System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to upload a face photo; means for storing the uploaded face photo and a prompt; means for generating a virtual image based on the stored face photo and prompt; means for providing the generated virtual image to an enterprise; means for tracking usage of the provided virtual image; and means for redeeming a data supplier based on the tracked usage.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, virtual person images generated using artificial intelligence technology have been widely used in advertising and marketing. However, these images inevitably face issues regarding the rights of the training data. This has led to a growing demand for ways to avoid the risks associated with their use in advertising media. It is also difficult to build a transparent system that pays fair compensation to individuals for the data they provide. This has created a need for safe virtual person images with clear rights, free from opacity and scandal risk. [Means for solving the problem]

[0005] The present invention provides a system including a means for a user to upload a facial photo, a means for saving the uploaded facial photo and a prompt, a means for generating a virtual image based on the saved facial photo and prompt, a means for providing the generated virtual image to a company, a means for tracking the usage of the provided virtual image, and a means for providing compensation to a data provider based on the tracked usage. This system allows a user to provide a facial photo and a virtual image generated based on the provided photo to be used safely for advertising. Furthermore, by tracking the usage of the provided data and providing appropriate compensation to the data provider based on the tracking, transparency and fairness can be ensured.

[0006] A "User" is an individual or legal entity that has the right to provide a facial photograph to the system.

[0007] A "face photo" is image data that a user uploads to the system and is stored with the prompt.

[0008] A "prompt" is text information that indicates specific instructions or settings that the user enters along with a facial photo.

[0009] A "virtual image" is a fictional image of a person based on a user's facial photograph, generated using AI technology.

[0010] "Company" means a legal entity that receives generated virtual images from the system for use in advertising and marketing.

[0011] "Consideration" means compensation or reward paid to a data provider based on the use of the data provided or the virtual image generated.

[0012] The "storage means" refers to a system or software for accumulating and storing facial photographs and prompts uploaded by users in a database.

[0013] The "generator" is an AI algorithm and computer program that creates a virtual image based on a stored facial photograph and prompts.

[0014] "Providing means" refers to a system or service for distributing or providing the generated virtual images to businesses.

[0015] "Tracking methods" are systems or software used to monitor and collect data about the use of provided virtual images.

[0016] A "rebate mechanism" is a system or service that distributes fair compensation to data providers based on tracked usage. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The system of this invention performs a series of processes: users upload facial photographs, companies are provided with virtual images generated from those photographs, usage is tracked, and compensation is paid to the data providers. A specific embodiment of the system is described below.

[0039] 1. User provides face photo

[0040] A user logs in to the system and uploads a facial photo. On the facial photo upload screen, the user selects their own facial photo file and enters prompts (e.g., output ratio and desired features). These data are received by the system and stored on the server.

[0041] example:

[0042] User A logs in to the system, selects his or her own face photo, and sets the "output ratio" to 50%.

[0043] User A clicks the "Upload" button to send the photo and prompt to the server.

[0044] The server stores the received images and prompts in a database.

[0045] 2. Generating virtual images using AI models

[0046] The server uses AI technology to generate a virtual person image based on the stored facial photo and prompts. During the generation process, the image is adjusted according to the prompts' specified features and output ratios. The generated virtual image is also stored in the database.

[0047] example:

[0048] The server extracts the face photo and prompt from the database and inputs them into the AI ​​model.

[0049] The AI ​​model generates a virtual person image from User A's facial photo with an output ratio of 50%.

[0050] The server stores the generated virtual images in a database.

[0051] 3. Providing the generated images to companies

[0052] When a company needs a virtual person image, the server receives the request from the company and searches for and provides virtual images that meet the company's requirements. The images presented to the company are strictly managed by the system and provided after appropriate authentication.

[0053] example:

[0054] Company B requests virtual images for a new advertising campaign.

[0055] The server receives Company B's requirements and searches the database for matching images.

[0056] The server provides Company B with a link to download the proposed virtual image.

[0057] 4. Usage tracking and rewards

[0058] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this, it pays compensation to the users who provide the data. The compensation is calculated based on the output rate of the provided data and the frequency of use of the generated virtual images.

[0059] example:

[0060] The server monitors the usage of virtual images used in Company B's advertisements.

[0061] The server aggregates the sales data obtained from Company B and calculates the reward for User A based on the output ratio of the facial components.

[0062] The server transfers the reward to User A's account and displays the reward details on their personal page.

[0063] This system allows users to provide a photograph of their face, and the virtual person image generated based on that photograph is used safely for advertising purposes with clear rights. Furthermore, users are compensated appropriately for the data they provide, ensuring transparency and fairness.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] The user logs into the system.

[0067] Step 2:

[0068] The server verifies the user's authentication information and checks the database to ensure the user is a legitimate user.

[0069] Step 3:

[0070] The user moves to the face photo upload screen and selects a face photo file.

[0071] Step 4:

[0072] The user enters the prompts (output ratio and desired characteristics) and clicks the "Upload" button.

[0073] Step 5:

[0074] The server receives the uploaded face photo and prompt and stores them in a database.

[0075] Step 6:

[0076] The server uses an AI model to generate a virtual persona based on the stored facial photo and prompts.

[0077] Step 7:

[0078] The server stores the generated virtual person images in a database.

[0079] Step 8:

[0080] The server receives requests for virtual persona images from businesses.

[0081] Step 9:

[0082] The server searches the database for matching virtual person images based on the company's request conditions.

[0083] Step 10:

[0084] The server selects virtual person images to propose to companies and provides them with downloadable links.

[0085] Step 11:

[0086] The server monitors the usage of the provided virtual person images.

[0087] Step 12:

[0088] The server aggregates sales data obtained from companies and calculates rewards based on the output ratio of the user's facial components.

[0089] Step 13:

[0090] The server transfers the calculated reward to the user's account.

[0091] Step 14:

[0092] The server displays the reward details on the user's My Page.

[0093] Example 1

[0094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0095] In recent years, the creation and commercial use of virtual person images has increased, but there is currently no system in place to securely manage facial photos provided by users, ensure transparency regarding the use of the generated virtual images, or provide fair compensation to users. Therefore, there is a need to develop a system that allows companies to efficiently use virtual images while maintaining a balance between protecting user privacy and providing compensation.

[0096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0097] In this invention, the server includes a means for users to upload image data, a means for storing the uploaded image data and instruction information, a means for generating a virtual person image based on the stored image data and instruction information, a means for providing the generated virtual person image to an organization, a means for tracking the usage of the provided virtual person image, and a means for providing compensation to the data provider based on the tracked usage. This allows users to safely provide their own facial photographs, and the virtual image generated based on them is used appropriately, enabling transparency and compensation to users. Furthermore, companies can effectively use high-quality virtual person images.

[0098] A "user" is a person who provides a facial photograph and instruction information to the system and receives payment for the use of the generated virtual person image.

[0099] "Image data" refers to facial photographs and other visual information that users upload to the system.

[0100] "Instruction information" refers to information related to prompt statements and output settings that the user inputs in relation to image data.

[0101] A "virtual person image" refers to an image of a non-existent person that is generated based on image data and instruction information.

[0102] "Server" refers to the equipment and programs that receive and store image data and instruction information, generate virtual person images, and provide them to companies.

[0103] "Organization" refers to a company or organization that commercially uses the generated virtual person images.

[0104] "Usage" refers to data used to track how the provided virtual person images are used by companies and organizations.

[0105] "Rebate" refers to the process of providing compensation or other benefits to users based on their use of the virtual person image.

[0106] The system of this invention performs a series of processes: a user uploads image data (a facial photograph), a virtual person image generated based on that image data is provided to a company, usage is tracked, and compensation is paid to the data provider. A specific embodiment of the system is described below.

[0107] 1. User-provided image data

[0108] Users log in to the system using their own terminals, entering their ID and password on the login page and undergoing authentication.

[0109] The user accesses the image data upload page, clicks the "Select File" button, and selects a photo of their own face (e.g., "my_photo.jpg").

[0110] The user inputs a prompt as instruction information related to the image data, such as "Output ratio 50%, desired feature: smiling face."

[0111] When the user clicks the "Upload" button, the image data and the prompt text are sent to the server.

[0112] 2. Data storage by the server

[0113] The server receives the image data and prompt text sent by the user. The received data is stored in the image storage and the database. The image data is stored in the image storage, and the prompt text and image file paths are stored in the database.

[0114] 3. Generation of Virtual Person Images

[0115] The server extracts the stored image data and prompt sentences from the database, and the extracted data is input to a generative AI model (e.g., StyleGAN).

[0116] The AI ​​model processes image data according to instructions and generates a virtual person image with the specified characteristics.

[0117] The generated virtual person image is stored in the database again by the server.

[0118] 4. Provision to companies

[0119] A company logs in to the system and requests a virtual person image. Based on the criteria submitted by the company (e.g., "male in his 30s, output ratio 50%, smiling"), the server searches the database for a matching image.

[0120] When a virtual person image that matches the criteria is found, the server provides the company with a download link.

[0121] 5. Usage tracking and rebates

[0122] The server monitors how companies use virtual person images, tracking company advertisements and usage reports, and collecting usage data.

[0123] The server calculates the rewards for users based on sales data from companies, and the rewards are calculated based on frequency of use and output ratio.

[0124] Rewards will be transferred to the user's account, and the user can check the details of the reward on their My Page.

[0125] This system allows users to safely provide their own facial photographs, and the virtual person images generated based on them are used appropriately, ensuring transparency and fairness. It also allows companies to efficiently use high-quality virtual person images.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1: User provides image data

[0128] Input: The user logs in to the system and selects a face photo file (e.g., "my_photo.jpg") and a prompt statement (e.g., "50% output ratio, desired feature: smile").

[0129] Operation: When the user clicks the "Upload" button, the image data and the prompt text are sent to the server. The data sent from the user's device is received by the server as an HTTP request.

[0130] Output: The server receives the image data and the prompt.

[0131] Step 2: The server saves the data

[0132] Input: The image data received in step 1 and the prompt text.

[0133] Operation: The server saves the image data to the image storage and stores the prompt text and image file path in the database. This includes the process of creating an entry in the database and recording the physical storage location of the facial photo data.

[0134] Output: The image data is saved to the image storage, and the prompt text and the path to the image file are saved to the database.

[0135] Step 3: The server uses the AI ​​model to generate the image

[0136] Input: Image data retrieved from the database and prompt text.

[0137] How it works: The server inputs image data and a prompt into an AI generative model (e.g., StyleGAN). The model generates a virtual person image according to the instructions. Here, the AI ​​model extracts features from the facial photo and processes them according to the prompt.

[0138] Output: The generated virtual person image is returned to the server.

[0139] Step 4: The server saves the generated image

[0140] Input: The virtual person image generated in step 3.

[0141] Operation: The server saves the generated virtual person image in the image storage and saves the path of the generated image in the database.

[0142] Output: The generated virtual person image is saved in the image storage, and its path is recorded in the database.

[0143] Step 5: The company requests images

[0144] Input: The company logs into the system and enters the required conditions (e.g., "male in his 30s, output ratio 50%, smiling face").

[0145] How it works: The server receives a request from a company and searches its database for images that match the criteria.

[0146] Output: As a search result, a list of virtual person images that match the conditions is extracted.

[0147] Step 6: The server serves the image to the company

[0148] Input: Virtual person images that match the criteria found in step 5.

[0149] How it works: The server provides the company with a download link for the image, which the company can then use to retrieve the image.

[0150] Output: A download link accessible to the company.

[0151] Step 7: The server tracks usage

[0152] Input: Information on the virtual person image used by the company.

[0153] How it works: A server monitors a company's use of images in advertising and collects usage data, including recording data such as when, where, and how often the images are used.

[0154] Output: Usage data is recorded in a database.

[0155] Step 8: The server calculates the payment and returns it to the user

[0156] Inputs: Usage data collected in step 7 and sales data from the company.

[0157] How it works: The server calculates the user's reward based on the frequency of use and output rate. The calculated reward is transferred to the user's account. The user can check the reward details on their My Page.

[0158] Output: Reward is transferred to the user and a reward statement is displayed.

[0159] (Application example 1)

[0160] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0161] In recent years, the generation and use of virtual images based on user-provided facial photographs has many potential applications. However, the way these images are used and how users are compensated remains unclear, making it difficult to gain user trust. Furthermore, there is a lack of an effective system for easily managing the generation and usage of virtual images. Therefore, there is a need for an environment where users can provide facial photographs with confidence and where companies can efficiently use virtual images.

[0162] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0163] In this invention, the server includes means for users to upload facial photographs, means for saving the uploaded facial photographs and prompts, means for generating virtual images based on the saved facial photographs and prompts, means for providing the generated virtual images to companies, means for tracking usage of the provided virtual images, means for paying compensation to users based on the tracked usage, and means for managing the generation and usage of virtual images via a smartphone application. This allows users to visualize how their provided data is used and receive appropriate compensation.

[0164] "User" refers to a person who uses this system to upload a facial photo and generate a virtual image.

[0165] "Facial photo" refers to image data of a user's face.

[0166] A "prompt" refers to text data used to specify the characteristics and output ratio of a virtual image generated based on a facial photograph.

[0167] "Virtual Image" refers to a virtual person image generated by an artificial intelligence model based on a user's facial photograph and prompts.

[0168] "Company" refers to a corporation or organization that uses the generated virtual images for purposes such as advertising materials.

[0169] "Smartphone application" refers to software that runs on a smartphone and provides the functions of this system.

[0170] "Server" refers to a computer system that executes the functions of this system and stores and processes data.

[0171] "Consideration" refers to the compensation paid for the use of a user's facial photograph.

[0172] This invention is a system that allows users to upload a facial photo, generates a virtual image based on the photo using an AI model, and provides it to companies. It also tracks the usage of the provided virtual image and can compensate users for it. These functions can be easily managed using a smartphone application.

[0173] Hardware and Software Configuration

[0174] Hardware:

[0175] Smartphone: A device that allows users to upload photos of their face and generate and manage virtual images.

[0176] Server: A set of computer systems that store facial photos and prompts, generate virtual images, and track usage.

[0177] software:

[0178] requests: A Python library for sending HTTP requests, uploading and retrieving data.

[0179] PIL (Python Imaging Library): A Python library for manipulating and processing image data.

[0180] Overall system flow

[0181] 1. Upload a photo of your face

[0182] A user logs in to the system using a smartphone application and uploads a facial photo. On the upload screen, the user enters the facial photo file along with prompts (e.g., output ratio and desired features). This data is sent to the server via an HTTP request and stored on the server.

[0183] Examples:

[0184] The user selects a photo of their face, enters prompts such as "50% output ratio" and "enhance brightness and contrast," and then uploads it.

[0185] 2. Virtual Image Generation

[0186] The server uses a generative AI model to generate a virtual image based on the stored facial photo and prompts. During the generation process, the image is adjusted according to the prompts, based on the specified features and output ratio. The generated virtual image is also stored in a database.

[0187] Examples:

[0188] The server extracts a face photo and prompts from the database and generates a virtual image with slightly enhanced brightness and contrast at a 50% output ratio according to the prompts.

[0189] 3. Providing the generated images to companies

[0190] When a company needs a virtual image, the server receives the request, searches for and provides virtual images that match the company's requirements, and the images are provided after strict authentication.

[0191] Examples:

[0192] Businesses request virtual images for new advertising campaigns, and the server provides the businesses with images that match their criteria.

[0193] 4. Usage tracking and rewards

[0194] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this, the server reimburses users. The reimbursement is calculated based on the output rate of the provided data and the frequency of use of the generated virtual images.

[0195] Examples:

[0196] The server tracks the usage of virtual images used in corporate advertisements and rewards users based on sales data obtained from the companies.

[0197] Prompt Sentence Examples

[0198] "Please use a face photo at 70% output ratio for advertising materials, and generate it with slightly enhanced brightness and contrast."

[0199] This system allows users to provide their own facial photos with peace of mind and receive compensation in a transparent and fair environment. It also enables businesses to efficiently obtain high-quality advertising materials.

[0200] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0201] Step 1:

[0202] A user logs in to the system using a smartphone application. They select a face photo and input prompts (e.g., output ratio and desired features). The input data (face photo file and prompt) is sent to the server as an HTTP request. The server receives it and stores it in a database. Based on the input data, the face photo and prompt are appropriately saved.

[0203] Step 2:

[0204] The server extracts the stored facial photo and prompt. The facial photo and prompt are input into the generation AI model. The AI ​​model processes the data (using image processing technology) to generate a virtual image. Specifically, it generates a virtual image that reflects the output ratio and specified features according to the prompt. This generated virtual image is then stored back in the database.

[0205] Step 3:

[0206] A company sends a request to the server to use a virtual image. The server searches its database for virtual images that match the company's criteria (e.g., type of advertising campaign or image characteristics). It selects the appropriate virtual image from the search results and provides it to the company. After authentication and appropriate data filtering, it sends the company a downloadable link.

[0207] Step 4:

[0208] The server monitors how the provided virtual images are used by companies. Specifically, it periodically collects and analyzes data on the companies' advertising campaigns and sales. Based on the analysis results, it evaluates the frequency of use of the virtual images and their contribution to sales. Based on this evaluation, it calculates the remuneration for the users.

[0209] Step 5:

[0210] The server returns rewards to users based on their usage. Specifically, it calculates an appropriate reward amount for each user based on sales data and frequency of use. The calculated reward is transferred to the user's account and displayed as a reward statement on the user's My Page in the smartphone application. Users can check the reward details on the application.

[0211] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0212] The system of the present invention performs a series of processes: users upload facial photos, virtual images generated from those photos are provided to companies, usage is tracked, and compensation is paid to the data provider. Furthermore, the present invention can generate more personalized virtual images by combining an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention are described in detail below.

[0213] 1. User provides face photo

[0214] A user logs in to the system and uploads a facial photo. On the facial photo upload screen, the user selects their own facial photo file and enters prompts (e.g., output ratio and desired features). These data are received by the system and stored on the server.

[0215] example:

[0216] User A logs in to the system, selects his or her own face photo, and sets the "output ratio" to 50%.

[0217] User A clicks the "Upload" button to send the photo and prompt to the server.

[0218] The server stores the received images and prompts in a database.

[0219] 2. Emotion Recognition by Emotion Engine

[0220] The server uses an emotion engine to recognize the user's emotions from the facial photo uploaded by the user. The recognized emotions are reflected in the prompts, allowing the user to reflect the facial expressions and emotions intended by the user in the virtual image.

[0221] example:

[0222] The server uses an emotion engine to recognize User A's emotions (e.g., happiness, surprise, sadness) from the uploaded facial photo.

[0223] Based on the perceived emotion, "happiness" was added to the prompt.

[0224] The server updates the prompt with the emotion and saves it in the database.

[0225] 3. Generating virtual images using AI models

[0226] The server uses AI technology to generate a virtual person image based on the stored facial photo and updated prompts. During the generation process, the image is adjusted according to the prompts to reflect the specified characteristics and emotions. The generated virtual image is also stored in a database.

[0227] example:

[0228] The server inputs a facial photo into the AI ​​model based on the updated prompt, and generates a virtual person image with an output ratio of 50% and reflecting the emotion of "happiness."

[0229] The server stores the generated virtual images in a database.

[0230] 4. Providing the generated images to companies

[0231] When a company needs a virtual person image, the server receives the request from the company and searches for and provides virtual images that meet the company's requirements. The images presented to the company are strictly managed by the system and provided after appropriate authentication.

[0232] example:

[0233] Company B requests virtual images for a new advertising campaign.

[0234] The server receives Company B's requirements and searches the database for matching images.

[0235] The server provides Company B with a link to download the proposed virtual image.

[0236] 5. Usage tracking and rewards

[0237] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this data, it pays compensation to the data provider, the user. Compensation is calculated based on the output ratio of the provided data, the frequency of use of the generated virtual image, and the impact of emotional reflection.

[0238] example:

[0239] The server monitors the usage of virtual images used in Company B's advertisements.

[0240] The server aggregates the sales data obtained from Company B and calculates the reward for User A based on the output ratio of facial components and the degree of influence of emotional reflection.

[0241] The server transfers the reward to User A's account and displays the reward details on their personal page.

[0242] This system allows users to provide a photo of their face, and the virtual person image generated based on that photo can be used safely for advertising purposes with clear rights. Furthermore, users can receive appropriate compensation for the data they provide, and more personalized advertising can be achieved by reflecting emotions.

[0243] The processing flow will be explained below.

[0244] Step 1:

[0245] The user logs into the system.

[0246] Step 2:

[0247] The server verifies the user's authentication information and checks the database to ensure the user is a legitimate user.

[0248] Step 3:

[0249] The user moves to the face photo upload screen and selects a face photo file.

[0250] Step 4:

[0251] The user enters the prompts (output ratio and desired characteristics) and clicks the "Upload" button.

[0252] Step 5:

[0253] The server receives the uploaded face photo and prompt and stores them in a database.

[0254] Step 6:

[0255] The server uses an emotion engine to recognize the user's emotions from the stored facial photographs.

[0256] Step 7:

[0257] The server updates the prompt based on the recognized emotion and stores it in a database.

[0258] Step 8:

[0259] The server inputs the updated prompt and facial photo into the AI ​​model to generate a virtual person image.

[0260] Step 9:

[0261] The server stores the generated virtual person images in a database.

[0262] Step 10:

[0263] The server receives requests for virtual persona images from businesses.

[0264] Step 11:

[0265] The server searches the database for matching virtual person images based on the company's request conditions.

[0266] Step 12:

[0267] The server selects virtual person images to propose to companies and provides them with downloadable links.

[0268] Step 13:

[0269] The server monitors the usage of the provided virtual person images.

[0270] Step 14:

[0271] The server aggregates sales data obtained from companies and calculates rewards based on the output ratio of the user's facial components and the influence of emotional reflection.

[0272] Step 15:

[0273] The server transfers the calculated reward to the user's account.

[0274] Step 16:

[0275] The server displays the reward details on the user's My Page.

[0276] Example 2

[0277] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0278] Conventional virtual image generation systems have the problem of being unable to extract sufficient information from facial photos uploaded by users, resulting in low personalization of the generated virtual images. Furthermore, they lacked mechanisms for tracking how the generated virtual images were used and providing appropriate compensation to users. This resulted in low user engagement and limited system usage.

[0279] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for a user to upload a facial photograph, means for saving the uploaded facial photograph and a prompt, means for generating a virtual image based on the saved facial photograph and the prompt, means for recognizing the user's emotion from the facial photograph in generating the virtual image and reflecting the emotion in the prompt, means for providing the generated virtual image to an organization, means for tracking the usage of the provided virtual image, and means for paying compensation to the data provider based on the tracked usage. This makes it possible to provide a more personalized virtual image that reflects the user's emotion, track the usage of the image, and pay appropriate compensation.

[0280] "User" refers to an individual or organization that uses the system to upload a facial photograph and generate a virtual image.

[0281] "Mugshot" refers to image data that a user uploads to the system, showing the face of themselves or another individual.

[0282] "Prompt text" refers to text data such as output ratio and desired features that a user enters when uploading a face photo.

[0283] An "emotion engine" refers to software that analyzes uploaded facial photos to recognize a user's emotions.

[0284] "Virtual image" refers to a virtual image of a person generated by an AI model based on the user's facial photo and prompt text.

[0285] A "generative AI model" refers to an artificial intelligence algorithm that generates a virtual image using a facial photo and a prompt as input.

[0286] "Organization" refers to a legal entity or group that receives the generated virtual image from the system for use.

[0287] "Usage" refers to tracking information about how the provided virtual imagery is used by an organization.

[0288] "Compensation" refers to the compensation a user receives for providing a virtual image.

[0289] The system of this invention involves a series of processes: users upload facial photos, companies are provided with virtual images generated from those photos, usage is tracked, and compensation is paid to the data provider. Furthermore, by combining this system with an emotion engine that recognizes the user's emotions, the system can generate more personalized virtual images. Specific embodiments of this system are described below.

[0290] Upload and save your photo

[0291] The user logs in to the system using a device (PC or smartphone) and uploads a facial photo. Once authentication is complete, the server displays a facial photo upload screen on the device. The user selects a facial photo file on this screen and enters prompts such as "output ratio" and "desired features." For example, the user can enter "output ratio 50%, bright features." When the user presses the "Upload" button, the facial photo and prompt are sent from the device to the server, which then stores this data in a database.

[0292] Emotion recognition by emotion engine

[0293] The server retrieves the face photo stored in the database and inputs it into the emotion engine. The emotion engine is software that analyzes the uploaded face photo to recognize the user's emotions (e.g., happiness, surprise, sadness, etc.). The emotion engine analyzes the face photo and adds the recognized emotion to the prompt text. For example, "happiness" can be added to "output ratio 50%, bright features." The server then saves the updated prompt text back to the database.

[0294] Generating virtual images using AI models

[0295] The server retrieves the updated prompt and facial photo from the database. Based on this, the server generates a virtual image using a generative AI model. A generative AI model is an artificial intelligence algorithm that generates a virtual image based on a facial photo and a prompt. During this generation process, the image is adjusted according to the prompt. The generated virtual image is stored in the database.

[0296] Providing generated images to companies

[0297] There is a means for a company to access the system and request the conditions of the virtual image they need. For example, a company can request "virtual images with positive emotions for an advertising campaign." The server searches the database for matching images based on the company's request conditions. If a matching virtual image is found, the server provides the company with a download link. The company can use this link to obtain the virtual image.

[0298] Usage tracking and rewards

[0299] The server monitors the usage of the provided virtual images through feedback from the companies. For example, it can track data such as how often the virtual images are displayed as advertisements and how many clicks they receive. In addition, the server collects sales data provided by the companies and calculates the user's compensation based on the frequency of use of the virtual images and the impact of their emotional reflection. Based on this calculation, the compensation is transferred to the user's account, and a compensation statement is displayed on the user's personal page.

[0300] With this system, users can provide a photo of their face, and the virtual image generated based on that photo can be safely used by companies with clear rights. Users can also receive appropriate compensation for the data they provide. By incorporating emotions, more personalized virtual images can be provided, making them attractive content for companies.

[0301] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0302] Step 1: Login authentication

[0303] A user logs in to the system using a terminal by entering a username and password. The entered authentication information is sent to the server, which checks it against the authentication information in the database. If authentication is successful, the server returns a success message and directs the user to a screen to upload a face photo.

[0304] Input: Username, Password

[0305] Data processing: Matching with authentication information in the database

[0306] Output: Login success message, face photo upload screen

[0307] Step 2: Upload your photo and prompt

[0308] The user selects a facial photo file and enters prompts such as desired features and output ratio into the terminal. When the user presses the "Upload" button, the facial photo and prompt are sent to the server, which then stores this data in a database.

[0309] Input: Face photo, prompt (e.g., "Output ratio 50%, bright features")

[0310] Data processing: Combining face photos and prompts

[0311] Output: Save to database

[0312] Step 3: Emotion Recognition

[0313] The server inputs the received facial photo into the emotion engine and performs image analysis. The emotion engine recognizes the user's emotion (e.g., "happiness") from the facial photo and adds the detected emotion to the prompt. The updated prompt is saved in the database.

[0314] Input: Face photo

[0315] Data processing: facial photo analysis, emotion recognition

[0316] Output: Save the updated prompt statement

[0317] Step 4: Virtual Image Generation

[0318] The server retrieves the face photo and updated prompt text from the database and inputs this data into the generative AI model, which then generates a virtual image based on the input data. The generated virtual image is then stored in the database.

[0319] Input: Face photo, updated prompt text

[0320] Data processing: Image generation based on facial photos and prompt sentences

[0321] Output: Save to database

[0322] Step 5: Provide images to companies

[0323] A company accesses the system and requests a virtual image. The server searches the database for a suitable virtual image based on the company's request criteria and provides it to the company. The provided image is presented as a link that the company can download.

[0324] Input: Company request conditions

[0325] Data processing: Virtual image retrieval from database

[0326] Output: Provide download link

[0327] Step 6: Track usage and redeem rewards

[0328] The server monitors the usage of virtual images by companies and tracks sales data. Based on this data, compensation is calculated taking into account frequency of use and the impact of emotional reflection. The calculated compensation is transferred to the user's account, and a compensation statement is displayed on the user's personal page.

[0329] Input: Sales data and usage data from companies

[0330] Data processing: Usage monitoring, reward calculation

[0331] Output: Reward transfer, reward details displayed on my page

[0332] (Application example 2)

[0333] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0334] Conventional virtual image generation systems are unable to fully reflect the user's emotions and individual characteristics, limiting their personalization. Furthermore, when companies use virtual person images in advertising, it is difficult to generate images that take the user's emotions and individual characteristics into account, and the compensation provided to users can be lacking in transparency. Furthermore, tracking of usage and compensation are insufficient, creating a need for a system to improve user motivation.

[0335] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0336] In this invention, the server includes means for a user to upload a facial photo, means for saving the uploaded facial photo and a prompt, means for recognizing the user's emotion using an emotion engine, means for reflecting the recognized emotion in a prompt, means for generating a virtual image based on the saved facial photo and the updated prompt, means for providing the generated virtual image to a company, means for tracking usage of the provided virtual image, and means for rewarding the data provider based on the tracked usage. This enables the generation of personalized virtual images that reflect the user's emotion, allowing companies to develop effective advertising campaigns. Furthermore, transparent tracking of usage and appropriate reward rewards are realized, thereby improving user motivation.

[0337] "User" means a person who uploads a facial photograph to the system and generates or provides a virtual image.

[0338] A "face photo" is an image file of a user's face that is uploaded to the system.

[0339] A "means" is a method or device for performing a particular function or role within a system.

[0340] A "prompt" is an instructional text indicating settings or requirements that the user inputs along with a facial photograph.

[0341] An "emotion engine" is an algorithm or software that recognizes a user's emotions from a facial photograph.

[0342] A "virtual image" is a digital fictional image of a person created based on a facial photograph and prompts.

[0343] "Generating" means processing data within the system to create a new virtual image.

[0344] "Company" refers to a corporation or organization that uses the generated virtual images for advertising or other purposes.

[0345] "Providing" means handing over data and images in the system to the company.

[0346] "Usage status" refers to information about how the provided virtual image is used.

[0347] "Tracking" means recording and monitoring the usage of the virtual images provided.

[0348] "Consideration" refers to money or other benefits paid as compensation to the user who provides the data.

[0349] "Rebate" means paying a user a fee based on their usage.

[0350] The "system" is a collection of devices and programs that perform a series of processes to generate and provide virtual images based on the user's facial photograph, track their usage, and provide compensation.

[0351] An "updated prompt" is a prompt after the emotion has been reflected by the emotion engine.

[0352] An "artificial intelligence model" is an AI algorithm that takes data as input and generates a virtual image.

[0353] The "Advertising Virtual Creator" system, an application example of this invention, is realized as follows: The system includes a series of processes: uploading a user's face photo, recognizing emotions, generating a virtual image, providing it to companies, tracking usage, and returning compensation.

[0354] First, the user logs in to the system using a device such as a smartphone and uploads a photo of their face. On the upload screen, the user selects a photo file and enters prompts such as the output ratio and desired features. This data is received by the system's server and stored in a database.

[0355] The server then analyzes the stored facial photo with an "emotion engine" to recognize the user's emotion (e.g., happiness, surprise, sadness). The recognized emotion is added to the prompt, generating an updated prompt. This updated prompt is then saved back to the database.

[0356] The server then inputs the updated prompt and the facial photo into a "generative AI model" to generate a virtual image, which is also stored in a database.

[0357] When a company needs a virtual image, the server receives the request and searches the database for a virtual image that matches the company's requirements. The image is provided after a strict authentication process.

[0358] The server monitors the usage of the provided virtual images and tracks sales data provided by companies. Based on this, rewards are paid to the users who provided the data. Rewards are calculated automatically within the system and transferred to the users' accounts.

[0359] As a specific example, the following prompt sentence may be entered:

[0360] Example prompt sentence:

[0361] Input image: face_photo.jpg

[0362] Output ratio: 50%

[0363] Emotion: Happiness

[0364] The generated virtual image is provided to Company B for advertising purposes.

[0365] This system enables the generation of personalized virtual images that reflect the user's emotions, allowing companies to develop effective advertising campaigns. It also enables transparent tracking of usage and appropriate rewards, improving user motivation.

[0366] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0367] Step 1:

[0368] A user logs in to the system using a terminal and uploads a photo of their face.

[0369] Input: Face photo file and prompt data (e.g., output ratio, desired features)

[0370] The server receives the facial photo file and prompt data and stores this data in a database.

[0371] Output: Face photo stored in the database and prompt

[0372] Step 2:

[0373] The server analyzes the stored facial photos using an emotion engine to recognize the user's emotions.

[0374] Input: A face photo stored in the database

[0375] The server uses an emotion engine to analyze the facial photo and update the prompt with the recognized emotion (e.g., happiness, surprise, sadness).

[0376] Output: The updated prompt is saved to the database.

[0377] Step 3:

[0378] The server inputs the updated prompt and facial photo into a generative AI model to generate a virtual image.

[0379] Input: Updated prompt and face photo

[0380] The server uses a generative AI model to generate a virtual image based on the facial photo and prompt, and stores the generated virtual image in a database.

[0381] Output: Virtual images stored in a database

[0382] Step 4:

[0383] When a business requests a virtual image, the server receives the request from the business.

[0384] Input: Request conditions from the company (e.g. requirements for virtual images for advertising)

[0385] The server searches the database for virtual images that match the requested criteria and provides them to the company.

[0386] Output: Virtual images provided to the company

[0387] Step 5:

[0388] The server monitors the usage of the provided virtual images and tracks sales data from the companies.

[0389] Input: Usage information of the provided virtual image and company sales data

[0390] The server aggregates usage and sales data and evaluates frequency of use and impact.

[0391] Output: Usage reports and evaluation data

[0392] Step 6:

[0393] The server will provide compensation to the user depending on the usage status.

[0394] Input: Usage reports and evaluation data

[0395] The server calculates the reward based on the evaluation data and deposits the reward into the user's account.

[0396] Output: Reward given to the user

[0397] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0398] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0399] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0400] [Second embodiment]

[0401] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0402] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0403] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0404] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0405] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0406] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0407] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0408] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0409] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0410] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0411] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0412] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0413] The system of this invention performs a series of processes: users upload facial photographs, companies are provided with virtual images generated from those photographs, usage is tracked, and compensation is paid to the data providers. A specific embodiment of the system is described below.

[0414] 1. User provides a photo of their face

[0415] A user logs in to the system and uploads a facial photo. On the facial photo upload screen, the user selects their own facial photo file and enters prompts (e.g., output ratio and desired features). These data are received by the system and stored on the server.

[0416] example:

[0417] User A logs in to the system, selects his or her own face photo, and sets the "output ratio" to 50%.

[0418] User A clicks the "Upload" button to send the photo and prompt to the server.

[0419] The server stores the received images and prompts in a database.

[0420] 2. Generating virtual images using AI models

[0421] The server uses AI technology to generate a virtual person image based on the stored facial photo and prompts. During the generation process, the image is adjusted according to the prompts' specified features and output ratios. The generated virtual image is also stored in the database.

[0422] example:

[0423] The server extracts the face photo and prompt from the database and inputs them into the AI ​​model.

[0424] The AI ​​model generates a virtual person image from User A's facial photo with an output ratio of 50%.

[0425] The server stores the generated virtual images in a database.

[0426] 3. Providing the generated images to companies

[0427] When a company needs a virtual person image, the server receives the request from the company and searches for and provides virtual images that meet the company's requirements. The images presented to the company are strictly managed by the system and provided after appropriate authentication.

[0428] example:

[0429] Company B requests virtual images for a new advertising campaign.

[0430] The server receives Company B's requirements and searches the database for matching images.

[0431] The server provides Company B with a link to download the proposed virtual image.

[0432] 4. Usage tracking and rewards

[0433] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this, it pays compensation to the users who provide the data. The compensation is calculated based on the output rate of the provided data and the frequency of use of the generated virtual images.

[0434] example:

[0435] The server monitors the usage of virtual images used in Company B's advertisements.

[0436] The server aggregates the sales data obtained from Company B and calculates the reward for User A based on the output ratio of the facial components.

[0437] The server transfers the reward to User A's account and displays the reward details on their personal page.

[0438] This system allows users to provide a photograph of their face, and the virtual person image generated based on that photograph is used safely for advertising purposes with clear rights. Furthermore, users receive appropriate compensation for the data they provide, ensuring transparency and fairness.

[0439] The processing flow will be explained below.

[0440] Step 1:

[0441] The user logs into the system.

[0442] Step 2:

[0443] The server verifies the user's authentication information and checks the database to ensure the user is a legitimate user.

[0444] Step 3:

[0445] The user moves to the face photo upload screen and selects a face photo file.

[0446] Step 4:

[0447] The user enters the prompts (output ratio and desired characteristics) and clicks the "Upload" button.

[0448] Step 5:

[0449] The server receives the uploaded face photo and prompt and stores them in a database.

[0450] Step 6:

[0451] The server uses an AI model to generate a virtual persona based on the stored facial photo and prompts.

[0452] Step 7:

[0453] The server stores the generated virtual person images in a database.

[0454] Step 8:

[0455] The server receives requests for virtual persona images from businesses.

[0456] Step 9:

[0457] The server searches the database for matching virtual person images based on the company's request conditions.

[0458] Step 10:

[0459] The server selects virtual person images to propose to companies and provides them with downloadable links.

[0460] Step 11:

[0461] The server monitors the usage of the provided virtual person images.

[0462] Step 12:

[0463] The server aggregates sales data obtained from companies and calculates rewards based on the output ratio of the user's facial components.

[0464] Step 13:

[0465] The server transfers the calculated reward to the user's account.

[0466] Step 14:

[0467] The server displays the reward details on the user's My Page.

[0468] Example 1

[0469] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0470] In recent years, the creation and commercial use of virtual person images has increased, but there is currently no system in place to securely manage facial photos provided by users, ensure transparency regarding the use of the generated virtual images, or provide fair compensation to users. Therefore, there is a need to develop a system that allows companies to efficiently use virtual images while maintaining a balance between protecting user privacy and providing compensation.

[0471] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0472] In this invention, the server includes a means for users to upload image data, a means for storing the uploaded image data and instruction information, a means for generating a virtual person image based on the stored image data and instruction information, a means for providing the generated virtual person image to an organization, a means for tracking the usage of the provided virtual person image, and a means for providing compensation to the data provider based on the tracked usage. This allows users to safely provide their own facial photographs, and the virtual image generated based on them is used appropriately, enabling transparency and compensation to users. Furthermore, companies can effectively use high-quality virtual person images.

[0473] A "user" is a person who provides a facial photograph and instruction information to the system and receives payment for the use of the generated virtual person image.

[0474] "Image data" refers to facial photographs and other visual information that users upload to the system.

[0475] "Instruction information" refers to information related to prompt statements and output settings that the user inputs in relation to image data.

[0476] A "virtual person image" refers to an image of a non-existent person that is generated based on image data and instruction information.

[0477] "Server" refers to the equipment and programs that receive and store image data and instruction information, generate virtual person images, and provide them to companies.

[0478] "Organization" refers to a company or organization that commercially uses the generated virtual person images.

[0479] "Usage" refers to data used to track how the provided virtual person images are used by companies and organizations.

[0480] "Rebate" refers to the process of providing compensation or other benefits to users based on their use of the virtual person image.

[0481] The system of this invention performs a series of processes: a user uploads image data (a facial photograph), a virtual person image generated based on that image data is provided to a company, usage is tracked, and compensation is paid to the data provider. A specific embodiment of the system is described below.

[0482] 1. User-provided image data

[0483] Users log in to the system using their own terminals, entering their ID and password on the login page and undergoing authentication.

[0484] The user accesses the image data upload page, clicks the "Select File" button, and selects a photo of their own face (e.g., "my_photo.jpg").

[0485] The user inputs a prompt as instruction information related to the image data, such as "Output ratio 50%, desired feature: smiling face."

[0486] When the user clicks the "Upload" button, the image data and the prompt text are sent to the server.

[0487] 2. Data storage by the server

[0488] The server receives the image data and prompt text sent by the user. The received data is stored in the image storage and the database. The image data is stored in the image storage, and the prompt text and image file paths are stored in the database.

[0489] 3. Generation of Virtual Person Images

[0490] The server extracts the stored image data and prompt sentences from the database, and the extracted data is input to a generative AI model (e.g., StyleGAN).

[0491] The AI ​​model processes image data according to instructions and generates a virtual person image with the specified characteristics.

[0492] The generated virtual person image is stored in the database again by the server.

[0493] 4. Provision to companies

[0494] A company logs in to the system and requests a virtual person image. Based on the criteria submitted by the company (e.g., "male in his 30s, output ratio 50%, smiling"), the server searches the database for a matching image.

[0495] When a virtual person image that matches the criteria is found, the server provides the company with a download link.

[0496] 5. Usage tracking and rebates

[0497] The server monitors how companies use virtual person images, tracking company advertisements and usage reports, and collecting usage data.

[0498] The server calculates the rewards for users based on sales data from companies, and the rewards are calculated based on frequency of use and output ratio.

[0499] Rewards will be transferred to the user's account, and the user can check the details of the reward on their My Page.

[0500] This system allows users to safely provide their own facial photographs, and the virtual person images generated based on them are used appropriately, ensuring transparency and fairness. It also allows companies to efficiently use high-quality virtual person images.

[0501] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0502] Step 1: User provides image data

[0503] Input: The user logs in to the system and selects a face photo file (e.g., "my_photo.jpg") and a prompt statement (e.g., "50% output ratio, desired feature: smile").

[0504] Operation: When the user clicks the "Upload" button, the image data and the prompt text are sent to the server. The data sent from the user's device is received by the server as an HTTP request.

[0505] Output: The server receives the image data and the prompt.

[0506] Step 2: The server saves the data

[0507] Input: The image data received in step 1 and the prompt text.

[0508] Operation: The server saves the image data to the image storage and stores the prompt text and image file path in the database. This includes the process of creating an entry in the database and recording the physical storage location of the facial photo data.

[0509] Output: The image data is saved to the image storage, and the prompt text and the path to the image file are saved to the database.

[0510] Step 3: The server uses the AI ​​model to generate the image

[0511] Input: Image data retrieved from the database and prompt text.

[0512] How it works: The server inputs image data and a prompt into an AI generative model (e.g., StyleGAN). The model generates a virtual person image according to the instructions. Here, the AI ​​model extracts features from the facial photo and processes them according to the prompt.

[0513] Output: The generated virtual person image is returned to the server.

[0514] Step 4: The server saves the generated image

[0515] Input: The virtual person image generated in step 3.

[0516] Operation: The server saves the generated virtual person image in the image storage and saves the path of the generated image in the database.

[0517] Output: The generated virtual person image is saved in the image storage, and its path is recorded in the database.

[0518] Step 5: The company requests images

[0519] Input: The company logs into the system and enters the required conditions (e.g., "male in his 30s, output ratio 50%, smiling face").

[0520] How it works: The server receives a request from a company and searches its database for images that match the criteria.

[0521] Output: As a search result, a list of virtual person images that match the conditions is extracted.

[0522] Step 6: The server serves the image to the company

[0523] Input: Virtual person images that match the criteria found in step 5.

[0524] How it works: The server provides the company with a download link for the image, which the company can then use to retrieve the image.

[0525] Output: A download link accessible to the company.

[0526] Step 7: The server tracks usage

[0527] Input: Information on the virtual person image used by the company.

[0528] How it works: A server monitors a company's use of images in advertising and collects usage data, including recording data such as when, where, and how often the images are used.

[0529] Output: Usage data is recorded in a database.

[0530] Step 8: The server calculates the payment and returns it to the user

[0531] Inputs: Usage data collected in step 7 and sales data from the company.

[0532] How it works: The server calculates the user's reward based on the frequency of use and output rate. The calculated reward is transferred to the user's account. The user can check the reward details on their My Page.

[0533] Output: Reward is transferred to the user and a reward statement is displayed.

[0534] (Application example 1)

[0535] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0536] In recent years, the generation and use of virtual images based on user-provided facial photographs has many potential applications. However, the way these images are used and how users are compensated remains unclear, making it difficult to gain user trust. Furthermore, there is a lack of an effective system for easily managing the generation and usage of virtual images. Therefore, there is a need for an environment where users can provide facial photographs with confidence and where companies can efficiently use virtual images.

[0537] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0538] In this invention, the server includes means for users to upload facial photographs, means for saving the uploaded facial photographs and prompts, means for generating virtual images based on the saved facial photographs and prompts, means for providing the generated virtual images to companies, means for tracking usage of the provided virtual images, means for paying compensation to users based on the tracked usage, and means for managing the generation and usage of virtual images via a smartphone application. This allows users to visualize how their provided data is used and receive appropriate compensation.

[0539] "User" refers to a person who uses this system to upload a facial photo and generate a virtual image.

[0540] "Facial photo" refers to image data of a user's face.

[0541] A "prompt" refers to text data used to specify the characteristics and output ratio of a virtual image generated based on a facial photograph.

[0542] "Virtual Image" refers to a virtual person image generated by an artificial intelligence model based on a user's facial photograph and prompts.

[0543] "Company" refers to a corporation or organization that uses the generated virtual images for purposes such as advertising materials.

[0544] "Smartphone application" refers to software that runs on a smartphone and provides the functions of this system.

[0545] "Server" refers to a computer system that executes the functions of this system and stores and processes data.

[0546] "Consideration" refers to the compensation paid for the use of a user's facial photograph.

[0547] This invention is a system that allows users to upload a facial photo, generates a virtual image based on the photo using an AI model, and provides it to companies. It also tracks the usage of the provided virtual image and can compensate users for it. These functions can be easily managed using a smartphone application.

[0548] Hardware and Software Configuration

[0549] Hardware:

[0550] Smartphone: A device that allows users to upload photos of their face and generate and manage virtual images.

[0551] Server: A set of computer systems that store facial photos and prompts, generate virtual images, and track usage.

[0552] software:

[0553] requests: A Python library for sending HTTP requests, uploading and retrieving data.

[0554] PIL (Python Imaging Library): A Python library for manipulating and processing image data.

[0555] Overall system flow

[0556] 1. Upload a photo of your face

[0557] A user logs in to the system using a smartphone application and uploads a facial photo. On the upload screen, the user enters the facial photo file along with prompts (e.g., output ratio and desired features). This data is sent to the server via an HTTP request and stored on the server.

[0558] Examples:

[0559] The user selects a photo of their face, enters prompts such as "50% output ratio" and "enhance brightness and contrast," and then uploads it.

[0560] 2. Virtual Image Generation

[0561] The server uses a generative AI model to generate a virtual image based on the stored facial photo and prompts. During the generation process, the image is adjusted according to the prompts, based on the specified features and output ratio. The generated virtual image is also stored in a database.

[0562] Examples:

[0563] The server extracts a face photo and prompts from the database and generates a virtual image with slightly enhanced brightness and contrast at a 50% output ratio according to the prompts.

[0564] 3. Providing the generated images to companies

[0565] When a company needs a virtual image, the server receives the request, searches for and provides virtual images that match the company's requirements, and the images are provided after strict authentication.

[0566] Examples:

[0567] Businesses request virtual images for new advertising campaigns, and the server provides the businesses with images that match their criteria.

[0568] 4. Usage tracking and rewards

[0569] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this, the server reimburses users. The reimbursement is calculated based on the output rate of the provided data and the frequency of use of the generated virtual images.

[0570] Examples:

[0571] The server tracks the usage of virtual images used in corporate advertisements and rewards users based on sales data obtained from the companies.

[0572] Prompt Sentence Examples

[0573] "Please use a face photo at 70% output ratio for advertising materials, and generate it with slightly enhanced brightness and contrast."

[0574] This system allows users to provide their own facial photos with peace of mind and receive compensation in a transparent and fair environment. It also enables businesses to efficiently obtain high-quality advertising materials.

[0575] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0576] Step 1:

[0577] A user logs in to the system using a smartphone application. They select a face photo and input prompts (e.g., output ratio and desired features). The input data (face photo file and prompt) is sent to the server as an HTTP request. The server receives it and stores it in a database. Based on the input data, the face photo and prompt are appropriately saved.

[0578] Step 2:

[0579] The server extracts the stored facial photo and prompt. The facial photo and prompt are input into the generation AI model. The AI ​​model processes the data (using image processing technology) to generate a virtual image. Specifically, it generates a virtual image that reflects the output ratio and specified features according to the prompt. This generated virtual image is then stored back in the database.

[0580] Step 3:

[0581] A company sends a request to the server to use a virtual image. The server searches its database for virtual images that match the company's criteria (e.g., type of advertising campaign or image characteristics). It selects the appropriate virtual image from the search results and provides it to the company. After authentication and appropriate data filtering, it sends the company a downloadable link.

[0582] Step 4:

[0583] The server monitors how the provided virtual images are used by companies. Specifically, it periodically collects and analyzes data on the companies' advertising campaigns and sales. Based on the analysis results, it evaluates the frequency of use of the virtual images and their contribution to sales. Based on this evaluation, it calculates the remuneration for the users.

[0584] Step 5:

[0585] The server returns rewards to users based on their usage. Specifically, it calculates an appropriate reward amount for each user based on sales data and frequency of use. The calculated reward is transferred to the user's account and displayed as a reward statement on the user's My Page in the smartphone application. Users can check the reward details on the application.

[0586] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0587] The system of the present invention performs a series of processes: users upload facial photos, virtual images generated from those photos are provided to companies, usage is tracked, and compensation is paid to the data provider. Furthermore, the present invention can generate more personalized virtual images by combining an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention are described in detail below.

[0588] 1. User provides a photo of their face

[0589] A user logs in to the system and uploads a facial photo. On the facial photo upload screen, the user selects their own facial photo file and enters prompts (e.g., output ratio and desired features). These data are received by the system and stored on the server.

[0590] example:

[0591] User A logs in to the system, selects his or her own face photo, and sets the "output ratio" to 50%.

[0592] User A clicks the "Upload" button to send the photo and prompt to the server.

[0593] The server stores the received images and prompts in a database.

[0594] 2. Emotion Recognition by Emotion Engine

[0595] The server uses an emotion engine to recognize the user's emotions from the facial photo uploaded by the user. The recognized emotions are reflected in the prompts, allowing the user to reflect the facial expressions and emotions intended by the user in the virtual image.

[0596] example:

[0597] The server uses an emotion engine to recognize User A's emotions (e.g., happiness, surprise, sadness) from the uploaded facial photo.

[0598] Based on the perceived emotion, "happiness" was added to the prompt.

[0599] The server updates the prompt with the emotion and saves it in the database.

[0600] 3. Generating virtual images using AI models

[0601] The server uses AI technology to generate a virtual person image based on the stored facial photo and updated prompts. During the generation process, the image is adjusted according to the prompts to reflect the specified characteristics and emotions. The generated virtual image is also stored in a database.

[0602] example:

[0603] The server inputs a facial photo into the AI ​​model based on the updated prompt, and generates a virtual person image with an output ratio of 50% and reflecting the emotion of "happiness."

[0604] The server stores the generated virtual images in a database.

[0605] 4. Providing the generated images to companies

[0606] When a company needs a virtual person image, the server receives the request from the company and searches for and provides virtual images that meet the company's requirements. The images presented to the company are strictly managed by the system and provided after appropriate authentication.

[0607] example:

[0608] Company B requests virtual images for a new advertising campaign.

[0609] The server receives Company B's requirements and searches the database for matching images.

[0610] The server provides Company B with a link to download the proposed virtual image.

[0611] 5. Usage tracking and rewards

[0612] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this data, it pays compensation to the data provider, the user. Compensation is calculated based on the output ratio of the provided data, the frequency of use of the generated virtual image, and the impact of emotional reflection.

[0613] example:

[0614] The server monitors the usage of virtual images used in Company B's advertisements.

[0615] The server aggregates the sales data obtained from Company B and calculates the reward for User A based on the output ratio of facial components and the degree of influence of emotional reflection.

[0616] The server transfers the reward to User A's account and displays the reward details on their personal page.

[0617] This system allows users to provide a photo of their face, and the virtual person image generated based on that photo can be used safely for advertising purposes with clear rights. Furthermore, users can receive appropriate compensation for the data they provide, and more personalized advertising can be achieved by reflecting emotions.

[0618] The processing flow will be explained below.

[0619] Step 1:

[0620] The user logs into the system.

[0621] Step 2:

[0622] The server verifies the user's authentication information and checks the database to ensure the user is a legitimate user.

[0623] Step 3:

[0624] The user moves to the face photo upload screen and selects a face photo file.

[0625] Step 4:

[0626] The user enters the prompts (output ratio and desired characteristics) and clicks the "Upload" button.

[0627] Step 5:

[0628] The server receives the uploaded face photo and prompt and stores them in a database.

[0629] Step 6:

[0630] The server uses an emotion engine to recognize the user's emotions from the stored facial photographs.

[0631] Step 7:

[0632] The server updates the prompt based on the recognized emotion and stores it in a database.

[0633] Step 8:

[0634] The server inputs the updated prompt and facial photo into the AI ​​model to generate a virtual person image.

[0635] Step 9:

[0636] The server stores the generated virtual person images in a database.

[0637] Step 10:

[0638] The server receives requests for virtual persona images from businesses.

[0639] Step 11:

[0640] The server searches the database for matching virtual person images based on the company's request conditions.

[0641] Step 12:

[0642] The server selects virtual person images to propose to companies and provides them with downloadable links.

[0643] Step 13:

[0644] The server monitors the usage of the provided virtual person images.

[0645] Step 14:

[0646] The server aggregates sales data obtained from companies and calculates rewards based on the output ratio of the user's facial components and the influence of emotional reflection.

[0647] Step 15:

[0648] The server transfers the calculated reward to the user's account.

[0649] Step 16:

[0650] The server displays the reward details on the user's My Page.

[0651] Example 2

[0652] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0653] Conventional virtual image generation systems have the problem of being unable to extract sufficient information from facial photos uploaded by users, resulting in low personalization of the generated virtual images. Furthermore, they lacked mechanisms for tracking how the generated virtual images were used and providing appropriate compensation to users. This resulted in low user engagement and limited system usage.

[0654] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for a user to upload a facial photograph, means for saving the uploaded facial photograph and a prompt, means for generating a virtual image based on the saved facial photograph and the prompt, means for recognizing the user's emotion from the facial photograph in generating the virtual image and reflecting the emotion in the prompt, means for providing the generated virtual image to an organization, means for tracking the usage of the provided virtual image, and means for paying compensation to the data provider based on the tracked usage. This makes it possible to provide a more personalized virtual image that reflects the user's emotion, track the usage of the image, and pay appropriate compensation.

[0655] "User" refers to an individual or organization that uses the system to upload a facial photograph and generate a virtual image.

[0656] "Mugshot" refers to image data that a user uploads to the system, showing the face of themselves or another individual.

[0657] "Prompt text" refers to text data such as output ratio and desired features that a user enters when uploading a face photo.

[0658] An "emotion engine" refers to software that analyzes uploaded facial photos to recognize a user's emotions.

[0659] "Virtual image" refers to a virtual image of a person generated by an AI model based on the user's facial photo and prompt text.

[0660] A "generative AI model" refers to an artificial intelligence algorithm that generates a virtual image using a facial photo and a prompt as input.

[0661] "Organization" refers to a legal entity or group that receives the generated virtual image from the system for use.

[0662] "Usage" refers to tracking information about how the provided virtual imagery is used by an organization.

[0663] "Compensation" refers to the compensation a user receives for providing a virtual image.

[0664] The system of this invention involves a series of processes: users upload facial photos, companies are provided with virtual images generated from those photos, usage is tracked, and compensation is paid to the data provider. Furthermore, by combining this system with an emotion engine that recognizes the user's emotions, the system can generate more personalized virtual images. Specific embodiments of this system are described below.

[0665] Upload and save your photo

[0666] The user logs in to the system using a device (PC or smartphone) and uploads a facial photo. Once authentication is complete, the server displays a facial photo upload screen on the device. The user selects a facial photo file on this screen and enters prompts such as "output ratio" and "desired features." For example, the user can enter "output ratio 50%, bright features." When the user presses the "Upload" button, the facial photo and prompt are sent from the device to the server, which then stores this data in a database.

[0667] Emotion recognition by emotion engine

[0668] The server retrieves the face photo stored in the database and inputs it into the emotion engine. The emotion engine is software that analyzes the uploaded face photo to recognize the user's emotions (e.g., happiness, surprise, sadness, etc.). The emotion engine analyzes the face photo and adds the recognized emotion to the prompt text. For example, "happiness" can be added to "output ratio 50%, bright features." The server then saves the updated prompt text back to the database.

[0669] Generating virtual images using AI models

[0670] The server retrieves the updated prompt and facial photo from the database. Based on this, the server generates a virtual image using a generative AI model. A generative AI model is an artificial intelligence algorithm that generates a virtual image based on a facial photo and a prompt. During this generation process, the image is adjusted according to the prompt. The generated virtual image is stored in the database.

[0671] Providing generated images to companies

[0672] There is a means for a company to access the system and request the conditions of the virtual image they need. For example, a company can request "virtual images with positive emotions for an advertising campaign." The server searches the database for matching images based on the company's request conditions. If a matching virtual image is found, the server provides the company with a download link. The company can use this link to obtain the virtual image.

[0673] Usage tracking and rewards

[0674] The server monitors the usage of the provided virtual images through feedback from the companies. For example, it can track data such as how often the virtual images are displayed as advertisements and how many clicks they receive. In addition, the server collects sales data provided by the companies and calculates the user's compensation based on the frequency of use of the virtual images and the impact of their emotional reflection. Based on this calculation, the compensation is transferred to the user's account, and a compensation statement is displayed on the user's personal page.

[0675] With this system, users can provide a photo of their face, and the virtual image generated based on that photo can be safely used by companies with clear rights. Users can also receive appropriate compensation for the data they provide. By incorporating emotions, more personalized virtual images can be provided, making them attractive content for companies.

[0676] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0677] Step 1: Login authentication

[0678] A user logs in to the system using a terminal by entering a username and password. The entered authentication information is sent to the server, which checks it against the authentication information in the database. If authentication is successful, the server returns a success message and directs the user to a screen to upload a face photo.

[0679] Input: Username, Password

[0680] Data processing: Matching with authentication information in the database

[0681] Output: Login success message, face photo upload screen

[0682] Step 2: Upload your photo and prompt

[0683] The user selects a facial photo file and enters prompts such as desired features and output ratio into the terminal. When the user presses the "Upload" button, the facial photo and prompt are sent to the server, which then stores this data in a database.

[0684] Input: Face photo, prompt (e.g., "Output ratio 50%, bright features")

[0685] Data processing: Combining face photos and prompts

[0686] Output: Save to database

[0687] Step 3: Emotion Recognition

[0688] The server inputs the received facial photo into the emotion engine and performs image analysis. The emotion engine recognizes the user's emotion (e.g., "happiness") from the facial photo and adds the detected emotion to the prompt. The updated prompt is saved in the database.

[0689] Input: Face photo

[0690] Data processing: facial photo analysis, emotion recognition

[0691] Output: Save the updated prompt statement

[0692] Step 4: Virtual Image Generation

[0693] The server retrieves the face photo and updated prompt text from the database and inputs this data into the generative AI model, which then generates a virtual image based on the input data. The generated virtual image is then stored in the database.

[0694] Input: Face photo, updated prompt text

[0695] Data processing: Image generation based on facial photos and prompt sentences

[0696] Output: Save to database

[0697] Step 5: Provide images to companies

[0698] A company accesses the system and requests a virtual image. The server searches the database for a suitable virtual image based on the company's request criteria and provides it to the company. The provided image is presented as a link that the company can download.

[0699] Input: Company request conditions

[0700] Data processing: Virtual image retrieval from database

[0701] Output: Provide download link

[0702] Step 6: Track usage and redeem rewards

[0703] The server monitors the usage of virtual images by companies and tracks sales data. Based on this data, compensation is calculated taking into account frequency of use and the impact of emotional reflection. The calculated compensation is transferred to the user's account, and a compensation statement is displayed on the user's personal page.

[0704] Input: Sales data and usage data from companies

[0705] Data processing: Usage monitoring, reward calculation

[0706] Output: Reward transfer, reward details displayed on my page

[0707] (Application example 2)

[0708] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0709] Conventional virtual image generation systems are unable to fully reflect the user's emotions and individual characteristics, limiting their personalization. Furthermore, when companies use virtual person images in advertising, it is difficult to generate images that take the user's emotions and individual characteristics into account, and the compensation provided to users can be lacking in transparency. Furthermore, tracking of usage and compensation are insufficient, creating a need for a system to improve user motivation.

[0710] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0711] In this invention, the server includes means for a user to upload a facial photo, means for saving the uploaded facial photo and a prompt, means for recognizing the user's emotion using an emotion engine, means for reflecting the recognized emotion in a prompt, means for generating a virtual image based on the saved facial photo and the updated prompt, means for providing the generated virtual image to a company, means for tracking usage of the provided virtual image, and means for rewarding the data provider based on the tracked usage. This enables the generation of personalized virtual images that reflect the user's emotion, allowing companies to develop effective advertising campaigns. Furthermore, transparent tracking of usage and appropriate reward rewards are realized, thereby improving user motivation.

[0712] "User" means a person who uploads a facial photograph to the system and generates or provides a virtual image.

[0713] A "face photo" is an image file of a user's face that is uploaded to the system.

[0714] A "means" is a method or device for performing a particular function or role within a system.

[0715] A "prompt" is an instructional text indicating settings or requirements that the user inputs along with a facial photograph.

[0716] An "emotion engine" is an algorithm or software that recognizes a user's emotions from a facial photograph.

[0717] A "virtual image" is a digital fictional image of a person created based on a facial photograph and prompts.

[0718] "Generating" means processing data within the system to create a new virtual image.

[0719] "Company" refers to a corporation or organization that uses the generated virtual images for advertising or other purposes.

[0720] "Providing" means handing over data and images in the system to the company.

[0721] "Usage status" refers to information about how the provided virtual image is used.

[0722] "Tracking" means recording and monitoring the usage of the virtual images provided.

[0723] "Consideration" refers to money or other benefits paid as compensation to the user who provides the data.

[0724] "Rebate" means paying a user a fee based on their usage.

[0725] The "system" is a collection of devices and programs that perform a series of processes to generate and provide virtual images based on the user's facial photograph, track their usage, and provide compensation.

[0726] An "updated prompt" is a prompt after the emotion has been reflected by the emotion engine.

[0727] An "artificial intelligence model" is an AI algorithm that takes data as input and generates a virtual image.

[0728] The "Advertising Virtual Creator" system, an application example of this invention, is realized as follows: The system includes a series of processes: uploading a user's facial photo, recognizing emotions, generating a virtual image, providing it to companies, tracking usage, and returning compensation.

[0729] First, the user logs in to the system using a device such as a smartphone and uploads a photo of their face. On the upload screen, the user selects a photo file and enters prompts such as the output ratio and desired features. This data is received by the system's server and stored in a database.

[0730] The server then analyzes the stored facial photo with an "emotion engine" to recognize the user's emotion (e.g., happiness, surprise, sadness). The recognized emotion is added to the prompt, generating an updated prompt. This updated prompt is then saved back to the database.

[0731] The server then inputs the updated prompt and the facial photo into a "generative AI model" to generate a virtual image, which is also stored in a database.

[0732] When a company needs a virtual image, the server receives the request, searches the database for a virtual image that matches the company's requirements, and provides it. The image is provided after a strict authentication process.

[0733] The server monitors the usage of the provided virtual images and tracks sales data provided by companies. Based on this, rewards are paid to the users who provided the data. Rewards are calculated automatically within the system and transferred to the users' accounts.

[0734] As a specific example, the following prompt sentence may be entered:

[0735] Example prompt sentence:

[0736] Input image: face_photo.jpg

[0737] Output ratio: 50%

[0738] Emotion: Happiness

[0739] The generated virtual image is provided to Company B for advertising purposes.

[0740] This system enables the generation of personalized virtual images that reflect the user's emotions, allowing companies to develop effective advertising campaigns. It also enables transparent tracking of usage and appropriate rewards, improving user motivation.

[0741] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0742] Step 1:

[0743] A user logs in to the system using a terminal and uploads a photo of their face.

[0744] Input: Face photo file and prompt data (e.g., output ratio, desired features)

[0745] The server receives the facial photo file and prompt data and stores this data in a database.

[0746] Output: Face photo stored in the database and prompt

[0747] Step 2:

[0748] The server analyzes the stored facial photos using an emotion engine to recognize the user's emotions.

[0749] Input: A face photo stored in the database

[0750] The server uses an emotion engine to analyze the facial photo and update the prompt with the recognized emotion (e.g., happiness, surprise, sadness).

[0751] Output: The updated prompt is saved to the database.

[0752] Step 3:

[0753] The server inputs the updated prompt and facial photo into a generative AI model to generate a virtual image.

[0754] Input: Updated prompt and face photo

[0755] The server uses a generative AI model to generate a virtual image based on the facial photo and prompt, and stores the generated virtual image in a database.

[0756] Output: Virtual images stored in a database

[0757] Step 4:

[0758] When a business requests a virtual image, the server receives the request from the business.

[0759] Input: Request conditions from the company (e.g. requirements for virtual images for advertising)

[0760] The server searches the database for virtual images that match the requested criteria and provides them to the company.

[0761] Output: Virtual images provided to the company

[0762] Step 5:

[0763] The server monitors the usage of the provided virtual images and tracks sales data from the companies.

[0764] Input: Usage information of the provided virtual image and company sales data

[0765] The server aggregates usage and sales data and evaluates frequency of use and impact.

[0766] Output: Usage reports and evaluation data

[0767] Step 6:

[0768] The server will provide compensation to the user depending on the usage status.

[0769] Input: Usage reports and evaluation data

[0770] The server calculates the reward based on the evaluation data and deposits the reward into the user's account.

[0771] Output: Reward given to the user

[0772] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0773] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0774] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0775] [Third embodiment]

[0776] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0777] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0778] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0779] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0780] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0781] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0782] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0783] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0784] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0785] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0786] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0787] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0788] The system of this invention performs a series of processes: users upload facial photographs, companies are provided with virtual images generated from those photographs, usage is tracked, and compensation is paid to the data providers. A specific embodiment of the system is described below.

[0789] 1. User provides a photo of their face

[0790] A user logs in to the system and uploads a facial photo. On the facial photo upload screen, the user selects their own facial photo file and enters prompts (e.g., output ratio and desired features). These data are received by the system and stored on the server.

[0791] example:

[0792] User A logs in to the system, selects his or her own face photo, and sets the "output ratio" to 50%.

[0793] User A clicks the "Upload" button to send the photo and prompt to the server.

[0794] The server stores the received images and prompts in a database.

[0795] 2. Generating virtual images using AI models

[0796] The server uses AI technology to generate a virtual person image based on the stored facial photo and prompts. During the generation process, the image is adjusted according to the prompts' specified features and output ratios. The generated virtual image is also stored in the database.

[0797] example:

[0798] The server extracts the face photo and prompt from the database and inputs them into the AI ​​model.

[0799] The AI ​​model generates a virtual person image from User A's facial photo with an output ratio of 50%.

[0800] The server stores the generated virtual images in a database.

[0801] 3. Providing the generated images to companies

[0802] When a company needs a virtual person image, the server receives the request from the company and searches for and provides virtual images that meet the company's requirements. The images presented to the company are strictly managed by the system and provided after appropriate authentication.

[0803] example:

[0804] Company B requests virtual images for a new advertising campaign.

[0805] The server receives Company B's requirements and searches the database for matching images.

[0806] The server provides Company B with a link to download the proposed virtual image.

[0807] 4. Usage tracking and rewards

[0808] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this, it pays compensation to the users who provide the data. The compensation is calculated based on the output rate of the provided data and the frequency of use of the generated virtual images.

[0809] example:

[0810] The server monitors the usage of virtual images used in Company B's advertisements.

[0811] The server aggregates the sales data obtained from Company B and calculates the reward for User A based on the output ratio of the facial components.

[0812] The server transfers the reward to User A's account and displays the reward details on their personal page.

[0813] This system allows users to provide a photograph of their face, and the virtual person image generated based on that photograph is used safely for advertising purposes with clear rights. Furthermore, users are compensated appropriately for the data they provide, ensuring transparency and fairness.

[0814] The processing flow will be explained below.

[0815] Step 1:

[0816] The user logs into the system.

[0817] Step 2:

[0818] The server verifies the user's authentication information and checks the database to ensure the user is a legitimate user.

[0819] Step 3:

[0820] The user moves to the face photo upload screen and selects a face photo file.

[0821] Step 4:

[0822] The user enters the prompts (output ratio and desired characteristics) and clicks the "Upload" button.

[0823] Step 5:

[0824] The server receives the uploaded face photo and prompt and stores them in a database.

[0825] Step 6:

[0826] The server uses an AI model to generate a virtual persona based on the stored facial photo and prompts.

[0827] Step 7:

[0828] The server stores the generated virtual person images in a database.

[0829] Step 8:

[0830] The server receives requests for virtual persona images from businesses.

[0831] Step 9:

[0832] The server searches the database for matching virtual person images based on the company's request conditions.

[0833] Step 10:

[0834] The server selects virtual person images to propose to companies and provides them with downloadable links.

[0835] Step 11:

[0836] The server monitors the usage of the provided virtual person images.

[0837] Step 12:

[0838] The server aggregates sales data obtained from companies and calculates rewards based on the output ratio of the user's facial components.

[0839] Step 13:

[0840] The server transfers the calculated reward to the user's account.

[0841] Step 14:

[0842] The server displays the reward details on the user's My Page.

[0843] Example 1

[0844] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0845] In recent years, the creation and commercial use of virtual person images has increased, but there is currently no system in place to securely manage facial photos provided by users, ensure transparency regarding the use of the generated virtual images, or provide fair compensation to users. Therefore, there is a need to develop a system that allows companies to efficiently use virtual images while maintaining a balance between protecting user privacy and providing compensation.

[0846] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0847] In this invention, the server includes a means for users to upload image data, a means for storing the uploaded image data and instruction information, a means for generating a virtual person image based on the stored image data and instruction information, a means for providing the generated virtual person image to an organization, a means for tracking the usage of the provided virtual person image, and a means for providing compensation to the data provider based on the tracked usage. This allows users to safely provide their own facial photographs, and the virtual image generated based on them is used appropriately, enabling transparency and compensation to users. Furthermore, companies can effectively use high-quality virtual person images.

[0848] A "user" is a person who provides a facial photograph and instruction information to the system and receives payment for the use of the generated virtual person image.

[0849] "Image data" refers to facial photographs and other visual information that users upload to the system.

[0850] "Instruction information" refers to information related to prompt statements and output settings that the user inputs in relation to image data.

[0851] A "virtual person image" refers to an image of a non-existent person that is generated based on image data and instruction information.

[0852] "Server" refers to the equipment and programs that receive and store image data and instruction information, generate virtual person images, and provide them to companies.

[0853] "Organization" refers to a company or organization that commercially uses the generated virtual person images.

[0854] "Usage" refers to data used to track how the provided virtual person images are used by companies and organizations.

[0855] "Rebate" refers to the process of providing compensation or other benefits to users based on their use of the virtual person image.

[0856] The system of this invention performs a series of processes: a user uploads image data (a facial photograph), a virtual person image generated based on that image data is provided to a company, usage is tracked, and compensation is paid to the data provider. A specific embodiment of this system is described below.

[0857] 1. User-provided image data

[0858] Users log in to the system using their own terminals, entering their ID and password on the login page and undergoing authentication.

[0859] The user accesses the image data upload page, clicks the "Select File" button, and selects a photo of their own face (e.g., "my_photo.jpg").

[0860] The user inputs a prompt as instruction information related to the image data, such as "Output ratio 50%, desired feature: smiling face."

[0861] When the user clicks the "Upload" button, the image data and the prompt text are sent to the server.

[0862] 2. Data storage by the server

[0863] The server receives the image data and prompt text sent by the user. The received data is stored in the image storage and the database. The image data is stored in the image storage, and the prompt text and image file paths are stored in the database.

[0864] 3. Generation of Virtual Person Images

[0865] The server extracts the stored image data and prompt sentences from the database, and the extracted data is input to a generative AI model (e.g., StyleGAN).

[0866] The AI ​​model processes image data according to instructions and generates a virtual person image with the specified characteristics.

[0867] The generated virtual person image is stored in the database again by the server.

[0868] 4. Provision to companies

[0869] A company logs in to the system and requests a virtual person image. Based on the criteria submitted by the company (e.g., "male in his 30s, output ratio 50%, smiling"), the server searches the database for a matching image.

[0870] When a virtual person image that matches the criteria is found, the server provides the company with a download link.

[0871] 5. Usage tracking and rebates

[0872] The server monitors how companies use virtual person images, tracking company advertisements and usage reports, and collecting usage data.

[0873] The server calculates the rewards for users based on sales data from companies, and the rewards are calculated based on frequency of use and output ratio.

[0874] Rewards will be transferred to the user's account, and the user can check the details of the reward on their My Page.

[0875] This system allows users to safely provide their own facial photographs, and the virtual person images generated based on them are used appropriately, ensuring transparency and fairness. It also allows companies to efficiently use high-quality virtual person images.

[0876] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0877] Step 1: User provides image data

[0878] Input: The user logs in to the system and selects a face photo file (e.g., "my_photo.jpg") and a prompt statement (e.g., "50% output ratio, desired feature: smile").

[0879] Operation: When the user clicks the "Upload" button, the image data and the prompt text are sent to the server. The data sent from the user's device is received by the server as an HTTP request.

[0880] Output: The server receives the image data and the prompt.

[0881] Step 2: The server saves the data

[0882] Input: The image data received in step 1 and the prompt text.

[0883] Operation: The server saves the image data to the image storage and stores the prompt text and image file path in the database. This includes the process of creating an entry in the database and recording the physical storage location of the facial photo data.

[0884] Output: The image data is saved to the image storage, and the prompt text and the path to the image file are saved to the database.

[0885] Step 3: The server uses the AI ​​model to generate the image

[0886] Input: Image data retrieved from the database and prompt text.

[0887] How it works: The server inputs image data and a prompt into an AI generative model (e.g., StyleGAN). The model generates a virtual person image according to the instructions. Here, the AI ​​model extracts features from the facial photo and processes them according to the prompt.

[0888] Output: The generated virtual person image is returned to the server.

[0889] Step 4: The server saves the generated image

[0890] Input: The virtual person image generated in step 3.

[0891] Operation: The server saves the generated virtual person image in the image storage and saves the path of the generated image in the database.

[0892] Output: The generated virtual person image is saved in the image storage, and its path is recorded in the database.

[0893] Step 5: The company requests images

[0894] Input: The company logs into the system and enters the required conditions (e.g., "male in his 30s, output ratio 50%, smiling face").

[0895] How it works: The server receives a request from a company and searches its database for images that match the criteria.

[0896] Output: As a search result, a list of virtual person images that match the conditions is extracted.

[0897] Step 6: The server serves the image to the company

[0898] Input: Virtual person images that match the criteria found in step 5.

[0899] How it works: The server provides the company with a download link for the image, which the company can then use to retrieve the image.

[0900] Output: A download link accessible to the company.

[0901] Step 7: The server tracks usage

[0902] Input: Information on the virtual person image used by the company.

[0903] How it works: A server monitors a company's use of images in advertising and collects usage data, including recording data such as when, where, and how often the images are used.

[0904] Output: Usage data is recorded in a database.

[0905] Step 8: The server calculates the payment and returns it to the user

[0906] Inputs: Usage data collected in step 7 and sales data from the company.

[0907] How it works: The server calculates the user's reward based on the frequency of use and output rate. The calculated reward is transferred to the user's account. The user can check the reward details on their My Page.

[0908] Output: Reward is transferred to the user and a reward statement is displayed.

[0909] (Application example 1)

[0910] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0911] In recent years, the generation and use of virtual images based on user-provided facial photographs has many potential applications. However, the way these images are used and how users are compensated remains unclear, making it difficult to gain user trust. Furthermore, there is a lack of an effective system for easily managing the generation and usage of virtual images. Therefore, there is a need for an environment where users can provide facial photographs with confidence and where companies can efficiently use virtual images.

[0912] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0913] In this invention, the server includes means for users to upload facial photographs, means for saving the uploaded facial photographs and prompts, means for generating virtual images based on the saved facial photographs and prompts, means for providing the generated virtual images to companies, means for tracking usage of the provided virtual images, means for paying compensation to users based on the tracked usage, and means for managing the generation and usage of virtual images via a smartphone application. This allows users to visualize how their provided data is used and receive appropriate compensation.

[0914] "User" refers to a person who uses this system to upload a facial photo and generate a virtual image.

[0915] "Facial photo" refers to image data of a user's face.

[0916] A "prompt" refers to text data used to specify the characteristics and output ratio of a virtual image generated based on a facial photograph.

[0917] "Virtual Image" refers to a virtual person image generated by an artificial intelligence model based on a user's facial photograph and prompts.

[0918] "Company" refers to a corporation or organization that uses the generated virtual images for purposes such as advertising materials.

[0919] "Smartphone application" refers to software that runs on a smartphone and provides the functions of this system.

[0920] "Server" refers to a computer system that executes the functions of this system and stores and processes data.

[0921] "Consideration" refers to the compensation paid for the use of a user's facial photograph.

[0922] This invention is a system that allows users to upload a facial photo, generates a virtual image based on the photo using an AI model, and provides it to companies. It also tracks the usage of the provided virtual image and can compensate users for it. These functions can be easily managed using a smartphone application.

[0923] Hardware and Software Configuration

[0924] Hardware:

[0925] Smartphone: A device that allows users to upload photos of their face and generate and manage virtual images.

[0926] Server: A set of computer systems that store facial photos and prompts, generate virtual images, and track usage.

[0927] software:

[0928] requests: A Python library for sending HTTP requests, uploading and retrieving data.

[0929] PIL (Python Imaging Library): A Python library for manipulating and processing image data.

[0930] Overall system flow

[0931] 1. Upload a photo of your face

[0932] A user logs in to the system using a smartphone application and uploads a facial photo. On the upload screen, the user enters the facial photo file along with prompts (e.g., output ratio and desired features). This data is sent to the server via an HTTP request and stored on the server.

[0933] Examples:

[0934] The user selects a photo of their face, enters prompts such as "50% output ratio" and "enhance brightness and contrast," and then uploads it.

[0935] 2. Virtual Image Generation

[0936] The server uses a generative AI model to generate a virtual image based on the stored facial photo and prompts. During the generation process, the image is adjusted according to the prompts, based on the specified features and output ratio. The generated virtual image is also stored in a database.

[0937] Examples:

[0938] The server extracts a face photo and prompts from the database and generates a virtual image with slightly enhanced brightness and contrast at a 50% output ratio according to the prompts.

[0939] 3. Providing the generated images to companies

[0940] When a company needs a virtual image, the server receives the request, searches for and provides virtual images that match the company's requirements, and the images are provided after strict authentication.

[0941] Examples:

[0942] Businesses request virtual images for new advertising campaigns, and the server provides the businesses with images that match their criteria.

[0943] 4. Usage tracking and rewards

[0944] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this, the server reimburses users. The reimbursement is calculated based on the output rate of the provided data and the frequency of use of the generated virtual images.

[0945] Examples:

[0946] The server tracks the usage of virtual images used in corporate advertisements and rewards users based on sales data obtained from the companies.

[0947] Prompt Sentence Examples

[0948] "Please use a face photo at 70% output ratio for advertising materials, and generate it with slightly enhanced brightness and contrast."

[0949] This system allows users to provide their own facial photos with peace of mind and receive compensation in a transparent and fair environment. It also enables businesses to efficiently obtain high-quality advertising materials.

[0950] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0951] Step 1:

[0952] A user logs in to the system using a smartphone application. They select a face photo and input prompts (e.g., output ratio and desired features). The input data (face photo file and prompt) is sent to the server as an HTTP request. The server receives it and stores it in a database. Based on the input data, the face photo and prompt are appropriately saved.

[0953] Step 2:

[0954] The server extracts the stored facial photo and prompt. The facial photo and prompt are input into the generation AI model. The AI ​​model processes the data (using image processing technology) to generate a virtual image. Specifically, it generates a virtual image that reflects the output ratio and specified features according to the prompt. This generated virtual image is then stored back in the database.

[0955] Step 3:

[0956] A company sends a request to the server to use a virtual image. The server searches its database for virtual images that match the company's criteria (e.g., type of advertising campaign or image characteristics). It selects the appropriate virtual image from the search results and provides it to the company. After authentication and appropriate data filtering, it sends the company a downloadable link.

[0957] Step 4:

[0958] The server monitors how the provided virtual images are used by companies. Specifically, it periodically collects and analyzes data on the companies' advertising campaigns and sales. Based on the analysis results, it evaluates the frequency of use of the virtual images and their contribution to sales. Based on this evaluation, it calculates the remuneration for the users.

[0959] Step 5:

[0960] The server returns rewards to users based on their usage. Specifically, it calculates the appropriate reward amount for each user based on sales data and frequency of use. The calculated reward is transferred to the user's account and displayed as a reward statement on the user's My Page in the smartphone application. Users can check the reward details on the application.

[0961] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0962] The system of the present invention performs a series of processes: users upload facial photos, virtual images generated from those photos are provided to companies, usage is tracked, and compensation is paid to the data provider. Furthermore, the present invention can generate more personalized virtual images by combining an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention are described in detail below.

[0963] 1. User provides face photo

[0964] A user logs in to the system and uploads a facial photo. On the facial photo upload screen, the user selects their own facial photo file and enters prompts (e.g., output ratio and desired features). These data are received by the system and stored on the server.

[0965] example:

[0966] User A logs in to the system, selects his or her own face photo, and sets the "output ratio" to 50%.

[0967] User A clicks the "Upload" button to send the photo and prompt to the server.

[0968] The server stores the received images and prompts in a database.

[0969] 2. Emotion Recognition by Emotion Engine

[0970] The server uses an emotion engine to recognize the user's emotions from the facial photo uploaded by the user. The recognized emotions are reflected in the prompts, allowing the user to reflect the facial expressions and emotions intended by the user in the virtual image.

[0971] example:

[0972] The server uses an emotion engine to recognize User A's emotions (e.g., happiness, surprise, sadness) from the uploaded facial photo.

[0973] Based on the perceived emotion, "happiness" was added to the prompt.

[0974] The server updates the prompt with the emotion and saves it in the database.

[0975] 3. Generating virtual images using AI models

[0976] The server uses AI technology to generate a virtual person image based on the stored facial photo and updated prompts. During the generation process, the image is adjusted according to the prompts to reflect the specified characteristics and emotions. The generated virtual image is also stored in a database.

[0977] example:

[0978] The server inputs a facial photo into the AI ​​model based on the updated prompt, and generates a virtual person image with an output ratio of 50% and reflecting the emotion of "happiness."

[0979] The server stores the generated virtual images in a database.

[0980] 4. Providing the generated images to companies

[0981] When a company needs a virtual person image, the server receives the request from the company and searches for and provides virtual images that meet the company's requirements. The images presented to the company are strictly managed by the system and provided after appropriate authentication.

[0982] example:

[0983] Company B requests virtual images for a new advertising campaign.

[0984] The server receives Company B's requirements and searches the database for matching images.

[0985] The server provides Company B with a link to download the proposed virtual image.

[0986] 5. Usage tracking and rewards

[0987] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this data, it pays compensation to the data provider, the user. Compensation is calculated based on the output ratio of the provided data, the frequency of use of the generated virtual image, and the impact of emotional reflection.

[0988] example:

[0989] The server monitors the usage of virtual images used in Company B's advertisements.

[0990] The server aggregates the sales data obtained from Company B and calculates the reward for User A based on the output ratio of facial components and the degree of influence of emotional reflection.

[0991] The server transfers the reward to User A's account and displays the reward details on their personal page.

[0992] This system allows users to provide a photo of their face, and the virtual person image generated based on that photo can be used safely for advertising purposes with clear rights. Furthermore, users can receive appropriate compensation for the data they provide, and more personalized advertising can be achieved by reflecting emotions.

[0993] The processing flow will be explained below.

[0994] Step 1:

[0995] The user logs into the system.

[0996] Step 2:

[0997] The server verifies the user's authentication information and checks the database to ensure the user is a legitimate user.

[0998] Step 3:

[0999] The user moves to the face photo upload screen and selects a face photo file.

[1000] Step 4:

[1001] The user enters the prompts (output ratio and desired characteristics) and clicks the "Upload" button.

[1002] Step 5:

[1003] The server receives the uploaded face photo and prompt and stores them in a database.

[1004] Step 6:

[1005] The server uses an emotion engine to recognize the user's emotions from the stored facial photographs.

[1006] Step 7:

[1007] The server updates the prompt based on the recognized emotion and stores it in a database.

[1008] Step 8:

[1009] The server inputs the updated prompt and facial photo into the AI ​​model to generate a virtual person image.

[1010] Step 9:

[1011] The server stores the generated virtual person images in a database.

[1012] Step 10:

[1013] The server receives requests for virtual persona images from businesses.

[1014] Step 11:

[1015] The server searches the database for matching virtual person images based on the company's request conditions.

[1016] Step 12:

[1017] The server selects virtual person images to propose to companies and provides them with downloadable links.

[1018] Step 13:

[1019] The server monitors the usage of the provided virtual person images.

[1020] Step 14:

[1021] The server aggregates sales data obtained from companies and calculates rewards based on the output ratio of the user's facial components and the influence of emotional reflection.

[1022] Step 15:

[1023] The server transfers the calculated reward to the user's account.

[1024] Step 16:

[1025] The server displays the reward details on the user's My Page.

[1026] Example 2

[1027] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1028] Conventional virtual image generation systems have the problem of being unable to extract sufficient information from facial photos uploaded by users, resulting in low personalization of the generated virtual images. Furthermore, they lacked mechanisms for tracking how the generated virtual images were used and providing appropriate compensation to users. This resulted in low user engagement and limited system usage.

[1029] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for a user to upload a facial photograph, means for saving the uploaded facial photograph and a prompt, means for generating a virtual image based on the saved facial photograph and the prompt, means for recognizing the user's emotion from the facial photograph in generating the virtual image and reflecting the emotion in the prompt, means for providing the generated virtual image to an organization, means for tracking the usage of the provided virtual image, and means for paying compensation to the data provider based on the tracked usage. This makes it possible to provide a more personalized virtual image that reflects the user's emotion, track the usage of the image, and pay appropriate compensation.

[1030] "User" refers to an individual or organization that uses the system to upload a facial photograph and generate a virtual image.

[1031] "Mugshot" refers to image data that a user uploads to the system, showing the face of themselves or another individual.

[1032] "Prompt text" refers to text data such as output ratio and desired features that a user enters when uploading a face photo.

[1033] An "emotion engine" refers to software that analyzes uploaded facial photos to recognize a user's emotions.

[1034] "Virtual image" refers to a virtual image of a person generated by an AI model based on the user's facial photo and prompt text.

[1035] A "generative AI model" refers to an artificial intelligence algorithm that generates a virtual image using a facial photo and a prompt as input.

[1036] "Organization" refers to a legal entity or group that receives the generated virtual image from the system for use.

[1037] "Usage" refers to tracking information about how the provided virtual imagery is used by an organization.

[1038] "Compensation" refers to the compensation a user receives for providing a virtual image.

[1039] The system of this invention involves a series of processes: users upload facial photos, companies are provided with virtual images generated from those photos, usage is tracked, and compensation is paid to the data provider. Furthermore, by combining this system with an emotion engine that recognizes the user's emotions, the system can generate more personalized virtual images. Specific embodiments of this system are described below.

[1040] Upload and save your photo

[1041] The user logs in to the system using a device (PC or smartphone) and uploads a facial photo. Once authentication is complete, the server displays a facial photo upload screen on the device. The user selects a facial photo file on this screen and enters prompts such as "output ratio" and "desired features." For example, the user can enter "output ratio 50%, bright features." When the user presses the "Upload" button, the facial photo and prompt are sent from the device to the server, which then stores this data in a database.

[1042] Emotion recognition by emotion engine

[1043] The server retrieves the face photo stored in the database and inputs it into the emotion engine. The emotion engine is software that analyzes the uploaded face photo to recognize the user's emotions (e.g., happiness, surprise, sadness, etc.). The emotion engine analyzes the face photo and adds the recognized emotion to the prompt text. For example, "happiness" can be added to "output ratio 50%, bright features." The server then saves the updated prompt text back to the database.

[1044] Generating virtual images using AI models

[1045] The server retrieves the updated prompt and facial photo from the database. Based on this, the server generates a virtual image using a generative AI model. A generative AI model is an artificial intelligence algorithm that generates a virtual image based on a facial photo and a prompt. During this generation process, the image is adjusted according to the prompt. The generated virtual image is stored in the database.

[1046] Providing generated images to companies

[1047] There is a means for a company to access the system and request the conditions of the virtual image they need. For example, a company can request "virtual images with positive emotions for an advertising campaign." The server searches the database for matching images based on the company's request conditions. If a matching virtual image is found, the server provides the company with a download link. The company can use this link to obtain the virtual image.

[1048] Usage tracking and rewards

[1049] The server monitors the usage of the provided virtual images through feedback from the companies. For example, it can track data such as how often the virtual images are displayed as advertisements and how many clicks they receive. In addition, the server collects sales data provided by the companies and calculates the user's compensation based on the frequency of use of the virtual images and the impact of their emotional reflection. Based on this calculation, the compensation is transferred to the user's account, and a compensation statement is displayed on the user's personal page.

[1050] With this system, users can provide a photo of their face, and the virtual image generated based on that photo can be safely used by companies with clear rights. Users can also receive appropriate compensation for the data they provide. By incorporating emotions, more personalized virtual images can be provided, making them attractive content for companies.

[1051] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1052] Step 1: Login authentication

[1053] A user logs in to the system using a terminal by entering a username and password. The entered authentication information is sent to the server, which checks it against the authentication information in the database. If authentication is successful, the server returns a success message and directs the user to a screen to upload a face photo.

[1054] Input: Username, Password

[1055] Data processing: Matching with authentication information in the database

[1056] Output: Login success message, face photo upload screen

[1057] Step 2: Upload your photo and prompt

[1058] The user selects a facial photo file and enters prompts such as desired features and output ratio into the terminal. When the user presses the "Upload" button, the facial photo and prompt are sent to the server, which then stores this data in a database.

[1059] Input: Face photo, prompt (e.g., "Output ratio 50%, bright features")

[1060] Data processing: Combining face photos and prompts

[1061] Output: Save to database

[1062] Step 3: Emotion Recognition

[1063] The server inputs the received facial photo into the emotion engine and performs image analysis. The emotion engine recognizes the user's emotion (e.g., "happiness") from the facial photo and adds the detected emotion to the prompt. The updated prompt is saved in the database.

[1064] Input: Face photo

[1065] Data processing: facial photo analysis, emotion recognition

[1066] Output: Save the updated prompt statement

[1067] Step 4: Virtual Image Generation

[1068] The server retrieves the face photo and updated prompt text from the database and inputs this data into the generative AI model, which then generates a virtual image based on the input data. The generated virtual image is then stored in the database.

[1069] Input: Face photo, updated prompt text

[1070] Data processing: Image generation based on facial photos and prompt sentences

[1071] Output: Save to database

[1072] Step 5: Provide images to companies

[1073] A company accesses the system and requests a virtual image. The server searches the database for a suitable virtual image based on the company's request criteria and provides it to the company. The provided image is presented as a link that the company can download.

[1074] Input: Company request conditions

[1075] Data processing: Virtual image retrieval from database

[1076] Output: Provide download link

[1077] Step 6: Track usage and redeem rewards

[1078] The server monitors the usage of virtual images by companies and tracks sales data. Based on this data, compensation is calculated taking into account frequency of use and the impact of emotional reflection. The calculated compensation is transferred to the user's account, and a compensation statement is displayed on the user's personal page.

[1079] Input: Sales data and usage data from companies

[1080] Data processing: usage monitoring, reward calculation

[1081] Output: Reward transfer, reward details displayed on my page

[1082] (Application example 2)

[1083] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1084] Conventional virtual image generation systems are unable to fully reflect the user's emotions and individual characteristics, limiting their personalization. Furthermore, when companies use virtual person images in advertising, it is difficult to generate images that take the user's emotions and individual characteristics into account, and the compensation provided to users can be lacking in transparency. Furthermore, tracking of usage and compensation are insufficient, creating a need for a system to improve user motivation.

[1085] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1086] In this invention, the server includes means for a user to upload a facial photo, means for saving the uploaded facial photo and a prompt, means for recognizing the user's emotion using an emotion engine, means for reflecting the recognized emotion in a prompt, means for generating a virtual image based on the saved facial photo and the updated prompt, means for providing the generated virtual image to a company, means for tracking usage of the provided virtual image, and means for rewarding the data provider based on the tracked usage. This enables the generation of personalized virtual images that reflect the user's emotion, allowing companies to develop effective advertising campaigns. Furthermore, transparent tracking of usage and appropriate reward rewards are realized, thereby improving user motivation.

[1087] "User" means a person who uploads a facial photograph to the system and generates or provides a virtual image.

[1088] A "face photo" is an image file of a user's face that is uploaded to the system.

[1089] A "means" is a method or device for performing a particular function or role within a system.

[1090] A "prompt" is an instructional text indicating settings or requirements that the user inputs along with a facial photograph.

[1091] An "emotion engine" is an algorithm or software that recognizes a user's emotions from a facial photograph.

[1092] A "virtual image" is a digital fictional image of a person created based on a facial photograph and prompts.

[1093] "Generating" means processing data within the system to create a new virtual image.

[1094] "Company" refers to a corporation or organization that uses the generated virtual images for advertising or other purposes.

[1095] "Providing" means handing over data and images in the system to the company.

[1096] "Usage status" refers to information about how the provided virtual image is used.

[1097] "Tracking" means recording and monitoring the usage of the virtual images provided.

[1098] "Consideration" refers to money or other benefits paid as compensation to the user who provides the data.

[1099] "Rebate" means paying a user a fee based on their usage.

[1100] The "system" is a collection of devices and programs that perform a series of processes to generate and provide virtual images based on the user's facial photograph, track their usage, and provide compensation.

[1101] An "updated prompt" is a prompt after the emotion has been reflected by the emotion engine.

[1102] An "artificial intelligence model" is an AI algorithm that takes data as input and generates a virtual image.

[1103] The "Advertising Virtual Creator" system, an application example of this invention, is realized as follows: The system includes a series of processes: uploading a user's facial photo, recognizing emotions, generating a virtual image, providing it to companies, tracking usage, and returning compensation.

[1104] First, the user logs in to the system using a device such as a smartphone and uploads a photo of their face. On the upload screen, the user selects a photo file and enters prompts such as the output ratio and desired features. This data is received by the system's server and stored in a database.

[1105] The server then analyzes the stored facial photo with an "emotion engine" to recognize the user's emotion (e.g., happiness, surprise, sadness). The recognized emotion is added to the prompt, generating an updated prompt. This updated prompt is then saved back to the database.

[1106] The server then inputs the updated prompt and the facial photo into a "generative AI model" to generate a virtual image, which is also stored in a database.

[1107] When a company needs a virtual image, the server receives the request, searches the database for a virtual image that matches the company's requirements, and provides it. The image is provided after a strict authentication process.

[1108] The server monitors the usage of the provided virtual images and tracks sales data provided by companies. Based on this, rewards are paid to the users who provided the data. Rewards are calculated automatically within the system and transferred to the users' accounts.

[1109] As a specific example, the following prompt sentence may be entered:

[1110] Example prompt sentence:

[1111] Input image: face_photo.jpg

[1112] Output ratio: 50%

[1113] Emotion: Happiness

[1114] The generated virtual image is provided to Company B for advertising purposes.

[1115] This system enables the generation of personalized virtual images that reflect the user's emotions, allowing companies to develop effective advertising campaigns. It also enables transparent tracking of usage and appropriate rewards, improving user motivation.

[1116] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1117] Step 1:

[1118] A user logs in to the system using a terminal and uploads a photo of their face.

[1119] Input: Face photo file and prompt data (e.g., output ratio, desired features)

[1120] The server receives the facial photo file and prompt data and stores this data in a database.

[1121] Output: Face photo stored in the database and prompt

[1122] Step 2:

[1123] The server analyzes the stored facial photos using an emotion engine to recognize the user's emotions.

[1124] Input: A face photo stored in the database

[1125] The server uses an emotion engine to analyze the facial photo and update the prompt with the recognized emotion (e.g., happiness, surprise, sadness).

[1126] Output: The updated prompt is saved to the database.

[1127] Step 3:

[1128] The server inputs the updated prompt and facial photo into a generative AI model to generate a virtual image.

[1129] Input: Updated prompt and face photo

[1130] The server uses a generative AI model to generate a virtual image based on the facial photo and prompt, and stores the generated virtual image in a database.

[1131] Output: Virtual images stored in a database

[1132] Step 4:

[1133] When a business requests a virtual image, the server receives the request from the business.

[1134] Input: Request conditions from the company (e.g. requirements for virtual images for advertising)

[1135] The server searches the database for virtual images that match the requested criteria and provides them to the company.

[1136] Output: Virtual images provided to the company

[1137] Step 5:

[1138] The server monitors the usage of the provided virtual images and tracks sales data from the companies.

[1139] Input: Usage information of the provided virtual image and company sales data

[1140] The server aggregates usage and sales data and evaluates frequency of use and impact.

[1141] Output: Usage reports and evaluation data

[1142] Step 6:

[1143] The server will provide compensation to the user depending on the usage status.

[1144] Input: Usage reports and evaluation data

[1145] The server calculates the reward based on the evaluation data and deposits the reward into the user's account.

[1146] Output: Reward given to the user

[1147] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1148] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1149] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1150] [Fourth embodiment]

[1151] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1152] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1153] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1154] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1155] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1156] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1157] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1158] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1159] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1160] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1161] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1162] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1163] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1164] The system of this invention performs a series of processes: users upload facial photographs, companies are provided with virtual images generated from those photographs, usage is tracked, and compensation is paid to the data providers. A specific embodiment of the system is described below.

[1165] 1. User provides face photo

[1166] A user logs in to the system and uploads a facial photo. On the facial photo upload screen, the user selects their own facial photo file and enters prompts (e.g., output ratio and desired features). These data are received by the system and stored on the server.

[1167] example:

[1168] User A logs in to the system, selects his or her own face photo, and sets the "output ratio" to 50%.

[1169] User A clicks the "Upload" button to send the photo and prompt to the server.

[1170] The server stores the received images and prompts in a database.

[1171] 2. Generating virtual images using AI models

[1172] The server uses AI technology to generate a virtual person image based on the stored facial photo and prompts. During the generation process, the image is adjusted according to the prompts' specified features and output ratios. The generated virtual image is also stored in the database.

[1173] example:

[1174] The server extracts the face photo and prompt from the database and inputs them into the AI ​​model.

[1175] The AI ​​model generates a virtual person image from User A's facial photo with an output ratio of 50%.

[1176] The server stores the generated virtual images in a database.

[1177] 3. Providing the generated images to companies

[1178] When a company needs a virtual person image, the server receives the request from the company and searches for and provides virtual images that meet the company's requirements. The images presented to the company are strictly managed by the system and provided after appropriate authentication.

[1179] example:

[1180] Company B requests virtual images for a new advertising campaign.

[1181] The server receives Company B's requirements and searches the database for matching images.

[1182] The server provides Company B with a link to download the proposed virtual image.

[1183] 4. Usage tracking and rewards

[1184] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this, it pays compensation to the users who provide the data. The compensation is calculated based on the output rate of the provided data and the frequency of use of the generated virtual images.

[1185] example:

[1186] The server monitors the usage of virtual images used in Company B's advertisements.

[1187] The server aggregates the sales data obtained from Company B and calculates the reward for User A based on the output ratio of the facial components.

[1188] The server transfers the reward to User A's account and displays the reward details on their personal page.

[1189] This system allows users to provide a photograph of their face, and the virtual person image generated based on that photograph is used safely for advertising purposes with clear rights. Furthermore, users are compensated appropriately for the data they provide, ensuring transparency and fairness.

[1190] The processing flow will be explained below.

[1191] Step 1:

[1192] The user logs into the system.

[1193] Step 2:

[1194] The server verifies the user's authentication information and checks the database to ensure the user is a legitimate user.

[1195] Step 3:

[1196] The user moves to the face photo upload screen and selects a face photo file.

[1197] Step 4:

[1198] The user enters the prompts (output ratio and desired characteristics) and clicks the "Upload" button.

[1199] Step 5:

[1200] The server receives the uploaded face photo and prompt and stores them in a database.

[1201] Step 6:

[1202] The server uses an AI model to generate a virtual persona based on the stored facial photo and prompts.

[1203] Step 7:

[1204] The server stores the generated virtual person images in a database.

[1205] Step 8:

[1206] The server receives requests for virtual persona images from businesses.

[1207] Step 9:

[1208] The server searches the database for matching virtual person images based on the company's request conditions.

[1209] Step 10:

[1210] The server selects virtual person images to propose to companies and provides them with downloadable links.

[1211] Step 11:

[1212] The server monitors the usage of the provided virtual person images.

[1213] Step 12:

[1214] The server aggregates sales data obtained from companies and calculates rewards based on the output ratio of the user's facial components.

[1215] Step 13:

[1216] The server transfers the calculated reward to the user's account.

[1217] Step 14:

[1218] The server displays the reward details on the user's My Page.

[1219] Example 1

[1220] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1221] In recent years, the creation and commercial use of virtual person images has increased, but there is currently no system in place to securely manage facial photos provided by users, ensure transparency regarding the use of the generated virtual images, or provide fair compensation to users. Therefore, there is a need to develop a system that allows companies to efficiently use virtual images while maintaining a balance between protecting user privacy and providing compensation.

[1222] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1223] In this invention, the server includes a means for users to upload image data, a means for storing the uploaded image data and instruction information, a means for generating a virtual person image based on the stored image data and instruction information, a means for providing the generated virtual person image to an organization, a means for tracking the usage of the provided virtual person image, and a means for providing compensation to the data provider based on the tracked usage. This allows users to safely provide their own facial photographs, and the virtual image generated based on them is used appropriately, enabling transparency and compensation to users. Furthermore, companies can effectively use high-quality virtual person images.

[1224] A "user" is a person who provides a facial photograph and instruction information to the system and receives payment for the use of the generated virtual person image.

[1225] "Image data" refers to facial photographs and other visual information that users upload to the system.

[1226] "Instruction information" refers to information related to prompt statements and output settings that the user inputs in relation to image data.

[1227] A "virtual person image" refers to an image of a non-existent person that is generated based on image data and instruction information.

[1228] "Server" refers to the equipment and programs that receive and store image data and instruction information, generate virtual person images, and provide them to companies.

[1229] "Organization" refers to a company or organization that commercially uses the generated virtual person images.

[1230] "Usage" refers to data used to track how the provided virtual person images are used by companies and organizations.

[1231] "Rebate" refers to the process of providing compensation or other benefits to users based on their use of the virtual person image.

[1232] The system of this invention performs a series of processes: a user uploads image data (a facial photograph), a virtual person image generated based on that image data is provided to a company, usage is tracked, and compensation is paid to the data provider. A specific embodiment of the system is described below.

[1233] 1. User-provided image data

[1234] Users log in to the system using their own terminals, entering their ID and password on the login page and undergoing authentication.

[1235] The user accesses the image data upload page, clicks the "Select File" button, and selects a photo of their own face (e.g., "my_photo.jpg").

[1236] The user inputs a prompt as instruction information related to the image data, such as "Output ratio 50%, desired feature: smiling face."

[1237] When the user clicks the "Upload" button, the image data and the prompt text are sent to the server.

[1238] 2. Data storage by the server

[1239] The server receives the image data and prompt text sent by the user. The received data is stored in the image storage and the database. The image data is stored in the image storage, and the prompt text and image file paths are stored in the database.

[1240] 3. Generation of Virtual Person Images

[1241] The server extracts the stored image data and prompt sentences from the database, and the extracted data is input to a generative AI model (e.g., StyleGAN).

[1242] The AI ​​model processes image data according to instructions and generates a virtual person image with the specified characteristics.

[1243] The generated virtual person image is stored in the database again by the server.

[1244] 4. Provision to companies

[1245] A company logs in to the system and requests a virtual person image. Based on the criteria submitted by the company (e.g., "male in his 30s, output ratio 50%, smiling"), the server searches the database for a matching image.

[1246] When a virtual person image that matches the criteria is found, the server provides the company with a download link.

[1247] 5. Usage tracking and rebates

[1248] The server monitors how companies use virtual person images, tracking company advertisements and usage reports, and collecting usage data.

[1249] The server calculates the rewards for users based on sales data from companies, and the rewards are calculated based on frequency of use and output ratio.

[1250] Rewards will be transferred to the user's account, and the user can check the details of the reward on their My Page.

[1251] This system allows users to safely provide their own facial photographs, and the virtual person images generated based on them are used appropriately, ensuring transparency and fairness. It also allows companies to efficiently use high-quality virtual person images.

[1252] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1253] Step 1: User provides image data

[1254] Input: The user logs in to the system and selects a face photo file (e.g., "my_photo.jpg") and a prompt statement (e.g., "50% output ratio, desired feature: smile").

[1255] Operation: When the user clicks the "Upload" button, the image data and the prompt text are sent to the server. The data sent from the user's device is received by the server as an HTTP request.

[1256] Output: The server receives the image data and the prompt.

[1257] Step 2: The server saves the data

[1258] Input: The image data received in step 1 and the prompt text.

[1259] Operation: The server saves the image data to the image storage and stores the prompt text and image file path in the database. This includes the process of creating an entry in the database and recording the physical storage location of the facial photo data.

[1260] Output: The image data is saved to the image storage, and the prompt text and the path to the image file are saved to the database.

[1261] Step 3: The server uses the AI ​​model to generate the image

[1262] Input: Image data retrieved from the database and prompt text.

[1263] How it works: The server inputs image data and a prompt into an AI generative model (e.g., StyleGAN). The model generates a virtual person image according to the instructions. Here, the AI ​​model extracts features from the facial photo and processes them according to the prompt.

[1264] Output: The generated virtual person image is returned to the server.

[1265] Step 4: The server saves the generated image

[1266] Input: The virtual person image generated in step 3.

[1267] Operation: The server saves the generated virtual person image in the image storage and saves the path of the generated image in the database.

[1268] Output: The generated virtual person image is saved in the image storage, and its path is recorded in the database.

[1269] Step 5: The company requests images

[1270] Input: The company logs into the system and enters the required conditions (e.g., "male in his 30s, output ratio 50%, smiling face").

[1271] How it works: The server receives a request from a company and searches its database for images that match the criteria.

[1272] Output: As a search result, a list of virtual person images that match the conditions is extracted.

[1273] Step 6: The server serves the image to the company

[1274] Input: Virtual person images that match the criteria found in step 5.

[1275] How it works: The server provides the company with a download link for the image, which the company can then use to retrieve the image.

[1276] Output: A download link accessible to the company.

[1277] Step 7: The server tracks usage

[1278] Input: Information on the virtual person image used by the company.

[1279] How it works: A server monitors a company's use of images in advertising and collects usage data, including recording data such as when, where, and how often the images are used.

[1280] Output: Usage data is recorded in a database.

[1281] Step 8: The server calculates the payment and returns it to the user

[1282] Inputs: Usage data collected in step 7 and sales data from the company.

[1283] How it works: The server calculates the user's reward based on the frequency of use and output rate. The calculated reward is transferred to the user's account. The user can check the reward details on their My Page.

[1284] Output: Reward is transferred to the user and a reward statement is displayed.

[1285] (Application example 1)

[1286] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1287] In recent years, the generation and use of virtual images based on user-provided facial photographs has many potential applications. However, the way these images are used and how users are compensated remains unclear, making it difficult to gain user trust. Furthermore, there is a lack of an effective system for easily managing the generation and usage of virtual images. Therefore, there is a need for an environment where users can provide facial photographs with confidence and where companies can efficiently use virtual images.

[1288] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1289] In this invention, the server includes means for users to upload facial photographs, means for saving the uploaded facial photographs and prompts, means for generating virtual images based on the saved facial photographs and prompts, means for providing the generated virtual images to companies, means for tracking usage of the provided virtual images, means for paying compensation to users based on the tracked usage, and means for managing the generation and usage of virtual images via a smartphone application. This allows users to visualize how their provided data is used and receive appropriate compensation.

[1290] "User" refers to a person who uses this system to upload a facial photo and generate a virtual image.

[1291] "Facial photo" refers to image data of a user's face.

[1292] A "prompt" refers to text data used to specify the characteristics and output ratio of a virtual image generated based on a facial photograph.

[1293] "Virtual Image" refers to a virtual person image generated by an artificial intelligence model based on a user's facial photograph and prompts.

[1294] "Company" refers to a corporation or organization that uses the generated virtual images for purposes such as advertising materials.

[1295] "Smartphone application" refers to software that runs on a smartphone and provides the functions of this system.

[1296] "Server" refers to a computer system that executes the functions of this system and stores and processes data.

[1297] "Consideration" refers to the compensation paid for the use of a user's facial photograph.

[1298] This invention is a system that allows users to upload a facial photo, generates a virtual image based on the photo using an AI model, and provides it to companies. It also tracks the usage of the provided virtual image and can compensate users for it. These functions can be easily managed using a smartphone application.

[1299] Hardware and Software Configuration

[1300] Hardware:

[1301] Smartphone: A device that allows users to upload photos of their face and generate and manage virtual images.

[1302] Server: A set of computer systems that store facial photos and prompts, generate virtual images, and track usage.

[1303] software:

[1304] requests: A Python library for sending HTTP requests, uploading and retrieving data.

[1305] PIL (Python Imaging Library): A Python library for manipulating and processing image data.

[1306] Overall system flow

[1307] 1. Upload a photo of your face

[1308] A user logs in to the system using a smartphone application and uploads a facial photo. On the upload screen, the user enters the facial photo file along with prompts (e.g., output ratio and desired features). This data is sent to the server via an HTTP request and stored on the server.

[1309] Examples:

[1310] The user selects a photo of their face, enters prompts such as "50% output ratio" and "enhance brightness and contrast," and then uploads it.

[1311] 2. Virtual Image Generation

[1312] The server uses a generative AI model to generate a virtual image based on the stored facial photo and prompts. During the generation process, the image is adjusted according to the prompts, based on the specified features and output ratio. The generated virtual image is also stored in a database.

[1313] Examples:

[1314] The server extracts a face photo and prompts from the database and generates a virtual image with slightly enhanced brightness and contrast at a 50% output ratio according to the prompts.

[1315] 3. Providing the generated images to companies

[1316] When a company needs a virtual image, the server receives the request, searches for and provides virtual images that match the company's requirements, and the images are provided after strict authentication.

[1317] Examples:

[1318] Businesses request virtual images for new advertising campaigns, and the server provides the businesses with images that match their criteria.

[1319] 4. Usage tracking and rewards

[1320] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this, the server reimburses users. The reimbursement is calculated based on the output rate of the provided data and the frequency of use of the generated virtual images.

[1321] Examples:

[1322] The server tracks the usage of virtual images used in corporate advertisements and rewards users based on sales data obtained from the companies.

[1323] Prompt Sentence Examples

[1324] "Please use a face photo at 70% output ratio for advertising materials, and generate it with slightly enhanced brightness and contrast."

[1325] This system allows users to provide their own facial photos with peace of mind and receive compensation in a transparent and fair environment. It also enables businesses to efficiently obtain high-quality advertising materials.

[1326] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1327] Step 1:

[1328] A user logs in to the system using a smartphone application. They select a face photo and input prompts (e.g., output ratio and desired features). The input data (face photo file and prompt) is sent to the server as an HTTP request. The server receives it and stores it in a database. Based on the input data, the face photo and prompt are appropriately saved.

[1329] Step 2:

[1330] The server extracts the stored facial photo and prompt. The facial photo and prompt are input into the generation AI model. The AI ​​model processes the data (using image processing technology) to generate a virtual image. Specifically, it generates a virtual image that reflects the output ratio and specified features according to the prompt. This generated virtual image is then stored back in the database.

[1331] Step 3:

[1332] A company sends a request to the server to use a virtual image. The server searches its database for virtual images that match the company's criteria (e.g., type of advertising campaign or image characteristics). It selects the appropriate virtual image from the search results and provides it to the company. After authentication and appropriate data filtering, it sends the company a downloadable link.

[1333] Step 4:

[1334] The server monitors how the provided virtual images are used by companies. Specifically, it periodically collects and analyzes data on the companies' advertising campaigns and sales. Based on the analysis results, it evaluates the frequency of use of the virtual images and their contribution to sales. Based on this evaluation, it calculates the remuneration for the users.

[1335] Step 5:

[1336] The server returns rewards to users based on their usage. Specifically, it calculates the appropriate reward amount for each user based on sales data and frequency of use. The calculated reward is transferred to the user's account and displayed as a reward statement on the user's My Page in the smartphone application. Users can check the reward details on the application.

[1337] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1338] The system of the present invention performs a series of processes: users upload facial photos, virtual images generated from those photos are provided to companies, usage is tracked, and compensation is paid to the data provider. Furthermore, the present invention can generate more personalized virtual images by combining an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention are described in detail below.

[1339] 1. User provides face photo

[1340] A user logs in to the system and uploads a facial photo. On the facial photo upload screen, the user selects their own facial photo file and enters prompts (e.g., output ratio and desired features). These data are received by the system and stored on the server.

[1341] example:

[1342] User A logs in to the system, selects his or her own face photo, and sets the "output ratio" to 50%.

[1343] User A clicks the "Upload" button to send the photo and prompt to the server.

[1344] The server stores the received images and prompts in a database.

[1345] 2. Emotion Recognition by Emotion Engine

[1346] The server uses an emotion engine to recognize the user's emotions from the facial photo uploaded by the user. The recognized emotions are reflected in the prompts, allowing the user to reflect the facial expressions and emotions intended by the user in the virtual image.

[1347] example:

[1348] The server uses an emotion engine to recognize User A's emotions (e.g., happiness, surprise, sadness) from the uploaded facial photo.

[1349] Based on the perceived emotion, "happiness" was added to the prompt.

[1350] The server updates the prompt with the emotion and saves it in the database.

[1351] 3. Generating virtual images using AI models

[1352] The server uses AI technology to generate a virtual person image based on the stored facial photo and updated prompts. During the generation process, the image is adjusted according to the prompts to reflect the specified characteristics and emotions. The generated virtual image is also stored in a database.

[1353] example:

[1354] The server inputs a facial photo into the AI ​​model based on the updated prompt, and generates a virtual person image with an output ratio of 50% and reflecting the emotion of "happiness."

[1355] The server stores the generated virtual images in a database.

[1356] 4. Providing the generated images to companies

[1357] When a company needs a virtual person image, the server receives the request from the company and searches for and provides virtual images that meet the company's requirements. The images presented to the company are strictly managed by the system and provided after appropriate authentication.

[1358] example:

[1359] Company B requests virtual images for a new advertising campaign.

[1360] The server receives Company B's requirements and searches the database for matching images.

[1361] The server provides Company B with a link to download the proposed virtual image.

[1362] 5. Usage tracking and rewards

[1363] The server monitors the usage of the provided virtual images and tracks sales data from companies. Based on this data, it pays compensation to the data provider, the user. Compensation is calculated based on the output ratio of the provided data, the frequency of use of the generated virtual image, and the impact of emotional reflection.

[1364] example:

[1365] The server monitors the usage of virtual images used in Company B's advertisements.

[1366] The server aggregates the sales data obtained from Company B and calculates the reward for User A based on the output ratio of facial components and the degree of influence of emotional reflection.

[1367] The server transfers the reward to User A's account and displays the reward details on their personal page.

[1368] This system allows users to provide a photo of their face, and the virtual person image generated based on that photo can be used safely for advertising purposes with clear rights. Furthermore, users can receive appropriate compensation for the data they provide, and more personalized advertising can be achieved by reflecting emotions.

[1369] The processing flow will be explained below.

[1370] Step 1:

[1371] The user logs into the system.

[1372] Step 2:

[1373] The server verifies the user's authentication information and checks the database to ensure the user is a legitimate user.

[1374] Step 3:

[1375] The user moves to the face photo upload screen and selects a face photo file.

[1376] Step 4:

[1377] The user enters the prompts (output ratio and desired characteristics) and clicks the "Upload" button.

[1378] Step 5:

[1379] The server receives the uploaded face photo and prompt and stores them in a database.

[1380] Step 6:

[1381] The server uses an emotion engine to recognize the user's emotions from the stored facial photographs.

[1382] Step 7:

[1383] The server updates the prompt based on the recognized emotion and stores it in a database.

[1384] Step 8:

[1385] The server inputs the updated prompt and facial photo into the AI ​​model to generate a virtual person image.

[1386] Step 9:

[1387] The server stores the generated virtual person images in a database.

[1388] Step 10:

[1389] The server receives requests for virtual persona images from businesses.

[1390] Step 11:

[1391] The server searches the database for matching virtual person images based on the company's request conditions.

[1392] Step 12:

[1393] The server selects virtual person images to propose to companies and provides them with downloadable links.

[1394] Step 13:

[1395] The server monitors the usage of the provided virtual person images.

[1396] Step 14:

[1397] The server aggregates sales data obtained from companies and calculates rewards based on the output ratio of the user's facial components and the influence of emotional reflection.

[1398] Step 15:

[1399] The server transfers the calculated reward to the user's account.

[1400] Step 16:

[1401] The server displays the reward details on the user's My Page.

[1402] Example 2

[1403] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1404] Conventional virtual image generation systems have the problem of being unable to extract sufficient information from facial photos uploaded by users, resulting in low personalization of the generated virtual images. Furthermore, they lacked mechanisms for tracking how the generated virtual images were used and providing appropriate compensation to users. This resulted in low user engagement and limited system usage.

[1405] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for a user to upload a facial photograph, means for saving the uploaded facial photograph and a prompt, means for generating a virtual image based on the saved facial photograph and the prompt, means for recognizing the user's emotion from the facial photograph in generating the virtual image and reflecting the emotion in the prompt, means for providing the generated virtual image to an organization, means for tracking the usage of the provided virtual image, and means for paying compensation to the data provider based on the tracked usage. This makes it possible to provide a more personalized virtual image that reflects the user's emotion, track the usage of the image, and pay appropriate compensation.

[1406] "User" refers to an individual or organization that uses the system to upload a facial photograph and generate a virtual image.

[1407] "Mugshot" refers to image data that a user uploads to the system, showing the face of themselves or another individual.

[1408] "Prompt text" refers to text data such as output ratio and desired features that a user enters when uploading a face photo.

[1409] An "emotion engine" refers to software that analyzes uploaded facial photos to recognize a user's emotions.

[1410] "Virtual image" refers to a virtual image of a person generated by an AI model based on the user's facial photo and prompt text.

[1411] A "generative AI model" refers to an artificial intelligence algorithm that generates a virtual image using a facial photo and a prompt as input.

[1412] "Organization" refers to a legal entity or group that receives the generated virtual image from the system for use.

[1413] "Usage" refers to tracking information about how the provided virtual imagery is used by an organization.

[1414] "Compensation" refers to the compensation a user receives for providing a virtual image.

[1415] The system of this invention involves a series of processes: users upload facial photos, companies are provided with virtual images generated from those photos, usage is tracked, and compensation is paid to the data provider. Furthermore, by combining this system with an emotion engine that recognizes the user's emotions, the system can generate more personalized virtual images. Specific embodiments of this system are described below.

[1416] Upload and save your photo

[1417] The user logs in to the system using a device (PC or smartphone) and uploads a facial photo. Once authentication is complete, the server displays a facial photo upload screen on the device. The user selects a facial photo file on this screen and enters prompts such as "output ratio" and "desired features." For example, the user can enter "output ratio 50%, bright features." When the user presses the "Upload" button, the facial photo and prompt are sent from the device to the server, which then stores this data in a database.

[1418] Emotion recognition by emotion engine

[1419] The server retrieves the face photo stored in the database and inputs it into the emotion engine. The emotion engine is software that analyzes the uploaded face photo to recognize the user's emotions (e.g., happiness, surprise, sadness, etc.). The emotion engine analyzes the face photo and adds the recognized emotion to the prompt text. For example, "happiness" can be added to "output ratio 50%, bright features." The server then saves the updated prompt text back to the database.

[1420] Generating virtual images using AI models

[1421] The server retrieves the updated prompt and facial photo from the database. Based on this, the server generates a virtual image using a generative AI model. A generative AI model is an artificial intelligence algorithm that generates a virtual image based on a facial photo and a prompt. During this generation process, the image is adjusted according to the prompt. The generated virtual image is stored in the database.

[1422] Providing generated images to companies

[1423] There is a means for a company to access the system and request the conditions of the virtual image they need. For example, a company can request "virtual images with positive emotions for an advertising campaign." The server searches the database for matching images based on the company's request conditions. If a matching virtual image is found, the server provides the company with a download link. The company can use this link to obtain the virtual image.

[1424] Usage tracking and rewards

[1425] The server monitors the usage of the provided virtual images through feedback from the companies. For example, it can track data such as how often the virtual images are displayed as advertisements and how many clicks they receive. In addition, the server collects sales data provided by the companies and calculates the user's compensation based on the frequency of use of the virtual images and the impact of their emotional reflection. Based on this calculation, the compensation is transferred to the user's account, and a compensation statement is displayed on the user's personal page.

[1426] With this system, users can provide a photo of their face, and the virtual image generated based on that photo can be safely used by companies with clear rights. Users can also receive appropriate compensation for the data they provide. By incorporating emotions, more personalized virtual images can be provided, making them attractive content for companies.

[1427] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1428] Step 1: Login authentication

[1429] A user logs in to the system using a terminal by entering a username and password. The entered authentication information is sent to the server, which checks it against the authentication information in the database. If authentication is successful, the server returns a success message and directs the user to a screen to upload a face photo.

[1430] Input: Username, Password

[1431] Data processing: Matching with authentication information in the database

[1432] Output: Login success message, face photo upload screen

[1433] Step 2: Upload your photo and prompt

[1434] The user selects a facial photo file and enters prompts such as desired features and output ratio into the terminal. When the user presses the "Upload" button, the facial photo and prompt are sent to the server, which then stores this data in a database.

[1435] Input: Face photo, prompt (e.g., "Output ratio 50%, bright features")

[1436] Data processing: Combining face photos and prompts

[1437] Output: Save to database

[1438] Step 3: Emotion Recognition

[1439] The server inputs the received facial photo into the emotion engine and performs image analysis. The emotion engine recognizes the user's emotion (e.g., "happiness") from the facial photo and adds the detected emotion to the prompt. The updated prompt is saved in the database.

[1440] Input: Face photo

[1441] Data processing: facial photo analysis, emotion recognition

[1442] Output: Save the updated prompt statement

[1443] Step 4: Virtual Image Generation

[1444] The server retrieves the face photo and updated prompt text from the database and inputs this data into the generative AI model, which then generates a virtual image based on the input data. The generated virtual image is then stored in the database.

[1445] Input: Face photo, updated prompt text

[1446] Data processing: Image generation based on facial photos and prompt sentences

[1447] Output: Save to database

[1448] Step 5: Provide images to companies

[1449] A company accesses the system and requests a virtual image. The server searches the database for a suitable virtual image based on the company's request criteria and provides it to the company. The provided image is presented as a link that the company can download.

[1450] Input: Company request conditions

[1451] Data processing: Virtual image retrieval from database

[1452] Output: Provide download link

[1453] Step 6: Track usage and redeem rewards

[1454] The server monitors the usage of virtual images by companies and tracks sales data. Based on this data, compensation is calculated taking into account frequency of use and the impact of emotional reflection. The calculated compensation is transferred to the user's account, and a compensation statement is displayed on the user's personal page.

[1455] Input: Sales data and usage data from companies

[1456] Data processing: usage monitoring, reward calculation

[1457] Output: Reward transfer, reward details displayed on my page

[1458] (Application example 2)

[1459] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1460] Conventional virtual image generation systems are unable to fully reflect the user's emotions and individual characteristics, limiting their personalization. Furthermore, when companies use virtual person images in advertising, it is difficult to generate images that take the user's emotions and individual characteristics into account, and the compensation provided to users can be lacking in transparency. Furthermore, tracking of usage and compensation are insufficient, creating a need for a system to improve user motivation.

[1461] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1462] In this invention, the server includes means for a user to upload a facial photo, means for saving the uploaded facial photo and a prompt, means for recognizing the user's emotion using an emotion engine, means for reflecting the recognized emotion in a prompt, means for generating a virtual image based on the saved facial photo and the updated prompt, means for providing the generated virtual image to a company, means for tracking usage of the provided virtual image, and means for rewarding the data provider based on the tracked usage. This enables the generation of personalized virtual images that reflect the user's emotion, allowing companies to develop effective advertising campaigns. Furthermore, transparent tracking of usage and appropriate reward rewards are realized, thereby improving user motivation.

[1463] "User" means a person who uploads a facial photograph to the system and generates or provides a virtual image.

[1464] A "face photo" is an image file of a user's face that is uploaded to the system.

[1465] A "means" is a method or device for performing a particular function or role within a system.

[1466] A "prompt" is an instructional text indicating settings or requirements that the user inputs along with a facial photograph.

[1467] An "emotion engine" is an algorithm or software that recognizes a user's emotions from a facial photograph.

[1468] A "virtual image" is a digital fictional image of a person created based on a facial photograph and prompts.

[1469] "Generating" means processing data within the system to create a new virtual image.

[1470] "Company" refers to a corporation or organization that uses the generated virtual images for advertising or other purposes.

[1471] "Providing" means handing over data and images in the system to the company.

[1472] "Usage status" refers to information about how the provided virtual image is used.

[1473] "Tracking" means recording and monitoring the usage of the virtual images provided.

[1474] "Consideration" refers to money or other benefits paid as compensation to the user who provides the data.

[1475] "Rebate" means paying a user a fee based on their usage.

[1476] The "system" is a collection of devices and programs that perform a series of processes to generate and provide virtual images based on the user's facial photograph, track their usage, and provide compensation.

[1477] An "updated prompt" is a prompt after the emotion has been reflected by the emotion engine.

[1478] An "artificial intelligence model" is an AI algorithm that takes data as input and generates a virtual image.

[1479] The "Advertising Virtual Creator" system, an application example of this invention, is realized as follows: The system includes a series of processes: uploading a user's facial photo, recognizing emotions, generating a virtual image, providing it to companies, tracking usage, and returning compensation.

[1480] First, the user logs in to the system using a device such as a smartphone and uploads a photo of their face. On the upload screen, the user selects a photo file and enters prompts such as the output ratio and desired features. This data is received by the system's server and stored in a database.

[1481] The server then analyzes the stored facial photo with an "emotion engine" to recognize the user's emotion (e.g., happiness, surprise, sadness). The recognized emotion is added to the prompt, generating an updated prompt. This updated prompt is then saved back to the database.

[1482] The server then inputs the updated prompt and the facial photo into a "generative AI model" to generate a virtual image, which is also stored in a database.

[1483] When a company needs a virtual image, the server receives the request, searches the database for a virtual image that matches the company's requirements, and provides it. The image is provided after a strict authentication process.

[1484] The server monitors the usage of the provided virtual images and tracks sales data provided by companies. Based on this, rewards are paid to the users who provided the data. Rewards are calculated automatically within the system and transferred to the users' accounts.

[1485] As a specific example, the following prompt sentence may be entered:

[1486] Example prompt sentence:

[1487] Input image: face_photo.jpg

[1488] Output ratio: 50%

[1489] Emotion: Happiness

[1490] The generated virtual image is provided to Company B for advertising purposes.

[1491] This system enables the generation of personalized virtual images that reflect the user's emotions, allowing companies to develop effective advertising campaigns. It also enables transparent tracking of usage and appropriate rewards, improving user motivation.

[1492] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1493] Step 1:

[1494] A user logs in to the system using a terminal and uploads a photo of their face.

[1495] Input: Face photo file and prompt data (e.g., output ratio, desired features)

[1496] The server receives the facial photo file and prompt data and stores this data in a database.

[1497] Output: Face photo stored in the database and prompt

[1498] Step 2:

[1499] The server analyzes the stored facial photos using an emotion engine to recognize the user's emotions.

[1500] Input: A face photo stored in the database

[1501] The server uses an emotion engine to analyze the facial photo and update the prompt with the recognized emotion (e.g., happiness, surprise, sadness).

[1502] Output: The updated prompt is saved to the database.

[1503] Step 3:

[1504] The server inputs the updated prompt and facial photo into a generative AI model to generate a virtual image.

[1505] Input: Updated prompt and face photo

[1506] The server uses a generative AI model to generate a virtual image based on the facial photo and prompt, and stores the generated virtual image in a database.

[1507] Output: Virtual images stored in a database

[1508] Step 4:

[1509] When a business requests a virtual image, the server receives the request from the business.

[1510] Input: Request conditions from the company (e.g. requirements for virtual images for advertising)

[1511] The server searches the database for virtual images that match the requested criteria and provides them to the company.

[1512] Output: Virtual images provided to the company

[1513] Step 5:

[1514] The server monitors the usage of the provided virtual images and tracks sales data from the companies.

[1515] Input: Usage information of the provided virtual image and company sales data

[1516] The server aggregates usage and sales data and evaluates frequency of use and impact.

[1517] Output: Usage reports and evaluation data

[1518] Step 6:

[1519] The server will provide compensation to the user depending on the usage status.

[1520] Input: Usage reports and evaluation data

[1521] The server calculates the reward based on the evaluation data and deposits the reward into the user's account.

[1522] Output: Reward given to the user

[1523] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1524] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1525] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1526] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1527] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1528] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1529] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1530] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1531] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1532] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1533] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1534] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1535] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1536] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1537] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1538] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1539] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1540] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1541] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1542] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1543] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1544] The following is further disclosed regarding the above embodiment.

[1545] (Claim 1)

[1546] a means for a user to upload a photograph of their face;

[1547] a means of storing the uploaded face photo and prompt;

[1548] a means for generating a virtual image based on a stored facial photograph and a prompt;

[1549] a means for providing the generated virtual image to a company;

[1550] a means of tracking the use of the virtual images provided; and

[1551] A system that includes a means for compensating data providers based on tracked usage.

[1552] (Claim 2)

[1553] 10. The system of claim 1, further comprising means for inputting a facial photo and a prompt.

[1554] (Claim 3)

[1555] 10. The system of claim 1, including an artificial intelligence model used to generate the virtual image.

[1556] "Example 1"

[1557] (Claim 1)

[1558] A means for a user to upload image data;

[1559] means for storing the uploaded image data and instruction information;

[1560] means for generating a virtual person image based on the stored image data and instruction information;

[1561] a means for providing the generated virtual person image to an organization;

[1562] A means for tracking usage of the provided virtual person image;

[1563] A system that includes a means for compensating data providers based on tracked usage.

[1564] (Claim 2)

[1565] 10. The system of claim 1, further comprising means for inputting image data and instruction information.

[1566] (Claim 3)

[1567] 10. The system of claim 1, comprising a machine learning model used to generate the virtual person image.

[1568] "Application Example 1"

[1569] (Claim 1)

[1570] a means for a user to upload a photograph of their face;

[1571] a means of storing the uploaded face photo and prompt;

[1572] a means for generating a virtual image based on a stored facial photograph and a prompt;

[1573] a means for providing the generated virtual image to a company;

[1574] a means of tracking the use of the virtual images provided; and

[1575] a means of rewarding users based on tracked usage; and

[1576] A system including means for managing the generation and use of virtual images via a smartphone application.

[1577] (Claim 2)

[1578] 10. The system of claim 1, further comprising means for inputting a facial photo and a prompt.

[1579] (Claim 3)

[1580] 10. The system of claim 1, including an artificial intelligence model used to generate the virtual image.

[1581] "Example 2: Combining Emotion Engines"

[1582] (Claim 1)

[1583] a means for a user to upload a photograph of their face;

[1584] a means for storing the uploaded face photo and prompt;

[1585] A means for generating a virtual image based on a stored facial photograph and a prompt sentence;

[1586] a means for recognizing a user's emotion from a facial photograph in generating a virtual image and reflecting the emotion in a prompt;

[1587] a means for providing the generated virtual image to an organization;

[1588] a means of tracking the use of the virtual images provided; and

[1589] A system that includes a means for compensating data providers based on tracked usage.

[1590] (Claim 2)

[1591] 10. The system of claim 1, further comprising means for inputting a facial photograph and a prompt statement.

[1592] (Claim 3)

[1593] 10. The system of claim 1, comprising a generative AI model used to generate the virtual image.

[1594] "Application example 2 when combining emotion engines"

[1595] (Claim 1)

[1596] a means for a user to upload a photograph of their face;

[1597] a means of storing the uploaded face photo and prompt;

[1598] means for recognizing a user's emotion using an emotion engine;

[1599] a means of reflecting the perceived emotions in the prompt;

[1600] a means for generating a virtual image based on a stored facial photograph and updated prompts;

[1601] a means for providing the generated virtual image to a company;

[1602] a means of tracking the use of the virtual images provided; and

[1603] A system that includes a means for compensating data providers based on tracked usage.

[1604] (Claim 2)

[1605] 10. The system of claim 1, further comprising means for inputting a facial photo and a prompt.

[1606] (Claim 3)

[1607] 10. The system of claim 1, including an artificial intelligence model used to generate the virtual image. [Explanation of symbols]

[1608] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to upload a photograph of their face; a means of storing the uploaded face photo and prompt; a means for generating a virtual image based on a stored facial photograph and a prompt; a means for providing the generated virtual image to a company; a means of tracking the use of the virtual images provided; and A system that includes a means for compensating data providers based on tracked usage.

2. The system of claim 1 further comprising means for inputting a facial photo and a prompt.

3. The system of claim 1 , further comprising an artificial intelligence model used to generate the virtual image.

Images