] The multiplexing unit 5415 multiplexes a plurality of pieces of encoding position information, a plurality of pieces of encoding attribute information, and a plurality of pieces of encoding additional information for a plurality of frames to generate encoded data (encoded stream), and transmits the generated encoded data. The encoded additional information is also used during decoding.

[0298] 43 is a block diagram of the dividing unit 5411. The dividing unit 5411 includes a tile dividing unit 5421 and a slice dividing unit 5422.

[0299] The tile dividing unit 5421 generates multiple pieces of tile position information by dividing each piece of position information (Position (Geometry)) of multiple frames into tiles. The tile dividing unit 5421 also generates multiple pieces of tile attribute information by dividing each piece of attribute information (Attribute) of multiple frames into tiles. The tile dividing unit 5421 also outputs tile additional information (Tile MetaData) including information related to the tile division and information generated during the tile division.

[0300] The slice division unit 5422 generates a plurality of pieces of division position information (a plurality of pieces of slice position information) by dividing a plurality of pieces of tile position information into slices. The slice division unit 5422 also generates a plurality of pieces of division attribute information (a plurality of pieces of slice attribute information) by dividing a plurality of pieces of tile attribute information into slices. The slice division unit 5422 also outputs slice additional information (Slice MetaData) including information related to the slice division and information generated in the slice division.

[0301] Furthermore, the dividing unit 5411 uses a frame number (frame index) to indicate the origin coordinates, attribute information, and the like in the dividing process.

[0302] 44 is a block diagram of the positional information encoding unit 5412. The positional information encoding unit 5412 includes a frame index generation unit 5431 and an entropy encoding unit 5432.

[0303] The frame index generating unit 5431 determines a frame index value based on the frame number and adds the determined frame index to the position information. The entropy coding unit 5432 generates coded position information by entropy coding the division position information to which the frame index has been added.

[0304] 45 is a block diagram of the attribute information encoding unit 5413. The attribute information encoding unit 5413 includes a frame index generation unit 5441 and an entropy encoding unit 5442.

[0305] The frame index generating unit 5441 determines a frame index value based on the frame number and adds the determined frame index to the attribute information. The entropy encoding unit 5442 generates encoded attribute information by entropy encoding the divided attribute information to which the frame index has been added.

[0306] Next, the flow of the encoding process and decoding process of point cloud data according to this embodiment will be described. Fig. 46 is a flowchart of the encoding process of point cloud data according to this embodiment.

[0307] First, the three-dimensional data encoding device determines the division method to be used (S5441). This division method includes whether to perform division into slices or whether to perform division into tiles. The division method may also include the number of divisions, the type of division, etc., when dividing into slices or tiles.

[0308] If tile division is to be performed (Yes in S5442), the three-dimensional data encoding device generates multiple pieces of tile position information and multiple pieces of tile attribute information by dividing the position information and the attribute information (S5443). The three-dimensional data encoding device also generates tile additional information related to the tile division.

[0309] If slice division is performed (Yes in S5444), the three-dimensional data encoding device divides the plurality of tile position information and the plurality of tile attribute information (or the position information and the attribute information) to generate a plurality of division position information and a plurality of division attribute information (S5445). In addition, the three-dimensional data encoding device generates slice additional information related to the slice division.

[0310] Next, the three-dimensional data encoding device generates a plurality of pieces of encoding position information and a plurality of pieces of encoding attribute information by encoding each of the plurality of pieces of division position information and the plurality of pieces of division attribute information with a frame index (S5446). The three-dimensional data encoding device also generates dependency relationship information.

[0311] Next, the three-dimensional data encoding device generates encoded data (encoded stream) by grouping (multiplexing) the plurality of pieces of encoding position information, the plurality of pieces of encoding attribute information, and the additional information into NAL units (S5447).The three-dimensional data encoding device also transmits the generated encoded data.

[0312] 47 is a flowchart of the encoding process (S5446). First, the three-dimensional data encoding device encodes the division position information (S5451). Next, the three-dimensional data encoding device encodes the frame index for the division position information (S5452).

[0313] If division attribute information exists (Yes in S5453), the three-dimensional data encoding device encodes the division attribute information (S5454) and encodes a frame index for the division attribute information (S5455). On the other hand, if division attribute information does not exist (No in S5453), the three-dimensional data encoding device does not encode the division attribute information or the frame index for the division attribute information. Note that the frame index may be stored in either or both of the division position information and the division attribute information.

[0314] The three-dimensional data encoding device may encode the attribute information using a frame index, or may encode the attribute information without using a frame index. In other words, the three-dimensional data encoding device may use a frame index to identify the frame to which each point belongs and encode the data for each frame, or may encode points belonging to all frames without identifying the frame.

[0315] The configuration of the three-dimensional data decoding device according to this embodiment will be described below. Fig. 48 is a block diagram showing the configuration of a decoding unit 5450. The decoding unit 5450 restores the point cloud data by decoding coded data (coded stream) generated by coding the point cloud data. The decoding unit 5450 includes a demultiplexing unit 5451, a plurality of position information decoding units 5452, a plurality of attribute information decoding units 5453, an additional information decoding unit 5454, and a combining unit 5455.

[0316] The demultiplexing unit 5451 demultiplexes the coded data (coded stream) to generate a plurality of pieces of coding position information, a plurality of pieces of coding attribute information, and coded additional information.

[0317] The position information decoding units 5452 generate a plurality of pieces of divided position information by decoding the plurality of pieces of encoded position information. For example, the position information decoding units 5452 process the plurality of pieces of encoded position information in parallel.

[0318] The attribute information decoding units 5453 generate a plurality of pieces of divided attribute information by decoding the plurality of pieces of encoded attribute information. For example, the attribute information decoding units 5453 process the plurality of pieces of encoded attribute information in parallel.

[0319] The plurality of additional information decoders 5454 generate additional information by decoding the encoded additional information.

[0320] The combining unit 5455 generates position information by combining multiple pieces of divided position information using the additional information. The combining unit 5455 generates attribute information by combining multiple pieces of divided attribute information using the additional information. The combining unit 5455 also divides the position information and attribute information into multiple frames of position information and multiple frames of attribute information using a frame index.

[0321] 49 is a block diagram of the position information decoding unit 5452. The position information decoding unit 5452 includes an entropy decoding unit 5461 and a frame index obtaining unit 5462. The entropy decoding unit 5461 generates division position information by entropy decoding the encoded position information. The frame index obtaining unit 5462 obtains a frame index from the division position information.

[0322] 50 is a block diagram of the attribute information decoding unit 5453. The attribute information decoding unit 5453 includes an entropy decoding unit 5471 and a frame index obtaining unit 5472. The entropy decoding unit 5471 generates divided attribute information by entropy decoding the encoded attribute information. The frame index obtaining unit 5472 obtains a frame index from the divided attribute information.

[0323] 51 is a diagram showing the configuration of the combining unit 5455. The combining unit 5455 generates position information by combining multiple pieces of divided position information. The combining unit 5455 generates attribute information by combining multiple pieces of divided attribute information. The combining unit 5455 also uses a frame index to divide the position information and attribute information into multiple frames of position information and multiple frames of attribute information.

[0324] 52 is a flowchart of a decoding process of point cloud data according to this embodiment. First, the three-dimensional data decoding device determines the division method by analyzing additional information (slice additional information and tile additional information) related to the division method included in the coded data (coded stream) (S5461). This division method includes whether or not to perform slice division and whether or not to perform tile division. The division method may also include the number of divisions when performing slice division or tile division, the type of division, etc.

[0325] Next, the three-dimensional data decoding device generates split position information and split attribute information by decoding the multiple pieces of coded position information and multiple pieces of coded attribute information contained in the coded data using the dependency information contained in the coded data (S5462).

[0326] If the additional information indicates that slice division has been performed (Yes in S5463), the 3D data decoding device generates multiple pieces of tile position information by combining multiple pieces of division position information, and generates multiple pieces of tile attribute information by combining multiple pieces of division attribute information, based on the slice additional information (S5464). Here, the multiple pieces of division position information, the multiple pieces of division attribute information, the multiple pieces of tile position information, and the multiple pieces of tile attribute information each include a frame index.

[0327] If the additional information indicates that tile division has been performed (Yes in S5465), the 3D data decoding device generates position information by combining multiple pieces of tile position information (multiple pieces of division position information) based on the tile additional information, and generates attribute information by combining multiple pieces of tile attribute information (multiple pieces of division attribute information) (S5466). Here, the multiple pieces of tile position information, the multiple pieces of tile attribute information, the position information, and the attribute information include a frame index.

[0328] 53 is a flowchart of the decoding process (S5464 or S5466). First, the three-dimensional data decoding device decodes the division position information (slice position information) (S5471). Next, the three-dimensional data decoding device decodes the frame index for the division position information (S5472).

[0329] If the split attribute information exists (Yes in S5473), the three-dimensional data decoding device decodes the split attribute information (S5474) and decodes the frame index for the split attribute information (S5475). On the other hand, if the split attribute information does not exist (No in S5473), the three-dimensional data decoding device does not decode the split attribute information or the frame index for the split attribute information.

[0330] The three-dimensional data decoding device may decode the attribute information using a frame index, or may decode the attribute information without using a frame index.

[0331] The coding unit for frame splicing will be described below. Figure 54 is a diagram showing an example of a frame splicing pattern. The example in the figure shows a case where, for example, PCC frames are in time series and data generation and encoding are performed in real time.

[0332] 54(a) shows a case where four frames are fixedly joined together, and the three-dimensional data encoding device waits for four frames of data to be generated before generating encoded data.

[0333] 54(b) shows a case where the number of frames changes adaptively. For example, a three-dimensional data encoding device changes the number of combined frames to adjust the amount of encoded data in rate control.

[0334] The three-dimensional data encoding device may not combine frames if there is a possibility that combining frames will not be effective. Also, the three-dimensional data encoding device may switch between combining frames and not combining frames.

[0335] Figure 54(c) shows an example where a portion of the frames to be combined overlaps with a portion of the next frames to be combined. This example is useful when real-time or low-delay processing is required, such as transmitting frames in order of encoding.

[0336] Figure 55 is a diagram showing an example of the structure of a PCC frame. The three-dimensional data encoding device may configure the frames to be combined so that they include at least data units that can be decoded independently. For example, as shown in (a) of Figure 55, if all PCC frames are intra-coded and can be decoded independently, any of the above patterns can be applied.

[0337] Also, as shown in (b) of Figure 55, when inter prediction is applied and a random access unit such as GOF (group of frames) is set, the three-dimensional data encoding device may combine data using the GOF unit as the smallest unit.

[0338] The three-dimensional data encoding device may encode the common information and the individual information together, or may encode each separately. Furthermore, the three-dimensional data encoding device may use a common data structure for the common information and the individual information, or may use different data structures.

[0339] Furthermore, the three-dimensional data encoding device may generate an occupancy code for each frame, and then compare the occupancy codes of multiple frames, determine whether there are many common parts between the occupancy codes of the multiple frames based on a predetermined criterion, and generate common information if there are many common parts. Alternatively, the three-dimensional data encoding device may determine whether to combine frames, which frames to combine, or the number of frames to combine based on whether there are many common parts.

[0340] Next, the structure of the encoded position information will be described. Figure 56 shows the structure of the encoded position information. The encoded position information includes a header and a payload.

[0341] 57 is a diagram illustrating an example of the syntax of the header (Geometry_header) of the encoded position information. The header of the encoded position information includes a GPS index (gps_idx), offset information (offset), other information (other_geometry_information), a frame combination flag (combine_frame_flag), and the number of combined frames (number_of_combine_frame).

[0342] The GPS index indicates the identifier (ID) of the parameter set (GPS) corresponding to the coded position information. A GPS is a parameter set for coded position information of one frame or multiple frames. If a parameter set exists for each frame, the identifiers of multiple parameter sets may be indicated in the header.

[0343] The offset information indicates an offset position for acquiring the combined data. The other information indicates other information related to the position information (for example, a quantization parameter difference value (QPdelta)). The frame combining flag indicates whether the encoded data is frame combined. The number of combined frames indicates the number of combined frames.

[0344] Note that some or all of the above information may be described in the SPS or GPS. Note that the SPS is a parameter set for each sequence (multiple frames) and is a parameter set that is used in common for the coded position information and the coded attribute information.

[0345] 58 is a diagram illustrating an example of the syntax of the payload (Geometry_data) of the encoded position information. The payload of the encoded position information includes common information and leaf node information.

[0346] The common information is data combined into one or more frames, and includes an occupancy code (occupancy_Code) and the like.

[0347] The leaf node information (combine_information) is information about each leaf node. The leaf node information may be indicated for each frame as a loop of the frame number.

[0348] As a method for indicating the frame index of a point included in a leaf node, either Method 1 or Method 2 can be used. Fig. 59 is a diagram showing an example of leaf node information in the case of Method 1. The leaf node information shown in Fig. 59 includes the number of three-dimensional points (NumberOfPoints) indicating the number of points included in the node, and a frame index (FrameIndex) for each point.

[0349] FIG. 60 is a diagram showing an example of leaf node information for Method 2. In the example shown in FIG. 60, the leaf node information includes bitmap information (bitmapIsFramePointsFlag) that indicates the frame indexes of multiple points using a bitmap. FIG. 61 is a diagram showing an example of bitmap information. In this example, the bitmap indicates that the leaf node includes 3D points with frame indexes 1, 3, and 5.

[0350] Note that if the quantization resolution is low, there may be duplicate points in the same frame. In this case, the number of 3D points (NumberOfPoints) may be shared, and the number of 3D points in each frame and the total number of 3D points across multiple frames may be indicated.

[0351] Furthermore, when lossy compression is used, the three-dimensional data encoding device may delete duplicated points to reduce the amount of information. The three-dimensional data encoding device may delete duplicated points before combining frames, or may delete duplicated points after combining frames.

[0352] Next, the structure of the encoded attribute information will be described. Fig. 62 shows the structure of the encoded attribute information. The encoded attribute information includes a header and a payload.

[0353] 63 is a diagram illustrating an example of the syntax of the header (Attribute_header) of the encoding attribute information. The header of the encoding attribute information includes an APS index (aps_idx), offset information (offset), other information (other_attribute_information), a frame combination flag (combine_frame_flag), and the number of combined frames (number_of_combine_frame).

[0354] The APS index indicates the identifier (ID) of the parameter set (APS) corresponding to the coding attribute information. An APS is a parameter set of coding attribute information for one frame or multiple frames. If there is a parameter set for each frame, the identifiers of multiple parameter sets may be indicated in the header.

[0355] The offset information indicates an offset position for acquiring the combined data. The other information indicates other information related to the attribute information (for example, a quantization parameter difference value (QPdelta)). The frame combination flag indicates whether the encoded data is frame combined. The number of combined frames indicates the number of combined frames.

[0356] Note that some or all of the above information may be included in the SPS or APS.

[0357] FIG. 64 is a diagram showing an example of the syntax of the payload (Attribute_data) of the encoded attribute information. The payload of the encoded attribute information includes leaf node information (combine_information). For example, the configuration of this leaf node information is the same as that of the leaf node information included in the payload of the encoded position information. In other words, the leaf node information (frame index) may be included in the attribute information.

[0358] Furthermore, the leaf node information (frame index) may be stored in either the encoding position information or the encoding attribute information, but not in the other. In this case, the leaf node information (frame index) stored in either the encoding position information or the encoding attribute information is referenced when the other information is decoded. Furthermore, information indicating the reference destination may be included in the encoding position information or the encoding attribute information.

[0359] Next, an example of the transmission order and decoding order of coded data will be described. Figure 65 is a diagram showing the structure of coded data. Coded data includes a header and a payload.

[0360] 66 to 68 are diagrams showing the data transmission order and the data reference relationship. In the diagrams, G(1) etc. indicate encoding position information, GPS(1) etc. indicate a parameter set for encoding position information, and SPS indicates a parameter set for a sequence (multiple frames). Furthermore, the numbers in parentheses indicate the frame index values. Note that the three-dimensional data encoding device may also transmit data in decoding order.

[0361] Fig. 66 is a diagram showing an example of a transmission order when frames are not combined. Fig. 67 is a diagram showing an example when frames are combined and metadata (parameter set) is added to each PCC frame. Fig. 68 is a diagram showing an example when frames are combined and metadata (parameter set) is added to each combination unit.

[0362] The header of the frame-combined data stores the identifier of the referenced metadata to obtain the metadata for that frame. As shown in Figure 68, metadata for multiple frames may be combined. Parameters that are common to multiple frames may be combined into one. Parameters that are not common to the frames indicate values ​​for each frame.

[0363] The information for each frame (parameters not common to all frames) is, for example, a timestamp indicating the time when the frame data was generated, encoded, or decoded. The information for each frame may also include information about the sensor that acquired the frame data (sensor speed, acceleration, position information, sensor orientation, other sensor information, etc.).

[0364] Figure 69 is a diagram showing an example of decoding some frames in the example shown in Figure 67. As shown in Figure 69, if there is no dependency between frames in the frame-spliced ​​data, the three-dimensional data decoding device can decode each piece of data independently.

[0365] When the point cloud data has attribute information, the three-dimensional data encoding device may frame-combine the attribute information. The attribute information is encoded and decoded with reference to position information. The referenced position information may be the position information before frame-combine, or the position information after frame-combine. The number of frames for combining the position information and the number of frames for combining the attribute information may be the same (the same), or may be independent (different).

[0366] 70 to 73 are diagrams showing the data transmission order and data reference relationships. FIGS. 70 and 71 show examples in which position information and attribute information are combined in four frames. In FIG. 70, metadata (parameter set) is added to each PCC frame. In FIG. 71, metadata (parameter set) is added for each combination unit. In these figures, A(1) etc. indicates coding attribute information, and APS(1) etc. indicates a parameter set of the coding attribute information. Also, the numbers in parentheses indicate frame index values.

[0367] Fig. 72 shows an example in which the position information is combined in four frames, but the attribute information is not combined. As shown in Fig. 72, the position information may be combined in frames, but the attribute information may not be combined in frames.

[0368] Fig. 73 shows an example of combining frame combining and tile division. When tile division is performed as shown in Fig. 73, the header of each tile position information includes information such as a GPS index (gps_idx) and the number of combined frames (number_of_combine_frame). In addition, the header of each tile position information includes a tile index (tile_idx) for identifying the tile.

[0369] As described above, the three-dimensional data encoding device according to this embodiment performs the processing shown in Fig. 74. First, the three-dimensional data encoding device generates third point cloud data by combining the first point cloud data and the second point cloud data (S5481). Next, the three-dimensional data encoding device generates encoded data by encoding the third point cloud data (S5482). Furthermore, the encoded data includes identification information (e.g., a frame index) indicating whether each of the multiple three-dimensional points included in the third point cloud data belongs to the first point cloud data or the second point cloud data.

[0370] According to this, the three-dimensional data encoding device can improve encoding efficiency by encoding a plurality of point group data collectively.

[0371] For example, the first point cloud data and the second point cloud data are point cloud data (e.g., PCC frames) at different times. For example, the first point cloud data and the second point cloud data are point cloud data (e.g., PCC frames) of the same object at different times.

[0372] The encoded data includes position information and attribute information of each of the plurality of three-dimensional points included in the third point cloud data, and the identification information is included in the attribute information.

[0373] For example, the encoded data includes position information (for example, occupancy code) that represents the position of each of a plurality of three-dimensional points included in the third point cloud data using an N-ary tree (N is an integer equal to or greater than 2).

[0374] For example, the three-dimensional data encoding device includes a processor and a memory, and the processor performs the above-mentioned processing using the memory.

[0375] Furthermore, the three-dimensional data decoding device according to this embodiment performs the processing shown in Fig. 75. First, the three-dimensional data decoding device decodes the encoded data to obtain third point cloud data generated by combining the first point cloud data and the second point cloud data, and identification information indicating whether each of the multiple three-dimensional points included in the third point cloud data belongs to the first point cloud data or the second point cloud data (S5491). Next, the three-dimensional data decoding device separates the first point cloud data and the second point cloud data from the third point cloud data using the identification information (S5492).

[0376] According to this, the three-dimensional data decoding device can decode coded data with improved coding efficiency by collectively coding a plurality of point cloud data.

[0377] For example, the first point cloud data and the second point cloud data are point cloud data (e.g., PCC frames) at different times. For example, the first point cloud data and the second point cloud data are point cloud data (e.g., PCC frames) of the same object at different times.

[0378] The encoded data includes position information and attribute information of each of the plurality of three-dimensional points included in the third point cloud data, and the identification information is included in the attribute information.

[0379] For example, the encoded data includes position information (for example, occupancy code) that represents the position of each of a plurality of three-dimensional points included in the third point cloud data using an N-ary tree (N is an integer equal to or greater than 2).

[0380] For example, the three-dimensional data decoding device includes a processor and a memory, and the processor performs the above processing using the memory.

[0381] (Sixth embodiment) The information of a 3D point cloud includes position information (geometry) and attribute information (attribute). The position information includes coordinates (x-coordinate, y-coordinate, z-coordinate) based on a certain point. When encoding the position information, instead of directly encoding the coordinates of each 3D point, a method is used in which the position of each 3D point is expressed in an octree representation and the octree information is encoded to reduce the amount of code.

[0382] On the other hand, the attribute information includes information indicating color information (RGB, YUV, etc.) of each three-dimensional point, reflectance, normal vector, etc. For example, the three-dimensional data encoding device can encode the attribute information using an encoding method different from that for the position information.

[0383] In this embodiment, a method for encoding attribute information when combining and encoding multiple point cloud data of multiple frames of position information will be described. In this embodiment, the attribute information values ​​will be described using integer values. For example, if each color component of RGB or YUV color information has 8-bit precision, each color component will take an integer value between 0 and 255. If the reflectance value has 10-bit precision, the reflectance value will take an integer value between 0 and 1023. If the bit precision of the attribute information is decimal precision, the three-dimensional data encoding device may multiply the attribute information value by a scale value and then round it to an integer value so that the attribute information value becomes an integer. The three-dimensional data encoding device may add this scale value to a bitstream header or the like.

[0384] As a method for encoding attribute information when the position information of each 3D point cloud is combined and encoded using point cloud data from multiple frames, for example, the combined position information may be used to encode the attribute information corresponding to each position information. Here, the combined position information may include the position information of the 3D point cloud and the frame_index (frame index) to which the 3D point cloud belongs. Furthermore, when encoding the attribute information of a first 3D point in the 3D point cloud, not only the position information or attribute information of the 3D point cloud included in the frame to which the first 3D point belongs, but also the position information or attribute information of the 3D point cloud included in a frame other than the frame to which the first 3D point belongs may be used.

[0385] Each of the multiple frames includes point cloud data. The first point cloud data belonging to a first frame of the multiple frames and the second point cloud data belonging to a second frame are point cloud data at different times. Furthermore, the first point cloud data and the second point cloud data are, for example, point cloud data of the same object at different times. The first point cloud data includes a frame index indicating that the three-dimensional point cloud included in the first point cloud data belongs to the first point cloud data. The second point cloud data includes a frame index indicating that the three-dimensional point cloud included in the second point cloud data belongs to the second point cloud data. The frame index is identification information indicating to which point cloud data the three-dimensional point cloud included in combined point cloud data obtained by combining multiple point cloud data belonging to different frames belongs. Note that a three-dimensional point cloud is also referred to as a plurality of three-dimensional points.

[0386] One possible method for encoding attribute information of a three-dimensional point is to calculate a predicted value of the attribute information of the three-dimensional point and encode the difference (prediction residual) between the value of the original attribute information and the predicted value. For example, if the value of the attribute information of a three-dimensional point p is Ap and the predicted value is Pp, the three-dimensional data encoding device encodes the absolute difference Diffp = |Ap - Pp|. In this case, if the predicted value Pp can be generated with high accuracy, the value of the absolute difference Diffp will be small. Therefore, for example, the amount of code can be reduced by entropy encoding the absolute difference Diffp using a coding table in which the smaller the value, the fewer bits are generated.

[0387] One possible method for generating a predicted value of attribute information is to use attribute information of a reference 3D point, which is another 3D point surrounding the target 3D point to be encoded. In this manner, the 3D data encoding device may encode the attribute information of a first 3D point using attribute information of the surrounding 3D points. Here, the other surrounding 3D points surrounding the target 3D point to be encoded may be present within the frame to which the target 3D point to be encoded belongs, or may be present in a frame different from the frame to which the target 3D point to be encoded belongs. That is, the attribute information of the target 3D point may include a first frame index indicating that the target 3D point belongs to the first point cloud data, and the attribute information of the surrounding 3D points may include a second frame index indicating that the surrounding 3D points belong to the second point cloud data. This allows for a highly accurate predicted value Pp to be generated by also referencing attribute information of 3D points other than the frame to which the target 3D point to be encoded belongs, thereby improving encoding efficiency.

[0388] Here, the reference 3D point is a 3D point within a predetermined distance range from the target 3D point. For example, if there are target 3D point p = (x1, y1, z1) and 3D point q = (x2, y2, z2), the 3D data encoding device calculates the Euclidean distance d(p, q) between the 3D points p and q shown in (Equation H1).

[0389]

number

[0390] If the Euclidean distance d(p, q) is smaller than a predetermined threshold THd, the three-dimensional data encoding device determines that the position of the three-dimensional point q is close to the position of the target three-dimensional point p, and determines to use the value of the attribute information of the three-dimensional point q to generate a predicted value of the attribute information of the target three-dimensional point p. Note that other distance calculation methods may be used, such as Mahalanobis distance. The three-dimensional data encoding device may also determine that three-dimensional points outside a predetermined distance range from the target three-dimensional point are not used in the prediction process. For example, if a three-dimensional point r exists and the distance d(p, r) between the target three-dimensional point p and the three-dimensional point r is equal to or greater than a threshold THd, the three-dimensional data encoding device may determine that the three-dimensional point r is not used for prediction. Note that the three-dimensional data encoding device may add information indicating the threshold THd to a bitstream header or the like. Note that if the three-dimensional data encoding device combines and encodes the position information of a three-dimensional point cloud from point cloud data of multiple frames, it may calculate the distance between each three-dimensional point from the combined three-dimensional point cloud. That is, the three-dimensional data encoding device may calculate the distance between two three-dimensional points that belong to different frames, or may calculate the distance between two three-dimensional points that belong to the same frame.

[0391] 76 is a diagram showing an example of a 3D point. In this example, the distance d(p, q) between the target 3D point p and the 3D point q is smaller than the threshold value THd. Therefore, the 3D data encoding device determines that the 3D point q is the reference 3D point of the target 3D point p, and determines that the value of the attribute information Aq of the 3D point q will be used to generate the predicted value Pp of the attribute information Ap of the target 3D point p.

[0392] On the other hand, the distance d(p, r) between the target 3D point p and the 3D point r is equal to or greater than the threshold value THd. Therefore, the 3D data encoding device determines that the 3D point r is not a reference 3D point of the target 3D point p, and determines not to use the value of the attribute information Ar of the 3D point r to generate the predicted value Pp of the attribute information Ap of the target 3D point p.

[0393] Here, 3D point p belongs to the frame indicated by the frame index (frame_idx=0), 3D point q belongs to the frame indicated by the frame index (frame_idx=1), and 3D point r belongs to the frame indicated by the frame index (frame_idx=0). The 3D encoding device may calculate the distance between 3D points p and r that are indicated by the frame index to belong to the same frame, or may calculate the distance between 3D points p and q that are indicated by the frame index to belong to different frames.

[0394] Furthermore, when the 3D data encoding device encodes attribute information of a target 3D point using a predicted value, it uses a 3D point whose attribute information has already been encoded and decoded as a reference 3D point. Similarly, when the 3D data decoding device decodes attribute information of a target 3D point to be decoded using a predicted value, it uses a 3D point whose attribute information has already been decoded as a reference 3D point. This allows the same predicted value to be generated during encoding and decoding, so that the bit stream of 3D points generated during encoding can be correctly decoded on the decoding side.

[0395] Although other surrounding 3D points around a target 3D point to be encoded may exist within the frame to which the target 3D point to be encoded belongs, or may exist in a frame other than the frame to which the target 3D point to be encoded belongs, this is not necessarily limited to this. For example, 3D points existing in a frame other than the frame to which the target 3D point to be encoded belongs may be determined not to be around the target 3D point to be encoded and not used as predicted values. As a result, when the attribute information of each 3D point in multiple frames to be combined is significantly different, the 3D data encoding device can improve encoding efficiency by encoding the position information using frame combination and predictively encoding the attribute information using attribute information of other surrounding 3D points in the same frame. During encoding using frame combination, the 3D data encoding device may add information to the header of the encoded data indicating whether to encode the attribute information of the target 3D point using attribute information of surrounding 3D points in the same frame or to encode the attribute information of the target 3D point using attribute information of surrounding 3D points in the same frame and other frames, and switch between these options. As a result, by decoding the header, the three-dimensional data decoding device can determine whether to decode the attribute information of the target three-dimensional point using the attribute information of the same frame or of surrounding three-dimensional points in the same frame and other frames when decoding encoded data using frame combining, and can switch between the two decoding methods, thereby enabling the bitstream to be decoded appropriately.

[0396] Furthermore, when encoding attribute information of 3D points after combining multiple frames, it is possible to classify each 3D point into multiple layers using the position information of 3D points belonging to the same frame or different frames, and then encode them. Here, each classified layer is called LoD (Level of Detail). The method for generating LoD will be explained using Figure 77.

[0397] First, the three-dimensional data encoding device selects an initial point a0 from the combined three-dimensional point cloud and assigns it to LoD0. Next, the three-dimensional data encoding device extracts point a1 whose distance from point a0 is greater than the LoD0 threshold Thres_LoD[0] and assigns it to LoD0. Next, the three-dimensional data encoding device extracts point a2 whose distance from point a1 is greater than the LoD0 threshold Thres_LoD[0] and assigns it to LoD0. In this way, the three-dimensional data encoding device constructs LoD0 so that the distance between each point in LoD0 is greater than the threshold Thres_LoD[0]. Note that the three-dimensional data encoding device may calculate the distance between two three-dimensional points using the same process regardless of whether they belong to the same frame or different frames. For example, point a0 and point a1 may belong to the same frame or different frames. Therefore, the distance between point a0 and point a1 is calculated using the same process whether they belong to the same frame or different frames.

[0398] Next, the three-dimensional data encoding device selects point b0, which has not yet been assigned an LoD, and assigns it to LoD1. Next, the three-dimensional data encoding device extracts point b1, whose distance from point b0 is greater than the LoD1 threshold Thres_LoD[1] and whose LoD has not been assigned, and assigns it to LoD1. Next, the three-dimensional data encoding device extracts point b2, whose distance from point b1 is greater than the LoD1 threshold Thres_LoD[1] and whose LoD has not been assigned, and assigns it to LoD1. In this way, the three-dimensional data encoding device configures LoD1 so that the distance between each point within LoD1 is greater than the threshold Thres_LoD[1].

[0399] Next, the three-dimensional data encoding device selects point c0, which has not yet been assigned an LoD, and assigns it to LoD2. Next, the three-dimensional data encoding device extracts point c1, which has not yet been assigned an LoD and whose distance from point c0 is greater than the LoD2 threshold Thres_LoD[2], and assigns it to LoD2. Next, the three-dimensional data encoding device extracts point c2, which has not yet been assigned an LoD and whose distance from point c1 is greater than the LoD2 threshold Thres_LoD[2], and assigns it to LoD2. In this way, the three-dimensional data encoding device configures LoD2 so that the distance between each point within LoD2 is greater than the threshold Thres_LoD[2]. For example, as shown in FIG. 78, thresholds Thres_LoD[0], Thres_LoD[1], and Thres_LoD[2] for each LoD are set.

[0400] Furthermore, the three-dimensional data encoding device may add information indicating the threshold value of each LoD to the header of the bitstream, etc. For example, in the example shown in Fig. 78, the three-dimensional data encoding device may add thresholds Thres_LoD[0], Thres_LoD[1], and Thres_LoD[2] to the header.

[0401] Alternatively, the three-dimensional data encoding device may assign all three-dimensional points to which no LoD has been assigned to the lowest layer of the LoD. In this case, the three-dimensional data encoding device can reduce the amount of header coding by not adding the threshold value for the lowest layer of the LoD to the header. For example, in the example shown in FIG. 78, the three-dimensional data encoding device adds thresholds Thres_LoD[0] and Thres_LoD[1] to the header, but does not add Thres_LoD[2] to the header. In this case, the three-dimensional data decoding device may estimate the value of Thres_LoD[2] to be 0. The three-dimensional data encoding device may also add the number of layers of the LoD to the header. This allows the three-dimensional data decoding device to determine the LoD of the lowest layer using the number of layers of the LoD.

[0402] Also, by setting the threshold value of each LoD layer to be larger for higher layers as shown in Figure 78, the higher the layer (layer closer to LoD0), the sparser the point cloud becomes, with 3D points spaced farther apart, and the lower the layer, the denser the point cloud becomes, with 3D points spaced closer together. In the example shown in Figure 78, LoD0 is the top layer.

[0403] Furthermore, the method for selecting the initial 3D point when setting each LoD may depend on the encoding order used when encoding the position information. For example, the 3D data encoding device may select the 3D point that was encoded first when encoding the position information as the initial point a0 of LoD0, and then select points a1 and a2 using the initial point a0 as the base point to construct LoD0. The 3D data encoding device may then select, as the initial point b0 of LoD1, the 3D point whose position information is encoded earliest among the 3D points that do not belong to LoD0. In other words, the 3D data encoding device may select, as the initial point n0 of LoDn, the 3D point whose position information is encoded earliest among the 3D points that do not belong to the upper layers (LoD0 to LoDn-1) of LoDn. This allows the 3D data decoding device to use the same initial point selection method during decoding to construct the same LoD as during encoding, thereby enabling appropriate decoding of the bitstream. Specifically, the 3D data decoding device selects, as the initial point n0 of LoDn, the 3D point whose position information is decoded earliest among the 3D points that do not belong to the upper layers of LoDn.

[0404] A method for generating predicted values ​​of attribute information of 3D points using LoD information will be described below. For example, when encoding 3D points included in LoD0 in order, a 3D data encoding device generates a target 3D point included in LoD1 using coded and decoded attribute information (hereinafter simply referred to as "coded") included in LoD0 and LoD1. In this way, the 3D data encoding device generates predicted values ​​of attribute information of 3D points included in LoDn using coded attribute information included in LoDn' (n'<=n). In other words, the 3D data encoding device does not use attribute information of 3D points included in a layer below LoDn when calculating predicted values ​​of attribute information of 3D points included in LoDn.

[0405] For example, the three-dimensional data encoding device generates a predicted value of attribute information of a three-dimensional point by calculating the average of attribute values ​​of N or fewer three-dimensional points among encoded three-dimensional points surrounding the target three-dimensional point to be encoded. The three-dimensional data encoding device may also add the value of N to a bitstream header or the like. The three-dimensional data encoding device may also change the value of N for each three-dimensional point and add a value of N to each three-dimensional point. This allows an appropriate N to be selected for each three-dimensional point, thereby improving the accuracy of the predicted value. This reduces the prediction residual. The three-dimensional data encoding device may also add the value of N to the bitstream header and fix the value of N within the bitstream. This eliminates the need to encode or decode the value of N for each three-dimensional point, thereby reducing the amount of processing. The three-dimensional data encoding device may also encode the value of N separately for each LoD. This allows an appropriate N to be selected for each LoD, thereby improving coding efficiency.

[0406] Alternatively, the three-dimensional data encoding device may calculate a predicted value of the attribute information of a three-dimensional point as a weighted average value of the attribute information of N surrounding encoded three-dimensional points. For example, the three-dimensional data encoding device calculates the weight using distance information between the target three-dimensional point and each of the N surrounding three-dimensional points.

[0407] When a 3D data encoding device encodes the value of N separately for each LoD, it sets the value of N larger for higher LoD layers and smaller for lower LoD layers. Because the distance between 3D points in higher LoD layers is greater, it may be possible to improve prediction accuracy by setting the value of N larger and selecting and averaging multiple surrounding 3D points. Also, because the distance between 3D points in lower LoD layers is closer, it is possible to set the value of N smaller, reducing the amount of averaging processing and enabling efficient prediction.

[0408] Fig. 79 is a diagram showing an example of attribute information used for predicted values. As described above, the predicted value of point P included in LoDN is generated using the coded surrounding points P' included in LoDN' (N'<=N). Here, the surrounding points P' are selected based on the distance from point P. For example, the predicted value of the attribute information of point b2 shown in Fig. 79 is generated using the attribute information of points a0, a1, a2, b0, and b1.

[0409] The surrounding points selected vary depending on the value of N. For example, when N=5, a0, a1, a2, b0, and b1 are selected as surrounding points of point b2. When N=4, points a0, a1, a2, and b1 are selected based on distance information.

[0410] The predicted value is calculated by a distance-dependent weighted average. For example, in the example shown in FIG. 79, the predicted value a2p of point a2 is calculated by a weighted average of the attribute information of points a0 and a1, as shown in (Equation H2) and (Equation H3). i is the value of the attribute information of point ai.

[0411]

number

[0412] Furthermore, the predicted value b2p of point b2 is calculated by the weighted average of the attribute information of points a0, a1, a2, b0, and b1, as shown in (Equation H4) to (Equation H6). i is the value of the attribute information of point bi.

[0413]

number

[0414] Furthermore, the three-dimensional data encoding device may calculate a difference value (prediction residual) between the value of the attribute information of the three-dimensional point and a predicted value generated from the surrounding points, and quantize the calculated prediction residual. For example, the three-dimensional data encoding device performs quantization by dividing the prediction residual by a quantization scale (also called a quantization step). In this case, the smaller the quantization scale, the smaller the error (quantization error) that may occur due to quantization. Conversely, the larger the quantization scale, the larger the quantization error.

[0415] The three-dimensional data encoding device may change the quantization scale used for each LoD. For example, the three-dimensional data encoding device may use a smaller quantization scale for higher layers and a larger quantization scale for lower layers. Since the values ​​of attribute information of three-dimensional points belonging to higher layers may be used as predicted values ​​of attribute information of three-dimensional points belonging to lower layers, the encoding efficiency can be improved by reducing the quantization scale for higher layers to suppress quantization errors that may occur in higher layers and increasing the accuracy of predicted values. The three-dimensional data encoding device may add the quantization scale used for each LoD to a header or the like. This allows the three-dimensional data decoding device to correctly decode the quantization scale and therefore appropriately decode the bitstream.

[0416] Furthermore, the three-dimensional data encoding device may convert signed integer values ​​(signed quantized values), which are prediction residuals after quantization, into unsigned integer values ​​(unsigned quantized values). This eliminates the need to consider the occurrence of negative integers when entropy encoding the prediction residuals. Note that the three-dimensional data encoding device does not necessarily need to convert signed integer values ​​into unsigned integer values; for example, the sign bit may be separately entropy encoded.

[0417] The prediction residual is calculated by subtracting a predicted value from an original value. For example, the prediction residual a2r of point a2 is calculated by subtracting the predicted value a2p of point a2 from the attribute information value A2 of point a2, as shown in (Equation H7). The prediction residual b2r of point b2 is calculated by subtracting the predicted value b2p of point b2 from the attribute information value B2 of point b2, as shown in (Equation H8).

[0418] a2r=A2-a2p (Eq. H7) b2r=B2-b2p (Eq. H8)

[0419] Furthermore, the prediction residual is quantized by dividing it by QS (Quantization Step). For example, the quantized value a2q of point a2 is calculated by (Equation H9). The quantized value b2q of point b2 is calculated by (Equation H10). Here, QS_LoD0 is the QS for LoD0, and QS_LoD1 is the QS for LoD1. That is, the QS may be changed depending on the LoD.

[0420] a2q=a2r / QS_LoD0 (Formula H9) b2q=b2r / QS_LoD1 (Formula H10)

[0421] Furthermore, the three-dimensional data encoding device converts the signed integer value, which is the quantized value, into an unsigned integer value as follows: If the signed integer value a2q is less than 0, the three-dimensional data encoding device sets the unsigned integer value a2u to -1-(2×a2q). If the signed integer value a2q is 0 or greater, the three-dimensional data encoding device sets the unsigned integer value a2u to 2×a2q.

[0422] Similarly, the three-dimensional data encoding device sets the unsigned integer value b2u to -1-(2×b2q) if the signed integer value b2q is less than 0. The three-dimensional data encoding device sets the unsigned integer value b2u to 2×b2q if the signed integer value b2q is greater than or equal to 0.

[0423] Furthermore, the three-dimensional data encoding device may encode the quantized prediction residuals (unsigned integer values) by entropy encoding. For example, the unsigned integer values ​​may be binarized and then subjected to binary arithmetic encoding.

[0424] In this case, the three-dimensional data encoding device may switch the binarization method depending on the value of the prediction residual. For example, when the prediction residual pu is smaller than a threshold R_TH, the three-dimensional data encoding device binarizes the prediction residual pu using a fixed number of bits required to express the threshold R_TH. When the prediction residual pu is equal to or greater than the threshold R_TH, the three-dimensional data encoding device binarizes the binarized data of the threshold R_TH and the value (pu-R_TH) using Exponential-Golomb or the like.

[0425] For example, if the threshold value R_TH is 63 and the prediction residual pu is smaller than 63, the three-dimensional data encoding device binarizes the prediction residual pu using 6 bits. Furthermore, if the prediction residual pu is 63 or greater, the three-dimensional data encoding device performs arithmetic encoding by binarizing the binary data of the threshold value R_TH (111111) and (pu-63) using Exponential Golomb algorithm.

[0426] In a more specific example, when the prediction residual pu is 32, the three-dimensional data encoding device generates 6-bit binary data (100000) and arithmetically encodes this bit string. Also, when the prediction residual pu is 66, the three-dimensional data encoding device generates binary data (111111) of the threshold R_TH and a bit string (00100) that expresses the value 3 (66-63) in Exponential Golomb notation, and arithmetically encodes this bit string (111111+00100).

[0427] In this way, the 3D data encoding device switches the binarization method depending on the size of the prediction residual, thereby enabling encoding while suppressing a sudden increase in the number of binarization bits when the prediction residual becomes large. Note that the 3D data encoding device may add the threshold value R_TH to the header of the bitstream, etc.

[0428] For example, when encoding is performed at a high bit rate, that is, when the quantization scale is small, the quantization error is small and the prediction accuracy is high, and as a result, the prediction residual may not be large. Therefore, in this case, the three-dimensional data encoding device sets the threshold R_TH to a large value. This reduces the possibility of encoding binarized data of the threshold R_TH, and improves encoding efficiency. Conversely, when encoding is performed at a low bit rate, that is, when the quantization scale is large, the quantization error is large and the prediction accuracy is poor, and as a result, the prediction residual may be large. Therefore, in this case, the three-dimensional data encoding device sets the threshold R_TH to a small value. This prevents a sudden increase in the bit length of the binarized data.

[0429] Furthermore, the three-dimensional data encoding device may switch the threshold R_TH for each LoD and add the threshold R_TH for each LoD to a header or the like. That is, the three-dimensional data encoding device may switch the binarization method for each LoD. For example, in higher layers, the distance between three-dimensional points is large, which may result in poor prediction accuracy and large prediction residuals. Therefore, the three-dimensional data encoding device prevents a sudden increase in the bit length of the binarized data by setting a small threshold R_TH for higher layers. Furthermore, in lower layers, the distance between three-dimensional points is small, which may result in high prediction accuracy and small prediction residuals. Therefore, the three-dimensional data encoding device improves encoding efficiency by setting a large threshold R_TH for each layer.

[0430] Fig. 80 is a diagram showing an example of exponential-Golomb coding, illustrating the relationship between values ​​(multiple values) before binarization and bits (codes) after binarization. Note that 0 and 1 shown in Fig. 80 may be reversed.

[0431] Furthermore, the three-dimensional data encoding device applies arithmetic coding to the binary data of the prediction residual, thereby improving encoding efficiency. Note that when applying arithmetic coding, the tendency of the occurrence probability of 0 and 1 for each bit may differ between the n-bit code, which is the portion of the binary data binarized with n bits, and the remaining code, which is the portion binarized using the Exponential Golomb algorithm. Therefore, the three-dimensional data encoding device may switch the application method of arithmetic coding between the n-bit code and the remaining code.

[0432] For example, a three-dimensional data encoder performs arithmetic coding on an n-bit code using a different coding table (probability table) for each bit. In this case, the three-dimensional data encoder may change the number of coding tables used for each bit. For example, the three-dimensional data encoder performs arithmetic coding on the first bit b0 of an n-bit code using one coding table. The three-dimensional data encoder also uses two coding tables for the next bit b1. The three-dimensional data encoder also switches the coding table used for arithmetic coding of bit b1 depending on the value of b0 (0 or 1). Similarly, the three-dimensional data encoder uses four coding tables for the next bit b2. The three-dimensional data encoder also switches the coding table used for arithmetic coding of bit b2 depending on the values ​​of b0 and b1 (0 to 3).

[0433] In this way, the three-dimensional data encoding device performs arithmetic encoding on each bit bn-1 of the n-bit code. n-1 The three-dimensional data encoding device uses coding tables. In addition, the three-dimensional data encoding device switches the coding table to be used depending on the value (occurrence pattern) of the bits before bn-1. This allows the three-dimensional data encoding device to use an appropriate coding table for each bit, thereby improving coding efficiency.

[0434] Note that the three-dimensional data encoding device may reduce the number of encoding tables used for each bit. For example, when arithmetic-encoding each bit bn-1, the three-dimensional data encoding device may switch between two encoding tables according to the value (occurrence pattern) of the m bits (m < n - 1) before bn-1. This can improve the encoding efficiency while suppressing the number of encoding tables used for each bit. Note that the three-dimensional data encoding device may update the occurrence probabilities of 0 and 1 in each encoding table according to the value of the actually generated binarized data. Also, the three-dimensional data encoding device may fix the occurrence probabilities of 0 and 1 in the encoding tables of some bits. This can suppress the number of updates of the occurrence probabilities and thus reduce the processing amount. m For example, when the n-bit code is b0b1b2…bn-1, there is 1 encoding table (CTb0) for b0. There are 2 encoding tables (CTb10, CTb11) for b1. Also, the encoding table to be used is switched according to the value (0 to 1) of b0. There are 4 encoding tables (CTb20, CTb21, CTb22, CTb23) for b2. Also, the encoding table to be used is switched according to the values (0 to 3) of b0 and b1. There are 2

[0435] encoding tables (CTbn0, CTbn1, …, CTbn(2 n-1 -1)) for bn-1. Also, the encoding table to be used is switched according to the value (0 to 2 n-1 -1) of b0b1…bn-2. n-1

[0436] Note that the three-dimensional data encoding device may apply m-ary arithmetic encoding (m = 2 n ) that sets values from 0 to 2 n -1 without binarizing for the n-bit code. Also, when the three-dimensional data encoding device arithmetic-encodes the n-bit code in m-ary, the three-dimensional data decoding device may also restore the n-bit code by m-ary arithmetic decoding.

[0437] Fig. 81 is a diagram for explaining processing when the residual code is an exponential-Golomb code, for example. The residual code, which is the portion binarized using the exponential-Golomb code, includes a prefix portion and a suffix portion, as shown in Fig. 81. For example, the three-dimensional data encoding device switches encoding tables between the prefix portion and the suffix portion. That is, the three-dimensional data encoding device arithmetically encodes each bit included in the prefix portion using the encoding table for the prefix, and arithmetically encodes each bit included in the suffix portion using the encoding table for the suffix.

[0438] The three-dimensional data encoding device may update the occurrence probabilities of 0 and 1 in each encoding table according to the value of the binary data that actually occurs. Alternatively, the three-dimensional data encoding device may fix the occurrence probabilities of 0 and 1 in one of the encoding tables. This reduces the number of updates to the occurrence probabilities, thereby reducing the amount of processing. For example, the three-dimensional data encoding device may update the occurrence probabilities for the prefix part and fix the occurrence probabilities for the suffix part.

[0439] Furthermore, the three-dimensional data encoding device decodes the quantized prediction residual by inverse quantization and reconstruction, and uses the decoded value, which is the decoded prediction residual, for prediction of the three-dimensional point to be encoded and beyond. Specifically, the three-dimensional data encoding device calculates an inverse quantized value by multiplying the quantized prediction residual (quantized value) by the quantization scale, and obtains a decoded value (reconstructed value) by adding the inverse quantized value and the predicted value.

[0440] For example, the inverse quantization value a2iq of point a2 is calculated by (Equation H11) using the quantization value a2q of point a2. The inverse quantization value b2iq of point b2 is calculated by (Equation H12) using the quantization value b2q of point b2. Here, QS_LoD0 is the QS for LoD0, and QS_LoD1 is the QS for LoD1. That is, the QS may be changed depending on the LoD.

[0441] a2iq=a2q×QS_LoD0 (Formula H11) b2iq=b2q×QS_LoD1 (Formula H12)

[0442] For example, the decoded value a2rec of point a2 is calculated by adding the predicted value a2p of point a2 to the inverse quantized value a2iq of point a2 as shown in (Equation H13). The decoded value b2rec of point b2 is calculated by adding the predicted value b2p of point b2 to the inverse quantized value b2iq of point b2 as shown in (Equation H14).

[0443] a2rec=a2iq+a2p (formula H13) b2rec=b2iq+b2p (formula H14)

[0444] An example of the syntax of a bitstream according to this embodiment will be described below. Fig. 82 is a diagram showing an example of the syntax of an attribute header (attribute_header) according to this embodiment. The attribute header is header information of attribute information. As shown in Fig. 82, the attribute header includes hierarchical level information (NumLoD), three-dimensional point number information (NumOfPoint[i]), hierarchical level threshold (Thres_Lod[i]), surrounding point number information (NumNeighborPoint[i]), predicted threshold (THd[i]), quantization scale (QS[i]), and binarization threshold (R_TH[i]).

[0445] The number of layers information (NumLoD) indicates the number of layers of the LoD to be used.

[0446] The three-dimensional point number information (NumOfPoint[i]) indicates the number of three-dimensional points belonging to layer i. The three-dimensional data encoding device may add three-dimensional point total number information (AllNumOfPoint), which indicates the total number of three-dimensional points, to a separate header. In this case, the three-dimensional data encoding device does not need to add NumOfPoint[NumLoD-1], which indicates the number of three-dimensional points belonging to the lowest layer, to the header. In this case, the three-dimensional data decoding device can calculate NumOfPoint[NumLoD-1] using (Equation H15). This allows the amount of coding in the header to be reduced.

[0447]

Number

[0448] The hierarchical threshold (Thres_Lod[i]) is the threshold used for the setting of layer i. The three-dimensional data encoding device and the three-dimensional data decoding device configure LoDi such that the distance between each point in LoDi is greater than the threshold Thres_LoD[i]. Also, the three-dimensional data encoding device may not add the value of Thres_Lod[NumLoD - 1] (the lowest layer) to the header. In this case, the three-dimensional data decoding device estimates the value of Thres_Lod[NumLoD - 1] as 0. Thereby, the amount of code for the header can be reduced.

[0449] The surrounding point number information (NumNeighorPoint[i]) indicates the upper limit value of the number of surrounding points used for generating the predicted value of the three-dimensional points belonging to layer i. When the number of surrounding points M is less than NumNeighorPoint[i] (M < NumNeighorPoint[i]), the three-dimensional data encoding device may calculate the predicted value using M surrounding points. Also, when the three-dimensional data encoding device does not need to divide the value of NumNeighorPoint[i] for each LoD, it may add one piece of surrounding point number information (NumNeighorPoint) used for all LoDs to the header.

[0450] The prediction threshold (THd[i]) indicates the upper limit value of the distance between the surrounding three-dimensional points used for predicting the target three-dimensional point to be encoded or decoded at layer i and the target three-dimensional point. The three-dimensional data encoding device and the three-dimensional data decoding device do not use the three-dimensional points whose distance from the target three-dimensional point is farther than THd[i] for prediction. Note that when the three-dimensional data encoding device does not need to divide the value of THd[i] for each LoD, it may add one prediction threshold (THd) used for all LoDs to the header.

[0451] The quantization scale (QS[i]) indicates the quantization scale used for quantization and inverse quantization of layer i.

[0452] The binarization threshold (R_TH[i]) is a threshold for switching the binarization method for the prediction residual of a 3D point belonging to layer i. For example, if the prediction residual is smaller than the threshold R_TH, the 3D data encoding device binarizes the prediction residual pu with a fixed number of bits, and if the prediction residual is equal to or greater than the threshold R_TH, the 3D data encoding device binarizes the binarized data of the threshold R_TH and the value (pu-R_TH) using the Exponential Golomb algorithm. Note that if it is not necessary to switch the value of R_TH[i] for each LoD, the 3D data encoding device may add a single binarization threshold (R_TH) used for all LoDs to the header.

[0453] Note that R_TH[i] may be the maximum value that can be represented in n bits. For example, R_TH is 63 in 6 bits, and R_TH is 255 in 8 bits. The three-dimensional data encoding device may also encode the number of bits as the binarization threshold instead of encoding the maximum value that can be represented in n bits. For example, the three-dimensional data encoding device may add a value of 6 to the header when R_TH[i]=63, or a value of 8 to the header when R_TH[i]=255. The three-dimensional data encoding device may also define a minimum value (minimum number of bits) for the number of bits representing R_TH[i], and add the relative number of bits from the minimum value to the header. For example, the three-dimensional data encoding device may add a value of 0 to the header when R_TH[i]=63 and the minimum number of bits is 6, or add a value of 2 to the header when R_TH[i]=255 and the minimum number of bits is 6.

[0454] The three-dimensional data encoding device may also entropy-encode at least one of NumLod, Thres_Lod[i], NumNeighborPoint[i], THd[i], QS[i], and R_TH[i] and add the result to the header. For example, the three-dimensional data encoding device may binarize each value and arithmetically encode it. The three-dimensional data encoding device may also encode each value at a fixed length to reduce the amount of processing.

[0455] Furthermore, the three-dimensional data encoding device may not need to add at least one of NumLod, Thres_Lod[i], NumNeighborPoint[i], THd[i], QS[i], and R_TH[i] to the header. For example, the value of at least one of these may be specified by a profile or level of a standard, etc. This allows the number of bits in the header to be reduced.

[0456] Fig. 83 is a diagram showing an example of the syntax of attribute data (attribute_data) according to this embodiment. This attribute data includes coded data of attribute information of multiple three-dimensional points. As shown in Fig. 83, the attribute data includes an n-bit code and a remaining code.

[0457] An n-bit code is the coded data of the prediction residual of the attribute information value or a part thereof. The bit length of the n-bit code depends on the value of R_TH[i]. For example, if the value indicated by R_TH[i] is 63, the n-bit code is 6 bits, and if the value indicated by R_TH[i] is 255, the n-bit code is 8 bits.

[0458] The remaining code is the coded data of the prediction residual of the attribute information value that is coded using the exponential Golomb coding method. This remaining code is coded or decoded when the n-bit code is the same as R_TH[i]. The three-dimensional data decoding device also decodes the prediction residual by adding the value of the n-bit code and the value of the remaining code. Note that if the n-bit code is not the same value as R_TH[i], the remaining code does not need to be coded or decoded.

[0459] The flow of processing in the three-dimensional data encoding device will be explained below. Figure 84 is a flowchart of three-dimensional data encoding processing by the three-dimensional data encoding device.

[0460] First, the three-dimensional data encoding device combines multiple frames (S5601). For example, the three-dimensional data encoding device combines multiple three-dimensional point clouds belonging to multiple input frames into one three-dimensional point cloud. During the combining process, the three-dimensional data encoding device adds a frame index to each three-dimensional point cloud, indicating the frame to which the three-dimensional point cloud belongs.

[0461] Next, the three-dimensional data encoding device encodes the position information (geometry) after the frame splicing (S5602). For example, the three-dimensional data is encoded using an octree representation.

[0462] If the position of a 3D point changes due to quantization or the like after encoding the position information, the three-dimensional data encoding device reallocates the attribute information of the original 3D point to the changed 3D point (S5603). For example, the three-dimensional data encoding device performs the reallocation by interpolating the value of the attribute information according to the amount of change in position. For example, the three-dimensional data encoding device detects N pre-change 3D points that are close to the changed 3D position and calculates a weighted average of the attribute information values ​​of the N 3D points. For example, the three-dimensional data encoding device determines a weight for the weighted average based on the distance from the changed 3D position to each of the N three-dimensional points. The three-dimensional data encoding device then determines the value obtained by the weighted average as the value of the attribute information of the changed 3D point. Furthermore, if two or more 3D points change to the same three-dimensional position due to quantization or the like, the three-dimensional data encoding device may assign the average value of the attribute information of the two or more pre-change 3D points as the value of the attribute information of the changed 3D point.

[0463] Next, the three-dimensional data encoding device encodes the reallocated attribute information (Attribute) (S5604). Here, for each of the multiple three-dimensional points, the three-dimensional data encoding device encodes the frame index of the corresponding three-dimensional point as the attribute information of the corresponding three-dimensional point. Furthermore, for example, when encoding multiple types of attribute information, the three-dimensional data encoding device may encode the multiple types of attribute information in order. For example, when encoding color, reflectance, and frame index as attribute information, the three-dimensional data encoding device may generate a bitstream in which the encoded result of reflectance is added after the encoded result of color, and the encoded result of frame index is added after the encoded result of reflectance. Note that the order of the multiple encoded results of attribute information added to the bitstream is not limited to this order and may be any order. Furthermore, the three-dimensional data encoding device encodes the frame index as attribute information in the same data format as other attribute information different from the frame index, such as color or reflectance. Therefore, the encoded data includes the frame index in the same data format as other attribute information different from the frame index.

[0464] The three-dimensional data encoding device may also add information indicating the start location of the encoded data for each piece of attribute information in the bitstream to a header or the like. This allows the three-dimensional data decoding device to selectively decode attribute information that needs to be decoded, thereby omitting the decoding process for attribute information that does not need to be decoded. This reduces the amount of processing required by the three-dimensional data decoding device. The three-dimensional data encoding device may also encode multiple types of attribute information in parallel and combine the encoding results into a single bitstream. This allows the three-dimensional data encoding device to encode multiple types of attribute information at high speed.

[0465] 85 is a flowchart of the attribute information encoding process (S5604). First, the three-dimensional data encoding device sets the LoD (S5611). That is, the three-dimensional data encoding device assigns each three-dimensional point to one of a plurality of LoDs.

[0466] Next, the three-dimensional data encoding device starts a loop for each LoD (S5612). That is, the three-dimensional data encoding device repeatedly performs the processes of steps S5613 to S5621 for each LoD.

[0467] Next, the three-dimensional data encoding device starts a loop for each three-dimensional point (S5613). That is, the three-dimensional data encoding device repeatedly performs the processes of steps S5614 to S5620 for each three-dimensional point.

[0468] First, the three-dimensional data encoding device searches for multiple surrounding points, which are three-dimensional points that exist around the target three-dimensional point to be processed, and are used to calculate a predicted value of the target three-dimensional point (S5614). Next, the three-dimensional data encoding device calculates a weighted average of the attribute information values ​​of the multiple surrounding points and sets the obtained value as the predicted value P (S5615). Next, the three-dimensional data encoding device calculates a prediction residual, which is the difference between the attribute information of the target three-dimensional point and the predicted value (S5616). Next, the three-dimensional data encoding device calculates a quantized value by quantizing the prediction residual (S5617). Next, the three-dimensional data encoding device arithmetically encodes the quantized value (S5618).

[0469] The three-dimensional data encoding device also calculates inverse quantized values ​​by inverse quantizing the quantized values ​​(S5619). Next, the three-dimensional data encoding device generates decoded values ​​by adding predicted values ​​to the inverse quantized values ​​(S5620). Next, the three-dimensional data encoding device ends the loop in units of three-dimensional points (S5621). Also, the three-dimensional data encoding device ends the loop in units of LoDs (S5622).

[0470] Hereinafter, a three-dimensional data decoding process in a three-dimensional data decoding device that decodes a bit stream generated by the above three-dimensional data encoding device will be described.

[0471] The three-dimensional data decoding device generates decoded binary data by performing arithmetic decoding on the binary data of the attribute information in the bit stream generated by the three-dimensional data encoding device in the same manner as the three-dimensional data encoding device. In the three-dimensional data encoding device, when the application method of arithmetic coding is switched between the part binary-coded with n bits (n-bit code) and the part binary-coded using exponential Golomb (remaining code), the three-dimensional data decoding device performs decoding accordingly when applying arithmetic decoding.

[0472] For example, in the arithmetic decoding method of the n-bit code, the three-dimensional data decoding device performs arithmetic decoding using a different encoding table (decoding table) for each bit. At this time, the three-dimensional data decoding device may change the number of encoding tables used for each bit. For example, for the leading bit b0 of the n-bit code, arithmetic decoding is performed using one encoding table. Also, for the next bit b1, the three-dimensional data decoding device uses two encoding tables. Further, the three-dimensional data decoding device switches the encoding table used for the arithmetic decoding of bit b1 according to the value (0 or 1) of b0. Similarly, for the next bit b2, the three-dimensional data decoding device uses four encoding tables. Also, the three-dimensional data decoding device switches the encoding table used for the arithmetic decoding of bit b2 according to the values (0 to 3) of b0 and b1.

[0473] Thus, when the three-dimensional data decoding device performs arithmetic decoding on each bit bn-1 of the n-bit code, it uses 2 n-1 encoding tables. Also, the three-dimensional data decoding device switches the encoding table to be used according to the values (occurrence patterns) of the bits before bn-1. Thereby, the three-dimensional data decoding device can appropriately decode a bit stream with improved encoding efficiency by using an appropriate encoding table for each bit.

[0474] Note that the three-dimensional data decoding device may reduce the number of encoding tables used for each bit. For example, when the three-dimensional data decoding device performs arithmetic decoding on each bit bn-1, it uses 2 according to the values (occurrence patterns) of the m bits (m < n-1) before bn-1.m The three-dimensional data decoding device may switch among the coding tables. This allows the three-dimensional data decoding device to appropriately decode a bitstream with improved coding efficiency while reducing the number of coding tables used for each bit. The three-dimensional data decoding device may update the occurrence probabilities of 0 and 1 in each coding table according to the value of the binary data that actually occurs. The three-dimensional data decoding device may also fix the occurrence probabilities of 0 and 1 in the coding table for some bits. This reduces the number of updates to the occurrence probabilities, thereby reducing the amount of processing.

[0475] For example, if the n-bit code is b0b1b2...bn-1, there is one coding table for b0 (CTb0). There are two coding tables for b1 (CTb10, CTb11). The coding table is switched depending on the value of b0 (0 to 1). There are four coding tables for b2 (CTb20, CTb21, CTb22, CTb23). The coding table is switched depending on the values ​​of b0 and b1 (0 to 3). There are two coding tables for bn-1 (CTb0, CTb10, CTb11). n-1 pieces (CTbn0, CTbn1, …, CTbn(2 n-1 -1)) and the value of b0b1...bn-2 (0 to 2 n-1 The encoding table is switched according to -1).

[0476] Fig. 86 is a diagram for explaining processing when, for example, the residual code is an exponential-Golomb code. The portion (residual code) that the three-dimensional data encoding device binarizes and encodes using the exponential-Golomb code includes a prefix portion and a suffix portion, as shown in Fig. 86. For example, the three-dimensional data decoding device switches the encoding table between the prefix portion and the suffix portion. That is, the three-dimensional data decoding device arithmetically decodes each bit included in the prefix portion using the encoding table for the prefix, and arithmetically decodes each bit included in the suffix portion using the encoding table for the suffix.

[0477] The three-dimensional data decoding device may update the occurrence probabilities of 0 and 1 in each encoding table according to the value of the binarized data generated during decoding. Alternatively, the three-dimensional data decoding device may fix the occurrence probabilities of 0 and 1 in one of the encoding tables. This reduces the number of updates to the occurrence probabilities, thereby reducing the amount of processing. For example, the three-dimensional data decoding device may update the occurrence probabilities for the prefix part and fix the occurrence probabilities for the suffix part.

[0478] Furthermore, the three-dimensional data decoding device decodes the quantized prediction residual (unsigned integer value) by multi-valuing the binary data of the arithmetically decoded prediction residual in accordance with the encoding method used in the three-dimensional data encoding device. The three-dimensional data decoding device first calculates the value of the decoded n-bit code by arithmetically decoding the binary data of the n-bit code. Next, the three-dimensional data decoding device compares the value of the n-bit code with the value of R_TH.

[0479] When the value of the n-bit code matches the value of R_TH, the three-dimensional data decoding device determines that a bit coded using the exponential-Golomb method exists next, and arithmetically decodes the remaining code, which is binary data coded using the exponential-Golomb method.The three-dimensional data decoding device then calculates the value of the remaining code from the decoded remaining code using a reverse lookup table showing the relationship between the remaining code and its value. Figure 87 is a diagram showing an example of a reverse lookup table showing the relationship between the remaining code and its value.Next, the three-dimensional data decoding device adds the value of the obtained remaining code to R_TH to obtain a multi-valued post-quantization prediction residual.

[0480] On the other hand, if the value of the n-bit code does not match the value of R_TH (the value is smaller than R_TH), the three-dimensional data decoding device determines the value of the n-bit code as the multi-valued post-quantization prediction residual. This allows the three-dimensional data decoding device to properly decode the bitstream generated by the three-dimensional data encoding device by switching the binarization method according to the value of the prediction residual.

[0481] If the threshold value R_TH is added to the header or the like of the bitstream, the three-dimensional data decoding device may decode the value of the threshold value R_TH from the header and switch the decoding method using the decoded threshold value R_TH. Also, if the threshold value R_TH is added to the header or the like for each LoD, the three-dimensional data decoding device switches the decoding method using the decoded threshold value R_TH for each LoD.

[0482] For example, if the threshold value R_TH is 63 and the value of the decoded n-bit code is 63, the three-dimensional data decoding device obtains the value of the residual code by decoding the residual code using the Exponential Golomb method. For example, in the example shown in FIG. 87, the residual code is 00100, and the value of the residual code is obtained as 3. Next, the three-dimensional data decoding device obtains the value of the prediction residual, 66, by adding the value of the threshold value R_TH, 63, and the value of the residual code, 3.

[0483] Furthermore, if the value of the decoded n-bit code is 32, the three-dimensional data decoding device sets the value of the n-bit code, 32, as the value of the prediction residual.

[0484] Furthermore, the three-dimensional data decoding device converts the decoded quantized prediction residuals from unsigned integer values ​​to signed integer values, for example, by a process reverse to that performed by the three-dimensional data encoding device. This allows the three-dimensional data decoding device to appropriately decode the generated bitstream when entropy encoding the prediction residuals, without taking into account the occurrence of negative integers. Note that the three-dimensional data decoding device does not necessarily need to convert unsigned integer values ​​to signed integer values; for example, when decoding a bitstream generated by separately entropy encoding the sign bits, the sign bits may be decoded.

[0485] The three-dimensional data decoding device generates decoded values ​​by decoding the quantized prediction residuals converted into signed integer values ​​through inverse quantization and reconstruction. The three-dimensional data decoding device also uses the generated decoded values ​​for prediction of the three-dimensional point to be decoded and thereafter. Specifically, the three-dimensional data decoding device calculates an inverse quantization value by multiplying the quantized prediction residuals by the decoded quantization scale, and obtains a decoded value by adding the inverse quantization value and the prediction value.

[0486] The decoded unsigned integer value (unsigned quantized value) is converted into a signed integer value by the following process. If the LSB (least significant bit) of the decoded unsigned integer value a2u is 1, the three-dimensional data decoding device sets the signed integer value a2q to -((a2u+1)>>1). If the LSB of the unsigned integer value a2u is not 1, the three-dimensional data decoding device sets the signed integer value a2q to (a2u>>1).

[0487] Similarly, if the LSB of the decoded unsigned integer value b2u is 1, the three-dimensional data decoding device sets the signed integer value b2q to -((b2u+1)>>1). If the LSB of the unsigned integer value n2u is not 1, the three-dimensional data decoding device sets the signed integer value b2q to (b2u>>1).

[0488] Furthermore, the details of the inverse quantization and reconstruction processing by the three-dimensional data decoding device are the same as those of the inverse quantization and reconstruction processing by the three-dimensional data encoding device.

[0489] The flow of processing in the three-dimensional data decoding device will be explained below. Figure 88 is a flowchart of three-dimensional data decoding processing by the three-dimensional data decoding device. First, the three-dimensional data decoding device decodes position information (geometry) from the bitstream (S5631). For example, the three-dimensional data decoding device performs decoding using an octree representation.

[0490] Next, the three-dimensional data decoding device decodes attribute information (Attribute) from the bitstream (S5632). For example, when decoding multiple types of attribute information, the three-dimensional data decoding device may decode the multiple types of attribute information in order. For example, when decoding color, reflectance, and frame index as attribute information, the three-dimensional data decoding device decodes the encoding result of color, the encoding result of reflectance, and the encoding result of frame index in the order in which they are added to the bitstream. For example, if the encoding result of reflectance is added after the encoding result of color in the bitstream, the three-dimensional data decoding device decodes the encoding result of color, and then the encoding result of reflectance. Also, if the encoding result of frame index is added after the encoding result of reflectance in the bitstream, the three-dimensional data decoding device decodes the encoding result of frame index after the decoding of the encoding result of reflectance. Note that the three-dimensional data decoding device may decode the encoding results of attribute information added to the bitstream in any order.

[0491] Furthermore, the three-dimensional data decoding device may obtain information indicating the start location of the encoded data for each piece of attribute information in the bitstream by decoding a header or the like. This allows the three-dimensional data decoding device to selectively decode attribute information that requires decoding, thereby omitting the decoding process for attribute information that does not require decoding. This reduces the amount of processing required by the three-dimensional data decoding device. Furthermore, the three-dimensional data decoding device may decode multiple types of attribute information in parallel and integrate the decoding results into a single three-dimensional point cloud. This allows the three-dimensional data decoding device to decode multiple types of attribute information at high speed.

[0492] Next, the three-dimensional data decoding device divides the decoded three-dimensional point cloud into multiple frames based on the value of the decoded frame index together with the position information of each three-dimensional point (S5633). For example, if the frame index of the decoded three-dimensional point a is 0, the three-dimensional data decoding device adds the position information and attribute information of the three-dimensional point a to frame 0, and if the frame index of the decoded three-dimensional point b is 1, the three-dimensional data decoding device adds the position information and attribute information of the three-dimensional point b to frame 1, thereby dividing the three-dimensional point cloud obtained by decoding into multiple three-dimensional point clouds each belonging to a different multiple frames.

[0493] 89 is a flowchart of the attribute information decoding process (S5632). First, the three-dimensional data decoding device sets the LoD (S5641). That is, the three-dimensional data decoding device assigns each of the multiple three-dimensional points having decoded position information to one of the multiple LoDs. For example, this assignment method is the same as the assignment method used in the three-dimensional data encoding device.

[0494] Next, the three-dimensional data decoding device starts a loop for each LoD (S5642). That is, the three-dimensional data decoding device repeatedly performs the processes of steps S5643 to S5649 for each LoD.

[0495] Next, the three-dimensional data decoding device starts a loop for each three-dimensional point (S5643). That is, the three-dimensional data decoding device repeatedly performs the processes of steps S5644 to S5648 for each three-dimensional point.

[0496] First, the three-dimensional data decoding device searches for a plurality of surrounding points, which are three-dimensional points existing around the target three-dimensional point to be processed, and are used to calculate a predicted value of the target three-dimensional point (S5644). Next, the three-dimensional data decoding device calculates a weighted average of the values ​​of the attribute information of the plurality of surrounding points, and sets the obtained value as the predicted value P (S5645). Note that these processes are similar to those in the three-dimensional data encoding device.

[0497] Next, the three-dimensional data decoding device arithmetically decodes the quantized value from the bitstream (S5646). The three-dimensional data decoding device also calculates an inverse quantized value by inverse quantizing the decoded quantized value (S5647). Next, the three-dimensional data decoding device generates a decoded value by adding a predicted value to the inverse quantized value (S5648). Next, the three-dimensional data decoding device ends the loop in three-dimensional point units (S5649). The three-dimensional data decoding device also ends the loop in LoD units (S5650).

[0498] Next, the configurations of a three-dimensional data encoding device and a three-dimensional data decoding device according to this embodiment will be described. Fig. 90 is a block diagram showing the configuration of a three-dimensional data encoding device 5600 according to this embodiment. This three-dimensional data encoding device 5600 includes a frame combining unit 5601, a position information encoding unit 5602, an attribute information reallocation unit 5603, and an attribute information encoding unit 5604.

[0499] The frame combining unit 5601 combines multiple frames. The position information encoding unit 5602 encodes the position information (geometry) of multiple 3D points included in the input point cloud. The attribute information reallocation unit 5603 reallocates the values ​​of the attribute information of multiple 3D points included in the input point cloud using the results of encoding and decoding the position information. The attribute information encoding unit 5604 encodes the reallocated attribute information. In addition, the 3D data encoding device 5600 generates a bitstream including the encoded position information and encoded attribute information.

[0500] 91 is a block diagram showing the configuration of a three-dimensional data decoding device 5610 according to this embodiment. This three-dimensional data decoding device 5610 includes a position information decoding unit 5611, an attribute information decoding unit 5612, and a frame dividing unit 5613.

[0501] The position information decoding unit 5611 decodes position information (geometry) of multiple 3D points from the bitstream. The attribute information decoding unit 5612 decodes attribute information (attribute) of multiple 3D points from the bitstream. The frame dividing unit 5613 divides the decoded 3D point cloud into multiple frames based on the frame index values ​​decoded together with the position information of each 3D point. The 3D data decoding device 5610 also generates an output point cloud by combining the decoded position information and the decoded attribute information.

[0502] Fig. 92 is a diagram showing the structure of attribute information, where (a) in Fig. 92 shows the structure of compressed attribute information, (b) in Fig. 92 shows an example of the syntax of the header of the attribute information, and (c) in Fig. 92 shows an example of the syntax of the payload (data) of the attribute information.

[0503] As shown in (b) of Figure 92, the syntax of the attribute information header will be described. apx_idx indicates the ID of the corresponding parameter set. If there is a parameter set for each frame, multiple IDs may be indicated in apx_idx. offset indicates the offset position for acquiring the combined data. other_attribute_information indicates other attribute data, such as QP delta indicating the difference value of the quantization parameter. combine_frame_flag is a flag indicating whether the coded data is frame combined. number_of _combine_frame indicates the number N of combined frames. number_of _combine_frame may be included in the SPS or APS.

[0504] "refer_different_frame" is a flag that indicates whether the attribute information of a target 3D point to be encoded / decoded is encoded / decoded using attribute information of surrounding 3D points that belong to the same frame, or the same frame and frames other than the same frame. For example, the following values ​​can be assigned: When "refer_different_frame" is 0, the 3D data encoding device or 3D data decoding device encodes / decodes the attribute information of the target 3D point using attribute information of surrounding 3D points in the same frame as the target 3D point. In this case, the 3D data encoding device or 3D data decoding device does not encode / decode the attribute information of the target 3D point using attribute information of surrounding 3D points in frames different from the target 3D point.

[0505] On the other hand, when refer_different_frame is 1, the 3D data encoding device or 3D data decoding device encodes / decodes the attribute information of the target 3D point using attribute information of surrounding 3D points in the same frame as the frame to which the target 3D point belongs and in frames other than the same frame. In other words, the 3D data encoding device or 3D data decoding device encodes / decodes the attribute information of the target 3D point using attribute information of surrounding 3D points, regardless of whether they belong to the same frame as the frame to which the target 3D point belongs.

[0506] Although an example has been shown in which color information or reflectance information is encoded using attribute information of surrounding 3D points as attribute information of a target 3D point, the frame index of the target 3D point may also be encoded using frame indexes of the surrounding 3D points. The 3D data encoding device may, for example, use the frame index added to each 3D point when combining multiple frames as attribute information of each 3D point and encode using the predictive encoding method described in this disclosure. For example, the 3D data encoding device may calculate a predicted value of the frame index of 3D point A from the frame index values ​​of 3D points B, C, and D surrounding 3D point A and encode the prediction residual. This allows the 3D data encoding device to reduce the amount of bits required to encode the frame index and improve encoding efficiency.

[0507] FIG. 93 is a diagram illustrating coded data.

[0508] When the point cloud data includes attribute information, the attribute information may be frame-combined. The attribute information is encoded or decoded with reference to position information. The referenced position information may be the position information before frame combining or the position information after frame combining. The number of combined frames of the position information and the number of combined frames of the attribute information may be the same or may be independent and different.

[0509] The numbers in parentheses in Figure 93 indicate frames; for example, 1 indicates information on frame 1, and 1-4 indicates information on combined frames 1 to 4. Also, G indicates position information, and A indicates attribute information. Frame_idx1 is the frame index of frame 1.

[0510] (a) of Figure 93 shows an example when refer_different_frame is 1. When refer_different_frame is 1, the three-dimensional data encoding device or three-dimensional data decoding device encodes or decodes A(1-4) based on the information of G(1-4). When decoding, the three-dimensional data decoding device divides G(1-4) and A(1-4) into Frames 1-4 using Frame_idx1-4 decoded together with G(1-4). When encoding or decoding A(1-4), the three-dimensional data encoding device or three-dimensional data decoding device may refer to other attribute information of A(1-4). In other words, when encoding or decoding A(1), the three-dimensional data encoding device or three-dimensional data decoding device may refer to another A(1) or A(2-4). Furthermore, arrows indicate the source and destination of information reference, with the origin of the arrow indicating the source and the tip of the arrow indicating the destination.

[0511] (b) of Figure 93 shows an example when refer_different_frame is 0. When refer_different_frame is 0, the three-dimensional data encoding device or three-dimensional data decoding device does not refer to the attribute information of different frames, unlike when refer_different_frame is 1. In other words, when encoding or decoding A(1), the three-dimensional data encoding device or three-dimensional data decoding device refers to other A(1), but does not refer to A(2-4).

[0512] (c) of Figure 93 shows another example when refer_different_frame is 0. In this case, the position information is coded in the combined frame, but the attribute information is coded for each frame. Therefore, when coding or decoding A(1), the three-dimensional data coding device or three-dimensional data decoding device refers to other A(1). Similarly, when coding or decoding attribute information, it refers to other attribute information belonging to the same frame. Note that A(1-4) may add their respective APSs to their headers.

[0513] As described above, the three-dimensional data encoding device according to this embodiment performs the processing shown in Fig. 94. The three-dimensional data encoding device acquires third point cloud data obtained by combining the first point cloud data and the second point cloud data, the third point cloud data including position information for each of a plurality of three-dimensional points included in the third point cloud data and identification information indicating whether each of the plurality of three-dimensional points belongs to the first point cloud data or the second point cloud data (S5661). Next, the three-dimensional data encoding device generates encoded data by encoding the acquired third point cloud data (S5662). In generating the encoded data, the three-dimensional data encoding device encodes the identification information for each of a plurality of three-dimensional points as attribute information for the three-dimensional point.

[0514] According to this, the three-dimensional data encoding method can improve encoding efficiency by encoding a plurality of point group data collectively.

[0515] For example, in generating encoded data (S5662), attribute information of a first 3D point is encoded using attribute information of second 3D points surrounding the first 3D point among the plurality of 3D points.

[0516] For example, the attribute information of the first 3D point includes first identification information indicating that the first 3D point belongs to the first point cloud data, and the attribute information of the second 3D point includes second identification information indicating that the second 3D point belongs to the second point cloud data.

[0517] For example, in generating coded data (S5662), a predicted value of attribute information of a first three-dimensional point is calculated using attribute information of a second three-dimensional point, a prediction residual, which is the difference between the attribute information of the first three-dimensional point and the predicted value, is calculated, and coded data including the prediction residual is generated.

[0518] For example, in the acquisition (S5661), the third point cloud data is acquired by generating the third point cloud data by combining the first point cloud data and the second point cloud data.

[0519] For example, the coded data includes the identification information in the same data format as other attribute information different from the identification information.

[0520] For example, the three-dimensional data encoding device includes a processor and a memory, and the processor performs the above-mentioned processing using the memory.

[0521] Furthermore, the three-dimensional data decoding device according to this embodiment performs the processing shown in Fig. 95. The three-dimensional data decoding device acquires encoded data (S5671). Next, the three-dimensional data decoding device decodes the encoded data to acquire position information and attribute information for each of a plurality of three-dimensional points included in third point cloud data formed by combining the first point cloud data and the second point cloud data (S5672). Note that the attribute information includes identification information indicating whether the three-dimensional point corresponding to the attribute information belongs to the first point cloud data or the second point cloud data.

[0522] According to this, the three-dimensional data decoding device can decode coded data with improved coding efficiency by collectively coding a plurality of point cloud data.

[0523] For example, in the acquisition (S5671), the attribute information of the first 3D point is decoded using the attribute information of the second 3D point surrounding the first 3D point among the plurality of 3D points.

[0524] For example, the attribute information of the first 3D point includes first identification information indicating that the first 3D point belongs to the first point cloud data, and the attribute information of the second 3D point includes second identification information indicating that the second 3D point belongs to the second point cloud data.

[0525] For example, the coded data includes a prediction residual. Then, in decoding the coded data (S5672), a predicted value of attribute information of the first 3D point is calculated using attribute information of the second 3D point, and the predicted value and the prediction residual are added together to calculate the attribute information of the first 3D point.

[0526] For example, the three-dimensional data decoding device further divides the data into third three-dimensional point cloud data, first point cloud data, and second point cloud data using the identification information.

[0527] For example, the coded data includes the identification information in the same data format as other attribute information different from the identification information.

[0528] For example, the three-dimensional data decoding device includes a processor and a memory, and the processor performs the above processing using the memory.

[0529] (Embodiment 7) As described above, when combining multiple frames, the frame index (frame_idx) added to each three-dimensional point is stored as new attribute information rather than as position information for each three-dimensional point. In this case, a specific example of a method for encoding using the predictive encoding method described in this disclosure will be described.

[0530] Fig. 96 is a diagram showing an example of coded data (bit stream) according to this embodiment. For example, as shown in Fig. 96, when point cloud data has position information G (Geometry) and first attribute information A1 (Attribute) (e.g., color) and frame splicing is applied, the three-dimensional data coding device codes a frame index as second attribute information A2. Furthermore, the three-dimensional data coding device stores identification information indicating that the type of the attribute information is a frame index in an SPS (Sequence Parameter Set). In other words, the identification information indicates attribute information that includes (indicates) a frame index among multiple pieces of attribute information. In other words, the identification information indicates whether or not each piece of multiple attribute information is attribute information that includes a frame index.

[0531] The SPS is a parameter set common to multiple frames (multiple combined frames) and is a parameter set common to position information and attribute information. Note that the identification information may be included in control information (metadata) other than the SPS. For example, the identification information may be included in the APS, etc.

[0532] FIG. 96 shows an example of coded data obtained by coding a combined frame formed by combining four frames, frames 1 to 4. In the figure, G(1-4) is position information of the combined frame. A1(1-4) is first attribute information of the combined frame, such as color information. A2(1-4) is second attribute information, indicating frame indexes for frames 1 to 4.

[0533] Furthermore, GPS(1-4) is a parameter set for G(1-4), APS1(1-4) is a parameter set for A1(1-4), and APS2(1-4) is a parameter set for A2(1-4).

[0534] For example, A1(1-4) is coded or decoded using information on G(1-4). Note that A1(1-4) may refer to each other. Furthermore, during decoding, G(1-4) and A(1-4) are divided into frames 1 to 4 using frame indexes 1 to 4 that are decoded together with G(1-4).

[0535] It may be specified that a lossless encoding method must be used when transmitting a frame index as attribute information. For example, a lossless encoding method is an encoding method that does not perform quantization. Furthermore, when a frame index is attribute information, a restriction may be imposed on the quantization parameter so that lossless encoding is performed. The three-dimensional data encoding device may store information indicating the encoding method or quantization parameter used in the bitstream.

[0536] The three-dimensional data encoding device may use a lossless encoding method or a lossy encoding method for part or all of the attribute information other than the position information and the frame index.

[0537] In addition to the frame index, the three-dimensional data encoding device may also transmit information for each frame as second attribute information. For example, the information for each frame may be a timestamp indicating the generation time, encoding time, or decoding time of the frame data. Alternatively, the information for each frame may be sensor information obtained when the frame data was acquired. The sensor information may include the speed, acceleration, position information, or orientation of the sensor.

[0538] Next, an example of compressing a 3D point group that does not have attribute information such as color or reflectance will be described. Fig. 97 is a diagram showing an example of encoded data in this case.

[0539] When performing frame splicing, the three-dimensional data encoding device generates attribute information A1 and transmits encoded data including the generated attribute information A1. Here, the attribute information A1 indicates a frame index.

[0540] Note that, in a case where the number of combined frames is variable, the three-dimensional data encoding device may not generate a frame index if the number of combined frames is 1. In this case, the three-dimensional data decoding device may determine that the number of combined frames is 1 if there is no attribute information indicating a frame index.

[0541] A three-dimensional data encoding device that performs motion compensation will be described below. For example, when one or more point cloud data sets that differ over time are acquired using a LiDAR or other device carried by a moving object, the objects that make up the first point cloud and the objects that make up the second point cloud may move. When combining such different PCC point clouds or point cloud frames, if the objects in the point clouds move slowly, there is a high possibility that they can share an octree, but if the objects move quickly, there is a high possibility that they cannot share an octree.

[0542] Therefore, the three-dimensional data encoding device predicts the motion between different frames, corrects the point clouds based on the motion, and then combines the point clouds. Figure 98 is a flowchart of the three-dimensional data encoding process in this case.

[0543] First, the three-dimensional data encoding device calculates a motion vector (motion information) indicating the motion between frames by predicting the motion between frames using motion prediction (S5801). For example, the three-dimensional data encoding device generates a motion vector by comparing a point cloud of a current frame with a point cloud of a past frame. Specifically, the three-dimensional data encoding device detects the positions of the same object included in the two frames and determines the motion based on the difference between the detected positions. Note that, in comparing the point clouds, the three-dimensional data encoding device may use some or all of the point clouds included in the frames. Furthermore, the three-dimensional data encoding device may extract feature points using position information or attribute information and predict the motion of the feature points.

[0544] Next, the three-dimensional data encoding device performs motion compensation using the calculated motion vector (S5802). Figure 99 shows an example of this motion compensation and frame splicing. (a) in the figure shows an example when motion compensation is not performed, and (b) in the figure shows an example when motion compensation is performed. For example, as shown in (b) in the figure, the three-dimensional data encoding device predicts the movement of the point cloud from frame 1 to frame 2, and corrects the position of the point cloud in frame 2 by moving the position of the point cloud in frame 2 by the amount of the movement.

[0545] Next, the three-dimensional data encoding device generates a combined frame by combining frame 1 and corrected frame 2 (S5803). Next, the three-dimensional data encoding device encodes the position information of the combined frame (S5804).

[0546] Next, the three-dimensional data encoding device converts the attribute information (S5805) and encodes the converted attribute information (S5806). Note that in converting the attribute information, for example, if the position of a three-dimensional point has changed due to quantization or the like, a process is performed in which the attribute information of the original three-dimensional point is reassigned to the changed three-dimensional point.

[0547] Next, a three-dimensional data decoding device that performs motion compensation will be described. Fig. 100 is a diagram showing an example of transmission of motion vectors from a three-dimensional data encoding device 5800 to a three-dimensional data decoding device 5810. Fig. 101 is a diagram showing an example of encoded data (bit stream).

[0548] The three-dimensional data encoding device 5800 stores the motion vector in control information (metadata) for each frame, such as GPS, and transmits it. The three-dimensional data encoding device 5800 may store the motion vector in the header of the position information, or may store it in the payload of the position information. Alternatively, the three-dimensional data encoding device 5800 may store the motion vector in other control information, such as SPS or APS. For example, the three-dimensional data encoding device 5800 stores the motion vector for each frame to be combined in GPS, as shown in FIG. 101.

[0549] 102 is a block diagram showing the configuration of a three-dimensional data decoding device 5810 according to this embodiment. The three-dimensional data decoding device 5810 includes a position information decoding unit 5811, an attribute information decoding unit 5812, a frame dividing unit 5813, and a motion compensation unit 5814.

[0550] The position information decoding unit 5811 decodes position information from the bitstream. The attribute information decoding unit 5812 decodes attribute information from the bitstream. The frame dividing unit 5813 divides the decoded combined frame (position information and attribute information) into multiple frames. The motion correction unit 5814 corrects the multiple divided frames using motion vectors to generate point cloud data for multiple frames. In other words, the motion correction unit 5814 uses motion vectors to perform processing to return the positions of points shifted in the three-dimensional data encoding device to their original positions.

[0551] Next, an example of a method for calculating a motion vector will be described. Fig. 103 is a diagram showing an example of a method for calculating a motion vector. The dotted line frame in Fig. 103 indicates a group of frames to be combined.

[0552] For example, as shown in (a) of the same figure, the three-dimensional data encoding device may derive and transmit a motion vector by comparing the current frame with the frame immediately preceding the current frame. In this case, for example, the three-dimensional data encoding device does not derive and transmit a motion vector for the first frame. Alternatively, as shown in (c) of the same figure, the three-dimensional data encoding device may derive and transmit a motion vector for the first frame by comparing it with the previous frame. Furthermore, as shown in (b) of the same figure, the three-dimensional data encoding device may derive and transmit a motion vector by comparing the current frame with the first frame of the group of frames to be combined.

[0553] Figure 104 is a diagram showing an example of a method for calculating a motion vector when inter prediction is applied. When inter prediction is applied, the 3D data encoding device may, for example, compare the current frame with the first frame of a GOF to derive a motion vector. Alternatively, the 3D data encoding device may derive a motion vector between the first frames of GOFs. Here, a GOF is a processing unit including multiple frames, and is, for example, a random access unit including an I frame.

[0554] In addition, the three-dimensional data encoding device may generate the motion vector from point cloud information, or may calculate it based on any one or more pieces of information such as the position information, velocity, and acceleration of the sensor when the point cloud was acquired.

[0555] Next, a case where tile division is used will be described. When a large-scale point cloud is divided into tiles, the magnitude of the motion vector between frames may differ for each tile.

[0556] Therefore, the three-dimensional data encoding device may determine whether to apply a motion vector for each tile. The three-dimensional data encoding device may change the method of deriving or compensating for a motion vector for each tile. For example, by deriving a motion vector for each tile, the three-dimensional data encoding device can apply appropriate motion compensation even when there are tiles with large motion vectors and tiles with small motion vectors.

[0557] Furthermore, the three-dimensional data encoding device may store in the bitstream a signal indicating whether a motion vector has been applied to each tile, and the method of deriving or compensating for the motion vector.

[0558] Note that when motion compensation is performed, the area of ​​the set of points may become larger due to a position offset. In this case, the three-dimensional data encoding device may either expand the bounding box, or convert the positions of the point cloud to positions within the existing bounding box without expanding the bounding box.

[0559] Fig. 105 is a diagram showing an example of coded data in this case. As shown in Fig. 105, for example, the motion vector of each tile may be stored in a GPS or the like.

[0560] Fig. 106 is a diagram showing an example of tiles to which motion compensation is applied. As shown in Fig. 106, for example, the three-dimensional data encoding device does not apply motion compensation to tiles close to a moving body such as a vehicle, but applies motion compensation to tiles far from the moving body.

[0561] As described above, the three-dimensional data encoding device according to this embodiment performs the processing shown in FIG. 107. First, the three-dimensional data encoding device generates encoded data by encoding third point cloud data obtained by combining the first point cloud data and the second point cloud data (S5811). The three-dimensional data encoding device generates a bit stream including encoded data and control information (S5812). The encoded data includes position information and multiple pieces of attribute information for each of multiple three-dimensional points included in the third point cloud data. One of the multiple pieces of attribute information includes first information (e.g., a frame index) indicating whether the corresponding three-dimensional point belongs to the first point cloud data or the second point cloud data. The control information includes second information (e.g., identification information) indicating which of the multiple pieces of attribute information includes the first information.

[0562] According to this, when the first information is included in any of a plurality of pieces of attribute information, a three-dimensional data decoding device that decodes a bitstream generated by a three-dimensional data encoding device can easily determine which piece of attribute information includes the first information by using the second information included in the control information. Therefore, the three-dimensional data encoding device can reduce the processing load of the three-dimensional data decoding device.

[0563] For example, the control information is control information (such as SPS) common to multiple frames. For example, the third point cloud data is multiple point cloud data at multiple times, and the control information is control information common to the multiple point cloud data.

[0564] For example, the three-dimensional data encoding device encodes the attribute information including the first information using a lossless encoding method. For example, the three-dimensional data encoding device sets a quantization parameter so that the lossless encoding method is used. For example, the three-dimensional data encoding device stores information indicating the set quantization parameter in a bitstream.

[0565] For example, the three-dimensional data encoding device corrects the positions of the point clouds included in the second point cloud data using motion information (e.g., motion vectors) indicating the motion between the first point cloud data and the second point cloud data, and generates third point cloud data by integrating the first point cloud data with the corrected second point cloud data, and the encoded data includes the motion information.

[0566] This allows the three-dimensional data encoding device to bring the positions of the point groups to be connected closer together, thereby improving encoding efficiency.

[0567] For example, the three-dimensional data encoding device includes a processor and a memory, and the processor performs the above-mentioned processing using the memory.

[0568] Furthermore, the three-dimensional data decoding device according to this embodiment performs the processing shown in FIG. 108. First, the three-dimensional data decoding device acquires, from the bit stream, coded data including position information of each of a plurality of three-dimensional points included in third point cloud data obtained by combining the first point cloud data and the second point cloud data and a plurality of pieces of attribute information (S5821). The three-dimensional data decoding device acquires, from the control information included in the bit stream, second information (e.g., identification information) indicating attribute information including first information (e.g., a frame index) indicating whether the corresponding three-dimensional point belongs to the first point cloud data or the second point cloud data, among the plurality of pieces of attribute information (S5822). The three-dimensional data decoding device acquires the first information using the second information (S5823). For example, the three-dimensional data decoding device identifies attribute information including the first information using the second information, and acquires the first information from the identified attribute information.

[0569] According to this, when the first information is included in any of the plurality of pieces of attribute information, the three-dimensional data decoding device can easily determine the attribute information that includes the first information by using the second information included in the control information. Therefore, the three-dimensional data decoding device can reduce the amount of processing.

[0570] For example, the control information is control information common to multiple frames (for example, SPS).

[0571] For example, the attribute information including the first information is encoded using a lossless encoding method, and the three-dimensional data decoding device decodes the attribute information encoded using the lossless encoding method using a decoding method corresponding to the lossless encoding method.

[0572] For example, the quantization parameter is set so that a lossless encoding method is used. For example, the three-dimensional data decoding device obtains information indicating the quantization parameter set so that a lossless encoding method is used from the bitstream, and decodes the attribute information using the quantization parameter and the decoding method.

[0573] For example, the three-dimensional data decoding device separates the first point cloud data and the second point cloud data from the third point cloud data using the first information.

[0574] For example, the three-dimensional data decoding device obtains motion information indicating the motion between the first point cloud data and the second point cloud data from the bit stream, and uses the motion information to correct the positions of the points contained in the second point cloud data.

[0575] This allows the three-dimensional data decoding device to decode a bitstream with improved coding efficiency by bringing the positions of the connecting point groups closer together.

[0576] For example, the three-dimensional data decoding device includes a processor and a memory, and the processor performs the above processing using the memory.

[0577] Although the three-dimensional data encoding device and the three-dimensional data decoding device according to the embodiments of the present disclosure have been described above, the present disclosure is not limited to these embodiments.

[0578] Furthermore, each processing unit included in the three-dimensional data encoding device and three-dimensional data decoding device according to the above embodiments is typically realized as an LSI, which is an integrated circuit. These may be individually implemented as single chips, or some or all of them may be integrated into a single chip.

[0579] Furthermore, the integration is not limited to LSI, but may be realized by dedicated circuits or general-purpose processors. FPGAs (Field Programmable Gate Arrays), which can be programmed after LSI fabrication, or reconfigurable processors, which allow the connections and settings of circuit cells within LSIs to be reconfigured, may also be used.

[0580] In each of the above embodiments, each component may be configured with dedicated hardware, or may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0581] Furthermore, the present disclosure may be realized as a three-dimensional data encoding method or a three-dimensional data decoding method executed by a three-dimensional data encoding device, a three-dimensional data decoding device, or the like.

[0582] The division of functional blocks in the block diagram is an example, and multiple functional blocks may be realized as a single functional block, one functional block may be divided into multiple blocks, or some functions may be moved to another functional block.Furthermore, the functions of multiple functional blocks having similar functions may be processed in parallel or in time-sharing by a single piece of hardware or software.

[0583] The order in which the steps in the flowchart are executed is merely an example for specifically explaining the present disclosure, and other orders may be used. Some of the steps may be executed simultaneously (in parallel) with other steps.

[0584] While the three-dimensional data encoding device and three-dimensional data decoding device according to one or more aspects have been described above based on the embodiments, the present disclosure is not limited to these embodiments. As long as they do not deviate from the spirit of the present disclosure, various modifications conceivable by those skilled in the art to the present embodiments, and configurations constructed by combining components of different embodiments, may also be included within the scope of one or more aspects. [Industrial Applicability]

[0585] The present disclosure is applicable to a three-dimensional data encoding device and a three-dimensional data decoding device. [Explanation of symbols]

[0586] 4601 Three-dimensional data encoding system 4602 Three-dimensional data decoding system 4603 Sensor Terminal 4604 External connection part 4611 Point Cloud Data Generation System 4612 Presentation section 4613 Encoding section 4614 Multiplexer 4615 Input / output section 4616 Control Unit 4617 Sensor information acquisition unit 4618 Point Cloud Data Generation Unit 4621 Sensor Information Acquisition Unit 4622 Input / output section 4623 Demultiplexer 4624 Decoding Unit 4625 Presentation section 4626 User Interface 4627 Control Unit 4630 First Encoding Section 4631 Location information encoder 4632 Attribute information encoder 4633 Additional information coding unit 4634 Multiplexer 4640 First Decoding Unit 4641 Demultiplexer 4642 Location Information Decoding Unit 4643 Attribute Information Decoding Unit 4644 Additional information decoding unit 4650 Second Encoding Section 4651 Additional Information Generation Unit 4652 Position image generation unit 4653 Attribute Image Generation Unit 4654 Video Encoding Unit 4655 Additional information coding unit 4656 Multiplexer 4660 Second Decoding Unit 4661 Demultiplexer 4662 Video Decoding Unit 4663 Additional information decoding unit 4664 Location information generator 4665 Attribute information generation section 4801 Encoding section 4802 Multiplexer 4910 First Encoding Section 4911 Split section 4912 Location information encoder 4913 Attribute information encoder 4914 Additional information coding unit 4915 Multiplexer 4920 First Decoding Unit 4921 Demultiplexer 4922 Location Information Decoding Unit 4923 Attribute Information Decoding Unit 4924 Additional information decoding unit 4925 Joint 4931 Slice division part 4932 Location information tile division part 4933 Attribute information tile division part 4941 Location information tile joint 4942 Attribute information tile combination 4943 Slice Junction 5410 Encoding section 5411 Split section 5412 Location information encoder 5413 Attribute information encoder 5414 Additional information coding unit 5415 Multiplexer 5421 Tile division section 5422 Slice division part 5431, 5441 Frame index generation unit 5432, 5442 Entropy coding unit 5450 Decryption Unit 5451 Demultiplexer 5452 Location Information Decoding Unit 5453 Attribute Information Decoding Unit 5454 Additional information decoding unit 5455 Joint 5461, 5471 Entropy Decoding Unit 5462, 5472 Frame index acquisition section 5600 3D data encoding device 5601 Frame joint 5602 Location information encoder 5603 Attribute Information Reassignment Unit 5604 Attribute information encoder 5610 Three-dimensional data decoding device 5611 Location Information Decoding Unit 5612 Attribute Information Decoding Unit 5613 Frame division unit 5800 3D data encoding device 5810 Three-dimensional data decoding device 5811 Location Information Decoding Unit 5812 Attribute Information Decoding Unit 5813 Frame division unit 5814 Motion Compensation Unit

Claims

1. A three-dimensional data processing method for processing three-dimensional data using an apparatus including a processor and a memory, comprising: The processor uses the memory to: Acquire multiple three-dimensional data, each corresponding to different time information, Combining the plurality of three-dimensional data to generate combined three-dimensional data; each of the plurality of three-dimensional data includes a data set configured of three-dimensional position information and attribute information associated with the three-dimensional position information; the combined three-dimensional data includes the dataset and metadata; the metadata includes information indicating an attribute type of the data set included in the combined three-dimensional data, The information indicating the attribute type indicates that the attribute information of the data set included in the combined three-dimensional data is information related to the time information. Three-dimensional data processing methods.

2. A three-dimensional data processing device comprising a processor and a memory, The processor uses the memory to: Acquire multiple three-dimensional data, each corresponding to different time information, Combining the plurality of three-dimensional data to generate combined three-dimensional data; each of the plurality of three-dimensional data includes a data set configured of three-dimensional position information and attribute information associated with the three-dimensional position information; the combined three-dimensional data includes the dataset and metadata; the metadata includes information indicating an attribute type of the data set included in the combined three-dimensional data, The information indicating the attribute type indicates that the attribute information of the data set included in the combined three-dimensional data is information related to the time information. Three-dimensional data processing device.

3. 1. A three-dimensional data processing system, comprising: a three-dimensional data processing device; The three-dimensional data processing device includes: Acquire multiple three-dimensional data, each corresponding to different time information, Combining the plurality of three-dimensional data to generate combined three-dimensional data; each of the plurality of three-dimensional data includes a data set configured of three-dimensional position information and attribute information associated with the three-dimensional position information; the combined three-dimensional data includes the dataset and metadata; the metadata includes information indicating an attribute type of the data set included in the combined three-dimensional data, The information indicating the attribute type indicates that the attribute information of the data set included in the combined three-dimensional data is information related to the time information. Three-dimensional data processing system.

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