Information processing system, information processing method, and program

Abstract

To associate a suitable image or the like with a predetermined item available in a virtual space.SOLUTION: The disclosed information processing system is provided with: a user input acquisition unit for acquiring a predetermined input from a user; an image acquisition unit for using a first machine learning model constructed by artificial intelligence to acquire a specific image obtained by inputting the predetermined input to the first machine learning model; and an association processing unit for associating the specific image with a predetermined item available in a virtual space.SELECTED DRAWING: Figure 20

Description

[Technical field]

[0001] The present disclosure relates to an information processing system, an information processing method, and a program. [Background technology]

[0002] In relation to Word2Image and the like, a technique for adding an image suitable for an input document is known. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2011-221794 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, it is difficult to apply the above-mentioned conventional techniques to specific items that can be used in a virtual space.

[0005] Therefore, in one aspect, the present disclosure aims to apply images generated by AI (artificial intelligence) to specific items available in a virtual space. [Means for solving the problem]

[0006] In one aspect, a user input acquisition unit that acquires a predetermined input from a user; an image acquisition unit that acquires a specific image obtained by inputting the predetermined input into a first machine learning model constructed by artificial intelligence; An information processing system is provided, comprising: an association processing unit that associates the specific image with a predetermined item that can be used in a virtual space. Effect of the Invention

[0007] According to one aspect, the present disclosure makes it possible to associate suitable images or the like with predetermined items that can be used in a virtual space. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram of a system according to an embodiment of the present invention. [Diagram 2] FIG. 1 is a block diagram of processing circuitry for performing computer-based operations according to the present disclosure. [Diagram 3] 1 is a flowchart showing an overview of an example of the flow of a process that may be executed in the system. [Figure 4] FIG. 4 is an explanatory diagram of the process shown in FIG. 3, showing an image of mixing in the semantic space. [Diagram 5] FIG. 4 is an explanatory diagram of the process shown in FIG. 3 and is an image diagram of a specific image. [Figure 6] FIG. 4 is an explanatory diagram of the process shown in FIG. 3, showing an image of an avatar and an item attached thereto. [Figure 7] FIG. 4 is an explanatory diagram of the process shown in FIG. 3, showing an image of items that can be arranged in the virtual space. [Figure 8] FIG. 4 is an explanatory diagram of the process shown in FIG. 3, showing an image of a combination of avatars and furniture in a virtual space. [Figure 9] 10 is a flowchart showing an overview of the flow of another example of processing that may be executed in the system. [Figure 10] FIG. 10 is an explanatory diagram of the process shown in FIG. 9, showing an image of differences in item textures. [Figure 11] 13 is a flowchart showing an overview of the flow of yet another example of processing that may be executed in the system. [Figure 12] FIG. 10 is an explanatory diagram of the process shown in FIG. 9, showing an image of the shape of an item that can be worn on an avatar, etc. [Figure 13A] FIG. 13 is a diagram showing an example of a UI that enables generation / input of input information, an instruction to mix a plurality of specific images, etc. [Figure 13B]FIG. 13 is a diagram illustrating an example of a UI that allows color adjustment. [Figure 13C] FIG. 13 is a diagram showing an example of a UI that allows item selection. [Figure 14] FIG. 11 is an explanatory diagram of item elements that can be managed for each pattern or part. [Figure 15] FIG. 2 is a diagram illustrating an example of a control that can be used in the metaverse space. [Figure 16] 10 is a flowchart illustrating an example of a user-side operational procedure that can be implemented in the system. [Figure 17] FIG. 17 is an explanatory diagram of the procedure of FIG. 16, showing a screen in which a user is editing the clothes (kimono) of an avatar. [Figure 18] 13 is a flowchart of a process that may be implemented by a server device when a store review application is received. [Figure 19] 11 is a schematic flowchart illustrating an example of a uniqueness evaluation process. [Figure 20] FIG. 2 is a block diagram illustrating an example of the functions of a server device. [Figure 21] FIG. 13 is an explanatory diagram of simultaneous (collective) reflection on a plurality of predetermined items. [Figure 22] This is an image of the contest. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, each embodiment will be described in detail with reference to the accompanying drawings. Note that in the accompanying drawings, for ease of viewing, only some of the reference symbols may be attached to multiple parts having the same attribute.

[0010] An overview of a system 1 according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram of the system 1 according to this embodiment.

[0011] The system 1 includes a server device 10 and one or more terminal devices 20. For simplicity, three terminal devices 20 are illustrated in Fig. 1, but the number of terminal devices 20 is arbitrary.

[0012] The server device 10 is an information processing device such as a server managed by an operator that provides one or more of the content creation support services. The terminal device 20 is a device used by a user, such as a mobile phone, a smartphone, a tablet terminal, a PC (Personal Computer), a head-mounted display, or a game device. A plurality of terminal devices 20 can be connected to the server device 10 via the network 3, typically in a different manner for each user.

[0013] The terminal device 20 is capable of executing a content generation assistance application according to this embodiment. The content generation assistance application may be received by the terminal device 20 from the server device 10 or a predetermined application distribution server via the network 3, or may be stored in advance in a storage device provided in the terminal device 20 or a storage medium such as a memory card readable by the terminal device 20. The server device 10 and the terminal device 20 are communicatively connected via the network 3. For example, the server device 10 and the terminal device 20 cooperate to execute various processes related to content generation assistance.

[0014] The network 3 may include a wireless communication network, the Internet, a Virtual Private Network (VPN), a Wide Area Network (WAN), a wired network, or any combination of these.

[0015] In this embodiment, the server device 10 may be connected to the blockchain network 5 (see arrow R10). The blockchain network 5 is a network in which many computers are connected to each other, and each connected computer serves as a node to record a processing request notified from the server device 10 to the blockchain network 5, executes processing according to the processing request from the user, and records the result in a storage managed by the node. The processing request is transmitted to each node, and each node executes the same processing for the processing request and records the output, thereby realizing that each node holds exactly the same information even in a distributed environment. The processing executed on this blockchain is also called a smart contract. Some or all of the nodes of the blockchain network 5 may be realized by the terminal device 20, and some or all of the network related to the blockchain network 5 may be realized by the network 3.

[0016] In the following, the system 1 realizes an example of an information processing system, but each element of a specific terminal device 20 (see the terminal communication unit 21 to the terminal control unit 25 in FIG. 1) may realize an example of an information processing system, or a plurality of terminal devices 20 may cooperate to realize an example of an information processing system. Also, the server device 10 may independently realize an example of an information processing system, or the server device 10 and one or more terminal devices 20 may cooperate to realize an example of an information processing system.

[0017] (Server device configuration) The configuration of the server device 10 will be specifically described. The server device 10 is composed of a server computer. The server device 10 may be realized by a plurality of server computers working in cooperation with each other. For example, the server device 10 may be realized by a server computer that provides various contents, a server computer that realizes various authentication servers, and the like working in cooperation with each other. The server device 10 may also include a Web server 820 (see FIG. 2). In this case, some of the functions of the terminal device 20 described later may be realized by a browser processing an HTML document received from the Web server 820 (see FIG. 2) and various programs (JavaScript (registered trademark) associated therewith.

[0018] As shown in FIG. 1, the server device 10 includes a server communication unit 11, a server storage unit 12, and a server control unit 13.

[0019] The server communication unit 11 includes an interface (see the I / O interface 612, the network controller 702, etc. in FIG. 2) that communicates with an external device wirelessly or via a wired connection and transmits and receives information. The server communication unit 11 may include, for example, a wireless LAN (Local Area Network) communication module or a wired LAN communication module. The server communication unit 11 is capable of transmitting and receiving information to and from the terminal device 20 via the network 3.

[0020] The server storage unit 12 is, for example, a storage device, and stores various information and programs required for various processes related to content creation support.

[0021] The server control unit 13 may include a dedicated microprocessor or a CPU (Central Processing Unit) that realizes a specific function by reading a specific program, a GPU (Graphics Processing Unit), etc. (see CPU 601 in FIG. 2). For example, the server control unit 13 cooperates with the terminal device 20 to execute a content generation support application in response to a user operation on the display unit 23 (touch panel) of the terminal device 20.

[0022] (Terminal Device Configuration) The following describes the configuration of the terminal device 20. As shown in Fig. 1, the terminal device 20 includes a terminal communication unit 21, a terminal storage unit 22, a display unit 23, an input unit 24, and a terminal control unit 25.

[0023] The terminal communication unit 21 includes an interface (see the I / O interface 612, the network controller 702, etc. in FIG. 2) that communicates with an external device wirelessly or wiredly and transmits and receives information. The terminal communication unit 21 may include a wireless communication module, a wireless LAN communication module, or a wired LAN communication module that supports mobile communication standards such as LTE (Long Term Evolution (registered trademark)), LTE-A (LTE-Advanced), a fifth generation mobile communication system, and UMB (Ultra Mobile Broadband). The terminal communication unit 21 is capable of transmitting and receiving information to and from the server device 10 via the network 3.

[0024] The terminal storage unit 22 includes, for example, a primary storage device and a secondary storage device. For example, the terminal storage unit 22 may include a semiconductor memory, a magnetic memory, an optical memory, or the like. The terminal storage unit 22 stores various information and programs related to content generation support received from the server device 10. The information and programs related to content generation support may be acquired from an external device via the terminal communication unit 21. For example, a content generation support application program may be acquired from a predetermined application distribution server. Hereinafter, the application program may also be simply referred to as an application.

[0025] The display unit 23 includes a display device such as a liquid crystal display or an organic EL (Electro-Luminescence) display (see also display 609 in FIG. 2). The display unit 23 is capable of displaying a variety of images. The display unit 23 is configured with, for example, a touch panel, and functions as an interface that detects a variety of user operations. Note that the display unit 23 may be in a form built into a head-mounted display, as described above.

[0026] The input unit 24 may include a physical key, or may further include any input interface including a pointing device such as a mouse. The input unit 24 may also be capable of accepting non-contact user input such as voice input, gesture input, and gaze input. For gesture input, a sensor (such as an image sensor, an acceleration sensor, or a distance sensor) for detecting various states of the user, a dedicated motion capture device integrating sensor technology and a camera, or a controller such as a joypad may be used. The camera for gaze detection may also be disposed in a head-mounted display. As described above, the various states of the user are, for example, the user's orientation, position, movement, or the like, and in this case, the user's orientation, position, and movement are concepts that include not only the orientation, position, and movement of the user's hands and body, but also the gaze direction, position, movement, or the like of the broadcasting user.

[0027] The terminal control unit 25 includes one or more processors. The terminal control unit 25 controls the operation of the entire terminal device 20.

[0028] The terminal control unit 25 transmits and receives information via the terminal communication unit 21. For example, the terminal control unit 25 receives various information and programs related to content generation support from at least one of the server device 10 and other external servers. The terminal control unit 25 stores the received information and programs in the terminal storage unit 22. For example, the terminal storage unit 22 may store a browser (internet browser) for connecting to a Web server 820 (see FIG. 2).

[0029] The terminal control unit 25 starts a content generation support application in response to a user operation. The terminal control unit 25 cooperates with the server device 10 to execute processing related to the content generation support. For example, the terminal control unit 25 may output a GUI (Graphic User Interface) for detecting a user operation on the screen of the display unit 23. The terminal control unit 25 can detect a user operation via the input unit 24. For example, the terminal control unit 25 can detect various operations (operations corresponding to a tap operation, a long tap operation, a flick operation, a swipe operation, etc.) by a user's gesture. The terminal control unit 25 may transmit operation information to the server device 10.

[0030] 2 is a block diagram of a processing circuit 600 for executing computer-based operations according to the present disclosure. The processing circuit 600 described below is suitable as a hardware configuration for implementing the server communication unit 11 to the server control unit 13 of the server device 10 shown in FIG. 1. The processing circuit 600 described below is also suitable as a hardware configuration for implementing the terminal communication unit 21, the terminal storage unit 22, and the terminal control unit 25 of the terminal device 20 shown in FIG.

[0031] The processing circuit 600 can be used to control any computer-based and cloud-based control process, and the descriptions or blocks in the flowcharts can be understood as representing modules, segments, or portions of code that include one or more executable instructions for implementing a particular logical function or step in the process, and alternative implementations can perform functions out of the order shown or discussed, such as substantially simultaneously or in reverse order, depending on the functionality involved, as will be understood by those skilled in the art, within the scope of the exemplary embodiments of the present invention. The functions of the elements disclosed herein can be implemented using circuits or processing circuits that may include general purpose processors, special purpose processors, integrated circuits, ASICs (Application Specific Integrated Circuits), conventional circuits, and / or combinations thereof, configured or programmed to perform the disclosed functions. A processor is a processing circuit or circuit, since it includes transistors and other circuits therein. A processor may be a programmed processor that executes a program stored in the memory 602. In the present disclosure, a processing circuit, unit, or means is hardware that performs or is programmed to perform the functions described. The hardware may be any hardware disclosed herein or otherwise known that is programmed or configured to perform the functions described.

[0032] 2, the processing circuit 600 is connected to a display controller 606, a storage controller 624, a network controller 702, a memory 602, an I / O interface 612, and the like, which are connected via a bus 628. In this case, the processing circuit 600 is connected to a display 609 via the display controller 606, and is connected to a keyboard, a mouse 614, a touch screen 616, and a peripheral device 618 via the I / O interface 612. The processing circuit 600 also accesses the network 3 via the network controller 702. The display 609 and the display controller 606 may be connected via a standard connection method based on a video transfer standard, such as VGA, DVI, DisplayPort, and HDMI.

[0033] In FIG. 2, the processing circuit 600 includes a CPU 601 that executes one or more of the control processes discussed in this disclosure. Process data and instructions may be stored in a memory 602. These processes and instructions may also be stored on a storage medium disk 604 (in FIG. 2, labeled "disk"), such as a hard disk drive (HDD) or a portable storage medium, or may be stored remotely. Furthermore, the developmental features recited in the claims are not limited by the form of the computer-readable medium on which the instructions of the disclosed processes are stored. For example, the instructions may be stored on a CD, DVD, FLASH memory, RAM, ROM, PROM, EPROM, EEPROM, hard disk or other non-transitory computer-readable medium of an information processing device with which the processing circuit 600 communicates, such as a server or computer. The processes may also be stored in a network-based storage, cloud-based storage, or other mobile-accessible storage and executable by the processing circuit 600.

[0034] Additionally, the developed features recited in the claims may be provided as utility applications, background daemons, or operating system components, or combinations thereof, executing in conjunction with the CPU 601 and an operating system, such as Microsoft Windows®, UNIX®, Solaris®, LINUX®, Apple®, MAC-OS®, Apple iOS®, and other systems known to those skilled in the art.

[0035] The hardware elements for implementing the processing circuit 600 may be implemented by various circuit elements. Furthermore, each function of the above-mentioned embodiments may be implemented by a circuit including one or more processing circuits. The processing circuit includes a specifically programmed processor, for example, a processor (CPU) 601, as shown in FIG. XX. The processing circuit also includes devices such as application specific integrated circuits (ASICs) and conventional circuit components arranged to perform the mentioned functions.

[0036] 2, the processing circuit 600 may be a computer or a specific special purpose machine. The processing circuit 600 is programmed to execute processes for controlling the device in which it is implemented (the server device 10 or the terminal device 20).

[0037] Alternatively, or in addition, CPU 601 may be implemented on a Field Programmable Gate Array (FPGA), an ASIC, a Programmable Logic Device (PLD), or using discrete logic circuitry, as will be appreciated by those skilled in the art. Furthermore, CPU 601 may be implemented as multiple processors operating in parallel and in coordination to execute instructions for various processes.

[0038] The processing circuit 600 of FIG. 2 also includes a network controller 702, such as an Ethernet PRO network interface card, for interfacing with the network 3. As can be appreciated, the network 3 can be a public network, such as the Internet, or a private network, such as a local area network (LAN) or a wide area network (WAN), or any combination thereof, and can also include a Public Switched Telephone Network (PSTN) or an Integrated Services Digital Network (ISDN), a sub-network. The network 3 can also be wired, such as an Ethernet network, a Universal Serial Bus (USB) cable, or wireless, such as a cellular network, including EDGE, 3G, 4G, and 5G wireless cellular systems. The wireless network can also be Wi-Fi, wireless LAN, Bluetooth, or other forms of wireless communication known in the art. Additionally, the network controller 702 can be compliant with other direct communication standards, such as Bluetooth, Near Field Communication (NFC), infrared, and the like. 2 also shows a configuration example of the server device 10. In the example shown in Fig. 2, the server device 10 includes a remote computer 815, a Web server 820, a cloud storage server 825, and a computer server 830. Although details of the hardware configurations of the remote computer 815, the Web server 820, the cloud storage server 825, and the computer server 830 will not be described, they may be similar to the processing circuit 600.

[0039] Next, further details of the system 1 will be described with reference to FIG.

[0040] Fig. 3 is a flow chart showing an outline of the flow of an example of processing that may be executed in the system 1. Figs. 4 to 8 are explanatory diagrams of the processing shown in Fig. 3.

[0041] In Fig. 3, the processing is shown separately for the server device 10 and the terminal device 20. Note that the processing realized by the machine learning model (an example of a first machine learning model) is the processing of the server device 10, but is shown separately for convenience. In the following, one terminal device 20 will be described, but similar functions can be realized in other terminal devices 20. In the following, a user refers to a user of one terminal device 20 unless otherwise specified.

[0042] A user generates input information (an example of a predetermined input) via the terminal device 20 (step S2100) and transmits it to the server device 10 (step S2110). In FIG. 3, the input information is information related to an image imagined by the user. For example, when a user wants to obtain a desired image, the input information is information representing the desired image. The input information may include at least one of text, symbols, pictograms, numbers, colors, textures, images, sounds, gestures (including motions), and any combination of two or more of these. The text is typically a character string having a meaning, but may include a meaningless character string. The input information may be input in a template format.

[0043] When the server device 10 acquires the input information, it acquires a specific image obtained by inputting the input information into a predetermined machine learning model (steps S2200, S2300). The predetermined machine learning model is a machine learning model constructed by artificial intelligence, and is a model that generates and outputs an image based on an input such as the above-mentioned input information. Hereinafter, for the sake of distinction, the predetermined machine learning model that generates and outputs an image based on an input such as the above-mentioned input information is also referred to as an "image output model". The image output model may be constructed in any manner, but for example, a model that can generate images that reflect various contexts based on the input information is desirable. The image output model may utilize Latent Diffusion Models or the like.

[0044] FIG. 4 is an explanatory diagram of an example of a method for generating input information, in which each character string is shown in a vector representation as an example of a mixed mode in a semantic space. The method for generating input information is arbitrary, but it is also possible to mix concepts (meanings, contexts, etc.) that combine two or more characters. For example, as conceptually shown in FIG. 4, an image output model may be constructed so as to generate an image of a character string C (e.g., a seagull as a seabird) based on a certain character string A (e.g., a bird) and another character string B (e.g., the sea). In this case, if a user uses not only the synthesis of multiple character strings but also synthesis by subtraction of multiple character strings, the possibility of obtaining a desired specific image can be increased even if an appropriate character string cannot be thought of. For example, synthesis by subtraction of character string C and character string B is equivalent to input of character string A. The above-mentioned Diffusion Model is advantageous in that it embeds a directionality that brings the target character string closer to the noise removal process, and therefore it is possible to visualize details that are difficult to express by simple synthesis of character strings alone.

[0045] The specific image may be a still image or a video. The type and size of the specific image may be specified by information other than the input information, or may be included in the input information. FIG. 5 shows an example of an image (specific image) G500 of a seagull flying over the sea. Such a specific image may be generated, for example, when the input information includes "bird" and "sea."

[0046] The input information may also be allowed to include character strings related to so-called negative words. Negative words are a concept similar to the "subtraction" involved in the synthesis of character strings described above, and are used to prevent images related to character strings related to negative words from being included. For example, if the input information includes "bird" and "sea" and also includes "seagull" as a negative word, a specific image that does not include seagulls may be generated.

[0047] The server device 10 may determine whether the input information contains a predetermined prohibited word, and if the input information contains the predetermined prohibited word, may notify the terminal device 20 of the fact and request the user to regenerate and resend the input information that does not contain the predetermined prohibited word. In this case, the predetermined prohibited word may include words that violate public order and morals, such as obscene words, slander, hate speech, etc., and words that infringe or are likely to infringe the intellectual property rights of others. The predetermined prohibited words may be stored and accumulated in the server storage unit 12 or the like in dictionary format.

[0048] 3, when the server device 10 acquires the specific image, it stores specific image information in the server storage unit 12 (step S2210). The specific image information includes image data of the specific image and input information used to generate the specific image, in a form in which the image data and the input information are associated with each other.

[0049] Next, the server device 10 generates a preview display of the specific image (step S2220) and enables output of the preview display on the terminal device 20. The user can determine the necessity of corrections, etc. while viewing the preview display on the terminal device 20 (step S2120). The preview display may be the specific image itself, or may be realized as a display reflecting any item available in the virtual space (for example, a desired item designated by the user). In the latter case, the item may include an item that can be associated with an avatar in the virtual space (for example, clothes 601, 602 of the avatar A6 as shown in FIG. 6), an item that can be placed in the virtual space (for example, the entire furniture B7 and its components IT701, IT702 as shown in FIG. 7), or any combination of these (for example, a combination of avatars and furniture in the virtual space as shown in FIG. 8), etc. In this case, the preview display may be a three-dimensional display, and may be panned and rotated like a CAD (Computer Aided Design) viewer. For example, if the item is clothing for a user's avatar, an avatar may be generated wearing clothing that reflects a specific image, and a preview may be displayed together with the avatar.

[0050] If the user determines that the specific image thus generated does not require any modification, the user generates a correspondence instruction for associating the specific image with any item available in the virtual space (e.g., a desired item designated by the user) as the final version, and transmits the correspondence instruction to the server device 10 (step S2130). The correspondence instruction may include information for identifying the item to be associated.

[0051] When the server device 10 receives the association instruction (step S2230), it associates the specific image with the predetermined item, which is the item to be associated (step S2240). The association method is arbitrary, and for example, when the predetermined item is clothes of the user's avatar, the association of the specific image may be realized by including the specific image in a part or all of the clothes. Such a reflection method may be specified by information separate from the input information, or may be included in the input information.

[0052] In this way, according to the process shown in Fig. 3, the user can obtain a specific image by generating input information according to his / her own image without drawing the image by himself / herself, and can reflect the specific image in any item available in the virtual space. Also, by providing a specific image as a base image, it is possible to generate a new design in any area (for example, an area in the virtual space).

[0053] 3, if the items to be associated are determined in advance, the input information generated in step S2100 may include attributes and names of the items to be associated (i.e., the predetermined items). In this case, it may be possible to acquire a specific image taking into account the attributes and the like of the predetermined items. Furthermore, if a preview display is not required, the input information may be transmitted in a lump sum to the server device 10 in a form including the association instruction of step S2130.

[0054] Fig. 11 is a flowchart showing an outline of the flow of another example of processing that may be executed in the system 1. Fig. 12 is an explanatory diagram of the processing shown in Fig. 11.

[0055] 11, the processing is shown separately for the server device 10 and the terminal device 20. As in FIG. 3, the processing realized by the machine learning model (an example of the second machine learning model) is the processing of the server device 10, but is shown separately for convenience.

[0056] A user generates input information via the terminal device 20 (step S4100) and transmits it to the server device 10 (step S4110). In FIG. 11, the input information is information related to an item shape imagined by the user. For example, when a user wants to obtain a desired item shape, the input information is information representing the item shape. The input information may include at least one of text, symbols, pictograms, numbers, colors, textures, images, sounds, gestures (including motions), and any combination of two or more of these. The text is typically a character string having a meaning, but may include a meaningless character string. The input information may be input in a template format.

[0057] When the server device 10 acquires the input information, it inputs the input information into a predetermined machine learning model to acquire the item shape obtained (steps S4200, S4300). The predetermined machine learning model is a machine learning model constructed by artificial intelligence, and is a model that generates and outputs an item shape based on an input such as the above-mentioned input information. Hereinafter, for the sake of distinction, the predetermined machine learning model that generates and outputs an item shape based on an input such as the above-mentioned input information is also referred to as a "model for outputting item shape." Note that the model for outputting item shape may be a model other than the above-mentioned model for outputting images, etc., and may be used as an integrated model.

[0058] The method of generating the input information is arbitrary and may be similar to the method described above with reference to FIG.

[0059] The item shape may be a shape related to any item available in the virtual space. The item shape may be a three-dimensional shape or a two-dimensional shape depending on the attributes of the item. For example, if the item related to the item shape is clothing, the item shape may be in the form of a pattern for the clothing. Also, if the item related to the item shape is a three-dimensional object, the item shape may be in the form of a drawing of the three-dimensional object, a three-dimensional form, or a combination thereof. The type, size, etc. of the item related to the item shape may be specified by information separate from the input information, or may be included in the input information.

[0060] The input information may also be allowed to include character strings related to so-called negative words. For example, if the input information includes "car" and "sports" and also includes "Germany" as a negative word, an item shape related to a sports car other than a German car may be generated.

[0061] 3, the server device 10 may determine whether the input information contains a predetermined prohibited word, and if the input information contains the predetermined prohibited word, may notify the terminal device 20 of the fact and request the user to regenerate and resend the input information that does not contain the predetermined prohibited word. In this case, the predetermined prohibited word may include words that violate public order and morals, such as obscene words, slander, hate speech, etc., and words that infringe or are likely to infringe the intellectual property rights of others. The predetermined prohibited words may be stored and accumulated in the server storage unit 12, etc. in dictionary format.

[0062] When the server device 10 acquires the item shape, it stores the item shape information in the server storage unit 12 (step S4210). The item shape information includes data of the item shape and input information used to generate the item shape, in a form in which the data and the input information are associated with each other.

[0063] Next, the server device 10 generates a preview display of the item shape (step S4220) and enables output of the preview display on the terminal device 20. The user can determine the necessity of corrections, etc. while viewing the preview display on the terminal device 20 (step S4120). The preview display may be the item shape itself, or may be realized as an item shape reflected in an image (for example, the above-mentioned specific image). The preview display may be a three-dimensional display, and may be panned or rotated. For example, when the item shape is the shape of clothes of the user's avatar, the item shape may be a planar form such as a paper pattern, or may be a three-dimensional form worn on the user's avatar. In either case, the preview display may be realized three-dimensionally. In this case, for example, as shown in FIG. 12, the item shape may be previewed together with an avatar A6 wearing clothing items IT601A and IT602A that reflect the item shape.

[0064] If the user determines that no corrections are required to the item shape generated in this manner, the user generates a shaping instruction for shaping any item available in the virtual space (e.g., a desired item designated by the user) as a final version, and transmits the shaping instruction to the server device 10 (step S4130). The shaping instruction may include information for identifying the item to be shaped (predetermined item).

[0065] When the server device 10 receives the shaping instruction (step S4230), it shapes the predetermined item, which is the item to be shaped (step S4240). The shaping method is arbitrary, and for example, when the predetermined item is clothes of the user's avatar, the shaping may be realized by making a part or all of the clothes include the item shape. Furthermore, such shaping may be realized according to the size of the predetermined item. Such a reflection method may be specified by information separate from the input information, or may be included in the input information.

[0066] In this way, according to the process shown in FIG. 11, a user can obtain an item shape by generating input information according to his or her own image without having to draw the item shape himself or herself, and can reflect the item shape in any item available in the virtual space.

[0067] 11, if the item to be associated is determined in advance, the input information generated in step S4100 may include the attributes and name of the item to be associated (i.e., the predetermined item). In this case, it may be possible to acquire an item shape that takes into account the attributes, etc. of the predetermined item.

[0068] 9 is a flowchart showing an outline of the flow of another example of processing that may be executed in the system 1. FIG 10 is an explanatory diagram of the processing shown in FIG 9.

[0069] 9, the processing is shown separately for the server device 10 and the terminal device 20. As in FIG. 3, the processing realized by the machine learning model (an example of a third machine learning model) is the processing of the server device 10, but is shown separately for convenience.

[0070] A user generates input information via the terminal device 20 (step S3100) and transmits it to the server device 10 (step S3110). In FIG. 9, the input information is information related to the texture of the item surface that the user imagines. For example, when a user wants to obtain a desired texture, the input information is information representing the texture. The input information may include at least one of text, symbols, pictograms, numbers, colors, textures, images, sounds, gestures (including motions), and any combination of two or more of these. The text is typically a character string having a meaning, but may include a meaningless character string. The input information may be input in a template format.

[0071] When the server device 10 acquires the input information, it inputs the input information into a predetermined machine learning model to acquire an item texture (steps S3200, S3300). The predetermined machine learning model is a machine learning model constructed by artificial intelligence, and is a model that generates and outputs a texture (item texture) based on an input such as the above-mentioned input information. Hereinafter, for the sake of distinction, the predetermined machine learning model that generates and outputs a texture based on an input such as the above-mentioned input information is also referred to as a "texture output model." Note that the texture output model may be a model different from the above-mentioned image output model, or an integrated model.

[0072] The method of generating the input information is arbitrary and may be similar to the method described above with reference to FIG.

[0073] The item texture may represent the surface texture of any item available in the virtual space. The granularity of the item texture may be adjustable so that the texture is visible depending on the attributes of the item. The type and size of the item related to the texture may be specified by information separate from the input information, or may be included in the input information.

[0074] The item texture may be only a plain texture, but may also be a texture including a pattern, as shown in Fig. 10. In this case, the pattern may be a pattern that is merely for making the texture easier to understand, or may be a pattern that can be used in combination with the texture. In the example shown in Fig. 10, the upper texture Tx1 has a relatively small surface irregularity, while the lower texture Tx2 has a relatively large surface irregularity.

[0075] The input information may also be allowed to include character strings related to so-called negative words. For example, if the input information includes "exterior wall" and "apartment" and also includes "sprayed" as a negative word, a texture related to the exterior wall of an apartment other than sprayed (for example, a texture including bricks and tiles) may be generated.

[0076] 3, the server device 10 may determine whether the input information contains a predetermined prohibited word, and if the input information contains the predetermined prohibited word, may notify the terminal device 20 of the fact and request the user to regenerate and resend the input information that does not contain the predetermined prohibited word. In this case, the predetermined prohibited word may include words that violate public order and morals, such as obscene words, slander, hate speech, etc., and words that infringe or are likely to infringe the intellectual property rights of others. The predetermined prohibited words may be stored and accumulated in the server storage unit 12, etc. in dictionary format.

[0077] When the server device 10 acquires the item texture, it stores the item texture information in the server storage unit 12 (step S3210). The item texture information includes data of the item texture and input information used to generate the item texture, in a form in which the data and the input information are associated with each other.

[0078] Next, the server device 10 generates a preview display of the item texture (step S3220) and enables output of the preview display on the terminal device 20. The user can determine the need for corrections, etc. while viewing the preview display on the terminal device 20 (step S3120). The preview display may be the item texture itself, or may be realized as an item texture reflected on an arbitrary item. The preview display may be a three-dimensional display, and may be capable of panning and rotation. For example, if the target item is clothing for a user's avatar, an avatar dressed in clothing reflected in the item texture may be generated, and a preview display may be possible together with the avatar.

[0079] If the user determines that no corrections are required for the item texture thus generated, the user generates a correspondence instruction for associating the final version with any item available in the virtual space (e.g., a desired item designated by the user) and transmits the correspondence instruction to the server device 10 (step S3130). The correspondence instruction may include information for identifying the item to be associated (predetermined item).

[0080] When the server device 10 receives the association instruction (step S3230), it associates the predetermined item, which is the item to be associated, with the item texture (step S3240). The association method is arbitrary, and for example, when the predetermined item is clothing of the user's avatar, the association may be realized by including an item texture in part or all of the clothing. Furthermore, such association may be realized according to the size of the predetermined item. Such a reflection method may be specified by information separate from the input information, or may be included in the input information.

[0081] In this way, according to the process shown in FIG. 9, a user can obtain a desired item texture by generating input information according to his or her own image without having to draw the item texture himself or herself, and the item texture can be reflected in any item available in the virtual space.

[0082] 9, if the item to be associated is determined in advance, the input information generated in step S3100 may include the attributes and name of the item to be associated (i.e., the predetermined item). In this case, it may be possible to acquire an item texture that takes into account the attributes, etc., of the predetermined item.

[0083] Next, a UI (User Interface) suitable for the above-mentioned preview display will be described with reference to Fig. 13A to Fig. 13C. The UI shown in Fig. 13A to Fig. 13C may be a UI available in a virtual space and may be arranged within the user's field of view.

[0084] FIG. 13A is a diagram showing an example of a UI 13 that allows the user to generate / input input information, give instructions to mix a plurality of specific images, and the like.

[0085] In the example shown in FIG. 13A, the UI13 includes four specific image display areas P13 and an input area K130. The input area K130 includes an input character output area K131 and a character input section K132. The four specific image display areas P13 may be areas that output specific images obtained by the method described above with reference to FIG. 3. Note that some or all of the four specific image display areas P13 may be capable of outputting an item texture obtained by the method described above with reference to FIG. 9 and / or an item shape obtained by the method described above with reference to FIG. 11, instead of or in addition to the specific image obtained by the method described above with reference to FIG. 3.

[0086] The input character output area K131 may be an area that displays the various input information described above. The character input unit K132 may be a UI for inputting the various input information described above, and may be in the form of a keyboard, for example. The input of characters, etc. into the input character output area K131 may be realized by other inputs such as voice input. In addition, the input character output area K131 may list input candidate words derived based on artificial intelligence or the like. For example, words suitable as input information, such as words for indicating patterns such as repeating patterns and seamless patterns, and words for indicating image operations such as image synthesis such as blending, may be listed. In this case, the user can input desired characters without inputting many characters. This is particularly suitable when the user wears a head-mounted display and stays in the metaverse space. This is because, unlike reality, in such an environment, it is often difficult to manually specify small parts or input small details.

[0087] In the UI13 shown in FIG. 13A, the user may select a desired specific image display area P13 from among the multiple specific image display areas P13, thereby allowing the user to select a specific image or the like displayed in the selected specific image display area P13. The selected specific image or the like may be reflected in a predetermined item, as described above. In addition, the user may select two or more specific images or the like displayed in the multiple specific image display areas P13, thereby allowing the user to mix specific images together, mix item textures together, combine specific images and item textures, combine specific images and item shapes, combine item textures and item shapes, combine specific images, item textures and item shapes, and the like. In this case, by combining various parameters, it becomes easier to form a desired item, improving the convenience of the user.

[0088] Such a UI 13 is suitable for the above-mentioned preview display (see, for example, step S2120 in FIG. 3). For example, the user can fine-tune a specific image by operating the UI 13 on the preview display.

[0089] FIG. 13B is a diagram showing an example of the UI 14 that allows color adjustment.

[0090] In the example shown in FIG. 13B, the UI14 includes a plurality of sections (color attributes of materials) P140 expressing a plurality of colors. Each of the plurality of sections P140 may be assigned a different color and colored with the corresponding color. In FIG. 13B, a 20×20 array is shown, but a larger number of sections may be prepared. The color settings of the plurality of sections P140 may be customizable by the user, or may be given as variables whose values ​​change dynamically. In addition, the color settings are not limited to RGB values, and may include parameters such as transparency and material reflectance. In addition, the color settings may be proposed as a color set that is set in advance according to the item to be colored, or may be automatically set by AI or the like according to the item to be colored. In addition, the overall form of the UI14 is also arbitrary, and may change according to the item to be colored. For example, in the case of coloring around the eyes of the face, the overall form of the UI14 may be in the form of a cosmetic eyeshadow palette. In addition, such a UI14 may be automatically generated when an image including a base color set is given.

[0091] 13B, the user may be able to select a desired one of the multiple sections P140 and select a color associated with the selected section P140. In this case, the selected color may be reflected in some or all of the predetermined items, as described above.

[0092] Such a UI 14 is suitable for the above-mentioned preview display (see, for example, step S2120 in FIG. 3). For example, the user can adjust the color, hue, etc. of a part or all of a specific image (or a part or all of a specific item in which the specific image is reflected) by operating the UI 14 on the preview display. In addition, as other parameters, reflectance, roughness, material (for example, the characteristics of the material of the item to be drawn), etc. may be adjustable. However, reflectance, etc. may be adjustable as a texture.

[0093] FIG. 13C is a diagram showing an example of the UI 15 that allows item selection.

[0094] In the example shown in FIG. 13C, the UI15 includes multiple sections P150 for each item. A different item or a part of an item (a part of an item) may be assigned to each of the multiple sections P150, and the outline shape of the corresponding item may be shown. In FIG. 13C, the number of the multiple sections P150 is five, and the overall shape is circular, but the number and shape are arbitrary. Such a circular shape is advantageous compared to a UI such as a button, because even if the number of items increases (for example, from five to eight), it is only necessary to change the angle of the circular shape without increasing the number of UI such as buttons.

[0095] 13C, the user may select a desired section P150 from among the multiple sections P150, thereby allowing the user to select an item or a portion thereof associated with the selected section P150. In this case, the selected item or the portion thereof may be editable by the UI13 and / or the UI14, as described above. Note that the items or the portions thereof selectable in the multiple sections P150 may be items owned by the user, etc.

[0096] Such UI 15 is suitable for the above-mentioned preview display (see, for example, step S2120 in FIG. 3) for simultaneously editing a plurality of items. For example, the user can select and edit some or all of the items of the user's avatar by operating UI 15 on the preview display.

[0097] For example, in the example shown in FIG. 14, clothes and decorations that can be worn by an avatar are managed for each pattern and part. Specifically, in FIG. 14, an avatar wearing the clothes and decoration is shown in the upper part, and patterns and parts for forming (drawing) the clothes and decoration are shown in the lower part. Note that drawing on each pattern may be realized by using a stencil buffer or the like. Also, the arrangement of an image on the pattern may be adjusted by adjusting the position of two UV axes. By drawing a specific image on one three-dimensional item via a corresponding pattern, the processing load can be reduced compared to the case of pasting a specific image on a three-dimensional surface.

[0098] FIG. 15 shows an example of a manipulator 1500 that can be used in the metaverse space. In this case, the manipulator 1500 has a form like a laser pointer, and can activate or select a UI at the position pointed to by the pointer. For example, in FIG. 14, a part selected by the manipulator 1500 is shown as a point P14. In this case, the user may be able to operate the part by moving the point P14 onto a part of a desired item. Also, in the example shown in FIG. 15, the state of the manipulator 1500 of a user who operates the UI 13 shown in FIG. 13A is shown. Note that the manipulator 1500 may be able to move in response to an input from an input device (e.g., a controller) held by a user (a user wearing a head-mounted display) in the real world. In the example shown in FIG. 15, an input method uses an operator 1500, but as described above, the input method can take a variety of forms, such as specifying a part of the body by voice input or inputting a keyword instead of letters.

[0099] Note that the various UIs shown in FIG. 13A and the like are merely examples and can be changed in various ways. Also, UIs other than the various UIs shown in FIG. 13A and the like may be used. For example, a UI may be prepared that allows the physical parameters of an item (for example, stiffness, gravity or resistance, collision radius) to be set. Note that gravity and resistance are parameters that may be associated with items such as the avatar's hair and clothes, and are parameters that affect the dynamic behavior (swaying, etc.) of the hair and clothes. Also, the collision radius is a parameter that specifies the distance at which a collision (interference) with other items occurs in the virtual space. Default values ​​for these parameters may be automatically prepared for each attribute of the item by artificial intelligence.

[0100] Further functionality that may be implemented in the system 1 will now be described with reference to FIG.

[0101] Fig. 16 is a flow chart showing an example of a user-side operation procedure that can be realized in the system 1. Fig. 17 is an explanatory diagram of the procedure in Fig. 16, showing a screen showing a state in which a user is editing the clothes (kimono) of an avatar. Note that the screen shown in Fig. 17 may be a screen on the display unit 23 of the terminal device 20 in the form of a head-mounted display.

[0102] Fig. 16 shows an example of an operation procedure for arranging items IT800, IT801 such as furniture in a virtual space as shown in Fig. 8, and for editing the arranged items and items IT601, IT602 of a user's avatar A6. Various functions based on the following operation procedure can be realized by a user via, for example, the input unit 24 of the terminal device 20.

[0103] In step S1700, the user places items such as furniture in the virtual space. The virtual space in which a user can place items is arbitrary, and may be, for example, a space on an area (land) in the virtual space owned by the user. The items that can be placed may be items owned by the user.

[0104] In step S1702, the user selects an item or a portion within the item to be edited from among various items in the virtual space. This selection may be realized, for example, via the UI 15 shown in FIG. 13C.

[0105] In step S1704, the user generates input information. The input information is as described above, and may be, for example, an original keyword. Note that the generation of the input information may be realized, for example, via the UI 13 shown in FIG. 13A.

[0106] In step S1706, the user inputs negative words as part of the input information. The negative words are as described above. Note that the operation in step S1706 may be omitted as appropriate.

[0107] When step S1704 (and step S1706) is thus completed, a specific image is generated according to the input information, as described above with reference to Fig. 4. The specific image thus generated may be reflected in the part selected in step S1702 as a preview display. That is, the part selected in step S1702 may be drawn in a manner including the generated specific image.

[0108] In step S1708, the user specifies a color variation of the specific image. The specification of the color variation of the specific image may be realized, for example, via the UI 14 shown in FIG. 13B.

[0109] In step S1710, the user changes the specific image displayed in the preview by mixing the reference image with the specific image. The reference image may be displayed in the specific image display area P13 of the UI 13 shown in FIG. 13A, for example, and may be realized by the user selecting the specific image display area P13 including the reference image to be mixed. The reference image may be an image prepared in advance for mixing, or may be another specific image generated based on other input information as described above. Step S1710 is an optional operation and may be omitted as appropriate.

[0110] In step S1712, the user reviews the item to be edited or a portion within the item reflecting the specific image thus obtained in three dimensions by panning, rotating, etc.

[0111] In step S1714, the user repeats editing while changing the item to be edited or a portion within the item. For example, as shown in Fig. 17, in a state in which various UIs 13, 14, and 15 as shown in Fig. 13A to 13C are simultaneously displayed, the user may perform various operations using the operator 1500 as shown in Fig. 15.

[0112] In step S1716, when the user has obtained an item that reflects the specific image in a satisfactory manner, the user applies for store review. The store review application is accepted by the server device 10, and the process therefor will be described later.

[0113] In addition, in FIG. 16, editing of a specific image is described, but the same can be done for the above-mentioned item shape and item texture. After the user finishes editing the item shape and item texture, the user may apply for store review. The store review application may be executed for each item.

[0114] Fig. 18 is a flowchart of a process that may be implemented by the server device 10 when a store review application is received. In Fig. 18, the process is shown separately for the server device 10, the terminal device 20, and the smart contract (blockchain network 5).

[0115] The user generates a store review application via the terminal device 20 (step S5100), and transmits the application to the server device 10 (step S5110). The store review application may include information specifying the item for which the application is being made.

[0116] When the server device 10 receives the store examination application, it acquires information on the application target (step S5200). The information on the application target may include information on the item on which the application is made, a specific image associated with the item on which the application is made, an item shape that gives the shape of the item on which the application is made, and an item texture associated with the item on which the application is made.

[0117] The server device 10 evaluates the uniqueness of the item that is the object of the application based on the acquired information of the object of the application (step S5210). Uniqueness is a parameter that correlates with originality. Instead of evaluating the uniqueness, the similarity with other items may be equivalently evaluated. This is because high / low uniqueness corresponds to low / high similarity. Therefore, in the following description, uniqueness can be read as similarity, and in this case, a state of high uniqueness corresponds to a state of low similarity, and a state of low uniqueness corresponds to a state of high similarity.

[0118] The uniqueness evaluation method is arbitrary, but is preferably as follows. When the item to be applied for includes a specific image generated based on input information, the uniqueness may be evaluated based on the similarity of the appearance between the specific image and other images. In this case, the input information (input information to the image output model) used to generate the specific image may be taken into consideration for the uniqueness. For example, when the input information used to generate one specific image is similar to the input information used to generate another image, the uniqueness of the specific image may be calculated to be a low value. In this case, since the uniqueness can be calculated based on a comparison between the input information, the reliability of the calculation result can be increased while reducing the processing load. The comparison between the input information may utilize word embedding in natural language processing such as Word2vec. In the case of Word2vec, word vectors that are located close to each other in the vector space among the characters (words) included in the input information may be determined to have a high similarity relationship. By utilizing such natural language processing, the similarity between the input information can be efficiently determined. In addition, the similarity between the input information can be efficiently determined for various types of languages. It is also possible to use comparisons in latent space, such as the Diffusion Model, or to use word edit distance or Euclidean distance in CLIP (Contrastive Language-Image Pre-training), which may be used internally.

[0119] The server device 10 may further perform an evaluation of the intellectual property rights based on the acquired information of the application subject (step S5220). The evaluation of the intellectual property rights may be performed from the perspective of whether or not the appearance of the application subject item clearly infringes the design right, etc., of another person. The evaluation of the intellectual property rights may also be performed from the perspective of whether or not the application subject item includes a trademark related to the trademark right of another person. Although not shown in FIG. 18, an evaluation (check) may also be performed from the perspective of whether or not the appearance of the application subject item clearly violates public order and morals.

[0120] The server device 10 notifies the uniqueness evaluation result (step S5230). The notified result may be displayed on the terminal device 20 (step S5120). At this time, the evaluation result of the intellectual property right does not have to be notified, but if the infringement is clearly or highly likely to be an infringement of another person's right, a notice to that effect may be given. The same applies to cases where the infringement is clearly or highly likely to be against public order and morals. If the infringement is clearly or highly likely to be against public order and morals, and / or if the infringement is clearly or highly likely to be against public order and morals, the application may be rejected.

[0121] Next, the server device 10 performs an application completion process to store the item that is the subject of the application in a predetermined database or the like (step S5240). The item stored in this manner may be used when evaluating the uniqueness of another item that is the subject of the application (step S5210). Although not shown in FIG. 18, when the application completion process is completed, a notification to that effect may be executed to the terminal device 20.

[0122] Thereafter, when the user makes an NFT request for the item that has undergone the application completion process (step S5130), the server device 10 executes the NFT process (step S5250). The NFT process includes issuing the target item as an NFT (Non-Fungible Token). In this case, the server device 10 may be minted via a smart contract on the blockchain network 5 (step S5300). The NFT process may also include listing the issued NFT on a marketplace or the like.

[0123] FIG. 19 is a schematic flowchart illustrating an example of a uniqueness evaluation process.

[0124] In step S1000, the server device 10 acquires (extracts) input information associated with a specific image based on specific image information of the specific image to be determined.

[0125] In step S1002, the server device 10 extracts images to be compared. The images to be compared may be stored in a given database. The images to be compared may be extracted one by one.

[0126] In step S1004, the server device 10 calculates the similarity between appearance elements between the image to be compared and the specific image to be determined. The appearance elements may include at least one of color, texture, and pattern, for example. The appearance elements may also include other elements such as composition (arrangement). The method of calculating the similarity between appearance elements is arbitrary, and may be calculated as a score, for example. For example, an avatar wearing clothes may be rotated over an azimuth angle range of 360 degrees and / or an elevation angle range of 90 degrees, and the similarity (color and shape) of the captured image may be evaluated as a numerical value.

[0127] In step S1006, the server device 10 acquires (extracts) input information related to the image to be compared. The input information related to the image to be compared is input information used to generate the image to be compared, and is input information input to the image output model. Such input information may be stored in a given database in association with the image to be compared. Note that in this embodiment, the image to be compared may be only an image to which such input information is associated.

[0128] In step S1008, the server device 10 calculates the similarity between the input information on the specific image to be judged and the input information on the image to be compared, based on the input information. The similarity between the input information may be calculated using Word2vec, as described above. This is because if the characters included in the input information input to the image output model match or are similar, there is a high possibility that a similar specific image will be generated.

[0129] Incidentally, the input information input to the image output model depends on the image output model, but may contain a random number seed value in order to ensure the uniqueness of the specific image to be generated. In this case, if the random number seed values ​​included in the input information input to the image output model match, there is a high possibility that a similar specific image will be generated. Therefore, in this case, the server device 10 may further calculate the similarity between the input information based on the relationship between the random number seed values.

[0130] In step S1010, the server device 10 calculates a uniqueness value based on the similarity between the appearance elements calculated in step S1004 and the similarity between the input information calculated in step S1008. In this case, the uniqueness value may be calculated using only one (e.g., the one with higher similarity) of the similarity between the appearance elements calculated in step S1004 and the similarity between the input information calculated in step S1008, or may be calculated by averaging or combining them.

[0131] In step S1012, the server device 10 judges whether all images to be compared have been extracted. That is, it judges whether evaluation of the uniqueness of the specific image to be judged for all images to be compared has been completed. If the judgment result is "YES", the process proceeds to step S1014, otherwise the process returns to step S1002 to extract a new image to be compared, and the process from step S1004 is repeated.

[0132] In step S1014, the server device 10 outputs a uniqueness value based on the evaluation result of the uniqueness of the specific image to be judged with respect to all the images to be compared. In this case, the uniqueness value for each image to be compared may be output, or only a specific value such as the minimum value (the uniqueness value for the most similar image to be compared) may be output.

[0133] 19, the uniqueness of the specific image to be judged is evaluated based on the similarity between the appearance elements and the similarity between the input information, so that the reliability of the evaluation result can be improved compared to the case where the uniqueness is evaluated based on only one of the similarity between the appearance elements and the similarity between the input information. However, in a modified example, the uniqueness of the specific image to be judged may be evaluated based on only one of the similarity between the appearance elements and the similarity between the input information.

[0134] Next, an example of the function of the server device 10 in the system 1 will be described with reference to FIG. 20 and subsequent figures.

[0135] In the following description, the functions of the server device 10 will be mainly described. However, some or all of the functions of the server device 10 may be realized by one or more terminal devices 20.

[0136] FIG. 20 is a block diagram illustrating an example of the functions of the server device 10. As shown in FIG.

[0137] In the example shown in FIG. 20, the server device 10 includes an operation input acquisition unit 150, an image acquisition unit 152, an image correspondence processing unit 154, a shape information acquisition unit 156, a shape assignment processing unit 158, an additional information acquisition unit 160, an item surface processing unit 162, an edit processing unit 164, a determination unit 166, a parameter calculation unit 168, an output processing unit 170, an information management unit 172, an image management unit 173, an item management unit 174, a token management unit 176, a contest processing unit 178, an evaluation information storage unit 190, and a user information storage unit 192. Each processing unit such as the operation input acquisition unit 150 can be realized by the server communication unit 11 and the server control unit 13 shown in FIG. 1. Also, a storage unit such as the evaluation information storage unit 190 and the user information storage unit 192 can be realized by the server storage unit 12 shown in FIG. 1.

[0138] The operation input acquisition unit 150 acquires various user inputs by each user inputted via the input unit 24 of the terminal device 20. The various inputs are as described above.

[0139] The image acquisition unit 152 acquires a specific image based on the input information from the user. The method of acquiring the specific image may be as described above in relation to step S2200 in FIG.

[0140] The image matching processing unit 154 matches a specific image with a predetermined item that can be used in the virtual space. The predetermined item may be as described above. The method of matching the specific image may be as described above in relation to step S2240 of FIG. 3.

[0141] The image matching processing unit 154 may simultaneously match the acquired specific image or a derivative image obtained by changing a part of the specific image to a predetermined item related to a plurality of avatars. The derivative image obtained by changing a part of the specific image may not be exactly the same image, but may have a common feature or a feature that can create a sense of unity in combination. In this case, the specific image or the like can be matched at once to the predetermined items of a plurality of avatars having a specific relationship, and the processing load can be reduced compared to the case where similar specific images are acquired and matched separately. FIG. 21 shows four avatars A1 to A4 performing in a band. The image matching processing unit 154 may simultaneously match the specific image or a derivative image obtained by changing a part of the specific image to the plurality of avatars of such friends. In this case, the matching instruction (see step S3130 in FIG. 9) may be generated by any one or more users among the users related to the plurality of avatars. Alternatively, a matching instruction for simultaneously matching the specific items related to the plurality of avatars may be generated based on the matching instructions (see step S3130 in FIG. 9) from all users.

[0142] The above-mentioned specific relationship may include a relationship in which multiple avatars are all linked to one user (when one user is associated with the avatars of a group). Also, instead of or in addition to such a relationship, the above-mentioned specific relationship may include a relationship in which one user and one avatar are linked, but multiple users are linked to each other (for example, users are friends).

[0143] The shape information acquiring section 156 acquires the item shape (an example of shape information) based on the input information from the user. The method of acquiring the item shape may be as described above in relation to step S4200 in FIG.

[0144] The shaping processing unit 158 ​​shapes the predetermined item based on the item shape. The method of shaping the predetermined item may be as described above in relation to step S4240 in FIG.

[0145] The shaping processing unit 158 ​​may simultaneously shaping predetermined items related to multiple avatars based on the acquired item shape or a derived item shape obtained by modifying a part of the item shape, similar to the image matching processing unit 154. In this case, shapes can be assigned at once to predetermined items of multiple avatars having a specific relationship, such as a friend relationship, and the processing load can be reduced compared to the case where similar item shapes are acquired and matched separately for each item.

[0146] The additional information acquisition unit 160 acquires item surface information that can be reflected on the surface (appearance) of a specific item based on input information from a user. The item surface information may be information for setting or changing at least one of the pattern, fabric, decoration, and texture of the specific item. The method of acquiring the item texture may be as described above in relation to step S3200 in FIG. 9. The method of acquiring other item surface information may be similar. In addition, when acquiring multiple pieces of item surface information, they may be acquired simultaneously or separately.

[0147] The item surface processing unit 162 sets or changes at least one of the pattern, fabric, decoration, and texture of the predetermined item based on the item surface information. The method of setting or changing the texture of the predetermined item based on the item texture may be as described above in relation to step S4240 in Fig. 11. The setting or changing method related to the other item surface information may be similar.

[0148] Like the image matching processor 154, the item surface processor 162 may simultaneously set or change at least one of the patterns, fabrics, decorations, and textures of predetermined items for multiple avatars based on the acquired item surface information or a derived item shape obtained by modifying a part of the item surface information. In this case, it is possible to set or change at once the predetermined items of multiple avatars having a specific relationship, such as a friend relationship, and the processing load can be reduced compared to the case where similar item surface information is acquired and set or changed separately for each item.

[0149] The editing processor 164 edits the item shape based on information on the avatar to which the predetermined item is to be associated and information on the space to which the predetermined item is to be placed. For example, when the size of the avatar that matches the item shape is larger or smaller than the size of the avatar to which the shape is to be added, the editing processor 164 may change the item shape similarly according to such a size difference. Also, when the size of the space to which the predetermined item (e.g., abutment) is to be placed is larger or smaller than the size of the space to which the item to be added is to be placed, the editing processor 164 may change the item shape similarly according to such a size difference. This can increase the versatility of the item shape, and as a result, the processing load (for example, the load required for processing such as obtaining the item shape for each size difference) can be reduced.

[0150] Furthermore, the editing processor 164 edits the item surface information based on information about the avatar to be associated with the predetermined item. For example, when the size of the avatar that matches the decoration related to the item surface information is larger or smaller than the size of the avatar to be associated, the editing processor 164 may change the decoration related to the item surface information similarly according to the size difference. This can increase the versatility of the item surface information, and as a result, the processing load (for example, the load required for processing such as obtaining item surface information for each size difference) can be reduced.

[0151] Here, the editing processor 164 may evaluate the corresponding avatar 3D model for editing based on, for example, VRM, which is a common standard for 3D avatars. In this case, it is possible to obtain a predetermined item (and an avatar associated with the predetermined item) that can be used on multiple avatar platforms (various services).

[0152] The determination unit 166 determines whether or not the input information acquired from the user satisfies a predetermined condition. The predetermined condition may be set from various viewpoints. For example, the predetermined condition may include that the input information contains a predetermined prohibited word. The predetermined prohibited word may be as described above. The predetermined condition may be satisfied when the possibility of infringing another person's intellectual property right is higher than a predetermined standard, or when the possibility of violating public order and morals is higher than a predetermined standard. The predetermined condition may be set as appropriate by the operator of this service.

[0153] The parameter calculation unit 168 calculates the values ​​of parameters (examples of predetermined parameters) relating to various similarities such as the above-mentioned uniqueness value, similarity between predetermined items, similarity between specific images, similarity between item shapes, similarity between item textures, etc. Note that the similarity between predetermined items may be evaluated in a state where any one of the specific image, item shape, and item texture is reflected.

[0154] The method of calculating the various similarity-related parameters and their values ​​is arbitrary, but may be as described above with reference to FIG. 19, for example.

[0155] In the present embodiment, the parameter calculation section 168 includes a first parameter calculation section 1681 and a second parameter calculation section 1682.

[0156] The first parameter calculation unit 1681 calculates the similarity between the appearance elements between the image to be compared and the specific image to be determined. The method of calculating the similarity between the appearance elements may be, for example, as in step S1004 described above with reference to FIG.

[0157] Furthermore, the first parameter calculation unit 1681 may calculate the similarity between the appearance elements based on the attribute of a predetermined item to which the specific image is associated. For example, the first parameter calculation unit 1681 may calculate the similarity between the appearance elements based on the relationship between the attribute of an item to which the comparison target image is associated and the attribute of a predetermined item to which the specific image is associated. In this case, the first parameter calculation unit 1681 may calculate the similarity between the appearance elements in such a manner that the similarity between the appearance elements is higher when the respective attributes match, are very similar, or have a common point, compared to when they do not.

[0158] Furthermore, the first parameter calculation unit 1681 may change the calculation method of the similarity between the appearance elements according to the attribute of the predetermined item to which the specific image is associated. For example, if the predetermined item to which the specific image is associated is a three-dimensional item, the first parameter calculation unit 1681 may calculate the similarity between the appearance elements based on three-dimensional views from multiple viewpoints. Alternatively, even if the predetermined item to which the specific image is associated is not a three-dimensional item, if it is an avatar item, the first parameter calculation unit 1681 may calculate the similarity between the appearance elements based on three-dimensional views from multiple viewpoints in a state where the item is attached to the avatar.

[0159] The second parameter calculation unit 1682 calculates the similarity between the pieces of input information. The method of calculating the similarity between the pieces of input information may be, for example, the same as that in step S1008 described above with reference to FIG.

[0160] In this case, the value calculated by the first parameter calculation section 1681 and the value calculated by the second parameter calculation section 1682 may be used in combination as described above with reference to FIG.

[0161] The output processing unit 170 outputs the value of the parameter related to the similarity calculated by the parameter calculation unit 168. The method of outputting the value of the parameter related to the similarity is arbitrary, and may be, for example, an output for processing by the item management unit 174 or the like described below. Alternatively, the output of the value of the parameter related to the similarity may be realized by, for example, notifying the owner of the predetermined item to be judged.

[0162] The information management unit 172 manages (stores, extracts, etc.) the specific image and the like in association with the input information. Specifically, the information management unit 172 may generate and manage the specific image information (step S2210) described above with reference to Fig. 3. In addition, the information management unit 172 may generate and manage the item texture information (step S3210) described above with reference to Fig. 9, the item shape information (step S4210) described above with reference to Fig. 11, and the like. As described above, the various pieces of information generated and managed by the information management unit 172 can be suitably used for the parameter calculation unit 168 to calculate various similarity-related parameters.

[0163] When the input information satisfies a predetermined condition based on the determination result by the determination unit 166, the image management unit 173 prohibits or restricts the use or distribution in the virtual space of the specific image acquired based on the input information. As described above, the predetermined condition can be determined, for example, by the operator of the virtual space. This makes it possible to appropriately prevent situations in which specific images are randomly associated with items that can be used in the virtual space. Note that distribution in the virtual space may include sales in a market in the virtual space.

[0164] The item management unit 174 permits, prohibits, or restricts the use or distribution of each predetermined item in the virtual space based on the value of the predetermined parameter calculated by the parameter calculation unit 168. For example, when a specific image is associated with a predetermined item by the image association processing unit 154, the item management unit 174 permits, prohibits, or restricts the use or distribution of the predetermined item in the virtual space in the state in which the specific image is associated based on the value of the predetermined parameter calculated by the parameter calculation unit 168. Similarly, when a shape is assigned to a predetermined item by the shaping processing unit 158, the item management unit 174 permits, prohibits, or restricts the use or distribution of the predetermined item in the virtual space in the state in which the shape is assigned based on the value of the predetermined parameter calculated by the parameter calculation unit 168. Similarly, when item surface information is associated with a predetermined item by the item surface processing unit 162, the item management unit 174 permits, prohibits, or restricts the use or distribution of the predetermined item in the virtual space in the state in which the item surface information is associated based on the value of the predetermined parameter calculated by the parameter calculation unit 168.

[0165] Furthermore, like the image management unit 173, the item management unit 174 may prohibit or restrict the use or distribution in the virtual space of an item associated with a specific image obtained based on the input information when the input information satisfies a predetermined condition based on the judgment result by the judgment unit 166.

[0166] The token management unit 176 issues and manages tokens such as non-fungible tokens (NFTs) for a predetermined item. The method of issuing an NFT for a predetermined item may be as described in step S5250 above with reference to Fig. 18. In addition, the token management unit 176 may record the owner and the transfer of ownership as management other than issuance, and may copy or destroy the tokens by application for a fee or free of charge in a market, smart contract, or distributed processing module outside the system 1.

[0167] In addition, like the image management unit 173, the token management unit 176 may prohibit or restrict the issuance and distribution of a token based on a specific image obtained based on the input information when the input information satisfies a predetermined condition based on the judgment result by the judgment unit 166.

[0168] The contest processing unit 178 executes processing related to holding various contests in the virtual space. The various contests are arbitrary and may include a contest related to the predetermined items as described above. FIG. 22 is an image diagram of the contest. FIG. 22 shows a form of a fashion contest, in which a plurality of users are showing off the predetermined items on a stage in the virtual space via avatars A11, A12, and A13 wearing the predetermined items to which the specific images are associated.

[0169] Regarding the predetermined item to which the specific image is associated by the image association processing unit 154, or the avatar to which the predetermined item is associated, evaluation results (e.g., voting results) from multiple users in the virtual space may be collected. Then, the contest processing unit 178 may execute various processes such as announcing rankings and awarding prizes to winners, etc., based on the evaluation results. In this case, artificial intelligence based on a given logic may be used instead of or in addition to the evaluation results by multiple users. For example, in a contest in which a certain theme or mission is presented, whether the theme matches or the mission has been cleared may be determined based on artificial intelligence. More specifically, for example, in the case of a theme of "cool adults," parameters such as the degree of maturity, coolness, and cuteness of the predetermined item worn by the avatar may be set, and the superiority or inferiority may be determined by the artificial intelligence based on the values ​​of these parameters. In this case, the artificial intelligence may be constructed by learning past evaluation results by humans (e.g., reliable evaluators or the management side).

[0170] The evaluation information storage unit 190 may store the various types of information described above that are generated and managed by the item management unit 174.

[0171] Information required to realize the various processes described above may be stored for each user (e.g., for each user ID) in the user information storage unit 192. For example, information on a corresponding avatar (e.g., a VRM file) and information on various predetermined items owned by each user may be stored.

[0172] 20, the image matching processing unit 154, the shaping processing unit 158, and the item surface processing unit 162 each execute processing independently of one another, but this is not limited to the above. That is, any combination of two or more of the image matching processing unit 154, the shaping processing unit 158, and the item surface processing unit 162 may function simultaneously. For example, the image matching processing unit 154 and the shaping processing unit 158 ​​may function simultaneously to generate a predetermined item that simultaneously reflects the item shape and specific image obtained in the above-mentioned manner.

[0173] Although each embodiment has been described in detail above, the present invention is not limited to a specific embodiment, and various modifications and changes are possible within the scope of the claims. In addition, it is also possible to combine all or a plurality of the components of the above-described embodiments.

[0174] For example, in the above-described embodiment, the specific image, the item shape, and the item texture are acquired independently of each other, but this is not limited to this. That is, any combination of two or more of the specific image, the item shape, and the item texture may be acquired simultaneously. In this case, the machine learning model may also be constructed in an integrated manner.

[0175] In addition, the following supplementary notes are disclosed regarding the above embodiment.

[0176] (Appendix 1) A user input acquisition unit that acquires a predetermined input from a user; an image acquisition unit that acquires a specific image obtained by inputting the predetermined input into a first machine learning model constructed by artificial intelligence; An information processing system comprising: an association processing unit that associates the specific image with a predetermined item that can be used in a virtual space.

[0177] (Appendix 2) The predetermined item is rendered visibly in a virtual space by reflecting the specific image on a corresponding pattern; The information processing system described in Appendix 1, further comprising a pattern generation unit that generates the pattern using a machine learning model constructed by artificial intelligence.

[0178] The inventions described in the claims of the original application of this application are set forth below. [1] A user input acquisition unit that acquires a predetermined input from a user; an image acquisition unit that acquires a specific image obtained by inputting the predetermined input into a first machine learning model constructed by artificial intelligence; An information processing system comprising: an association processing unit that associates the specific image with a predetermined item that can be used in a virtual space. [2] The information processing system according to [1], wherein the specified items include at least one of an item that can be associated with an avatar in a virtual space and an item that can be placed in the virtual space. [3] a shape information acquisition unit that acquires shape information of the predetermined item obtained by inputting the predetermined input into a second machine learning model constructed by artificial intelligence; The information processing system according to [1], further comprising a shaping processing unit that shapes the specified item based on the shape information. [4] an additional information acquisition unit that utilizes a third machine learning model constructed by artificial intelligence to acquire item surface information obtained by inputting the predetermined input into the third machine learning model; The information processing system described in [1], further comprising an item surface processing unit that sets or changes at least one of the pattern, fabric, decoration, and texture of the specified item based on the item surface information. [5] the predetermined item includes at least one of an item that can be associated with an avatar in a virtual space and an item that can be placed in the virtual space; The information processing system described in [3], further comprising an editing processing unit that edits the shape information based on information regarding an avatar to which the specified item is to be associated, or information regarding the space to which the specified item is to be placed. [6] the predetermined item includes an item that can be associated with an avatar in a virtual space; The information processing system described in [4], further comprising an editing processing unit that edits the item surface information based on information regarding the avatar to which the specified item is to be associated. [7] The information processing system according to [1], wherein the specified input includes at least one of text, symbols, emojis, numbers, colors, textures, images, sounds, gestures, and any combination of two or more of these. [8] The information processing system described in [1] further includes a contest processing unit that collects evaluation results from a plurality of users in a virtual space regarding the specified item to which the specific image is associated by the association processing unit, or the avatar to which the specified item is associated. [9] The information processing system according to [1], wherein the association processing unit simultaneously associates the specific image or a derivative image obtained by modifying a part of the specific image with the specified item relating to a plurality of avatars.

[10] a calculation unit that calculates a value of a predetermined parameter related to a similarity between the predetermined item to which the specific image is associated by the association processing unit and another item that can be used in a virtual space; The information processing system according to [1], further comprising: an output processing unit that outputs the value of the predetermined parameter calculated by the calculation unit.

[11] The information processing system described in

[10] , wherein the calculation unit calculates the value of the specified parameter related to one of the specified items to which the specific image is associated based on the specific image associated with the one specified item and the specified input used to acquire the specific image.

[12] The information processing system according to

[11] , wherein the calculation unit further calculates the value of the specified parameter related to one of the specified items to which the specific image corresponds based on attributes of the one of the specified items.

[13] the calculation unit includes a first calculation unit that calculates a value of a first parameter related to a similarity between the specific image and an image associated with the other item; The information processing system according to

[11] , wherein the value of the specified parameter includes the value of the first parameter calculated by the first calculation unit or a value based thereon.

[14] The information processing system according to

[13] , wherein the first calculation unit calculates the value of the first parameter based on at least one of color, texture, and pattern.

[15] The information processing system according to

[13] , wherein the first calculation unit calculates the value of the first parameter based on three-dimensional views from multiple viewpoints.

[16] the calculation unit includes a second calculation unit that calculates a value of a second parameter related to a similarity between the predetermined input used to acquire the specific image and another input corresponding to the predetermined input used to generate an image associated with the other item; The information processing system according to

[10] , wherein the value of the specified parameter includes the value of the second parameter calculated by the second calculation unit or a value based thereon.

[17] The information processing system of

[16] , wherein the second calculation unit calculates the value of the second parameter based on a relationship between text included in the specified input and text included in the other input.

[18] the predetermined input and the other input each further include a seed value of a random number; The information processing system of

[16] , wherein the second calculation unit calculates the value of the second parameter based on a relationship between the seed value included in the specified input and the seed value included in the other input.

[19] The information processing system described in

[10] further comprises an item management unit that permits, prohibits, or restricts the use or distribution in a virtual space of the specified item to which the specific image is associated by the matching processing unit based on the value of the specified parameter calculated by the calculation unit.

[20] The information processing system according to any one of [1] to

[17] , further comprising an information management unit that manages the specific image or the specific item to which the specific image is associated in correspondence with the specified input. [twenty one] A determination unit that determines whether the predetermined input satisfies a predetermined condition, The information processing system of any one of [1] to

[17] , further comprising an image management unit that, when the specified input satisfies the specified condition, prohibits or restricts the use or distribution in a virtual space of the specific image obtained based on the specified input. [twenty two] The information processing system described in

[21] , wherein the specified condition is satisfied when the possibility of infringing another person's intellectual property right is higher than a specified standard, or when the possibility of violating public order and morals is higher than a specified standard. [twenty three] An information processing system described in any one of [1] to

[17] , further comprising a token management unit that issues and manages non-fungible tokens based on the specific image or the specified item to which the specific image is associated. [twenty four] Obtaining a predetermined input from a user; Using a first machine learning model constructed by artificial intelligence, a specific image is obtained by inputting the predetermined input into the first machine learning model; An information processing method executed by a computer, comprising: associating the specific image with a predetermined item available in a virtual space. [twenty five] Obtaining a predetermined input from a user; Using a first machine learning model constructed by artificial intelligence, a specific image is obtained by inputting the predetermined input into the first machine learning model; The specific image is associated with a predetermined item that can be used in the virtual space. A program that causes a computer to carry out processing. [Explanation of symbols]

[0179] 1 System 3. Network 5. Blockchain Network 10. Server device 11 Server Communication Section 12 Server memory section 13 Server control unit 20 Terminal Equipment 21 Terminal communication unit 22 Terminal memory section 23 Display section 24 Input section 25 Terminal control unit 150 Operation input acquisition unit 152 Image acquisition unit 154 Image matching processing unit 156 Shape information acquisition unit 158 Shaping Processing Section 160 Additional information acquisition unit 162 Item Surface Treatment 164 Editing Processing Section 166 Judgment section 168 Parameter Calculation Unit 1681 1st parameter calculation unit (1st calculation unit) 1682 second parameter calculation unit (second calculation unit) 170 Output Processing Section 172 Information Management Department 173 Image Management Department 174 Item Management Department 176 Token Management Unit 178 Contest Processing Section 190 Evaluation information storage unit 192 User information storage unit

Claims

1. A user input acquisition unit that acquires a predetermined input from a user; an image acquisition unit that acquires a specific image obtained by inputting the predetermined input into a first machine learning model using a first machine learning model that is constructed by artificial intelligence and generates and outputs an image that reflects a context based on input information; a matching processing unit that matches the specific image with a predetermined item that can be used in a virtual space; An information processing system comprising: a calculation unit that calculates a value of a predetermined parameter related to the similarity between the specified item to which the specific image is associated by the association processing unit and other items available in a virtual space.

2. The information processing system according to claim 1 , wherein the predetermined items include at least one of an item that can be associated with an avatar in a virtual space and an item that can be placed in the virtual space.

3. a shape information acquisition unit that acquires shape information of the predetermined item obtained by inputting the predetermined input into a second machine learning model, the second machine learning model being constructed by artificial intelligence and generating and outputting an item shape based on input information; The information processing system according to claim 1 , further comprising a shaping processing unit that shapes the predetermined item based on the shape information.

4. an additional information acquisition unit that acquires item surface information obtained by inputting the predetermined input into a third machine learning model, the third machine learning model being constructed by artificial intelligence and generating and outputting an item texture based on input information; The information processing system according to claim 1 , further comprising an item surface processing unit that sets or changes at least one of a pattern, a fabric, a decoration, and a texture of the predetermined item based on the item surface information.

5. the predetermined item includes at least one of an item that can be associated with an avatar in a virtual space and an item that can be placed in the virtual space; The information processing system according to claim 3 , further comprising an editing processing unit that edits the shape information based on information on an avatar to be associated with the specified item, or information on a space to be placed in the specified item.

6. the predetermined item includes an item that can be associated with an avatar in a virtual space, The information processing system according to claim 4 , further comprising an editing processing unit that edits the item surface information based on information about an avatar to be associated with the predetermined item.

7. The information processing system according to claim 1 , wherein the predetermined input includes at least one of a text, a symbol, an emoji, a number, a color, a texture, an image, a sound, a gesture, and a combination of any two or more of these.

8. The information processing system according to claim 1 , further comprising a contest processing unit that collects evaluation results from a plurality of users in a virtual space regarding the specified item to which the specific image is associated by the association processing unit, or an avatar to which the specified item is associated.

9. The information processing system according to claim 1 , wherein the association processing unit simultaneously associates the specific image or a derivative image obtained by modifying a part of the specific image with the predetermined item related to a plurality of avatars.

10. The information processing system according to claim 1 , further comprising an output processing unit that outputs the value of the predetermined parameter calculated by the calculation unit.

11. The information processing system of claim 1, wherein the calculation unit calculates the value of the specified parameter related to one of the specified items to which the specific image corresponds based on the specific image corresponding to the one of the specified items and the specified input used to obtain the specific image.

12. The information processing system according to claim 11 , wherein the calculation unit calculates the value of the predetermined parameter related to the one predetermined item to which the specific image is associated, further based on an attribute of the one predetermined item.

13. the calculation unit includes a first calculation unit that calculates a value of a first parameter related to a similarity between the specific image and an image associated with the other item; The information processing system according to claim 1 , wherein the value of the predetermined parameter includes the value of the first parameter calculated by the first calculation unit or a value based thereon.

14. The information processing system according to claim 13 , wherein the first calculation unit calculates the value of the first parameter based on at least one of a color, a texture, and a pattern.

15. The information processing system according to claim 13 , wherein the first calculator calculates the value of the first parameter based on three-dimensional views from a plurality of viewpoints.

16. the calculation unit includes a second calculation unit that calculates a value of a second parameter related to a similarity between the predetermined input used to acquire the specific image and another input corresponding to the predetermined input used to generate an image associated with the other item; The information processing system according to claim 1 , wherein the value of the predetermined parameter includes the value of the second parameter calculated by the second calculation unit or a value based thereon.

17. The information processing system according to claim 16 , wherein the second calculation unit calculates the value of the second parameter based on a relationship between text included in the predetermined input and text included in the other input.

18. the predetermined input and the other input each further include a seed value of a random number; The information processing system according to claim 16 , wherein the second calculation unit calculates the value of the second parameter based on a relationship between the seed value included in the predetermined input and the seed value included in the other input.

19. The information processing system according to claim 10, further comprising an item management unit that permits, prohibits or restricts the use or distribution in a virtual space of the specified item to which the specific image is associated by the association processing unit based on the value of the specified parameter calculated by the calculation unit and output by the output processing unit.

20. The information processing system according to claim 1 , further comprising an information management unit that manages the specific image or the specific item with which the specific image is associated, in association with the specific input.

21. A determination unit that determines whether the predetermined input satisfies a predetermined condition, An information processing system as claimed in any one of claims 1 to 17, further comprising an image management unit that, when the specified input satisfies the specified condition, prohibits or restricts the use or distribution in a virtual space of the specific image obtained based on the specified input.

22. 22. The information processing system according to claim 21, wherein the predetermined condition is satisfied when a possibility of infringing an intellectual property right of another person is higher than a predetermined standard, or when a possibility of being contrary to public order and morals is higher than a predetermined standard.

23. The information processing system according to claim 1 , further comprising a token management unit that issues and manages a non-fungible token based on the specific image or the specified item to which the specific image is associated.

24. A user input acquisition step of acquiring a predetermined input from a user; an image acquisition step of acquiring a specific image obtained by inputting the predetermined input into a first machine learning model using a first machine learning model that is constructed by artificial intelligence and generates and outputs an image that reflects a context based on input information; a matching process step of matching the specific image with a predetermined item that can be used in a virtual space; An information processing method executed by a computer, comprising: a calculation step of calculating a value of a predetermined parameter related to the similarity between the specified item to which the specific image is associated by the association processing step and other items available in a virtual space.

25. A user input acquisition process for acquiring a predetermined input from a user; an image acquisition process that acquires a specific image obtained by inputting the predetermined input into a first machine learning model using a first machine learning model that is constructed by artificial intelligence and generates and outputs an image that reflects a context based on input information; a matching process for matching the specific image with a predetermined item that can be used in a virtual space; A program that causes a computer to execute a calculation process that calculates the value of a specified parameter related to the similarity between the specified item to which the specific image is associated by the matching process and other items that can be used in a virtual space.

Images