System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to upload a photo of the user; means for the user to enter a type of business, a title, and an age; means for a server to store the photo and the entered information in a database; means for the server to determine image processing parameters based on the information of the user; means for a AI model to process the photo based on the parameters; and means for the server to store the processed photo in the database and provide the processed photo to the user.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 today's world, with the increase in remote communication, icon images for online meetings and emails play an important role. However, the images used are not standardized, and blurry or unimpressive images are often seen. Such images can leave a bad impression on meeting participants and email recipients and have a negative impact on the company's image. First impressions are particularly important for sales staff and new employees, so it is important to use appropriate images. Therefore, in order to improve the image of individuals and companies, a system is needed that automatically generates optimal images based on the user's industry, position, and age. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a means for users to upload their own photos and enter their industry, job title, and age. It also includes a means for a server to store these photos and input information in a database and determine image processing parameters based on the user's information. The AI ​​model processes the photos based on these parameters, and the server stores the results in the database. It also provides a means for users to view and download the processed photos. This realizes a system that automatically generates, for example, bright and friendly images for sales staff, lively images for new employees, and calm images for back office staff, thereby contributing to improving the online impression of individuals and companies.

[0006] A "user" is a person who uses the system to register their own photo and enter information such as industry, job title, and age.

[0007] A "photo" is image data representing a user's appearance that is uploaded to the system.

[0008] "Industry" is information that indicates the type of job or work to which the user belongs.

[0009] A "position" is a title that indicates the position or role a user holds at work.

[0010] "Age" is information indicating the user's current age.

[0011] "Server" means the central system that receives, stores, and processes photos and input information uploaded by users.

[0012] A "database" is a system for systematically storing and managing users' photos and input information.

[0013] "Image processing parameters" are setting information such as brightness, background color, and contrast required to process a photograph.

[0014] An "AI model" is an artificial intelligence program that analyzes and processes photos based on user information and image processing parameters.

[0015] "Processed photos" are image data that have been appropriately processed by an AI model according to the user's industry, job title, and age.

[0016] "Online meeting tools" are software and services for conducting remote meetings and communication.

[0017] An "email icon" is an image used to visually represent a user of an email account. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The system based on this patent claim allows users to upload their own photos and input their industry, job title, and age, and then AI generates and provides the most suitable image.

[0040] System configuration

[0041] 1. Photo upload function

[0042] User: Logs into the system and uploads a photo of himself.

[0043] Terminal: Provides an interface for uploading photos and sends selected photos to the server.

[0044] Server: Receives uploaded photos and stores them in a database.

[0045] 2. Input function for industry, job title, and age

[0046] Terminal: Provides users with fields to input information such as industry, job title, and age.

[0047] User: Enter the required information in the provided fields and submit.

[0048] Server: Receives the entered information and stores it in a database.

[0049] 3. Image processing parameter determination function

[0050] Server: Retrieves the user's photo and input information from the database.

[0051] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, and age information.

[0052] 4. AI-based image analysis and processing functions

[0053] Server: Inputs the determined parameters and photos into the AI ​​model and instructs it on image analysis and processing.

[0054] AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[0055] Server: Obtains the processed photos and stores them in a database.

[0056] 5. Image provision function

[0057] User: Log in to the system and check the processed image.

[0058] On-device: The processed image is displayed to the user and a download function is provided.

[0059] Program processing flow

[0060] The program of this system proceeds as follows:

[0061] 1. Upload a photo

[0062] A user logs into the system and uploads a photo.

[0063] The terminal transmits the selected photos to the server, and the server stores the received photos in a database.

[0064] 2. Enter your industry and job title information

[0065] The device displays an input form for industry, job title, and age, and the user enters the information.

[0066] The terminal sends the entered information to the server, which stores it in a database.

[0067] 3. Determining image processing parameters

[0068] The server retrieves the user's photo and input information from the database.

[0069] The server determines image processing parameters based on the information.

[0070] 4. Image analysis and processing

[0071] The server inputs the photo and parameters into the AI ​​model and instructs it to analyze and process it.

[0072] The AI ​​model analyzes the photo and performs optimal processing based on the parameters.

[0073] The server retrieves the processed photos and stores them in a database.

[0074] 5. Providing edited images

[0075] Users can log in to view the edited images and download them if necessary.

[0076] The device displays the processed image and provides a download function.

[0077] Specific examples

[0078] Example of a sales representative (30 years old)

[0079] The user (sales representative) logs into the system, uploads three photos, and enters the industry as "sales," the job title as "responsible person," and the age as "30 years old."

[0080] The server stores the photos and information in a database and determines the parameters of "light background," "high brightness," and "strong contrast" based on industry, job title, and age.

[0081] The AI ​​model analyzes the photo and applies specified effects based on the parameters, such as increasing the brightness of the photo, setting a bright background, and increasing the contrast of the face.

[0082] The server stores the edited photos in a database, and users can log in to view and download the photos.

[0083] In this way, the present invention uses AI technology to automatically generate optimal images based on user information, providing photos suitable for use in online meetings and emails.

[0084] The processing flow will be explained below.

[0085] Step 1:

[0086] A user logs into the system and accesses the photo upload page.

[0087] Step 2:

[0088] The device will display a photo upload interface, where users can click the file selection button and select up to three of their own photos.

[0089] Step 3:

[0090] The user selects a photo and presses the upload button.

[0091] Step 4:

[0092] The terminal transmits the selected photo file to the server.

[0093] Step 5:

[0094] The server analyzes the received photo data and verifies whether it has been uploaded correctly.

[0095] After the server verifies it, it stores the photo data in a database.

[0096] Step 6:

[0097] The device displays a form for entering occupation, position, and age.

[0098] Step 7:

[0099] The user enters their occupation (e.g., sales), position (e.g., manager), and age (e.g., 30 years old), and presses the send button.

[0100] Step 8:

[0101] The terminal transmits the input information to the server.

[0102] The server stores the received information in a database.

[0103] Step 9:

[0104] The server retrieves the user's photo and input information from the database.

[0105] Step 10:

[0106] The server determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, and age information.

[0107] Step 11:

[0108] The server inputs the determined parameters and photo data into the AI ​​model and instructs it on image analysis and processing.

[0109] Step 12:

[0110] The AI ​​model analyzes the photo and processes it based on determined parameters.

[0111] For example, adjust brightness, change background, enhance contrast, etc.

[0112] Step 13:

[0113] The server retrieves the processed photo data and stores it in a database.

[0114] Step 14:

[0115] The user logs back into the system and accesses the confirmation page for the processed image.

[0116] Step 15:

[0117] The device will then display the edited photo to the user and offer the option to download it.

[0118] Step 16:

[0119] Users can view the edited photos and download them if necessary.

[0120] Set the photos downloaded by the user as icons for online meeting tools and emails.

[0121] Example 1

[0122] 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."

[0123] In the past, it was often time-consuming and required specialized knowledge for users to obtain the perfect profile picture for use in online meetings or emails. In particular, when editing images themselves, it was often difficult to adjust the appropriate brightness, background color, contrast, etc., resulting in a lack of a professional impression. An effective and easy-to-use system to solve these problems is needed.

[0124] 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.

[0125] In this invention, the server includes a means for users to upload their own electronic images, a means for users to input their occupation, job title, and age, and a means for the generative AI model to process the electronic images based on these parameters, thereby enabling users to easily generate their own profile pictures in an optimal form.

[0126] A "user" is a person who uses the system and uploads an electronic image of himself or herself and enters his or her occupation, job title, and age.

[0127] "Server" means a computing device that processes information received from users, stores it in a data storage device, and utilizes generative AI models to manipulate electronic images.

[0128] "Electronic images" refer to photographic data uploaded by users to the system and used as profile images for online meeting tools and email.

[0129] "Occupation" refers to information that indicates the industry or occupation in which the user is engaged.

[0130] "Position" refers to information that indicates a user's job position or title.

[0131] "Age" refers to information indicating the user's age.

[0132] A "generative AI model" is an artificial intelligence model that performs optimal image processing based on uploaded electronic images and user input.

[0133] "Image processing parameters" are the settings or conditions used by a generative AI model to process an electronic image, including brightness, background color, contrast, etc.

[0134] "Data storage device" means storage for electronic images and input information received from users, and electronic images processed by generative AI models.

[0135] This invention is a system in which a user uploads their own digital image and inputs their occupation, job title, and age, and a generative AI model generates and provides the most suitable image. This system is mainly composed of three parties: a server, a terminal, and the user.

[0136] First, a user logs in to the system and uploads their own electronic image. The user can easily perform operations through the system interface. The terminal provides an interface for uploading photos and sends the electronic image selected by the user to the server. The server validates the received electronic image and stores it in a data storage device.

[0137] Next, the terminal provides the user with an input form for information such as occupation, position, age, etc. The user enters this information and submits it. The terminal then transmits the input information to the server, which stores it in a data storage device.

[0138] The server retrieves the user's digital image and input information from the data storage device and determines image processing parameters based on the user's occupation, position, and age. For example, if the occupation is "sales," the position is "person in charge," and the age is "30," the parameters set are "light background," "high brightness," and "strong contrast."

[0139] The server then inputs the digital image along with the determined parameters into a generative AI model, which then performs image analysis and processing using libraries such as TensorFlow and PyTorch. This includes adjusting brightness, changing background colors, and enhancing contrast.

[0140] The server receives the electronic images processed by the generative AI model and stores them again in the data storage device. The user can log in to the system again and check the processed electronic images. The terminal displays the processed images to the user and provides a download function. The user can download the images as needed and use them in online meeting tools or email.

[0141] Specific examples

[0142] For example, a sales user (30 years old) logs in to the system and uploads three photos. The user enters their occupation as "sales," their position as "responsible," and their age as "30." The server stores this information in a data storage device and determines the parameters for "light background," "high brightness," and "strong contrast" based on the industry, position, and age information. The generative AI model processes the photos based on these settings, generating an image with, for example, increased brightness, a bright background, and enhanced facial contrast. The server then stores the processed electronic images in a data storage device, and the user can log in again to review the images and download them if necessary.

[0143] Prompt Sentence Examples

[0144] "Improve your sales profile photo. I have three photos. I'm 30 years old. Safely adjust the brightness, background, and contrast accordingly."

[0145] The system allows users to easily get the best profile picture possible, creating a professional impression in online meetings and emails.

[0146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0147] Step 1: The user logs in to the system and accesses the photo upload screen. The terminal displays a file input field and provides an interface for the user to select a photo. When the user selects a photo and presses the "Upload" button, the terminal sends the photo data to the server. The input is the user's photo file, and the output is the transmission result to the server. The server validates the received photo and saves it in the data storage device.

[0148] Step 2: The user accesses a screen to input occupation, position, and age information. The terminal displays a form for inputting this information, allowing the user to enter data. The terminal sends the input information to the server. The input is occupation, position, and age information, and the output is the transmission result to the server. The server saves the received information in a data storage device.

[0149] Step 3: The server retrieves the user's photo and input information from the data storage device. Using SQL queries or similar, the server retrieves the stored photo and information on occupation, position, and age. The input is the stored data record, and the output is the retrieved data. The server determines the image processing parameters based on this information. For example, for a sales representative (age 30), the parameters set are "light background," "high brightness," and "strong contrast."

[0150] Step 4: The server inputs the determined image processing parameters and the user's photo into the generative AI model. The generative AI model analyzes and processes the photo based on these parameters. The input is the image processing parameters and photo data, and the output is the processed photo data. Specifically, the generative AI model adjusts brightness, changes the background color, and enhances contrast.

[0151] Step 5: The server receives the processed photo returned by the generative AI model and stores it in the data storage device. The server re-encodes the processed photo data, stores it in cloud storage, and adds its URL to the data record. The input is the processed photo data, and the output is the result of the storage completion.

[0152] Step 6: The user logs in to the system again to view the edited photo. The device requests the edited photo data from the server and displays it. The user can download the photo if needed. The input is the user request, and the output is the edited photo data. The device generates a download link, allowing the user to download the photo.

[0153] (Application example 1)

[0154] 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."

[0155] Conventional photo editing systems require specialized knowledge and highly accurate tools for users to edit their own photos optimally, and the process requires a lot of time and effort. Furthermore, they lack the functionality to automatically generate promotional images for use in physical stores, and creating them manually is time-consuming. Therefore, there was a demand for a system that could easily and quickly generate and provide optimal promotional images.

[0156] 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.

[0157] In this invention, the server includes: a means for users to upload their own photos; a means for users to input their industry, job title, and age; a means for the server to save these photos and input information in a database; a means for the server to determine image processing parameters based on the user's information; a means for an AI model to edit the photos based on these parameters; a means for the server to save the edited photos in a database and provide them to users; a means for users to check and download the edited photos; and a means for the AI ​​to generate optimal promotional images by users inputting their own photos and store information (industry, job title, age) and provide the promotional images to be displayed on smart displays in physical stores. This allows users to quickly and efficiently generate optimal promotional images without the need for specialized knowledge or tools, and to immediately use them in physical stores, etc.

[0158] "Server" means a computer system that receives, stores, processes, and analyzes data entered by users.

[0159] "User" refers to a person or organization that uses this system to upload their own photo, enter their industry, job title, and age, and obtain the most suitable edited photo.

[0160] "Photo Uploader" means the functionality or interface that allows a User to provide their photo to the System.

[0161] "Means for inputting industry, job title, and age" refers to the functions and interfaces that allow a user to provide information about their industry, job title, and age to the system.

[0162] "Image processing parameters" refer to adjustment elements such as brightness, background, and contrast required for processing a photograph.

[0163] An "AI model" is an artificial intelligence algorithm and system that analyzes and processes input data.

[0164] "Promotional images" are images used for promotional and advertising purposes, such as on smart displays in physical stores.

[0165] A "smart display" is an electronic display device such as digital signage that is used to provide information and display advertisements in stores, events, etc.

[0166] An "edited photo" is a photo after brightness, background, and contrast have been adjusted based on image processing parameters specified by the AI ​​model.

[0167] A "database" is a storage device or medium for systematically organizing and storing information within a system.

[0168] MODE FOR CARRYING OUT THE INVENTION

[0169] This system for implementing the invention allows users to upload their own photos and input their industry, job title, and age, and then AI generates and provides the most suitable image.The system can also automatically generate promotional images for smart displays in physical stores based on user input.

[0170] System configuration

[0171] 1. Photo upload function

[0172] The server provides a means for users to upload their own photos via their devices, which are then sent to the server and stored in a database.

[0173] 2. Input function for industry, job title, and age

[0174] Users have the means to input their industry, job title, and age through the terminal, and the input information is sent to the server and stored in a database.

[0175] 3. Image processing parameter determination function

[0176] The server determines image processing parameters (brightness, background, contrast, etc.) based on the user's industry, job title, and age information, which is obtained from a database.

[0177] 4. AI-based image analysis and processing functions

[0178] The server inputs the determined parameters and the photo into the AI ​​model and instructs it to analyze and process the image. The AI ​​model analyzes the image and performs optimal processing based on the parameters.

[0179] 5. Image provision function

[0180] The processed photos are stored on a server and can be accessed by users via their devices to view and download them.

[0181] Promotional images can also be provided for display on smart displays in physical stores.

[0182] Hardware and software used

[0183] 1. Server: Stores, processes, and analyzes data. For processing functions, we use cloud computing services such as Amazon Web Services (AWS).

[0184] 2. Device: Use an internet-enabled device such as a smartphone or tablet to upload photos and enter information.

[0185] 3. AI model: For image analysis and processing, we use machine learning frameworks such as TensorFlow and PyTorch, which allow us to properly analyze the input image and generate the optimal promotional image.

[0186] Examples and prompts

[0187] For example, suppose a 25-year-old salesperson working at an apparel store wants to generate promotional images for the store's smart displays. In this case, the user would follow the steps below:

[0188] 1. Users take a photo of themselves using their smartphone and upload it to the system.

[0189] 2. The user enters the industry as "apparel," the job title as "store clerk," and the age as "25."

[0190] 3. Based on the input information, the server determines that the brightness should be set to 1.2 times, the background to a fashion-themed image, and the contrast to 1.5 times.

[0191] 4. The AI ​​model runs these settings and generates the edited photo.

[0192] 5. The user can review the edited photo and download it to display on their smart display.

[0193] Example prompt sentence:

[0194] "Based on the photo uploaded by the user, the industry "Apparel", job title "Store Clerk", and age "25", set a bright background image and adjust the photo brightness by 1.2 times and the contrast by 1.5 times."

[0195] This makes it possible to quickly generate and use effective promotional images even in physical stores.

[0196] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0197] Step 1:

[0198] The user takes and uploads their own photo using the device. The device provides a photo upload interface and sends the photo selected by the user to the server. The input is the user's photo, and the output is a photo file stored on the server.

[0199] Step 2:

[0200] The user inputs their industry, job title, and age through the terminal. The terminal displays an input form for industry, job title, and age, and when the user enters the information, it sends the data to the server. The input is the user's industry, job title, and age information, and the output is that information saved on the server.

[0201] Step 3:

[0202] The server retrieves the user's photo and input information from the database. The server loads the necessary data into memory based on the saved photo file and input information. The input is the photo and input information from the database, and the output is the related data stored in memory.

[0203] Step 4:

[0204] The server determines image processing parameters (brightness, background, contrast, etc.) based on the user's industry, job title, and age information. The server calculates the parameters using pre-set rules and models. The input is the user's information, and the output is the determined image processing parameters.

[0205] Step 5:

[0206] The server inputs the determined parameters and photo into the AI ​​model and instructs it to analyze and process the image. The AI ​​model analyzes the image and performs optimal processing based on the parameters. The input is the processing parameters and photo file, and the output is the processed image data.

[0207] Step 6:

[0208] The server stores the processed photos in a database and provides them to the user. The processed images are stored on the server and can be accessed by the user through the system. The input is the processed image data, and the output is the processed image stored in the database.

[0209] Step 7:

[0210] The user checks the edited photo on their device and downloads it if necessary. The device displays the edited photo to the user and provides a download option. The input is the edited image retrieved from the database, and the output is an image file saved on the user's device.

[0211] These specific processing steps enable users to quickly and efficiently generate optimal promotional images without the need for specialized knowledge or tools, and to immediately use them in physical stores, etc.

[0212] 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.

[0213] The present invention is a system in which users not only upload their own photos and input their industry, job title, and age, but also recognize the user's emotions using an emotion engine, and AI generates the optimal image. The detailed configuration and processing flow of the system based on the present invention are described below.

[0214] System configuration

[0215] 1. Photo upload function

[0216] User: Logs into the system and uploads a photo of himself.

[0217] Terminal: Provides an interface for uploading photos and sends selected photos to the server.

[0218] Server: Receives uploaded photos and stores them in a database.

[0219] 2. Input function for industry, job title, and age

[0220] Device: Displays an input form for industry, job title, age, etc.

[0221] User: Enter the required information in the provided fields and submit.

[0222] Server: Receives the entered information and stores it in a database.

[0223] 3. Emotion recognition function using an emotion engine

[0224] Server: Inputs the uploaded photo into the emotion engine to recognize the user's emotion.

[0225] Emotion engine: Analyzes the user's facial expressions and quantifies their emotions, such as happiness, sadness, and anger.

[0226] 4. Image processing parameter determination function

[0227] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, age, and recognized emotion.

[0228] 5. AI-based image analysis and processing functions

[0229] Server: Inputs the determined parameters and photos into the AI ​​model and instructs it on image analysis and processing.

[0230] AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[0231] Server: Obtains the processed photos and stores them in a database.

[0232] 6. Image provision function

[0233] User: Log back into the system and access the confirmation page for the processed image.

[0234] On-device: The processed image is displayed to the user and a download function is provided.

[0235] Program processing flow

[0236] The program of this system proceeds as follows:

[0237] Specific examples

[0238] Example of a sales representative (30 years old)

[0239] 1. User: A sales person logs in to the system and uploads three photos. The user enters the industry as "Sales," the job title as "Responsible Person," and the age as "30."

[0240] 2. Server: Stores the photos and input information in a database.

[0241] 3. Server: The uploaded photo is sent to the emotion engine, where the emotion of joy is recognized.

[0242] 4. Server: Determines the parameters of "bright background," "high brightness," and "strong contrast" based on industry, job title, age, and perceived happiness.

[0243] 5. AI model: Analyzes the photo and performs processing based on the determined parameters, such as increasing the brightness of the photo, setting a bright background, and enhancing the contrast of the face.

[0244] 6. Server: Stores the processed photos in a database and provides them to users.

[0245] 7. User: Log back in to the system to check the edited photo and download it if necessary. Set the downloaded photo as an icon for online meeting tools or emails.

[0246] In this way, by combining emotion engines, the present invention realizes a system that automatically generates optimal images according to the user's emotions, and further contributes to improving the image of individuals and companies online.

[0247] The processing flow will be explained below.

[0248] Step 1:

[0249] A user logs into the system and accesses the photo upload page.

[0250] Step 2:

[0251] The device will display a photo upload interface, where users can click the file selection button and select up to three of their own photos.

[0252] Step 3:

[0253] The user selects a photo and presses the upload button.

[0254] Step 4:

[0255] The terminal transmits the selected photo file to the server.

[0256] Step 5:

[0257] The server analyzes the received photo data and verifies whether it has been uploaded correctly.

[0258] After the server verifies it, it stores the photo data in a database.

[0259] Step 6:

[0260] The device displays a form for entering industry, job title, and age.

[0261] Step 7:

[0262] The user enters the industry (e.g., sales), job title (e.g., person in charge), and age (e.g., 30 years old), and presses the send button.

[0263] Step 8:

[0264] The terminal transmits the input information to the server.

[0265] The server stores the received information in a database.

[0266] Step 9:

[0267] The server retrieves the user's photo and input information from the database.

[0268] Step 10:

[0269] The server inputs the uploaded photos into an emotion engine to recognize the user's emotions.

[0270] Step 11:

[0271] The emotion engine analyzes the user's facial expressions and quantifies the corresponding emotion from a range of emotions (e.g., joy, sadness, anger, etc.).

[0272] Step 12:

[0273] The server determines image processing parameters based on the user's industry, job title, age and recognized emotion.

[0274] Step 13:

[0275] The server inputs the determined parameters and photo data into the AI ​​model and instructs it on image analysis and processing.

[0276] Step 14:

[0277] The AI ​​model analyzes the photo and performs optimal processing based on the parameters (e.g., adjusting brightness, changing the background, adjusting contrast, etc.).

[0278] Step 15:

[0279] The server retrieves the processed photo data and stores it in a database.

[0280] Step 16:

[0281] The user logs back into the system and accesses the confirmation page for the processed image.

[0282] Step 17:

[0283] The device will then display the edited photo to the user and offer the option to download it.

[0284] Step 18:

[0285] Users can view the edited photos and download them if necessary.

[0286] Set the photos downloaded by the user as icons for online meeting tools and emails.

[0287] Example 2

[0288] 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."

[0289] In online communication and business, there is a demand for effective use of users' photos to improve the image of individuals and companies. However, it is difficult for users to create the optimal image on their own, requiring specialized knowledge and skills. Furthermore, conventional image processing tools have the problem of making it difficult to create the optimal image that reflects the user's emotion or occupation.

[0290] 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 a means for a user to upload his / her own image, a means for a user to input his / her occupation, role, and age, and a means for inputting the user's image into an emotion engine and recognizing emotions. This makes it possible to automatically generate and provide an optimal image according to the user's emotion and occupation.

[0291] "User" refers to an individual who logs into the system, uploads their photo, and enters the required information.

[0292] "Images" refers to visual data such as photographs or drawings uploaded by users.

[0293] "Occupation" refers to the industry or occupation to which the user belongs.

[0294] "Role" refers to the position or title a user holds within a profession.

[0295] "Age" refers to the number of years calculated from the user's date of birth.

[0296] "Server" refers to a computer system that receives photos and information from users, stores them in a database, and performs various processing.

[0297] An "emotion engine" refers to software or algorithms that analyze a user's image and quantify their emotions.

[0298] "Image processing parameters" refer to adjustment values ​​such as image brightness, background color, and contrast that are determined based on the user's emotions and occupation.

[0299] A "generative AI model" refers to an artificial intelligence system that analyzes and processes images based on specific parameters.

[0300] "Database" refers to a collection of digital data for storing user photos and information.

[0301] "Online communication tools" refers to software and services that allow users to communicate with each other via the Internet.

[0302] The present invention is a system in which users not only upload their own images and input their occupation, role, and age, but also recognize the user's emotions using an emotion engine, and a generative AI model generates an optimal image. The detailed configuration and processing flow of the system based on the present invention are described below.

[0303] System configuration

[0304] 1. Photo upload function

[0305] User: Log in to the system and upload their own images. Specifically, the user enters their username and password on the login screen, and after logging in, they are directed to the photo upload screen. The photos are uploaded through the file selection interface.

[0306] Terminal: Provides an interface for uploading photos and sends selected photos to the server. This interface uses HTML and JavaScript.

[0307] Server: Receives uploaded photos and stores them in a database. Photo data is stored in a MySQL database using a Python script.

[0308] 2. Occupation, role, and age input function

[0309] Terminal: Displays an input form for occupation, role, age, etc. This form is also built using HTML and JavaScript.

[0310] User: Enter the required information in the provided input field and submit. The entered information is sent from the device to the server.

[0311] Server: Stores the entered information in a database, also done using a Python script.

[0312] 3. Emotion recognition function using an emotion engine

[0313] Server: The uploaded photo is input into the emotion engine to recognize the user's emotions. In this case, we use Microsoft's Azure Face API as the emotion engine.

[0314] Emotion engine: Analyzes the user's facial expressions and quantifies their emotions. For example, it recognizes emotions such as joy, sadness, and anger and returns them as numerical data.

[0315] 4. Image processing parameter determination function

[0316] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's occupation, role, age, and recognized emotion. This process is performed using Python scripts and machine learning libraries.

[0317] 5. AI-based image analysis and processing functions

[0318] Server: The determined parameters and photos are input into the generative AI model, and instructions are given for image analysis and processing. The generative AI model uses libraries such as TensorFlow and PyTorch.

[0319] Generative AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[0320] Server: Stores the processed photos in a database, also done using a Python script.

[0321] 6. Image provision function

[0322] User: Log in to the system again and access the confirmation page for the processed image. After logging in again, you will be able to view and download the processed image.

[0323] On the device: The processed image is displayed to the user and a download function is provided. Image display and download links are provided using HTML and JavaScript.

[0324] Specific examples

[0325] Example of a sales representative (30 years old)

[0326] 1. User: A sales person logs in to the system, uploads three photos, and enters their occupation as "Sales," role as "Responsible Person," and age as "30."

[0327] 2. Server: Stores the photos and input information in a database.

[0328] 3. Server: The uploaded photo is sent to the emotion engine, where the emotion of joy is recognized.

[0329] 4. Server: Determines the parameters of "bright background", "high brightness" and "high contrast" based on occupation, role, age and perceived happiness.

[0330] 5. Generative AI model: Analyzes the photo and performs processing based on determined parameters, such as increasing the brightness of the photo, setting a bright background, and enhancing the contrast of the face.

[0331] 6. Server: Stores the processed photos in a database and provides them to users.

[0332] 7. User: Log back in to the system to check the edited photo, download it if necessary, and set the downloaded photo as an icon for online communication tools or emails.

[0333] Prompt Sentence Examples

[0334] Here is an example of a prompt to input to a generative AI model:

[0335] "A 30-year-old salesperson has uploaded three photos with the emotion Happy. For these photos, we want to increase the brightness, add a lighter background, and increase the contrast of the face."

[0336] In this way, by combining an emotion engine and a generative AI model, the present invention automatically generates and provides optimal images according to the user's emotions and occupation, thereby contributing to improving the online image of individuals and companies.

[0337] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0338] Step 1:

[0339] A user logs in to the system. They enter their username and password on the login screen and click "Login". The server authenticates the entered username and password, and if authentication is successful, displays the homepage. Specifically, a Python framework (e.g., Django) is used for user authentication. The input is the username and password, and the output is the login status (success or failure).

[0340] Step 2:

[0341] After logging in, the user uploads their own image. The device displays an interface for uploading photos. The user selects a photo and clicks the upload button. The device sends the selected photo to the server via an AJAX request. The server stores the received photo in a MySQL database. The input is the selected image file, and the output is a message that the image was successfully saved to the database.

[0342] Step 3:

[0343] The user enters their occupation, role, and age. The terminal displays an input form for occupation, role, age, etc. The user enters this information and clicks the submit button. The terminal sends the input information to the server via an AJAX request. The server receives the input information and saves it in a MySQL database. The input is text data for occupation, role, and age, and the output is a message that the information was successfully saved to the database.

[0344] Step 4:

[0345] The server sends the uploaded photo to the emotion engine to recognize the user's emotion. The photo data is sent to the emotion engine (for example, Azure Face API) to obtain emotion data. Specifically, the server calls the API, and the emotion engine analyzes the photo and returns emotion data. The input is photo data, and the output is emotion data (numeric values ​​such as joy, sadness, anger, etc.).

[0346] Step 5:

[0347] The server determines image processing parameters based on the user's occupation, role, age, and recognized emotion. A Python script is used to analyze the input information and emotion data, and set image processing parameters such as "brightness," "background color," and "contrast." The input is occupation, role, age, and emotion data, and the output is image processing parameters.

[0348] Step 6:

[0349] The server inputs the determined parameters and the photo into the generative AI model and instructs it to analyze and process the image. The generative AI model (such as TensorFlow or PyTorch) analyzes the photo data and processes the image based on the parameters. The input is the photo data and image processing parameters, and the output is the processed photo data.

[0350] Step 7:

[0351] The server saves the processed photo to the database. Using a Python script, the processed photo data is stored in the MySQL database. The input is the processed photo data, and the output is a message that the data was successfully saved to the database.

[0352] Step 8:

[0353] The user re-logins into the system and accesses the confirmation page for the processed image. The user logs in again and is directed to a dedicated confirmation page. The terminal displays the processed image to the user and provides a downloadable link. The input is the user's re-login information, and the output is the processed image and download link displayed on the confirmation page.

[0354] (Application example 2)

[0355] 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."

[0356] Conventional advertising visual generation systems have difficulty generating optimal images based on the target user's emotions and profile. Furthermore, new technology is needed to enable advertising agencies to quickly create effective advertising visuals that meet their clients' needs. Furthermore, if the generated visuals do not match the target user's emotions, the effectiveness of the advertisement decreases.

[0357] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to upload their own photo, means for the user to input their industry, job title, and age, means for the server to save these photos and input information in a database, means for the server to recognize the user's emotion from the uploaded photo using an emotion engine, means for the server to determine image processing parameters based on the user's information and the recognized emotion, means for the AI ​​model to edit the photo based on these parameters, means for the server to save the edited photo in a database and provide it to the user, and means for the user to check and download the edited photo. This enables the automatic generation of optimal advertising visuals based on the emotions and profile of target users.

[0358] "User" means any person or entity using the system who uploads photos and enters required information.

[0359] "Client" refers to an entity, such as an advertising agency or company, that uses the system to generate advertising visuals for target users.

[0360] "Target users" refers to the specific people or customer groups for whom advertising visuals are created.

[0361] "Photos" are image files of users or target users, and are digital data uploaded to the system.

[0362] "Industry" refers to the occupation or industry to which the user or target user belongs.

[0363] "Job title" is information that refers to the job position or role of the user or target user.

[0364] "Age" refers to the numerical stage of development calculated from the user's or target user's year of birth.

[0365] A "server" is a computer system responsible for storing, processing, and managing data.

[0366] A "database" is a system for managing and storing data such as photographs, input information, and generated advertising visuals.

[0367] An "emotion engine" is a machine learning model or algorithm that analyzes uploaded photos and quantifies the emotions of users and target users.

[0368] "Image processing parameters" refers to settings and adjustments related to image processing, such as brightness, background color, and contrast of a photograph.

[0369] An "AI model" is a machine learning model used to process and generate images based on input data.

[0370] "Processed photos" are photographic data that have been processed according to image processing parameters specified by the AI ​​model.

[0371] "Advertising visuals" are visual advertising materials created to help clients effectively approach their target users.

[0372] This invention is a system that automatically generates optimal advertising visuals based on user emotions and profiles, enabling clients to quickly and easily create effective advertisements for target users. This system is composed of the following steps, hardware, and software.

[0373] System configuration

[0374] 1. User and Client Account Management

[0375] Terminal: Provides an interface for account creation and login.

[0376] Server: Manage account information using Firebase Authentication.

[0377] 2. Targeted user photo upload feature

[0378] Terminal: Provides a UI for clients to upload photos of target users.

[0379] Server: Save the uploaded photos to Firebase Storage.

[0380] 3. Profile data entry function

[0381] Terminal: Provides a form where clients can enter the industry, job title, and age of their target users.

[0382] Server: Save the entered data to Firebase Firestore.

[0383] 4. Emotion recognition function

[0384] Server: Sends the uploaded photo to Google Cloud Vision API and obtains the sentiment analysis results.

[0385] Emotion engine: Analyzes the user's facial expressions and quantifies emotions (e.g., joy, sadness, anger, etc.).

[0386] 5. Image generation function

[0387] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the emotion engine results and profile data.

[0388] Server and AI model: Using TensorFlow, the target user's photo is processed based on the determined parameters.

[0389] AI Model: Uses a generative AI model to create optimal ad visuals based on the prompt you provide.

[0390] 6. Image confirmation and download function

[0391] Terminal: Provides a UI where clients can view and download the generated ad visuals.

[0392] Server: Stores the generated advertising visuals in a database and provides them to clients.

[0393] Specific examples

[0394] For example, to generate advertising visuals for a 30-year-old salesperson, the client uploads a photo and profile of the salesperson (industry: sales, job title: responsible, age: 30). The system provides the following prompt sentence to the generative AI model:

[0395] Prompt Sentence Examples

[0396] Please generate the best advertising visual for a 30-year-old salesperson. The emotion of the photo is recognized as "joy." Please use a light background, high brightness, and strong contrast settings.

[0397] Hardware and software used

[0398] Firebase Authentication: A platform for managing authentication.

[0399] Firebase Firestore: A cloud database for storing and managing data.

[0400] Firebase Storage: Cloud storage for saving photos.

[0401] Google Cloud Vision API: A cloud-based image analysis service for emotion recognition.

[0402] TensorFlow: A platform for image generation and processing using machine learning models.

[0403] React Native: A framework used to build user interfaces.

[0404] In this way, the system of the present invention combines an emotion engine and a generative AI model to automatically generate optimal advertising visuals based on the emotions and profiles of target users, enabling clients to quickly create effective advertising visuals and maximize marketing effectiveness.

[0405] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0406] Step 1:

[0407] Terminal: The client logs in to the system. The client's authentication information (username, password) is entered and authentication is performed using Firebase Authentication. If authentication is successful, the client's account information is obtained and the system proceeds to the next step.

[0408] Step 2:

[0409] Device: After logging in, the client uploads a photo of the target user. The client selects the photo file using the device's UI and clicks the upload button. Once the photo file is selected, the device sends the photo data to Firebase Storage.

[0410] Step 3:

[0411] Server: Retrieve the photo data stored in Firebase Storage and save it to the database. The server saves the photo file URL and metadata such as the upload date and time to Firebase Firestore. Once saving is complete, proceed to the next step.

[0412] Step 4:

[0413] Terminal: Provides a form for entering profile information (industry, job title, age) of the target user. The client enters information in each field and clicks the submit button. The entered information is sent from the terminal to the server.

[0414] Step 5:

[0415] Server: Receives the profile information sent from the client and saves it to the database. The profile information is stored in Firebase Firestore and associated with the photo data. Once saved, proceed to the next step.

[0416] Step 6:

[0417] Server: Sends photo data to the Google Cloud Vision API and performs emotion recognition. Receives emotion data (e.g., joy, sadness, anger, etc.) returned from the API. Analyzes and quantifies the received emotion data. Stores the analysis results in a database and proceeds to the next step.

[0418] Step 7:

[0419] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on profile information and emotion data. Sets these parameters and prepares them as input data for the AI ​​model.

[0420] Step 8:

[0421] Server and AI model: Using TensorFlow, the photo is processed based on the set image processing parameters. A specific prompt is input to the generation AI model. For example, the following prompt is used to generate an image:

[0422] Please generate the best advertising visual for a 30-year-old salesperson. The emotion of the photo is recognized as "joy." Please use a light background, high brightness, and strong contrast settings.

[0423] The AI ​​model processes the photo according to the prompt, generates the optimal advertising visual, and returns the generated image to the server.

[0424] Step 9:

[0425] Server: Saves the generated ad visuals to the database. Once saved, sends a notification to the client to let them know the image has been generated.

[0426] Step 10:

[0427] Terminal: The client accesses the UI to view the generated ad visuals. The generated images are displayed on the terminal, and the client can view them and download them if necessary.

[0428] By following these steps, clients can automatically generate optimal advertising visuals based on the emotions and profiles of their target users, thereby enhancing their marketing effectiveness.

[0429] 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.

[0430] 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.

[0431] 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.

[0432] [Second embodiment]

[0433] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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).

[0439] 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.

[0440] 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.

[0441] 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.

[0442] 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.

[0443] 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.

[0444] 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."

[0445] The system based on this patent claim allows users to upload their own photos and input their industry, job title, and age, and then AI generates and provides the most suitable image.

[0446] System configuration

[0447] 1. Photo upload function

[0448] User: Logs into the system and uploads a photo of himself.

[0449] Terminal: Provides an interface for uploading photos and sends selected photos to the server.

[0450] Server: Receives uploaded photos and stores them in a database.

[0451] 2. Input function for industry, job title, and age

[0452] Terminal: Provides users with fields to input information such as industry, job title, and age.

[0453] User: Enter the required information in the provided fields and submit.

[0454] Server: Receives the entered information and stores it in a database.

[0455] 3. Image processing parameter determination function

[0456] Server: Retrieves the user's photo and input information from the database.

[0457] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, and age information.

[0458] 4. AI-based image analysis and processing functions

[0459] Server: Inputs the determined parameters and photos into the AI ​​model and instructs it on image analysis and processing.

[0460] AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[0461] Server: Obtains the processed photos and stores them in a database.

[0462] 5. Image provision function

[0463] User: Log in to the system and check the processed image.

[0464] On-device: The processed image is displayed to the user and a download function is provided.

[0465] Program processing flow

[0466] The program of this system proceeds as follows:

[0467] 1. Upload a photo

[0468] A user logs into the system and uploads a photo.

[0469] The terminal transmits the selected photos to the server, and the server stores the received photos in a database.

[0470] 2. Enter your industry and job title information

[0471] The device displays an input form for industry, job title, and age, and the user enters the information.

[0472] The terminal sends the entered information to the server, which stores it in a database.

[0473] 3. Determining image processing parameters

[0474] The server retrieves the user's photo and input information from the database.

[0475] The server determines image processing parameters based on the information.

[0476] 4. Image analysis and processing

[0477] The server inputs the photo and parameters into the AI ​​model and instructs it to analyze and process it.

[0478] The AI ​​model analyzes the photo and performs optimal processing based on the parameters.

[0479] The server retrieves the processed photos and stores them in a database.

[0480] 5. Providing edited images

[0481] Users can log in to view the edited images and download them if necessary.

[0482] The device displays the processed image and provides a download function.

[0483] Specific examples

[0484] Example of a sales representative (30 years old)

[0485] The user (sales representative) logs into the system, uploads three photos, and enters the industry as "sales," the job title as "responsible person," and the age as "30 years old."

[0486] The server stores the photos and information in a database and determines the parameters of "light background," "high brightness," and "strong contrast" based on industry, job title, and age.

[0487] The AI ​​model analyzes the photo and applies specified effects based on the parameters, such as increasing the brightness of the photo, setting a bright background, and increasing the contrast of the face.

[0488] The server stores the edited photos in a database, and users can log in to view and download the photos.

[0489] In this way, the present invention uses AI technology to automatically generate optimal images based on user information, providing photos suitable for use in online meetings and emails.

[0490] The processing flow will be explained below.

[0491] Step 1:

[0492] A user logs into the system and accesses the photo upload page.

[0493] Step 2:

[0494] The device will display a photo upload interface, where users can click the file selection button and select up to three of their own photos.

[0495] Step 3:

[0496] The user selects a photo and presses the upload button.

[0497] Step 4:

[0498] The terminal transmits the selected photo file to the server.

[0499] Step 5:

[0500] The server analyzes the received photo data and verifies whether it has been uploaded correctly.

[0501] After the server verifies it, it stores the photo data in a database.

[0502] Step 6:

[0503] The device displays a form for entering occupation, position, and age.

[0504] Step 7:

[0505] The user enters their occupation (e.g., sales), position (e.g., manager), and age (e.g., 30 years old), and presses the send button.

[0506] Step 8:

[0507] The terminal transmits the input information to the server.

[0508] The server stores the received information in a database.

[0509] Step 9:

[0510] The server retrieves the user's photo and input information from the database.

[0511] Step 10:

[0512] The server determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, and age information.

[0513] Step 11:

[0514] The server inputs the determined parameters and photo data into the AI ​​model and instructs it on image analysis and processing.

[0515] Step 12:

[0516] The AI ​​model analyzes the photo and processes it based on determined parameters.

[0517] For example, adjust brightness, change background, enhance contrast, etc.

[0518] Step 13:

[0519] The server retrieves the processed photo data and stores it in a database.

[0520] Step 14:

[0521] The user logs back into the system and accesses the confirmation page for the processed image.

[0522] Step 15:

[0523] The device will then display the edited photo to the user and offer the option to download it.

[0524] Step 16:

[0525] Users can view the edited photos and download them if necessary.

[0526] Set the photos downloaded by the user as icons for online meeting tools and emails.

[0527] Example 1

[0528] 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."

[0529] In the past, it was often time-consuming and required specialized knowledge for users to obtain the perfect profile picture for use in online meetings or emails. In particular, when editing images themselves, it was often difficult to adjust the appropriate brightness, background color, contrast, etc., resulting in a lack of a professional impression. An effective and easy-to-use system to solve these problems is needed.

[0530] 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.

[0531] In this invention, the server includes a means for users to upload their own electronic images, a means for users to input their occupation, job title, and age, and a means for the generative AI model to process the electronic images based on these parameters, thereby enabling users to easily generate their own profile pictures in an optimal form.

[0532] A "user" is a person who uses the system and uploads an electronic image of himself or herself and enters his or her occupation, job title, and age.

[0533] "Server" means a computing device that processes information received from users, stores it in a data storage device, and utilizes generative AI models to manipulate electronic images.

[0534] "Electronic images" refer to photographic data uploaded by users to the system and used as profile images for online meeting tools and email.

[0535] "Occupation" refers to information that indicates the industry or occupation in which the user is engaged.

[0536] "Position" refers to information that indicates a user's job position or title.

[0537] "Age" refers to information indicating the user's age.

[0538] A "generative AI model" is an artificial intelligence model that performs optimal image processing based on uploaded electronic images and user input.

[0539] "Image processing parameters" are the settings or conditions used by a generative AI model to process an electronic image, including brightness, background color, contrast, etc.

[0540] "Data storage device" means storage for electronic images and input information received from users, and electronic images processed by generative AI models.

[0541] This invention is a system in which a user uploads their own digital image and inputs their occupation, job title, and age, and a generative AI model generates and provides the most suitable image. This system is mainly composed of three parties: a server, a terminal, and the user.

[0542] First, a user logs in to the system and uploads their own electronic image. The user can easily perform operations through the system interface. The terminal provides an interface for uploading photos and sends the electronic image selected by the user to the server. The server validates the received electronic image and stores it in a data storage device.

[0543] Next, the terminal provides the user with an input form for information such as occupation, position, age, etc. The user enters this information and submits it. The terminal then transmits the input information to the server, which stores it in a data storage device.

[0544] The server retrieves the user's digital image and input information from the data storage device and determines image processing parameters based on the user's occupation, position, and age. For example, if the occupation is "sales," the position is "person in charge," and the age is "30," the parameters set are "light background," "high brightness," and "strong contrast."

[0545] The server then inputs the digital image along with the determined parameters into a generative AI model, which then performs image analysis and processing using libraries such as TensorFlow and PyTorch. This includes adjusting brightness, changing background colors, and enhancing contrast.

[0546] The server receives the electronic images processed by the generative AI model and stores them again in the data storage device. The user can log in to the system again and check the processed electronic images. The terminal displays the processed images to the user and provides a download function. The user can download the images as needed and use them in online meeting tools or email.

[0547] Specific examples

[0548] For example, a sales user (30 years old) logs in to the system and uploads three photos. The user enters their occupation as "sales," their position as "responsible," and their age as "30." The server stores this information in a data storage device and determines the parameters for "light background," "high brightness," and "strong contrast" based on the industry, position, and age information. The generative AI model processes the photos based on these settings, generating an image with, for example, increased brightness, a bright background, and enhanced facial contrast. The server then stores the processed electronic images in a data storage device, and the user can log in again to review the images and download them if necessary.

[0549] Prompt Sentence Examples

[0550] "Improve your sales profile photo. I have three photos. I'm 30 years old. Safely adjust the brightness, background, and contrast accordingly."

[0551] The system allows users to easily get the best profile picture possible, creating a professional impression in online meetings and emails.

[0552] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0553] Step 1: The user logs in to the system and accesses the photo upload screen. The terminal displays a file input field and provides an interface for the user to select a photo. When the user selects a photo and presses the "Upload" button, the terminal sends the photo data to the server. The input is the user's photo file, and the output is the transmission result to the server. The server validates the received photo and saves it in the data storage device.

[0554] Step 2: The user accesses a screen to input occupation, position, and age information. The terminal displays a form for inputting this information, allowing the user to enter data. The terminal sends the input information to the server. The input is occupation, position, and age information, and the output is the transmission result to the server. The server saves the received information in a data storage device.

[0555] Step 3: The server retrieves the user's photo and input information from the data storage device. Using SQL queries or similar, the server retrieves the stored photo and information on occupation, position, and age. The input is the stored data record, and the output is the retrieved data. The server determines the image processing parameters based on this information. For example, for a sales representative (age 30), the parameters set are "light background," "high brightness," and "strong contrast."

[0556] Step 4: The server inputs the determined image processing parameters and the user's photo into the generative AI model. The generative AI model analyzes and processes the photo based on these parameters. The input is the image processing parameters and photo data, and the output is the processed photo data. Specifically, the generative AI model adjusts brightness, changes the background color, and enhances contrast.

[0557] Step 5: The server receives the processed photo returned by the generative AI model and stores it in the data storage device. The server re-encodes the processed photo data, stores it in cloud storage, and adds its URL to the data record. The input is the processed photo data, and the output is the result of the storage completion.

[0558] Step 6: The user logs in to the system again to view the edited photo. The device requests the edited photo data from the server and displays it. The user can download the photo if needed. The input is the user request, and the output is the edited photo data. The device generates a download link, allowing the user to download the photo.

[0559] (Application example 1)

[0560] 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."

[0561] Conventional photo editing systems require specialized knowledge and highly accurate tools for users to edit their own photos optimally, and the process requires a lot of time and effort. Furthermore, they lack the functionality to automatically generate promotional images for use in physical stores, and creating them manually is time-consuming. Therefore, there was a demand for a system that could easily and quickly generate and provide optimal promotional images.

[0562] 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.

[0563] In this invention, the server includes: a means for users to upload their own photos; a means for users to input their industry, job title, and age; a means for the server to save these photos and input information in a database; a means for the server to determine image processing parameters based on the user's information; a means for an AI model to edit the photos based on these parameters; a means for the server to save the edited photos in a database and provide them to users; a means for users to check and download the edited photos; and a means for the AI ​​to generate optimal promotional images by users inputting their own photos and store information (industry, job title, age) and provide the promotional images to be displayed on smart displays in physical stores. This allows users to quickly and efficiently generate optimal promotional images without the need for specialized knowledge or tools, and to immediately use them in physical stores, etc.

[0564] "Server" means a computer system that receives, stores, processes, and analyzes data entered by users.

[0565] "User" refers to a person or organization that uses this system to upload their own photo, enter their industry, job title, and age, and obtain the most suitable edited photo.

[0566] "Photo Uploader" means the functionality or interface that allows a User to provide their photo to the System.

[0567] "Means for inputting industry, job title, and age" refers to the functions and interfaces that allow a user to provide information about their industry, job title, and age to the system.

[0568] "Image processing parameters" refer to adjustment elements such as brightness, background, and contrast required for processing a photograph.

[0569] An "AI model" is an artificial intelligence algorithm and system that analyzes and processes input data.

[0570] "Promotional images" are images used for promotional and advertising purposes, such as on smart displays in physical stores.

[0571] A "smart display" is an electronic display device such as digital signage that is used to provide information and display advertisements in stores, events, etc.

[0572] An "edited photo" is a photo after brightness, background, and contrast have been adjusted based on image processing parameters specified by the AI ​​model.

[0573] A "database" is a storage device or medium for systematically organizing and storing information within a system.

[0574] MODE FOR CARRYING OUT THE INVENTION

[0575] This system for implementing the invention allows users to upload their own photos and input their industry, job title, and age, and then AI generates and provides the most suitable image.The system can also automatically generate promotional images for smart displays in physical stores based on user input.

[0576] System configuration

[0577] 1. Photo upload function

[0578] The server provides a means for users to upload their own photos via their devices, which are then sent to the server and stored in a database.

[0579] 2. Input function for industry, job title, and age

[0580] Users have the means to input their industry, job title, and age through the terminal, and the input information is sent to the server and stored in a database.

[0581] 3. Image processing parameter determination function

[0582] The server determines image processing parameters (brightness, background, contrast, etc.) based on the user's industry, job title, and age information, which is obtained from a database.

[0583] 4. AI-based image analysis and processing functions

[0584] The server inputs the determined parameters and the photo into the AI ​​model and instructs it to analyze and process the image. The AI ​​model analyzes the image and performs optimal processing based on the parameters.

[0585] 5. Image provision function

[0586] The processed photos are stored on a server and can be accessed by users via their devices to view and download them.

[0587] Promotional images can also be provided for display on smart displays in physical stores.

[0588] Hardware and software used

[0589] 1. Server: Stores, processes, and analyzes data. For processing functions, we use cloud computing services such as Amazon Web Services (AWS).

[0590] 2. Device: Use an internet-enabled device such as a smartphone or tablet to upload photos and enter information.

[0591] 3. AI model: For image analysis and processing, we use machine learning frameworks such as TensorFlow and PyTorch, which allow us to properly analyze the input image and generate the optimal promotional image.

[0592] Examples and prompts

[0593] For example, suppose a 25-year-old salesperson working at an apparel store wants to generate promotional images for the store's smart displays. In this case, the user would follow the steps below:

[0594] 1. Users take a photo of themselves using their smartphone and upload it to the system.

[0595] 2. The user enters the industry as "apparel," the job title as "store clerk," and the age as "25."

[0596] 3. Based on the input information, the server determines that the brightness should be set to 1.2 times, the background to a fashion-themed image, and the contrast to 1.5 times.

[0597] 4. The AI ​​model runs these settings and generates the edited photo.

[0598] 5. The user can review the edited photo and download it to display on their smart display.

[0599] Example prompt sentence:

[0600] "Based on the photo uploaded by the user, the industry "Apparel", job title "Store Clerk", and age "25", set a bright background image and adjust the photo brightness by 1.2 times and the contrast by 1.5 times."

[0601] This makes it possible to quickly generate and use effective promotional images even in physical stores.

[0602] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0603] Step 1:

[0604] The user takes and uploads their own photo using the device. The device provides a photo upload interface and sends the photo selected by the user to the server. The input is the user's photo, and the output is a photo file stored on the server.

[0605] Step 2:

[0606] The user inputs their industry, job title, and age through the terminal. The terminal displays an input form for industry, job title, and age, and when the user enters the information, it sends the data to the server. The input is the user's industry, job title, and age information, and the output is that information saved on the server.

[0607] Step 3:

[0608] The server retrieves the user's photo and input information from the database. The server loads the necessary data into memory based on the saved photo file and input information. The input is the photo and input information from the database, and the output is the related data stored in memory.

[0609] Step 4:

[0610] The server determines image processing parameters (brightness, background, contrast, etc.) based on the user's industry, job title, and age information. The server calculates the parameters using pre-set rules and models. The input is the user's information, and the output is the determined image processing parameters.

[0611] Step 5:

[0612] The server inputs the determined parameters and photo into the AI ​​model and instructs it to analyze and process the image. The AI ​​model analyzes the image and performs optimal processing based on the parameters. The input is the processing parameters and photo file, and the output is the processed image data.

[0613] Step 6:

[0614] The server stores the processed photos in a database and provides them to the user. The processed images are stored on the server and can be accessed by the user through the system. The input is the processed image data, and the output is the processed image stored in the database.

[0615] Step 7:

[0616] The user checks the edited photo on their device and downloads it if necessary. The device displays the edited photo to the user and provides a download option. The input is the edited image retrieved from the database, and the output is an image file saved on the user's device.

[0617] These specific processing steps enable users to quickly and efficiently generate optimal promotional images without the need for specialized knowledge or tools, and to immediately use them in physical stores, etc.

[0618] 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.

[0619] The present invention is a system in which users not only upload their own photos and input their industry, job title, and age, but also recognize the user's emotions using an emotion engine, and AI generates the optimal image. The detailed configuration and processing flow of the system based on the present invention are described below.

[0620] System configuration

[0621] 1. Photo upload function

[0622] User: Logs into the system and uploads a photo of himself.

[0623] Terminal: Provides an interface for uploading photos and sends selected photos to the server.

[0624] Server: Receives uploaded photos and stores them in a database.

[0625] 2. Input function for industry, job title, and age

[0626] Device: Displays an input form for industry, job title, age, etc.

[0627] User: Enter the required information in the provided fields and submit.

[0628] Server: Receives the entered information and stores it in a database.

[0629] 3. Emotion recognition function using an emotion engine

[0630] Server: Inputs the uploaded photo into the emotion engine to recognize the user's emotion.

[0631] Emotion engine: Analyzes the user's facial expressions and quantifies their emotions, such as happiness, sadness, and anger.

[0632] 4. Image processing parameter determination function

[0633] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, age, and recognized emotion.

[0634] 5. AI-based image analysis and processing functions

[0635] Server: Inputs the determined parameters and photos into the AI ​​model and instructs it on image analysis and processing.

[0636] AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[0637] Server: Obtains the processed photos and stores them in a database.

[0638] 6. Image provision function

[0639] User: Log back into the system and access the confirmation page for the processed image.

[0640] On-device: The processed image is displayed to the user and a download function is provided.

[0641] Program processing flow

[0642] The program of this system proceeds as follows:

[0643] Specific examples

[0644] Example of a sales representative (30 years old)

[0645] 1. User: A sales person logs in to the system and uploads three photos. The user enters the industry as "Sales," the job title as "Responsible Person," and the age as "30."

[0646] 2. Server: Stores the photos and input information in a database.

[0647] 3. Server: The uploaded photo is sent to the emotion engine, where the emotion of joy is recognized.

[0648] 4. Server: Determines the parameters of "bright background," "high brightness," and "strong contrast" based on industry, job title, age, and perceived happiness.

[0649] 5. AI model: Analyzes the photo and performs processing based on the determined parameters, such as increasing the brightness of the photo, setting a bright background, and enhancing the contrast of the face.

[0650] 6. Server: Stores the processed photos in a database and provides them to users.

[0651] 7. User: Log back in to the system to check the edited photo and download it if necessary. Set the downloaded photo as an icon for online meeting tools or emails.

[0652] In this way, by combining emotion engines, the present invention realizes a system that automatically generates optimal images according to the user's emotions, and further contributes to improving the image of individuals and companies online.

[0653] The processing flow will be explained below.

[0654] Step 1:

[0655] A user logs into the system and accesses the photo upload page.

[0656] Step 2:

[0657] The device will display a photo upload interface, where users can click the file selection button and select up to three of their own photos.

[0658] Step 3:

[0659] The user selects a photo and presses the upload button.

[0660] Step 4:

[0661] The terminal transmits the selected photo file to the server.

[0662] Step 5:

[0663] The server analyzes the received photo data and verifies whether it has been uploaded correctly.

[0664] After the server verifies it, it stores the photo data in a database.

[0665] Step 6:

[0666] The device displays a form for entering industry, job title, and age.

[0667] Step 7:

[0668] The user enters the industry (e.g., sales), job title (e.g., person in charge), and age (e.g., 30 years old), and presses the send button.

[0669] Step 8:

[0670] The terminal transmits the input information to the server.

[0671] The server stores the received information in a database.

[0672] Step 9:

[0673] The server retrieves the user's photo and input information from the database.

[0674] Step 10:

[0675] The server inputs the uploaded photos into an emotion engine to recognize the user's emotions.

[0676] Step 11:

[0677] The emotion engine analyzes the user's facial expressions and quantifies the corresponding emotion from a range of emotions (e.g., joy, sadness, anger, etc.).

[0678] Step 12:

[0679] The server determines image processing parameters based on the user's industry, job title, age and recognized emotion.

[0680] Step 13:

[0681] The server inputs the determined parameters and photo data into the AI ​​model and instructs it on image analysis and processing.

[0682] Step 14:

[0683] The AI ​​model analyzes the photo and performs optimal processing based on the parameters (e.g., adjusting brightness, changing the background, adjusting contrast, etc.).

[0684] Step 15:

[0685] The server retrieves the processed photo data and stores it in a database.

[0686] Step 16:

[0687] The user logs back into the system and accesses the confirmation page for the processed image.

[0688] Step 17:

[0689] The device will then display the edited photo to the user and offer the option to download it.

[0690] Step 18:

[0691] Users can view the edited photos and download them if necessary.

[0692] Set the photos downloaded by the user as icons for online meeting tools and emails.

[0693] Example 2

[0694] 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."

[0695] In online communication and business, there is a demand for effective use of users' photos to improve the image of individuals and companies. However, it is difficult for users to create the optimal image on their own, requiring specialized knowledge and skills. Furthermore, conventional image processing tools have the problem of making it difficult to create the optimal image that reflects the user's emotion or occupation.

[0696] 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 a means for a user to upload his / her own image, a means for a user to input his / her occupation, role, and age, and a means for inputting the user's image into an emotion engine and recognizing emotions. This makes it possible to automatically generate and provide an optimal image according to the user's emotion and occupation.

[0697] "User" refers to an individual who logs into the system, uploads their photo, and enters the required information.

[0698] "Images" refers to visual data such as photographs or drawings uploaded by users.

[0699] "Occupation" refers to the industry or occupation to which the user belongs.

[0700] "Role" refers to the position or title a user holds within a profession.

[0701] "Age" refers to the number of years calculated from the user's date of birth.

[0702] "Server" refers to a computer system that receives photos and information from users, stores them in a database, and performs various processing.

[0703] An "emotion engine" refers to software or algorithms that analyze a user's image and quantify their emotions.

[0704] "Image processing parameters" refer to adjustment values ​​such as image brightness, background color, and contrast that are determined based on the user's emotions and occupation.

[0705] A "generative AI model" refers to an artificial intelligence system that analyzes and processes images based on specific parameters.

[0706] "Database" refers to a collection of digital data for storing user photos and information.

[0707] "Online communication tools" refers to software and services that allow users to communicate with each other via the Internet.

[0708] The present invention is a system in which users not only upload their own images and input their occupation, role, and age, but also recognize the user's emotions using an emotion engine, and a generative AI model generates an optimal image. The detailed configuration and processing flow of the system based on the present invention are described below.

[0709] System configuration

[0710] 1. Photo upload function

[0711] User: Log in to the system and upload their own images. Specifically, the user enters their username and password on the login screen, and after logging in, they are directed to the photo upload screen. The photos are uploaded through the file selection interface.

[0712] Terminal: Provides an interface for uploading photos and sends selected photos to the server. This interface uses HTML and JavaScript.

[0713] Server: Receives uploaded photos and stores them in a database. Photo data is stored in a MySQL database using a Python script.

[0714] 2. Occupation, role, and age input function

[0715] Terminal: Displays an input form for occupation, role, age, etc. This form is also built using HTML and JavaScript.

[0716] User: Enter the required information in the provided input field and submit. The entered information is sent from the device to the server.

[0717] Server: Stores the entered information in a database, also done using a Python script.

[0718] 3. Emotion recognition function using an emotion engine

[0719] Server: The uploaded photo is input into the emotion engine to recognize the user's emotions. In this case, we use Microsoft's Azure Face API as the emotion engine.

[0720] Emotion engine: Analyzes the user's facial expressions and quantifies their emotions. For example, it recognizes emotions such as joy, sadness, and anger and returns them as numerical data.

[0721] 4. Image processing parameter determination function

[0722] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's occupation, role, age, and recognized emotion. This process is performed using Python scripts and machine learning libraries.

[0723] 5. AI-based image analysis and processing functions

[0724] Server: The determined parameters and photos are input into the generative AI model, and instructions are given for image analysis and processing. The generative AI model uses libraries such as TensorFlow and PyTorch.

[0725] Generative AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[0726] Server: Stores the processed photos in a database, also done using a Python script.

[0727] 6. Image provision function

[0728] User: Log in to the system again and access the confirmation page for the processed image. After logging in again, you will be able to view and download the processed image.

[0729] On the device: The processed image is displayed to the user and a download function is provided. Image display and download links are provided using HTML and JavaScript.

[0730] Specific examples

[0731] Example of a sales representative (30 years old)

[0732] 1. User: A sales person logs in to the system, uploads three photos, and enters their occupation as "Sales," role as "Responsible Person," and age as "30."

[0733] 2. Server: Stores the photos and input information in a database.

[0734] 3. Server: The uploaded photo is sent to the emotion engine, where the emotion of joy is recognized.

[0735] 4. Server: Determines the parameters of "bright background", "high brightness" and "high contrast" based on occupation, role, age and perceived happiness.

[0736] 5. Generative AI model: Analyzes the photo and performs processing based on determined parameters, such as increasing the brightness of the photo, setting a bright background, and enhancing the contrast of the face.

[0737] 6. Server: Stores the processed photos in a database and provides them to users.

[0738] 7. User: Log back in to the system to check the edited photo, download it if necessary, and set the downloaded photo as an icon for online communication tools or emails.

[0739] Prompt Sentence Examples

[0740] Here is an example of a prompt to input to a generative AI model:

[0741] "A 30-year-old salesperson has uploaded three photos with the emotion Happy. For these photos, we want to increase the brightness, add a lighter background, and increase the contrast of the face."

[0742] In this way, by combining an emotion engine and a generative AI model, the present invention automatically generates and provides optimal images according to the user's emotions and occupation, thereby contributing to improving the online image of individuals and companies.

[0743] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0744] Step 1:

[0745] A user logs in to the system. They enter their username and password on the login screen and click "Login". The server authenticates the entered username and password, and if authentication is successful, displays the homepage. Specifically, a Python framework (e.g., Django) is used for user authentication. The input is the username and password, and the output is the login status (success or failure).

[0746] Step 2:

[0747] After logging in, the user uploads their own image. The device displays an interface for uploading photos. The user selects a photo and clicks the upload button. The device sends the selected photo to the server via an AJAX request. The server stores the received photo in a MySQL database. The input is the selected image file, and the output is a message that the image was successfully saved to the database.

[0748] Step 3:

[0749] The user enters their occupation, role, and age. The terminal displays an input form for occupation, role, age, etc. The user enters this information and clicks the submit button. The terminal sends the input information to the server via an AJAX request. The server receives the input information and saves it in a MySQL database. The input is text data for occupation, role, and age, and the output is a message that the information was successfully saved to the database.

[0750] Step 4:

[0751] The server sends the uploaded photo to the emotion engine to recognize the user's emotion. The photo data is sent to the emotion engine (for example, Azure Face API) to obtain emotion data. Specifically, the server calls the API, and the emotion engine analyzes the photo and returns emotion data. The input is photo data, and the output is emotion data (numeric values ​​such as joy, sadness, anger, etc.).

[0752] Step 5:

[0753] The server determines image processing parameters based on the user's occupation, role, age, and recognized emotion. A Python script is used to analyze the input information and emotion data, and set image processing parameters such as "brightness," "background color," and "contrast." The input is occupation, role, age, and emotion data, and the output is image processing parameters.

[0754] Step 6:

[0755] The server inputs the determined parameters and the photo into the generative AI model and instructs it to analyze and process the image. The generative AI model (such as TensorFlow or PyTorch) analyzes the photo data and processes the image based on the parameters. The input is the photo data and image processing parameters, and the output is the processed photo data.

[0756] Step 7:

[0757] The server saves the processed photo to the database. Using a Python script, the processed photo data is stored in the MySQL database. The input is the processed photo data, and the output is a message that the data was successfully saved to the database.

[0758] Step 8:

[0759] The user re-logins into the system and accesses the confirmation page for the processed image. The user logs in again and is directed to a dedicated confirmation page. The terminal displays the processed image to the user and provides a downloadable link. The input is the user's re-login information, and the output is the processed image and download link displayed on the confirmation page.

[0760] (Application example 2)

[0761] 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."

[0762] Conventional advertising visual generation systems have difficulty generating optimal images based on the target user's emotions and profile. Furthermore, new technology is needed to enable advertising agencies to quickly create effective advertising visuals that meet their clients' needs. Furthermore, if the generated visuals do not match the target user's emotions, the effectiveness of the advertisement decreases.

[0763] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to upload their own photo, means for the user to input their industry, job title, and age, means for the server to save these photos and input information in a database, means for the server to recognize the user's emotion from the uploaded photo using an emotion engine, means for the server to determine image processing parameters based on the user's information and the recognized emotion, means for the AI ​​model to edit the photo based on these parameters, means for the server to save the edited photo in a database and provide it to the user, and means for the user to check and download the edited photo. This enables the automatic generation of optimal advertising visuals based on the emotions and profile of target users.

[0764] "User" means any person or entity using the system who uploads photos and enters required information.

[0765] "Client" refers to an entity, such as an advertising agency or company, that uses the system to generate advertising visuals for target users.

[0766] "Target users" refers to the specific people or customer groups for whom advertising visuals are created.

[0767] "Photos" are image files of users or target users, and are digital data uploaded to the system.

[0768] "Industry" refers to the occupation or industry to which the user or target user belongs.

[0769] "Job title" is information that refers to the job position or role of the user or target user.

[0770] "Age" refers to the numerical stage of development calculated from the user's or target user's year of birth.

[0771] A "server" is a computer system responsible for storing, processing, and managing data.

[0772] A "database" is a system for managing and storing data such as photographs, input information, and generated advertising visuals.

[0773] An "emotion engine" is a machine learning model or algorithm that analyzes uploaded photos and quantifies the emotions of users and target users.

[0774] "Image processing parameters" refers to settings and adjustments related to image processing, such as brightness, background color, and contrast of a photograph.

[0775] An "AI model" is a machine learning model used to process and generate images based on input data.

[0776] "Processed photos" are photographic data that have been processed according to image processing parameters specified by the AI ​​model.

[0777] "Advertising visuals" are visual advertising materials created to help clients effectively approach their target users.

[0778] This invention is a system that automatically generates optimal advertising visuals based on user emotions and profiles, enabling clients to quickly and easily create effective advertisements for target users. This system is composed of the following steps, hardware, and software.

[0779] System configuration

[0780] 1. User and Client Account Management

[0781] Terminal: Provides an interface for account creation and login.

[0782] Server: Manage account information using Firebase Authentication.

[0783] 2. Targeted user photo upload feature

[0784] Terminal: Provides a UI for clients to upload photos of target users.

[0785] Server: Save the uploaded photos to Firebase Storage.

[0786] 3. Profile data entry function

[0787] Terminal: Provides a form where clients can enter the industry, job title, and age of their target users.

[0788] Server: Save the entered data to Firebase Firestore.

[0789] 4. Emotion recognition function

[0790] Server: Sends the uploaded photo to Google Cloud Vision API and obtains the sentiment analysis results.

[0791] Emotion engine: Analyzes the user's facial expressions and quantifies emotions (e.g., joy, sadness, anger, etc.).

[0792] 5. Image generation function

[0793] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the emotion engine results and profile data.

[0794] Server and AI model: Using TensorFlow, the target user's photo is processed based on the determined parameters.

[0795] AI Model: Uses a generative AI model to create optimal ad visuals based on the prompt you provide.

[0796] 6. Image confirmation and download function

[0797] Terminal: Provides a UI where clients can view and download the generated ad visuals.

[0798] Server: Stores the generated advertising visuals in a database and provides them to clients.

[0799] Specific examples

[0800] For example, to generate advertising visuals for a 30-year-old salesperson, the client uploads a photo and profile of the salesperson (industry: sales, job title: responsible, age: 30). The system provides the following prompt sentence to the generative AI model:

[0801] Prompt Sentence Examples

[0802] Please generate the best advertising visual for a 30-year-old salesperson. The emotion of the photo is recognized as "joy." Please use a light background, high brightness, and strong contrast settings.

[0803] Hardware and software used

[0804] Firebase Authentication: A platform for managing authentication.

[0805] Firebase Firestore: A cloud database for storing and managing data.

[0806] Firebase Storage: Cloud storage for saving photos.

[0807] Google Cloud Vision API: A cloud-based image analysis service for emotion recognition.

[0808] TensorFlow: A platform for image generation and processing using machine learning models.

[0809] React Native: A framework used to build user interfaces.

[0810] In this way, the system of the present invention combines an emotion engine and a generative AI model to automatically generate optimal advertising visuals based on the emotions and profiles of target users, enabling clients to quickly create effective advertising visuals and maximize marketing effectiveness.

[0811] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0812] Step 1:

[0813] Terminal: The client logs in to the system. The client's authentication information (username, password) is entered and authentication is performed using Firebase Authentication. If authentication is successful, the client's account information is obtained and the system proceeds to the next step.

[0814] Step 2:

[0815] Device: After logging in, the client uploads a photo of the target user. The client selects the photo file using the device's UI and clicks the upload button. Once the photo file is selected, the device sends the photo data to Firebase Storage.

[0816] Step 3:

[0817] Server: Retrieve the photo data stored in Firebase Storage and save it to the database. The server saves the photo file URL and metadata such as the upload date and time to Firebase Firestore. Once saving is complete, proceed to the next step.

[0818] Step 4:

[0819] Terminal: Provides a form for entering profile information (industry, job title, age) of the target user. The client enters information in each field and clicks the submit button. The entered information is sent from the terminal to the server.

[0820] Step 5:

[0821] Server: Receives the profile information sent from the client and saves it to the database. The profile information is stored in Firebase Firestore and associated with the photo data. Once saved, proceed to the next step.

[0822] Step 6:

[0823] Server: Sends photo data to the Google Cloud Vision API and performs emotion recognition. Receives emotion data (e.g., joy, sadness, anger, etc.) returned from the API. Analyzes and quantifies the received emotion data. Stores the analysis results in a database and proceeds to the next step.

[0824] Step 7:

[0825] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on profile information and emotion data. Sets these parameters and prepares them as input data for the AI ​​model.

[0826] Step 8:

[0827] Server and AI model: Using TensorFlow, the photo is processed based on the set image processing parameters. A specific prompt is input to the generation AI model. For example, the following prompt is used to generate an image:

[0828] Please generate the best advertising visual for a 30-year-old salesperson. The emotion of the photo is recognized as "joy." Please use a light background, high brightness, and strong contrast settings.

[0829] The AI ​​model processes the photo according to the prompt, generates the optimal advertising visual, and returns the generated image to the server.

[0830] Step 9:

[0831] Server: Saves the generated ad visuals to the database. Once saved, sends a notification to the client to let them know the image has been generated.

[0832] Step 10:

[0833] Terminal: The client accesses the UI to view the generated ad visuals. The generated images are displayed on the terminal, and the client can view them and download them if necessary.

[0834] By following these steps, clients can automatically generate optimal advertising visuals based on the emotions and profiles of their target users, thereby enhancing their marketing effectiveness.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] [Third embodiment]

[0839] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0840] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0841] 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).

[0842] 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.

[0843] 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.

[0844] 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).

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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."

[0851] The system based on this patent claim allows users to upload their own photos and input their industry, job title, and age, and then AI generates and provides the most suitable image.

[0852] System configuration

[0853] 1. Photo upload function

[0854] User: Logs into the system and uploads a photo of himself.

[0855] Terminal: Provides an interface for uploading photos and sends selected photos to the server.

[0856] Server: Receives uploaded photos and stores them in a database.

[0857] 2. Input function for industry, job title, and age

[0858] Terminal: Provides users with fields to input information such as industry, job title, and age.

[0859] User: Enter the required information in the provided fields and submit.

[0860] Server: Receives the entered information and stores it in a database.

[0861] 3. Image processing parameter determination function

[0862] Server: Retrieves the user's photo and input information from the database.

[0863] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, and age information.

[0864] 4. AI-based image analysis and processing functions

[0865] Server: Inputs the determined parameters and photos into the AI ​​model and instructs it on image analysis and processing.

[0866] AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[0867] Server: Obtains the processed photos and stores them in a database.

[0868] 5. Image provision function

[0869] User: Log in to the system and check the processed image.

[0870] On-device: The processed image is displayed to the user and a download function is provided.

[0871] Program processing flow

[0872] The program of this system proceeds as follows:

[0873] 1. Upload a photo

[0874] A user logs into the system and uploads a photo.

[0875] The terminal transmits the selected photos to the server, and the server stores the received photos in a database.

[0876] 2. Enter your industry and job title information

[0877] The device displays an input form for industry, job title, and age, and the user enters the information.

[0878] The terminal sends the entered information to the server, which stores it in a database.

[0879] 3. Determining image processing parameters

[0880] The server retrieves the user's photo and input information from the database.

[0881] The server determines image processing parameters based on the information.

[0882] 4. Image analysis and processing

[0883] The server inputs the photo and parameters into the AI ​​model and instructs it to analyze and process it.

[0884] The AI ​​model analyzes the photo and performs optimal processing based on the parameters.

[0885] The server retrieves the processed photos and stores them in a database.

[0886] 5. Providing edited images

[0887] Users can log in to view the edited images and download them if necessary.

[0888] The device displays the processed image and provides a download function.

[0889] Specific examples

[0890] Example of a sales representative (30 years old)

[0891] The user (sales representative) logs into the system, uploads three photos, and enters the industry as "sales," the job title as "responsible person," and the age as "30 years old."

[0892] The server stores the photos and information in a database and determines the parameters of "light background," "high brightness," and "strong contrast" based on industry, job title, and age.

[0893] The AI ​​model analyzes the photo and applies specified effects based on the parameters, such as increasing the brightness of the photo, setting a bright background, and increasing the contrast of the face.

[0894] The server stores the edited photos in a database, and users can log in to view and download the photos.

[0895] In this way, the present invention uses AI technology to automatically generate optimal images based on user information, providing photos suitable for use in online meetings and emails.

[0896] The processing flow will be explained below.

[0897] Step 1:

[0898] A user logs into the system and accesses the photo upload page.

[0899] Step 2:

[0900] The device will display a photo upload interface, where users can click the file selection button and select up to three of their own photos.

[0901] Step 3:

[0902] The user selects a photo and presses the upload button.

[0903] Step 4:

[0904] The terminal transmits the selected photo file to the server.

[0905] Step 5:

[0906] The server analyzes the received photo data and verifies whether it has been uploaded correctly.

[0907] After the server verifies it, it stores the photo data in a database.

[0908] Step 6:

[0909] The device displays a form for entering occupation, position, and age.

[0910] Step 7:

[0911] The user enters their occupation (e.g., sales), position (e.g., manager), and age (e.g., 30 years old), and presses the send button.

[0912] Step 8:

[0913] The terminal transmits the input information to the server.

[0914] The server stores the received information in a database.

[0915] Step 9:

[0916] The server retrieves the user's photo and input information from the database.

[0917] Step 10:

[0918] The server determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, and age information.

[0919] Step 11:

[0920] The server inputs the determined parameters and photo data into the AI ​​model and instructs it on image analysis and processing.

[0921] Step 12:

[0922] The AI ​​model analyzes the photo and processes it based on determined parameters.

[0923] For example, adjust brightness, change background, enhance contrast, etc.

[0924] Step 13:

[0925] The server retrieves the processed photo data and stores it in a database.

[0926] Step 14:

[0927] The user logs back into the system and accesses the confirmation page for the processed image.

[0928] Step 15:

[0929] The device will then display the edited photo to the user and offer the option to download it.

[0930] Step 16:

[0931] Users can view the edited photos and download them if necessary.

[0932] Set the photos downloaded by the user as icons for online meeting tools and emails.

[0933] Example 1

[0934] 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."

[0935] In the past, it was often time-consuming and required specialized knowledge for users to obtain the perfect profile picture for use in online meetings or emails. In particular, when editing images themselves, it was often difficult to adjust the appropriate brightness, background color, contrast, etc., resulting in a lack of a professional impression. An effective and easy-to-use system to solve these problems is needed.

[0936] 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.

[0937] In this invention, the server includes a means for users to upload their own electronic images, a means for users to input their occupation, job title, and age, and a means for the generative AI model to process the electronic images based on these parameters, thereby enabling users to easily generate their own profile pictures in an optimal form.

[0938] A "user" is a person who uses the system and uploads an electronic image of himself or herself and enters his or her occupation, job title, and age.

[0939] "Server" means a computing device that processes information received from users, stores it in a data storage device, and utilizes generative AI models to manipulate electronic images.

[0940] "Electronic images" refer to photographic data uploaded by users to the system and used as profile images for online meeting tools and email.

[0941] "Occupation" refers to information that indicates the industry or occupation in which the user is engaged.

[0942] "Position" refers to information that indicates a user's job position or title.

[0943] "Age" refers to information indicating the user's age.

[0944] A "generative AI model" is an artificial intelligence model that performs optimal image processing based on uploaded electronic images and user input.

[0945] "Image processing parameters" are the settings or conditions used by a generative AI model to process an electronic image, including brightness, background color, contrast, etc.

[0946] "Data storage device" means storage for electronic images and input information received from users, and electronic images processed by generative AI models.

[0947] This invention is a system in which a user uploads their own digital image and inputs their occupation, job title, and age, and a generative AI model generates and provides the most suitable image. This system is mainly composed of three parties: a server, a terminal, and the user.

[0948] First, a user logs in to the system and uploads their own electronic image. The user can easily perform operations through the system interface. The terminal provides an interface for uploading photos and sends the electronic image selected by the user to the server. The server validates the received electronic image and stores it in a data storage device.

[0949] Next, the terminal provides the user with an input form for information such as occupation, position, age, etc. The user enters this information and submits it. The terminal then transmits the input information to the server, which stores it in a data storage device.

[0950] The server retrieves the user's digital image and input information from the data storage device and determines image processing parameters based on the user's occupation, position, and age. For example, if the occupation is "sales," the position is "person in charge," and the age is "30," the parameters set are "light background," "high brightness," and "strong contrast."

[0951] The server then inputs the digital image along with the determined parameters into a generative AI model, which then performs image analysis and processing using libraries such as TensorFlow and PyTorch. This includes adjusting brightness, changing background colors, and enhancing contrast.

[0952] The server receives the electronic images processed by the generative AI model and stores them again in the data storage device. The user can log in to the system again and check the processed electronic images. The terminal displays the processed images to the user and provides a download function. The user can download the images as needed and use them in online meeting tools or email.

[0953] Specific examples

[0954] For example, a sales user (30 years old) logs in to the system and uploads three photos. The user enters their occupation as "sales," their position as "responsible," and their age as "30." The server stores this information in a data storage device and determines the parameters for "light background," "high brightness," and "strong contrast" based on the industry, position, and age information. The generative AI model processes the photos based on these settings, generating an image with, for example, increased brightness, a bright background, and enhanced facial contrast. The server then stores the processed electronic images in a data storage device, and the user can log in again to review the images and download them if necessary.

[0955] Prompt Sentence Examples

[0956] "Improve your sales profile photo. I have three photos. I'm 30 years old. Safely adjust the brightness, background, and contrast accordingly."

[0957] The system allows users to easily get the best profile picture possible, creating a professional impression in online meetings and emails.

[0958] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0959] Step 1: The user logs in to the system and accesses the photo upload screen. The terminal displays a file input field and provides an interface for the user to select a photo. When the user selects a photo and presses the "Upload" button, the terminal sends the photo data to the server. The input is the user's photo file, and the output is the transmission result to the server. The server validates the received photo and saves it in the data storage device.

[0960] Step 2: The user accesses a screen to input occupation, position, and age information. The terminal displays a form for inputting this information, allowing the user to enter data. The terminal sends the input information to the server. The input is occupation, position, and age information, and the output is the transmission result to the server. The server saves the received information in a data storage device.

[0961] Step 3: The server retrieves the user's photo and input information from the data storage device. Using SQL queries or similar, the server retrieves the stored photo and information on occupation, position, and age. The input is the stored data record, and the output is the retrieved data. The server determines the image processing parameters based on this information. For example, for a sales representative (age 30), the parameters set are "light background," "high brightness," and "strong contrast."

[0962] Step 4: The server inputs the determined image processing parameters and the user's photo into the generative AI model. The generative AI model analyzes and processes the photo based on these parameters. The input is the image processing parameters and photo data, and the output is the processed photo data. Specifically, the generative AI model adjusts brightness, changes the background color, and enhances contrast.

[0963] Step 5: The server receives the processed photo returned by the generative AI model and stores it in the data storage device. The server re-encodes the processed photo data, stores it in cloud storage, and adds its URL to the data record. The input is the processed photo data, and the output is the result of the storage completion.

[0964] Step 6: The user logs in to the system again to view the edited photo. The device requests the edited photo data from the server and displays it. The user can download the photo if needed. The input is the user request, and the output is the edited photo data. The device generates a download link, allowing the user to download the photo.

[0965] (Application example 1)

[0966] 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."

[0967] Conventional photo editing systems require specialized knowledge and highly accurate tools for users to edit their own photos optimally, and the process requires a lot of time and effort. Furthermore, they lack the functionality to automatically generate promotional images for use in physical stores, and creating them manually is time-consuming. Therefore, there was a demand for a system that could easily and quickly generate and provide optimal promotional images.

[0968] 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.

[0969] In this invention, the server includes: a means for users to upload their own photos; a means for users to input their industry, job title, and age; a means for the server to save these photos and input information in a database; a means for the server to determine image processing parameters based on the user's information; a means for an AI model to edit the photos based on these parameters; a means for the server to save the edited photos in a database and provide them to users; a means for users to check and download the edited photos; and a means for the AI ​​to generate optimal promotional images by users inputting their own photos and store information (industry, job title, age) and provide the promotional images to be displayed on smart displays in physical stores. This allows users to quickly and efficiently generate optimal promotional images without the need for specialized knowledge or tools, and to immediately use them in physical stores, etc.

[0970] "Server" means a computer system that receives, stores, processes, and analyzes data entered by users.

[0971] "User" refers to a person or organization that uses this system to upload their own photo, enter their industry, job title, and age, and obtain the most suitable edited photo.

[0972] "Photo Uploader" means the functionality or interface that allows a User to provide their photo to the System.

[0973] "Means for inputting industry, job title, and age" refers to the functions and interfaces that allow a user to provide information about their industry, job title, and age to the system.

[0974] "Image processing parameters" refer to adjustment elements such as brightness, background, and contrast required for processing a photograph.

[0975] An "AI model" is an artificial intelligence algorithm and system that analyzes and processes input data.

[0976] "Promotional images" are images used for promotional and advertising purposes, such as on smart displays in physical stores.

[0977] A "smart display" is an electronic display device such as digital signage that is used to provide information and display advertisements in stores, events, etc.

[0978] An "edited photo" is a photo after brightness, background, and contrast have been adjusted based on image processing parameters specified by the AI ​​model.

[0979] A "database" is a storage device or medium for systematically organizing and storing information within a system.

[0980] MODE FOR CARRYING OUT THE INVENTION

[0981] This system for implementing the invention allows users to upload their own photos and input their industry, job title, and age, and then AI generates and provides the most suitable image.The system can also automatically generate promotional images for smart displays in physical stores based on user input.

[0982] System configuration

[0983] 1. Photo upload function

[0984] The server provides a means for users to upload their own photos via their devices, which are then sent to the server and stored in a database.

[0985] 2. Input function for industry, job title, and age

[0986] Users have the means to input their industry, job title, and age through the terminal, and the input information is sent to the server and stored in a database.

[0987] 3. Image processing parameter determination function

[0988] The server determines image processing parameters (brightness, background, contrast, etc.) based on the user's industry, job title, and age information, which is obtained from a database.

[0989] 4. AI-based image analysis and processing functions

[0990] The server inputs the determined parameters and the photo into the AI ​​model and instructs it to analyze and process the image. The AI ​​model analyzes the image and performs optimal processing based on the parameters.

[0991] 5. Image provision function

[0992] The processed photos are stored on a server and can be accessed by users via their devices to view and download them.

[0993] Promotional images can also be provided for display on smart displays in physical stores.

[0994] Hardware and software used

[0995] 1. Server: Stores, processes, and analyzes data. For processing functions, we use cloud computing services such as Amazon Web Services (AWS).

[0996] 2. Device: Use an internet-enabled device such as a smartphone or tablet to upload photos and enter information.

[0997] 3. AI model: For image analysis and processing, we use machine learning frameworks such as TensorFlow and PyTorch, which allow us to properly analyze the input image and generate the optimal promotional image.

[0998] Examples and prompts

[0999] For example, suppose a 25-year-old salesperson working at an apparel store wants to generate promotional images for the store's smart displays. In this case, the user would follow the steps below:

[1000] 1. Users take a photo of themselves using their smartphone and upload it to the system.

[1001] 2. The user enters the industry as "apparel," the job title as "store clerk," and the age as "25."

[1002] 3. Based on the input information, the server determines that the brightness should be set to 1.2 times, the background to a fashion-themed image, and the contrast to 1.5 times.

[1003] 4. The AI ​​model runs these settings and generates the edited photo.

[1004] 5. The user can review the edited photo and download it to display on their smart display.

[1005] Example prompt sentence:

[1006] "Based on the photo uploaded by the user, the industry "Apparel", job title "Store Clerk", and age "25", set a bright background image and adjust the photo brightness by 1.2 times and the contrast by 1.5 times."

[1007] This makes it possible to quickly generate and use effective promotional images even in physical stores.

[1008] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1009] Step 1:

[1010] The user takes and uploads their own photo using the device. The device provides a photo upload interface and sends the photo selected by the user to the server. The input is the user's photo, and the output is a photo file stored on the server.

[1011] Step 2:

[1012] The user inputs their industry, job title, and age through the terminal. The terminal displays an input form for industry, job title, and age, and when the user enters the information, it sends the data to the server. The input is the user's industry, job title, and age information, and the output is that information saved on the server.

[1013] Step 3:

[1014] The server retrieves the user's photo and input information from the database. The server loads the necessary data into memory based on the saved photo file and input information. The input is the photo and input information from the database, and the output is the related data stored in memory.

[1015] Step 4:

[1016] The server determines image processing parameters (brightness, background, contrast, etc.) based on the user's industry, job title, and age information. The server calculates the parameters using pre-set rules and models. The input is the user's information, and the output is the determined image processing parameters.

[1017] Step 5:

[1018] The server inputs the determined parameters and photo into the AI ​​model and instructs it to analyze and process the image. The AI ​​model analyzes the image and performs optimal processing based on the parameters. The input is the processing parameters and photo file, and the output is the processed image data.

[1019] Step 6:

[1020] The server stores the processed photos in a database and provides them to the user. The processed images are stored on the server and can be accessed by the user through the system. The input is the processed image data, and the output is the processed image stored in the database.

[1021] Step 7:

[1022] The user checks the edited photo on their device and downloads it if necessary. The device displays the edited photo to the user and provides a download option. The input is the edited image retrieved from the database, and the output is an image file saved on the user's device.

[1023] These specific processing steps enable users to quickly and efficiently generate optimal promotional images without the need for specialized knowledge or tools, and to immediately use them in physical stores, etc.

[1024] 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.

[1025] The present invention is a system in which users not only upload their own photos and input their industry, job title, and age, but also recognize the user's emotions using an emotion engine, and AI generates the optimal image. The detailed configuration and processing flow of the system based on the present invention are described below.

[1026] System configuration

[1027] 1. Photo upload function

[1028] User: Logs into the system and uploads a photo of himself.

[1029] Terminal: Provides an interface for uploading photos and sends selected photos to the server.

[1030] Server: Receives uploaded photos and stores them in a database.

[1031] 2. Input function for industry, job title, and age

[1032] Device: Displays an input form for industry, job title, age, etc.

[1033] User: Enter the required information in the provided fields and submit.

[1034] Server: Receives the entered information and stores it in a database.

[1035] 3. Emotion recognition function using an emotion engine

[1036] Server: Inputs the uploaded photo into the emotion engine to recognize the user's emotion.

[1037] Emotion engine: Analyzes the user's facial expressions and quantifies their emotions, such as happiness, sadness, and anger.

[1038] 4. Image processing parameter determination function

[1039] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, age, and recognized emotion.

[1040] 5. AI-based image analysis and processing functions

[1041] Server: Inputs the determined parameters and photos into the AI ​​model and instructs it on image analysis and processing.

[1042] AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[1043] Server: Obtains the processed photos and stores them in a database.

[1044] 6. Image provision function

[1045] User: Log back into the system and access the confirmation page for the processed image.

[1046] On-device: The processed image is displayed to the user and a download function is provided.

[1047] Program processing flow

[1048] The program of this system proceeds as follows:

[1049] Specific examples

[1050] Example of a sales representative (30 years old)

[1051] 1. User: A sales person logs in to the system and uploads three photos. The user enters the industry as "Sales," the job title as "Responsible Person," and the age as "30."

[1052] 2. Server: Stores the photos and input information in a database.

[1053] 3. Server: The uploaded photo is sent to the emotion engine, where the emotion of joy is recognized.

[1054] 4. Server: Determines the parameters of "bright background," "high brightness," and "strong contrast" based on industry, job title, age, and perceived happiness.

[1055] 5. AI model: Analyzes the photo and performs processing based on the determined parameters, such as increasing the brightness of the photo, setting a bright background, and enhancing the contrast of the face.

[1056] 6. Server: Stores the processed photos in a database and provides them to users.

[1057] 7. User: Log back in to the system to check the edited photo and download it if necessary. Set the downloaded photo as an icon for online meeting tools or emails.

[1058] In this way, by combining emotion engines, the present invention realizes a system that automatically generates optimal images according to the user's emotions, and further contributes to improving the image of individuals and companies online.

[1059] The processing flow will be explained below.

[1060] Step 1:

[1061] A user logs into the system and accesses the photo upload page.

[1062] Step 2:

[1063] The device will display a photo upload interface, where users can click the file selection button and select up to three of their own photos.

[1064] Step 3:

[1065] The user selects a photo and presses the upload button.

[1066] Step 4:

[1067] The terminal transmits the selected photo file to the server.

[1068] Step 5:

[1069] The server analyzes the received photo data and verifies whether it has been uploaded correctly.

[1070] After the server verifies it, it stores the photo data in a database.

[1071] Step 6:

[1072] The device displays a form for entering industry, job title, and age.

[1073] Step 7:

[1074] The user enters the industry (e.g., sales), job title (e.g., person in charge), and age (e.g., 30 years old), and presses the send button.

[1075] Step 8:

[1076] The terminal transmits the input information to the server.

[1077] The server stores the received information in a database.

[1078] Step 9:

[1079] The server retrieves the user's photo and input information from the database.

[1080] Step 10:

[1081] The server inputs the uploaded photos into an emotion engine to recognize the user's emotions.

[1082] Step 11:

[1083] The emotion engine analyzes the user's facial expressions and quantifies the corresponding emotion from a range of emotions (e.g., joy, sadness, anger, etc.).

[1084] Step 12:

[1085] The server determines image processing parameters based on the user's industry, job title, age and recognized emotion.

[1086] Step 13:

[1087] The server inputs the determined parameters and photo data into the AI ​​model and instructs it on image analysis and processing.

[1088] Step 14:

[1089] The AI ​​model analyzes the photo and performs optimal processing based on the parameters (e.g., adjusting brightness, changing the background, adjusting contrast, etc.).

[1090] Step 15:

[1091] The server retrieves the processed photo data and stores it in a database.

[1092] Step 16:

[1093] The user logs back into the system and accesses the confirmation page for the processed image.

[1094] Step 17:

[1095] The device will then display the edited photo to the user and offer the option to download it.

[1096] Step 18:

[1097] Users can view the edited photos and download them if necessary.

[1098] Set the photos downloaded by the user as icons for online meeting tools and emails.

[1099] Example 2

[1100] 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."

[1101] In online communication and business, there is a demand for effective use of users' photos to improve the image of individuals and companies. However, it is difficult for users to create the optimal image on their own, requiring specialized knowledge and skills. Furthermore, conventional image processing tools have the problem of making it difficult to create the optimal image that reflects the user's emotion or occupation.

[1102] 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 a means for a user to upload his / her own image, a means for a user to input his / her occupation, role, and age, and a means for inputting the user's image into an emotion engine and recognizing emotions. This makes it possible to automatically generate and provide an optimal image according to the user's emotion and occupation.

[1103] "User" refers to an individual who logs into the system, uploads their photo, and enters the required information.

[1104] "Images" refers to visual data such as photographs or drawings uploaded by users.

[1105] "Occupation" refers to the industry or occupation to which the user belongs.

[1106] "Role" refers to the position or title a user holds within a profession.

[1107] "Age" refers to the number of years calculated from the user's date of birth.

[1108] "Server" refers to a computer system that receives photos and information from users, stores them in a database, and performs various processing.

[1109] An "emotion engine" refers to software or algorithms that analyze a user's image and quantify their emotions.

[1110] "Image processing parameters" refer to adjustment values ​​such as image brightness, background color, and contrast that are determined based on the user's emotions and occupation.

[1111] A "generative AI model" refers to an artificial intelligence system that analyzes and processes images based on specific parameters.

[1112] "Database" refers to a collection of digital data for storing user photos and information.

[1113] "Online communication tools" refers to software and services that allow users to communicate with each other via the Internet.

[1114] The present invention is a system in which users not only upload their own images and input their occupation, role, and age, but also recognize the user's emotions using an emotion engine, and a generative AI model generates an optimal image. The detailed configuration and processing flow of the system based on the present invention are described below.

[1115] System configuration

[1116] 1. Photo upload function

[1117] User: Log in to the system and upload their own images. Specifically, the user enters their username and password on the login screen, and after logging in, they are directed to the photo upload screen. The photos are uploaded through the file selection interface.

[1118] Terminal: Provides an interface for uploading photos and sends selected photos to the server. This interface uses HTML and JavaScript.

[1119] Server: Receives uploaded photos and stores them in a database. Photo data is stored in a MySQL database using a Python script.

[1120] 2. Occupation, role, and age input function

[1121] Terminal: Displays an input form for occupation, role, age, etc. This form is also built using HTML and JavaScript.

[1122] User: Enter the required information in the provided input field and submit. The entered information is sent from the device to the server.

[1123] Server: Stores the entered information in a database, also done using a Python script.

[1124] 3. Emotion recognition function using an emotion engine

[1125] Server: The uploaded photo is input into the emotion engine to recognize the user's emotions. In this case, we use Microsoft's Azure Face API as the emotion engine.

[1126] Emotion engine: Analyzes the user's facial expressions and quantifies their emotions. For example, it recognizes emotions such as joy, sadness, and anger and returns them as numerical data.

[1127] 4. Image processing parameter determination function

[1128] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's occupation, role, age, and recognized emotion. This process is performed using Python scripts and machine learning libraries.

[1129] 5. AI-based image analysis and processing functions

[1130] Server: The determined parameters and photos are input into the generative AI model, and instructions are given for image analysis and processing. The generative AI model uses libraries such as TensorFlow and PyTorch.

[1131] Generative AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[1132] Server: Stores the processed photos in a database, also done using a Python script.

[1133] 6. Image provision function

[1134] User: Log in to the system again and access the confirmation page for the processed image. After logging in again, you will be able to view and download the processed image.

[1135] On the device: The processed image is displayed to the user and a download function is provided. Image display and download links are provided using HTML and JavaScript.

[1136] Specific examples

[1137] Example of a sales representative (30 years old)

[1138] 1. User: A sales person logs in to the system, uploads three photos, and enters their occupation as "Sales," role as "Responsible Person," and age as "30."

[1139] 2. Server: Stores the photos and input information in a database.

[1140] 3. Server: The uploaded photo is sent to the emotion engine, where the emotion of joy is recognized.

[1141] 4. Server: Determines the parameters of "bright background", "high brightness" and "high contrast" based on occupation, role, age and perceived happiness.

[1142] 5. Generative AI model: Analyzes the photo and performs processing based on determined parameters, such as increasing the brightness of the photo, setting a bright background, and enhancing the contrast of the face.

[1143] 6. Server: Stores the processed photos in a database and provides them to users.

[1144] 7. User: Log back in to the system to check the edited photo, download it if necessary, and set the downloaded photo as an icon for online communication tools or emails.

[1145] Prompt Sentence Examples

[1146] Here is an example of a prompt to input to a generative AI model:

[1147] "A 30-year-old salesperson has uploaded three photos with the emotion Happy. For these photos, we want to increase the brightness, add a lighter background, and increase the contrast of the face."

[1148] In this way, by combining an emotion engine and a generative AI model, the present invention automatically generates and provides optimal images according to the user's emotions and occupation, thereby contributing to improving the online image of individuals and companies.

[1149] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1150] Step 1:

[1151] A user logs in to the system. They enter their username and password on the login screen and click "Login". The server authenticates the entered username and password, and if authentication is successful, displays the homepage. Specifically, a Python framework (e.g., Django) is used for user authentication. The input is the username and password, and the output is the login status (success or failure).

[1152] Step 2:

[1153] After logging in, the user uploads their own image. The device displays an interface for uploading photos. The user selects a photo and clicks the upload button. The device sends the selected photo to the server via an AJAX request. The server stores the received photo in a MySQL database. The input is the selected image file, and the output is a message that the image was successfully saved to the database.

[1154] Step 3:

[1155] The user enters their occupation, role, and age. The terminal displays an input form for occupation, role, age, etc. The user enters this information and clicks the submit button. The terminal sends the input information to the server via an AJAX request. The server receives the input information and saves it in a MySQL database. The input is text data for occupation, role, and age, and the output is a message that the information was successfully saved to the database.

[1156] Step 4:

[1157] The server sends the uploaded photo to the emotion engine to recognize the user's emotion. The photo data is sent to the emotion engine (for example, Azure Face API) to obtain emotion data. Specifically, the server calls the API, and the emotion engine analyzes the photo and returns emotion data. The input is photo data, and the output is emotion data (numeric values ​​such as joy, sadness, anger, etc.).

[1158] Step 5:

[1159] The server determines image processing parameters based on the user's occupation, role, age, and recognized emotion. A Python script is used to analyze the input information and emotion data, and set image processing parameters such as "brightness," "background color," and "contrast." The input is occupation, role, age, and emotion data, and the output is image processing parameters.

[1160] Step 6:

[1161] The server inputs the determined parameters and the photo into the generative AI model and instructs it to analyze and process the image. The generative AI model (such as TensorFlow or PyTorch) analyzes the photo data and processes the image based on the parameters. The input is the photo data and image processing parameters, and the output is the processed photo data.

[1162] Step 7:

[1163] The server saves the processed photo to the database. Using a Python script, the processed photo data is stored in the MySQL database. The input is the processed photo data, and the output is a message that the data was successfully saved to the database.

[1164] Step 8:

[1165] The user re-logins into the system and accesses the confirmation page for the processed image. The user logs in again and is directed to a dedicated confirmation page. The terminal displays the processed image to the user and provides a downloadable link. The input is the user's re-login information, and the output is the processed image and download link displayed on the confirmation page.

[1166] (Application example 2)

[1167] 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."

[1168] Conventional advertising visual generation systems have difficulty generating optimal images based on the target user's emotions and profile. Furthermore, new technology is needed to enable advertising agencies to quickly create effective advertising visuals that meet their clients' needs. Furthermore, if the generated visuals do not match the target user's emotions, the effectiveness of the advertisement decreases.

[1169] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to upload their own photo, means for the user to input their industry, job title, and age, means for the server to save these photos and input information in a database, means for the server to recognize the user's emotion from the uploaded photo using an emotion engine, means for the server to determine image processing parameters based on the user's information and the recognized emotion, means for the AI ​​model to edit the photo based on these parameters, means for the server to save the edited photo in a database and provide it to the user, and means for the user to check and download the edited photo. This enables the automatic generation of optimal advertising visuals based on the emotions and profile of target users.

[1170] "User" means any person or entity using the system who uploads photos and enters required information.

[1171] "Client" refers to an entity, such as an advertising agency or company, that uses the system to generate advertising visuals for target users.

[1172] "Target users" refers to the specific people or customer groups for whom advertising visuals are created.

[1173] "Photos" are image files of users or target users, and are digital data uploaded to the system.

[1174] "Industry" refers to the occupation or industry to which the user or target user belongs.

[1175] "Job title" is information that refers to the job position or role of the user or target user.

[1176] "Age" refers to the numerical stage of development calculated from the user's or target user's year of birth.

[1177] A "server" is a computer system responsible for storing, processing, and managing data.

[1178] A "database" is a system for managing and storing data such as photographs, input information, and generated advertising visuals.

[1179] An "emotion engine" is a machine learning model or algorithm that analyzes uploaded photos and quantifies the emotions of users and target users.

[1180] "Image processing parameters" refers to settings and adjustments related to image processing, such as brightness, background color, and contrast of a photograph.

[1181] An "AI model" is a machine learning model used to process and generate images based on input data.

[1182] "Processed photos" are photographic data that have been processed according to image processing parameters specified by the AI ​​model.

[1183] "Advertising visuals" are visual advertising materials created to help clients effectively approach their target users.

[1184] This invention is a system that automatically generates optimal advertising visuals based on user emotions and profiles, enabling clients to quickly and easily create effective advertisements for target users. This system is composed of the following steps, hardware, and software.

[1185] System configuration

[1186] 1. User and Client Account Management

[1187] Terminal: Provides an interface for account creation and login.

[1188] Server: Manage account information using Firebase Authentication.

[1189] 2. Targeted user photo upload feature

[1190] Terminal: Provides a UI for clients to upload photos of target users.

[1191] Server: Save the uploaded photos to Firebase Storage.

[1192] 3. Profile data entry function

[1193] Terminal: Provides a form where clients can enter the industry, job title, and age of their target users.

[1194] Server: Save the entered data to Firebase Firestore.

[1195] 4. Emotion recognition function

[1196] Server: Sends the uploaded photo to Google Cloud Vision API and obtains the sentiment analysis results.

[1197] Emotion engine: Analyzes the user's facial expressions and quantifies emotions (e.g., joy, sadness, anger, etc.).

[1198] 5. Image generation function

[1199] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the emotion engine results and profile data.

[1200] Server and AI model: Using TensorFlow, the target user's photo is processed based on the determined parameters.

[1201] AI Model: Uses a generative AI model to create optimal ad visuals based on the prompt you provide.

[1202] 6. Image confirmation and download function

[1203] Terminal: Provides a UI where clients can view and download the generated ad visuals.

[1204] Server: Stores the generated advertising visuals in a database and provides them to clients.

[1205] Specific examples

[1206] For example, to generate advertising visuals for a 30-year-old salesperson, the client uploads a photo and profile of the salesperson (industry: sales, job title: responsible, age: 30). The system provides the following prompt sentence to the generative AI model:

[1207] Prompt Sentence Examples

[1208] Please generate the best advertising visual for a 30-year-old salesperson. The emotion of the photo is recognized as "joy." Please use a light background, high brightness, and strong contrast settings.

[1209] Hardware and software used

[1210] Firebase Authentication: A platform for managing authentication.

[1211] Firebase Firestore: A cloud database for storing and managing data.

[1212] Firebase Storage: Cloud storage for saving photos.

[1213] Google Cloud Vision API: A cloud-based image analysis service for emotion recognition.

[1214] TensorFlow: A platform for image generation and processing using machine learning models.

[1215] React Native: A framework used to build user interfaces.

[1216] In this way, the system of the present invention combines an emotion engine and a generative AI model to automatically generate optimal advertising visuals based on the emotions and profiles of target users, enabling clients to quickly create effective advertising visuals and maximize marketing effectiveness.

[1217] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1218] Step 1:

[1219] Terminal: The client logs in to the system. The client's authentication information (username, password) is entered and authentication is performed using Firebase Authentication. If authentication is successful, the client's account information is obtained and the system proceeds to the next step.

[1220] Step 2:

[1221] Device: After logging in, the client uploads a photo of the target user. The client selects the photo file using the device's UI and clicks the upload button. Once the photo file is selected, the device sends the photo data to Firebase Storage.

[1222] Step 3:

[1223] Server: Retrieve the photo data stored in Firebase Storage and save it to the database. The server saves the photo file URL and metadata such as the upload date and time to Firebase Firestore. Once saving is complete, proceed to the next step.

[1224] Step 4:

[1225] Terminal: Provides a form for entering profile information (industry, job title, age) of the target user. The client enters information in each field and clicks the submit button. The entered information is sent from the terminal to the server.

[1226] Step 5:

[1227] Server: Receives the profile information sent from the client and saves it to the database. The profile information is stored in Firebase Firestore and associated with the photo data. Once saved, proceed to the next step.

[1228] Step 6:

[1229] Server: Sends photo data to the Google Cloud Vision API and performs emotion recognition. Receives emotion data (e.g., joy, sadness, anger, etc.) returned from the API. Analyzes and quantifies the received emotion data. Stores the analysis results in a database and proceeds to the next step.

[1230] Step 7:

[1231] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on profile information and emotion data. Sets these parameters and prepares them as input data for the AI ​​model.

[1232] Step 8:

[1233] Server and AI model: Using TensorFlow, the photo is processed based on the set image processing parameters. A specific prompt is input to the generation AI model. For example, the following prompt is used to generate an image:

[1234] Please generate the best advertising visual for a 30-year-old salesperson. The emotion of the photo is recognized as "joy." Please use a light background, high brightness, and strong contrast settings.

[1235] The AI ​​model processes the photo according to the prompt, generates the optimal advertising visual, and returns the generated image to the server.

[1236] Step 9:

[1237] Server: Saves the generated ad visuals to the database. Once saved, sends a notification to the client to let them know the image has been generated.

[1238] Step 10:

[1239] Terminal: The client accesses the UI to view the generated ad visuals. The generated images are displayed on the terminal, and the client can view them and download them if necessary.

[1240] By following these steps, clients can automatically generate optimal advertising visuals based on the emotions and profiles of their target users, thereby enhancing their marketing effectiveness.

[1241] 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.

[1242] 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.

[1243] 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.

[1244] [Fourth embodiment]

[1245] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1246] 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.

[1247] 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).

[1248] 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.

[1249] 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.

[1250] 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).

[1251] 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.

[1252] 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.

[1253] 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.

[1254] 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.

[1255] 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.

[1256] 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.

[1257] 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."

[1258] The system based on this patent claim allows users to upload their own photos and input their industry, job title, and age, and then AI generates and provides the most suitable image.

[1259] System configuration

[1260] 1. Photo upload function

[1261] User: Logs into the system and uploads a photo of himself.

[1262] Terminal: Provides an interface for uploading photos and sends selected photos to the server.

[1263] Server: Receives uploaded photos and stores them in a database.

[1264] 2. Input function for industry, job title, and age

[1265] Terminal: Provides users with fields to input information such as industry, job title, and age.

[1266] User: Enter the required information in the provided fields and submit.

[1267] Server: Receives the entered information and stores it in a database.

[1268] 3. Image processing parameter determination function

[1269] Server: Retrieves the user's photo and input information from the database.

[1270] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, and age information.

[1271] 4. AI-based image analysis and processing functions

[1272] Server: Inputs the determined parameters and photos into the AI ​​model and instructs it on image analysis and processing.

[1273] AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[1274] Server: Obtains the processed photos and stores them in a database.

[1275] 5. Image provision function

[1276] User: Log in to the system and check the processed image.

[1277] On-device: The processed image is displayed to the user and a download function is provided.

[1278] Program processing flow

[1279] The program of this system proceeds as follows:

[1280] 1. Upload a photo

[1281] A user logs into the system and uploads a photo.

[1282] The terminal transmits the selected photos to the server, and the server stores the received photos in a database.

[1283] 2. Enter your industry and job title information

[1284] The device displays an input form for industry, job title, and age, and the user enters the information.

[1285] The terminal sends the entered information to the server, which stores it in a database.

[1286] 3. Determining image processing parameters

[1287] The server retrieves the user's photo and input information from the database.

[1288] The server determines image processing parameters based on the information.

[1289] 4. Image analysis and processing

[1290] The server inputs the photo and parameters into the AI ​​model and instructs it to analyze and process it.

[1291] The AI ​​model analyzes the photo and performs optimal processing based on the parameters.

[1292] The server retrieves the processed photos and stores them in a database.

[1293] 5. Providing edited images

[1294] Users can log in to view the edited images and download them if necessary.

[1295] The device displays the processed image and provides a download function.

[1296] Specific examples

[1297] Example of a sales representative (30 years old)

[1298] The user (sales representative) logs into the system, uploads three photos, and enters the industry as "sales," the job title as "responsible person," and the age as "30 years old."

[1299] The server stores the photos and information in a database and determines the parameters of "light background," "high brightness," and "strong contrast" based on industry, job title, and age.

[1300] The AI ​​model analyzes the photo and applies specified effects based on the parameters, such as increasing the brightness of the photo, setting a bright background, and increasing the contrast of the face.

[1301] The server stores the edited photos in a database, and users can log in to view and download the photos.

[1302] In this way, the present invention uses AI technology to automatically generate optimal images based on user information, providing photos suitable for use in online meetings and emails.

[1303] The processing flow will be explained below.

[1304] Step 1:

[1305] A user logs into the system and accesses the photo upload page.

[1306] Step 2:

[1307] The device will display a photo upload interface, where users can click the file selection button and select up to three of their own photos.

[1308] Step 3:

[1309] The user selects a photo and presses the upload button.

[1310] Step 4:

[1311] The terminal transmits the selected photo file to the server.

[1312] Step 5:

[1313] The server analyzes the received photo data and verifies whether it has been uploaded correctly.

[1314] After the server verifies it, it stores the photo data in a database.

[1315] Step 6:

[1316] The device displays a form for entering occupation, position, and age.

[1317] Step 7:

[1318] The user enters their occupation (e.g., sales), position (e.g., manager), and age (e.g., 30 years old), and presses the send button.

[1319] Step 8:

[1320] The terminal transmits the input information to the server.

[1321] The server stores the received information in a database.

[1322] Step 9:

[1323] The server retrieves the user's photo and input information from the database.

[1324] Step 10:

[1325] The server determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, and age information.

[1326] Step 11:

[1327] The server inputs the determined parameters and photo data into the AI ​​model and instructs it on image analysis and processing.

[1328] Step 12:

[1329] The AI ​​model analyzes the photo and processes it based on determined parameters.

[1330] For example, adjust brightness, change background, enhance contrast, etc.

[1331] Step 13:

[1332] The server retrieves the processed photo data and stores it in a database.

[1333] Step 14:

[1334] The user logs back into the system and accesses the confirmation page for the processed image.

[1335] Step 15:

[1336] The device will then display the edited photo to the user and offer the option to download it.

[1337] Step 16:

[1338] Users can view the edited photos and download them if necessary.

[1339] Set the photos downloaded by the user as icons for online meeting tools and emails.

[1340] Example 1

[1341] 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."

[1342] In the past, it was often time-consuming and required specialized knowledge for users to obtain the perfect profile picture for use in online meetings or emails. In particular, when editing images themselves, it was often difficult to adjust the appropriate brightness, background color, contrast, etc., resulting in a lack of a professional impression. An effective and easy-to-use system to solve these problems is needed.

[1343] 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.

[1344] In this invention, the server includes a means for users to upload their own electronic images, a means for users to input their occupation, job title, and age, and a means for the generative AI model to process the electronic images based on these parameters, thereby enabling users to easily generate their own profile pictures in an optimal form.

[1345] A "user" is a person who uses the system and uploads an electronic image of himself or herself and enters his or her occupation, job title, and age.

[1346] "Server" means a computing device that processes information received from users, stores it in a data storage device, and utilizes generative AI models to manipulate electronic images.

[1347] "Electronic images" refer to photographic data uploaded by users to the system and used as profile images for online meeting tools and email.

[1348] "Occupation" refers to information that indicates the industry or occupation in which the user is engaged.

[1349] "Position" refers to information that indicates a user's job position or title.

[1350] "Age" refers to information indicating the user's age.

[1351] A "generative AI model" is an artificial intelligence model that performs optimal image processing based on uploaded electronic images and user input.

[1352] "Image processing parameters" are the settings or conditions used by a generative AI model to process an electronic image, including brightness, background color, contrast, etc.

[1353] "Data storage device" means storage for electronic images and input information received from users, and electronic images processed by generative AI models.

[1354] This invention is a system in which a user uploads their own digital image and inputs their occupation, job title, and age, and a generative AI model generates and provides the most suitable image. This system is mainly composed of three parties: a server, a terminal, and the user.

[1355] First, a user logs in to the system and uploads their own electronic image. The user can easily perform operations through the system interface. The terminal provides an interface for uploading photos and sends the electronic image selected by the user to the server. The server validates the received electronic image and stores it in a data storage device.

[1356] Next, the terminal provides the user with an input form for information such as occupation, position, age, etc. The user enters this information and submits it. The terminal then transmits the input information to the server, which stores it in a data storage device.

[1357] The server retrieves the user's digital image and input information from the data storage device and determines image processing parameters based on the user's occupation, position, and age. For example, if the occupation is "sales," the position is "person in charge," and the age is "30," the parameters set are "light background," "high brightness," and "strong contrast."

[1358] The server then inputs the digital image along with the determined parameters into a generative AI model, which then performs image analysis and processing using libraries such as TensorFlow and PyTorch. This includes adjusting brightness, changing background colors, and enhancing contrast.

[1359] The server receives the electronic images processed by the generative AI model and stores them again in the data storage device. The user can log in to the system again and check the processed electronic images. The terminal displays the processed images to the user and provides a download function. The user can download the images as needed and use them in online meeting tools or email.

[1360] Specific examples

[1361] For example, a sales user (30 years old) logs in to the system and uploads three photos. The user enters their occupation as "sales," their position as "responsible," and their age as "30." The server stores this information in a data storage device and determines the parameters for "light background," "high brightness," and "strong contrast" based on the industry, position, and age information. The generative AI model processes the photos based on these settings, generating an image with, for example, increased brightness, a bright background, and enhanced facial contrast. The server then stores the processed electronic images in a data storage device, and the user can log in again to review the images and download them if necessary.

[1362] Prompt Sentence Examples

[1363] "Improve your sales profile photo. I have three photos. I'm 30 years old. Safely adjust the brightness, background, and contrast accordingly."

[1364] The system allows users to easily get the best profile picture possible, creating a professional impression in online meetings and emails.

[1365] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1366] Step 1: The user logs in to the system and accesses the photo upload screen. The terminal displays a file input field and provides an interface for the user to select a photo. When the user selects a photo and presses the "Upload" button, the terminal sends the photo data to the server. The input is the user's photo file, and the output is the transmission result to the server. The server validates the received photo and saves it in the data storage device.

[1367] Step 2: The user accesses a screen to input occupation, position, and age information. The terminal displays a form for inputting this information, allowing the user to enter data. The terminal sends the input information to the server. The input is occupation, position, and age information, and the output is the transmission result to the server. The server saves the received information in a data storage device.

[1368] Step 3: The server retrieves the user's photo and input information from the data storage device. Using SQL queries or similar, the server retrieves the stored photo and information on occupation, position, and age. The input is the stored data record, and the output is the retrieved data. The server determines the image processing parameters based on this information. For example, for a sales representative (age 30), the parameters set are "light background," "high brightness," and "strong contrast."

[1369] Step 4: The server inputs the determined image processing parameters and the user's photo into the generative AI model. The generative AI model analyzes and processes the photo based on these parameters. The input is the image processing parameters and photo data, and the output is the processed photo data. Specifically, the generative AI model adjusts brightness, changes the background color, and enhances contrast.

[1370] Step 5: The server receives the processed photo returned by the generative AI model and stores it in the data storage device. The server re-encodes the processed photo data, stores it in cloud storage, and adds its URL to the data record. The input is the processed photo data, and the output is the result of the storage completion.

[1371] Step 6: The user logs in to the system again to view the edited photo. The device requests the edited photo data from the server and displays it. The user can download the photo if needed. The input is the user request, and the output is the edited photo data. The device generates a download link, allowing the user to download the photo.

[1372] (Application example 1)

[1373] 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."

[1374] Conventional photo editing systems require specialized knowledge and highly accurate tools for users to edit their own photos optimally, and the process requires a lot of time and effort. Furthermore, they lack the functionality to automatically generate promotional images for use in physical stores, and creating them manually is time-consuming. Therefore, there was a demand for a system that could easily and quickly generate and provide optimal promotional images.

[1375] 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.

[1376] In this invention, the server includes: a means for users to upload their own photos; a means for users to input their industry, job title, and age; a means for the server to save these photos and input information in a database; a means for the server to determine image processing parameters based on the user's information; a means for an AI model to edit the photos based on these parameters; a means for the server to save the edited photos in a database and provide them to users; a means for users to check and download the edited photos; and a means for the AI ​​to generate optimal promotional images by users inputting their own photos and store information (industry, job title, age) and provide the promotional images to be displayed on smart displays in physical stores. This allows users to quickly and efficiently generate optimal promotional images without the need for specialized knowledge or tools, and to immediately use them in physical stores, etc.

[1377] "Server" means a computer system that receives, stores, processes, and analyzes data entered by users.

[1378] "User" refers to a person or organization that uses this system to upload their own photo, enter their industry, job title, and age, and obtain the most suitable edited photo.

[1379] "Photo Uploader" means the functionality or interface that allows a User to provide their photo to the System.

[1380] "Means for inputting industry, job title, and age" refers to the functions and interfaces that allow a user to provide information about their industry, job title, and age to the system.

[1381] "Image processing parameters" refer to adjustment elements such as brightness, background, and contrast required for processing a photograph.

[1382] An "AI model" is an artificial intelligence algorithm and system that analyzes and processes input data.

[1383] "Promotional images" are images used for promotional and advertising purposes, such as on smart displays in physical stores.

[1384] A "smart display" is an electronic display device such as digital signage that is used to provide information and display advertisements in stores, events, etc.

[1385] An "edited photo" is a photo after brightness, background, and contrast have been adjusted based on image processing parameters specified by the AI ​​model.

[1386] A "database" is a storage device or medium for systematically organizing and storing information within a system.

[1387] MODE FOR CARRYING OUT THE INVENTION

[1388] This system for implementing the invention allows users to upload their own photos and input their industry, job title, and age, and then AI generates and provides the most suitable image.The system can also automatically generate promotional images for smart displays in physical stores based on user input.

[1389] System configuration

[1390] 1. Photo upload function

[1391] The server provides a means for users to upload their own photos via their devices, which are then sent to the server and stored in a database.

[1392] 2. Input function for industry, job title, and age

[1393] Users have the means to input their industry, job title, and age through the terminal, and the input information is sent to the server and stored in a database.

[1394] 3. Image processing parameter determination function

[1395] The server determines image processing parameters (brightness, background, contrast, etc.) based on the user's industry, job title, and age information, which is obtained from a database.

[1396] 4. AI-based image analysis and processing functions

[1397] The server inputs the determined parameters and the photo into the AI ​​model and instructs it to analyze and process the image. The AI ​​model analyzes the image and performs optimal processing based on the parameters.

[1398] 5. Image provision function

[1399] The processed photos are stored on a server and can be accessed by users via their devices to view and download them.

[1400] Promotional images can also be provided for display on smart displays in physical stores.

[1401] Hardware and software used

[1402] 1. Server: Stores, processes, and analyzes data. For processing functions, we use cloud computing services such as Amazon Web Services (AWS).

[1403] 2. Device: Use an internet-enabled device such as a smartphone or tablet to upload photos and enter information.

[1404] 3. AI model: For image analysis and processing, we use machine learning frameworks such as TensorFlow and PyTorch, which allow us to properly analyze the input image and generate the optimal promotional image.

[1405] Examples and prompts

[1406] For example, suppose a 25-year-old salesperson working at an apparel store wants to generate promotional images for the store's smart displays. In this case, the user would follow the steps below:

[1407] 1. Users take a photo of themselves using their smartphone and upload it to the system.

[1408] 2. The user enters the industry as "apparel," the job title as "store clerk," and the age as "25."

[1409] 3. Based on the input information, the server determines that the brightness should be set to 1.2 times, the background to a fashion-themed image, and the contrast to 1.5 times.

[1410] 4. The AI ​​model runs these settings and generates the edited photo.

[1411] 5. The user can review the edited photo and download it to display on their smart display.

[1412] Example prompt sentence:

[1413] "Based on the photo uploaded by the user, the industry "Apparel", job title "Store Clerk", and age "25", set a bright background image and adjust the photo brightness by 1.2 times and the contrast by 1.5 times."

[1414] This makes it possible to quickly generate and use effective promotional images even in physical stores.

[1415] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1416] Step 1:

[1417] The user takes and uploads their own photo using the device. The device provides a photo upload interface and sends the photo selected by the user to the server. The input is the user's photo, and the output is a photo file stored on the server.

[1418] Step 2:

[1419] The user inputs their industry, job title, and age through the terminal. The terminal displays an input form for industry, job title, and age, and when the user enters the information, it sends the data to the server. The input is the user's industry, job title, and age information, and the output is that information saved on the server.

[1420] Step 3:

[1421] The server retrieves the user's photo and input information from the database. The server loads the necessary data into memory based on the saved photo file and input information. The input is the photo and input information from the database, and the output is the related data stored in memory.

[1422] Step 4:

[1423] The server determines image processing parameters (brightness, background, contrast, etc.) based on the user's industry, job title, and age information. The server calculates the parameters using pre-set rules and models. The input is the user's information, and the output is the determined image processing parameters.

[1424] Step 5:

[1425] The server inputs the determined parameters and photo into the AI ​​model and instructs it to analyze and process the image. The AI ​​model analyzes the image and performs optimal processing based on the parameters. The input is the processing parameters and photo file, and the output is the processed image data.

[1426] Step 6:

[1427] The server stores the processed photos in a database and provides them to the user. The processed images are stored on the server and can be accessed by the user through the system. The input is the processed image data, and the output is the processed image stored in the database.

[1428] Step 7:

[1429] The user checks the edited photo on their device and downloads it if necessary. The device displays the edited photo to the user and provides a download option. The input is the edited image retrieved from the database, and the output is an image file saved on the user's device.

[1430] These specific processing steps enable users to quickly and efficiently generate optimal promotional images without the need for specialized knowledge or tools, and to immediately use them in physical stores, etc.

[1431] 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.

[1432] The present invention is a system in which users not only upload their own photos and input their industry, job title, and age, but also recognize the user's emotions using an emotion engine, and AI generates the optimal image. The detailed configuration and processing flow of the system based on the present invention are described below.

[1433] System configuration

[1434] 1. Photo upload function

[1435] User: Logs into the system and uploads a photo of himself.

[1436] Terminal: Provides an interface for uploading photos and sends selected photos to the server.

[1437] Server: Receives uploaded photos and stores them in a database.

[1438] 2. Input function for industry, job title, and age

[1439] Device: Displays an input form for industry, job title, age, etc.

[1440] User: Enter the required information in the provided fields and submit.

[1441] Server: Receives the entered information and stores it in a database.

[1442] 3. Emotion recognition function using an emotion engine

[1443] Server: Inputs the uploaded photo into the emotion engine to recognize the user's emotion.

[1444] Emotion engine: Analyzes the user's facial expressions and quantifies their emotions, such as happiness, sadness, and anger.

[1445] 4. Image processing parameter determination function

[1446] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's industry, job title, age, and recognized emotion.

[1447] 5. AI-based image analysis and processing functions

[1448] Server: Inputs the determined parameters and photos into the AI ​​model and instructs it on image analysis and processing.

[1449] AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[1450] Server: Obtains the processed photos and stores them in a database.

[1451] 6. Image provision function

[1452] User: Log back into the system and access the confirmation page for the processed image.

[1453] On-device: The processed image is displayed to the user and a download function is provided.

[1454] Program processing flow

[1455] The program of this system proceeds as follows:

[1456] Specific examples

[1457] Example of a sales representative (30 years old)

[1458] 1. User: A sales person logs in to the system and uploads three photos. The user enters the industry as "Sales," the job title as "Responsible Person," and the age as "30."

[1459] 2. Server: Stores the photos and input information in a database.

[1460] 3. Server: The uploaded photo is sent to the emotion engine, where the emotion of joy is recognized.

[1461] 4. Server: Determines the parameters of "bright background," "high brightness," and "strong contrast" based on industry, job title, age, and perceived happiness.

[1462] 5. AI model: Analyzes the photo and performs processing based on the determined parameters, such as increasing the brightness of the photo, setting a bright background, and enhancing the contrast of the face.

[1463] 6. Server: Stores the processed photos in a database and provides them to users.

[1464] 7. User: Log back in to the system to check the edited photo and download it if necessary. Set the downloaded photo as an icon for online meeting tools or emails.

[1465] In this way, by combining emotion engines, the present invention realizes a system that automatically generates optimal images according to the user's emotions, and further contributes to improving the image of individuals and companies online.

[1466] The processing flow will be explained below.

[1467] Step 1:

[1468] A user logs into the system and accesses the photo upload page.

[1469] Step 2:

[1470] The device will display a photo upload interface, where users can click the file selection button and select up to three of their own photos.

[1471] Step 3:

[1472] The user selects a photo and presses the upload button.

[1473] Step 4:

[1474] The terminal transmits the selected photo file to the server.

[1475] Step 5:

[1476] The server analyzes the received photo data and verifies whether it has been uploaded correctly.

[1477] After the server verifies it, it stores the photo data in a database.

[1478] Step 6:

[1479] The device displays a form for entering industry, job title, and age.

[1480] Step 7:

[1481] The user enters the industry (e.g., sales), job title (e.g., person in charge), and age (e.g., 30 years old), and presses the send button.

[1482] Step 8:

[1483] The terminal transmits the input information to the server.

[1484] The server stores the received information in a database.

[1485] Step 9:

[1486] The server retrieves the user's photo and input information from the database.

[1487] Step 10:

[1488] The server inputs the uploaded photos into an emotion engine to recognize the user's emotions.

[1489] Step 11:

[1490] The emotion engine analyzes the user's facial expressions and quantifies the corresponding emotion from a range of emotions (e.g., joy, sadness, anger, etc.).

[1491] Step 12:

[1492] The server determines image processing parameters based on the user's industry, job title, age and recognized emotion.

[1493] Step 13:

[1494] The server inputs the determined parameters and photo data into the AI ​​model and instructs it on image analysis and processing.

[1495] Step 14:

[1496] The AI ​​model analyzes the photo and performs optimal processing based on the parameters (e.g., adjusting brightness, changing the background, adjusting contrast, etc.).

[1497] Step 15:

[1498] The server retrieves the processed photo data and stores it in a database.

[1499] Step 16:

[1500] The user logs back into the system and accesses the confirmation page for the processed image.

[1501] Step 17:

[1502] The device will then display the edited photo to the user and offer the option to download it.

[1503] Step 18:

[1504] Users can view the edited photos and download them if necessary.

[1505] Set the photos downloaded by the user as icons for online meeting tools and emails.

[1506] Example 2

[1507] 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."

[1508] In online communication and business, there is a demand for effective use of users' photos to improve the image of individuals and companies. However, it is difficult for users to create the optimal image on their own, requiring specialized knowledge and skills. Furthermore, conventional image processing tools have the problem of making it difficult to create the optimal image that reflects the user's emotion or occupation.

[1509] 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 a means for a user to upload his / her own image, a means for a user to input his / her occupation, role, and age, and a means for inputting the user's image into an emotion engine and recognizing emotions. This makes it possible to automatically generate and provide an optimal image according to the user's emotion and occupation.

[1510] "User" refers to an individual who logs into the system, uploads their photo, and enters the required information.

[1511] "Images" refers to visual data such as photographs or drawings uploaded by users.

[1512] "Occupation" refers to the industry or occupation to which the user belongs.

[1513] "Role" refers to the position or title a user holds within a profession.

[1514] "Age" refers to the number of years calculated from the user's date of birth.

[1515] "Server" refers to a computer system that receives photos and information from users, stores them in a database, and performs various processing.

[1516] An "emotion engine" refers to software or algorithms that analyze a user's image and quantify their emotions.

[1517] "Image processing parameters" refer to adjustment values ​​such as image brightness, background color, and contrast that are determined based on the user's emotions and occupation.

[1518] A "generative AI model" refers to an artificial intelligence system that analyzes and processes images based on specific parameters.

[1519] "Database" refers to a collection of digital data for storing user photos and information.

[1520] "Online communication tools" refers to software and services that allow users to communicate with each other via the Internet.

[1521] The present invention is a system in which users not only upload their own images and input their occupation, role, and age, but also recognize the user's emotions using an emotion engine, and a generative AI model generates an optimal image. The detailed configuration and processing flow of the system based on the present invention are described below.

[1522] System configuration

[1523] 1. Photo upload function

[1524] User: Log in to the system and upload their own images. Specifically, the user enters their username and password on the login screen, and after logging in, they are directed to the photo upload screen. The photos are uploaded through the file selection interface.

[1525] Terminal: Provides an interface for uploading photos and sends selected photos to the server. This interface uses HTML and JavaScript.

[1526] Server: Receives uploaded photos and stores them in a database. Photo data is stored in a MySQL database using a Python script.

[1527] 2. Occupation, role, and age input function

[1528] Terminal: Displays an input form for occupation, role, age, etc. This form is also built using HTML and JavaScript.

[1529] User: Enter the required information in the provided input field and submit. The entered information is sent from the device to the server.

[1530] Server: Stores the entered information in a database, also done using a Python script.

[1531] 3. Emotion recognition function using an emotion engine

[1532] Server: The uploaded photo is input into the emotion engine to recognize the user's emotions. In this case, we use Microsoft's Azure Face API as the emotion engine.

[1533] Emotion engine: Analyzes the user's facial expressions and quantifies their emotions. For example, it recognizes emotions such as joy, sadness, and anger and returns them as numerical data.

[1534] 4. Image processing parameter determination function

[1535] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the user's occupation, role, age, and recognized emotion. This process is performed using Python scripts and machine learning libraries.

[1536] 5. AI-based image analysis and processing functions

[1537] Server: The determined parameters and photos are input into the generative AI model, and instructions are given for image analysis and processing. The generative AI model uses libraries such as TensorFlow and PyTorch.

[1538] Generative AI model: Analyzes the input photo and performs optimal processing based on the parameters (adjusting brightness, changing the background, adjusting contrast, etc.).

[1539] Server: Stores the processed photos in a database, also done using a Python script.

[1540] 6. Image provision function

[1541] User: Log in to the system again and access the confirmation page for the processed image. After logging in again, you will be able to view and download the processed image.

[1542] On the device: The processed image is displayed to the user and a download function is provided. Image display and download links are provided using HTML and JavaScript.

[1543] Specific examples

[1544] Example of a sales representative (30 years old)

[1545] 1. User: A sales person logs in to the system, uploads three photos, and enters their occupation as "Sales," role as "Responsible Person," and age as "30."

[1546] 2. Server: Stores the photos and input information in a database.

[1547] 3. Server: The uploaded photo is sent to the emotion engine, where the emotion of joy is recognized.

[1548] 4. Server: Determines the parameters of "bright background", "high brightness" and "high contrast" based on occupation, role, age and perceived happiness.

[1549] 5. Generative AI model: Analyzes the photo and performs processing based on determined parameters, such as increasing the brightness of the photo, setting a bright background, and enhancing the contrast of the face.

[1550] 6. Server: Stores the processed photos in a database and provides them to users.

[1551] 7. User: Log back in to the system to check the edited photo, download it if necessary, and set the downloaded photo as an icon for online communication tools or emails.

[1552] Prompt Sentence Examples

[1553] Here is an example of a prompt to input to a generative AI model:

[1554] "A 30-year-old salesperson has uploaded three photos with the emotion Happy. For these photos, we want to increase the brightness, add a lighter background, and increase the contrast of the face."

[1555] In this way, by combining an emotion engine and a generative AI model, the present invention automatically generates and provides optimal images according to the user's emotions and occupation, thereby contributing to improving the online image of individuals and companies.

[1556] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1557] Step 1:

[1558] A user logs in to the system. They enter their username and password on the login screen and click "Login". The server authenticates the entered username and password, and if authentication is successful, displays the homepage. Specifically, a Python framework (e.g., Django) is used for user authentication. The input is the username and password, and the output is the login status (success or failure).

[1559] Step 2:

[1560] After logging in, the user uploads their own image. The device displays an interface for uploading photos. The user selects a photo and clicks the upload button. The device sends the selected photo to the server via an AJAX request. The server stores the received photo in a MySQL database. The input is the selected image file, and the output is a message that the image was successfully saved to the database.

[1561] Step 3:

[1562] The user enters their occupation, role, and age. The terminal displays an input form for occupation, role, age, etc. The user enters this information and clicks the submit button. The terminal sends the input information to the server via an AJAX request. The server receives the input information and saves it in a MySQL database. The input is text data for occupation, role, and age, and the output is a message that the information was successfully saved to the database.

[1563] Step 4:

[1564] The server sends the uploaded photo to the emotion engine to recognize the user's emotion. The photo data is sent to the emotion engine (for example, Azure Face API) to obtain emotion data. Specifically, the server calls the API, and the emotion engine analyzes the photo and returns emotion data. The input is photo data, and the output is emotion data (numeric values ​​such as joy, sadness, anger, etc.).

[1565] Step 5:

[1566] The server determines image processing parameters based on the user's occupation, role, age, and recognized emotion. A Python script is used to analyze the input information and emotion data, and set image processing parameters such as "brightness," "background color," and "contrast." The input is occupation, role, age, and emotion data, and the output is image processing parameters.

[1567] Step 6:

[1568] The server inputs the determined parameters and the photo into the generative AI model and instructs it to analyze and process the image. The generative AI model (such as TensorFlow or PyTorch) analyzes the photo data and processes the image based on the parameters. The input is the photo data and image processing parameters, and the output is the processed photo data.

[1569] Step 7:

[1570] The server saves the processed photo to the database. Using a Python script, the processed photo data is stored in the MySQL database. The input is the processed photo data, and the output is a message that the data was successfully saved to the database.

[1571] Step 8:

[1572] The user re-logins into the system and accesses the confirmation page for the processed image. The user logs in again and is directed to a dedicated confirmation page. The terminal displays the processed image to the user and provides a downloadable link. The input is the user's re-login information, and the output is the processed image and download link displayed on the confirmation page.

[1573] (Application example 2)

[1574] 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."

[1575] Conventional advertising visual generation systems have difficulty generating optimal images based on the target user's emotions and profile. Furthermore, new technology is needed to enable advertising agencies to quickly create effective advertising visuals that meet their clients' needs. Furthermore, if the generated visuals do not match the target user's emotions, the effectiveness of the advertisement decreases.

[1576] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to upload their own photo, means for the user to input their industry, job title, and age, means for the server to save these photos and input information in a database, means for the server to recognize the user's emotion from the uploaded photo using an emotion engine, means for the server to determine image processing parameters based on the user's information and the recognized emotion, means for the AI ​​model to edit the photo based on these parameters, means for the server to save the edited photo in a database and provide it to the user, and means for the user to check and download the edited photo. This enables the automatic generation of optimal advertising visuals based on the emotions and profile of target users.

[1577] "User" means any person or entity using the system who uploads photos and enters required information.

[1578] "Client" refers to an entity, such as an advertising agency or company, that uses the system to generate advertising visuals for target users.

[1579] "Target users" refers to the specific people or customer groups for whom advertising visuals are created.

[1580] "Photos" are image files of users or target users, and are digital data uploaded to the system.

[1581] "Industry" refers to the occupation or industry to which the user or target user belongs.

[1582] "Job title" is information that refers to the job position or role of the user or target user.

[1583] "Age" refers to the numerical stage of development calculated from the user's or target user's year of birth.

[1584] A "server" is a computer system responsible for storing, processing, and managing data.

[1585] A "database" is a system for managing and storing data such as photographs, input information, and generated advertising visuals.

[1586] An "emotion engine" is a machine learning model or algorithm that analyzes uploaded photos and quantifies the emotions of users and target users.

[1587] "Image processing parameters" refers to settings and adjustments related to image processing, such as brightness, background color, and contrast of a photograph.

[1588] An "AI model" is a machine learning model used to process and generate images based on input data.

[1589] "Processed photos" are photographic data that have been processed according to image processing parameters specified by the AI ​​model.

[1590] "Advertising visuals" are visual advertising materials created to help clients effectively approach their target users.

[1591] This invention is a system that automatically generates optimal advertising visuals based on user emotions and profiles, enabling clients to quickly and easily create effective advertisements for target users. This system is composed of the following steps, hardware, and software.

[1592] System configuration

[1593] 1. User and Client Account Management

[1594] Terminal: Provides an interface for account creation and login.

[1595] Server: Manage account information using Firebase Authentication.

[1596] 2. Targeted user photo upload feature

[1597] Terminal: Provides a UI for clients to upload photos of target users.

[1598] Server: Save the uploaded photos to Firebase Storage.

[1599] 3. Profile data entry function

[1600] Terminal: Provides a form where clients can enter the industry, job title, and age of their target users.

[1601] Server: Save the entered data to Firebase Firestore.

[1602] 4. Emotion recognition function

[1603] Server: Sends the uploaded photo to Google Cloud Vision API and obtains the sentiment analysis results.

[1604] Emotion engine: Analyzes the user's facial expressions and quantifies emotions (e.g., joy, sadness, anger, etc.).

[1605] 5. Image generation function

[1606] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on the emotion engine results and profile data.

[1607] Server and AI model: Using TensorFlow, the target user's photo is processed based on the determined parameters.

[1608] AI Model: Uses a generative AI model to create optimal ad visuals based on the prompt you provide.

[1609] 6. Image confirmation and download function

[1610] Terminal: Provides a UI where clients can view and download the generated ad visuals.

[1611] Server: Stores the generated advertising visuals in a database and provides them to clients.

[1612] Specific examples

[1613] For example, to generate advertising visuals for a 30-year-old salesperson, the client uploads a photo and profile of the salesperson (industry: sales, job title: responsible, age: 30). The system provides the following prompt sentence to the generative AI model:

[1614] Prompt Sentence Examples

[1615] Please generate the best advertising visual for a 30-year-old salesperson. The emotion of the photo is recognized as "joy." Please use a light background, high brightness, and strong contrast settings.

[1616] Hardware and software used

[1617] Firebase Authentication: A platform for managing authentication.

[1618] Firebase Firestore: A cloud database for storing and managing data.

[1619] Firebase Storage: Cloud storage for saving photos.

[1620] Google Cloud Vision API: A cloud-based image analysis service for emotion recognition.

[1621] TensorFlow: A platform for image generation and processing using machine learning models.

[1622] React Native: A framework used to build user interfaces.

[1623] In this way, the system of the present invention combines an emotion engine and a generative AI model to automatically generate optimal advertising visuals based on the emotions and profiles of target users, enabling clients to quickly create effective advertising visuals and maximize marketing effectiveness.

[1624] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1625] Step 1:

[1626] Terminal: The client logs in to the system. The client's authentication information (username, password) is entered and authentication is performed using Firebase Authentication. If authentication is successful, the client's account information is obtained and the system proceeds to the next step.

[1627] Step 2:

[1628] Device: After logging in, the client uploads a photo of the target user. The client selects the photo file using the device's UI and clicks the upload button. Once the photo file is selected, the device sends the photo data to Firebase Storage.

[1629] Step 3:

[1630] Server: Retrieve the photo data stored in Firebase Storage and save it to the database. The server saves the photo file URL and metadata such as the upload date and time to Firebase Firestore. Once saving is complete, proceed to the next step.

[1631] Step 4:

[1632] Terminal: Provides a form for entering profile information (industry, job title, age) of the target user. The client enters information in each field and clicks the submit button. The entered information is sent from the terminal to the server.

[1633] Step 5:

[1634] Server: Receives the profile information sent from the client and saves it to the database. The profile information is stored in Firebase Firestore and associated with the photo data. Once saved, proceed to the next step.

[1635] Step 6:

[1636] Server: Sends photo data to the Google Cloud Vision API and performs emotion recognition. Receives emotion data (e.g., joy, sadness, anger, etc.) returned from the API. Analyzes and quantifies the received emotion data. Stores the analysis results in a database and proceeds to the next step.

[1637] Step 7:

[1638] Server: Determines image processing parameters (brightness, background color, contrast, etc.) based on profile information and emotion data. Sets these parameters and prepares them as input data for the AI ​​model.

[1639] Step 8:

[1640] Server and AI model: Using TensorFlow, the photo is processed based on the set image processing parameters. A specific prompt is input to the generation AI model. For example, the following prompt is used to generate an image:

[1641] Please generate the best advertising visual for a 30-year-old salesperson. The emotion of the photo is recognized as "joy." Please use a light background, high brightness, and strong contrast settings.

[1642] The AI ​​model processes the photo according to the prompt, generates the optimal advertising visual, and returns the generated image to the server.

[1643] Step 9:

[1644] Server: Saves the generated ad visuals to the database. Once saved, sends a notification to the client to let them know the image has been generated.

[1645] Step 10:

[1646] Terminal: The client accesses the UI to view the generated ad visuals. The generated images are displayed on the terminal, and the client can view them and download them if necessary.

[1647] By following these steps, clients can automatically generate optimal advertising visuals based on the emotions and profiles of their target users, thereby enhancing their marketing effectiveness.

[1648] 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.

[1649] 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.

[1650] 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.

[1651] 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.

[1652] 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.

[1653] 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.

[1654] 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).

[1655] 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.

[1656] 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."

[1657] 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.

[1658] 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).

[1659] 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.

[1660] 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.

[1661] 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.

[1662] 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.

[1663] 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.

[1664] 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.

[1665] 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.

[1666] 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.

[1667] 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.

[1668] 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.

[1669] The following is further disclosed regarding the above embodiment.

[1670] (Claim 1)

[1671] a means for users to upload their own photos;

[1672] A means for users to enter their industry, job title, and age;

[1673] a means for the server to store these photographs and input information in a database;

[1674] A means for the server to determine image processing parameters based on user information;

[1675] How the AI ​​model processes photos based on these parameters;

[1676] The server stores the processed photos in a database and provides them to users.

[1677] A way for users to view and download the edited photos,

[1678] A system including:

[1679] (Claim 2)

[1680] 10. The system of claim 1, wherein the AI ​​model enhances the user's photo by adjusting brightness, background color, and contrast.

[1681] (Claim 3)

[1682] The system of claim 1, wherein a user can set the downloaded edited photo as an icon for an online meeting tool or email.

[1683] "Example 1"

[1684] (Claim 1)

[1685] a means for users to upload electronic images of themselves;

[1686] a means for the user to input occupation, job title, and age;

[1687] means for the server to store these electronic images and input information in a data storage device;

[1688] A means for the server to determine image processing parameters based on user information;

[1689] a means for the generative AI model to process the electronic image based on these parameters; and

[1690] means for the server to store the processed electronic image in a data storage device and provide it to the user;

[1691] A means by which users can review and download the processed electronic images;

[1692] A system including:

[1693] (Claim 2)

[1694] 10. The system of claim 1, wherein the generative AI model enhances the user's electronic image by adjusting brightness, background color, and contrast.

[1695] (Claim 3)

[1696] The system of claim 1, wherein the user can set the downloaded processed electronic image as an icon for an online meeting tool or email.

[1697] "Application Example 1"

[1698] (Claim 1)

[1699] a means for users to upload their own photos;

[1700] A means for users to enter their industry, job title, and age;

[1701] a means for the server to store these photographs and input information in a database;

[1702] A means for the server to determine image processing parameters based on user information;

[1703] How the AI ​​model processes photos based on these parameters;

[1704] The server stores the processed photos in a database and provides them to users.

[1705] A way for users to view and download the edited photos,

[1706] A means for users to input their own photos and store information (industry, job title, age) and have AI generate optimal promotional images to be displayed on smart displays in physical stores;

[1707] A system including:

[1708] (Claim 2)

[1709] The system of claim 1, wherein the AI ​​model enhances the user's photos by adjusting brightness, background, and contrast, and generates promotional images optimized for smart displays in physical stores.

[1710] (Claim 3)

[1711] The system according to claim 1 allows users to set the edited photos they download as icons for online meeting tools or emails, and also allows them to be used as promotional materials for physical stores.

[1712] "Example 2: Combining Emotion Engines"

[1713] (Claim 1)

[1714] a means for users to upload images of themselves;

[1715] a means for the user to input occupation, role, and age;

[1716] a means for the server to store these images and input information in a database;

[1717] A means for the server to input the user's image into an emotion engine and recognize emotions;

[1718] A means for the server to determine image processing parameters based on the user's information and the recognized emotion;

[1719] A means by which the generative AI model processes the image based on these parameters; and

[1720] The server stores the processed images in a database and provides them to users.

[1721] A way for users to view and download the processed images,

[1722] A system including:

[1723] (Claim 2)

[1724] 10. The system of claim 1, wherein the generative AI model enhances the user's image by adjusting brightness, background color, and contrast.

[1725] (Claim 3)

[1726] The system of claim 1, wherein the user can set the downloaded processed image as an icon for an online communication tool or email.

[1727] "Application example 2 when combining emotion engines"

[1728] (Claim 1)

[1729] a means for users to upload their own photos;

[1730] A means for users to enter their industry, job title, and age;

[1731] a means for the server to store these photographs and input information in a database;

[1732] A means for the server to recognize a user's emotion from the uploaded photo using an emotion engine;

[1733] means for the server to determine image processing parameters based on the user's information and the recognized emotion;

[1734] How the AI ​​model processes photos based on these parameters;

[1735] The server stores the processed photos in a database and provides them to users.

[1736] A way for users to view and download the edited photos,

[1737] A system including:

[1738] (Claim 2)

[1739] 10. The system of claim 1, wherein the AI ​​model enhances the user's photo by adjusting brightness, background color, and contrast.

[1740] (Claim 3)

[1741] The system according to claim 1, wherein a client uploads photos of target users and automatically generates optimal advertising visuals based on profile information and emotional data. [Explanation of symbols]

[1742] 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 users to upload their own photos; A means for users to enter their industry, job title, and age; a means for the server to store these photographs and input information in a database; A means for the server to determine image processing parameters based on user information; How the AI ​​model processes photos based on these parameters; The server stores the processed photos in a database and provides them to users. A way for users to view and download the edited photos, A system including:

2. 10. The system of claim 1, wherein the AI ​​model enhances the user's photo by adjusting brightness, background color, and contrast.

3. The system according to claim 1, wherein the user can set the downloaded processed photo as an icon for an online meeting tool or email.

Images