Patent Publication Number: US-2023154056-A1

Title: Three-dimensional data encoding method, three-dimensional data decoding method, three-dimensional data encoding device, and three-dimensional data decoding device

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is a U.S. continuation application of PCT International Patent Application Number PCT/JP2021/027117 filed on Jul. 20, 2021, claiming the benefit of priority of U.S. Provisional Patent Application No. 63/055,042 filed on Jul. 22, 2020, the entire contents of which are hereby incorporated by reference. 
    
    
     BACKGROUND 
     1. Technical Field 
     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. 
     2. Description of the Related Art 
     Devices or services utilizing three-dimensional data are expected to find their widespread use in a wide range of fields, such as computer vision that enables autonomous operations of cars or robots, map information, monitoring, infrastructure inspection, and video distribution. Three-dimensional data is obtained through various means including a distance sensor such as a rangefinder, as well as a stereo camera and a combination of a plurality of monocular cameras. 
     Methods of representing three-dimensional data include a method known as a point cloud scheme that represents the shape of a three-dimensional structure by a point cloud in a three-dimensional space. In the point cloud scheme, the positions and colors of a point cloud are stored. While point cloud is expected to be a mainstream method of representing three-dimensional data, a massive amount of data of a point cloud necessitates compression of the amount of three-dimensional data by encoding for accumulation and transmission, as in the case of a two-dimensional moving picture (examples include Moving Picture Experts Group-4 Advanced Video Coding (MPEG-4 AVC) and High Efficiency Video Coding (HEVC) standardized by MPEG). 
     Meanwhile, point cloud compression is partially supported by, for example, an open-source library (Point Cloud Library) for point cloud-related processing. 
     Furthermore, a technique for searching for and displaying a facility located in the surroundings of the vehicle by using three-dimensional map data is known (see, for example, Patent Literature (PTL) 1 (International Publication WO 2014/020663)). 
     SUMMARY 
     There is a demand for reducing the data amount of a bitstream including encoded three-dimensional data. 
     The present disclosure provides a three-dimensional data encoding method, a three-dimensional data decoding method, a three-dimensional data encoding device, or a three-dimensional decoding device capable of reducing the data amount. 
     A three-dimensional data encoding method according to an aspect of the present disclosure includes: encoding geometry information of a plurality of three-dimensional points represented by a tree structure; and generating a bitstream including the geometry information encoded and division number information indicating a total number of divisions of each of a plurality of nodes included in the tree structure, wherein the division number information includes common division number information collectively indicating the total number of divisions of two or more nodes among the plurality of nodes. 
     A three-dimensional data decoding method according to an aspect of the present disclosure includes: obtaining a bitstream including encoded geometry information and division number information, the encoded geometry information being geometry information of a plurality of three-dimensional points represented by a tree structure, the division number information indicating a total number of divisions of each of a plurality of nodes included in the tree structure; and decoding the encoded geometry information based on the division number information, wherein the division number information includes common division number information collectively indicating the total number of divisions of two or more nodes among the plurality of nodes. 
     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 decoding device capable of reducing the data amount. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
       These and other objects, advantages and features of the disclosure will become apparent from the following description thereof taken in conjunction with the accompanying drawings that illustrate a specific embodiment of the present disclosure. 
         FIG.  1    is a diagram illustrating a configuration of a three-dimensional data encoding and decoding system according to Embodiment 1; 
         FIG.  2    is a diagram illustrating a structure example of point cloud data according to Embodiment 1; 
         FIG.  3    is a diagram illustrating a structure example of a data file indicating the point cloud data according to Embodiment 1; 
         FIG.  4    is a diagram illustrating types of the point cloud data according to Embodiment 1; 
         FIG.  5    is a diagram illustrating a structure of a first encoder according to Embodiment 1; 
         FIG.  6    is a block diagram illustrating the first encoder according to Embodiment 1; 
         FIG.  7    is a diagram illustrating a structure of a first decoder according to Embodiment 1; 
         FIG.  8    is a block diagram illustrating the first decoder according to Embodiment 1; 
         FIG.  9    is a block diagram of a three-dimensional data encoding device according to Embodiment 1; 
         FIG.  10    is a diagram showing an example of geometry information according to Embodiment 1; 
         FIG.  11    is a diagram showing an example of an octree representation of geometry information according to Embodiment 1; 
         FIG.  12    is a block diagram of a three-dimensional data decoding device according to Embodiment 1; 
         FIG.  13    is a block diagram of an attribute information encoder according to Embodiment 1; 
         FIG.  14    is a block diagram of an attribute information decoder according to Embodiment 1; 
         FIG.  15    is a block diagram showing a configuration of the attribute information encoder according to the variation of Embodiment 1; 
         FIG.  16    is a block diagram of the attribute information encoder according to Embodiment 1; 
         FIG.  17    is a block diagram showing a configuration of the attribute information decoder according to the variation of Embodiment 1; 
         FIG.  18    is a block diagram of the attribute information decoder according to Embodiment 1; 
         FIG.  19    is a diagram illustrating a structure of a second encoder according to Embodiment 1; 
         FIG.  20    is a block diagram illustrating the second encoder according to Embodiment 1; 
         FIG.  21    is a diagram illustrating a structure of a second decoder according to Embodiment 1; 
         FIG.  22    is a block diagram illustrating the second decoder according to Embodiment 1; 
         FIG.  23    is a diagram illustrating a protocol stack related to PCC encoded data according to Embodiment 1; 
         FIG.  24    is a diagram illustrating structures of an encoder and a multiplexer according to Embodiment 2; 
         FIG.  25    is a diagram illustrating a structure example of encoded data according to Embodiment 2; 
         FIG.  26    is a diagram illustrating a structure example of encoded data and a NAL unit according to Embodiment 2; 
         FIG.  27    is a diagram illustrating a semantics example of pcc_nal_unit_type according to Embodiment 2; 
         FIG.  28    is a diagram illustrating an example of a transmitting order of NAL units according to Embodiment 2; 
         FIG.  29    is a diagram illustrating an example of position data according to Embodiment 3; 
         FIG.  30    is a diagram illustrating an example of a tree structure according to Embodiment 3; 
         FIG.  31    is a diagram illustrating the relationship between the number of divisions of a tree structure and tree_axis_flag according to Embodiment 3; 
         FIG.  32    is a diagram illustrating the relationship between the number of divisions of a tree structure and tree_axis_flag according to Embodiment 3; 
         FIG.  33    is a diagram illustrating the relationship between the number of divisions of a tree structure and tree_axis_flag according to Embodiment 3; 
         FIG.  34    is a diagram illustrating the relationship between the number of divisions of a tree structure and tree_axis_flag according to Embodiment 3; 
         FIG.  35    is a diagram illustrating the relationship between the number of divisions of a tree structure and tree_axis_flag according to Embodiment 3; 
         FIG.  36    is a diagram illustrating the relationship between the number of divisions of a tree structure and tree_axis_flag according to Embodiment 3; 
         FIG.  37    is a diagram illustrating the relationship between the number of divisions of a tree structure and tree_axis_flag according to Embodiment 3; 
         FIG.  38    is a block diagram of a three-dimensional data encoding device according to Embodiment 3; 
         FIG.  39    is a block diagram of a three-dimensional data decoding device according to Embodiment 3; 
         FIG.  40    is a flowchart illustrating a procedure for generating a flag indicating a tree structure that is performed by the three-dimensional data encoding device according to Embodiment 3; 
         FIG.  41    is a flowchart illustrating a procedure for determining a tree structure that is performed by the three-dimensional data decoding device according to Embodiment 3; 
         FIG.  42    is a flowchart illustrating a first example of a procedure for generating a flag indicating a tree structure that is performed by the three-dimensional data encoding device according to Embodiment 3; 
         FIG.  43    is a flowchart illustrating a first example of a procedure for determining a tree structure that is performed by the three-dimensional data decoding device according to Embodiment 3; 
         FIG.  44    is a diagram illustrating a first example of the syntax of header information according to Embodiment 3; 
         FIG.  45    is a diagram for describing a first example of the relationship between the depth and the number of divisions in a tree structure according to Embodiment 3; 
         FIG.  46    is a diagram illustrating a second example of the syntax of header information according to Embodiment 3; 
         FIG.  47    is a flowchart illustrating a second example of a procedure for determining a tree structure that is performed by the three-dimensional data decoding device according to Embodiment 3; 
         FIG.  48    is a diagram for describing a second example of the relationship between the depth and the number of divisions in a tree structure according to Embodiment 3; 
         FIG.  49    is a diagram illustrating a third example of the syntax of header information according to Embodiment 3; 
         FIG.  50    is a diagram for describing a third example of the relationship between the depth and the number of divisions in a tree structure according to Embodiment 3; 
         FIG.  51    is a diagram illustrating a fourth example of the syntax of header information according to Embodiment 3; 
         FIG.  52    is a diagram for describing a fourth example of the relationship between the depth and the number of divisions in a tree structure according to Embodiment 3; 
         FIG.  53    is a flowchart illustrating a procedure performed by the three-dimensional data encoding device according to Embodiment 3; 
         FIG.  54    is a flowchart illustrating a procedure performed by the three-dimensional data decoding device according to Embodiment 3; 
         FIG.  55    is a block diagram of a three-dimensional data creation device according to Embodiment 4; 
         FIG.  56    is a flowchart of a three-dimensional data creation method according to Embodiment 4; 
         FIG.  57    is a diagram showing a structure of a system according to Embodiment 4; 
         FIG.  58    is a block diagram of a client device according to Embodiment 4; 
         FIG.  59    is a block diagram of a server according to Embodiment 4; 
         FIG.  60    is a flowchart of a three-dimensional data creation process performed by the client device according to Embodiment 4; 
         FIG.  61    is a flowchart of a sensor information transmission process performed by the client device according to Embodiment 4; 
         FIG.  62    is a flowchart of a three-dimensional data creation process performed by the server according to Embodiment 4; 
         FIG.  63    is a flowchart of a three-dimensional map transmission process performed by the server according to Embodiment 4; 
         FIG.  64    is a diagram showing a structure of a variation of the system according to Embodiment 4; 
         FIG.  65    is a diagram showing a structure of the server and client devices according to Embodiment 4; 
         FIG.  66    is a diagram illustrating a configuration of a server and a client device according to Embodiment 4; 
         FIG.  67    is a flowchart of a process performed by the client device according to Embodiment 4; 
         FIG.  68    is a diagram illustrating a configuration of a sensor information collection system according to Embodiment 4; 
         FIG.  69    is a diagram illustrating an example of a system according to Embodiment 4; 
         FIG.  70    is a diagram illustrating a variation of the system according to Embodiment 4; 
         FIG.  71    is a flowchart illustrating an example of an application process according to Embodiment 4; 
         FIG.  72    is a diagram illustrating the sensor range of various sensors according to Embodiment 4; 
         FIG.  73    is a diagram illustrating a configuration example of an automated driving system according to Embodiment 4; 
         FIG.  74    is a diagram illustrating a configuration example of a bitstream according to Embodiment 4; 
         FIG.  75    is a flowchart of a point cloud selection process according to Embodiment 4; 
         FIG.  76    is a diagram illustrating a screen example for point cloud selection process according to Embodiment 4; 
         FIG.  77    is a diagram illustrating a screen example of the point cloud selection process according to Embodiment 4; and 
         FIG.  78    is a diagram illustrating a screen example of the point cloud selection process according to Embodiment 4. 
     
    
    
     DETAILED DESCRIPTION OF THE EMBODIMENTS 
     A three-dimensional data encoding method according to an aspect of the present disclosure includes: encoding geometry information of a plurality of three-dimensional points represented by a tree structure; and generating a bitstream including the geometry information encoded and division number information indicating a total number of divisions of each of a plurality of nodes included in the tree structure. The division number information includes common division number information collectively indicating the total number of divisions of two or more nodes among the plurality of nodes. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information. Therefore, the data amount included in the bitstream can be reduced. 
     Furthermore, for example, among the plurality of nodes, nodes located at a same depth in the tree structure are divided into a same number of divisions. The division number information indicates the total number of divisions of nodes for each of depths in the tree structure, and the common division number information collectively indicates the total number of divisions of nodes for two or more of the depths. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information for a plurality of depths, Therefore, the data amount included in the bitstream can be reduced. 
     Furthermore, for example, the common division number information includes trigger information indicating that nodes have a same number of divisions from a predetermined depth and beyond in the tree structure. 
     Accordingly, nodes that have the same number of divisions can be easily indicated by means of trigger information. 
     Furthermore, for example, the common division number information further includes end depth information indicating an end depth up to which the number of divisions of nodes from the predetermined depth is the same. 
     Accordingly, for example, when the numbers of divisions of nodes are viewed in order from the shallowest depth, if the number of divisions of nodes is successively the same from an intermediate depth, the number of divisions of the nodes can be easily indicated. 
     Furthermore, for example, the plurality of nodes each correspond to at least part of a space in a three-axis orthogonal coordinate system. The division number information includes flag information indicating, for each of depths in the tree structure, whether to divide the space in each of three axial directions of the three-axis orthogonal coordinate system. The trigger information is the flag information indicating not to divide the space in each of the three axial directions. 
     Accordingly, trigger information can be easily indicated using the flag information. 
     Furthermore, a three-dimensional data decoding method according to an aspect of the present disclosure includes: obtaining a bitstream including encoded geometry information and division number information, the encoded geometry information being geometry information of a plurality of three-dimensional points represented by a tree structure, the division number information indicating a total number of divisions of each of a plurality of nodes included in the tree structure; and decoding the encoded geometry information based on the division number information. The division number information includes common division number information collectively indicating the total number of divisions of two or more nodes among the plurality of nodes. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information. Therefore, the data amount included in the bitstream can be reduced. 
     Furthermore, for example, among the plurality of nodes, nodes located at a same depth in the tree structure are divided into a same number of divisions. The division number information indicates the total number of divisions of nodes for each of depths in the tree structure, and the common division number information collectively indicates the total number of divisions of nodes for two or more of the depths. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information for a plurality of depths. Therefore, the data amount included in the bitstream can be reduced. 
     Furthermore, for example, the common division number information includes trigger information indicating that nodes have a same number of divisions from a predetermined depth and beyond in the tree structure. 
     Accordingly, the number of divisions of nodes can be easily determined by means of trigger information. 
     Furthermore, for example, the common division number information further includes end depth information indicating an end depth up to which the number of divisions of nodes from the predetermined depth is the same. 
     Accordingly, for example, when the numbers of divisions of nodes are viewed in order from the shallowest depth, if the number of divisions of nodes is successively the same from an intermediate depth, the number of divisions of the nodes can be easily determined. 
     Furthermore, for example, the plurality of nodes each correspond to at least part of a space in a three-axis orthogonal coordinate system. The division number information includes flag information indicating, for each of depths in the tree structure, whether to divide the space in each of three axial directions of the three-axis orthogonal coordinate system. The trigger information is the flag information indicating not to divide the space in each of the three axial directions. 
     Accordingly, the number of division of nodes can be appropriately determined even with trigger information that is simply indicated using flag information. 
     Furthermore, a three-dimensional data encoding device according to an aspect of the present disclosure includes: a processor; and memory. Using the memory, the processor: encodes geometry information of a plurality of three-dimensional points represented by a tree structure; and generates a bitstream including the geometry information encoded and division number information indicating a total number of divisions of each of a plurality of nodes included in the tree structure. The division number information includes common division number information collectively indicating the total number of divisions of two or more nodes among the plurality of nodes. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information. Therefore, the data amount included in the bitstream can be reduced. 
     A three-dimensional data decoding device according to an aspect of the present disclosure includes: a processor; and memory. Using the memory, the processor: obtains a bitstream including encoded geometry information and division number information, the encoded geometry information being geometry information of a plurality of three-dimensional points represented by a tree structure, the division number information indicating a total number of divisions of each of a plurality of nodes included in the tree structure; and decodes the encoded geometry information based on the division number information. The division number information includes common division number information collectively indicating the total number of divisions of two or more nodes among the plurality of nodes. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information. Therefore, the data amount included in the bitstream can be reduced. 
     It is to be noted that these general or specific aspects may be implemented 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 implemented as any combination of a system, a method, an integrated circuit, a computer program, and a recording medium. 
     Hereinafter, embodiments will be specifically described with reference to the drawings. It is to be noted that each of the following embodiments indicate a specific example of the present disclosure. The numerical values, shapes, materials, constituent elements, the arrangement and connection of the constituent elements, steps, the processing order of the steps, etc., indicated in the following embodiments are mere examples, and thus are not intended to limit the present disclosure. Among the constituent elements described in the following embodiments, constituent elements not recited in any one of the independent claims that indicate the broadest concepts will be described as optional constituent elements. 
     Embodiment 1 
     When using encoded data of a point cloud in a device or for a service in practice, required information for the application is desirably transmitted and received in order to reduce the network bandwidth. However, conventional encoding structures for three-dimensional data have no such a function, and there is &amp;so no encoding method for such a function. 
     Embodiment 1 described below relates to a three-dimensional data encoding method and a three-dimensional data encoding device for encoded data of a three-dimensional point cloud that provides a function of transmitting and receiving required information for an application, a three-dimensional data decoding method and a three-dimensional data decoding device for decoding the encoded data, a three-dimensional data multiplexing method for multiplexing the encoded data, and a three-dimensional data transmission method for transmitting the encoded data. 
     In particular, at present, a first encoding method and a second encoding method are under investigation as encoding methods (encoding schemes) for point cloud data. However, there is no method defined for storing the configuration of encoded data and the encoded data in a system format. Thus, there is a problem that an encoder cannot perform an MUX process (multiplexing), transmission, or accumulation of data. 
     In addition, there is no method for supporting a format that involves two codecs, the first encoding method and the second encoding method, such as point cloud compression (PCC). 
     With regard to this embodiment, a configuration of PCC-encoded data that involves two codecs, a first encoding method and a second encoding method, and a method of storing the encoded data in a system format will be described. 
     A configuration of a three-dimensional data (point cloud data) encoding and decoding system according to this embodiment will be first described,  FIG.  1    is a diagram showing an example of a configuration of the three-dimensional data encoding and decoding system according to this embodiment. As shown in  FIG.  1   , the three-dimensional data encoding and decoding system includes three-dimensional data encoding system  4601 , three-dimensional data decoding system  4602 , sensor terminal  4603 , and external connector  4604 . 
     Three-dimensional data encoding system  4601  generates encoded data or multiplexed data by encoding point cloud data, which is three-dimensional data. Three-dimensional data encoding system  4601  may be a three-dimensional data encoding device implemented by a single device or a system implemented by a plurality of devices. The three-dimensional data encoding device may include a part of a plurality of processors included in three-dimensional data encoding system  4601 . 
     Three-dimensional data encoding system  4601  includes point cloud data generation system  4611 , presenter  4612 , encoder  4613 , multiplexer  4614 , input/output unit  4615 , and controller  4616 . Point cloud data generation system  4611  includes sensor information obtainer  4617 , and point cloud data generator  4618 . 
     Sensor information obtainer  4617  obtains sensor information from sensor terminal  4603 , and outputs the sensor information to point cloud data generator  4618 . Point cloud data generator  4618  generates point cloud data from the sensor information, and outputs the point cloud data to encoder  4613 . 
     Presenter  4612  presents the sensor information or point cloud data to a user. For example, presenter  4612  displays information or an image based on the sensor information or point cloud data. 
     Encoder  4613  encodes (compresses) the point cloud data, and outputs the resulting encoded data, control information (signaling information) obtained in the course of the encoding, and other additional information to multiplexer  4614 . The additional information includes the sensor information, for example. 
     Multiplexer  4614  generates multiplexed data by multiplexing the encoded data, the control information, and the additional information input thereto from encoder  4613 . A format of the multiplexed data is a file format for accumulation or a packet format for transmission, for example. 
     Input/output unit  4615  (a communication unit or interface, for example) outputs the multiplexed data to the outside. Alternatively, the multiplexed data may be accumulated in an accumulator, such as an internal memory. Controller  4616  (or an application executor) controls each processor. That is, controller  4616  controls the encoding, the multiplexing, or other processing. 
     Note that the sensor information may be input to encoder  4613  or multiplexer  4614 , Alternatively, input/output unit  4615  may output the point cloud data or encoded data to the outside as it is. 
     A transmission signal (multiplexed data) output from three-dimensional data encoding system  4601  is input to three-dimensional data decoding system  4602  via external connector  4604 . 
     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 three-dimensional data decoding system  4602  may be a three-dimensional data decoding device implemented by a single device or a system implemented by a plurality of devices. The three-dimensional data decoding device may include a part of a plurality of processors included in three-dimensional data decoding system  4602 . 
     Three-dimensional data decoding system  4602  includes sensor information obtainer  4621 , input/output unit  4622 , demultiplexer  4623 , decoder  4624 , presenter  4625 , user interface  4626 , and controller  4627 . Sensor information obtainer  4621  obtains sensor information from sensor terminal  4603 . 
     Input/output unit  4622  obtains the transmission signal, decodes the transmission signal into the multiplexed data (file format or packet), and outputs the multiplexed data to demultiplexer  4623 . 
     Demultiplexer  4623  obtains the encoded data, the control information, and the additional information from the multiplexed data, and outputs the encoded data, the control information, and the additional information to decoder  4624 . 
     Decoder  4624  reconstructs the point cloud data by decoding the encoded data. 
     Presenter  4625  presents the point cloud data to a user. For example, presenter  4625  displays information or an image based on the point cloud data. User interface  4626  obtains an indication based on a manipulation by the user. Controller  4627  (or an application executor) controls each processor. That is, controller  4627  controls the demultiplexing, the decoding, the presentation, or other processing. 
     Note that input/output unit  4622  may obtain the point cloud data or encoded data as it is from the outside. Presenter  4625  may obtain additional information, such as sensor information, and present information based on the additional information. Presenter  4625  may perform a presentation based on an indication from a user obtained on user interface  4626 . 
     Sensor terminal  4603  generates sensor information, which is information obtained by a sensor. Sensor terminal  4603  is a terminal provided with a sensor or a camera. For example, sensor terminal  4603  is a mobile body, such as an automobile, a flying object, such as an aircraft, a mobile terminal, or a camera. 
     Sensor information that can be generated by sensor terminal  4603  includes (1) the distance between sensor terminal  4603  and an object or the reflectance of the object obtained by LiDAR, a millimeter wave radar, or an infrared sensor or (2) the distance between a camera and an object or the reflectance of the object obtained by a plurality of monocular camera images or a stereo-camera image, for example. The sensor information may include the posture, orientation, gyro (angular velocity), position (GPS information or altitude), velocity, or acceleration of the sensor, for example. The sensor information may include aft temperature, aft pressure, air humidity, or magnetism, for example. 
     External connector  4604  is implemented by an integrated circuit (LSI or IC), an external accumulator, communication with a cloud server via the Internet, or broadcasting, for example. 
     Next, point cloud data will be described.  FIG.  2    is a diagram showing a configuration of point cloud data.  FIG.  3    is a diagram showing a configuration example of a data file describing information of the point cloud data. 
     Point cloud data includes data on a plurality of points. Data on each point includes geometry information (three-dimensional coordinates) and attribute information associated with the geometry information. A set of a plurality of such points is referred to as a point cloud. For example, a point cloud indicates a three-dimensional shape of an object. 
     Geometry information (position), such as three-dimensional coordinates, may be referred to as geometry. Data on each point may include attribute information (attribute) on a plurality of types of attributes. A type of attribute is color or reflectance, for example. 
     One item of attribute information (in other words, a piece of attribute information or an attribute information item) may be associated with one item of geometry information (in other words, a piece of geometry information or a geometry information item), or attribute information on a plurality of different types of attributes may be associated with one item of geometry information. Alternatively, items of attribute information on the same type of attribute may be associated with one item of geometry information. 
     The configuration example of a data file shown in  FIG.  3    is an example in which geometry information and attribute information are associated with each other in a one-to-one relationship, and geometry information and attribute information on N points forming point cloud data are shown. 
     The geometry information is information on three axes, specifically, an x-axis, a y-axis, and a z-axis, for example. The attribute information is RGB color information, for example. A representative data file is ply file, for example. 
     Next, types of point cloud data will be described.  FIG.  4    is a diagram showing types of point cloud data. As shown in  FIG.  4   , point cloud data includes a static object and a dynamic object. 
     The static object is three-dimensional point cloud data at an arbitrary time (a time point). The dynamic object is three-dimensional point cloud data that varies with time. In the following, three-dimensional point cloud data associated with a time point will be referred to as a PCC frame or a frame. 
     The object may be a point cloud whose range is limited to some extent, such as ordinary video data, or may be a large point cloud whose range is not limited, such as map information. 
     There are point cloud data having varying densities. There may be sparse point cloud data and dense point cloud data. 
     In the following, each processor will be described in detail. Sensor information is obtained by various means, including a distance sensor such as LiDAR or a range finder, a stereo camera, or a combination of a plurality of monocular cameras, Point cloud data generator  4618  generates point cloud data based on the sensor information obtained by sensor information obtainer  4617 , Point cloud data generator  4618  generates geometry information as point cloud data, and adds attribute information associated with the geometry information to the geometry information. 
     When generating geometry information or adding attribute information, point cloud data generator  4618  may process the point cloud data. For example, point cloud data generator  4618  may reduce the data amount by omitting a point cloud whose position coincides with the position of another point cloud. Point cloud data generator  4618  may also convert the geometry information (such as shifting, rotating or normalizing the position) or render the attribute information. 
     Note that, although  FIG.  1    shows point cloud data generation system  4611  as being included in three-dimensional data encoding system  4601 , point cloud data generation system  4611  may be independently provided outside three-dimensional data encoding system  4601 . 
     Encoder  4613  generates encoded data by encoding point cloud data according to an encoding method previously defined. In general, there are the two types of encoding methods described below. One is an encoding method using geometry information, which will be referred to as a first encoding method, hereinafter. The other is an encoding method using a video codec, which will be referred to as a second encoding method, hereinafter. 
     Decoder  4624  decodes the encoded data into the point cloud data using the encoding method previously defined. 
     Multiplexer  4614  generates multiplexed data by multiplexing the encoded data in an existing multiplexing method. The generated multiplexed data is transmitted or accumulated. Multiplexer  4614  multiplexes not only the PCC-encoded data but also another medium, such as a video, an audio, subtitles, an application, or a file, or reference time information. Multiplexer  4614  may further multiplex attribute information associated with sensor information or point cloud data. 
     Multiplexing schemes or file formats include ISOBMFF, MPEG-DASH, which is a transmission scheme based on ISOBMFF, MMT, MPEG-2 TS Systems, or RMP, for example. 
     Demultiplexer  4623  extracts PCC-encoded data, other media, time information and the like from the multiplexed data. 
     Input/output unit  4615  transmits the multiplexed data in a method suitable for the transmission medium or accumulation medium, such as broadcasting or communication. Input/output unit  4615  may communicate with another device over the Internet or communicate with an accumulator, such as a cloud server. 
     As a communication protocol, http, ftp, TCP, UDP or the like is used. The pull communication scheme or the push communication scheme can be used. 
     A wired transmission or a wireless transmission can be used. For the wired transmission, Ethernet (registered trademark), USB, RS-232C, HDMI (registered trademark), or a coaxial cable is used, for example. For the wireless transmission, wireless LAN, Wi-Fi (registered trademark), Bluetooth (registered trademark), or a millimeter wave is used, for example. 
     As a broadcasting scheme, DVB-T2, DVB-S2, DVB-C2, ATSC3.0, or ISDB-S3 is used, for example, 
       FIG.  5    is a diagram showing a configuration of first encoder  4630 , which is an example of encoder  4613  that performs encoding in the first encoding method.  FIG.  6    is a block diagram showing first encoder  4630 . First encoder  4630  generates encoded data (encoded stream) by encoding point cloud data in the first encoding method. First encoder  4630  includes geometry information encoder  4631 , attribute information encoder  4632 , additional information encoder  4633 , and multiplexer  4634 . 
     First encoder  4630  is characterized by performing encoding by keeping a three-dimensional structure in mind. First encoder  4630  is further characterized in that attribute information encoder  4632  performs encoding using information obtained from geometry information encoder  4631 . The first encoding method is referred to also as geometry-based PCC (GPCC). 
     Point cloud data is PCC point cloud data like a PLY file or PCC point cloud data generated from sensor information, and includes geometry information (position), attribute information (attribute), and other additional information (metadata). The geometry information is input to geometry information encoder  4631 , the attribute information is input to attribute information encoder  4632 , and the additional information is input to additional information encoder  4633 . 
     Geometry information encoder  4631  generates encoded geometry information (compressed geometry), which is encoded data, by encoding geometry information. For example, geometry information encoder  4631  encodes geometry information using an N-ary tree structure, such as an octree. Specifically, in the case of an octree, a current space (target space) is divided into eight nodes (subspaces), 8-bit information (occupancy code) that indicates whether each node includes a point cloud or not is generated. A node including a point cloud is further divided into eight nodes, and 8-bit information that indicates whether each of the eight nodes includes a point cloud or not is generated. This process is repeated until a predetermined level is reached or the number of the point clouds included in each node becomes equal to or less than a threshold. 
     Attribute information encoder  4632  generates encoded attribute information (compressed attribute), which is encoded data, by encoding attribute information using configuration information generated by geometry information encoder  4631 . For example, attribute information encoder  4632  determines a reference point (reference node) that is to be referred to in encoding a current point (in other words, a current node or a target node) to be processed based on the octree structure generated by geometry information encoder  4631 . For example, attribute information encoder  4632  refers to a node whose parent node in the octree is the same as the parent node of the current node, of peripheral nodes or neighboring nodes. Note that the method of determining a reference relationship is not limited to this method. 
     The process of encoding attribute information may include at least one of a quantization process, a prediction process, and an arithmetic encoding process. In this case, “refer to” means using a reference node for calculating a predicted value of attribute information or using a state of a reference node (occupancy information that indicates whether a reference node includes a point cloud or not, for example) for determining a parameter of encoding. For example, the parameter of encoding is a quantization parameter in the quantization process or a context or the like in the arithmetic encoding. 
     Additional information encoder  4633  generates encoded additional information (compressed metadata), which is encoded data, by encoding compressible data of additional information. 
     Multiplexer  4634  generates encoded stream (compressed stream), which is encoded data, by multiplexing encoded geometry information, encoded attribute information, encoded additional information, and other additional information. The generated encoded stream is output to a processor in a system layer (not shown). 
     Next, first decoder  4640 , which is an example of decoder  4624  that performs decoding in the first encoding method, will be described.  FIG.  7    is a diagram showing a configuration of first decoder  4640 .  FIG.  8    is a block diagram showing first decoder  4640 . First decoder  4640  generates point cloud data by decoding encoded data (encoded stream) encoded in the first encoding method in the first encoding method, First decoder  4640  includes demultiplexer  4641 , geometry information decoder  4642 , attribute information decoder  4643 , and additional information decoder  4644 . 
     An encoded stream (compressed stream), which is encoded data, is input to first decoder  4640  from a processor in a system layer (not shown). 
     Demultiplexer  4641  separates encoded geometry information (compressed geometry), encoded attribute information (compressed attribute), encoded additional information (compressed metadata), and other additional information from the encoded data. 
     Geometry information decoder  4642  generates geometry information by decoding the encoded geometry information. For example, geometry information decoder  4642  restores the geometry information on a point cloud represented by three-dimensional coordinates from encoded geometry information represented by an N-ary structure, such as an octree. 
     Attribute information decoder  4643  decodes the encoded attribute information based on configuration information generated by geometry information decoder  4642 . For example, attribute information decoder  4643  determines a reference point (reference node) that is to be referred to in decoding a current point (current node) to be processed based on the octree structure generated by geometry information decoder  4642 . For example, attribute information decoder  4643  refers to a node whose parent node in the octree is the same as the parent node of the current node, of peripheral nodes or neighboring nodes. Note that the method of determining a reference relationship is not limited to this method. 
     The process of decoding attribute information may include at least one of an inverse quantization process, a prediction process, and an arithmetic decoding process. In this case, “refer to” means using a reference node for calculating a predicted value of attribute information or using a state of a reference node (occupancy information that indicates whether a reference node includes a point cloud or not, for example) for determining a parameter of decoding. For example, the parameter of decoding is a quantization parameter in the inverse quantization process or a context or the like in the arithmetic decoding. 
     Additional information decoder  4644  generates additional information by decoding the encoded additional information, First decoder  4640  uses additional information required for the decoding process for the geometry information and the attribute information in the decoding, and outputs additional information required for an application to the outside. 
     Next, an example configuration of a geometry information encoder will be described.  FIG.  9    is a block diagram of geometry information encoder  2700  according to this embodiment. Geometry information encoder  2700  includes octree generator  2701 , geometry information calculator  2702 , encoding table selector  2703 , and entropy encoder  2704 . 
     Octree generator  2701  generates an octree, for example, from input position information, and generates an occupancy code of each node of the octree. Geometry information calculator  2702  obtains information that indicates whether a neighboring node of a current node (target node) is an occupied node or not. For example, geometry information calculator  2702  calculates occupancy information on a neighboring node from an occupancy code of a parent node to which a current node belongs (information that indicates whether a neighboring node is an occupied node or not). Geometry information calculator  2702  may save an encoded node in a list and search the list for a neighboring node. Note that geometry information calculator  2702  may change neighboring nodes in accordance with the position of the current node in the parent node. 
     Encoding table selector  2703  selects an encoding table used for entropy encoding of the current node based on the occupancy information on the neighboring node calculated by geometry information calculator  2702 . For example, encoding table selector  2703  may generate a bit sequence based on the occupancy information on the neighboring node and select an encoding table of an index number generated from the bit sequence. 
     Entropy encoder  2704  generates encoded geometry information and metadata by entropy-encoding the occupancy code of the current node using the encoding table of the selected index number. Entropy encoder may add, to the encoded geometry information, information that indicates the selected encoding table. 
     In the following, an octree representation and a scan order for geometry information will be described. Geometry information (geometry data) is transformed into an octree structure (octree transform) and then encoded. The octree structure includes nodes and leaves. Each node has eight nodes or leaves, and each leaf has voxel (VXL) information.  FIG.  10    is a diagram showing an example structure of geometry information including a plurality of voxels.  FIG.  11    is a diagram showing an example in which the geometry information shown in  FIG.  10    is transformed into an octree structure. Here, of leaves shown in  FIG.  11   , leaves  1 ,  2 , and  3  represent voxels VXL 1 , VXL 2 , and VXL 3  shown in  FIG.  10   , respectively, and each represent VXL containing a point cloud (referred to as a valid VXL, hereinafter). 
     Specifically, node  1  corresponds to the entire space comprising the geometry information in  FIG.  10   , The entire space corresponding to node  1  is divided into eight nodes, and among the eight nodes, a node containing valid VXL is further divided into eight nodes or leaves. This process is repeated for every layer of the tree structure. Here, each node corresponds to a subspace, and has information (occupancy code) that indicates where the next node or leaf is located after division as node information. A block in the bottom layer is designated as a leaf and retains the number of the points contained in the leaf as leaf information. 
     Next, an example configuration of a geometry information decoder will be described.  FIG.  12    is a block diagram of geometry information decoder  2710  according to this embodiment. Geometry information decoder  2710  includes octree generator  2711 , geometry information calculator  2712 , encoding table selector  2713 , and entropy decoder  2714 . 
     Octree generator  2711  generates an octree of a space (node) based on header information, metadata or the like of a bitstream. For example, octree generator  2711  generates an octree by generating a large space (root node) based on the sizes of a space in an x-axis direction, a y-axis direction, and a z-axis direction added to the header information and dividing the space into two parts in the x-axis direction, the y-axis direction, and the z-axis direction to generate eight small spaces A (nodes A 0  to A 7 ). Nodes A 0  to A 7  are sequentially designated as a current node. 
     Geometry information calculator  2712  obtains occupancy information that indicates whether a neighboring node of a current node is an occupied node or not. For example, geometry information calculator  2712  calculates occupancy information on a neighboring node from an occupancy code of a parent node to which a current node belongs. Geometry information calculator  2712  may save a decoded node in a list and search the list for a neighboring node. Note that geometry information calculator  2712  may change neighboring nodes in accordance with the position of the current node in the parent node. 
     Encoding table selector  2713  selects an encoding table (decoding table) used for entropy decoding of the current node based on the occupancy information on the neighboring node calculated by geometry information calculator  2712 . For example, encoding table selector  2713  may generate a bit sequence based on the occupancy information on the neighboring node and select an encoding table of an index number generated from the bit sequence. 
     Entropy decoder  2714  generates position information by entropy-decoding the occupancy code of the current node using the selected encoding table, Note that entropy decoder  2714  may obtain information on the selected encoding table by decoding the bitstream, and entropy-decode the occupancy code of the current node using the encoding table indicated by the information. 
     In the following, configurations of an attribute information encoder and an attribute information decoder will be described.  FIG.  13    is a block diagram showing an example configuration of attribute information encoder A 100 . The attribute information encoder may include a plurality of encoders that perform different encoding methods. For example, the attribute information encoder may selectively use any of the two methods described below in accordance with the use case. 
     Attribute information encoder A 100  includes LoD attribute information encoder A 101  and transformed-attribute-information encoder A 102 . LoD attribute information encoder A 101  classifies three-dimensional points into a plurality of layers based on geometry information on the three-dimensional points, predicts attribute information on three-dimensional points belonging to each layer, and encodes a prediction residual therefor. Here, each layer into which a three-dimensional point is classified is referred to as a level of detail (LoD). 
     Transformed-attribute-information encoder A 102  encodes attribute information using region adaptive hierarchical transform (RAHT), Specifically, transformed-attribute-information encoder A 102  generates a high frequency component and a low frequency component for each layer by applying RAHT or Haar transform to each item of attribute information based on the geometry information on three-dimensional points, and encodes the values by quantization, entropy encoding or the like. 
       FIG.  14    is a block diagram showing an example configuration of attribute information decoder A 110 , The attribute information decoder may include a plurality of decoders that perform different decoding methods. For example, the attribute information decoder may selectively use any of the two methods described below for decoding based on the information included in the header or metadata. 
     Attribute information decoder A 110  includes LoD attribute information decoder A 111  and transformed-attribute-information decoder A 112 . LoD attribute information decoder A 111  classifies three-dimensional points into a plurality of layers based on the geometry information on the three-dimensional points, predicts attribute information on three-dimensional points belonging to each layer, and decodes attribute values thereof. 
     Transformed-attribute-information decoder A 112  decodes attribute information using region adaptive hierarchical transform (RAHT). Specifically, transformed-attribute-information decoder A 112  decodes each attribute value by applying inverse RAHT or inverse Haar transform to the high frequency component and the low frequency component of the attribute value based on the geometry information on the three-dimensional point. 
       FIG.  15    is a block diagram showing a configuration of attribute information encoder  3140  that is an example of LoD attribute information encoder A 101 . 
     Attribute information encoder  3140  includes LoD generator  3141 , periphery searcher  3142 , predictor  3143 , prediction residual calculator  3144 , quantizer  3145 , arithmetic encoder  3146 , inverse quantizer  3147 , decoded value generator  3148 , and memory  3149 . 
     LoD generator  3141  generates an LoD using geometry information on a three-dimensional point. 
     Periphery searcher  3142  searches for a neighboring three-dimensional point neighboring each three-dimensional point using a result of LoD generation by LoD generator  3141  and distance information indicating distances between three-dimensional points. 
     Predictor  3143  generates a predicted value of an item of attribute information on a current (target) three-dimensional point to be encoded. 
     Prediction residual calculator  3144  calculates (generates) a prediction residual of the predicted value of the item of the attribute information generated by predictor  3143 . 
     Quantizer  3145  quantizes the prediction residual of the item of attribute information calculated by prediction residual calculator  3144 . 
     Arithmetic encoder  3146  arithmetically encodes the prediction residual quantized by quantizer  3145 . Arithmetic encoder  3146  outputs a bitstream including the arithmetically encoded prediction residual to the three-dimensional data decoding device, for example. 
     The prediction residual may be binarized by quantizer  3145  before being arithmetically encoded by arithmetic encoder  3146 . 
     Arithmetic encoder  3146  may initialize the encoding table used for the arithmetic encoding before performing the arithmetic encoding. Arithmetic encoder  3146  may initialize the encoding table used for the arithmetic encoding for each layer, Arithmetic encoder  3146  may output a bitstream including information that indicates the position of the layer at which the encoding table is initialized. 
     Inverse quantizer  3147  inverse-quantizes the prediction residual quantized by quantizer  3145 . 
     Decoded value generator  3148  generates a decoded value by adding the predicted value of the item of attribute information generated by predictor  3143  and the prediction residual inverse-quantized by inverse quantizer  3147  together. 
     Memory  3149  is a memory that stores a decoded value of an item of attribute information on each three-dimensional point decoded by decoded value generator  3148 . For example, when generating a predicted value of a three-dimensional point yet to be encoded, predictor  3143  may generate the predicted value using a decoded value of an item of attribute information on each three-dimensional point stored in memory  3149 . 
       FIG.  16    is a block diagram of attribute information encoder  6600  that is an example of transformation attribute information encoder A 102 . Attribute information encoder  6600  includes sorter  6601 , Haar transformer  6602 , quantizer  6603 , inverse quantizer  6604 , inverse Haar transformer  6605 , memory  6606 , and arithmetic encoder  6607 . 
     Sorter  6601  generates the Morton codes by using the geometry information of three-dimensional points, and sorts the plurality of three-dimensional points in the order of the Morton codes. Haar transformer  6602  generates the coding coefficient by applying the Haar transform to the attribute information. Quantizer  6603  quantizes the coding coefficient of the attribute information. 
     Inverse quantizer  6604  inverse quantizes the coding coefficient after the quantization. Inverse Haar transformer  6605  applies the inverse Haar transform to the coding coefficient. Memory  6606  stores the values of items of attribute information of a plurality of decoded three-dimensional points. For example, the attribute information of the decoded three-dimensional points stored in memory  6606  may be utilized for prediction and the like of an unencoded three-dimensional point. 
     Arithmetic encoder  6607  calculates ZeroCnt from the coding coefficient after the quantization, and arithmetically encodes ZeroCnt. Additionally, arithmetic encoder  6607  arithmetically encodes the non-zero coding coefficient after the quantization. Arithmetic encoder  6607  may binarize the coding coefficient before the arithmetic encoding. In addition, arithmetic encoder  6607  may generate and encode various kinds of header information. 
       FIG.  17    is a block diagram showing a configuration of attribute information decoder  3150  that is an example of LoD attribute information decoder AM. 
     Attribute information decoder  3150  includes LoD generator  3151 , periphery searcher  3152 , predictor  3153 , arithmetic decoder  3154 , inverse quantizer  3155 , decoded value generator  3156 , and memory  3157 . 
     LoD generator  3151  generates an LoD using geometry information on a three-dimensional point decoded by the geometry information decoder (not shown in  FIG.  17   ). 
     Periphery searcher  3152  searches for a neighboring three-dimensional point neighboring each three-dimensional point using a result of LoD generation by LoD generator  3151  and distance information indicating distances between three-dimensional points. 
     Predictor  3153  generates a predicted value of attribute information item on a current three-dimensional point to be decoded. 
     Arithmetic decoder  3154  arithmetically decodes the prediction residual in the bitstream obtained from attribute information encoder  3140  shown in  FIG.  15   . Note that arithmetic decoder  3154  may initialize the decoding table used for the arithmetic decoding. Arithmetic decoder  3154  initializes the decoding table used for the arithmetic decoding for the layer for which the encoding process has been performed by arithmetic encoder  3146  shown in  FIG.  15   . Arithmetic decoder  3154  may initialize the decoding table used for the arithmetic decoding for each layer. Arithmetic decoder  3154  may initialize the decoding table based on the information included in the bitstream that indicates the position of the layer for which the encoding table has been initialized. 
     Inverse quantizer  3155  inverse-quantizes the prediction residual arithmetically decoded by arithmetic decoder  3154 . 
     Decoded value generator  3156  generates a decoded value by adding the predicted value generated by predictor  3153  and the prediction residual inverse-quantized by inverse quantizer  3155  together. Decoded value generator  3156  outputs the decoded attribute information data to another device. 
     Memory  3157  is a memory that stores a decoded value of an item of attribute information on each three-dimensional point decoded by decoded value generator  3156 . For example, when generating a predicted value of a three-dimensional point yet to be decoded, predictor  3153  generates the predicted value using a decoded value of an item of attribute information on each three-dimensional point stored in memory  3157 . 
       FIG.  18    is a block diagram of attribute information decoder  6610  that is an example of transformation attribute information decoder A 112 . Attribute information decoder  6610  includes arithmetic decoder  6611 , inverse quantizer  6612 , inverse Haar transformer  6613 , and memory  6614 . 
     Arithmetic decoder  6611  arithmetically decodes ZeroCnt and the coding coefficient included in a bitstream. Note that arithmetic decoder  6611  may decode various kinds of header information. 
     Inverse quantizer  6612  inverse quantizes the arithmetically decoded coding coefficient. Inverse Haar transformer  6613  applies the inverse Haar transform to the coding coefficient after the inverse quantization. Memory  6614  stores the values of items of attribute information of a plurality of decoded three-dimensional points. For example, the attribute information of the decoded three-dimensional points stored in memory  6614  may be utilized for prediction of an undecoded three-dimensional point. 
     Next, second encoder  4650 , which is an example of encoder  4613  that performs encoding in the second encoding method, will be described.  FIG.  19    is a diagram showing a configuration of second encoder  4650 .  FIG.  20    is a block diagram showing second encoder  4650 . 
     Second encoder  4650  generates encoded data (encoded stream) by encoding point cloud data in the second encoding method. Second encoder  4650  includes additional information generator  4651 , geometry image generator  4652 , attribute image generator  4653 , video encoder  4654 , additional information encoder  4655 , and multiplexer  4656 . 
     Second encoder  4650  is characterized by generating a geometry image and an attribute image by projecting a three-dimensional structure onto a two-dimensional image, and encoding the generated geometry image and attribute image in an existing video encoding scheme. The second encoding method is referred to as video-based PCC (VPCC). 
     Point cloud data is PCC point cloud data like a PLY file or PCC point cloud data generated from sensor information, and includes geometry information (position), attribute information (attribute), and other additional information (metadata). 
     Additional information generator  4651  generates map information on a plurality of two-dimensional images by projecting a three-dimensional structure onto a two-dimensional image. 
     Geometry image generator  4652  generates a geometry image based on the geometry information and the map information generated by additional information generator  4651 . The geometry image is a distance image in which distance (depth) is indicated as a pixel value, for example. The distance image may be an image of a plurality of point clouds viewed from one point of view (an image of a plurality of point clouds projected onto one two-dimensional plane), a plurality of images of a plurality of point clouds viewed from a plurality of points of view, or a single image integrating the plurality of images. 
     Attribute image generator  4653  generates an attribute image based on the attribute information and the map information generated by additional information generator  4651 . The attribute image is an image in which attribute information (color (RGB), for example) is indicated as a pixel value, for example. The image may be an image of a plurality of point clouds viewed from one point of view (an image of a plurality of point clouds projected onto one two-dimensional plane), a plurality of images of a plurality of point clouds viewed from a plurality of points of view, or a single image integrating the plurality of images. 
     Video encoder  4654  generates an encoded geometry image (compressed geometry image) and an encoded attribute image (compressed attribute image), which are encoded data, by encoding the geometry image and the attribute image in a video encoding scheme. Note that, as the video encoding scheme, any well-known encoding method can be used. For example, the video encoding scheme is AVC or HEVC. 
     Additional information encoder  4655  generates encoded additional information (compressed metadata) by encoding the additional information, the map information and the like included in the point cloud data. 
     Multiplexer  4656  generates an encoded stream (compressed stream), which is encoded data, by multiplexing the encoded geometry image, the encoded attribute image, the encoded additional information, and other additional information. The generated encoded stream is output to a processor in a system layer (not shown). 
     Next, second decoder  4660 , which is an example of decoder  4624  that performs decoding in the second encoding method, will be described.  FIG.  21    is a diagram showing a configuration of second decoder  4660 .  FIG.  22    is a block diagram showing second decoder  4660 . Second decoder  4660  generates point cloud data by decoding encoded data (encoded stream) encoded in the second encoding method in the second encoding method. Second decoder  4660  includes demultiplexer  4661 , video decoder  4662 , additional information decoder  4663 , geometry information generator  4664 , and attribute information generator  4665 . 
     An encoded stream (compressed stream), which is encoded data, is input to second decoder  4660  from a processor in a system layer (not shown). 
     Demultiplexer  4661  separates an encoded geometry image (compressed geometry image), an encoded attribute image (compressed attribute image), an encoded additional information (compressed metadata), and other additional information from the encoded data. 
     Video decoder  4662  generates a geometry image and an attribute image by decoding the encoded geometry image and the encoded attribute image in a video encoding scheme. Note that, as the video encoding scheme, any well-known encoding method can be used. For example, the video encoding scheme is AVC or HEVC. 
     Additional information decoder  4663  generates additional information including map information or the like by decoding the encoded additional information. 
     Geometry information generator  4664  generates geometry information from the geometry image and the map information. Attribute information generator  4665  generates attribute information from the attribute image and the map information. 
     Second decoder  4660  uses additional information required for decoding in the decoding, and outputs additional information required for an application to the outside. 
     In the following, a problem with the PCC encoding scheme will be described.  FIG.  23    is a diagram showing a protocol stack relating to PCC-encoded data.  FIG.  23    shows an example in which PCC-encoded data is multiplexed with other medium data, such as a video (HEVC, for example) or an audio, and transmitted or accumulated. 
     A multiplexing scheme and a file format have a function of multiplexing various encoded data and transmitting or accumulating the data. To transmit or accumulate encoded data, the encoded data has to be converted into a format for the multiplexing scheme. For example, with HEVC, a technique for storing encoded data in a data structure referred to as a NAL unit and storing the NAL unit in ISOBMFF is prescribed. 
     At present, a first encoding method (Coded1) and a second encoding method (Codec2) are under investigation as encoding methods for point cloud data. However, there is no method defined for storing the configuration of encoded data and the encoded data in a system format. Thus, there is a problem that an encoder cannot perform an MUX process (multiplexing), transmission, or accumulation of data. 
     Note that, in the following, the term “encoding method” means any of the first encoding method and the second encoding method unless a particular encoding method is specified. 
     Embodiment 2 
     In this embodiment, types of the encoded data (geometry information (geometry), attribute information (attribute), and addition&amp; information (metadata)) generated by first encoder  4630  or second encoder  4650  described above, a method of generating additional information (metadata), and a multiplexing process in the multiplexer will be described. The additional information (metadata) may be referred to as a parameter set or control information (signaling information). 
     In this embodiment, the dynamic object (three-dimensional point cloud data that varies with time) described above with reference to  FIG.  4    will be described, for example. However, the same method can also be used for the static object (three-dimensional point cloud data associated with an arbitrary time point). 
       FIG.  24    is a diagram showing configurations of encoder  4801  and multiplexer  4802  in a three-dimensional data encoding device according to this embodiment. Encoder  4801  corresponds to first encoder  4630  or second encoder  4650  described above, for example. Multiplexer  4802  corresponds to multiplexer  4634  or  4656  described above. 
     Encoder  4801  encodes a plurality of PCC (point cloud compression) frames of point cloud data to generate a plurality of pieces of encoded data (multiple compressed data) of geometry information, attribute information, and additional information. 
     Multiplexer  4802  integrates a plurality of types of data (geometry information, attribute information, and additional information) into a NAL unit, thereby converting the data into a data configuration that takes data access in the decoding device into consideration. 
       FIG.  25    is a diagram showing a configuration example of the encoded data generated by encoder  4801 , Arrows in the drawing indicate a dependence involved in decoding of the encoded data. The source of an arrow depends on data of the destination of the arrow. That is, the decoding device decodes the data of the destination of an arrow, and decodes the data of the source of the arrow using the decoded data. In other words, “a first entity depends on a second entity” means that data of the second entity is referred to (used) in processing (encoding, decoding, or the like) of data of the first entity. 
     First, a process of generating encoded data of geometry information will be described, Encoder  4801  encodes geometry information of each frame to generate encoded geometry data (compressed geometry data) for each frame. The encoded geometry data is denoted by G(i). i denotes a frame number or a time point of a frame, for example. 
     Furthermore, encoder  4801  generates a geometry parameter set (GPS(i)) for each frame. The geometry parameter set includes a parameter that can be used for decoding of the encoded geometry data. The encoded geometry data for each frame depends on an associated geometry parameter set. 
     The encoded geometry data formed by a plurality of frames is defined as a geometry sequence. Encoder  4801  generates a geometry sequence parameter set (referred to also as geometry sequence PS or geometry SPS) that stores a parameter commonly used for a decoding process for the plurality of frames in the geometry sequence. The geometry sequence depends on the geometry SPS. 
     Next, a process of generating encoded data of attribute information will be described, Encoder  4801  encodes attribute information of each frame to generate encoded attribute data (compressed attribute data) for each frame. The encoded attribute data is denoted by A(i).  FIG.  25    shows an example in which there are attribute X and attribute Y, and encoded attribute data for attribute X is denoted by AX(i), and encoded attribute data for attribute Y is denoted by AY(i). 
     Furthermore, encoder  4801  generates an attribute parameter set (APS(i)) for each frame. The attribute parameter set for attribute X is denoted by AXPS(i), and the attribute parameter set for attribute Y is denoted by AYPS(i), The attribute parameter set includes a parameter that can be used for decoding of the encoded attribute information. The encoded attribute data depends on an associated attribute parameter set. 
     The encoded attribute data formed by a plurality of frames is defined as an attribute sequence. Encoder  4801  generates an attribute sequence parameter set (referred to also as attribute sequence PS or attribute SPS) that stores a parameter commonly used for a decoding process for the plurality of frames in the attribute sequence. The attribute sequence depends on the attribute SPS. 
     In the first encoding method, the encoded attribute data depends on the encoded geometry data. 
       FIG.  25    shows an example in which there are two types of attribute information (attribute X and attribute Y). When there are two types of attribute information, for example, two encoders generate data and metadata for the two types of attribute information. 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. 
     Note that, although  FIG.  25    shows an example in which there is one type of geometry information, and there are two types of attribute information, the present disclosure is not limited thereto. There may be one type of attribute information or three or more types of attribute information. In such cases, encoded data can be generated in the same manner. If the point cloud data has no attribute information, there may be no attribute information. In such a case, encoder  4801  does not have to generate a parameter set associated with attribute information. 
     Next, a process of generating encoded data of additional information (metadata) will be described. Encoder  4801  generates a PCC stream PS (referred to also as PCC stream PS or stream PS), which is a parameter set for the entire PCC stream. Encoder  4801  stores a parameter that can be commonly used for a decoding process for one or more geometry sequences and one or more attribute sequences in the stream PS. For example, the stream PS includes identification information indicating the codec for the point cloud data and information indicating an algorithm used for the encoding, for example. The geometry sequence and the attribute sequence depend on the stream PS. 
     Next, an access unit and a GOF will be described. In this embodiment, concepts of access unit (AU) and group of frames (GOF) are newly introduced. 
     An access unit is a basic unit for accessing data in decoding, and is formed by one or more pieces of data and one or more pieces of metadata. For example, an access unit is formed by geometry information and one or more pieces of attribute information associated with a same time point. A GOF is a random access unit, and is formed by one or more access units. 
     Encoder  4801  generates an access unit header (AU header) as identification information indicating the top of an access unit. Encoder  4801  stores a parameter relating to the access unit in the access unit header. For example, the access unit header includes a configuration of or information on the encoded data included in the access unit. The access unit header further includes a parameter commonly used for the data included in the access unit, such as a parameter relating to decoding of the encoded data. 
     Note that encoder  4801  may generate an access unit delimiter that includes no parameter relating to the access unit, instead of the access unit header. The access unit delimiter is used as identification information indicating the top of the access unit. The decoding device identifies the top of the access unit by detecting the access unit header or the access unit delimiter. 
     Next, generation of identification information for the top of a GOF will be described. As identification information indicating the top of a GOF, encoder  4801  generates a GOF header. Encoder  4801  stores a parameter relating to the GOF in the GOF header. For example, the GOF header includes a configuration of or information on the encoded data included in the GOF. The GOF header further includes a parameter commonly used for the data included in the GOF, such as a parameter relating to decoding of the encoded data. 
     Note that encoder  4801  may generate a GOF delimiter that includes no parameter relating to the GOF, instead of the GOF header. The GOF delimiter is used as identification information indicating the top of the GOF. The decoding device identifies the top of the GOF by detecting the GOF header or the GOF delimiter. 
     In the PCC-encoded data, the access unit is defined as a PCC frame unit, for example. The decoding device accesses a PCC frame based on the identification information for the top of the access unit. 
     For example, the GOF is defined as one random access unit. The decoding device accesses a random access unit based on the identification information for the top of the GOF. For example, if PCC frames are independent from each other and can be separately decoded, a PCC frame can be defined as a random access unit. 
     Note that two or more PCC frames may be assigned to one access unit, and a plurality of random access units may be assigned to one GOF. 
     Encoder  4801  may define and generate a parameter set or metadata other than those described above. For example, encoder  4801  may generate supplemental enhancement information (SEI) that stores a parameter (an optional parameter) that is not always used for decoding. 
     Next, a configuration of encoded data and a method of storing encoded data in a NAL unit will be described. 
     For example, a data format is defined for each type of encoded data,  FIG.  26    is a diagram showing an example of encoded data and a NAL unit. 
     For example, as shown in  FIG.  26   , encoded data includes a header and a payload. The encoded data may include length information indicating the length (data amount) of the encoded data, the header, or the payload. The encoded data may include no header. 
     The header includes identification information for identifying the data, for example. The identification information indicates a data type or a frame number, for example. 
     The header includes identification information indicating a reference relationship, for example. The identification information is stored in the header when there is a dependence relationship between data, for example, and allows an entity to refer to another entity. For example, the header of the entity to be referred to includes identification information for identifying the data. The header of the referring entity includes identification information indicating the entity to be referred to. 
     Note that, when the entity to be referred to or the referring entity can be identified or determined from other information, the identification information for identifying the data or identification information indicating the reference relationship can be omitted. 
     Multiplexer  4802  stores the encoded data in the payload of the NAL unit. The NAL unit header includes pcc_nal_unit_type, which is identification information for the encoded data.  FIG.  27    is a diagram showing a semantics example of pcc_nal_unit_type. 
     As shown in  FIG.  27   , when pcc_codec_type is codec 1 (Codec1: first encoding method), values 0 to 10 of pcc_nal_unit_type are assigned to encoded geometry data (Geometry), encoded attribute X data (AttributeX), encoded attribute Y data (AttributeY), geometry PS (Geom. PS), attribute XPS (AttrX, S), attribute YPS (AttrY. PS), geometry SPS (Geometry Sequence PS), attribute X SPS (AttributeX Sequence PS), attribute V SPS (AttributeY Sequence PS), AU header (AU Header), and GOF header (GOF Header) in codec 1. Values of 11 and greater are reserved in codec 1. 
     When pcc_codec_type is codec 2 (Codec2: second encoding method), values of 0 to 2 of pcc_nal_unit_type are assigned to data A (DataA), metadata A (MetaDataA), and metadata B (MetaDataB) in the coder. Values of 3 and greater are reserved in codec 2. 
     Next, an order of transmission of data will be described. In the following, restrictions on the order of transmission of NAL units will be described. 
     Multiplexer  4802  transmits NAL units on a GOF basis or on an AU basis. Multiplexer  4802  arranges the GOF header at the top of a GOF, and arranges the AU header at the top of an AU. 
     In order to allow the decoding device to decode the next AU and the following AUs even when data is lost because of a packet loss or the like, multiplexer  4802  may arrange a sequence parameter set (SPS) in each AU. 
     When there is a dependence relationship for decoding between encoded data, the decoding device decodes the data of the entity to be referred to and then decodes the data of the referring entity. In order to allow the decoding device to perform decoding in the order of reception without rearranging the data, multiplexer  4802  first transmits the data of the entity to be referred to. 
       FIG.  28    is a diagram showing examples of the order of transmission of NAL units.  FIG.  28    shows three examples, that is, geometry information-first order, parameter-first order, and data-integrated order. 
     The geometry information-first order of transmission is an example in which information relating to geometry information is transmitted together, and information relating to attribute information is transmitted together. In the case of this order of transmission, the transmission of the information relating to the geometry information ends earlier than the transmission of the information relating to the attribute information. 
     For example, according to this order of transmission is used, when the decoding device does not decode attribute information, the decoding device may be able to have an idle time since the decoding device can omit decoding of attribute information. When the decoding device is required to decode geometry information early, the decoding device may be able to decode geometry information earlier since the decoding device obtains encoded data of the geometry information earlier. 
     Note that, although in  FIG.  28    the attribute X SPS and the attribute Y SPS are integrated and shown as the attribute SPS, the attribute X SPS and the attribute Y SPS may be separately arranged. 
     In the parameter set-first order of transmission, a parameter set is first transmitted, and data is then transmitted. 
     As described above, as far as the restrictions on the order of transmission of NAL units are met, multiplexer  4802  can transmit NAL units in any order. For example, order identification information may be defined, and multiplexer  4802  may have a function of transmitting NAL units in a plurality of orders. For example, the order identification information for NAL units is stored in the stream PS. 
     The three-dimensional data decoding device may perform decoding based on the order identification information. The three-dimensional data decoding device may indicate a desired order of transmission to the three-dimensional data encoding device, and the three-dimensional data encoding device (multiplexer  4802 ) may control the order of transmission according to the indicated order of transmission. 
     Note that multiplexer  4802  can generate encoded data having a plurality of functions merged to each other as in the case of the data-integrated order of transmission, as far as the restrictions on the order of transmission are met. For example, as shown in  FIG.  28   , the GOF header and the AU header may be integrated, or AXPS and AYPS may be integrated. In such a case, an identifier that indicates data having a plurality of functions is defined in pcc_nal_unit_type. 
     In the following, variations of this embodiment will be described. There are levels of PSs, such as a frame-level PS, a sequence-level PS, and a PCC sequence-level PS. Provided that the PCC sequence level is a higher level, and the frame level is a lower level, parameters can be stored in the manner described below. 
     The value of a default PS is indicated in a PS at a higher level. If the value of a PS at a lower level differs from the value of the PS at a higher level, the value of the PS is indicated in the PS at the lower level. Alternatively, the value of the PS is not described in the PS at the higher level but is described in the PS at the lower level. Alternatively, information indicating whether the value of the PS is indicated in the PS at the lower level, at the higher level, or at both the levels is indicated in both or one of the PS at the lower level and the PS at the higher level. Alternatively, the PS at the lower level may be merged with the PS at the higher level. If the PS at the lower level and the PS at the higher level overlap with each other, multiplexer  4802  may omit transmission of one of the PSs. 
     Note that encoder  4801  or multiplexer  4802  may divide data into slices or toes and transmit each of the divided slices or toes as divided data. The divided data includes information for identifying the divided data, and a parameter used for decoding of the divided data is included in the parameter set. In this case, an identifier that indicates that the data is data relating to a the or slice or data storing a parameter is defined in pcc_nal_unit_type. 
     Embodiment 3 
     A tree structure formed by combining an octree (octree structure), a quadtree (quadtree structure), and a binary tree (binary tree structure) will now be described. Specifically, hereunder an example is described in which the three-dimensional data encoding device and the three-dimensional data decoding device performing encoding and decoding, respectively, by combining tree structures having a plurality of dimensions (number of divisions), such as a quadtree or a binary tree in addition to an octree, 
       FIG.  29    is a diagram illustrating an example of position data according to the present embodiment.  FIG.  30    is a diagram illustrating an example of a tree structure according to the present embodiment. 
     Position data is transformed into a tree structure that is an octree, a quadtree, or a binary tree, and then encoded. Each tree structure includes nodes and leaves (leaf node). Each node has eight, four, or two blocks (nodes or leaves). That is, each node is divided (partitioned) into eight, four, or two nodes. Each leaf has voxel (VXL) information. For example, the position data illustrated in  FIG.  29    is transformed into a tree structure illustrated in  FIG.  30   . 
     Here, of the leaves shown in  FIG.  30   , leaf  1  represents VXL 1  shown in  FIG.  29    (the hatched region in  FIG.  29   ), and represents VXL containing a three-dimensional point cloud (referred to as a valid VXL, hereinafter). Specifically, node  1  corresponds to the entire space comprising the position data in  FIG.  29   . 
     The entire space corresponding to node  1  is divided into two nodes. In this case, the occupancy code of node  1  is represented by two bits such as “10”, for example. Further, the space corresponding to node  2  is divided into four nodes. In this case, the occupancy code of node  1  is represented by four bits such as “1000”, for example. Further, the space corresponding to node  3  is divided into eight nodes. In this case, the occupancy code of node  1  is represented by eight bits such as “10000000”, for example. 
     In this way, a process in which a node containing valid VXL (VXL containing three-dimensional points) is divided into eight, four, or two nodes or leaves is repeated for every layer (depth) of the tree structure. 
     Here, each node corresponds to a subspace, and has an occupancy code that is information that indicates where the next node or leaf is located after division as node information. A block in the bottom layer is designated as a leaf, and has the number of the points contained in the leaf as leaf information. 
     By representing a tree structure which combines tree structures of a plurality of dimensions using three-dimensional data (more specifically, position data), the three-dimensional data encoding device, for example, can replace an 8-bit occupancy code that is division information of an octree (more specifically, information of a node in a case where the number of divisions of that node is an octree) with a 4-bit occupancy code that shows division information of a quadtree or a 2-bit occupancy code that shows division information of a binary tree. Therefore, it is possible to reduce the number of coding bits, and the coding rate is improved. 
     Next, examples of tree structures represented by an octree, a quadtree, or a binary tree are described. 
       FIG.  31    to  FIG.  37    are each a diagram illustrating the relationship between the number of divisions of a tree structure and tree_axis_flag according to the present embodiment. 
     In order to indicate whether each node is divided into an octree, a quadtree, or a binary tree, respectively, and the direction in which the space is divided, the three-dimensional data encoding device shows a flag (tree_coded_axis_flag) indicating which division method (tree structure) was used for each layer (depth) of the node. Specifically, the three-dimensional data encoding device generates tree_coded_axis_flag that indicates, for each depth of the nodes, (i) whether each node was divided into eight nodes, four nodes, or two nodes, and (ii) how the node was divided for each division, more specifically, how the space corresponding to the node was divided. 
     For example, when it is defined that tree_coded_axis_flag[depth][A]=B, “depth” indicates the depth of the node that is the object of the flag. For example, depth=0 indicates that the depth of the node that is the object of the flag is 0. Further, A indicates the direction in which the space corresponding to the node is divided. For example, A=0 indicates that the direction in which the space is divided is the direction orthogonal to the x-axis. For example, A=1 indicates that the direction in which the space is divided is the direction orthogonal to the y-axis. For example, A=2 indicates that the direction in which the space is divided is the direction orthogonal to the z-axis. Further, B indicates whether or not the space is divided. For example, B=0 indicates that the space is not divided. Further, for example, B=1 indicates that the space is divided. For example, tree_coded_axis_flag[0][0]=0 indicates that the space corresponding to the node having a depth of 0 is not divided in the direction orthogonal to the x-axis. 
     The three-dimensional data encoding device represents the presence or absence of a three-dimensional point in the node (that is, the space corresponding to the node) by, for example, a combination of tree_coded_axis_flag and the occupancy code corresponding to the division method (tree structure). 
     The three-dimensional data encoding device, for example, transmits tree_coded_axis_flag to the three-dimensional data decoding device. The three-dimensional data encoding device, for example, generates a bitstream including tree_coded_axis_flag, and transmits the generated bitstream to the three-dimensional data decoding device. 
     Accordingly, it is possible for the three-dimensional data encoding device to flexibly determine the division method. For example, even if the three-dimensional data encoding device arbitrarily decided the tree structure, by notifying tree_coded_axis_flag to the three-dimensional data decoding device, it is possible for the three-dimensional data decoding device to determine the number of divisions in the tree structure that the three-dimensional data encoding device used to represent the position data, and the number of bits in the occupancy code. 
     As shown in  FIG.  31   , for example, in the case of dividing a node into eight nodes, that is, dividing the space into eight parts, the three-dimensional data encoding device generates tree_coded_axis_flag[depth][0]=1, tree_coded_axis_flag[depth][1]=1, and tree_coded_axis_flag[depth][2]=1. 
     Note that, as described above, the three-dimensional data encoding device may transform position data into not only an octree as illustrated in  FIG.  31   , but also into a quadtree or a binary tree, that is, may represent the position data as a quadtree or a binary tree. 
     In the case of a quadtree, for example, three patterns exist, namely, a pattern in which the space is divided with respect to the x-axis and the y-axis as shown in  FIG.  32   , a pattern in which the space is divided with respect to the x-axis and the z-axis as shown in  FIG.  33   , and a pattern in which the space is divided with respect to the y-axis and the z-axis as shown in  FIG.  34   . 
     For example, in a case of dividing a node into four nodes by dividing the space in a direction orthogonal to the x-axis and a direction orthogonal to the y-axis as shown in  FIG.  32   , the three-dimensional data encoding device generates tree_coded_axis_flag[depth][0]=1, tree_coded_axis_flag[depth][1]=1, and tree_coded_axis_flag[depth][2]=0. 
     Further, for example, in a case of dividing a node into four nodes by dividing the space in a direction orthogonal to the x-axis and a direction orthogonal to the z-axis as shown in  FIG.  33   , the three-dimensional data encoding device generates tree_coded_axis_flag[depth][0]=1, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=1. 
     Further, for example, in a case of dividing a node into four nodes by dividing the space in a direction orthogonal to the y-axis and a direction orthogonal to the z-axis as shown in  FIG.  34   , the three-dimensional data encoding device generates tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=1, and tree_coded_axis_flag[depth][2]=1. 
     In the case of a binary tree, for example, three patterns exist, namely, a pattern in which the space is divided with respect to the x-axis as shown in  FIG.  35   , a pattern in which the space is divided with respect to the y-axis as shown in  FIG.  36   , and a pattern in which the space is divided with respect to the z-axis as shown in  FIG.  37   . 
     For example, in a case of dividing a node into two nodes by dividing the space in a direction orthogonal to the x-axis as shown in  FIG.  35   , the three-dimensional data encoding device generates tree_coded_axis_flag[depth][0]=1, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0. 
     Further, for example, in a case of dividing a node into two nodes by dividing the space in a direction orthogonal to the y-axis as shown in  FIG.  36   , the three-dimensional data encoding device generates tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=1, and tree_coded_axis_flag[depth][2]=0. 
     Further, for example, in a case of dividing a node into two nodes by dividing the space in a direction orthogonal to the z-axis as shown in  FIG.  37   , the three-dimensional data encoding device generates tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=1. 
     Note that the initial structure (root node) of a voxel (VXL) may be not only a cube that has the same size in each of the x-axis, y-axis, and z-axis directions, but may also be a rectangular parallelepiped structure whose sizes in the x-axis, y-axis, and z-axis directions are different to each other. 
     Further, the three-dimensional data encoding device may encode according to a predetermined division rule. Similarly, the three-dimensional data decoding device may decode according to a predetermined division rule. 
     Accordingly, since the three-dimensional data decoding device can decode appropriately according to a predetermined division rule even if the three-dimensional data encoding device does not transmit tree_coded_axis_flag to the three-dimensional data decoding device, it is possible to reduce the number of bits (for example, the number of bits in a bitstream including tree_coded_axis_flag). 
     Next, configuration examples of the three-dimensional data decoding device and the three-dimensional data decoding device will be described. 
       FIG.  38    is a block diagram of the three-dimensional data encoding device according to the present embodiment. Specifically,  FIG.  38    is a block diagram illustrating the configuration of a geometry information encoder that encodes geometry information (position information), which the three-dimensional data encoding device according to the present embodiment includes. 
     The three-dimensional data encoding device uses a predetermined method to determine a tree structure to be used to divide a three-dimensional point cloud. For example, the three-dimensional data encoding device determines the tree structure based on the shape and uneven distribution of points of the three-dimensional point cloud. The geometry information encoder included in the three-dimensional data encoding device includes tree structure generator  12401 , geometry information calculator  12402 , encoding table selector  12403 , and entropy encoder  12404 . 
     Tree structure generator  12401  generates a binary tree, a quadtree, or an octree, or a tree structure that combines these tree structures, from input position data, and generates an occupancy code of each node of the generated tree structure. Further, tree structure generator  12401 , for example, generates tree_coded_axis_flag. 
     Geometry information calculator  12402  obtains information that indicates whether a neighboring node of a node to be encoded (current node) is an occupied node or not. For example, geometry information calculator  12402  obtains occupancy information on a neighboring node (information that indicates whether a neighboring node is an occupied node or not) from an occupancy code of a parent node to which the current node belongs. 
     Note that, geometry information calculator  12402  may save an encoded node in a list and search the list for a neighboring node. Further, geometry information calculator  12402  may change neighboring nodes in accordance with the position of the current node in the parent node. 
     Encoding table selector  12403  selects a coding table used for entropy encoding of the current node based on the occupancy information on the neighboring node calculated by geometry information calculator  12402 , For example, encoding table selector  12403  generates a bit sequence based on the occupancy information on the neighboring node, and selects a coding table of an index number generated from the bit sequence. 
     Entropy encoder  12404  generates encoded geometry information and metadata by entropy-encoding the occupancy code of the current node using the coding table of the selected index number. Entropy encoder  12404  may add, to the encoded geometry information, information that indicates the selected coding table. 
       FIG.  39    is a block diagram of the three-dimensional data decoding device according to the present embodiment. Specifically,  FIG.  39    is a block diagram illustrating the configuration of a geometry information decoder that decodes geometry information, which the three-dimensional data decoding device according to the present embodiment includes. 
     The three-dimensional data decoding device decodes encoded data by generating the same tree structure as the tree structure which the three-dimensional data encoding device used for encoding. Examples of available methods by which the three-dimensional data encoding device and the three-dimensional data decoding device can encode and decode data using the same tree structure include a method in which the three-dimensional data encoding device and the three-dimensional data decoding device each determine a tree structure based on a predetermined rule, and a method in which a tree structure determined by the three-dimensional data encoding device is notified to the three-dimensional data decoding device. The geometry information decoder included in the three-dimensional data decoding device includes tree structure generator  12411 , geometry information calculator  12412 , encoding table selector  12413 , and entropy decoder  12414 . 
     Tree structure generator  12411  generates a binary tree, a quadtree, an octree, or a tree structure that combines these tree structures of a space (node) based on the header information, metadata and the like of a bitstream. For example, tree structure generator  12411  generates a binary tree, a quadtree, or an octree by generating a large space (root node) based on the sizes of a space in an x-axis direction, a y-axis direction, and a z-axis direction added to the header information and dividing the space into two parts in the x-axis direction, the y-axis direction, and the z-axis direction, or not dividing the space with respect to one or more of the axial directions, to thereby generate two, four, or eight small spaces. Further, nodes are sequentially designated as a current node. 
     Note that tree structure generator  12411  may divide a node into a predetermined tree structure, or may generate a tree structure according to tree_coded_axis_flag transmitted from the three-dimensional data encoding device. 
     Geometry information calculator  12412  obtains occupancy information that indicates whether a neighboring node of a node to be decoded (current node) is an occupied node or not. For example, geometry information calculator  12412  obtains occupancy information on a neighboring node from an occupancy code of a parent node to which the current node belongs. 
     Note that geometry information calculator  12412  may save a decoded node in a list and search the list for a neighboring node. Further, geometry information calculator  12412  may change neighboring nodes in accordance with the position of the current node in the parent node. 
     Encoding table selector  12413  selects a decoding table (coding table) used for entropy decoding of the current node based on the occupancy information on the neighboring node calculated by geometry information calculator  12412 . For example, encoding table selector  12413  generates a bit sequence based on the occupancy information on the neighboring node, and selects a coding table of an index number generated from the bit sequence. 
     Entropy decoder  12414  generates geometry information (position data) by entropy-decoding the occupancy code of the current node using the selected coding table. 
     Note that entropy decoder  12414  may obtain information on the selected coding table by decoding the bitstream, and entropy-decode the occupancy code of the current node using the coding table indicated by the information. 
     Next, a procedure in which the three-dimensional data encoding device indicates a tree structure by using a flag will be described. 
       FIG.  40    is a flowchart showing a procedure for generating a flag indicating a tree structure that is performed by the three-dimensional data encoding device according to the present embodiment. 
     First, the three-dimensional data encoding device generates a root node (S 12401 ). A root node is a node corresponding to a bounding box (space) including a three-dimensional point cloud. 
     Next, the three-dimensional data encoding device determines whether or not a leaf node is reached (S 12402 ). For example, the three-dimensional data encoding device selects one block and determines whether or not the selected block is a leaf node. 
     If the three-dimensional data encoding device determines that a leaf node has not been reached, that is, that the selected block is not a leaf node (No in S 12402 ), the three-dimensional data encoding device determines whether or not to generate a binary tree, that is, whether to divide the selected block (node) into two blocks (S 12403 ). 
     If the three-dimensional data encoding device determines that a binary tree is to be generated (Yes in S 12403 ), the three-dimensional data encoding device generates a binary tree of the selected node (that is, divides the node into two nodes) and generates tree_coded_axis_flag indicating the tree structure is a binary tree (S 12404 ), and then returns the process to step S 12402 . 
     On the other hand, if the three-dimensional data encoding device determines that a binary tree is not to be generated (No in S 12403 ), the three-dimensional data encoding device determines whether or not to generate a quadtree, that is, whether to divide the selected node into four nodes (S 12405 ). 
     If the three-dimensional data encoding device determines that a quadtree is to be generated (Yes in S 12405 ), the three-dimensional data encoding device generates a quadtree of the selected node (that is, divides the node into four nodes) and generates tree_coded_axis_flag indicating the tree structure is a quadtree (S 12406 ), and then returns the process to step S 12402 . 
     On the other hand, if the three-dimensional data encoding device determines that a quadtree is not to be generated (No in S 12405 ), the three-dimensional data encoding device generates an octree of the selected node (that is, divides the node into eight nodes) and generates tree_coded_axis_flag indicating the tree structure is an octree (S 12407 ), and then returns the process to step S 12402 . 
     After executing step S 12404 , step S 12406 , or step S 12407  and returning the process to step S 12402 , the three-dimensional data encoding device selects a different block and determines whether or not the selected block is a leaf node. 
     If the three-dimensional data encoding device determines that a leaf node is reached (Yes in S 12402 ), the three-dimensional data encoding device determines whether or not processing of all the blocks is completed (S 12408 ). Specifically, the three-dimensional data encoding device determines whether or not the determination in step S 12402  was performed for all the blocks, and the process from step S 12403  onward was performed when the result of the determination in step S 12402  was “No”. 
     If the three-dimensional data encoding device determines that processing of all blocks is completed (Yes in S 12408 ), the three-dimensional data encoding device ends the process. 
     On the other hand, if the three-dimensional data encoding device determines that processing of all blocks is not completed (No in S 12408 ), the three-dimensional data encoding device returns the process to step S 12402 , selects a block that was not selected, and repeats the process from step S 12402  onward. 
     As described above, the three-dimensional data encoding device generates tree_coded_axis_flag, and signals (that is, notifies) the tree structure to the three-dimensional data decoding device using that flag. Accordingly, even if the three-dimensional data encoding device freely creates a tree structure, it is possible for the three-dimensional data decoding device to appropriately determine the tree structure when performing the decoding process, and hence the compression performance can be improved. 
     Note that it suffices to arbitrarily specify in advance the method for determining which type of tree structure to generate in step S 12403  and step S 12405 , and the method is not particularly limited. 
     Next, a procedure in which the three-dimensional data decoding device determines a tree structure using a flag will be described. 
       FIG.  41    is a flowchart showing a procedure for determining a tree structure that is performed by the three-dimensional data decoding device according to the present embodiment. 
     First, the three-dimensional data decoding device obtains a bitstream including encoded geometry information, metadata, and tree_coded_axis_flag, and generates a root node with respect to the encoded geometry information (S 12411 ). 
     Next, the three-dimensional data decoding device determines whether or not a leaf node is reached (S 12412 ). For example, the three-dimensional data decoding device selects one block and determines whether or not the selected block is a leaf node. 
     If the three-dimensional data decoding device determines that a leaf node has not been reached, that is, that the selected block is not a leaf node (No in S 12412 ), the three-dimensional data decoding device refers to tree_coded_axis_flag corresponding to the block (S 12413 ). 
     Next, based on tree_coded_axis_flag, the three-dimensional data decoding device determines whether or not to generate a binary tree, that is, whether or not to divide the selected block (node) in into two blocks (S 12414 ). 
     If the three-dimensional data decoding device determines that a binary tree is to be generated (Yes in S 12414 ), the three-dimensional data decoding device generates a binary tree of the selected node (S 12415 ), and then returns the process to step S 12412 . 
     On the other hand, if the three-dimensional data decoding device determines that a binary tree is not to be generated (No in S 12414 ), the three-dimensional data decoding device determines whether or not to generate a quadtree, that is, whether or not to divide the selected node into four nodes (S 12416 ). 
     If the three-dimensional data decoding device determines that a quadtree is to be generated (Yes in S 12416 ), the three-dimensional data decoding device generates a quadtree of the selected node (S 12417 ), and then returns the process to step S 12412 . 
     On the other hand, if the three-dimensional data decoding device determines that a quadtree is not to be generated (No in S 12416 ), the three-dimensional data decoding device generates an octree of the selected node (S 12418 ), and then returns the process to step S 12412 . 
     After executing step S 12415 , step S 12417 , or step S 12418  and returning the process to step S 12412 , the three-dimensional data decoding device selects a different block and determines whether or not the selected block is a leaf node. 
     If the three-dimensional data decoding device determines that a leaf node is reached (Yes in S 12412 ), the three-dimensional data decoding device determines whether or not processing of all the blocks is completed (S 12419 ). Specifically, the three-dimensional data decoding device performs the determination in step S 12412  for all the blocks, and determines whether or not the process from step S 12413  onward was performed when the result of the determination in step S 12412  was “No”. 
     If the three-dimensional data decoding device determines that processing of all blocks is completed (Yes in S 12419 ), the three-dimensional data decoding device ends the process. 
     On the other hand, if the three-dimensional data decoding device determines that processing of all blocks is not completed (No in S 12419 ), the three-dimensional data decoding device returns the process to step S 12412 , selects a block that was not selected, and repeats the process from step S 12412  onward. 
     As described above, the three-dimensional data decoding device, for example, forms a tree structure according to a flag (tree_coded_axis_flag) transmitted from the three-dimensional data encoding device. 
     Accordingly, it is possible for the three-dimensional data decoding device to form tree structures that are the same as various tree structures that the three-dimensional data encoding device created, and hence the compression performance can be improved. 
     Next, specific examples of a procedure for reducing the processing amount of the syntax of information indicating a tree structure will be described. 
     In a method for generating a tree structure in which a plurality of kinds of N-ary tree structures are combined as described above, an improvement in the coding efficiency at the three-dimensional data encoding device can be expected by changing the tree structure according to an uneven distribution of the positions of points of a three-dimensional point cloud. For example, when generating a tree structure, in the case of a shallow depth (that is, in a case where the depth is small), there is a high possibility that the coding efficiency will be improved by using a tree structure other than an octree (specifically, a binary tree or a quadtree), On the other hand, when generating a tree structure, in the case of a deep depth (that is, in a case where the depth is large), there is a high possibility that the coding efficiency will be improved by using an octree. 
     Thus, in order to improve the coding efficiency, when a plurality of kinds of tree structures are used for the first half of the depth (that is, a case where the depth is small) and an octree is used for the latter half of the depth (that is, a case where the depth is large), it is possible to reduce the number of bits of the syntax for signaling flags by omitting flags indicating an octree in the latter half by using the following method. 
       FIG.  42    is a flowchart illustrating a first example of a procedure for generating a flag indicating a tree structure performed by the three-dimensional data encoding device according to the present embodiment. 
     First, the three-dimensional data encoding device starts construction of a tree structure that combines a plurality (plurality of kinds) of tree structures (S 12421 ). 
     Next, the three-dimensional data encoding device generates a tree structure using a predetermined method (S 12422 ). For example, the three-dimensional data encoding device generates a tree structure by executing the process shown in  FIG.  40   , excluding the processing for generating a flag in step S 12404 , step S 12406 , and step S 12407 . 
     Next, for each depth of the tree structure, the three-dimensional data encoding device starts a process for generating a flag indicating how many nodes each node was divided into. For example, the three-dimensional data encoding device generates tree_coded_axis_flag in order from the shallowest depth in the tree structure (more specifically, depth=0). 
     The three-dimensional data encoding device determines whether or not the tree structures from the target depth (in the present example, the depth corresponding to tree_coded_axis_flag that the three-dimensional data encoding device generates) and beyond are all octrees, that is, whether or not the number of divisions of nodes located at depths from the target depth and beyond are all 8 (S 12423 ). 
     If the three-dimensional data encoding device determines that all the tree structures are octrees (Yes in S 12423 ), the three-dimensional data encoding device generates tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag [depth][1]=0, and tree_coded_axis_flag[depth][2]=0 (that is, generates tree_coded_axis_flag[depth][0/1/2]=0) (S 12424 ), and does not generate tree_coded_axis_flag indicating a tree structure at the next depth and beyond after the target depth (S 12425 ). Note that, a value indicating the target depth is set for “depth” here. For example, it is predetermined that when it is indicated that division is not performed with respect to each of the x-axis direction, the y-axis direction, and the z-axis direction by tree_coded_axis_flag, the number of divisions is eight for all nodes located at depths from the target depth and beyond. Accordingly, in a case where the same number of divisions (for example, eight divisions) continues even when the depths change, by using a flag indicating the number of divisions for each depth, the three-dimensional data encoding device can indicate the tree structures using a small number of flags (that is, number of bits). 
     On the other hand, if the three-dimensional data encoding device determines that all the tree structures are not octrees, that is, that a binary tree or a quadtree is also included (No in S 12423 ), the three-dimensional data encoding device generates tree_coded_axis_flag indicating the tree structure at the target depth (S 12426 ), and furthermore, with respect to the tree structures at the next depth and beyond after the target depth, generates tree_coded_axis_flag for each depth (S 12427 ). 
       FIG.  43    is a flowchart illustrating a first example of a procedure for determining a tree structure performed by the three-dimensional data decoding device according to the present embodiment. 
     First, for example, the three-dimensional data decoding device obtains a bitstream from the three-dimensional data encoding device, and analyzes tree_coded_axis_flag included in the obtained bitstream (S 12431 ). The three-dimensional data decoding device determines (decides) the tree structure at each depth based on the analyzed tree_coded_axis_flag. 
     The three-dimensional data decoding device determines whether or not the flags corresponding to the target depth are tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0 (S 12432 ). 
     If the three-dimensional data decoding device determines that the flags corresponding to the target depth are tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0 (Yes in S 12432 ), the three-dimensional data decoding device determines that the tree structures at the depths from the target depth and beyond are all octrees (S 12433 ). That is, the three-dimensional data decoding device determines that the flags corresponding to the depths from the target depth and beyond are tree_coded_axis_flag[depth][0]=1, tree_coded_axis_flag [depth][1]=1, and tree_coded_axis_flag[depth][2]=1. 
     On the other hand, if the three-dimensional data decoding device determines that the flags corresponding to the target depth are not tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0 (No in S 12432 ), the three-dimensional data decoding device determines the tree structure at the target depth based on tree_coded_axis_flag (S 12434 ). 
     Further, with respect to the tree structure at each depth from the next depth and beyond after the target depth also, the three-dimensional data decoding device analyzes tree_coded_axis_flag to determine the tree structure (S 12435 ). 
       FIG.  44    is a diagram illustrating a first example of the syntax of header information according to the present embodiment. The syntax shown in  FIG.  44    is an example of a case in which it is predetermined that, with tree_coded_axis_flag[depth][0/1/2]=0 as a trigger, generation of tree_coded_axis_flag is omitted with respect to the depths after that depth, and the tree structures is regarded as an octree. 
     Here, tree_coded_axis_list_present_flag is a flag that indicates whether a flag indicating whether or not division was performed for each depth and axis (axes such as the x-axis) is present. For example, tree_coded_axis_list_present_flag=1 indicates that a flag indicating that division was performed is present. On the other hand, tree_coded_axis_list_present_flag=0 indicates that a flag indicating that division was performed is not present, and that only division into eight nodes (octree) was performed. 
     As described above, tree_coded_axis_flag is a flag indicating whether or not division was performed for each depth and axis. For example, tree_coded_axis_flag=1 indicates that, at the depth of the node that is the target, the node is divided with respect to the axial direction that is the target. On the other hand, tree_coded_axis_flag=0 indicates that the node is not divided. 
     Further, in a case where flags for all three axial directions are tree_coded_axis_flag=0, that is, a case where tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0, transmission of tree_coded_axis_flag with respect to deeper depths than a depth indicated by these flags may be omitted. 
     Accordingly, for example, by prescribing in advance that it is only possible for the tree structure of a depth for which tree_coded_axis_flag is not present to be an octree, the amount of code can be reduced by a code amount corresponding to omission of tree_coded_axis_flag, and the three-dimensional data decoding device can also appropriately determine the tree structure. In particular, the effect is noticeable in a case where the usage frequency of octrees is high. 
     The flag tree_depth_minus1 indicates depth −1 of the node that transmits tree_coded_axis_flag. For example, the maximum number of tree_coded_axis_flag that the three-dimensional data encoding device can transmit can be set to (tree_depth_minus1+1)×3. 
     However, in a case where, at a certain depth, tree_coded_axis_flag=0 for all three axial directions, transmission of tree_coded_axis_flag for deeper depths than that depth may be omitted irrespective of tree_depth_minus1. 
     Each of tree_coded_axis_list_present_flag, tree_coded_axis_flag, and tree_depth_minus1 generated as described above may be entropy-encoded. For example, each value may be binarized and arithmetically encoded. 
     Further, although the present embodiment is described taking an octree, a quadtree, and a binary tree as examples, the tree structures are not necessarily limited to these, and the present embodiment may be extended and applied to any tree structure such as a 16-tree structure. 
     Further, although in the present embodiment an example is described in which all the flags are present in the same header, tree_coded_axis_list_present_flag, tree_coded_axis_flag, and tree_depth_minus1 may be present in different headers to each other. Furthermore, although in the present embodiment an example is described in which tree_coded_axis_flag is transmitted in order from the smallest depth, tree_coded_axis_flag may be transmitted in order from the largest depth. The greater the extent to which code which it is desired to omit occurs later, the greater that the effect of reducing the code amount becomes. 
     Further, although in the present embodiment an example is described in which, in a case where tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0, transmission of tree_coded_axis_flag corresponding to deeper depths than that depth is omitted, it is not necessarily required for all of the values to be 0, and for example the values may be different. Further, although it has been described in the present embodiment that in a case where tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0, the tree structure at deeper depths than that depth is an octree, the tree structure may be a quadtree or a binary tree instead of an octree. By omitting the transmission of flags corresponding to a tree structure which has a high frequency of occurrence, the effect of reducing the code amount increases. 
     Further, although in the present embodiment an example is illustrated in which only an octree is applied in a case where tree_coded_axis_list_present_flag=0, a tree structure may be formed on a rule basis, that is, based on conditions that are arbitrarily determined in advance in a case where tree_coded_axis_list_present_flag=0. Furthermore, a flag indicating that only an octree is used, a flag indicating that only a quadtree is used, and a flag indicating that only a binary tree is used may be set. 
     Furthermore, tree_coded_axis_flag may be information that is provided for each node, may be information that is provided for each group in which a plurality of nodes are collected together such as a slice or a tile, or may be information that is provided for each frame. For example, the code amount can be decreased by the commonization of information for each node having the same properties. 
     Further, for example, in a case where an octree is used at a certain depth, that is, in a case where tree_coded_axis_flag[depth][0], tree_coded_axis_flag[depth][1], and tree_coded_axis_flag[depth][2] are all 1, tree structures at depths from that depth onward may each be taken to be an octree, and tree_coded_axis_flag corresponding to deeper depths than that depth may be omitted. 
       FIG.  45    is a diagram for describing a first example of the relationship between the depth and the number of divisions in a tree structure according to the present embodiment. 
     The three-dimensional data encoding device transforms position data by, for example, representing a tree structure in a case where the depths are from 0 to 3 as an octree, a quadtree, or a binary tree, and representing a tree structure in a case where the depth is 4 and beyond as an octree. In this case, for example, in the case of the depths from 0 to 3, for each depth the three-dimensional data encoding device generates tree_coded_axis_flag indicating the tree structure. Further, for example, the three-dimensional data encoding device generates tree_coded_axis_flag that indicates the tree structure (octree) in a case where the depth is 4 and also indicates that signaling of the tree structure in a case where the depth is 5 and beyond is not performed. For example, the three-dimensional data encoding device generates tree_coded_axis_flag[4][0]=0, tree_coded_axis_flag[4]=0, and tree_coded_axis_flag[4][2]= 0 . 
       FIG.  46    is a diagram illustrating a second example of the syntax of header information according to the present embodiment. The syntax shown in  FIG.  46    is an example of a case in which it is predetermined that, with respect to the next depth and beyond after a depth indicated by multi_tree_depth, generation of tree_coded_axis_flag is omitted and the respective tree structures are regarded as an octree. 
     Here, multi_tree_depth_minus1 indicates a depth for which there is a possibility that a tree structure selected from a plurality of kinds of tree structure can be used. That is, for example, an octree, a quadtree, or a binary tree is employed for a depth indicated by multi_tree_depth_minus1. 
     Thus, by using multi_tree_depth_minus1, a depth for which there is a possibility of using any one of a plurality of kinds of tree structures may be indicated separately from tree_depth_minus1. In this case, for example, the three-dimensional data encoding device generates tree_coded_axis_flag[x|y|z] indicating the tree structure at the depth indicated by multi_tree_depth_minus1. 
     Note that in this case, for example, it is determined in advance that the tree structure in deeper depths than the depth indicated by multi_tree_depth_minus1 is regarded as an octree. 
       FIG.  47    is a flowchart illustrating a second example of a procedure for determining a tree structure performed by the three-dimensional data decoding device according to the present embodiment. 
     First, the three-dimensional data decoding device, for example, starts a process to determine the tree structure at a depth (target depth) that is the target for determination of the tree structure, by analyzing pc_header included in a bitstream obtained from the three-dimensional data encoding device (S 12441 ). 
     Next, the three-dimensional data decoding device determines whether or not the target depth is equal to or less than (is a depth equal to or shallower than) the depth indicated by multi_tree_depth_minus1 included in the bitstream (S 12442 ). 
     If the three-dimensional data decoding device determines that the target depth is equal to or less than the depth indicated by multi_tree_depth_minus1 included in the bitstream (Yes in S 12442 ), the three-dimensional data decoding device determines the tree structure at the target depth based on tree_coded_axis_flag included in the bitstream (S 12443 ). In this case, for example, the three-dimensional data decoding device sets the next depth after the target depth as a new target depth, and performs the process from step S 12441  once more. 
     On the other hand, if the three-dimensional data decoding device determines that the target depth is deeper than the depth indicated by multi_tree_depth_minus1 included in the bitstream (No in S 12442 ), the three-dimensional data decoding device determines that the tree structure at the target depth is an octree (S 12444 ). In this case, for example, the three-dimensional data decoding device determines that the tree structures at the depths from the target depth and beyond are all octrees. 
       FIG.  48    is a diagram for describing a second example of the relationship between the depth and the number of divisions in a tree structure according to the present embodiment. 
     The three-dimensional data encoding device, for example, transforms position data by representing a tree structure in a case where the depths are from 0 to 3 as an octree, a quadtree, or a binary tree, and representing a tree structure in a case where the depth is 4 and beyond as an octree. In this case, for example, in the case of the depths from 0 to 3, for each depth the three-dimensional data encoding device generates tree_coded_axis_flag indicating the tree structure. Further, for example, the three-dimensional data encoding device sets a depth that multi_tree_depth_minus1 indicates to 4. 
       FIG.  49    is a diagram illustrating a third example of the syntax of header information according to the present embodiment. The syntax illustrated in  FIG.  49    is an example of a case where, when the respective depths are viewed in order from a depth of 0, at first the tree structure is an octree, a quadtree, or a binary tree, and then from an intermediate depth the tree structures are consecutively octrees, and thereafter the tree structure is again an octree, a quadtree, or a binary tree. 
     In the syntax shown in  FIG.  49   , tree_coded_axis_flag[depth][0/1/2]=0 is taken as a trigger, and for the next depth and beyond after that depth the generation of tree_coded_axis_flag is omitted and the respective tree structures are regarded as an octree. 
     In the syntax in the present example, num_end_flag is generated. Here, num_end_flag indicates the end of the depths for which generation of tree_coded_axis_flag is omitted and the tree structure is regarded as an octree. For example, in a case where the depth that tree_coded_axis_flag[depth][0/1/2]=0 indicates is 4, and the depth that num_end_flag indicates is 6, the tree structure at each of depths 4, 5 and 6 is regarded as an octree. In this case, when there are depths of 7 and beyond in the tree structure representing the position data, the three-dimensional data encoding device generates tree_coded_axis_flag indicating the tree structure of each depth from depth of 7 and beyond. 
       FIG.  50    is a diagram for describing a third example of the relationship between the depth and the number of divisions in a tree structure according to the present embodiment. 
     The three-dimensional data encoding device, for example, transforms position data by representing a tree structure in a case where the depths are from 0 to 3 as an octree, a quadtree, or a binary tree, representing a tree structure in a case where the depths are from 4 to 6 as an octree, and representing a tree structure in a case where the depth is 7 as an octree, a quadtree, or a binary tree. In this case, for example, in the case of the depths from 0 to 3, for each depth the three-dimensional data encoding device generates tree_coded_axis_flag indicating the tree structure. Further, for example, to indicate the tree structure in the case where the depths are from 4 to 6, the three-dimensional data encoding device generates tree_coded_axis_flag[4][0]=0, tree_coded_axis_flag[4][1]=0, and tree_coded_axis_flag[4][2]=0, and num_end_flag indicating that the depth is 6. Further, for example, the three-dimensional data encoding device generates tree_coded_axis_flag indicating the tree structure in the case where the depth is 7. 
       FIG.  51    is a diagram illustrating a fourth example of the syntax of header information according to the present embodiment. The syntax illustrated in  FIG.  51    is an example of a case where, when the respective depths are viewed in order from a depth of 0, at first the tree structure is an octree, a quadtree, or a binary tree, and then from an intermediate depth the tree structures are consecutively octrees, and thereafter the tree structure is again an octree, a quadtree, or a binary tree. 
     In the syntax shown in  FIG.  51   , generation of tree_coded_axis_flag is omitted from the depth that multi_tree_depth indicates and beyond until the depth that num_end_flag indicates, and the respective tree structures are regarded as an octree. 
     Note that, instead of generating num_end_flag, information indicating the number of consecutive depths in which the tree structure is an octree may be generated. 
       FIG.  52    is a diagram for describing a fourth example of the relationship between the depth and the number of divisions in a tree structure according to the present embodiment. 
     The three-dimensional data encoding device, for example, transforms position data by representing a tree structure in a case where the depths are from 0 to 3 as an octree, a quadtree, or a binary tree, representing a tree structure in a case where the depths are from 4 to 6 as an octree, and representing a tree structure in a case where the depth is 7 as an octree, a quadtree, or a binary tree. In this case, for example, in the case of the depths from 0 to 3, for each depth the three-dimensional data encoding device generates tree_coded_axis_flag indicating the tree structure. Further, for example, the three-dimensional data encoding device generates multi_tree_depth_minus1 indicating the depth is 4 and num_end_flag indicating the depth is 6. Further, for example, the three-dimensional data encoding device generates tree_coded_axis_flag indicating the tree structure in the case where the depth is 7. 
     Next, a specific example of a method for determining a tree structure at each depth will be described. In the method for determining a tree structure described hereunder, for example, a space is divided so as to form one of a plurality of kinds of tree structures according to a predetermined rule that is prescribed in advance. The predetermined rule may be, for example, to determine the tree structure based on the number of times a tree structure other than an octree is used, or based on the length of a bounding box forming a three-dimensional point cloud. 
     By the use of a predetermined rule that is prescribed in advance, in a case where a space corresponding to a root node is a rectangular parallelepiped structure, by preferentially dividing the space in the direction of an axis parallel to the long side in the rectangular parallelepiped, the accuracy of the position data can be maintained by quickly causing the space after being divided to approximate a cubic structure. Further, according to this division method, even a rectangular parallelepiped structure at a deep depth can be ultimately formed into a cubic structure. 
     As described above, the three-dimensional data encoding apparatus according to the present embodiment performs the process illustrated in  FIG.  53   . 
       FIG.  53    is a flowchart illustrating a procedure performed by the three-dimensional data encoding device according to the present embodiment. 
     First, the three-dimensional data encoding device encodes geometry information of a plurality of three-dimensional points represented by a tree structure (S 12481 ). 
     Next, the three-dimensional data encoding device generates a bitstream including the geometry information encoded and division number information indicating a total number of divisions of each of a plurality of nodes included in the tree structure. 
     The division number information includes common division number information collectively indicating the total number of divisions of two or more nodes among the plurality of nodes. The division number information is, for example, information including the tree_coded_axis_flag described above. The common division number information is, for example, tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag [depth][1]=0, and tree_coded_axis_flag[depth][2]=0. Alternatively, the common division number information is the multi_tree_depth described above. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information. Therefore, the data amount included in the bitstream can be reduced. 
     Furthermore, for example, among the plurality of nodes, nodes located at a same depth in the tree structure are divided into a same number of divisions. In this case, for example, the division number information indicates the total number of divisions of nodes for each of depths in the tree structure. Furthermore, for example, the common division number information collectively indicates the total number of divisions of nodes for a plurality of depths. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information for a plurality of depths. Therefore, the data amount included in the bitstream can be reduced. 
     Furthermore, for example, the common division number information includes trigger information indicating that nodes have a same number of divisions from a predetermined depth and beyond in the tree structure, Trigger information is, for example, tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0. Alternatively, trigger information is, for example, multi_tree_depth described above. 
     Accordingly, nodes that have the same number of divisions can be easily indicated by means of trigger information. 
     Furthermore, for example, the common division number information further includes end depth information indicating an end depth up to which the number of divisions of nodes from the predetermined depth is the same. The end depth information is, for example, num_end_flag described above. 
     Accordingly, for example, when the numbers of divisions of nodes are viewed in order from the shallowest depth, if the number of divisions of nodes is successively the same from an intermediate depth, the number of divisions of the nodes can be easily indicated. 
     Furthermore, for example, the plurality of nodes each correspond to at least part of a space in a three-axis orthogonal coordinate system. In this case, for example, the division number information includes flag information indicating, for each of depths in the tree structure, whether to divide the space in each of three axial directions of the three-axis orthogonal coordinate system. Furthermore, for example, the trigger information is the flag information indicating not to divide the space in each of the three axial directions. The trigger information in this case is, for example, tree_coded_axis_flag[depth][0]=0, tree_coded_axis_flag[depth][1]=0, and tree_coded_axis_flag[depth][2]=0 
     Accordingly, trigger information can be easily indicated using the flag information. 
     Furthermore, for example, the three-dimensional data encoding device includes a processor and memory, and the processor performs the above process using the memory. A control program for performing the above process may be stored in the memory. 
     Furthermore, the three-dimensional data encoding device performs the process illustrated in  FIG.  54   . 
       FIG.  54    is a flowchart illustrating a procedure performed by the three-dimensional data decoding device according to the present embodiment. 
     First, the three-dimensional data decoding device obtains a bitstream including encoded geometry information and division number information. Here, the encoded geometry information is geometry information of a plurality of three-dimensional points represented by a tree structure, and the division number information indicates a total number of divisions of each of a plurality of nodes included in the tree structure (S 12491 ). 
     Next, the three-dimensional data decoding device decodes the encoded geometry information based on the division number information (S 12492 ). 
     The division number information includes common division number information collectively indicating the total number of divisions of two or more nodes among the plurality of nodes. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information. Therefore, the data amount included in the bitstream can be reduced. 
     Furthermore, for example, among the plurality of nodes, nodes located at a same depth in the tree structure are divided into a same number of divisions. In this case, for example, the division number information indicates the total number of divisions of nodes for each of depths in the tree structure. Furthermore, for example, the common division number information collectively indicates the total number of divisions of nodes for a plurality of depths. 
     Accordingly, for nodes in which the number of divisions is the same, information indicating the number of divisions is collected as common information for a plurality of depths, Therefore, the data amount included in the bitstream can be reduced. 
     Furthermore, for example, the common division number information includes trigger information indicating that nodes have a same number of divisions from a predetermined depth and beyond in the tree structure. 
     Accordingly, the number of divisions of nodes can be easily determined by means of trigger information. 
     Furthermore, for example, the common division number information further includes end depth information indicating an end depth up to which the number of divisions of nodes from the predetermined depth is the same. 
     Accordingly, for example, when the numbers of divisions of nodes are viewed in order from the shallowest depth, if the number of divisions of nodes is successively the same from an intermediate depth, the number of divisions of the nodes can be easily determined. 
     Furthermore, for example, the plurality of nodes each correspond to at least part of a space in a three-axis orthogonal coordinate system. In this case, for example, the division number information includes flag information indicating, for each of depths in the tree structure, whether to divide the space in each of three axial directions of the three-axis orthogonal coordinate system. Furthermore, for example, the trigger information is the flag information indicating not to divide the space in each of the three axial directions. 
     Accordingly, the number of division of nodes can be appropriately determined even with trigger information that is simply indicated using flag information. 
     Furthermore, for example, the three-dimensional data decoding device includes a processor and memory, and the processor performs the above process using the memory. A control program for performing the above process may be stored in the memory. 
     Embodiment 4 
     The following describes the structure of three-dimensional data creation device  810  according to the present embodiment.  FIG.  55    is a block diagram of an exemplary structure of three-dimensional data creation device  810  according to the present embodiment, Such three-dimensional data creation device  810  is equipped, for example, in a vehicle. Three-dimensional data creation device  810  transmits and receives three-dimensional data to and from an external cloud-based traffic monitoring system, a preceding vehicle, or a following vehicle, and creates and stores three-dimensional data. 
     Three-dimensional data creation device  810  includes data receiver  811 , communication unit  812 , reception controller  813 , format converter  814 , a plurality of sensors  815 , three-dimensional data creator  816 , three-dimensional data synthesizer  817 , three-dimensional data storage  818 , communication unit  819 , transmission controller  820 , format converter  821 , and data transmitter  822 . 
     Data receiver  811  receives three-dimensional data  831  from a cloud-based traffic monitoring system or a preceding vehicle. Three-dimensional data  831  includes, for example, information on a region undetectable by sensors  815  of the own vehicle, such as a point cloud, visible light video, depth information, sensor position information, and speed information. 
     Communication unit  812  communicates with the cloud-based traffic monitoring system or the preceding vehicle to transmit a data transmission request, etc. to the cloud-based traffic monitoring system or the preceding vehicle. 
     Reception controller  813  exchanges information, such as information on supported formats, with a communications partner via communication unit  812  to establish communication with the communications partner. 
     Format converter  814  applies format conversion, etc. on three-dimensional data  831  received by data receiver  811  to generate three-dimensional data  832 . Format converter  814  also decompresses or decodes three-dimensional data  831  when three-dimensional data  831  is compressed or encoded. 
     A plurality of sensors  815  are a group of sensors, such as visible light cameras and infrared cameras, that obtain information on the outside of the vehicle and generate sensor information  833 . Sensor information  833  is, for example, three-dimensional data such as a point cloud (point group data), when sensors  815  are laser sensors such as LiDARs. Note that a single sensor may serve as a plurality of sensors  815 . 
     Three-dimensional data creator  816  generates three-dimensional data  834  from sensor information  833 . Three-dimensional data  834  includes, for example, information such as a point cloud, visible light video, depth information, sensor position information, and speed information. 
     Three-dimensional data synthesizer  817  synthesizes three-dimensional data  834  created on the basis of sensor information  833  of the own vehicle with three-dimensional data  832  created by the cloud-based traffic monitoring system or the preceding vehicle, etc., thereby forming three-dimensional data  835  of a space that includes the space ahead of the preceding vehicle undetectable by sensors  815  of the own vehicle. 
     Three-dimensional data storage  818  stores generated three-dimensional data  835 , etc. 
     Communication unit  819  communicates with the cloud-based traffic monitoring system or the following vehicle to transmit a data transmission request, etc. to the cloud-based traffic monitoring system or the following vehicle. 
     Transmission controller  820  exchanges information such as information on supported formats with a communications partner via communication unit  819  to establish communication with the communications partner. Transmission controller  820  also determines a transmission region, which is a space of the three-dimensional data to be transmitted, on the basis of three-dimensional data formation information on three-dimensional data  832  generated by three-dimensional data synthesizer  817  and the data transmission request from the communications partner. 
     More specifically, transmission controller  820  determines a transmission region that includes the space ahead of the own vehicle undetectable by a sensor of the following vehicle, in response to the data transmission request from the cloud-based traffic monitoring system or the following vehicle. Transmission controller  820  judges, for example, whether a space is transmittable or whether the already transmitted space includes an update, on the basis of the three-dimensional data formation information to determine a transmission region. For example, transmission controller  820  determines, as a transmission region, a region that is: a region specified by the data transmission request; and a region, corresponding three-dimensional data  835  of which is present, Transmission controller  820  then notifies format converter  821  of the format supported by the communications partner and the transmission region. 
     Of three-dimensional data  835  stored in three-dimensional data storage  818 , format converter  821  converts three-dimensional data  836  of the transmission region into the format supported by the receiver end to generate three-dimensional data  837 . Note that format converter  821  may compress or encode three-dimensional data  837  to reduce the data amount. 
     Data transmitter  822  transmits three-dimensional data  837  to the cloud-based traffic monitoring system or the following vehicle. Such three-dimensional data  837  includes, for example, information on a blind spot, which is a region hidden from view of the following vehicle, such as a point cloud ahead of the own vehicle, visible light video, depth information, and sensor position information. 
     Note that an example has been described in which format converter  814  and format converter  821  perform format conversion, etc., but format conversion may not be performed. 
     With the above structure, three-dimensional data creation device  810  obtains, from an external device, three-dimensional data  831  of a region undetectable by sensors  815  of the own vehicle, and synthesizes three-dimensional data  831  with three-dimensional data  834  that is based on sensor information  833  detected by sensors  815  of the own vehicle, thereby generating three-dimensional data  835 . Three-dimensional data creation device  810  is thus capable of generating three-dimensional data of a range undetectable by sensors  815  of the own vehicle. 
     Three-dimensional data creation device  810  is also capable of transmitting, to the cloud-based traffic monitoring system or the following vehicle, etc., three-dimensional data of a space that includes the space ahead of the own vehicle undetectable by a sensor of the following vehicle, in response to the data transmission request from the cloud-based traffic monitoring system or the following vehicle. 
     The following describes the steps performed by three-dimensional data creation device  810  of transmitting three-dimensional data to a following vehicle.  FIG.  56    is a flowchart showing exemplary steps performed by three-dimensional data creation device  810  of transmitting three-dimensional data to a cloud-based traffic monitoring system or a following vehicle. 
     First, three-dimensional data creation device  810  generates and updates three-dimensional data  835  of a space that includes space on the road ahead of the own vehicle (S 801 ). More specifically, three-dimensional data creation device  810  synthesizes three-dimensional data  834  created on the basis of sensor information  833  of the own vehicle with three-dimensional data  831  created by the cloud-based traffic monitoring system or the preceding vehicle, etc., for example, thereby forming three-dimensional data  835  of a space that also includes the space ahead of the preceding vehicle undetectable by sensors  815  of the own vehicle. 
     Three-dimensional data creation device  810  then judges whether any change has occurred in three-dimensional data  835  of the space included in the space already transmitted (S 802 ). 
     When a change has occurred in three-dimensional data  835  of the space included in the space already transmitted due to, for example, a vehicle or a person entering such space from outside (Yes in S 802 ), three-dimensional data creation device  810  transmits, to the cloud-based traffic monitoring system or the following vehicle, the three-dimensional data that includes three-dimensional data  835  of the space in which the change has occurred (S 803 ). 
     Three-dimensional data creation device  810  may transmit three-dimensional data in which a change has occurred, at the same timing of transmitting three-dimensional data that is transmitted at a predetermined time interval, or may transmit three-dimensional data in which a change has occurred soon after the detection of such change. Stated differently, three-dimensional data creation device  810  may prioritize the transmission of three-dimensional data of the space in which a change has occurred to the transmission of three-dimensional data that is transmitted at a predetermined time interval. 
     Also, three-dimensional data creation device  810  may transmit, as three-dimensional data of a space in which a change has occurred, the whole three-dimensional data of the space in which such change has occurred, or may transmit only a difference in the three-dimensional data (e.g., information on three-dimensional points that have appeared or vanished, or information on the displacement of three-dimensional points). 
     Three-dimensional data creation device  810  may also transmit, to the following vehicle, meta-data on a risk avoidance behavior of the own vehicle such as hard breaking warning, before transmitting three-dimensional data of the space in which a change has occurred. This enables the following vehicle to recognize at an early stage that the preceding vehicle is to perform hard braking, etc., and thus to start performing a risk avoidance behavior at an early stage such as speed reduction. 
     When no change has occurred in three-dimensional data  835  of the space included in the space already transmitted (No in S 802 ), or after step S 803 , three-dimensional data creation device  810  transmits, to the cloud-based traffic monitoring system or the following vehicle, three-dimensional data of the space included in the space having a predetermined shape and located ahead of the own vehicle by distance L (S 804 ). 
     The processes of step S 801  through step S 804  are repeated, for example at a predetermined time interval. 
     When three-dimensional data  835  of the current space to be transmitted includes no difference from the three-dimensional map, three-dimensional data creation device  810  may not transmit three-dimensional data  837  of the space. 
     In the present embodiment, a client device transmits sensor information obtained through a sensor to a server or another client device. 
     A structure of a system according to the present embodiment will first be described.  FIG.  57    is a diagram showing the structure of a transmission/reception system of a three-dimensional map and sensor information according to the present embodiment. This system includes server  901 , and client devices  902 A and  902 B, Note that client devices  902 A and  902 B are also referred to as client device  902  when no particular distinction is made therebetween, Client device  902  is, for example, a vehicle-mounted device equipped in a mobile object such as a vehicle, Server  901  is, for example, a cloud-based traffic monitoring system, and is capable of communicating with the plurality of client devices  902 . 
     Server  901  transmits the three-dimensional map formed by a point cloud to client device  902 . Note that a structure of the three-dimensional map is not limited to a point cloud, and may also be another structure expressing three-dimensional data such as a mesh structure. 
     Client device  902  transmits the sensor information obtained by client device  902  to server  901 . The sensor information includes, for example, at least one of information obtained by LiDAR, a visible light image, an infrared image, a depth image, sensor position information, or sensor speed information. 
     The data to be transmitted and received between server  901  and client device  902  may be compressed in order to reduce data volume, and may also be transmitted uncompressed in order to maintain data precision. When compressing the data, it is possible to use a three-dimensional compression method on the point cloud based on, for example, an octree structure. It is possible to use a two-dimensional image compression method on the visible light image, the infrared image, and the depth image. The two-dimensional image compression method is, for example, MPEG-4 AVC or HEVC standardized by MPEG. 
     Server  901  transmits the three-dimensional map managed by server  901  to client device  902  in response to a transmission request for the three-dimensional map from client device  902 . Note that server  901  may also transmit the three-dimensional map without waiting for the transmission request for the three-dimensional map from client device  902 . For example, server  901  may broadcast the three-dimensional map to at least one client device  902  located in a predetermined space. Server  901  may also transmit the three-dimensional map suited to a position of client device  902  at fixed time intervals to client device  902  that has received the transmission request once, Server  901  may also transmit the three-dimensional map managed by server  901  to client device  902  every time the three-dimensional map is updated. 
     Client device  902  sends the transmission request for the three-dimensional map to server  901 . For example, when client device  902  wants to perform the self-location estimation during traveling, client device  902  transmits the transmission request for the three-dimensional map to server  901 . 
     Note that in the following cases, client device  902  may send the transmission request for the three-dimensional map to server  901 . Client device  902  may send the transmission request for the three-dimensional map to server  901  when the three-dimensional map stored by client device  902  is old. For example, client device  902  may send the transmission request for the three-dimensional map to server  901  when a fixed period has passed since the three-dimensional map is obtained by client device  902 . 
     Client device  902  may also send the transmission request for the three-dimensional map to server  901  before a fixed time when client device  902  exits a space shown in the three-dimensional map stored by client device  902 . For example, client device  902  may send the transmission request for the three-dimensional map to server  901  when client device  902  is located within a predetermined distance from a boundary of the space shown in the three-dimensional map stored by client device  902 . When a movement path and a movement speed of client device  902  are understood, a time when client device  902  exits the space shown in the three-dimensional map stored by client device  902  may be predicted based on the movement path and the movement speed of client device  902 . 
     Client device  902  may also send the transmission request for the three-dimensional map to server  901  when an error during alignment of the three-dimensional data and the three-dimensional map created from the sensor information by client device  902  is at least at a fixed level. 
     Client device  902  transmits the sensor information to server  901  in response to a transmission request for the sensor information from server  901 . Note that client device  902  may transmit the sensor information to server  901  without waiting for the transmission request for the sensor information from server  901 . For example, client device  902  may periodically transmit the sensor information during a fixed period when client device  902  has received the transmission request for the sensor information from server  901  once. Client device  902  may determine that there is a possibility of a change in the three-dimensional map of a surrounding area of client device  902  having occurred, and transmit this information and the sensor information to server  901 , when the error during alignment of the three-dimensional data created by client device  902  based on the sensor information and the three-dimensional map obtained from server  901  is at least at the fixed level. 
     Server  901  sends a transmission request for the sensor information to client device  902 . For example, server  901  receives position information, such as GPS information, about client device  902  from client device  902 , Server  901  sends the transmission request for the sensor information to client device  902  in order to generate a new three-dimensional map, when it is determined that client device  902  is approaching a space in which the three-dimensional map managed by server  901  contains little information, based on the position information about client device  902 . Server  901  may also send the transmission request for the sensor information, when wanting to (i) update the three-dimensional map, (ii) check road conditions during snowfall, a disaster, or the like, or (iii) check traffic congestion conditions, accident/incident conditions, or the like. 
     Client device  902  may set an amount of data of the sensor information to be transmitted to server  901  in accordance with communication conditions or bandwidth during reception of the transmission request for the sensor information to be received from server  901 . Setting the amount of data of the sensor information to be transmitted to server  901  is, for example, increasing/reducing the data itself or appropriately selecting a compression method. 
       FIG.  58    is a block diagram showing an example structure of client device  902 . Client device  902  receives the three-dimensional map formed by a point cloud and the like from server  901 , and estimates a self-location of client device  902  using the three-dimensional map created based on the sensor information of client device  902 . Client device  902  transmits the obtained sensor information to server  901 . 
     Client device  902  includes data receiver  1011 , communication unit  1012 , reception controller  1013 , format converter  1014 , sensors  1015 , three-dimensional data creator  1016 , three-dimensional image processor  1017 , three-dimensional data storage  1018 , format converter  1019 , communication unit  1020 , transmission controller  1021 , and data transmitter  1022 . 
     Data receiver  1011  receives three-dimensional map  1031  from server  901 . Three-dimensional map  1031  is data that includes a point cloud such as a WLD or a SWLD. Three-dimensional map  1031  may include compressed data or uncompressed data. 
     Communication unit  1012  communicates with server  901  and transmits a data transmission request (e.g., transmission request for three-dimensional map) to server  901 . 
     Reception controller  1013  exchanges information, such as information on supported formats, with a communications partner via communication unit  1012  to establish communication with the communications partner. 
     Format converter  1014  performs a format conversion and the like on three-dimensional map  1031  received by data receiver  1011  to generate three-dimensional map  1032 . Format converter  1014  also performs a decompression or decoding process when three-dimensional map  1031  is compressed or encoded. Note that format converter  1014  does not perform the decompression or decoding process when three-dimensional map  1031  is uncompressed data. 
     Sensors  1015  are a group of sensors, such as LiDARs, visible light cameras, infrared cameras, or depth sensors that obtain information about the outside of a vehicle equipped with client device  902 , and generate sensor information  1033 . Sensor information  1033  is, for example, three-dimensional data such as a point cloud (point group data) when sensors  1015  are laser sensors such as LiDARs. Note that a single sensor may serve as sensors  1015 . 
     Three-dimensional data creator  1016  generates three-dimensional data  1034  of a surrounding area of the own vehicle based on sensor information  1033 . For example, three-dimensional data creator  1016  generates point cloud data with color information on the surrounding area of the own vehicle using information obtained by LiDAR and visible light video obtained by a visible light camera. 
     Three-dimensional image processor  1017  performs a self-location estimation process and the like of the own vehicle, using (i) the received three-dimensional map  1032  such as a point cloud, and (ii) three-dimensional data  1034  of the surrounding area of the own vehicle generated using sensor information  1033 , Note that three-dimensional image processor  1017  may generate three-dimensional data  1035  about the surroundings of the own vehicle by merging three-dimensional map  1032  and three-dimensional data  1034 , and may perform the self-location estimation process using the created three-dimensional data  1035 . 
     Three-dimensional data storage  1018  stores three-dimensional map  1032 , three-dimensional data  1034 , three-dimensional data  1035 , and the like. 
     Format converter  1019  generates sensor information  1037  by converting sensor information  1033  to a format supported by a receiver end. Note that format converter  1019  may reduce the amount of data by compressing or encoding sensor information  1037 . Format converter  1019  may omit this process when format conversion is not necessary. Format converter  1019  may also control the amount of data to be transmitted in accordance with a specified transmission range. 
     Communication unit  1020  communicates with server  901  and receives a data transmission request (transmission request for sensor information) and the like from server  901 . 
     Transmission controller  1021  exchanges information, such as information on supported formats, with a communications partner via communication unit  1020  to establish communication with the communications partner. 
     Data transmitter  1022  transmits sensor information  1037  to server  901 . Sensor information  1037  includes, for example information obtained through sensors  1015 , such as information obtained by LiDAR, a luminance image obtained by a visible light camera, an infrared image obtained by an infrared camera, a depth image obtained by a depth sensor, sensor position information, and sensor speed information. 
     A structure of server  901  will be described next.  FIG.  59    is a block diagram showing an example structure of server  901 . Server  901  transmits sensor information from client device  902  and creates three-dimensional data based on the received sensor information. Server  901  updates the three-dimensional map managed by server  901  using the created three-dimensional data. Server  901  transmits the updated three-dimensional map to client device  902  in response to a transmission request for the three-dimensional lap from client device  902 . 
     Server  901  includes data receiver  1111 , communication unit  1112 , reception controller  1113 , format converter  1114 , three-dimensional data creator  1116 , three-dimensional data merger  1117 , three-dimensional data storage  1118 , format converter  1119 , communication unit  1120 , transmission controller  1121 , and data transmitter  1122 . 
     Data receiver  1111  receives sensor information  1037  from client device  902 . Sensor information  1037  includes, for example, information obtained by LiDAR, a luminance image obtained by a visible light camera, an infrared image obtained by an infrared camera, a depth image obtained by a depth sensor, sensor position information, sensor speed information, and the like. 
     Communication unit  1112  communicates with client device  902  and transmits a data transmission request (e.g., transmission request for sensor information) and the like to client device  902 . 
     Reception controller  1113  exchanges information, such as information on supported formats, with a communications partner via communication unit  1112  to establish communication with the communications partner. 
     Format converter  1114  generates sensor information  1132  by performing a decompression or decoding process when received sensor information  1037  is compressed or encoded. Note that format converter  1114  does not perform the decompression or decoding process when sensor information  1037  is uncompressed data. 
     Three-dimensional data creator  1116  generates three-dimensional data  1134  of a surrounding area of client device  902  based on sensor information  1132 . For example, three-dimensional data creator  1116  generates point cloud data with color information on the surrounding area of client device  902  using information obtained by LiDAR and visible light video obtained by a visible light camera. 
     Three-dimensional data merger  1117  updates three-dimensional map  1135  by merging three-dimensional data  1134  created based on sensor information  1132  with three-dimensional map  1135  managed by server  901 . 
     Three-dimensional data storage  1118  stores three-dimensional map  1135  and the like. 
     Format converter  1119  generates three-dimensional map  1031  by converting three-dimensional map  1135  to a format supported by the receiver end. Note that format converter  1119  may reduce the amount of data by compressing or encoding three-dimensional map  1135 . Format converter  1119  may omit this process when format conversion is not necessary. Format converter  1119  may also control the amount of data to be transmitted in accordance with a specified transmission range. 
     Communication unit  1120  communicates with client device  902  and receives a data transmission request (transmission request for three-dimensional map) and the like from client device  902 . 
     Transmission controller  1121  exchanges information, such as information on supported formats, with a communications partner via communication unit  1120  to establish communication with the communications partner. 
     Data transmitter  1122  transmits three-dimensional map  1031  to client device  902 . Three-dimensional map  1031  is data that includes a point cloud such as a WLD or a SWLD. Three-dimensional map  1031  may include one of compressed data and uncompressed data. 
     An operational flow of client device  902  will be described next.  FIG.  60    is a flowchart of an operation when client device  902  obtains the three-dimensional map. 
     Client device  902  first requests server  901  to transmit the three-dimensional map (point cloud, etc.) (S 1001 ). At this point, by also transmitting the position information about client device  902  obtained through GPS and the like, client device  902  may also request server  901  to transmit a three-dimensional map relating to this position information, Client device  902  next receives the three-dimensional map from server  901  (S 1002 ). When the received three-dimensional map is compressed data, client device  902  decodes the received three-dimensional map and generates an uncompressed three-dimensional map (S 1003 ). 
     Client device  902  next creates three-dimensional data  1034  of the surrounding area of client device  902  using sensor information  1033  obtained by sensors  1015  (S 1004 ). Client device  902  next estimates the self-location of client device  902  using three-dimensional map  1032  received from server  901  and three-dimensional data  1034  created using sensor information  1033  (S 1005 ). 
       FIG.  61    is a flowchart of an operation when client device  902  transmits the sensor information. Client device  902  first receives a transmission request for the sensor information from server  901  (S 1011 ). Client device  902  that has received the transmission request transmits sensor information  1037  to server  901  (S 1012 ). Note that client device  902  may generate sensor information  1037  by compressing each piece of information using a compression method suited to each piece of information, when sensor information  1033  includes a plurality of pieces of information obtained by sensors  1015 . 
     An operational flow of server  901  will be described next.  FIG.  62    is a flowchart of an operation when server  901  obtains the sensor information. Server  901  first requests client device  902  to transmit the sensor information (S 1021 ). Server  901  next receives sensor information  1037  transmitted from client device  902  in accordance with the request (S 1022 ), Server  901  next creates three-dimensional data  1134  using the received sensor information  1037  (S 1023 ), Server  901  next reflects the created three-dimensional data  1134  in three-dimensional map  1135  (S 1024 ). 
       FIG.  63    is a flowchart of an operation when server  901  transmits the three-dimensional map. Server  901  first receives a transmission request for the three-dimensional map from client device  902  (S 1031 ). Server  901  that has received the transmission request for the three-dimensional map transmits the three-dimensional map to client device  902  (S 1032 ). At this point, server  901  may extract a three-dimensional map of a vicinity of client device  902  along with the position information about client device  902 , and transmit the extracted three-dimensional map. Server  901  may compress the three-dimensional map formed by a point cloud using, for example, an octree structure compression method, and transmit the compressed three-dimensional map. 
     The following describes variations of the present embodiment. 
     Server  901  creates three-dimensional data  1134  of a vicinity of a position of client device  902  using sensor information  1037  received from client device  902 . Server  901  next calculates a difference between three-dimensional data  1134  and three-dimensional map  1135 , by matching the created three-dimensional data  1134  with three-dimensional map  1135  of the same area managed by server  901 . Server  901  determines that a type of anomaly has occurred in the surrounding area of client device  902 , when the difference is greater than or equal to a predetermined threshold. For example, it is conceivable that a large difference occurs between three-dimensional map  1135  managed by server  901  and three-dimensional data  1134  created based on sensor information  1037 , when land subsidence and the like occurs due to a natural disaster such as an earthquake. 
     Sensor information  1037  may include information indicating at least one of a sensor type, a sensor performance, and a sensor model number. Sensor information  1037  may also be appended with a class ID and the like in accordance with the sensor performance. For example, when sensor information  1037  is obtained by LiDAR, it is conceivable to assign identifiers to the sensor performance, A sensor capable of obtaining information with precision in units of several millimeters is class 1, a sensor capable of obtaining information with precision in units of several centimeters is class 2, and a sensor capable of obtaining information with precision in units of several meters is class 3. Server  901  may estimate sensor performance information and the like from a model number of client device  902 . For example, when client device  902  is equipped in a vehicle, server  901  may determine sensor specification information from a type of the vehicle. In this case, server  901  may obtain information on the type of the vehicle in advance, and the information may also be included in the sensor information. Server  901  may change a degree of correction with respect to three-dimensional data  1134  created using sensor information  1037 , using obtained sensor information  1037 . For example, when the sensor performance is high in precision (class 1), server  901  does not correct three-dimensional data  1134 , When the sensor performance is low in precision (class 3), server  901  corrects three-dimensional data  1134  in accordance with the precision of the sensor. For example, server  901  increases the degree (intensity) of correction with a decrease in the precision of the sensor. 
     Server  901  may simultaneously send the transmission request for the sensor information to the plurality of client devices  902  in a certain space, Server  901  does not need to use all of the sensor information for creating three-dimensional data  1134  and may, for example, select sensor information to be used in accordance with the sensor performance, when having received a plurality of pieces of sensor information from the plurality of client devices  902 , For example, when updating three-dimensional map  1135 , server  901  may select high-precision sensor information (class 1) from among the received plurality of pieces of sensor information, and create three-dimensional data  1134  using the selected sensor information. 
     Server  901  is not limited to only being a server such as a cloud-based traffic monitoring system, and may also be another (vehicle-mounted) client device,  FIG.  64    is a diagram of a system structure in this case. 
     For example, client device  902 C sends a transmission request for sensor information to client device  902 A located nearby, and obtains the sensor information from client device  902 A, Client device  902 C then creates three-dimensional data using the obtained sensor information of client device  902 A, and updates a three-dimensional map of client device  902 C. This enables client device  902 C to generate a three-dimensional map of a space that can be obtained from client device  902 A, and fully utilize the performance of client device  902 C. For example, such a case is conceivable when client device  902 C has high performance. 
     In this case, client device  902 A that has provided the sensor information is given rights to obtain the high-precision three-dimensional map generated by client device  902 C. Client device  902 A receives the high-precision three-dimensional map from client device  902 C in accordance with these rights. 
     Server  901  may send the transmission request for the sensor information to the plurality of client devices  902  (client device  902 A and client device  902 B) located nearby client device  902 C, When a sensor of client device  902 A or client device  902 B has high performance, client device  902 C is capable of creating the three-dimensional data using the sensor information obtained by this high-performance sensor. 
       FIG.  65    is a block diagram showing a functionality structure of server  901  and client device  902 . Server  901  includes, for example, three-dimensional map compression/decoding processor  1201  that compresses and decodes the three-dimensional map and sensor information compression/decoding processor  1202  that compresses and decodes the sensor information. 
     Client device  902  includes three-dimensional map decoding processor  1211  and sensor information compression processor  1212 . Three-dimensional map decoding processor  1211  receives encoded data of the compressed three-dimensional map, decodes the encoded data, and obtains the three-dimensional map, Sensor information compression processor  1212  compresses the sensor information itself instead of the three-dimensional data created using the obtained sensor information, and transmits the encoded data of the compressed sensor information to server  901 . With this structure, client device  902  does not need to internally store a processor that performs a process for compressing the three-dimensional data of the three-dimensional map (point cloud, etc.), as long as client device  902  internally stores a processor that performs a process for decoding the three-dimensional map (point cloud, etc.). This makes it possible to limit costs, power consumption, and the like of client device  902 . 
     As stated above, client device  902  according to the present embodiment is equipped in the mobile object, and creates three-dimensional data  1034  of a surrounding area of the mobile object using sensor information  1033  that is obtained through sensor  1015  equipped in the mobile object and indicates a surrounding condition of the mobile object. Client device  902  estimates a self-location of the mobile object using the created three-dimensional data  1034 . Client device  902  transmits obtained sensor information  1033  to server  901  or another client device  902 . 
     This enables client device  902  to transmit sensor information  1033  to server  901  or the like. This makes it possible to further reduce the amount of transmission data compared to when transmitting the three-dimensional data. Since there is no need for client device  902  to perform processes such as compressing or encoding the three-dimensional data, it is possible to reduce the processing amount of client device  902 . As such, client device  902  is capable of reducing the amount of data to be transmitted or simplifying the structure of the device. 
     Client device  902  further transmits the transmission request for the three-dimensional map to server  901  and receives three-dimensional map  1031  from server  901 . In the estimating of the self-location, client device  902  estimates the self-location using three-dimensional data  1034  and three-dimensional map  1032 . 
     Sensor information  1033  includes at least one of information obtained by a laser sensor, a luminance image, an infrared image, a depth image, sensor position information, or sensor speed information. 
     Sensor information  1033  includes information that indicates a performance of the sensor. 
     Client device  902  encodes or compresses sensor information  1033 , and in the transmitting of the sensor information, transmits sensor information  1037  that has been encoded or compressed to server  901  or another client device  902 . This enables client device  902  to reduce the amount of data to be transmitted. 
     For example, client device  902  includes a processor and memory. The processor performs the above processes using the memory. 
     Server  901  according to the present embodiment is capable of communicating with client device  902  equipped in the mobile object, and receives sensor information  1037  that is obtained through sensor  1015  equipped in the mobile object and indicates a surrounding condition of the mobile object. Server  901  creates three-dimensional data  1134  of a surrounding area of the mobile object using received sensor information  1037 . 
     With this, server  901  creates three-dimensional data  1134  using sensor information  1037  transmitted from client device  902 , This makes it possible to further reduce the amount of transmission data compared to when client device  902  transmits the three-dimensional data. Since there is no need for client device  902  to perform processes such as compressing or encoding the three-dimensional data, it is possible to reduce the processing amount of client device  902 . As such, server  901  is capable of reducing the amount of data to be transmitted or simplifying the structure of the device. 
     Server  901  further transmits a transmission request for the sensor information to client device  902 . 
     Server  901  further updates three-dimensional map  1135  using the created three-dimensional data  1134 , and transmits three-dimensional map  1135  to client device  902  in response to the transmission request for three-dimensional map  1135  from client device  902 . 
     Sensor information  1037  includes at least one of information obtained by a laser sensor, a luminance image, an infrared image, a depth image, sensor position information, or sensor speed information. 
     Sensor information  1037  includes information that indicates a performance of the sensor. 
     Server  901  further corrects the three-dimensional data in accordance with the performance of the sensor. This enables the three-dimensional data creation method to improve the quality of the three-dimensional data. 
     In the receiving of the sensor information, server  901  receives a plurality of pieces of sensor information  1037  received from a plurality of client devices  902 , and selects sensor information  1037  to be used in the creating of three-dimensional data  1134 , based on a plurality of pieces of information that each indicates the performance of the sensor included in the plurality of pieces of sensor information  1037 . This enables server  901  to improve the quality of three-dimensional data  1134 . 
     Server  901  decodes or decompresses received sensor information  1037 , and creates three-dimensional data  1134  using sensor information  1132  that has been decoded or decompressed. This enables server  901  to reduce the amount of data to be transmitted. 
     For example, server  901  includes a processor and memory. The processor performs the above processes using the memory. 
     The following will describe a variation of the present embodiment.  FIG.  66    is a diagram illustrating a configuration of a system according to the present embodiment. The system illustrated in  FIG.  66    includes server  2001 , client device  2002 A, and client device  20023 . 
     Client device  2002 A and client device  20023  are each provided in a mobile object such as a vehicle, and transmit sensor information to server  2001 . Server  2001  transmits a three-dimensional map (a point cloud) to client device  2002 A and client device  20023 . 
     Client device  2002 A includes sensor information obtainer  2011 , storage  2012 , and data transmission possibility determiner  2013 . It should be noted that client device  20023  has the same configuration. Additionally, when client device  2002 A and client device  2002 B are not particularly distinguished below, client device  2002 A and client device  20023  are also referred to as client device  2002 . 
       FIG.  67    is a flowchart illustrating operation of client device  2002  according to the present embodiment. 
     Sensor information obtainer  2011  obtains a variety of sensor information using sensors (a group of sensors) provided in a mobile object. 
     In other words, sensor information obtainer  2011  obtains sensor information obtained by the sensors (the group of sensors) provided in the mobile object and indicating a surrounding state of the mobile object. Sensor information obtainer  2011  also stores the obtained sensor information into storage  2012 . This sensor information includes at least one of information obtained by LiDAR, a visible light image, an infrared image, or a depth image. Additionally, the sensor information may include at least one of sensor position information, speed information, obtainment time information, or obtainment location information. Sensor position information indicates a position of a sensor that has obtained sensor information. Speed information indicates a speed of the mobile object when a sensor obtained sensor information. Obtainment time information indicates a time when a sensor obtained sensor information. Obtainment location information indicates a position of the mobile object or a sensor when the sensor obtained sensor information. 
     Next, data transmission possibility determiner  2013  determines whether the mobile object (client device  2002 ) is in an environment in which the mobile object can transmit sensor information to server  2001  (S 2002 ). For example, data transmission possibility determiner  2013  may specify a location and a time at which client device  2002  is present using GPS information etc., and may determine whether data can be transmitted. Additionally, data transmission possibility determiner  2013  may determine whether data can be transmitted, depending on whether it is possible to connect to a specific access point. 
     When client device  2002  determines that the mobile object is in the environment in which the mobile object can transmit the sensor information to server  2001  (YES in S 2002 ), client device  2002  transmits the sensor information to server  2001  (S 2003 ), In other words, when client device  2002  becomes capable of transmitting sensor information to server  2001 , client device  2002  transmits the sensor information held by client device  2002  to server  2001 . For example, an access point that enables high-speed communication using millimeter waves is provided in an intersection or the like. When client device  2002  enters the intersection, client device  2002  transmits the sensor information held by client device  2002  to server  2001  at high speed using the millimeter-wave communication. 
     Next, client device  2002  deletes from storage  2012  the sensor information that has been transmitted to server  2001  (S 2004 ). It should be noted that when sensor information that has not been transmitted to server  2001  meets predetermined conditions, client device  2002  may delete the sensor information. For example, when an obtainment time of sensor information held by client device  2002  precedes a current time by a certain time, client device  2002  may delete the sensor information from storage  2012 . In other words, when a difference between the current time and a time when a sensor obtained sensor information exceeds a predetermined time, client device  2002  may delete the sensor information from storage  2012 . Besides, when an obtainment location of sensor information held by client device  2002  is separated from a current location by a certain distance, client device  2002  may delete the sensor information from storage  2012 . In other words, when a difference between a current position of the mobile object or a sensor and a position of the mobile object or the sensor when the sensor obtained sensor information exceeds a predetermined distance, client device  2002  may delete the sensor information from storage  2012 , Accordingly, it is possible to reduce the capacity of storage  2012  of client device  2002 . 
     When client device  2002  does not finish obtaining sensor information (NO in S 2005 ), client device  2002  performs step S 2001  and the subsequent steps again. Further, when client device  2002  finishes obtaining sensor information (YES in S 2005 ), client device  2002  completes the process. 
     Client device  2002  may select sensor information to be transmitted to server  2001 , in accordance with communication conditions. For example, when high-speed communication is available, client device  2002  preferentially transmits sensor information (e.g., information obtained by LiDAR) of which the data size held in storage  2012  is large. Additionally, when high-speed communication is not readily available, client device  2002  transmits sensor information (e.g., a visible light image) which has high priority and of which the data size held in storage  2012  is small. Accordingly, client device  2002  can efficiently transmit sensor information held in storage  2012 , in accordance with network conditions Client device  2002  may obtain, from server  2001 , time information indicating a current time and location information indicating a current location. Moreover, client device  2002  may determine an obtainment time and an obtainment location of sensor information based on the obtained time information and location information. In other words, client device  2002  may obtain time information from server  2001  and generate obtainment time information using the obtained time information. Client device  2002  may also obtain location information from server  2001  and generate obtainment location information using the obtained location information. 
     For example, regarding time information, server  2001  and client device  2002  perform clock synchronization using a means such as the Network Time Protocol (NTP) or the Precision Time Protocol (PTP). This enables client device  2002  to obtain accurate time information. What&#39;s more, since it is possible to synchronize docks between server  2001  and client devices  2002 , it is possible to synchronize times included in pieces of sensor information obtained by separate client devices  2002 . As a result, server  2001  can handle sensor information indicating a synchronized time. It should be noted that a means of synchronizing docks may be any means other than the NTP or PTP. In addition, GPS information may be used as the time information and the location information. 
     Server  2001  may specify a time or a location and obtain pieces of sensor information from client devices  2002 . For example, when an accident occurs, in order to search for a client device in the vicinity of the accident, server  2001  specifies an accident occurrence time and an accident occurrence location and broadcasts sensor information transmission requests to client devices  2002 . Then, client device  2002  having sensor information obtained at the corresponding time and location transmits the sensor information to server  2001 . In other words, client device  2002  receives, from server  2001 , a sensor information transmission request including specification information specifying a location and a time. When sensor information obtained at a location and a time indicated by the specification information is stored in storage  2012 , and client device  2002  determines that the mobile object is present in the environment in which the mobile object can transmit the sensor information to server  2001 , client device  2002  transmits, to server  2001 , the sensor information obtained at the location and the time indicated by the specification information. Consequently, server  2001  can obtain the pieces of sensor information pertaining to the occurrence of the accident from client devices  2002 , and use the pieces of sensor information for accident analysis etc. 
     It should be noted that when client device  2002  receives a sensor information transmission request from server  2001 , client device  2002  may refuse to transmit sensor information. Additionally, client device  2002  may set in advance which pieces of sensor information can be transmitted. Alternatively, server  2001  may inquire of client device  2002  each time whether sensor information can be transmitted. 
     A point may be given to client device  2002  that has transmitted sensor information to server  2001 . This point can be used in payment for, for example, gasoline expenses, electric vehicle (EV) charging expenses, a highway toll, or rental car expenses, After obtaining sensor information, server  2001  may delete information for specifying client device  2002  that has transmitted the sensor information. For example, this information is a network address of client device  2002 . Since this enables the anonymization of sensor information, a user of client device  2002  can securely transmit sensor information from client device  2002  to server  2001 . Server  2001  may include servers. For example, by servers sharing sensor information, even when one of the servers breaks down, the other servers can communicate with client device  2002 . Accordingly, it is possible to avoid service outage due to a server breakdown. 
     A specified location specified by a sensor information transmission request indicates an accident occurrence location etc., and may be different from a position of client device  2002  at a specified time specified by the sensor information transmission request. For this reason, for example, by specifying, as a specified location, a range such as within XX meters of a surrounding area, server  2001  can request information from client device  2002  within the range. Similarly, server  2001  may also specify, as a specified time, a range such as within N seconds before and after a certain time. As a result, server  2001  can obtain sensor information from client device  2002  present for a time from t−N to t+N and in a location within XX meters from absolute position S. When client device  2002  transmits three-dimensional data such as LiDAR, client device  2002  may transmit data created immediately after time t. 
     Server  2001  may separately specify information indicating, as a specified location, a location of client device  2002  from which sensor information is to be obtained, and a location at which sensor information is desirably obtained. For example, server  2001  specifies that sensor information including at least a range within YY meters from absolute position S is to be obtained from client device  2002  present within XX meters from absolute position S. When client device  2002  selects three-dimensional data to be transmitted, client device  2002  selects one or more pieces of three-dimensional data so that the one or more pieces of three-dimensional data include at least the sensor information including the specified range. Each of the one or more pieces of three-dimensional data is a random-accessible unit of data. In addition, when client device  2002  transmits a visible light image, client device  2002  may transmit pieces of temporally continuous image data including at least a frame immediately before or immediately after time t. 
     When client device  2002  can use physical networks such as 5G, Wi-Fi, or modes in 5G for transmitting sensor information, client device  2002  may select a network to be used according to the order of priority notified by server  2001 . Alternatively, client device  2002  may select a network that enables client device  2002  to ensure an appropriate bandwidth based on the size of transmit data. Alternatively, client device  2002  may select a network to be used, based on data transmission expenses etc. A transmission request from server  2001  may include information indicating a transmission deadline, for example, performing transmission when client device  2002  can start transmission by time t. When server  2001  cannot obtain sufficient sensor information within a time limit, server  2001  may issue a transmission request again. 
     Sensor information may include header information indicating characteristics of sensor data along with compressed or uncompressed sensor data. Client device  2002  may transmit header information to server  2001  via a physical network or a communication protocol that is different from a physical network or a communication protocol used for sensor data. For example, client device  2002  transmits header information to server  2001  prior to transmitting sensor data, Server  2001  determines whether to obtain the sensor data of client device  2002 , based on a result of analysis of the header information. For example, header information may include information indicating a point cloud obtainment density, an elevation angle, or a frame rate of LiDAR, or information indicating, for example, a resolution, an SN ratio, or a frame rate of a visible light image. Accordingly, server  2001  can obtain the sensor information from client device  2002  having the sensor data of determined quality. 
     As stated above, client device  2002  is provided in the mobile object, obtains sensor information that has been obtained by a sensor provided in the mobile object and indicates a surrounding state of the mobile object, and stores the sensor information into storage  2012 . Client device  2002  determines whether the mobile object is present in an environment in which the mobile object is capable of transmitting the sensor information to server  2001 , and transmits the sensor information to server  2001  when the mobile object is determined to be present in the environment in which the mobile object is capable of transmitting the sensor information to server  2001 . 
     Additionally, client device  2002  further creates, from the sensor information, three-dimensional data of a surrounding area of the mobile object, and estimates a self-location of the mobile object using the three-dimensional data created. 
     Besides, client device  2002  further transmits a transmission request for a three-dimensional map to server  2001 , and receives the three-dimensional map from server  2001 , In the estimating, client device  2002  estimates the self-location using the three-dimensional data and the three-dimensional map. 
     It should be noted that the above process performed by client device  2002  may be realized as an information transmission method for use in client device  2002 . 
     In addition, client device  2002  may include a processor and memory. Using the memory, the processor may perform the above process. 
     Next, a sensor information collection system according to the present embodiment will be described.  FIG.  68    is a diagram illustrating a configuration of the sensor information collection system according to the present embodiment. As illustrated in  FIG.  68   , the sensor information collection system according to the present embodiment includes terminal  2021 A, terminal  2021 B, communication device  2022 A, communication device  2022 B, network  2023 , data collection server  2024 , map server  2025 , and client device  2026 . It should be noted that when terminal  2021 A and terminal  2021 B are not particularly distinguished, terminal  2021 A and terminal  2021 B are also referred to as terminal  2021 . Additionally, when communication device  2022 A and communication device  2022 B are not particularly distinguished, communication device  2022 A and communication device  2022 B are also referred to as communication device  2022 . 
     Data collection server  2024  collects data such as sensor data obtained by a sensor included in terminal  2021  as position-related data in which the data is associated with a position in a three-dimensional space. 
     Sensor data is data obtained by, for example, detecting a surrounding state of terminal  2021  or an internal state of terminal  2021  using a sensor included in terminal  2021 . Terminal  2021  transmits, to data collection server  2024 , one or more pieces of sensor data collected from one or more sensor devices in locations at which direct communication with terminal  2021  is possible or at which communication with terminal  2021  is possible by the same communication system or via one or more relay devices. 
     Data included in position-related data may include, for example, information indicating an operating state, an operating log, a service use state, etc. of a terminal or a device included in the terminal. In addition, the data include in the position-related data may include, for example, information in which an identifier of terminal  2021  is associated with a position or a movement path etc, of terminal  2021 . 
     Information indicating a position included in position-related data is associated with, for example, information indicating a position in three-dimensional data such as three-dimensional map data. The details of information indicating a position will be described later. 
     Position-related data may include at least one of the above-described time information or information indicating an attribute of data included in the position-related data or a type (e.g., a model number) of a sensor that has created the data, in addition to position information that is information indicating a position. The position information and the time information may be stored in a header area of the position-related data or a header area of a frame that stores the position-related data. Further, the position information and the time information may be transmitted and/or stored as metadata associated with the position-related data, separately from the position-related data. 
     Map server  2025  is connected to, for example, network  2023 , and transmits three-dimensional data such as three-dimensional map data in response to a request from another device such as terminal  2021 . Besides, as described in the aforementioned embodiments, map server  2025  may have, for example, a function of updating three-dimensional data using sensor information transmitted from terminal  2021 . 
     Data collection server  2024  is connected to, for example, network  2023 , collects position-related data from another device such as terminal  2021 , and stores the collected position-related data into a storage of data collection server  2024  or a storage of another server. In addition, data collection server  2024  transmits, for example, metadata of collected position-related data or three-dimensional data generated based on the position-related data, to terminal  2021  in response to a request from terminal  2021 . 
     Network  2023  is, for example, a communication network such as the Internet. Terminal  2021  is connected to network  2023  via communication device  2022 . Communication device  2022  communicates with terminal  2021  using one communication system or switching between communication systems. Communication device  2022  is a communication satellite that performs communication using, for example, (1) a base station compliant with Long-Term Evolution (LTE) etc., (2) an access point (AP) for Wi-Fi or millimeter-wave communication etc., (3) a low-power wide-area (LPWA) network gateway such as SIGFOX, LoRaWAN, or Wi-SUN, or (4) a satellite communication system such as DVB-S2. 
     It should be noted that a base station may communicate with terminal  2021  using a system classified as an LPWA network such as Narrowband Internet of Things (NB IoT) or LTE-M, or switching between these systems. 
     Here, although, in the example given, terminal  2021  has a function of communicating with communication device  2022  that uses two types of communication systems, and communicates with map server  2025  or data collection server  2024  using one of the communication systems or switching between the communication systems and between communication devices  2022  to be a direct communication partner; a configuration of the sensor information collection system and terminal  2021  is not limited to this. For example, terminal  2021  need not have a function of performing communication using communication systems, and may have a function of performing communication using one of the communication systems, Terminal  2021  may also support three or more communication systems, Additionally, each terminal  2021  may support a different communication system. 
     Terminal  2021  includes, for example, the configuration of client device  902  illustrated in  FIG.  58   . Terminal  2021  estimates a self-location etc. using received three-dimensional data. Besides, terminal  2021  associates sensor data obtained from a sensor and position information obtained by self-location estimation to generate position-related data. 
     Position information appended to position-related data indicates, for example, a position in a coordinate system used for three-dimensional data. For example, the position information is coordinate values represented using a value of a latitude and a value of a longitude, Here, terminal  2021  may include, in the position information, a coordinate system serving as a reference for the coordinate values and information indicating three-dimensional data used for location estimation, along with the coordinate values, Coordinate values may also include altitude information. 
     The position information may be associated with a data unit or a space unit usable for encoding the above three-dimensional data, Such a unit is, for example, WLD, GOS, SPC, VLM, or VXL. Here, the position information is represented by, for example, an identifier for identifying a data unit such as the SPC corresponding to position-related data. It should be noted that the position information may include, for example, information indicating three-dimensional data obtained by encoding a three-dimensional space including a data unit such as the SPC or information indicating a detailed position within the SPC, in addition to the identifier for identifying the data unit such as the SPC. The information indicating the three-dimensional data is, for example, a file name of the three-dimensional data. 
     As stated above, by generating position-related data associated with position information based on location estimation using three-dimensional data, the system can give more accurate position information to sensor information than when the system appends position information based on a self-location of a client device (terminal  2021 ) obtained using a GPS to sensor information. As a result, even when another device uses the position-related data in another service, there is a possibility of more accurately determining a position corresponding to the position-related data in an actual space, by performing location estimation based on the same three-dimensional data. 
     It should be noted that although the data transmitted from terminal  2021  is the position-related data in the example given in the present embodiment, the data transmitted from terminal  2021  may be data unassociated with position information. In other words, the transmission and reception of three-dimensional data or sensor data described in the other embodiments may be performed via network  2023  described in the present embodiment. 
     Next, a different example of position information indicating a position in a three-dimensional or two-dimensional actual space or in a map space will be described. The position information appended to position-related data may be information indicating a relative position relative to a keypoint in three-dimensional data, Here, the keypoint serving as a reference for the position information is encoded as, for example, SWLD, and notified to terminal  2021  as three-dimensional data. 
     The information indicating the relative position relative to the keypoint may be, for example, information that is represented by a vector from the keypoint to the point indicated by the position information, and indicates a direction and a distance from the keypoint to the point indicated by the position information. Alternatively, the information indicating the relative position relative to the keypoint may be information Indicating an amount of displacement from the keypoint to the point indicated by the position information along each of the x axis, the y axis, and the z axis. Additionally, the information indicating the relative position relative to the keypoint may be information indicating a distance from each of three or more keypoints to the point indicated by the position information. It should be noted that the relative position need not be a relative position of the point indicated by the position information represented using each keypoint as a reference, and may be a relative position of each keypoint represented with respect to the point indicated by the position information. Examples of position information based on a relative position relative to a keypoint include information for identifying a keypoint to be a reference, and information indicating the relative position of the point indicated by the position information and relative to the keypoint. When the information indicating the relative position relative to the keypoint is provided separately from three-dimensional data, the information indicating the relative position relative to the keypoint may include, for example, coordinate axes used in deriving the relative position, information indicating a type of the three-dimensional data, and/or information indicating a magnitude per unit amount (e.g., a scale) of a value of the information indicating the relative position. 
     The position information may include, for each keypoint, information indicating a relative position relative to the keypoint. When the position information is represented by relative positions relative to keypoints, terminal  2021  that intends to identify a position in an actual space indicated by the position information may calculate candidate points of the position indicated by the position information from positions of the keypoints each estimated from sensor data, and may determine that a point obtained by averaging the calculated candidate points is the point indicated by the position information, Since this configuration reduces the effects of errors when the positions of the keypoints are estimated from the sensor data, it is possible to improve the estimation accuracy for the point in the actual space indicated by the position information. Besides, when the position information includes information indicating relative positions relative to keypoints, if it is possible to detect any one of the keypoints regardless of the presence of keypoints undetectable due to a limitation such as a type or performance of a sensor included in terminal  2021 , it is possible to estimate a value of the point indicated by the position information. 
     A point identifiable from sensor data can be used as a keypoint. Examples of the point identifiable from the sensor data include a point or a point within a region that satisfies a predetermined keypoint detection condition, such as the above-described three-dimensional feature or feature of visible light data is greater than or equal to a threshold value. 
     Moreover, a marker etc. placed in an actual space may be used as a keypoint. In this case, the maker may be detected and located from data obtained using a sensor such as LiDAR or a camera. For example, the marker may be represented by a change in color or luminance value (degree of reflection), or a three-dimensional shape (e.g., unevenness). Coordinate values indicating a position of the marker, or a two-dimensional bar code or a bar code etc. generated from an identifier of the marker may be also used. 
     Furthermore, a light source that transmits an optical signal may be used as a marker. When a light source of an optical signal is used as a marker, not only information for obtaining a position such as coordinate values or an identifier but also other data may be transmitted using an optical signal. For example, an optical signal may include contents of service corresponding to the position of the marker, an address for obtaining contents such as a URL, or an identifier of a wireless communication device for receiving service, and information indicating a wireless communication system etc, for connecting to the wireless communication device. The use of an optical communication device (a light source) as a marker not only facilitates the transmission of data other than information indicating a position but also makes it possible to dynamically change the data. 
     Terminal  2021  finds out a correspondence relationship of keypoints between mutually different data using, for example, a common identifier used for the data, or information or a table indicating the correspondence relationship of the keypoints between the data. When there is no information indicating a correspondence relationship between keypoints, terminal  2021  may also determine that when coordinates of a keypoint in three-dimensional data are converted into a position in a space of another three-dimensional data, a keypoint closest to the position is a corresponding keypoint. 
     When the position information based on the relative position described above is used, terminal  2021  that uses mutually different three-dimensional data or services can identify or estimate a position indicated by the position information with respect to a common keypoint included in or associated with each three-dimensional data. As a result, terminal  2021  that uses the mutually different three-dimensional data or the services can identify or estimate the same position with higher accuracy. 
     Even when map data or three-dimensional data represented using mutually different coordinate systems are used, since it is possible to reduce the effects of errors caused by the conversion of a coordinate system, it is possible to coordinate services based on more accurate position information. 
     Hereinafter, an example of functions provided by data collection server  2024  will be described. Data collection server  2024  may transfer received position-related data to another data server. When there are data servers, data collection server  2024  determines to which data server received position-related data is to be transferred, and transfers the position-related data to a data server determined as a transfer destination. 
     Data collection server  2024  determines a transfer destination based on, for example, transfer destination server determination rules preset to data collection server  2024 . The transfer destination server determination rules are set by, for example, a transfer destination table in which identifiers respectively associated with terminals  2021  are associated with transfer destination data servers. 
     Terminal  2021  appends an identifier associated with terminal  2021  to position-related data to be transmitted, and transmits the position-related data to data collection server  2024 . Data collection server  2024  determines a transfer destination data server corresponding to the identifier appended to the position-related data, based on the transfer destination server determination rules set out using the transfer destination table etc.; and transmits the position-related data to the determined data server. The transfer destination server determination rules may be specified based on a determination condition set using a time, a place, etc. at which position-related data is obtained. Here, examples of the identifier associated with transmission source terminal  2021  include an identifier unique to each terminal  2021  or an identifier indicating a group to which terminal  2021  belongs. 
     The transfer destination table need not be a table in which identifiers associated with transmission source terminals are directly associated with transfer destination data servers. For example, data collection server  2024  holds a management table that stores tag information assigned to each identifier unique to terminal  2021 , and a transfer destination table in which the pieces of tag information are associated with transfer destination data servers, Data collection server  2024  may determine a transfer destination data server based on tag information, using the management table and the transfer destination table, Here, the tag information is, for example, control information for management or control information for providing service assigned to a type, a model number, an owner of terminal  2021  corresponding to the identifier, a group to which terminal  2021  belongs, or another identifier. Moreover, in the transfer destination able, identifiers unique to respective sensors may be used instead of the identifiers associated with transmission source terminals  2021 , Furthermore, the transfer destination server determination rules may be set by client device  2026 . 
     Data collection server  2024  may determine data servers as transfer destinations, and transfer received position-related data to the data servers, According to this configuration, for example, when position-related data is automatically backed up or when, in order that position-related data is commonly used by different services, there is a need to transmit the position-related data to a data server for providing each service, it is possible to achieve data transfer as intended by changing a setting of data collection server  2024 . As a result, it is possible to reduce the number of steps necessary for building and changing a system, compared to when a transmission destination of position-related data is set for each terminal  2021 . 
     Data collection server  2024  may register, as a new transfer destination, a data server specified by a transfer request signal received from a data server; and transmit position-related data subsequently received to the data server, in response to the transfer request signal. 
     Data collection server  2024  may store position-related data received from terminal  2021  into a recording device, and transmit position-related data specified by a transmission request signal received from terminal  2021  or a data server to request source terminal  2021  or the data server in response to the transmission request signal. 
     Data collection server  2024  may determine whether position-related data is suppliable to a request source data server or terminal  2021 , and transfer or transmit the position-related data to the request source data server or terminal  2021  when determining that the position-related data is suppliable. 
     When data collection server  2024  receives a request for current position-related data from client device  2026 , even if it is not a timing for transmitting position-related data by terminal  2021 , data collection server  2024  may send a transmission request for the current position-related data to terminal  2021 , and terminal  2021  may transmit the current position-related data in response to the transmission request. 
     Although terminal  2021  transmits position information data to data collection server  2024  in the above description, data collection server  2024  may have a function of managing terminal  2021  such as a function necessary for collecting position-related data from terminal  2021  or a function used when collecting position-related data from terminal  2021 . 
     Data collection server  2024  may have a function of transmitting, to terminal  2021 , a data request signal for requesting transmission of position information data, and collecting position-related data. 
     Management information such as an address for communicating with terminal  2021  from which data is to be collected or an identifier unique to terminal  2021  is registered in advance in data collection server  2024 . Data collection server  2024  collects position-related data from terminal  2021  based on the registered management information. Management information may include information such as types of sensors included in terminal  2021 , the number of sensors included in terminal  2021 , and communication systems supported by terminal  2021 . 
     Data collection server  2024  may collect information such as an operating state or a current position of terminal  2021  from terminal  2021 . 
     Registration of management information may be instructed by client device  2026 , or a process for the registration may be started by terminal  2021  transmitting a registration request to data collection server  2024 . Data collection server  2024  may have a function of controlling communication between data collection server  2024  and terminal  2021 . 
     Communication between data collection server  2024  and terminal  2021  may be established using a dedicated line provided by a service provider such as a mobile network operator (MNO) or a mobile virtual network operator (MVNO), or a virtual dedicated line based on a virtual private network (VPN). According to this configuration, it is possible to perform secure communication between terminal  2021  and data collection server  2024 . 
     Data collection server  2024  may have a function of authenticating terminal  2021  or a function of encrypting data to be transmitted and received between data collection server  2024  and terminal  2021 . Here, the authentication of terminal  2021  or the encryption of data is performed using, for example, an identifier unique to terminal  2021  or an identifier unique to a terminal group including terminals  2021 , which is shared in advance between data collection server  2024  and terminal  2021 . Examples of the identifier include an international mobile subscriber identity (IMSI) that is a unique number stored in a subscriber identity module (SIM) card. An identifier for use in authentication and an identifier for use in encryption of data may be identical or different. 
     The authentication or the encryption of data between data collection server  2024  and terminal  2021  is feasible when both data collection server  2024  and terminal  2021  have a function of performing the process. The process does not depend on a communication system used by communication device  2022  that performs relay. Accordingly, since it is possible to perform the common authentication or encryption without considering whether terminal  2021  uses a communication system, the user&#39;s convenience of system architecture is increased. However, the expression “does not depend on a communication system used by communication device  2022  that performs relay” means a change according to a communication system is not essential. In other words, in order to improve the transfer efficiency or ensure security, the authentication or the encryption of data between data collection server  2024  and terminal  2021  may be changed according to a communication system used by a relay device. 
     Data collection server  2024  may provide client device  2026  with a User Interface (UI) that manages data collection rules such as types of position-related data collected from terminal  2021  and data collection schedules. Accordingly, a user can specify, for example, terminal  2021  from which data is to be collected using client device  2026 , a data collection time, and a data collection frequency. Additionally, data collection server  2024  may specify, for example, a region on a map from which data is to be desirably collected, and collect position-related data from terminal  2021  included in the region. 
     When the data collection rules are managed on a per terminal  2021  basis, client device  2026  presents, on a screen, a list of terminals  2021  or sensors to be managed. The user sets, for example, a necessity for data collection or a collection schedule for each item in the list. 
     When a region on a map from which data is to be desirably collected is specified, client device  2026  presents, on a screen, a two-dimensional or three-dimensional map of a region to be managed. The user selects the region from which data is to be collected on the displayed map. Examples of the region selected on the map include a circular or rectangular region having a point specified on the map as the center, or a circular or rectangular region specifiable by a drag operation. Client device  2026  may also select a region in a preset unit such as a city, an area or a block in a city, or a main road, etc. Instead of specifying a region using a map, a region may be set by inputting values of a latitude and a longitude, or a region may be selected from a list of candidate regions derived based on inputted text information, Text information is, for example, a name of a region, a city, or a landmark. 
     Moreover, data may be collected while the user dynamically changes a specified region by specifying one or more terminals  2021  and setting a condition such as within 100 meters of one or more terminals  2021 . 
     When client device  2026  includes a sensor such as a camera, a region on a map may be specified based on a position of client device  2026  in an actual space obtained from sensor data. For example, client device  2026  may estimate a self-location using sensor data, and specify, as a region from which data is to be collected, a region within a predetermined distance from a point on a map corresponding to the estimated location or a region within a distance specified by the user. Client device  2026  may also specify, as the region from which the data is to be collected, a sensing region of the sensor, that is, a region corresponding to obtained sensor data. Alternatively, client device  2026  may specify, as the region from which the data is to be collected, a region based on a location corresponding to sensor data specified by the user. Either client device  2026  or data collection server  2024  may estimate a region on a map or a location corresponding to sensor data. 
     When a region on a map is specified, data collection server  2024  may specify terminal  2021  within the specified region by collecting current position information of each terminal  2021 , and may send a transmission request for position-related data to specified terminal  2021 . When data collection server  2024  transmits information indicating a specified region to terminal  2021 , determines whether terminal  2021  is present within the specified region, and determines that terminal  2021  is present within the specified region, rather than specifying terminal  2021  within the region, terminal  2021  may transmit position-related data. 
     Data collection server  2024  transmits, to client device  2026 , data such as a list or a map for providing the above-described User Interface (UI) in an application executed by client device  2026 . Data collection server  2024  may transmit, to client device  2026 , not only the data such as the list or the map but also an application program. Additionally, the above UI may be provided as contents created using HTML displayable by a browser. It should be noted that part of data such as map data may be supplied from a server, such as map server  2025 , other than data collection server  2024 . 
     When client device  2026  receives an input for notifying the completion of an input such as pressing of a setup key by the user, client device  2026  transmits the inputted information as configuration information to data collection server  2024 . Data collection server  2024  transmits, to each terminal  2021 , a signal for requesting position-related data or notifying position-related data collection rules, based on the configuration information received from client device  2026 , and collects the position-related data. 
     Next, an example of controlling operation of terminal  2021  based on additional information added to three-dimensional or two-dimensional map data will be described. 
     In the present configuration, object information that indicates a position of a power feeding part such as a feeder antenna or a feeder coil for wireless power feeding buried under a road or a parking lot is included in or associated with three-dimensional data, and such object information is provided to terminal  2021  that is a vehicle or a drone. 
     A vehicle or a drone that has obtained the object information to get charged automatically moves so that a position of a charging part such as a charging antenna or a charging coil included in the vehicle or the drone becomes opposite to a region indicated by the object information, and such vehicle or a drone starts to charge itself. It should be noted that when a vehicle or a drone has no automatic driving function, a direction to move in or an operation to perform is presented to a driver or an operator by using an image displayed on a screen, audio, etc. When a position of a charging part calculated based on an estimated self-location is determined to fall within the region indicated by the object information or a predetermined distance from the region, an image or audio to be presented is changed to a content that puts a stop to driving or operating, and the charging is started. 
     Object information need not be information indicating a position of a power feeding part, and may be information indicating a region within which placement of a charging part results in a charging efficiency greater than or equal to a predetermined threshold value. A position indicated by object information may be represented by, for example, the central point of a region indicated by the object information, a region or a line within a two-dimensional plane, or a region, a line, or a plane within a three-dimensional space. 
     According to this configuration, since it is possible to identify the position of the power feeding antenna unidentifiable by sensing data of LiDAR or an image captured by the camera, it is possible to highly accurately align a wireless charging antenna included in terminal  2021  such as a vehicle with a wireless power feeding antenna buried under a road. As a result, it is possible to increase a charging speed at the time of wireless charging and improve the charging efficiency. 
     Object information may be an object other than a power feeding antenna. For example, three-dimensional data includes, for example, a position of an AP for millimeter-wave wireless communication as object information. Accordingly, since terminal  2021  can identify the position of the AP in advance, terminal  2021  can steer a directivity of beam to a direction of the object information and start communication. As a result, it is possible to improve communication quality such as increasing transmission rates, reducing the duration of time before starting communication, and extending a communicable period. 
     Object information may include information indicating a type of an object corresponding to the object information. In addition, when terminal  2021  is present within a region in an actual space corresponding to a position in three-dimensional data of the object information or within a predetermined distance from the region, the object information may include information indicating a process to be performed by terminal  2021 . 
     Object information may be provided by a server different from a server that provides three-dimensional data. When object information is provided separately from three-dimensional data, object groups in which object information used by the same service is stored may be each provided as separate data according to a type of a target service or a target device. 
     Three-dimensional data used in combination with object information may be point cloud data of WLD or keypoint data of SWLD. 
     In the three-dimensional data encoding device, when attribute information of a current three-dimensional point to be encoded is layer-encoded using Levels of Detail (LoDs), the three-dimensional data decoding device may decode the attribute information in layers down to LoD required by the three-dimensional data decoding device and need not decode the attribute information in layers not required. For example, when the total number of LoDs for the attribute information in a bitstream generated by the three-dimensional data encoding device is N, the three-dimensional data decoding device may decode M LoDs (M&lt;N), i.e., layers from the uppermost layer LoD0 to LoD(M−1), and need not decode the remaining LoDs, i.e., layers down to LoD(N−1), With this, while reducing the processing load, the three-dimensional data decoding device can decode the attribute information in layers from LoD0 to LoD(M−1) required by the three-dimensional data decoding device. 
       FIG.  69    is a diagram illustrating the foregoing use case. In the example shown in  FIG.  69   , a server stores a three-dimensional map obtained by encoding three-dimensional geometry information and attribute information. The server (the three-dimensional data encoding device) broadcasts the three-dimensional map to client devices (the three-dimensional data decoding devices: for example, vehicles, drones, etc.) in an area managed by the server, and each client device uses the three-dimensional map received from the server to perform a process for identifying the self-position of the client device or a process for displaying map information to a user or the like who operates the client device. 
     The following describes an example of the operation in this case. First, the server encodes the geometry information of the three-dimensional map using an octree structure or the like. Then, the sever layer-encodes the attribute information of the three-dimensional map using N LoDs established based on the geometry information. The server stores a bitstream of the three-dimensional map obtained by the layer-encoding. 
     Next, in response to a send request for the map information from the client device in the area managed by the server, the server sends the bitstream of the encoded three-dimensional map to the client device. 
     The client device receives the bitstream of the three-dimensional map sent from the server, and decodes the geometry information and the attribute information of the three-dimensional map in accordance with the intended use of the client device. For example, when the client device performs highly accurate estimation of the self-position using the geometry information and the attribute information in N LoDs, the client device determines that a decoding result to the dense three-dimensional points is necessary as the attribute information, and decodes all the information in the bitstream. 
     Moreover, when the client device displays the three-dimensional map information to a user or the like, the client device determines that a decoding result to the sparse three-dimensional points is necessary as the attribute information, and decodes the geometry information and the attribute information in M LoDs (M&lt;N) starting from an upper layer WM. 
     In this way, the processing load of the client device can be reduced by changing LoDs for the attribute information to be decoded in accordance with the intended use of the client device. 
     In the example shown in  FIG.  69   , for example, the three-dimensional map includes geometry information and attribute information. The geometry information is encoded using the octree. The attribute information is encoded using N LoDs. 
     Client device A performs highly accurate estimation of the self-position. In this case, client device A determines that all the geometry information and all the attribute information are necessary, and decodes ail the geometry information and ail the attribute information constructed from N LoDs in the bitstream. 
     Client device B displays the three-dimensional map to a user. In this case, client device B determines that the geometry information and the attribute information in M LoDs (M&lt;N) are necessary, and decodes the geometry information and the attribute information constructed from M LoDs in the bitstream. 
     It is to be noted that the server may broadcast the three-dimensional map to the client devices, or multicast or unicast the three-dimensional map to the client devices. 
     The following describes a variation of the system according to the present embodiment. In the three-dimensional data encoding device, when attribute information of a current three-dimensional point to be encoded is layer-encoded using LoDs, the three-dimensional data encoding device may encode the attribute information in layers down to LoD required by the three-dimensional data decoding device and need not encode the attribute information in layers not required. For example, when the total number of LoDs is N, the three-dimensional data encoding device may generate a bitstream by encoding M LoDs (M&lt;N), i.e., layers from the uppermost layer LoD0 to LoD(M−1), and not encoding the remaining LoDs, i.e., layers down to LoD(N−1). With this, in response to a request from the three-dimensional data decoding device, the three-dimensional data encoding device can provide a bitstream in which the attribute information from LoD0 to LoD(M−1) required by the three-dimensional data decoding device is encoded. 
       FIG.  70    is a diagram illustrating the foregoing use case. In the example shown in  FIG.  70   , a server stores a three-dimensional map obtained by encoding three-dimensional geometry information and attribute information. The server (the three-dimensional data encoding device) unicasts, in response to a request from the client device, the three-dimensional map to a client device (the three-dimensional data decoding device: for example, a vehicle, a drone, etc.) in an area managed by the server, and the client device uses the three-dimensional map received from the server to perform a process for identifying the self-position of the client device or a process for displaying map information to a user or the like who operates the client device. 
     The following describes an example of the operation in this case, First, the server encodes the geometry information of the three-dimensional map using an octree structure, or the like. Then, the sever generates a bitstream of three-dimensional map A by layer-encoding the attribute information of the three-dimensional map using N LoDs established based on the geometry information, and stores the generated bitstream in the server. The sever also generates a bitstream of three-dimensional map B by layer-encoding the attribute information of the three-dimensional map using M LoDs (M&lt;N) established based on the geometry information, and stores the generated bitstream in the server. 
     Next, the client device requests the server to send the three-dimensional map in accordance with the intended use of the client device. For example, when the client device performs highly accurate estimation of the self-position using the geometry information and the attribute information in N LoDs, the client device determines that a decoding result to the dense three-dimensional points is necessary as the attribute information, and requests the server to send the bitstream of three-dimensional map A. Moreover, when the client device displays the three-dimensional map information to a user or the like, the client device determines that a decoding result to the sparse three-dimensional points is necessary as the attribute information, and requests the server to send the bitstream of three-dimensional map B including the geometry information and the attribute information in M LoDs (M&lt;N) starting from an upper layer LoD0, Then, in response to the send request for the map information from the client device, the server sends the bitstream of encoded three-dimensional map A or B to the client device. 
     The client device receives the bitstream of three-dimensional map A or B sent from the server in accordance with the intended use of the client device, and decodes the received bitstream. In this way, the server changes a bitstream to be sent, in accordance with the intended use of the client device, With this, it is possible to reduce the processing load of the client device. 
     In the example shown in  FIG.  70   , the server stores three-dimensional map A and three-dimensional map B. The server generates three-dimensional map A by encoding the geometry information of the three-dimensional map using, for example, an octree structure, and encoding the attribute information of the three-dimensional map using N LoDs. In other words, NumLoD included in the bitstream of three-dimensional map A indicates N. 
     The server also generates three-dimensional map B by encoding the geometry information of the three-dimensional map using, for example, an octree structure, and encoding the attribute information of the three-dimensional map using M LoDs. In other words, NumLoD included in the bitstream of three-dimensional map B indicates M. 
     Client device A performs highly accurate estimation of the self-position. In this case, client device A determines that all the geometry information and all the attribute information are necessary, and requests the server to send three-dimensional map A including all the geometry information and the attribute information constructed from N LoDs. Client device A receives three-dimensional map A, and decodes all the geometry information and the attribute information constructed from N LoDs. 
     Client device B displays the three-dimensional map to a user. In this case, client device B determines that all the geometry information and the attribute information in M LoDs (M&lt;N) are necessary, and requests the server to send three-dimensional map B including all the geometry information and the attribute information constructed from M LoDs. Client device B receives three-dimensional map B, and decodes all the geometry information and the attribute information constructed from M LoDs. 
     It is to be noted that in addition to three-dimensional map B, the server (the three-dimensional data encoding device) may generate three-dimensional map C in which attribute information in the remaining N−M LoDs is encoded, and send three-dimensional map C to client device B in response to the request from client device B. Moreover, client device B may obtain the decoding result of N LoDs using the bitstreams of three-dimensional maps B and C. 
     Hereinafter, an example of an application process will be described.  FIG.  71    is a flowchart illustrating an example of the application process. When an application operation is started, a three-dimensional data demultiplexing device obtains an ISOBMFF file including point cloud data and a plurality of pieces of encoded data (S 7301 ). For example, the three-dimensional data demultiplexing device may obtain the ISOBMFF file through communication, or may read the ISOBMFF file from the accumulated data. 
     Next, the three-dimensional data demultiplexing device analyzes the general configuration information in the ISOBMFF file, and specifies the data to be used for the application (S 7302 ). For example, the three-dimensional data demultiplexing device obtains data that is used for processing, and does not obtain data that is not used for processing. 
     Next, the three-dimensional data demultiplexing device extracts one or more pieces of data to be used for the application, and analyzes the configuration information on the data (S 7303 ). 
     When the type of the data is encoded data (encoded data in S 7304 ), the three-dimensional data demultiplexing device converts the ISOBMFF to an encoded stream, and extracts a timestamp (S 7305 ). Additionally, the three-dimensional data demultiplexing device refers to, for example, the flag indicating whether or not the synchronization between data is aligned to determine whether or not the synchronization between data is aligned, and may perform a synchronization process when not aligned. 
     Next, the three-dimensional data demultiplexing device decodes the data with a predetermined method according to the timestamp and the other instructions, and processes the decoded data (S 7306 ). 
     On the other hand, when the type of the data is RAW data (RAW data in S 7304 ), the three-dimensional data demultiplexing device extracts the data and timestamp (S 7307 ), Additionally, the three-dimensional data demultiplexing device may refer to, for example, the flag indicating whether or not the synchronization between data is aligned to determine whether or not the synchronization between data is aligned, and may perform a synchronization process when not aligned. Next, the three-dimensional data demultiplexing device processes the data according to the timestamp and the other instructions (S 7308 ). 
     For example, an example will be described in which the sensor signals obtained by a beam LiDAR, a FLASH LiDAR, and a camera are encoded and multiplexed with respective different encoding schemes.  FIG.  72    is a diagram illustrating examples of the sensor ranges of a beam LiDAR, a FLASH LiDAR, and a camera. For example, the beam LiDAR detects all directions in the periphery of a vehicle (sensor), and the FLASH LiDAR and the camera detect the range in one direction (for example, the front) of the vehicle. 
     In the case of an application that integrally handles a LiDAR point cloud, the three-dimensional data demultiplexing device refers to the general configuration information, and extracts and decodes the encoded data of the beam LiDAR and the FLASH LiDAR. Additionally, the three-dimensional data demultiplexing device does not extract camera images. 
     According to the timestamps of the beam LiDAR and the FLASH LiDAR, the three-dimensional data demultiplexing device simultaneously processes the respective encoded data of the time of the same timestamp. 
     For example, the three-dimensional data demultiplexing device may present the processed data with a presentation device, may synthesize the point cloud data of the beam LiDAR and the FLASH LiDAR, or may perform a process such as rendering. 
     Additionally, in the case of an application that performs calibration between data, the three-dimensional data demultiplexing device may extract sensor geometry information, and use the sensor geometry information in the application. 
     For example, the three-dimensional data demultiplexing device may select whether to use beam LiDAR information or FLASH LiDAR information in the application, and may switch the process according to the selection result. 
     In this manner, since it is possible to adaptively change the obtaining of data and the encoding process according to the process of the application, the processing amount and the power consumption can be reduced. 
     Hereinafter, a use case in automated driving will be described.  FIG.  73    is a diagram illustrating a configuration example of an automated driving system. This automated driving system includes cloud server  7350 , and edge  7360  such as an in-vehicle device or a mobile device. Cloud server  7350  includes demultiplexer  7351 , decoders  7352 A,  73526 , and  7355 , point cloud data synthesizer  7353 , large data accumulator  7354 , comparator  7356 , and encoder  7357 . Edge  7360  includes sensors  7361 A and  73616 , point cloud data generators  7362 A and  73626 , synchronizer  7363 , encoders  7364 A and  73646 , multiplexer  7365 , update data accumulator  7366 , demultiplexer  7367 , decoder  7368 , filter  7369 , self-position estimator  7370 , and driving controller  7371 . 
     In this system, edge  7360  downloads large data, which is large point-cloud map data accumulated in cloud server  7350 . Edge  7360  performs a self-position estimation process of edge  7360  (a vehicle or a terminal) by matching the large data with the sensor information obtained by edge  7360 . Additionally, edge  7360  uploads the obtained sensor information to cloud server  7350 , and updates the large data to the latest map data. 
     Additionally, in various applications that handle point cloud data in the system, point cloud data with different encoding methods are handled. 
     Cloud server  7350  encodes and multiplexes large data. Specifically, encoder  7357  performs encoding by using a third encoding method suitable for encoding a large point cloud. Additionally, encoder  7357  multiplexes encoded data. Large data accumulator  7354  accumulates the data encoded and multiplexed by encoder  7357 . 
     Edge  7360  performs sensing, Specifically, point cloud data generator  7362 A generates first point cloud data (geometry information (geometry) and attribute information) by using the sensing information obtained by sensor  7361 A. Point cloud data generator  7362 B generates second point cloud data (geometry information and attribute information) by using the sensing information obtained by sensor  7361 B. The generated first point cloud data and second point cloud data are used for the self-position estimation or vehicle control of automated driving, or for map updating. In each process, a part of information of the first point cloud data and the second point cloud data may be used. 
     Edge  7360  performs the self-position estimation. Specifically, edge  7360  downloads large data from cloud server  7350 . Demultiplexer  7367  obtains encoded data by demultiplexing the large data in a file format. Decoder  7368  obtains large data, which is large point-cloud map data, by decoding the obtained encoded data. 
     Self-position estimator  7370  estimates the self-position in the map of a vehicle by matching the obtained large data with the first point cloud data and the second point cloud data generated by point cloud data generators  7362 A and  7362 B. Additionally, driving controller  7371  uses the matching result or the self-position estimation result for driving control. 
     Note that self-position estimator  7370  and driving controller  7371  may extract specific information, such as geometry information, of the large data, and may perform processes by using the extracted information, Additionally, filter  7369  performs a process such as correction or decimation on the first point cloud data and the second point cloud data, Self-position estimator  7370  and driving controller  7371  may use the first point cloud data and second point cloud data on which the process has been performed, Additionally, self-position estimator  7370  and driving controller  7371  may use the sensor signals obtained by sensors  7361 A and  7361 B. 
     Synchronizer  7363  performs time synchronization and geometry correction between a plurality of sensor signals or the pieces of data of a plurality of pieces of point cloud data. Additionally, synchronizer  7363  may correct the geometry information on the sensor signal or point cloud data to match the large data, based on geometry correction information on the large data and sensor data generated by the self-position estimation process. 
     Note that synchronization and geometry correction may be performed not by edge  7360 , but by cloud server  7350 . In this case, edge  7360  may multiplex the synchronization information and the geometry information to transmit the synchronization information and the geometry information to cloud server  7350 . 
     Edge  7360  encodes and multiplexes the sensor signal or point cloud data. Specifically, the sensor signal or point cloud data is encoded by using a first encoding method or a second encoding method suitable for encoding each signal. For example, encoder  7364 A generates first encoded data by encoding first point cloud data by using the first encoding method. Encoder  7364 B generates second encoded data by encoding second point cloud data by using the second encoding method. 
     Multiplexer  7365  generates a multiplexed signal by multiplexing the first encoded data, the second encoded data, the synchronization information, and the like. Update data accumulator  7366  accumulates the generated multiplexed signal. Additionally, update data accumulator  7366  uploads the multiplexed signal to cloud server  7350 . 
     Cloud server  7350  synthesizes the point cloud data. Specifically, demultiplexer  7351  obtains the first encoded data and the second encoded data by demultiplexing the multiplexed signal uploaded to cloud server  7350 . Decoder  7352 A obtains the first point cloud data (or sensor signal) by decoding the first encoded data. Decoder  7352 B obtains the second point cloud data (or sensor signal) by decoding the second encoded data. 
     Point cloud data synthesizer  7353  synthesizes the first point cloud data and the second point cloud data with a predetermined method. When the synchronization information and the geometry correction information are multiplexed in the multiplexed signal, point cloud data synthesizer  7353  may perform synthesis by using these pieces of information. 
     Decoder  7355  demultiplexes and decodes the large data accumulated in large data accumulator  7354 . Comparator  7356  compares the point cloud data generated based on the sensor signal obtained by edge  7360  with the large data held by cloud server  7350 , and determines the point cloud data that needs to be updated. Comparator  7356  updates the point cloud data that is determined to need to be updated of the large data to the point cloud data obtained from edge  7360 . 
     Encoder  7357  encodes and multiplexes the updated large data, and accumulates the obtained data in large data accumulator  7354 . 
     As described above, the signals to be handled may be different, and the signals to be multiplexed or encoding methods may be different, according to the usage or applications to be used. Even in such a case, flexible decoding and application processes are enabled by multiplexing data of various encoding schemes by using the present embodiment. Additionally, even in a case where the encoding schemes of signals are different, by conversion to an encoding scheme suitable for demultiplexing, decoding, data conversion, encoding, and multiplexing processing, it becomes possible to build various applications and systems, and to offer of flexible services. 
     Hereinafter, an example of decoding and application of divided data will be described. First, the information on divided data will be described.  FIG.  74    is a diagram illustrating a configuration example of a bitstream. The general information of divided data indicates, for each divided data, the sensor ID (sensor_id) and data ID (data_id) of the divided data, Note that the data ID is also indicated in the header of each encoded data. 
     Note that the general information of divided data illustrated in FIG.  74  includes, in addition to the sensor ID, at least one of the sensor information (Sensor), the version (Version) of the sensor, the maker name (Maker) of the sensor, the mount information (Mount Info.) of the sensor, and the position coordinates of the sensor (World Coordinate). Accordingly, the three-dimensional data decoding device can obtain the information on various sensors from the configuration information. 
     The general information of divided data may be stored in SPS, GPS, or APS, which is the metadata, or may be stored in SET, which is the metadata not required for encoding, Additionally, at the time of multiplexing, the three-dimensional data encoding device stores the SET in a file of ISOBMFF. The three-dimensional data decoding device can obtain desired divided data based on the metadata. 
     In  FIG.  74   , SPS is the metadata of the entire encoded data, GPS is the metadata of the geometry information, APS is the metadata for each attribute information, G is encoded data of the geometry information for each divided data, and A1, etc. are encoded data of the attribute information for each divided data. 
     Next, an application example of divided data will be described. An example of application will be described in which an arbitrary point cloud is selected, and the selected point cloud is presented.  FIG.  75    is a flowchart of a point cloud selection process performed by this application.  FIG.  76    to  FIG.  78    are diagrams illustrating screen examples of the point cloud selection process. 
     As illustrated in  FIG.  76   , the three-dimensional data decoding device that performs the application includes, for example, a UI unit that displays an input UI (user interface)  8661  for selecting an arbitrary point cloud, Input UI  8661  includes presenter  8662  that presents the selected point cloud, and an operation unit (buttons  8663  and  8664 ) that receives operations by a user. After a point cloud is selected in UI  8661 , the three-dimensional data decoding device obtains desired data from accumulator  8665 . 
     First, based on an operation by the user on input UI  8661 , the point cloud information that the user wants to display is selected (S 8631 ). Specifically, by selecting button  8663 , the point cloud based on sensor 1 is selected. By selecting button  8664 , the point cloud based on sensor 2 is selected. Alternatively, by selecting both button  8663  and button  8664 , the point cloud based on sensor 1 and the point cloud based on sensor 2 are selected. Note that it is an example of the selection method of point cloud, and it is not limited to this. 
     Next, the three-dimensional data decoding device analyzes the general information of divided data included in the multiplexed signal (bitstream) or encoded data, and specifies the data ID (data_id) of the divided data constituting the selected point cloud from the sensor ID (sensor_id) of the selected sensor (S 8632 ). Next, the three-dimensional data decoding device extracts, from the multiplexed signal, the encoded data including the specified and desired data ID, and decodes the extracted encoded data to decode the point cloud based on the selected sensor (S 8633 ). Note that the three-dimensional data decoding device does not decode the other encoded data. 
     Lastly, the three-dimensional data decoding device presents (for example, displays) the decoded point cloud (S 8634 ).  FIG.  77    illustrates an example in the case where button  8663  for sensor 1 is pressed, and the point cloud of sensor 1 is presented,  FIG.  78    illustrates an example in the case where both button  8663  for sensor 1 and button  8664  for sensor 2 are pressed, and the point clouds of sensor 1 and sensor 2 are presented. 
     A three-dimensional data encoding device, a three-dimensional data decoding device, and the like according to the embodiments of the present disclosure have been described above, but the present disclosure is not limited to these embodiments. 
     Note that each of the processors included in the three-dimensional data encoding device, the three-dimensional data decoding device, and the like according to the above embodiments is typically implemented as a large-scale integrated (LSI) circuit, which is an integrated circuit (IC), These may take the form of individual chips, or may be partially or entirely packaged into a single chip. 
     Such IC is not limited to an LSI, and thus may be implemented as a dedicated circuit or a general-purpose processor. Alternatively, a field programmable gate array (FPGA) that allows for programming after the manufacture of an LSI, or a reconfigurable processor that allows for reconfiguration of the connection and the setting of circuit cells inside an LSI may be employed. 
     Moreover, in the above embodiments, the structural components may be implemented as dedicated hardware or may be realized by executing a software program suited to such structural components. Alternatively, the structural components may be implemented by a program executor such as a CPU or a processor reading out and executing the software program recorded in a recording medium such as a hard disk or a semiconductor memory. 
     The present disclosure may also be implemented as a three-dimensional data encoding method, a three-dimensional data decoding method, or the like executed by the three-dimensional data encoding device, the three-dimensional data decoding device, and the like. 
     Also, the divisions of the functional blocks shown in the block diagrams are mere examples, and thus a plurality of functional blocks may be implemented as a single functional block, or a single functional block may be divided into a plurality of functional blocks, or one or more functions may be moved to another functional block. Also, the functions of a plurality of functional blocks having similar functions may be processed by single hardware or software in a parallelized or time-divided manner. 
     Also, the processing order of executing the steps shown in the flowcharts is a mere illustration for specifically describing the present disclosure, and thus may be an order other than the shown order. Also, one or more of the steps may be executed simultaneously (in parallel) with another step. 
     A three-dimensional data encoding device, a three-dimensional data decoding device, and the like according to one or more aspects have been described above based on the embodiments, but the present disclosure is not limited to these embodiments. The one or more aspects may thus include forms achieved by making various modifications to the above embodiments that can be conceived by those skilled in the art, as well forms achieved by combining structural components in different embodiments, without materially departing from the spirit of the present disclosure. 
     Although only some exemplary embodiments of the present disclosure have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the exemplary embodiments without materially departing from the novel teachings and advantages of the present disclosure. Accordingly, all such modifications are intended to be included within the scope of the present disclosure. 
     INDUSTRIAL APPLICABILITY 
     The present disclosure is applicable to a three-dimensional data encoding device and a three-dimensional data decoding device.