Information processing apparatus, information processing method, and program

Abstract

To support users in buying and selling digital content with NFTs attached by presenting the estimated value of the digital content.SOLUTION: An information processing apparatus is configured to: set information indicating a static evaluation for digital content, which is an evaluation according to the content of the digital content generated based on three-dimensional shape data indicating the three-dimensional shape of a subject that is generated using a plurality of captured images acquired by a plurality of imaging apparatuses; determine a dynamic evaluation for the digital content, an evaluation that can change over time; and estimate the value of the digital content based on both the static and dynamic evaluations.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and a program, and more particularly to evaluation of digital content. [Background technology]

[0002] Volumetric capture technology, which generates a three-dimensional shape model of a subject using multiple captured images obtained by a multi-viewpoint camera, has been attracting attention. By using volumetric capture technology, it is possible to generate an image from any viewpoint specified in a virtual space (hereinafter referred to as a virtual viewpoint image) (Patent Document 1).

[0003] Additionally, blockchain technology that uses non-fungible tokens (NFTs) to prove ownership of digital content has been attracting attention. For example, by assigning NFTs to digital content such as digital items in virtual spaces or computer games and digital artworks, ownership of such digital content can be proven. Patent Document 2 discloses a method for assessing the value of an NFT assigned to a virtual object in a computer game. When an NFT owner performs well in the game by operating a virtual object to which an NFT is assigned, the NFT owner becomes famous, and the value of the NFT increases. To reflect this mechanism, Patent Document 2 discloses assessing the value of an NFT assigned to a virtual object based on performance information indicating the performance of game actions using the virtual object. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-45920 [Patent Document 2] Japanese Patent Publication No. 2023-54812 Summary of the Invention [Problem to be solved by the invention]

[0005] There is a need to provide digital content created using volumetric capture technology to users while protecting the rights of its creators. For this purpose, NFTs can be attached to digital content. Digital content with NFTs can be bought and sold between users. However, it has not been easy to assess the value of such digital content with NFTs attached.

[0006] The present disclosure aims to assist users in buying and selling digital content with NFTs attached by presenting an estimated value of the digital content. [Means for solving the problem]

[0007] An information processing device according to an embodiment of the present disclosure has the following configuration: a setting means for setting information indicating a static evaluation of the digital content, the static evaluation being an evaluation according to the content of the digital content generated based on three-dimensional shape data indicating a three-dimensional shape of a subject generated using a plurality of captured images acquired by a plurality of imaging devices; a determining means for determining a dynamic rating of the digital content, the rating being a rating that may change over time; an estimation means for estimating a value of the digital content based on both the static evaluation and the dynamic evaluation; Equipped with. [Effects of the Invention]

[0008] By presenting an estimated value of digital content, we can assist users in buying and selling digital content with NFTs attached. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a configuration diagram of an information processing system according to an embodiment. [Figure 2] FIG. 1 is a hardware configuration diagram of an information processing apparatus according to an embodiment. [Figure 3] 1 is a flowchart of an information processing method according to an embodiment. [Figure 4] Schematic diagram of blockchain. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the scope of the claims. Although multiple features are described in the embodiments, not all of these multiple features are necessarily essential, and multiple features may be combined arbitrarily. Furthermore, in the accompanying drawings, the same reference numerals are used to designate the same or similar components, and redundant explanations will be omitted.

[0011] An information processing device according to one embodiment assigns a non-fungible token (hereinafter referred to as an NFT) to digital content generated from volumetric capture data. The NFT identifies the owner of the digital content to which the NFT is assigned. The information processing device also estimates the value of the digital content to which the NFT is assigned. Based on the value of the digital content, the value of the NFT assigned to the digital content can also be estimated.

[0012] Volumetric capture data (hereinafter simply referred to as capture data) is three-dimensional shape data that represents the three-dimensional shape of a subject. Such capture data is generated using multiple captured images acquired by multiple image capture devices. For example, the capture data can be generated based on position and orientation information for multiple cameras and captured images by the multiple cameras. The capture data can include a three-dimensional model of the subject. Here, the capture data may include a three-dimensional model of the subject that changes over time. The capture data may also include captured images or videos by multiple real cameras.

[0013] Examples of digital content generated from capture data include a video of a characteristic scene extracted from an arbitrary real camera video, and a virtual viewpoint video of the characteristic scene from a specified virtual viewpoint.

[0014] NFTs are a type of token issued and circulated on the blockchain. By utilizing NFTs, it is possible to give unique value to digital content. One example of an NFT format is a token standard called ERC-721 or ERC-1155.

[0015] (System Configuration) An information processing system according to one embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the configuration of the information processing system according to one embodiment and an example of the functional configuration of an information processing device 1. The information processing system includes the information processing device 1, an imaging device 2, an image processing device 3, a storage device 4, a blockchain system 5, and a display device 6.

[0016] The information processing device 1 generates digital content from the capture data. The information processing device 1 also assigns NFTs to the digital content. Furthermore, the information processing device 1 manages buying and selling information for the digital content to which the NFTs are assigned. Note that multiple NFTs can be assigned to one piece of digital content. In this specification, selling digital content is equivalent to selling NFTs. In other words, multiple NFTs can be sold for one piece of digital content. The information processing device 1 can also estimate the value of the digital content. As will be described later, the information processing device 1 can estimate the value of the digital content based on information accompanying the capture data, the buying and selling status of the digital content, etc.

[0017] The imaging device 2 includes multiple cameras. The multiple cameras are installed, for example, so as to capture images of a subject within the imaging area from different directions. Each camera has an identification number for identifying the camera. It is not necessary for the cameras to be installed all around the subject. For example, due to restrictions on installation space, cameras may be installed only in certain directions relative to the subject. The number of cameras is not limited. For example, when capturing images of a soccer or rugby match, tens to hundreds of cameras can be installed around the stadium. Furthermore, the imaging device 2 may include multiple cameras with different angles of view, such as a combination of telephoto and wide-angle cameras.

[0018] Each camera is synchronized according to one piece of real-world time information. Each frame of captured image that constitutes the video captured by each camera is assigned with capture time information. Furthermore, each camera can generate a foreground image from the captured image. A foreground image is an image generated by extracting a subject area (foreground area) from the captured image. The subject extracted as the foreground area is, for example, a dynamic subject (moving object). A moving object is a subject that moves (changes position or shape) when images are captured in time series from the same direction.

[0019] Examples of moving objects include people on the field where a game is being played, such as players or referees. In ball games, examples of moving objects include people as well as balls. In concerts or entertainment events, examples of moving objects include singers, musicians, performers, or presenters.

[0020] In this embodiment, one arithmetic unit is connected to each camera included in the imaging device 2. However, multiple cameras may be connected to one arithmetic unit. The arithmetic unit can hold state information such as the camera's position, attitude (direction and imaging direction), focal length, optical center, distortion, and F-number. Camera parameters related to the camera's position and attitude (direction and imaging direction) are so-called extrinsic parameters. Parameters related to the camera's focal length, image center, and distortion are so-called intrinsic parameters.

[0021] The image processing device 3 can acquire a foreground image and camera parameters from the imaging device 2. Then, the image processing device 3 estimates the three-dimensional shape of the subject based on this information and generates three-dimensional shape information indicating the three-dimensional shape of the subject. The image processing device 3 transmits the generated information to the storage device 4 as capture data.

[0022] Note that instead of the imaging device 2 processing the captured images as described above, the image processing device 3 may process the captured images. In this case, the image processing device 3 receives captured images from each camera and generates a foreground image. Alternatively, the image processing device 3 may obtain captured images that have been captured in advance and stored in an auxiliary storage device (not shown) and generate a foreground image.

[0023] Furthermore, the image processing device 3 may calculate the camera parameters instead of acquiring them from the imaging device 2. In this case, the image processing device 3 extracts feature points from marker images for camera calibration (e.g., captured images of a checkerboard) captured in advance by each camera, and associates the feature points between the cameras. The image processing device 3 can then calculate the camera parameters by optimizing the camera parameters of each camera so that the error between corresponding feature points when projected onto each camera is minimized. The method for optimizing the camera parameters is not particularly limited. The image processing device 3 may acquire the camera parameters synchronously with the captured image, or may acquire them asynchronously with the captured image as necessary. The camera parameters may also be acquired or generated in a preliminary preparation stage.

[0024] The image processing device 3 can estimate 3D shape information based on the foreground image and camera parameters. The 3D shape information can be represented by a set of points having 3D coordinates (hereinafter referred to as a point cloud model), or a mesh model having triangles or quadrangles as elements. The image processing device 3 may also calculate a color for each point of the point cloud model or for each element of the mesh model. The image processing device 3 can assign the calculated color to the 3D shape information as texture information. To generate the texture information, the image processing device 3 can, for example, convert the 3D coordinates of the points or elements into image coordinates on the captured image according to the camera parameters of each camera. If the converted image coordinates are within the foreground area, the image processing device 3 can acquire the pixel values ​​at the converted image coordinates as color information corresponding to the points or elements. If the converted image coordinates are within the foreground area in multiple images captured by multiple cameras, the image processing device 3 can blend colors by, for example, calculating the average of pixel values ​​in each of the multiple captured images.

[0025] The storage device 4 stores the foreground images, camera parameters, and 3D shape information generated by the image processing device 3 as capture data. The storage device 4 can store time-series foreground images, camera parameters, and 3D shape information. The storage device 4 may generate and store new information based on this information. An example of the new information is skeletal information. The skeletal information is information that represents the skeleton of the subject. The skeletal information can be expressed by the positions or angles of the joints of the subject. The joints of the subject and the connection relationships between the joints can be determined in advance.

[0026] The blockchain system 5 registers digital content on the blockchain in accordance with a request from the information processing device 1. At that time, the blockchain system 5 can issue an NFT for the digital content. In this way, the blockchain system 5 assigns an NFT to the digital content. The blockchain system 5 can issue a number of NFTs for the digital content determined by the creator of the digital content. For example, if 500 NFTs are issued, a maximum of 500 people can own the digital content. In order to increase the asset value of the digital content, for example, the number of NFTs issued can be limited, thereby increasing the scarcity of the digital content. Furthermore, NFTs can be managed by serial numbers.

[0027] The display device 6 is a device for displaying a screen. The display device 6 can display a user interface generated by the information processing device 1. The display device 6 can also acquire user input. The display device 6 can transmit the acquired user input to the information processing device 1. The display device 6 can be a device such as a personal computer, a smartphone, or a tablet. A user can use the display device 6 to set static information in capture data. A user can also use the display device 6 to buy and sell digital content to which NFTs are attached.

[0028] The information processing device 1 has a communication unit 100, a user information management unit 110, a static information setting unit 120, a generation unit 130, a content management unit 140, an NFT granting unit 150, a dynamic information calculation unit 160, and a value estimation unit 170.

[0029] The communication unit 100 communicates with the display device 6. The user information management unit 110 manages user information of users who access the information processing device 1. For example, the communication unit 100 can acquire user information of users of the display device 6 from the user information management unit 110. The communication unit 100 can also perform access control and function control according to the acquired user information. In the following example, there are two types of users: creators who take capture data or create digital content, and traders who buy and sell digital content.

[0030] The static information setting unit 120 sets information indicating a static evaluation of digital content (hereinafter referred to as static information). The static information setting unit 120 can acquire user input indicating such static information from the display device 6. Then, the static information setting unit 120 can set the static information for the digital content. In this embodiment, the static information indicates a static evaluation of the digital content that does not change over time. The static information can be information indicating an evaluation according to the content of the digital content.

[0031] The static information may be set according to the type of scene represented by the digital content. For example, the static information may indicate the rarity of the scene represented by the digital content. A high rarity indicates a high static evaluation of the digital content. The rarity may also be set according to the stage of the tournament of the match represented by the digital content, the scale of the competition, etc. For example, if the stage is the final, the rarity may be set high. Also, if the competition is an international competition, the rarity may be set high.

[0032] The static information may be set according to the type of subject represented by the digital content. Examples of the type of subject include a person, a ball, or a vehicle. Examples of the type of subject include a person's role, such as a pitcher, a batter, or a catcher. The static information may also be set according to the popularity of the subject. High popularity means that the digital content has a high static rating.

[0033] In this embodiment, the static information setting unit 120 sets static information for the capture data. The static information for the capture data may be information corresponding to the content of the capture data, such as the scene represented by the capture data. In this case, the static information setting unit 120 can set static information for digital content generated based on this capture data, based on the static information set for the capture data.

[0034] The generation unit 130 generates digital content according to the capture data and user instructions. The generation unit 130 can set content generation information used to generate the digital content. For example, the generation unit 130 can set the content generation information based on instructions from a creator. The content generation information can indicate settings for a process to generate the digital content. That is, the content generation information can indicate a static evaluation of the digital content, such as the type or quality of the digital content. Thus, in this embodiment, the content generation information is included in static information. That is, the generation unit 130 can also set static information.

[0035] In this embodiment, the digital content generated by the generation unit 130 is a real camera image, a shape model, a virtual viewpoint image, or a skeletal model. The real camera image is an image generated using a foreground image from the same viewpoint as the selected real camera. The shape model is a shape model representing the three-dimensional shape of a subject, generated using three-dimensional shape information stored in the storage device 4. For example, if the storage device 4 stores three-dimensional shape information representing the shapes of multiple subjects, the generation unit 130 can generate a shape model, which is digital content representing the shape of each subject. The virtual viewpoint image is an image of a subject from a virtual viewpoint set by a creator. The generation unit 130 can generate such a virtual viewpoint image using a foreground image, three-dimensional shape information, and virtual viewpoint information. The skeletal model represents the skeleton of the subject. The generation unit 130 can generate a skeletal model for each subject based on the skeletal information in each frame.

[0036] The content management unit 140 manages the digital content generated by the generation unit 130. The content management unit 140 also manages static information set in the digital content. Furthermore, the content management unit 140 can manage content generation information used to generate the digital content. Furthermore, the content management unit 140 can manage owner information of the digital content in cooperation with the blockchain system 5. An NFT can indicate owner information of the digital content to which the NFT is attached. Furthermore, the content management unit 140 can manage the buying and selling of digital content, and can further manage the buying and selling history. For example, the content management unit 140 can manage records of traders' purchases of each piece of digital content put up for sale by a creator. Furthermore, the content management unit 140 can manage records of traders' purchases of digital content from other traders.

[0037] The content management unit 140 may provide the digital content that it manages. For example, the content management unit 140 may transmit the digital content to the display device 6 for playback. Furthermore, the content management unit 140 may manage the usage status (e.g., playback status) of the digital content that it manages.

[0038] The NFT granting unit 150 requests the blockchain system 5 to grant an NFT to digital content. In this way, digital content managed by the content management unit 140 can be registered in the blockchain system 5. In addition, an NFT can be granted to digital content managed by the content management unit 140.

[0039] The dynamic information calculation unit 160 determines the dynamic rating of the digital content, which is a rating that can change over time. Hereinafter, information indicating the dynamic rating will be referred to as dynamic information. The dynamic information calculation unit 160 can calculate the dynamic information according to the buying and selling status of the digital content, or the buying and selling status of a group of digital content items generated based on the same volumetric capture data.

[0040] The value estimator 170 estimates the value of the digital content based on both static and dynamic ratings.

[0041] An example of the hardware configuration of the information processing device 1 will be described with reference to Fig. 2. Other devices included in the information processing system, such as the image processing device 3, storage device 4, blockchain system 5, and display device 6, can also be realized using similar hardware.

[0042] The information processing device 1 has a CPU 211, a ROM 212, a RAM 213, an auxiliary storage device 214, a display unit 215, an operation unit 216, a communication I / F 217, and a bus 218. The CPU 211 controls the entire system using computer programs or data stored in the ROM 212 or the RAM 213. In this way, the CPU 211 can realize each function of the information processing device 1 shown in FIG. 1. Note that the information processing device 1 may also have one or more dedicated hardware pieces different from the CPU 211. Such dedicated hardware can execute at least a part of the processing by the CPU 211. An example of the dedicated hardware is an ASIC (application-specific integrated circuit).

[0043] The ROM 212 stores programs that do not require modification. The RAM 213 temporarily stores programs or data supplied from the auxiliary storage device 214, or data supplied from the outside via the communication I / F 217. The auxiliary storage device 214 is, for example, a hard disk drive. The auxiliary storage device 214 can store various data such as image data or audio data.

[0044] The display unit 215 is, for example, a liquid crystal display or an LED. The display unit 215 can display a GUI (Graphical User Interface) for the user to operate the system. The operation unit 216 is, for example, a keyboard, a mouse, a joystick, or a touch panel. The operation unit 216 receives operations by the user and inputs various instructions to the CPU 211. The CPU 211 can operate as a display control unit that controls the display unit 215 and an operation control unit that controls the operation unit 216. The communication I / F 217 communicates with devices external to the information processing device 1. For example, when the information processing device 1 is connected to an external device via a wired connection, a communication cable is connected to the communication I / F 217. When the information processing device 1 communicates wirelessly with an external device, the communication I / F 217 includes an antenna. The bus 218 connects the various components to each other and transmits information between them. In FIG. 2, the display unit 215 and the operation unit 216 are located inside the information processing device 1. On the other hand, at least one of the display unit 215 and the operation unit 216 may exist as a separate device outside the information processing device 1 system.

[0045] In this way, a processor such as the CPU 211 executes a program stored in a memory such as the ROM 212, the RAM 213, or the auxiliary storage device 214, thereby realizing the functions of each unit shown in FIG. 1 and the like. Note that the information processing device 1 may be configured by a plurality of information processing devices connected via a network, for example. That is, the functions of the information processing device 1 may be provided by a cloud service. Furthermore, one information processing device may have the functions of two or more of the information processing device 1, the imaging device 2, the image processing device 3, the storage device 4, the blockchain system 5, and the display device 6.

[0046] (Operation flow) The processing performed by the information processing device 1 according to one embodiment will be described with reference to the flowchart shown in Fig. 3. Through the following processing, the information processing device 1 can estimate the value of digital content to which an NFT has been assigned.

[0047] In S300, the user logs in to the information processing device 1 via the display device 6. At this time, the communication unit 100 transmits the account information input by the user to the user information management unit 110. The user information management unit 110 compares the transmitted account information with the account information it manages. The user information management unit 110 then transmits the comparison result to the display device 6 via the communication unit 100. If the comparison is successful, the user information management unit 110 sets the user's account to a logged-in state. If the user is a new user, the user information management unit 110 prompts the user to input a username and account information for buying and selling digital content via the display device 6. The user information management unit 110 also prompts the user to select a user type, such as creator, trader, or other type. The user information management unit 110 then creates an account based on the input information. The following describes a case where a creator user logs in to the information processing device 1.

[0048] In S310, the generation unit 130 generates digital content using the capture data stored in the storage device 4. The creator first searches for characteristic scenes from the capture data stored in the storage device 4. In this embodiment, the creator searches for scenes representing a certain time period among the scenes indicated by the capture data. The creator then registers the start time and end time of the scene as scene information in the information processing device 1. When registering the scene information, the generation unit 130 automatically issues a scene ID for identifying the scene. This scene ID is assigned to the generated digital content. The creator may select scene information set by another creator.

[0049] The creator also inputs the type of digital content that he or she wishes to create to the information processing device 1. Furthermore, the creator inputs content generation information that specifies the process for generating the digital content to the information processing device 1. Note that the content generation information may include scene information.

[0050] For example, when generating real camera footage as digital content, the generation unit 130 receives a camera ID and scene information as content generation information. When the content generation information is input, the generation unit 130 generates the real camera footage based on the foreground image. The generation unit 130 then transmits the real camera footage together with the content generation information to the content management unit 140.

[0051] Furthermore, when generating a virtual viewpoint video as digital content, the generation unit 130 receives information specifying the virtual viewpoint as content generation information. The generation unit 130 can also receive image size and scene information (i.e., the start time and end time of the virtual start point video) as content generation information. When the content generation information is input, the generation unit 130 generates the virtual viewpoint video according to the capture data and the content generation information. The generation unit 130 then transmits the virtual viewpoint video together with the content generation information to the content management unit 140.

[0052] The information specifying the virtual viewpoint may be information on the trajectory of the virtual viewpoint over time (hereinafter referred to as a virtual camera path). The creator can input such information by operating the virtual viewpoint using a controller (not shown). For example, when the creator operates the virtual viewpoint, the generation unit 130 can transmit a virtual viewpoint video from this virtual viewpoint to the display device 6. The creator can specify a virtual camera path while viewing the virtual viewpoint video displayed on the display device 6. The virtual viewpoint video generated at this time may be a low-resolution video for virtual viewpoint operation. This configuration is expected to reduce the processing time and delay for specifying a virtual camera path. In this way, when the creator specifies a virtual camera path, the generation unit 130 generates a virtual viewpoint video according to the specified virtual camera path. This virtual viewpoint video is a virtual viewpoint video for final output and can have a higher resolution than the video for virtual viewpoint operation.

[0053] Furthermore, when generating a shape model as digital content, the generation unit 130 receives scene information as content generation information. Then, the generation unit 130 generates a shape model of the subject between the start time and the end time. At this time, the creator may select a method for generating the shape model. If the selected method can generate shape information with higher accuracy than the method for generating the 3D shape information stored in the storage device 4, the generation unit 130 can regenerate the 3D shape information. Then, the generation unit 130 can generate a shape model based on the regenerated 3D shape information.

[0054] Examples of methods for generating point cloud models that represent three-dimensional shapes include VisualHull and PhotoHull. When VisualHull is used, concave areas of the subject cannot be represented, resulting in large shape errors. On the other hand, when PhotoHull is used, shape errors are smaller. Furthermore, shape errors can be further reduced by using a method that uses acquired depth values. Therefore, as will be described later, the value of digital content can be set according to the selected shape generation method.

[0055] Furthermore, when generating a point cloud model representing a three-dimensional shape, the spacing between the points can be set. The narrower the spacing between the points, the higher the accuracy of the generated model. Furthermore, when generating a mesh model representing a three-dimensional shape, the number of triangular or quadrilateral patches that make up the mesh can be set. The greater the number of patches, the more accurately the shape of the subject can be approximated. Furthermore, when generating a mesh model, the resolution of the texture applied to the mesh can be set.

[0056] When multiple objects exist in a scene, the generation unit 130 can separate the 3D shape information for each object. The generation unit 130 can also assign a model ID to the shape model for each object. Adjacent points or patches can be considered to represent one model. The generation unit 130 can separate the 3D shape information into shape models for each object by scanning all points or patches according to such criteria.

[0057] As described above, when generating a point cloud model, the content generation information can include the model generation method and the point cloud spacing. When generating a mesh model, the content generation information can include the number of meshes, texture resolution, and model generation method. The generation unit 130 then transmits the shape model together with the content generation information to the content management unit 140.

[0058] When generating a skeletal model as digital content, the generation unit 130 receives scene information as content generation information. Then, the generation unit 130 generates the skeletal model using skeletal information from the start time to the end time stored in the storage device 4. If there are multiple subjects in the scene, the generation unit 130 can generate a skeletal model for each subject. Furthermore, the generation unit 130 can assign a model ID to the skeletal model for each subject.

[0059] The fewer the number of joints representing the skeleton, the shorter the time required to generate a skeletal model. On the other hand, the more joints the skeletal model can express, the more detailed movements it can represent. For example, increasing the number of joints allows for movements closer to those of a human, as well as movements of finer parts such as the fingers. Therefore, when generating a skeletal model, the content generation information can include the number of joints. For example, if the number of joints is 20 or less, the generation unit 130 can generate a basic skeletal model represented only by the joints of large bones, such as the hip bone, spine 1, spine 2, neck, throat, head, shoulders, elbows, wrists, groin, knees, ankles, and toes. On the other hand, the generation unit 130 can generate a more detailed skeletal model with a larger number of joints. In this case, the number of joints in the hands and feet can be increased. The generation unit 130 then transmits the skeletal model along with the content generation information to the content management unit 140.

[0060] As described above, the generation unit 130 can generate various digital content. Furthermore, the generation unit 130 can associate a capture data ID, which identifies the capture data used to generate the digital content, with the digital content as creator information. By referencing such creator information, the capture data stored in the storage device 4 can be tracked.

[0061] In S320, the static information setting unit 120 sets static information for the digital content stored in the storage device 4. The static information setting unit 120 may set static information for the digital content generated based on the capture data based on the static information of the capture data. Such static information for the capture data may be set in advance. For example, the static information for the capture data may be manually set by the creator of the capture data, such as the photographer of the captured image used to generate the capture data. For example, when setting static information based on the rarity of a scene represented by the capture data, the user can select the rarity from a list including "low (or rare)," "medium," and "high (or common)." On the other hand, the scale of a tournament corresponding to the capture data may be set as static information. In this case, the user can set the scale of the tournament from a list including "international tournament" and "domestic tournament." Similarly, the stage of a match corresponding to the capture data may be set as static information. In this case, the user can set the stage from a list including "final," "semi-final," or other stages.

[0062] Such lists can be set in advance. Value information corresponding to the items included in each list can also be registered in advance. For example, a user can register "tournament scale" as a type of static information. Furthermore, "international tournament" and "domestic tournament" can be registered as specific items of tournament scale. The user can then register value information corresponding to each item. Similarly, each stage and the value information corresponding to each stage can also be registered in advance.

[0063] On the other hand, the static information setting unit 120 may set static information different from the static information of the capture data as the static information of the digital content. For example, when creating digital content, the user may input static information of the digital content. For example, the user may add static information indicating the rarity of a scene depicted in the digital content. The user may also input static information indicating that the digital content depicts a goal scene or a home run scene that decides the game. The static information setting unit 120 may set the static information thus input by the user as the static information of the digital content.

[0064] The content management unit 140 registers the digital content generated by the generation unit 130 as described above. The content management unit 140 also registers static information about the digital content. As described above, the static information may include static information set by the static information setting unit 120 and content generation information set by the generation unit 130. The content management unit 140 can assign a content ID to the digital content received from the generation unit 130. The digital content is managed in the content management unit 140 using the content ID. The content management unit 140 can also record a capture data ID, a scene ID, and static information, each associated with digital content data. By referencing such capture data ID and scene ID, it is possible to track that the digital content was created from specific scene data of specific capture data managed in the storage device 4. Furthermore, the content management unit 140 can manage the latest dynamic information about the digital content determined by the dynamic information calculation unit 160, as described below.

[0065] In S330, the NFT granting unit 150 requests the blockchain system 5 to grant an NFT to digital content managed by the content management unit 140. After the generation unit 130 generates the digital content, the NFT granting unit 150 can accept user input indicating whether or not to grant an NFT to the digital content. Furthermore, when granting an NFT, the NFT granting unit 150 can set the number of NFTs. The NFT granting unit 150 can set the number of NFTs based on the user input.

[0066] When it is decided to assign an NFT, the blockchain system 5 issues a set number of NFTs in accordance with the request of the NFT assigner 150. For example, if a creator wants to sell 1,000 shape models, the blockchain system 5 issues an NFT with an ID between 0 and 999. When different types of data, such as a combination of a shape model and a skeletal model, are registered as a single piece of content, the blockchain system 5 can assign an NFT to each piece of data.

[0067] NFTs can be managed using a blockchain, as shown in Figure 4. Figure 4 shows the first block 400 and the latest block 401. Each block contains a hash value 410 of the previous block, a nonce value 420, data information 430, and a transaction 440. The nonce value 420 is used once to generate a block. The data information 430 contains an IP address for identifying the database and a content ID for identifying the digital content data. This configuration prevents the registration of huge amounts of data on the blockchain. The transaction 440 contains user information, such as a user ID, indicating the current owner of the content as a content transaction. Furthermore, a description of a smart contract (execution of an automated contract with a digital content purchaser) may be registered on the blockchain. For example, by including the creator's user ID and whether or not the right of resale is exercised in the smart contract, the creator can earn revenue each time the digital content is sold. Furthermore, by including a usage expiration date for the content data in the smart contract, the purchaser's ownership can be invalidated after the expiration date. Digital content to which an NFT has been assigned as described above is managed by the content management unit 140 in a state in which ownership can be proven.

[0068] In S340, the dynamic information calculation unit 160 determines a dynamic rating of the digital content. This dynamic rating is information that changes over time. Hereinafter, information indicating the dynamic rating will be referred to as dynamic information. The dynamic information is used to estimate the value of the digital content (or the value of the scene represented by the digital content). To calculate such dynamic information, the dynamic information calculation unit 160 acquires information about the digital content from the content management unit 140. The dynamic information calculation unit 160 can then calculate the dynamic information as follows. The dynamic information calculation unit 160 may calculate the dynamic information according to the type of content. The dynamic information calculation unit 160 may periodically perform a calculation process for the dynamic information. The dynamic information is updated each time the calculation process is performed. In one embodiment, the dynamic information is set independently of the content. Note that the dynamic information calculation unit 160 can perform a dynamic rating based on the sales status or the number of digital contents, etc., according to the digital contents or their transaction history managed by the content management unit 140. On the other hand, the dynamic information calculation unit 160 may perform such a dynamic rating taking into account the digital contents or their transaction history managed by another device.

[0069] The dynamic information calculation unit 160 can calculate the dynamic information according to the sales status of the digital content. Furthermore, the dynamic information calculation unit 160 can calculate the dynamic information according to the transaction history of the digital content. For example, the dynamic information calculation unit 160 can determine the dynamic rating according to the number of times the digital content has been bought and sold. More specifically, the dynamic information calculation unit 160 can determine the dynamic rating according to the number of times the digital content put on sale by the information processing system has been sold. This number of sales may be the number of times the digital content has been sold from the creator to the trader. On the other hand, in the following example, the dynamic information calculation unit 160 does not calculate the dynamic information according to information related to the amount. For example, the dynamic information calculation unit 160 does not calculate the dynamic information according to the buying and selling price of the digital content.

[0070] As a specific example, the dynamic information calculation unit 160 can calculate dynamic information according to the ratio (sales rate) between the number of NFTs offered for sale by the information processing system and the number actually sold. For example, if 1,000 NFTs attached to digital content are offered for sale and 100 of them are actually sold, the sales rate is 0.1. The sales rate is maximized when the NFTs are sold out. The higher the sales rate, the higher the dynamic evaluation the dynamic information calculation unit 160 can set.

[0071] Furthermore, the dynamic information calculation unit 160 can calculate dynamic information according to the number of NFTs sold per hour that are put up for sale by the information processing system. As a specific example, if 1,000 NFTs are put up for sale and it takes 100 days for them to sell out, the number of sales per hour is 1,000 / 100 days = 10 / day. Also, if 10 pieces of content are put up for sale and it takes 100 days for them to sell out, the number of sales per hour is 10 / 100 days = 0.1 / day. The dynamic information calculation unit 160 can set a higher dynamic evaluation the more NFTs are sold per hour.

[0072] Furthermore, the dynamic information calculation unit 160 can calculate dynamic information according to the number of days it took for the NFTs put up for sale by the information processing system to sell out (number of days to sell out). The shorter the number of days to sell out, the higher the dynamic evaluation the dynamic information calculation unit 160 can set. In particular, for multiple digital contents of the same type and with the same number of NFTs attached, the dynamic information calculation unit 160 can set a higher dynamic evaluation for digital content that sold out faster.

[0073] Furthermore, the dynamic information calculation unit 160 can calculate dynamic information according to the number of times an NFT has been bought and sold between users (number of times of buying and selling). One buying and selling corresponds to another user purchasing an NFT that a user has put up for sale, and ownership of the digital content to which the NFT is attached being transferred. The number of times of buying and selling is the number of times such buying and selling has taken place. The dynamic information calculation unit 160 can set a higher dynamic evaluation as the number of times an NFT has been bought and sold between users increases. After the initial 1,000 NFTs put up for sale are sold out, the dynamic information calculation unit 160 can set a higher dynamic evaluation for the digital content as the number of times of buying and selling increases.

[0074] The method of calculating the dynamic information of digital content by the dynamic information calculation unit 160 is not limited to the method based on the transaction history as described above. For example, the dynamic information calculation unit 160 may calculate the dynamic information based on information about a subject shown in the digital content. The information about the subject may be an evaluation of the subject. For example, the information about the subject may be the popularity of the subject. Furthermore, if the subject is a player, the information about the subject may be the player's record. In this way, the information about the subject may change daily. It is possible to set the popularity of a notable player in a scene shown in the digital content.

[0075] The popularity of a subject can be represented by the number of digital content pieces created for the subject. For example, the popularity of a player can be set according to the number of digital content pieces representing the player. For a player for whom a popularity level is being set for the first time, the photographer of the captured image may set an initial popularity value in advance. Alternatively, for a player for whom a popularity level is being set for the first time, the average popularity level for all players may be set as the initial value. The dynamic information calculation unit 160 then counts the number of digital content pieces representing the player that have been created for each player. The counted number of digital content pieces can be used as the player's popularity. To count the number of digital content pieces, a creator can link player information to the digital content pieces when creating the digital content pieces. A counting period for the number of content pieces may be set. For example, the counting period may be one week. The dynamic information calculation unit 160 can count the number of digital content pieces representing the player that have been created within this counting period for each player. This method makes it possible to determine whether a player's popularity is increasing or decreasing.

[0076] The dynamic information calculation unit 160 may also calculate dynamic information based on an evaluation of the capture data used to generate the digital content. The evaluation of the capture data may be an evaluation that changes over time. For example, the capture data may be evaluated according to the number of digital content items generated based on the capture data. The capture data may also be evaluated according to the sales status of the digital content items generated based on the capture data. The capture data may also be evaluated according to the number of traders who own the digital content items generated based on the capture data. A large number of digital content items generated based on the capture data or good sales status indicates a high evaluation of the capture data. With this configuration, the sales or ownership status of other digital content items generated using the same capture data can be reflected in the value of the digital content.

[0077] Furthermore, the dynamic information calculation unit 160 may calculate the dynamic information according to an evaluation of the creator, i.e., the creator, of the digital content. The creator can be evaluated, for example, by the creator's popularity. In this embodiment, the popularity can be indicated by the evaluation of each creator by traders. As another example, the popularity can be indicated by the total playback time of the digital content created by the creator.

[0078] In S350, the value estimation unit 170 estimates the value of the digital content. The value estimation unit 170 can estimate the value of the digital content based on both the static rating and the dynamic rating. To this end, the value estimation unit 170 can acquire static information and dynamic information of the content from the content management unit 140. As described above, the static information of the content can include content generation information. The value estimation unit 170 can estimate a value based on the static information and a value based on the dynamic information. Then, the value estimation unit 170 can estimate the final value of the digital content based on each of the values. The value estimation unit 170 can transmit information on the estimated value of the digital content to the content management unit 140.

[0079] First, a method for the value estimation unit 170 to estimate value based on the static information set by the static information setting unit 120 will be described. When rarity is set as static information, the value estimation unit 170 can set a value according to the rarity. For example, when the rarity is low (= rare), the value estimation unit 170 can set the value to 1.0. Also, when the rarity is high (= not rare), the value estimation unit 170 can set the value to 0.0. In this example, a large numerical value representing the value means a large value.

[0080] Furthermore, when the tournament scale is set as static information, the value estimation unit 170 can set a value according to the tournament scale. For example, when the tournament scale is an "international tournament," the value estimation unit 170 can set the value to 1.0. When the tournament scale is a "domestic tournament," the value estimation unit 170 can set the value to 0.1.

[0081] Furthermore, when the stage of a game is set as static information, the value estimating unit 170 can set a value according to the stage. For example, when the stage is the final, the semi-final, or other stage, the value estimating unit 170 can set 1.0, 0.5, and 0.1 as the respective values. Furthermore, when scene information is set as static information, the value estimating unit 170 can set a value according to the scene. For example, the value estimating unit 170 can set a value according to the importance of the scene to the outcome of the game. Specifically, when the scene information indicates a normal home run scene or goal scene, the value estimating unit 170 can set 0.5 as the value. Furthermore, when the scene information indicates a decisive home run scene or goal scene that will determine the game, the value estimating unit 170 can set 1.0 as the value.

[0082] Next, a method for the value estimation unit 170 to estimate a value based on content generation information will be described. When the type of digital content is a real camera image or a virtual viewpoint image, the value estimation unit 170 may set a value according to the resolution or frame rate. For example, if the resolution of the image is greater than 4K, the value may be 1.0. Also, if the resolution is greater than or equal to 2K and less than 4K, the value may be 0.5. Also, if the resolution is less than 2K, the value may be 0.1. The number of resolution classifications may increase according to the resolution of the input image. Similarly, if the frame rate of the image is 60 fps or greater, the value may be 1.0. Also, if the frame rate is 30 fps, the value may be 0.5. Also, if the frame rate is less than 30 fps, the value may be 0.1.

[0083] If the type of digital content is a shape model, the value estimation unit 170 may set the value according to the generation method or accuracy of the shape model. For example, if the shape model is generated using VisualHull, the value may be 0.1. If the shape model is generated using PhotoHull, the value may be 0.5. If the shape model is generated using depth values, the value may be 1.0. If the spacing between points in a point cloud model is narrowest, the value may be 1.0. If the spacing between points is wider, a smaller value is set. For example, the set value may decrease linearly as the spacing between points increases. If the shape model is a mesh model, the value may be set according to the number of triangular or quadrilateral patches that make up the mesh. For example, if the number of patches used to represent the shape of a single subject exceeds a certain number, the value may be 0.5. If the texture resolution is higher than a certain value, the value may be 1.0.

[0084] If the type of digital content is a skeleton model, the value estimator 170 may set a value according to the number of joints. For example, if the number of joints is 20 or less, the value may be 0.1. If the number of joints is greater than 20, the value may be 1.0.

[0085] When multiple indices are set as static information (including content generation information), the value estimation unit 170 can calculate statistical values ​​of values ​​according to each type of static information. For example, the value estimation unit 170 can calculate the maximum value, average value, or weighted average value of the values ​​based on each indices as the value estimated based on the static information.

[0086] Finally, a method for estimating value based on dynamic information by the value estimation unit 170 will be described. The value estimation unit 170 can estimate value according to dynamic information such as sales rate, number of days until sold out, number of purchases and sales, popularity of players, and popularity of creators who created digital content.

[0087] For example, if a sales rate is set as dynamic information, the sales rate can be used as a value. In other words, the sales rate can be considered to represent the value of the digital content. For example, if the sales rate is 0.1, the value can be 0.1. If the digital content is sold out, the value can be the maximum of 1.0.

[0088] When the number of days to sell out is set as dynamic information, the value estimation unit 170 can obtain the average number of days to sell out for digital content of the same type for which the same number of NFTs have been sold. The value estimation unit 170 can compare this average number of days with the number of days to sell out the digital content. For example, if the number of days to sell out is shorter than the average number of days, the value may be 1.0. Also, if the number of days to sell out is longer than the average number of days, the value may be 0.0. If the digital content is not sold out, the value may be 0.0.

[0089] If the number of trades is set as dynamic information, the value estimation unit 170 can count the maximum number of trades for the same type of digital content. Then, the value estimation unit 170 can set a value based on a comparison between the number of trades and the maximum number of trades. For example, if the maximum number of trades is 100 and the digital content has been traded 20 times, the value can be 0.2. Every time the maximum number of trades is updated, the value estimation unit 170 can reset the value for all digital content.

[0090] When player popularity is set as dynamic information, the value estimation unit 170 can set a value by calculating the maximum popularity for all players and calculating each player's popularity relative to the maximum popularity. In this embodiment, popularity is indicated by the number of digital content items created for each player. A value proportional to the number of digital content items for each player can be set. Therefore, the value estimation unit 170 obtains the maximum number of digital content items for each player. Then, the value estimation unit 170 calculates the ratio of the number of digital content items for each player to the obtained maximum value. The value of digital content representing the player with the highest popularity can be set to 1.0. The calculated ratio can also be used as the value of digital content items representing other players. By setting a period for calculating popularity, it is possible to set a value according to popularity over, for example, a week, month, or year.

[0091] When the popularity of a creator is set as dynamic information, the value estimation unit 170 calculates the maximum popularity for all creators and calculates the popularity of each creator relative to the maximum popularity, thereby setting a value. The value estimation unit 170 calculates the ratio of the popularity of each creator relative to the obtained maximum popularity. The calculated ratio can then be used as the value of the digital content created by the creator.

[0092] When multiple indicators are set as dynamic information, the value estimation unit 170 can calculate statistical values ​​of values ​​according to each type of dynamic information. For example, the value estimation unit 170 can calculate the maximum value, average value, or weighted average value of the values ​​based on each indicator as the value estimated based on the dynamic information.

[0093] As described above, the value estimation unit 170 can estimate the value of digital content based on both static information and dynamic information. The value estimation unit 170 may separately manage the value of content estimated based on static information and the value of content estimated based on dynamic information. Furthermore, the value estimation unit 170 may separately manage the value of content estimated based on static information set by the static information setting unit 120 and the value of content estimated based on content generation information set by the generation unit 130. On the other hand, the value estimation unit 170 may calculate the maximum value, average value, weighted average value, or total value of the content values ​​estimated based on each piece of information as the value of the content.

[0094] As a specific example, a case will be described in which the static information indicates the scale of the tournament and the dynamic information indicates the sales rate. In this example, the tournament scale of the first digital content is a domestic tournament, and therefore the value based on the static information is 0.1. Furthermore, the sales rate of the first digital content is 0.5, and therefore the value based on the dynamic information is 0.5. In this case, the value estimation unit 170 can calculate the average value of these values, 0.3, as the value of the first digital content. Similarly, if the sales rate of the second digital content is 0.9, the value estimation unit 170 can calculate the value of the second digital content as 0.5. The value estimation unit 170 can present the estimated value to the trader via the display device 6.

[0095] A trader selling digital content can determine the selling price of the digital content by referring to the value estimated by the value estimation unit 170. For example, the trader can set the selling price of the second digital content higher than the selling price of the first digital content. The trader may instruct the content management unit 140 via the display device 6 to perform a process to sell the digital content so that it can be purchased at a specific selling price.

[0096] Furthermore, a trader who purchases digital content can refer to the value estimated by the value estimator 170 to decide whether or not to purchase the digital content. Furthermore, a trader who purchases digital content can refer to the value estimated by the value estimator 170 to determine whether the selling price offered by a trader selling the digital content is high or low. The trader may instruct the content management unit 140 and the NFT granter 150 via the display device 6 to perform a process of purchasing the digital content at a specific selling price, i.e., a process of changing the owner of the digital content.

[0097] On the other hand, the value estimation unit 170 may determine the selling price of the digital content based on the estimated value. For example, the value estimation unit 170 may determine the selling price of the digital content based on a base price determined according to the type of digital content and the value of the digital content. In one example, the first and second digital content are shape models of players in a baseball game. In this example, the base price of the shape model of a player in a baseball game is 1,000 yen. In this case, the value estimation unit 170 may set the selling price of the first digital content to 1,000 x 0.3 = 300 yen. In addition, the value estimation unit 170 may set the selling price of the second digital content to 1,000 x 0.5 = 500 yen. The content management unit 140 may perform a process in which a trader buys and sells digital content at the selling price determined in this manner. Note that such a base price may be set as static information of the digital content. In this case, the static information setting unit 120 may set such a base price according to input by the creator of the digital content.

[0098] The information processing device 1 can generate digital content and estimate the value of the generated digital content as described above according to the flowchart shown in FIG. 3 . However, the information processing device 1 may also estimate the value of digital content that has already been generated. In this case, the information processing device 1 can set static information for the already generated digital content as in S320, set dynamic information as in S340, and estimate the value as in S350. For example, when a trader logs in at S300, the information processing device 1 can perform a process to re-estimate the value of the digital content owned by the trader. In this case, the static information setting unit 120 may obtain static information previously set for the digital content. On the other hand, since the dynamic information may change, the dynamic information calculation unit 160 can re-calculate the dynamic information of the digital content. With this configuration, the information processing device 1 can periodically present updated values ​​to the owners of the digital content.

[0099] An information processing system according to an embodiment may control the display of digital content depending on whether the trader owns the digital content. For example, the content management unit 140 may provide the display device 6 with digital content owned by the trader for display. For example, the content management unit 140 may transmit a virtual viewpoint image to which a texture representing an object has been added to the display device 6. On the other hand, the content management unit 140 may transmit digital content not owned by the trader so that it is displayed at a lower quality. For example, the content management unit 140 may transmit an image to the display device 6 in which a wireframe representing the shape of the object is displayed. The content management unit 140 may also reduce the quality of the digital content by applying degradation processing such as blurring or binarization to the digital content. The content management unit 140 may transmit the digital content after such quality reduction processing to the display device 6. Displaying digital content not owned by the trader in this manner helps the trader decide whether to purchase the digital content.

[0100] At this time, the content management unit 140 may present to the trader information indicating the value of the digital content estimated by the value estimation unit 170. For example, the display device 6 can display information indicating the value of digital content that is displayed at a low quality and that the trader does not own. By referring to this information, the trader can decide whether to purchase the digital content.

[0101] For example, a trader owns a shape model of a pitcher in a particular scene. In this case, the content management unit 140 can transmit a high-quality image of the pitcher in this scene to the display device 6. On the other hand, the trader does not own a shape model of a batter in this scene. In this case, the content management unit 140 can transmit a low-quality image of the batter in this scene to the display device 6. With this configuration, the trader can know that there is digital content in the same scene that the trader does not yet own. Furthermore, the trader does not own a shape model of a pitcher in a subsequent scene. In this case, the content management unit 140 can transmit a low-quality image of the pitcher in the subsequent scene to the display device 6. With this configuration, the trader can know that there is digital content in the subsequent scene that the trader does not yet own.

[0102] Note that the types of static information and dynamic information are not limited to those listed in this specification. Furthermore, the types of information listed as examples of static information may be updated over time, in which case this type of information can be used as dynamic information. Conversely, the types of information listed as examples of dynamic information may be unchanging, in which case this type of information can be used as static information. For example, the popularity of a subject may be a fixed value, in which case the popularity of the subject can be used as static information. Furthermore, the popularity of a subject may be updated according to the number of digital contents, as described above, in which case the popularity of the subject can be used as dynamic information.

[0103] According to the above embodiment, the information processing device 1 can estimate the value of digital content. When buying or selling digital content, a trader can refer to the estimated value of the digital content to decide whether to trade or set a price.

[0104] (Value assessment taking into account the content collection status) Multiple digital contents generated from a specific scene can be associated with each other. Below, a method for estimating the value of digital contents by taking into account the collection status of the associated digital contents will be described. In this specification, a group of digital contents associated with each other is called a collection. In other words, multiple digital contents that make up a collection are defined. The collection status indicates the ownership status of the digital contents that make up the collection by a user.

[0105] In this embodiment, in addition to the capture data ID and the scene ID, the digital content generated by the generation unit 130 is assigned information for identifying other digital content associated with each other. For example, collection information can be assigned to the digital content. The collection information includes a collection ID assigned to the digital content to identify the digital content included in a collection designated by the creator. The collection information also includes a collection list. The collection list is a list of collection IDs of digital content included in the same collection. Based on such collection information, the collection level of the digital content owned by the trader can be calculated.

[0106] In this embodiment, the content management unit 140 can manage collection information in addition to digital content and static information. Furthermore, when registering new digital content in the blockchain, the NFT granting unit 150 can describe the collection information in the blockchain data information. The value estimation unit 170 estimates the value of the digital content based on the static information and dynamic information. The collection status of the digital content is information that changes over time and is included in the dynamic information. That is, in this embodiment, the value estimation unit 170 determines a dynamic evaluation of the digital content owned by the user based on the user's ownership status of the digital content that makes up the collection.

[0107] Even in such an embodiment, the information processing device 1 can estimate the value of digital content to which an NFT has been assigned, according to the flowchart shown in Fig. 3. The processes of S300, S320, and S340 can be performed as already described. The processes of S310, S330, and S350 will be described below.

[0108] In S310, the generation unit 130 generates digital content using the capture data stored in the storage device 4, as already described. A capture data ID and a scene ID are also assigned to the digital content. These processes can be performed as already described. In this embodiment, the generation unit 130 also assigns collection information to the digital content. A method for assigning collection information to digital content will be described below with reference to a baseball scene in which a pitcher and a batter face off, as an example.

[0109] When generating real camera footage of this scene, the generation unit 130 sets the camera ID of the real camera. The generation unit 130 can automatically set the camera ID of the camera capturing a specific subject (e.g., the pitcher). For example, the information processing device 1 can recognize the camera capturing the pitcher from the image. Then, the generation unit 130 can select a camera capturing the pitcher at high resolution from among these cameras. The process of recognizing the subject from the image can be achieved by facial recognition, uniform recognition, or pitching motion recognition based on skeletal information. Alternatively, the creator may select an arbitrary camera while viewing the footage from each camera and input the camera ID of the selected camera into the system. Similarly, the camera ID of the camera capturing the batter can also be set. Based on these camera IDs, the generation unit 130 can generate real camera footage of the pitcher and batter as described above.

[0110] Furthermore, the generation unit 130 assigns collection ID 0 to the generated real camera footage of the pitcher. The generation unit 130 also assigns collection ID 1 to the real camera footage of the batter. The generation unit 130 also enters collection ID 0 and collection ID 1 in the collection list. In this way, the collection list includes collection IDs for all digital content that makes up the collection. By assigning this information, an owner who only has digital content with collection ID 0 can know that they do not have digital content with collection ID 1. Furthermore, by referring to this information, the information processing system can present to the trader any digital content that is missing to complete the collection.

[0111] When one collection includes multiple digital content items, the generation unit 130 may set a value weight for each piece of digital content. For example, the creator may determine the weights based on the popularity of each pitcher and batter. Alternatively, the generation unit 130 may set the weights based on the popularity of the players described above. Here, the generation unit 130 may set a weight for each piece of digital content item included in one collection so that the sum of the weights is 1.0. Alternatively, a weight may be set for each of multiple collections. The generation unit 130 may transmit the assigned collection information to the content management unit 140 in addition to the real camera footage and content generation information.

[0112] When generating a virtual viewpoint video of this scene, the generation unit 130 receives information specifying a virtual viewpoint as already described, and generates a virtual viewpoint video according to the virtual viewpoint. Here, the generation unit 130 may generate multiple virtual camera paths. For example, the generation unit 130 can use virtual camera paths indicating the pitcher's viewpoint and the batter's viewpoint to generate virtual viewpoint video according to each viewpoint. In this case, the generation unit 130 can assign collection ID 0 to the virtual camera path and virtual viewpoint video according to the pitcher's viewpoint. Furthermore, the generation unit 130 can assign collection ID 1 to the virtual camera path and virtual viewpoint video according to the batter's viewpoint. Then, the generation unit 130 enters the collection ID of each virtual viewpoint video in a collection list.

[0113] In this way, when a collection of virtual viewpoint images includes multiple virtual viewpoint images, the generation unit 130 can assign a value weight to each virtual viewpoint image. For example, when each virtual viewpoint image is a virtual viewpoint image from a fixed viewpoint, the generation unit 130 may assign the same weight to each virtual viewpoint image. Furthermore, the generation unit 130 may assign a larger weight to a virtual viewpoint image that follows a dynamic virtual camera path set according to a scene. The generation unit 130 can assign this collection information to the virtual viewpoint image. The generation unit 130 can transmit the assigned collection information to the content management unit 140 in addition to the virtual viewpoint image and content generation information.

[0114] When generating a shape model for this scene, the generation unit 130 acquires, from the storage device 4, three-dimensional shape information corresponding to the scene ID set by the creator. As already described, the generation unit 130 may regenerate the three-dimensional shape information. Then, the generation unit 130 generates a shape model as described above. As described above, the generation unit 130 separates the three-dimensional shape information for each object, thereby generating a shape model for each object assigned a model ID. Because this scene includes a pitcher and a batter, the generation unit 130 can acquire a shape model corresponding to the model ID selected by the creator.

[0115] Furthermore, the generation unit 130 can assign collection information to the shape model. For example, the collection ID assigned to the shape model of a pitcher may be 0. The collection ID assigned to the shape model of a batter may be 1. Then, the generation unit 130 writes the collection ID 0 and the collection ID 1 in the collection list.

[0116] When the collection of shape models includes multiple shape models, the generation unit 130 can set a value weight for each shape model. The generation unit 130 may set the same weight for the shape model of the pitcher and the shape model of the batter. The collection of shape models may also include a shape model of a ball. In this case, the generation unit 130 may assign a lower weight to the shape model of the ball than to the shape models of the players. The generation unit 130 can transmit the assigned collection information to the content management unit 140 in addition to the shape models and content generation information.

[0117] When creating a skeleton model for this scene, the generation unit 130 creates the skeleton model using the skeleton information as already described. Because this scene includes a pitcher and a batter, the generation unit 130 can obtain a skeleton model corresponding to the model ID selected by the creator.

[0118] Furthermore, the generation unit 130 can assign collection information to the skeletal model. For example, the collection ID assigned to the skeletal model of a pitcher may be 0. The collection ID assigned to the skeletal model of a batter may be 1. Then, the generation unit 130 writes collection ID 0 and collection ID 1 in the collection list.

[0119] If the skeleton model collection includes multiple skeleton models, the generator 130 can assign a value weight to each skeleton model. The generator 130 can transmit the assigned collection information to the content manager 140 in addition to the skeleton models and content generation information.

[0120] The content management unit 140 can record such collection information in addition to the capture data ID, scene ID, and static information in association with each piece of digital content data.

[0121] Note that a single collection may include different types of digital content, such as a shape model and a skeletal model. For example, a single piece of digital content may include a shape model of a pitcher and a skeletal model of the pitcher. The generation unit 130 may assign collection ID0 and ID1 to the shape model and skeletal model of the pitcher, respectively. Furthermore, the content list includes collection ID0 and collection ID1. In this case, an NFT may be assigned to each piece of digital content.

[0122] In S330, as already explained, the NFT granting unit 150 requests the blockchain system 5 to grant NFTs to the digital content managed by the content management unit 140. When a collection includes multiple digital contents, as in this embodiment, an NFT can be granted to each digital content. The number of NFTs granted to each digital content included in a collection may be the same or different. For example, 1,000 NFTs may be issued for digital content with collection ID 0, and 2,000 NFTs may be issued for digital content with collection ID 1. In this way, by changing the number of NFTs, the rarity of each digital content can be changed.

[0123] If a collection contains two digital contents, a process for presenting the other collection ID may be written in a smart contract registered on the blockchain, so that when a trader purchases one digital content, the existence of the other digital content included in the same collection can be presented and the trader can be prompted to purchase such digital content.

[0124] In S350, the value estimation unit 170 estimates the value of the digital content based on both the static evaluation and the dynamic evaluation. In this embodiment, the value estimation unit 170 can estimate the value of the digital content using collection information. In particular, the value estimation unit 170 can estimate the value of the digital content based on the collection status of the digital content. To this end, the value estimation unit 170 can obtain the collection information from the content management unit 140. Meanwhile, the value estimation unit 170 may also use the value estimation methods already described.

[0125] A method for estimating value using collection information will be described below. In the following example, the value estimation unit 170 estimates the value of a collection that includes multiple digital content items. After a creator creates digital content items and the blockchain system 5 assigns an NFT to the digital content items, the value estimation unit 170 initializes the value of the collection. First, the value estimation unit 170 determines the number of digital content items included in the collection by referring to the collection list. Then, the value of the collection is set based on the weight of the value of each digital content item.

[0126] When a trader purchases digital content, the value estimation unit 170 obtains the collection IDs of other digital content included in the collection based on the collection list. If the trader does not own the digital content corresponding to this collection ID, the value estimation unit 170 can present the trader with information on the missing digital content.

[0127] When a trader owns some of the digital contents included in a collection, the value of each digital content can be set according to its weight. In this case, the value of the group of digital contents can be set according to the degree of collection. The value estimation unit 170 can set the value so that the higher the degree of collection, the higher the value. When a trader owns all of the digital contents included in a collection, the value may be 1.0. Alternatively, the value of the group of digital contents may be the sum of the weights of the values ​​of the individual digital contents.

[0128] When all digital content is collected, the trader can specify whether to keep the individual digital content as is or combine them into a single digital content. When combining them, the trader can continue to own the individual digital content. On the other hand, the content management unit 140 can manage the combined digital content as a new digital content. When a trader or creator sells a collection containing multiple digital content, the value is set to 1.0. When multiple digital content items are sold individually, a new value weight is set for each digital content item.

[0129] As described above, the value estimator 170 can set a value based on the collection status for a collection that includes multiple digital content items. Alternatively, the value estimator 170 may set an estimated value for the collection for each digital content item included in the collection.

[0130] The value estimation unit 170 may separately manage the value estimated based on the collection status of the collection and the value estimated by other methods such as those described above. Furthermore, the value estimation unit 170 may calculate the maximum value, average value, weighted average value, or total value of these values ​​as the value.

[0131] As a specific example, a case will be described in which a collection includes a pitcher shape model and a batter shape model. In this example, a value weight of 0.6 is set for the pitcher shape model. Furthermore, a value weight of 0.3 is set for the batter shape model. In this case, if a trader owns only the pitcher shape model, the value based on the collection status of the owned shape model is 0.6. Furthermore, if the trader owns only the batter shape model, the value based on the collection status of the owned shape model is 0.3. Furthermore, if the trader owns both shape models, the value based on the collection status of the owned shape model is 1.0. In this way, the greater the number of digital contents that a trader owns among the multiple digital contents that make up a collection, the greater the value estimated based on the collection status of the collection.

[0132] In this specific example, the value based on static information for the pitcher shape model and the batter shape model is 0.1. Furthermore, the sales rate of the pitcher shape model is 0.9, and the sales rate of the batter shape model is 0.5. When the collection rate is taken into account, if a trader owns only the pitcher shape model, the value of the owned shape model is (0.1 + 0.9 + 0.6) / 3 = approximately 0.53. If a trader owns only the batter shape model, the value of the owned shape model is (0.1 + 0.5 + 0.3) / 3 = 0.3. If a trader owns only both shape models, the value of the pitcher shape model is (0.1 + 0.9 + 1.0) / 3 = approximately 0.67. The value of the batter shape model is (0.1 + 0.5 + 1.0) / 3 = approximately 0.53. If a trader owns a larger number of digital contents among the plurality of digital contents that make up the collection, the value estimated based on the collection status of the collection will be larger.

[0133] As described above, an information processing system according to an embodiment may control the display of digital content depending on whether the trader owns the digital content. For example, the content management unit 140 may provide the display device 6 with digital content owned by the trader from among the digital content constituting a collection for display. Furthermore, the content management unit 140 may transmit digital content not owned by the trader from among the digital content constituting a collection to the display device 6 so that the digital content is displayed at a lower quality. In this case, the content management unit 140 may present the trader with information indicating the value of each digital content estimated by the value estimation unit 170. Furthermore, the content management unit 140 may present the trader with information indicating the value of a group of digital content or information indicating the value of each digital content when the trader purchases digital content that the trader does not own. This configuration allows the trader to know the increase in value of the digital content by owning the digital content constituting the collection. The trader can refer to this information to determine whether to purchase the digital content.

[0134] According to this embodiment, when a trader puts digital content up for sale, the value of the digital content can be estimated taking into account the collection status.

[0135] (Other Examples) The present disclosure can also be realized by a process in which a program that realizes one or more functions of the above-described embodiments is supplied to a system or device via a network or a storage medium, and one or more processors in the computer of the system or device read and execute the program. It can also be realized by a circuit (e.g., ASIC) that realizes one or more functions.

[0136] The disclosure of this specification includes the following information processing device, information processing method, and program. (Item 1) a setting means for setting information indicating a static evaluation of the digital content, the static evaluation being an evaluation according to the content of the digital content generated based on three-dimensional shape data indicating a three-dimensional shape of a subject generated using a plurality of captured images acquired by a plurality of imaging devices; a determining means for determining a dynamic rating of the digital content, the rating being a rating that may change over time; an estimation means for estimating a value of the digital content based on both the static evaluation and the dynamic evaluation; An information processing device comprising: (Item 2) 2. The information processing device according to item 1, wherein the determining means determines the dynamic evaluation according to the sales status of the digital content. (Item 3) 3. The information processing device according to any one of items 1 to 2, wherein the determining means determines the dynamic evaluation according to information about a subject indicated in the digital content. (Item 4) 4. The information processing device according to item 3, wherein the information about the subject indicates an evaluation of the subject. (Item 5) 5. The information processing device according to any one of items 3 to 4, wherein the information about the subject indicates the number of digital contents generated for the subject. (Item 6) 6. The information processing device according to any one of items 1 to 5, wherein the determining means determines the dynamic evaluation based on an evaluation of the three-dimensional shape data that may change over time. (Item 7) 7. The information processing device according to any one of items 1 to 6, wherein the determination means determines the dynamic evaluation according to the number or sales status of digital content generated based on the three-dimensional shape data. (Item 8) 8. The information processing device according to any one of items 1 to 7, wherein the determining means determines the dynamic evaluation in accordance with an evaluation of a creator who created the digital content. (Item 9) The collection includes multiple digital contents. 9. The information processing device according to any one of items 1 to 8, wherein the determination means determines the dynamic evaluation of the digital content owned by the user based on the user's ownership status of the digital content that constitutes the collection. (Item 10) 10. The information processing device according to any one of items 1 to 9, wherein the static evaluation is set according to the type of scene represented by the digital content. (Item 11) 11. The information processing device according to any one of items 1 to 10, wherein the static evaluation is set according to the type of subject represented by the digital content. (Item 12) 12. The information processing device according to any one of items 1 to 11, wherein the static evaluation is set according to a setting of a process for generating the digital content. (Item 13) The information processing device described in any one of items 1 to 12, characterized in that the setting means sets information indicating a static evaluation of digital content generated based on the three-dimensional shape data based on information indicating a static evaluation of the three-dimensional shape data. (Item 14) 14. The information processing device according to any one of items 1 to 13, further comprising a generating unit that generates digital content in accordance with three-dimensional shape data of a subject and user instructions. (Item 15) 15. The information processing device according to any one of items 1 to 14, further comprising a management unit for managing owner information of the digital content. (Item 16) Item 16. The information processing device according to item 15, wherein the management means manages the buying and selling of the digital content between users. (Item 17) The information processing device described in any one of items 1 to 16, characterized in that the digital content is registered on a blockchain and is assigned an NFT indicating the owner. (Item 18) An information processing method performed by an information processing device, a setting step of setting information indicating a static evaluation of the digital content, the static evaluation being an evaluation according to the content of the digital content generated based on three-dimensional shape data indicating a three-dimensional shape of a subject generated using a plurality of captured images acquired by a plurality of imaging devices; a determining step of determining a dynamic rating of the digital content, the rating being a rating that may change over time; an estimation step of estimating a value of the digital content based on both the static and dynamic assessments; An information processing method comprising: (Item 19) 18. A program for causing a computer to function as the information processing device according to any one of items 1 to 17.

[0137] The invention is not limited to the above-described embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention. [Explanation of symbols]

[0138] 1: Information processing device, 100: Communication unit, 110: User information management unit, 120: Static information setting unit, 130: Generation unit, 140: Content management unit, 150: NFT assignment unit, 160: Dynamic information calculation unit, 170: Value estimation unit

Claims

1. a setting means for setting information indicating a static evaluation of the digital content, the static evaluation being an evaluation according to the content of the digital content generated based on three-dimensional shape data indicating a three-dimensional shape of a subject generated using a plurality of captured images acquired by a plurality of imaging devices; a determining means for determining a dynamic rating of the digital content, the rating being a rating that may change over time; an estimation means for estimating a value of the digital content based on both the static evaluation and the dynamic evaluation; An information processing device comprising:

2. 2. The information processing apparatus according to claim 1, wherein said determining means determines said dynamic evaluation in accordance with a sales status of said digital content.

3. The information processing apparatus according to claim 1 , wherein the determining means determines the dynamic evaluation in accordance with information about a subject indicated in the digital content.

4. The information processing device according to claim 3 , wherein the information about the subject indicates an evaluation of the subject.

5. The information processing device according to claim 3 , wherein the information about the subject indicates the number of digital contents generated for the subject.

6. 2. The information processing apparatus according to claim 1, wherein said determining means determines said dynamic evaluation based on an evaluation of said three-dimensional shape data that may change over time.

7. 2. The information processing apparatus according to claim 1, wherein said determining means determines said dynamic evaluation according to the number or sales status of digital content generated based on said three-dimensional shape data.

8. 2. The information processing apparatus according to claim 1, wherein said determining means determines said dynamic evaluation in accordance with an evaluation of a creator who created said digital content.

9. The collection includes multiple digital contents.

2. The information processing apparatus according to claim 1, wherein said determining means determines said dynamic evaluation of the digital content owned by the user according to the state of ownership of the digital content constituting said collection by the user.

10. The information processing device according to claim 1 , wherein the static evaluation is set according to the type of scene represented by the digital content.

11. The information processing device according to claim 1 , wherein the static evaluation is set according to the type of subject indicated by the digital content.

12. The information processing apparatus according to claim 1 , wherein the static evaluation is set in accordance with a setting of a process for generating the digital content.

13. 2. The information processing device according to claim 1, wherein the setting means sets information indicating a static evaluation of the digital content generated based on the three-dimensional shape data based on the information indicating a static evaluation of the three-dimensional shape data.

14. 2. The information processing apparatus according to claim 1, further comprising a generating unit for generating digital content in accordance with the three-dimensional shape data of the subject and a user instruction.

15. 2. The information processing apparatus according to claim 1, further comprising a management unit for managing owner information of said digital content.

16. 16. The information processing apparatus according to claim 15, wherein said management means manages buying and selling of said digital content between users.

17. The information processing device according to claim 1 , wherein the digital content is registered in a blockchain and is assigned an NFT indicating the owner.

18. An information processing method performed by an information processing device, a setting step of setting information indicating a static evaluation of the digital content, the static evaluation being an evaluation according to the content of the digital content generated based on three-dimensional shape data indicating a three-dimensional shape of a subject generated using a plurality of captured images acquired by a plurality of imaging devices; a determining step of determining a dynamic rating of the digital content, the rating being a rating that may change over time; an estimation step of estimating a value of the digital content based on both the static and dynamic assessments; An information processing method comprising:

19. A program for causing a computer to function as the information processing device according to any one of claims 1 to 17.

Images