System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving image and preference settings from a user; means for analyzing the received image to extract features such as colors, shapes, and motifs; means for using a AI model to generate a nail design based on the extracted features; and means for providing the generated nail design 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] This invention relates to the creation of nail designs based on favorite idols or characters. With existing nail design services, it can be difficult to find a manicurist willing to work with you to create a specific design, and specialized manicurists can be expensive. Other issues include the time required to coordinate designs with a manicurist beforehand, and the difficulty of expressing dissatisfaction with the finished product. Therefore, there is a need for a way for users to easily enjoy their favorite idol nails. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for receiving image data and user preferences from a user, a means for analyzing the received image data to extract features such as color, shape, and motif, a means for using an AI model to generate nail designs based on the extracted features, and a means for providing the generated nail designs to the user. The system also includes a means for generating different nail designs in response to a regeneration request and providing them to the user again, and a means for saving the generated nail designs and providing them in a format that can be output for use at a nail salon or for self-nail care. This allows users to easily enjoy their favorite nails and reduces the effort and cost of design negotiations with a manicurist.

[0006] A "user" is an individual or entity who uses the system to create nail designs of their favorite idols or characters.

[0007] "Image data" refers to visual information such as photos and illustrations of favorite idols and characters uploaded by users.

[0008] "Preferences" are personal requirements and conditions such as the color, style, and simplicity of the design desired by the user.

[0009] "Means" is a general term for methods or devices used to achieve a specific purpose.

[0010] "Means for receiving" refers to the functions or processes by which the system receives image data and preference settings from the user.

[0011] "Means of analysis" refers to the functions and processes for extracting features such as color, shape, and motif from image data.

[0012] "Means for extracting features" refers to functions and processes for identifying design elements such as color, shape, and motif obtained through image analysis.

[0013] An "AI model" is a model that is used to automatically generate specific designs based on artificial intelligence technology.

[0014] "Means of generation" refers to the functions and processes for automatically creating nail designs based on features extracted using an AI model.

[0015] The "means for providing" refers to a function or process for displaying or providing the generated nail design to the user.

[0016] A "regeneration request" is a request made by a user when they wish to generate a different design.

[0017] The "means for saving" refers to a function or process for recording and saving the generated nail design in a data format.

[0018] An "outputtable format" is a data format (e.g., PNG, JPEG, PDF, etc.) suitable for use in a nail salon or for self-nail design. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] The system of the present invention allows users to easily and conveniently enjoy nail designs of their favorite idols or characters. The system automatically generates and provides nail designs using an AI model when the user provides the system with specific image data and preferred settings.

[0041] System configuration

[0042] The system consists of the following main components:

[0043] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0044] Server: A cloud-based server system containing the AI ​​model

[0045] Program processing (natural language)

[0046] The system operates in the following steps:

[0047] 1. Receiving user input data

[0048] The user launches the nail design generation application on the device.

[0049] An interface will appear that allows users to upload an image of their favorite character.

[0050] Users upload image data and set preferences such as the color and style of the nail design they want.

[0051] 2. Sending input data

[0052] The device sends the image data and user preferences to a server, usually over the Internet.

[0053] 3. Image analysis and feature extraction

[0054] The server then enters the phase of analyzing the received image data.

[0055] The server's image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs.

[0056] 4. Nail design generation

[0057] The AI ​​model on the server generates multiple nail designs based on the extracted features and the user's preferences.

[0058] The generated designs look generic at first glance, but upon closer inspection you'll see that motifs of your favorite character have been cleverly incorporated.

[0059] 5. Providing the generated results

[0060] The server returns the generated nail designs to the terminal.

[0061] The device displays a list of nail designs to the user, which is the first time the user sees the designs.

[0062] 6. User Verification and Regeneration

[0063] Users will have the ability to review the generated design and request a regeneration if necessary.

[0064] If the user wishes to regenerate, a request to generate a new design is sent to the server.

[0065] 7. Final design and output

[0066] Users choose the design they like.

[0067] The device will then present you with the option to download the selected design in a format suitable for taking to a nail salon or for self-nail application.

[0068] The user saves the final design data.

[0069] Specific examples

[0070] For example, consider a case where a user uploads an image of "Idol X" and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "Pastel" in the color settings. The system receives the image data and performs image analysis on the server to extract specific colors and symbols. The AI ​​model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X."

[0071] In this way, the system of the present invention allows users to easily enjoy unique and personalized nail designs.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] The user launches the nail design generation application on their device. When the application is launched, a user interface appears, presenting input fields for uploading an image of their favorite character and setting options.

[0075] Step 2:

[0076] Users upload an image of their favorite character to their device. They then set their preferences for the nail design, such as color, style, and level of simplicity. This input data (image data and preference settings) is used as the initial data for the next step.

[0077] Step 3:

[0078] The device sends the image data and user preferences as data packets to a server, typically via secure internet communication.

[0079] Step 4:

[0080] The server receives the data packets sent from the device, and the received image data and preference settings are passed on to the next analysis process.

[0081] Step 5:

[0082] The server launches an image analysis module to analyze the image data. The image analysis module uses machine learning algorithms and image recognition technology to extract features such as color, shape, and motif.

[0083] Step 6:

[0084] The server inputs the extracted feature data, such as color, shape, and motif, into a generative AI model. The generative AI model generates multiple nail designs based on this feature data and the user's preferences. The generated designs are set up so that, upon closer inspection, the motif of the user's favorite idol is hidden.

[0085] Step 7:

[0086] The server sends multiple nail designs generated by the generative AI model to the device as data packets, in a format that can be viewed by the user.

[0087] Step 8:

[0088] The device displays the received nail design data in a list format to the user, allowing the user to compare and check multiple designs from the list.

[0089] Step 9:

[0090] The user checks the generated design and requests regeneration if necessary. The regeneration request is sent to the server in the form of another design being generated.

[0091] Step 10:

[0092] The server receives the regeneration request and runs the process again to generate a new design. Once the new design is generated, it sends the data back to the device and redisplays it.

[0093] Step 11:

[0094] The user selects the final design they like and downloads it using the appropriate save option displayed on their device.

[0095] Step 12:

[0096] The device saves the selected nail design in a format for download (e.g. PNG, JPEG, PDF, etc.) The saved design data can be used to take to a nail salon or as a guide for self-nail design.

[0097] In this way, each step is tailored to the user's preferences and goes through a process to automatically generate and provide top-quality nail designs.

[0098] Example 1

[0099] 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."

[0100] The problem that this invention aims to solve is to provide a system that allows users to easily enjoy unique and personalized nail designs that incorporate elements of their favorite idols or characters, and also to provide a highly convenient system that can respond to changes in users' preferences and additional requests, and has regeneration functions and flexibility in saving and outputting.

[0101] 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.

[0102] In this invention, the server includes means for receiving image data and preference settings from a user, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using a generative AI model to generate nail designs based on the extracted features, means for inputting a prompt to the generative AI model, means for providing the generated nail designs to the user, means for generating different nail designs in response to a regeneration request and providing them again to the user, and means for saving the generated nail designs and providing them in a format that can be output. This allows users to easily generate and regenerate personalized nail designs incorporating elements of their favorite idols, and further save and output them.

[0103] "Image data" refers to visual information such as photographs and illustrations uploaded by users.

[0104] "Preference settings" refers to information about individual preferences, such as colors and design styles, specified by the user.

[0105] "Means for extracting features" refers to technology that uses AI models and algorithms to analyze and extract features such as color, shape, and motifs from image data.

[0106] A "generative AI model" refers to an artificial intelligence model that generates new nail designs based on extracted features and user preferences.

[0107] A "prompt sentence" refers to an input sentence that provides specific instructions or conditions to a generative AI model.

[0108] "Regeneration Request" refers to a request to generate a new design when a user is not satisfied with an existing design.

[0109] "Outputable format" means saving the generated nail design and providing it in a printable format (e.g. PNG, JPEG) for use in a nail salon or for self-nail design.

[0110] "Device" refers to an electronic device used by a user, such as a desktop computer, laptop, tablet, or smartphone.

[0111] "Server" refers to the computer system on which the cloud-based system, including the AI ​​model, runs.

[0112] The present invention is a system that allows users to easily create nail designs incorporating elements of their favorite idols or characters. The system includes a process in which a user provides specific image data and preferred settings, and an AI model is used to automatically generate and provide nail designs.

[0113] System configuration

[0114] The system consists of the following main components:

[0115] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0116] Server: A cloud-based server system containing the AI ​​model

[0117] Program processing

[0118] The program of this system operates as follows.

[0119] Receiving user input data

[0120] The user launches the nail design generation application on their device. The application displays an interface for uploading an image of their favorite character. The user uploads the image data and sets preferences such as the color and style of the desired nail design.

[0121] Sending input data

[0122] The device sends the image data and user preferences to a server, usually over the Internet.

[0123] Image analysis and feature extraction

[0124] The server then enters the analysis phase of the received image data. The server's image analysis module analyzes the image data and uses deep learning technology to extract features such as color, shape, and unique motifs.

[0125] Nail design generation

[0126] The generative AI model on the server generates multiple nail designs based on the extracted features and the user's preferences. Specifically, the extracted data is used as a prompt. For example, a prompt could be, "Generate a pastel-toned nail design incorporating the colors and motifs of idol X."

[0127] Providing generated results

[0128] The server returns the generated nail designs to the terminal, which displays the nail designs to the user in a list format, allowing the user to confirm each design.

[0129] Verify and regenerate users

[0130] The user is given the ability to review the generated design and request a regeneration if necessary, and the server will generate a new design upon request.

[0131] Final design decision and output

[0132] The user selects a design they like. The device displays an option to download the selected design in a format suitable for taking to a nail salon or for self-nail care. The user saves the final design data.

[0133] Specific example explanation

[0134] For example, consider a case where a user uploads an image of "Idol X" and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "Pastel" in the color settings. The system receives the image data and performs image analysis on the server to extract specific colors and symbols. The generative AI model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X."

[0135] Prompt Sentence Examples

[0136] "Create a pastel-colored nail design based on a photo of idol X. Subtly incorporate motifs of your favorite idol into the design."

[0137] In this way, the system of the present invention allows users to easily enjoy unique and personalized nail designs.

[0138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0139] Step 1:

[0140] The user launches the nail design generation application on their device. The application displays an interface for uploading an image of their favorite character. The user taps the "Upload Image" button and selects an image of their favorite character from their gallery. Options for color and style selection are then displayed, allowing the user to make the settings.

[0141] Input: User-selected image data and preferred settings (color tone, style).

[0142] Output: Send the prepared image data and your preferred settings to the server.

[0143] Step 2:

[0144] The device sends the image data and preferred settings entered by the user to a server, usually over the Internet. When the user taps the "Send" button, an app on the device consolidates the data and sends it over the Internet to the server.

[0145] Input: Ready image data and your preferred settings.

[0146] Output: Data sent to server completed.

[0147] Step 3:

[0148] The server then enters the analysis phase of the received image data. The server's image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs. Specifically, it uses a deep learning model to extract features such as color and shape.

[0149] Input: Image data received by the server.

[0150] Output: Data with extracted features such as color, shape, and motif.

[0151] Step 4:

[0152] The server-based generative AI model generates multiple nail designs based on the extracted features and the user's preferences, using the extracted data as prompts, such as "Generate a pastel nail design incorporating the colors and motifs of idol X."

[0153] Input: Parsed feature data and user preference data.

[0154] Output: Generated multiple nail design data.

[0155] Step 5:

[0156] The server sends the generated nail designs back to the device. The device application receives this data and displays a list-style design selection screen on the GUI. The user can swipe to view multiple designs.

[0157] Input: Each generated nail design data.

[0158] Output: Multiple nail designs displayed on the user's device.

[0159] Step 6:

[0160] The user can review the generated design and request a regeneration if necessary. The regeneration request is sent to the server and the process of generating a new design is repeated. When the user taps the "Regenerate" button, the request is sent to the server.

[0161] Input: The user's regeneration request.

[0162] Output: Generation and presentation of new nail design data.

[0163] Step 7:

[0164] The user selects a design they like. The device displays an option to download the selected design in a format suitable for taking to a nail salon or for self-nail care. When the user taps the "Download" button, the device saves the design data.

[0165] Input: Selected nail design.

[0166] Output: The final nail design data saved on your device.

[0167] (Application example 1)

[0168] 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."

[0169] The present invention relates to a system that allows users to easily create and visually confirm individual nail designs based on their favorite characters or idols. Conventional nail design creation methods have faced challenges such as communication gaps between nail technicians and users, and the difficulty of reviewing designs in real time. Additionally, there is a lack of means for customers to intuitively understand and adjust specific designs.

[0170] 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.

[0171] In this invention, the server includes means for receiving image data and preference settings from a user, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using a generative AI model to generate a nail design based on the extracted features, means for providing the generated nail design to the user, and means for displaying the generated nail design in real time through the smart glasses, thereby enabling the user to check the generated nail design in real time through the smart glasses and make adjustments in collaboration with the manicurist.

[0172] "User" means an individual who uses the system to create and review nail designs.

[0173] "Image data" refers to image files of favorite characters, idols, etc. provided by users.

[0174] "Preference settings" is information that indicates specific design requests, such as the color tone and style of the nail design desired by the user.

[0175] "Characteristics such as color, shape, and motif" are visual features analyzed from image data and serve as materials for nail design.

[0176] A "generative AI model" is an artificial intelligence model that automatically generates nail designs based on image data and the user's preferences.

[0177] "Smart glasses" are wearable devices that are glasses-type devices equipped with a display that can display information in real time.

[0178] "Real-time" is a term that refers to processing and reactions occurring almost immediately, with results being displayed immediately.

[0179] A "regeneration request" is an instruction to request the AI ​​model to generate a new design when the user is dissatisfied with the existing nail design or wants a new design.

[0180] The system of the present invention allows users to create and view their favorite nail designs in real time. The system is configured using a user terminal, a server, and smart glasses.

[0181] System configuration

[0182] 1. User Device

[0183] User devices include smartphones, tablets, desktop computers, and laptops.

[0184] It provides an interface for users to input image data and preference settings.

[0185] 2. Server

[0186] The cloud-based server analyzes the received image data and generates nail designs using a generative AI model.

[0187] The server has the ability to extract features such as color, shape, and motif based on the received image data and user preferences.

[0188] After feature extraction, the generative AI model automatically generates multiple nail designs.

[0189] Generated nail designs can also be regenerated upon request, allowing you to regenerate different designs.

[0190] 3. Smart Glasses

[0191] The smart glasses include a display that displays the generated nail designs to the user in real time.

[0192] Users can check the nail design generated through the smart glasses by overlaying it on the image of their hands.

[0193] Program processing (natural language)

[0194] The user launches a nail design generation application on their device. They upload image data of their favorite character or idol and select their preferred color and style. The device then sends this data to the server. The server analyzes the image, extracts features, and generates a nail design using a generative AI model. The generated nail design is sent back from the server to the device and simultaneously displayed on the smart glasses. The user can view the design in real time through the smart glasses and make any adjustments in consultation with the manicurist.

[0195] Technology and hardware used

[0196] AI models: Machine learning frameworks such as TensorFlow and PyTorch

[0197] Cloud services: AWS, Google Cloud, Microsoft Azure, etc.

[0198] Smart glasses: Google Glass, Microsoft HoloLens, etc.

[0199] User devices: iOS, Android, Windows, macOS

[0200] Specific examples

[0201] For example, consider the case where a user uploads an image of their favorite character, "Idol X," and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "pastel" in the color setting. The server receives the image data, and the AI ​​model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X." The generated nail design is displayed in real time on the user's hand via smart glasses.

[0202] Prompt Sentence Examples

[0203] Upload an image of "Idol X" and generate a nail design with a pastel design.

[0204] In this way, the system of the present invention allows users to create and check nail designs easily and intuitively.

[0205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0206] Step 1:

[0207] A user launches a nail design generation application on their device. They upload an image of their favorite character or idol and input their preferred settings (e.g., color tone and style). The device then receives and temporarily stores the image data and preferred settings.

[0208] Step 2:

[0209] The device sends the image data and user preferences entered by the user to the server. This communication is typically over the Internet. The device sends the uploaded image data and user preferences as an HTTP request.

[0210] Step 3:

[0211] The server analyzes the image data it receives and extracts features such as color, shape, and motif. The server's image analysis module applies an image processing algorithm (e.g., CNN) to the received image data, converts the extracted features into an internal format, and saves them.

[0212] Input: Image data received by the server

[0213] Output: Extracted feature data

[0214] Step 4:

[0215] The server generates nail designs using a generative AI model based on the extracted feature data and the user's preference settings. The AI ​​model (e.g., using TensorFlow or PyTorch) receives the features and preference settings as prompts and generates nail design images.

[0216] Input: extracted feature data and preference settings

[0217] Output: Generated nail design

[0218] Step 5:

[0219] The server returns the generated nail design to the user's device and also transmits it to the smart glasses so that it can be displayed in real time.The server's communication module sends the design data as an HTTP response and simultaneously transmits it to the smart glasses in a compatible format.

[0220] Input: Generated nail design

[0221] Output: Nail design displayed on user device and smart glasses

[0222] Step 6:

[0223] The user checks the generated nail design in real time through the smart glasses. The user checks the design and requests regeneration if necessary. This input is sent back to the server via the terminal.

[0224] Input: Nail design displayed on smart glasses

[0225] Output: User confirmation and regeneration request

[0226] Step 7:

[0227] The server receives the regeneration request and regenerates a new nail design. The regenerated nail design is then sent to the user device and smart glasses. The server then uses the AI ​​model to generate a different nail design and sends it through the endpoint.

[0228] Input: Regeneration request

[0229] Output: Regenerated nail design

[0230] Step 8:

[0231] The user selects their final nail design and saves it on the device, which then displays an option to download the final design in a printable format for use at a nail salon or for self-nail care.

[0232] Input: Final selection by user

[0233] Output: Saved final nail design

[0234] Through these processing steps, users can easily and intuitively create, check, and save unique nail designs.

[0235] 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.

[0236] The system of the present invention allows users to easily and conveniently enjoy nail designs of their favorite idols or characters. Furthermore, by combining it with an emotion engine that recognizes the user's emotional state and adjusts the nail design based on that emotion, it is possible to propose more personalized designs.

[0237] System configuration

[0238] The system consists of the following main components:

[0239] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0240] Server: A cloud-based server system containing the AI ​​model

[0241] Emotion Engine: An engine for analyzing and recognizing user emotions

[0242] Program processing (natural language)

[0243] The system operates in the following steps:

[0244] 1. Receiving user input data

[0245] The user launches the nail design generation application on the device.

[0246] An interface will appear that allows users to upload an image of their favorite character.

[0247] Users upload image data and set preferences such as the color and style of the nail design they want.

[0248] 2. Recognizing emotional states

[0249] The emotion engine analyzes the image data uploaded by the user, as well as the voice and facial expression data while the user is using the app, to recognize the user's emotional state.

[0250] The recognized emotions are classified into categories such as "happiness," "sadness," "surprise," and "calmness."

[0251] 3. Sending input data

[0252] The terminal transmits the user's input data (image data and preference settings) and the emotional state recognized by the emotion engine to the server.

[0253] 4. Image analysis and feature extraction

[0254] The server then enters the phase of analyzing the received image data.

[0255] The image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs.

[0256] 5. Nail design generation

[0257] The server-based AI model generates nail designs based on the extracted features, the user's preference settings, and the perceived emotional state.

[0258] The generated design is set up so that, upon closer inspection, motifs of the favorite idol are hidden. The color tone and style of the design are adjusted according to the emotional state.

[0259] 6. Providing the generated results

[0260] The server transmits the generated nail design to the terminal.

[0261] The device displays a list of nail designs to the user, where the user can review the designs.

[0262] 7. User Verification and Regeneration

[0263] The user can review the generated design and request a regeneration if necessary, which sends a request to the server to generate another design.

[0264] 8. Final design and output

[0265] The user selects the final design they like.

[0266] The device will then display an option to download the selected design in a format suitable for salon or self-nail use.

[0267] The user saves the final design data.

[0268] Specific examples

[0269] For example, if a user uploads an image of "Idol X" and requests a nail design that matches that image, the system will recognize that the user is in a "joy" emotional state. In this case, the system will generate a nail design incorporating bright colors and positive design elements to reflect the user's joy. As a result, the generated nail design combines the user's emotional state with the characteristics of the idol, providing a more personalized and optimal design.

[0270] In this way, the system of the present invention can improve user satisfaction by automatically generating and providing unique and personalized nail designs while recognizing and reflecting the user's emotional state.

[0271] The processing flow will be explained below.

[0272] Step 1:

[0273] The user launches the nail design generation application on their device. When the application is launched, a user interface appears, presenting input fields for uploading an image of their favorite character and setting options.

[0274] Step 2:

[0275] Users upload an image of their favorite character to their device. They then set their preferences for the nail design, such as color, style, and level of simplicity. This input data (image data and preference settings) is used as the initial data for the next step.

[0276] Step 3:

[0277] The emotion engine starts working and analyzes the input data to recognize the user's emotional state. The input data may include the user's facial image data and voice data during activities. The emotion engine analyzes this data and identifies the user's emotion (e.g., "happiness," "sadness," "surprise," etc.).

[0278] Step 4:

[0279] The device sends the image data and preferences entered by the user, as well as the emotional state recognized by the emotion engine, as data packets to the server. Communication is typically securely carried out over the Internet.

[0280] Step 5:

[0281] The server receives the data packets sent from the terminal, and the received image data, preference settings, and recognized emotional state are passed on to the next analysis process.

[0282] Step 6:

[0283] The server launches an image analysis module to analyze the image data. The image analysis module uses machine learning algorithms and image recognition technology to extract features such as color, shape, and motif.

[0284] Step 7:

[0285] The server inputs extracted feature data such as color, shape, and motif, along with the user's preference settings and recognized emotional state, into a generative AI model. The generative AI model generates multiple nail designs based on this data. The generated designs are set up so that the motif of the user's favorite idol is hidden upon closer inspection, and the color tone and style of the design are adjusted according to the user's emotional state.

[0286] Step 8:

[0287] The server sends multiple nail designs generated by the generative AI model to the device as data packets, in a format that can be viewed by the user.

[0288] Step 9:

[0289] The device displays the received nail design data in a list format to the user, allowing the user to compare and check multiple designs from the list.

[0290] Step 10:

[0291] The user checks the generated design and requests regeneration if necessary. The regeneration request is sent to the server in the form of another design being generated.

[0292] Step 11:

[0293] The server receives the regeneration request and runs the process again to generate a new design. Once the new design is generated, it sends the data back to the device and redisplays it.

[0294] Step 12:

[0295] The user selects the final design they like and downloads it using the appropriate save option displayed on their device.

[0296] Step 13:

[0297] The device saves the selected nail design in a format for download (e.g. PNG, JPEG, PDF, etc.) The saved design data can be used to take to a nail salon or as a guide for self-nail design.

[0298] In this way, each step corresponds to the user's preferences and emotional state, and the process is carried out to automatically generate and provide top-quality personalized nail designs.

[0299] Example 2

[0300] 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."

[0301] In the modern nail design market, many users desire personalized designs based on their preferences and emotional state. However, conventional systems face challenges in recognizing users' diverse emotional states and adjusting designs accordingly, making it difficult to provide optimal designs for each individual user. Furthermore, if users are dissatisfied with a generated design, the process for requesting a regeneration is often complicated. This results in poor usability and dissatisfaction for many users.

[0302] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0303] In this invention, the server includes a means for recognizing a user's emotional state, a means for adjusting a nail design based on the recognized emotional state, and a means for using a generative AI model to generate a nail design based on the extracted features. This allows a design to be generated by incorporating the user's emotional state into its composition. Furthermore, automatic adjustment of the motif and color tone of the user's favorite character included in the generated design can increase user satisfaction. Furthermore, adding a function for easily generating and providing different designs in response to a regeneration request improves the user experience and eliminates the cumbersome regeneration procedure.

[0304] "User" means an individual who intends to use the system to generate a nail design.

[0305] "Image data" refers to image files of favorite characters or idols uploaded by users.

[0306] "Preference settings" include individual specifications such as the color tone and style of the nail design desired by the user.

[0307] "Means for receiving" refers to a method for obtaining image data and preference settings from a user as input.

[0308] "Means for analysis" refers to the method of analyzing the received image data and extracting features such as color, shape, and motif.

[0309] "Emotional state" is data that indicates the user's emotions, extracted from the user's facial expressions, voice data, etc.

[0310] "Means for recognition" refers to a method for analyzing a user's emotional state and classifying it into a specific emotional category.

[0311] "Adjusting means" refers to methods of changing the color tone or style of a nail design based on a perceived emotional state.

[0312] "Means for generating" refers to a method for using an AI model to generate nail designs based on the extracted features and the user's preferences and emotional state.

[0313] "Means for providing" refers to a method for displaying the generated nail design to the user and making it viewable.

[0314] A "regeneration request" refers to a request to generate a different design again for a design that the user does not like.

[0315] "Means for saving" refers to a method for saving the generated nail design in a file format for later use.

[0316] "Outputable format" refers to a file format in which the generated nail design is suitable for use at a nail salon or for self-nail design.

[0317] The present invention is a system for users to create personalized nail designs according to their preferences and emotions. The system is broadly composed of the following main components:

[0318] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0319] Server: A cloud-based server system containing the generative AI model

[0320] Emotion Engine: An engine for analyzing and recognizing user emotions

[0321] The operation of the system will now be described in detail.

[0322] User device roles

[0323] First, the user launches the nail design generation application on their device. They upload an image of their favorite character and set their desired nail design preferences. The emotion engine acquires the user's facial expressions and voice data on the device and recognizes their emotional state.

[0324] Server Roles

[0325] The device sends input data and emotional state to a server. The server uses an image analysis module to analyze the received image data and extract features such as color, shape, and distinctive motifs. A generative AI model then generates a nail design based on the extracted features, the user's preference settings, and the user's emotional state. The generated nail design is individually adjusted in color and style depending on the user's emotional state.

[0326] System Operation

[0327] The server sends the generated nail design to the terminal, which displays the result to the user. If the user is dissatisfied with the result, the server can generate a different design and provide it again by making a regeneration request.

[0328] Specific operation examples

[0329] For example, if a user uploads an image of "Idol X" and requests a nail design to match that image, the system will recognize that the user is in a "joy" emotional state. In this case, the system will generate a nail design incorporating bright colors and positive design elements to reflect the user's joy. This provides a unique and personalized design that combines the user's emotional state with the characteristics of their favorite character.

[0330] Prompt Sentence Examples

[0331] You can simulate real-world behavior by feeding the following prompts into the generative AI model:

[0332] "You're a fan of idol X. Imagine a situation that makes you feel particularly happy. Based on that emotion, generate a brightly colored nail design with idol X as the motif."

[0333] The system can improve user satisfaction by recognizing the user's emotional state and generating personalized nail designs based on it.

[0334] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0335] Step 1:

[0336] The user launches the nail design generation application on their device. An interface is displayed for the user to upload image data of their favorite character. The user selects the character image file and sets preferences such as color tone and style. The input is the image data of the favorite character and preferences for the desired nail design, and the output is a state in which these input data are ready to be passed to the next processing step.

[0337] Step 2:

[0338] The emotion engine acquires the user's facial expression and voice data and recognizes their emotional state. Specifically, it uses the device's camera and microphone to collect the user's facial expressions and voice in real time. The input is the user's facial expression data and voice data, and the output is data that classifies the recognized emotional state into categories. The data is classified into specific emotional categories such as "happiness," "sadness," "surprise," and "calm."

[0339] Step 3:

[0340] The device sends the user's input data (image data and preference settings) and the emotional state recognized by the emotion engine to the server. The input here is the user's preference data and the recognized emotional data, and the output is that these data are sent to the server. It is required that the device transmits the data accurately to the server.

[0341] Step 4:

[0342] The server analyzes the image data it receives. An image analysis module within the server analyzes the image data and extracts color tones, shapes, distinctive motifs, etc. The input is the image data sent from the device, and the output is the extracted image feature data. Specifically, the process uses an image recognition algorithm to extract and analyze each element of the image.

[0343] Step 5:

[0344] A generative AI model on the server generates nail designs based on the extracted features, the user's preference settings, and the recognized emotional state. The input is feature data, user preference information, and emotional state data, and the output is the generated nail design. The AI ​​model fine-tunes the color tone and style depending on the user's emotional state.

[0345] Step 6:

[0346] The server sends the generated nail design to the terminal. The input is the generated nail design data, and the output is receiving the design data on the terminal side. The server sends the design data to the terminal in an appropriate format.

[0347] Step 7:

[0348] The terminal displays the received nail designs to the user in a list format. The user confirms the generated designs. The input is the nail design data sent from the server, and the output is a list of designs displayed on the user's screen. The user previews the generated designs at this stage.

[0349] Step 8:

[0350] If the user does not like the design, they can request a regeneration. The device sends the regeneration request to the server. The input is the user's regeneration request, and the output is a regeneration instruction sent to the server. The server generates a new design and sends it to the device again.

[0351] Step 9:

[0352] At the final decision stage, the user selects the final design they like, and the device provides the selected design in a storable format. The input is the design selected by the user, and the output is the saved design data. The user can download this data and use it at a nail salon or for self-nail care.

[0353] (Application example 2)

[0354] 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."

[0355] Conventional nail design generation systems generate designs without considering the user's emotional state, resulting in insufficient personalized suggestions. This makes it impossible to provide the highly satisfying, individualized designs desired by users. Furthermore, the nail design regeneration function does not reflect the user's emotional state, making it difficult to fully meet the user's needs.

[0356] The specific processing by the specific 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 receiving image data and preference settings from a user, means for using an emotion engine that recognizes the user's emotions, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using an AI model that generates a nail design based on the extracted features and the recognized emotion, and means for providing the generated nail design to the user. This makes it possible to automatically generate and provide a personalized nail design that reflects the user's emotional state.

[0357] "User terminal" means a device used by a User, including a smartphone, tablet, laptop, or desktop computer.

[0358] "Image data" refers to image files uploaded by users, including images of their favorite idols or characters.

[0359] "Preference settings" refers to individual preference information such as the color tone and style of the nail design desired by the user.

[0360] The "emotion engine" is a module for recognizing and analyzing the user's emotional state, and has the ability to classify emotions through facial expression analysis, voice analysis, etc.

[0361] "Feature extraction" refers to the process of analyzing and extracting attributes such as color, shape, and distinctive motifs from image data.

[0362] An "AI model" is a model that uses artificial intelligence and includes algorithms that generate new nail designs based on feature extraction and sentiment analysis.

[0363] "Nail designs" are designs or patterns for the purpose of decorating fingertips, which are generated and individually provided based on the user's preferences and feelings.

[0364] A "regeneration request" is an action in which a user is not satisfied with an already generated nail design and requests the system to generate a new design.

[0365] The "nail salon format" is digital data in a format that allows a professional nail artist to apply the generated nail design.

[0366] The "self-nail format" is digital data in a format that allows the user to create the generated nail design at home.

[0367] "Server" means a cloud-based computer system that includes hardware and software for processing data sent from user devices and generating and providing nail designs using AI models.

[0368] The system that realizes this invention mainly consists of the following components: a user terminal, an emotion engine, and a server. The detailed functions and processing of each component are explained below.

[0369] System configuration and program processing

[0370] 1. User Device:

[0371] The user device is a device used by the user, such as a smartphone, tablet, laptop, or desktop computer. This device collects image data from the user and works with the emotion engine to analyze the user's emotional state. It also transmits the data from the device to the server and provides the generated nail design to the user.

[0372] 2. Emotion Engine:

[0373] The emotion engine is a module that recognizes emotions by analyzing the user's facial expressions and voice data. This is achieved using Microsoft Azure's Face API and Amazon Rekognition. The engine classifies emotions into categories such as "happiness," "sadness," "surprise," and "calmness." For example, if a user smiles into the smartphone camera, the emotion engine will recognize this as "happiness."

[0374] 3. Server:

[0375] The server is a cloud-based computer system that processes data sent from user devices. The server has the following main functions:

[0376] Processing and storage of received data: Receives and temporarily stores image data and preference settings sent by the user, as well as the emotional state recognized by the emotion engine.

[0377] Image analysis module: Analyzes image data using Google Cloud Vision API and other tools to extract features such as color, shape, and motif.

[0378] AI model design generation: A custom AI model using TensorFlow or PyTorch generates novel nail designs based on extracted features, the user's preference settings, and the perceived emotional state. For example, based on an image of "Idol X" and the emotion "joy," the model might incorporate bright colors and positive design elements.

[0379] Providing results: The generated nail design is sent to the user's device and the results are provided to the user.

[0380] Specific examples

[0381] For example, if a user uploads an image of "Popular Artist X" and requests a nail design that matches that image, the system will further recognize that the user is in an emotional state of "joy." In this case, the system will generate a nail design that incorporates bright colors and positive design elements to reflect the user's joy. The prompt sentence to be input into the generative AI model in this example is as follows:

[0382] "A user uploads a cheerful image of popular artist X, and they are in the emotional state of 'joy.' Extract the color, shape, and distinctive motifs from the image and generate a nail design that incorporates positive design elements in cheerful tones."

[0383] In this way, the present invention is a system that automatically generates and provides personalized nail designs that reflect the user's emotional state, and is capable of providing a service that is highly satisfying to users.

[0384] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0385] Step 1: Start the user terminal and enter data

[0386] The user launches the application and uploads image data of their favorite idol or character on the main screen. The user inputs their preferred settings, such as the color tone and style of their nail design, and provides the app with a face photo and voice data to recognize their emotional state. In this step, the application obtains "image data," "preferred settings," and "emotional data" as input data. These data are then sent to the next step.

[0387] Step 2: Emotional state analysis by the emotion engine

[0388] The device uses an emotion engine to analyze the user's emotional state based on the facial photo and voice data provided by the user. Specifically, facial expressions are recognized using Microsoft Azure's Face API, and voice data is analyzed through Amazon Rekognition. For example, the emotional state may be recognized as "joy." The input data is a "face photo" and "voice data," and the output is an "emotional state."

[0389] Step 3: Sending data

[0390] The device sends the user's input data ("image data," "preferred settings") and the "emotional state" recognized by the emotion engine to the server. The server receives this data and temporarily stores it. It receives "image data," "preferred settings," and "emotional state" as input data and sends them to the server.

[0391] Step 4: Image analysis and feature extraction

[0392] On the server side, the image analysis module uses the Google Cloud Vision API to analyze the image data and extract features such as color, shape, and motif. Specifically, it analyzes the image data at the pixel level to identify dominant color tones, shape patterns, and unique motifs. For example, the color blue and a star-shaped motif are extracted from an image of "Idol X." It uses "image data" as input data and obtains "feature data" as output.

[0393] Step 5: Generate nail designs using AI models

[0394] An AI model on the server generates new nail designs based on the extracted "feature data," the user's "preference settings," and their "emotional state." This is done using a custom model using TensorFlow and PyTorch. For example, a nail design incorporating bright colors and positive design elements is generated based on the color "blue," a "star-shaped motif," and an emotional state of "joy." The input data are "feature data," "preference settings," and "emotional state," and the output is a "generated nail design."

[0395] Step 6: Providing the generated results

[0396] The server sends the generated "nail design" to the terminal, which then displays the design proposals to the user in a list format. The user can then confirm the generated design. The input data is the "generated nail design," and the output is a "list display of designs."

[0397] Step 7: Verify and regenerate users

[0398] The user can check the generated design and request regeneration if necessary. In the case of regeneration, a different design is generated based on the new feature data and sent again by the server to the device. In this step, the "regeneration request" is received as input data, and the "generated nail design" is obtained again.

[0399] Step 8: Decide on the final design and output

[0400] The user finally selects the design they like, and the device displays the option to provide the selected design in a format suitable for nail salons or self-nail care. The user saves the final design data and downloads it as needed. The device receives the "final design selection" as input data and provides the "nail salon format" or "self-nail format" as output.

[0401] The above is an explanation of the processing steps of the program implemented based on the patent, as well as the specific operations and inputs / outputs of each.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] [Second embodiment]

[0406] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0407] 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.

[0408] 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).

[0409] 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.

[0410] 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.

[0411] 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).

[0412] 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.

[0413] 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.

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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."

[0418] The system of the present invention allows users to easily and conveniently enjoy nail designs of their favorite idols or characters. The system automatically generates and provides nail designs using an AI model when the user provides the system with specific image data and preferred settings.

[0419] System configuration

[0420] The system consists of the following main components:

[0421] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0422] Server: A cloud-based server system containing the AI ​​model

[0423] Program processing (natural language)

[0424] The system operates in the following steps:

[0425] 1. Receiving user input data

[0426] The user launches the nail design generation application on the device.

[0427] An interface will appear that allows users to upload an image of their favorite character.

[0428] Users upload image data and set preferences such as the color and style of the nail design they want.

[0429] 2. Sending input data

[0430] The device sends the image data and user preferences to a server, usually over the Internet.

[0431] 3. Image analysis and feature extraction

[0432] The server then enters the phase of analyzing the received image data.

[0433] The server's image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs.

[0434] 4. Nail design generation

[0435] The AI ​​model on the server generates multiple nail designs based on the extracted features and the user's preferences.

[0436] The generated designs look generic at first glance, but upon closer inspection you'll see that motifs of your favorite character have been cleverly incorporated.

[0437] 5. Providing the generated results

[0438] The server returns the generated nail designs to the terminal.

[0439] The device displays a list of nail designs to the user, which is the first time the user sees the designs.

[0440] 6. User Verification and Regeneration

[0441] Users will have the ability to review the generated design and request a regeneration if necessary.

[0442] If the user wishes to regenerate, a request to generate a new design is sent to the server.

[0443] 7. Final design and output

[0444] Users choose the design they like.

[0445] The device will then present you with the option to download the selected design in a format suitable for taking to a nail salon or for self-nail application.

[0446] The user saves the final design data.

[0447] Specific examples

[0448] For example, consider a case where a user uploads an image of "Idol X" and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "Pastel" in the color settings. The system receives the image data and performs image analysis on the server to extract specific colors and symbols. The AI ​​model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X."

[0449] In this way, the system of the present invention allows users to easily enjoy unique and personalized nail designs.

[0450] The processing flow will be explained below.

[0451] Step 1:

[0452] The user launches the nail design generation application on their device. When the application is launched, a user interface appears, presenting input fields for uploading an image of their favorite character and setting options.

[0453] Step 2:

[0454] Users upload an image of their favorite character to their device. They then set their preferences for the nail design, such as color, style, and level of simplicity. This input data (image data and preference settings) is used as the initial data for the next step.

[0455] Step 3:

[0456] The device sends the image data and user preferences as data packets to a server, typically via secure internet communication.

[0457] Step 4:

[0458] The server receives the data packets sent from the device, and the received image data and preference settings are passed on to the next analysis process.

[0459] Step 5:

[0460] The server launches an image analysis module to analyze the image data. The image analysis module uses machine learning algorithms and image recognition technology to extract features such as color, shape, and motif.

[0461] Step 6:

[0462] The server inputs the extracted feature data, such as color, shape, and motif, into a generative AI model. The generative AI model generates multiple nail designs based on this feature data and the user's preferences. The generated designs are set up so that, upon closer inspection, the motif of the user's favorite idol is hidden.

[0463] Step 7:

[0464] The server sends multiple nail designs generated by the generative AI model to the device as data packets, in a format that can be viewed by the user.

[0465] Step 8:

[0466] The device displays the received nail design data in a list format to the user, allowing the user to compare and check multiple designs from the list.

[0467] Step 9:

[0468] The user checks the generated design and requests regeneration if necessary. The regeneration request is sent to the server in the form of another design being generated.

[0469] Step 10:

[0470] The server receives the regeneration request and runs the process again to generate a new design. Once the new design is generated, it sends the data back to the device and redisplays it.

[0471] Step 11:

[0472] The user selects the final design they like and downloads it using the appropriate save option displayed on their device.

[0473] Step 12:

[0474] The device saves the selected nail design in a format for download (e.g. PNG, JPEG, PDF, etc.) The saved design data can be used to take to a nail salon or as a guide for self-nail design.

[0475] In this way, each step is tailored to the user's preferences and goes through a process to automatically generate and provide top-quality nail designs.

[0476] Example 1

[0477] 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."

[0478] The problem that this invention aims to solve is to provide a system that allows users to easily enjoy unique and personalized nail designs that incorporate elements of their favorite idols or characters, and also to provide a highly convenient system that can respond to changes in users' preferences and additional requests, and has regeneration functions and flexibility in saving and outputting.

[0479] 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.

[0480] In this invention, the server includes means for receiving image data and preference settings from a user, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using a generative AI model to generate nail designs based on the extracted features, means for inputting a prompt to the generative AI model, means for providing the generated nail designs to the user, means for generating different nail designs in response to a regeneration request and providing them again to the user, and means for saving the generated nail designs and providing them in a format that can be output. This allows users to easily generate and regenerate personalized nail designs incorporating elements of their favorite idols, and further save and output them.

[0481] "Image data" refers to visual information such as photographs and illustrations uploaded by users.

[0482] "Preference settings" refers to information about individual preferences, such as colors and design styles, specified by the user.

[0483] "Means for extracting features" refers to technology that uses AI models and algorithms to analyze and extract features such as color, shape, and motifs from image data.

[0484] A "generative AI model" refers to an artificial intelligence model that generates new nail designs based on extracted features and user preferences.

[0485] A "prompt sentence" refers to an input sentence that provides specific instructions or conditions to a generative AI model.

[0486] "Regeneration Request" refers to a request to generate a new design when a user is not satisfied with an existing design.

[0487] "Outputable format" means saving the generated nail design and providing it in a printable format (e.g. PNG, JPEG) for use in a nail salon or for self-nail design.

[0488] "Device" refers to an electronic device used by a user, such as a desktop computer, laptop, tablet, or smartphone.

[0489] "Server" refers to the computer system on which the cloud-based system, including the AI ​​model, runs.

[0490] The present invention is a system that allows users to easily create nail designs incorporating elements of their favorite idols or characters. The system includes a process in which a user provides specific image data and preferred settings, and an AI model is used to automatically generate and provide nail designs.

[0491] System configuration

[0492] The system consists of the following main components:

[0493] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0494] Server: A cloud-based server system containing the AI ​​model

[0495] Program processing

[0496] The program of this system operates as follows.

[0497] Receiving user input data

[0498] The user launches the nail design generation application on their device. The application displays an interface for uploading an image of their favorite character. The user uploads the image data and sets preferences such as the color and style of the desired nail design.

[0499] Sending input data

[0500] The device sends the image data and user preferences to a server, usually over the Internet.

[0501] Image analysis and feature extraction

[0502] The server then enters the analysis phase of the received image data. The server's image analysis module analyzes the image data and uses deep learning technology to extract features such as color, shape, and unique motifs.

[0503] Nail design generation

[0504] The generative AI model on the server generates multiple nail designs based on the extracted features and the user's preferences. Specifically, the extracted data is used as a prompt. For example, a prompt could be, "Generate a pastel-toned nail design incorporating the colors and motifs of idol X."

[0505] Providing generated results

[0506] The server returns the generated nail designs to the terminal, which displays the nail designs to the user in a list format, allowing the user to confirm each design.

[0507] Verify and regenerate users

[0508] The user is given the ability to review the generated design and request a regeneration if necessary, and the server will generate a new design upon request.

[0509] Final design decision and output

[0510] The user selects a design they like. The device displays an option to download the selected design in a format suitable for taking to a nail salon or for self-nail care. The user saves the final design data.

[0511] Specific example explanation

[0512] For example, consider a case where a user uploads an image of "Idol X" and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "Pastel" in the color settings. The system receives the image data and performs image analysis on the server to extract specific colors and symbols. The generative AI model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X."

[0513] Prompt Sentence Examples

[0514] "Create a pastel-colored nail design based on a photo of idol X. Subtly incorporate motifs of your favorite idol into the design."

[0515] In this way, the system of the present invention allows users to easily enjoy unique and personalized nail designs.

[0516] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0517] Step 1:

[0518] The user launches the nail design generation application on their device. The application displays an interface for uploading an image of their favorite character. The user taps the "Upload Image" button and selects an image of their favorite character from their gallery. Options for color and style selection are then displayed, allowing the user to make the settings.

[0519] Input: User-selected image data and preferred settings (color tone, style).

[0520] Output: Send the prepared image data and your preferred settings to the server.

[0521] Step 2:

[0522] The device sends the image data and preferred settings entered by the user to a server, usually over the Internet. When the user taps the "Send" button, an app on the device consolidates the data and sends it over the Internet to the server.

[0523] Input: Ready image data and your preferred settings.

[0524] Output: Data sent to server completed.

[0525] Step 3:

[0526] The server then enters the analysis phase of the received image data. The server's image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs. Specifically, it uses a deep learning model to extract features such as color and shape.

[0527] Input: Image data received by the server.

[0528] Output: Data with extracted features such as color, shape, and motif.

[0529] Step 4:

[0530] The server-based generative AI model generates multiple nail designs based on the extracted features and the user's preferences, using the extracted data as prompts, such as "Generate a pastel nail design incorporating the colors and motifs of idol X."

[0531] Input: Parsed feature data and user preference data.

[0532] Output: Generated multiple nail design data.

[0533] Step 5:

[0534] The server sends the generated nail designs back to the device. The device application receives this data and displays a list-style design selection screen on the GUI. The user can swipe to view multiple designs.

[0535] Input: Each generated nail design data.

[0536] Output: Multiple nail designs displayed on the user's device.

[0537] Step 6:

[0538] The user can review the generated design and request a regeneration if necessary. The regeneration request is sent to the server and the process of generating a new design is repeated. When the user taps the "Regenerate" button, the request is sent to the server.

[0539] Input: The user's regeneration request.

[0540] Output: Generation and presentation of new nail design data.

[0541] Step 7:

[0542] The user selects a design they like. The device displays an option to download the selected design in a format suitable for taking to a nail salon or for self-nail care. When the user taps the "Download" button, the device saves the design data.

[0543] Input: Selected nail design.

[0544] Output: The final nail design data saved on your device.

[0545] (Application example 1)

[0546] 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."

[0547] The present invention relates to a system that allows users to easily create and visually confirm individual nail designs based on their favorite characters or idols. Conventional nail design creation methods have faced challenges such as communication gaps between nail technicians and users, and the difficulty of reviewing designs in real time. Additionally, there is a lack of means for customers to intuitively understand and adjust specific designs.

[0548] 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.

[0549] In this invention, the server includes means for receiving image data and preference settings from a user, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using a generative AI model to generate a nail design based on the extracted features, means for providing the generated nail design to the user, and means for displaying the generated nail design in real time through the smart glasses, thereby enabling the user to check the generated nail design in real time through the smart glasses and make adjustments in collaboration with the manicurist.

[0550] "User" means an individual who uses the system to create and review nail designs.

[0551] "Image data" refers to image files of favorite characters, idols, etc. provided by users.

[0552] "Preference settings" is information that indicates specific design requests, such as the color tone and style of the nail design desired by the user.

[0553] "Characteristics such as color, shape, and motif" are visual features analyzed from image data and serve as materials for nail design.

[0554] A "generative AI model" is an artificial intelligence model that automatically generates nail designs based on image data and the user's preferences.

[0555] "Smart glasses" are wearable devices that are glasses-type devices equipped with a display that can display information in real time.

[0556] "Real-time" is a term that refers to processing and reactions occurring almost immediately, with results being displayed immediately.

[0557] A "regeneration request" is an instruction to request the AI ​​model to generate a new design when the user is dissatisfied with the existing nail design or wants a new design.

[0558] The system of the present invention allows users to create and view their favorite nail designs in real time. The system is configured using a user terminal, a server, and smart glasses.

[0559] System configuration

[0560] 1. User Device

[0561] User devices include smartphones, tablets, desktop computers, and laptops.

[0562] It provides an interface for users to input image data and preference settings.

[0563] 2. Server

[0564] The cloud-based server analyzes the received image data and generates nail designs using a generative AI model.

[0565] The server has the ability to extract features such as color, shape, and motif based on the received image data and user preferences.

[0566] After feature extraction, the generative AI model automatically generates multiple nail designs.

[0567] Generated nail designs can also be regenerated upon request, allowing you to regenerate different designs.

[0568] 3. Smart Glasses

[0569] The smart glasses include a display that displays the generated nail designs to the user in real time.

[0570] Users can check the nail design generated through the smart glasses by overlaying it on the image of their hands.

[0571] Program processing (natural language)

[0572] The user launches a nail design generation application on their device. They upload image data of their favorite character or idol and select their preferred color and style. The device then sends this data to the server. The server analyzes the image, extracts features, and generates a nail design using a generative AI model. The generated nail design is sent back from the server to the device and simultaneously displayed on the smart glasses. The user can view the design in real time through the smart glasses and make any adjustments in consultation with the manicurist.

[0573] Technology and hardware used

[0574] AI models: Machine learning frameworks such as TensorFlow and PyTorch

[0575] Cloud services: AWS, Google Cloud, Microsoft Azure, etc.

[0576] Smart glasses: Google Glass, Microsoft HoloLens, etc.

[0577] User devices: iOS, Android, Windows, macOS

[0578] Specific examples

[0579] For example, consider the case where a user uploads an image of their favorite character, "Idol X," and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "pastel" in the color setting. The server receives the image data, and the AI ​​model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X." The generated nail design is displayed in real time on the user's hand via smart glasses.

[0580] Prompt Sentence Examples

[0581] Upload an image of "Idol X" and generate a nail design with a pastel design.

[0582] In this way, the system of the present invention allows users to create and check nail designs easily and intuitively.

[0583] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0584] Step 1:

[0585] A user launches a nail design generation application on their device. They upload an image of their favorite character or idol and input their preferred settings (e.g., color tone and style). The device then receives and temporarily stores the image data and preferred settings.

[0586] Step 2:

[0587] The device sends the image data and user preferences entered by the user to the server. This communication is typically over the Internet. The device sends the uploaded image data and user preferences as an HTTP request.

[0588] Step 3:

[0589] The server analyzes the image data it receives and extracts features such as color, shape, and motif. The server's image analysis module applies an image processing algorithm (e.g., CNN) to the received image data, converts the extracted features into an internal format, and saves them.

[0590] Input: Image data received by the server

[0591] Output: Extracted feature data

[0592] Step 4:

[0593] The server generates nail designs using a generative AI model based on the extracted feature data and the user's preference settings. The AI ​​model (e.g., using TensorFlow or PyTorch) receives the features and preference settings as prompts and generates nail design images.

[0594] Input: extracted feature data and preference settings

[0595] Output: Generated nail design

[0596] Step 5:

[0597] The server returns the generated nail design to the user's device and also transmits it to the smart glasses so that it can be displayed in real time.The server's communication module sends the design data as an HTTP response and simultaneously transmits it to the smart glasses in a compatible format.

[0598] Input: Generated nail design

[0599] Output: Nail design displayed on user device and smart glasses

[0600] Step 6:

[0601] The user checks the generated nail design in real time through the smart glasses. The user checks the design and requests regeneration if necessary. This input is sent back to the server via the terminal.

[0602] Input: Nail design displayed on smart glasses

[0603] Output: User confirmation and regeneration request

[0604] Step 7:

[0605] The server receives the regeneration request and regenerates a new nail design. The regenerated nail design is then sent to the user device and smart glasses. The server then uses the AI ​​model to generate a different nail design and sends it through the endpoint.

[0606] Input: Regeneration request

[0607] Output: Regenerated nail design

[0608] Step 8:

[0609] The user selects their final nail design and saves it on the device, which then displays an option to download the final design in a printable format for use at a nail salon or for self-nail care.

[0610] Input: Final selection by user

[0611] Output: Saved final nail design

[0612] Through these processing steps, users can easily and intuitively create, check, and save unique nail designs.

[0613] 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.

[0614] The system of the present invention allows users to easily and conveniently enjoy nail designs of their favorite idols or characters. Furthermore, by combining it with an emotion engine that recognizes the user's emotional state and adjusts the nail design based on that emotion, it is possible to propose more personalized designs.

[0615] System configuration

[0616] The system consists of the following main components:

[0617] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0618] Server: A cloud-based server system containing the AI ​​model

[0619] Emotion Engine: An engine for analyzing and recognizing user emotions

[0620] Program processing (natural language)

[0621] The system operates in the following steps:

[0622] 1. Receiving user input data

[0623] The user launches the nail design generation application on the device.

[0624] An interface will appear that allows users to upload an image of their favorite character.

[0625] Users upload image data and set preferences such as the color and style of the nail design they want.

[0626] 2. Recognizing emotional states

[0627] The emotion engine analyzes the image data uploaded by the user, as well as the voice and facial expression data while the user is using the app, to recognize the user's emotional state.

[0628] The recognized emotions are classified into categories such as "happiness," "sadness," "surprise," and "calmness."

[0629] 3. Sending input data

[0630] The terminal transmits the user's input data (image data and preference settings) and the emotional state recognized by the emotion engine to the server.

[0631] 4. Image analysis and feature extraction

[0632] The server then enters the phase of analyzing the received image data.

[0633] The image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs.

[0634] 5. Nail design generation

[0635] The server-based AI model generates nail designs based on the extracted features, the user's preference settings, and the perceived emotional state.

[0636] The generated design is set up so that, upon closer inspection, motifs of the favorite idol are hidden. The color tone and style of the design are adjusted according to the emotional state.

[0637] 6. Providing the generated results

[0638] The server transmits the generated nail design to the terminal.

[0639] The device displays a list of nail designs to the user, where the user can review the designs.

[0640] 7. User Verification and Regeneration

[0641] The user can review the generated design and request a regeneration if necessary, which sends a request to the server to generate another design.

[0642] 8. Final design and output

[0643] The user selects the final design they like.

[0644] The device will then display an option to download the selected design in a format suitable for salon or self-nail use.

[0645] The user saves the final design data.

[0646] Specific examples

[0647] For example, if a user uploads an image of "Idol X" and requests a nail design that matches that image, the system will recognize that the user is in a "joy" emotional state. In this case, the system will generate a nail design incorporating bright colors and positive design elements to reflect the user's joy. As a result, the generated nail design combines the user's emotional state with the characteristics of the idol, providing a more personalized and optimal design.

[0648] In this way, the system of the present invention can improve user satisfaction by automatically generating and providing unique and personalized nail designs while recognizing and reflecting the user's emotional state.

[0649] The processing flow will be explained below.

[0650] Step 1:

[0651] The user launches the nail design generation application on their device. When the application is launched, a user interface appears, presenting input fields for uploading an image of their favorite character and setting options.

[0652] Step 2:

[0653] Users upload an image of their favorite character to their device. They then set their preferences for the nail design, such as color, style, and level of simplicity. This input data (image data and preference settings) is used as the initial data for the next step.

[0654] Step 3:

[0655] The emotion engine starts working and analyzes the input data to recognize the user's emotional state. The input data may include the user's facial image data and voice data during activities. The emotion engine analyzes this data and identifies the user's emotion (e.g., "happiness," "sadness," "surprise," etc.).

[0656] Step 4:

[0657] The device sends the image data and preferences entered by the user, as well as the emotional state recognized by the emotion engine, as data packets to the server. Communication is typically securely carried out over the Internet.

[0658] Step 5:

[0659] The server receives the data packets sent from the terminal, and the received image data, preference settings, and recognized emotional state are passed on to the next analysis process.

[0660] Step 6:

[0661] The server launches an image analysis module to analyze the image data. The image analysis module uses machine learning algorithms and image recognition technology to extract features such as color, shape, and motif.

[0662] Step 7:

[0663] The server inputs extracted feature data such as color, shape, and motif, along with the user's preference settings and recognized emotional state, into a generative AI model. The generative AI model generates multiple nail designs based on this data. The generated designs are set up so that the motif of the user's favorite idol is hidden upon closer inspection, and the color tone and style of the design are adjusted according to the user's emotional state.

[0664] Step 8:

[0665] The server sends multiple nail designs generated by the generative AI model to the device as data packets, in a format that can be viewed by the user.

[0666] Step 9:

[0667] The device displays the received nail design data in a list format to the user, allowing the user to compare and check multiple designs from the list.

[0668] Step 10:

[0669] The user checks the generated design and requests regeneration if necessary. The regeneration request is sent to the server in the form of another design being generated.

[0670] Step 11:

[0671] The server receives the regeneration request and runs the process again to generate a new design. Once the new design is generated, it sends the data back to the device and redisplays it.

[0672] Step 12:

[0673] The user selects the final design they like and downloads it using the appropriate save option displayed on their device.

[0674] Step 13:

[0675] The device saves the selected nail design in a format for download (e.g. PNG, JPEG, PDF, etc.) The saved design data can be used to take to a nail salon or as a guide for self-nail design.

[0676] In this way, each step corresponds to the user's preferences and emotional state, and the process is carried out to automatically generate and provide top-quality personalized nail designs.

[0677] Example 2

[0678] 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."

[0679] In the modern nail design market, many users desire personalized designs based on their preferences and emotional state. However, conventional systems face challenges in recognizing users' diverse emotional states and adjusting designs accordingly, making it difficult to provide optimal designs for each individual user. Furthermore, if users are dissatisfied with a generated design, the process for requesting a regeneration is often complicated. This results in poor usability and dissatisfaction for many users.

[0680] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0681] In this invention, the server includes a means for recognizing a user's emotional state, a means for adjusting a nail design based on the recognized emotional state, and a means for using a generative AI model to generate a nail design based on the extracted features. This allows a design to be generated by incorporating the user's emotional state into its composition. Furthermore, automatic adjustment of the motif and color tone of the user's favorite character included in the generated design can increase user satisfaction. Furthermore, adding a function for easily generating and providing different designs in response to a regeneration request improves the user experience and eliminates the cumbersome regeneration procedure.

[0682] "User" means an individual who intends to use the system to generate a nail design.

[0683] "Image data" refers to image files of favorite characters or idols uploaded by users.

[0684] "Preference settings" include individual specifications such as the color tone and style of the nail design desired by the user.

[0685] "Means for receiving" refers to a method for obtaining image data and preference settings from a user as input.

[0686] "Means for analysis" refers to the method of analyzing the received image data and extracting features such as color, shape, and motif.

[0687] "Emotional state" is data that indicates the user's emotions, extracted from the user's facial expressions, voice data, etc.

[0688] "Means for recognition" refers to a method for analyzing a user's emotional state and classifying it into a specific emotional category.

[0689] "Adjusting means" refers to methods of changing the color tone or style of a nail design based on a perceived emotional state.

[0690] "Means for generating" refers to a method for using an AI model to generate nail designs based on the extracted features and the user's preferences and emotional state.

[0691] "Means for providing" refers to a method for displaying the generated nail design to the user and making it viewable.

[0692] A "regeneration request" refers to a request to generate a different design again for a design that the user does not like.

[0693] "Means for saving" refers to a method for saving the generated nail design in a file format for later use.

[0694] "Outputable format" refers to a file format in which the generated nail design is suitable for use at a nail salon or for self-nail design.

[0695] The present invention is a system for users to create personalized nail designs according to their preferences and emotions. The system is broadly composed of the following main components:

[0696] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0697] Server: A cloud-based server system containing the generative AI model

[0698] Emotion Engine: An engine for analyzing and recognizing user emotions

[0699] The operation of the system will now be described in detail.

[0700] User device roles

[0701] First, the user launches the nail design generation application on their device. They upload an image of their favorite character and set their desired nail design preferences. The emotion engine acquires the user's facial expressions and voice data on the device and recognizes their emotional state.

[0702] Server Roles

[0703] The device sends input data and emotional state to a server. The server uses an image analysis module to analyze the received image data and extract features such as color, shape, and distinctive motifs. A generative AI model then generates a nail design based on the extracted features, the user's preference settings, and the user's emotional state. The generated nail design is individually adjusted in color and style depending on the user's emotional state.

[0704] System Operation

[0705] The server sends the generated nail design to the terminal, which displays the result to the user. If the user is dissatisfied with the result, the server can generate a different design and provide it again by making a regeneration request.

[0706] Specific operation examples

[0707] For example, if a user uploads an image of "Idol X" and requests a nail design to match that image, the system will recognize that the user is in a "joy" emotional state. In this case, the system will generate a nail design incorporating bright colors and positive design elements to reflect the user's joy. This provides a unique and personalized design that combines the user's emotional state with the characteristics of their favorite character.

[0708] Prompt Sentence Examples

[0709] You can simulate real-world behavior by feeding the following prompts into the generative AI model:

[0710] "You're a fan of idol X. Imagine a situation that makes you feel particularly happy. Based on that emotion, generate a brightly colored nail design with idol X as the motif."

[0711] The system can improve user satisfaction by recognizing the user's emotional state and generating personalized nail designs based on it.

[0712] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0713] Step 1:

[0714] The user launches the nail design generation application on their device. An interface is displayed for the user to upload image data of their favorite character. The user selects the character image file and sets preferences such as color tone and style. The input is the image data of the favorite character and preferences for the desired nail design, and the output is a state in which these input data are ready to be passed to the next processing step.

[0715] Step 2:

[0716] The emotion engine acquires the user's facial expression and voice data and recognizes their emotional state. Specifically, it uses the device's camera and microphone to collect the user's facial expressions and voice in real time. The input is the user's facial expression data and voice data, and the output is data that classifies the recognized emotional state into categories. The data is classified into specific emotional categories such as "happiness," "sadness," "surprise," and "calm."

[0717] Step 3:

[0718] The device sends the user's input data (image data and preference settings) and the emotional state recognized by the emotion engine to the server. The input here is the user's preference data and the recognized emotional data, and the output is that these data are sent to the server. It is required that the device transmits the data accurately to the server.

[0719] Step 4:

[0720] The server analyzes the image data it receives. An image analysis module within the server analyzes the image data and extracts color tones, shapes, distinctive motifs, etc. The input is the image data sent from the device, and the output is the extracted image feature data. Specifically, the process uses an image recognition algorithm to extract and analyze each element of the image.

[0721] Step 5:

[0722] A generative AI model on the server generates nail designs based on the extracted features, the user's preference settings, and the recognized emotional state. The input is feature data, user preference information, and emotional state data, and the output is the generated nail design. The AI ​​model fine-tunes the color tone and style depending on the user's emotional state.

[0723] Step 6:

[0724] The server sends the generated nail design to the terminal. The input is the generated nail design data, and the output is receiving the design data on the terminal side. The server sends the design data to the terminal in an appropriate format.

[0725] Step 7:

[0726] The terminal displays the received nail designs to the user in a list format. The user confirms the generated designs. The input is the nail design data sent from the server, and the output is a list of designs displayed on the user's screen. The user previews the generated designs at this stage.

[0727] Step 8:

[0728] If the user does not like the design, they can request a regeneration. The device sends the regeneration request to the server. The input is the user's regeneration request, and the output is a regeneration instruction sent to the server. The server generates a new design and sends it to the device again.

[0729] Step 9:

[0730] At the final decision stage, the user selects the final design they like, and the device provides the selected design in a storable format. The input is the design selected by the user, and the output is the saved design data. The user can download this data and use it at a nail salon or for self-nail care.

[0731] (Application example 2)

[0732] 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."

[0733] Conventional nail design generation systems generate designs without considering the user's emotional state, resulting in insufficient personalized suggestions. This makes it impossible to provide the highly satisfying, individualized designs desired by users. Furthermore, the nail design regeneration function does not reflect the user's emotional state, making it difficult to fully meet the user's needs.

[0734] The specific processing by the specific 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 receiving image data and preference settings from a user, means for using an emotion engine that recognizes the user's emotions, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using an AI model that generates a nail design based on the extracted features and the recognized emotion, and means for providing the generated nail design to the user. This makes it possible to automatically generate and provide a personalized nail design that reflects the user's emotional state.

[0735] "User terminal" means a device used by a User, including a smartphone, tablet, laptop, or desktop computer.

[0736] "Image data" refers to image files uploaded by users, including images of their favorite idols or characters.

[0737] "Preference settings" refers to individual preference information such as the color tone and style of the nail design desired by the user.

[0738] The "emotion engine" is a module for recognizing and analyzing the user's emotional state, and has the ability to classify emotions through facial expression analysis, voice analysis, etc.

[0739] "Feature extraction" refers to the process of analyzing and extracting attributes such as color, shape, and distinctive motifs from image data.

[0740] An "AI model" is a model that uses artificial intelligence and includes algorithms that generate new nail designs based on feature extraction and sentiment analysis.

[0741] "Nail designs" are designs or patterns for the purpose of decorating fingertips, which are generated and individually provided based on the user's preferences and feelings.

[0742] A "regeneration request" is an action in which a user is not satisfied with an already generated nail design and requests the system to generate a new design.

[0743] The "nail salon format" is digital data in a format that allows a professional nail artist to apply the generated nail design.

[0744] The "self-nail format" is digital data in a format that allows the user to create the generated nail design at home.

[0745] "Server" means a cloud-based computer system that includes hardware and software for processing data sent from user devices and generating and providing nail designs using AI models.

[0746] The system that realizes this invention mainly consists of the following components: a user terminal, an emotion engine, and a server. The detailed functions and processing of each component are explained below.

[0747] System configuration and program processing

[0748] 1. User Device:

[0749] The user device is a device used by the user, such as a smartphone, tablet, laptop, or desktop computer. This device collects image data from the user and works with the emotion engine to analyze the user's emotional state. It also transmits the data from the device to the server and provides the generated nail design to the user.

[0750] 2. Emotion Engine:

[0751] The emotion engine is a module that recognizes emotions by analyzing the user's facial expressions and voice data. This is achieved using Microsoft Azure's Face API and Amazon Rekognition. The engine classifies emotions into categories such as "happiness," "sadness," "surprise," and "calmness." For example, if a user smiles into the smartphone camera, the emotion engine will recognize this as "happiness."

[0752] 3. Server:

[0753] The server is a cloud-based computer system that processes data sent from user devices. The server has the following main functions:

[0754] Processing and storage of received data: Receives and temporarily stores image data and preference settings sent by the user, as well as the emotional state recognized by the emotion engine.

[0755] Image analysis module: Analyzes image data using Google Cloud Vision API and other tools to extract features such as color, shape, and motif.

[0756] AI model design generation: A custom AI model using TensorFlow or PyTorch generates novel nail designs based on extracted features, the user's preference settings, and the perceived emotional state. For example, based on an image of "Idol X" and the emotion "joy," the model might incorporate bright colors and positive design elements.

[0757] Providing results: The generated nail design is sent to the user's device and the results are provided to the user.

[0758] Specific examples

[0759] For example, if a user uploads an image of "Popular Artist X" and requests a nail design that matches that image, the system will further recognize that the user is in an emotional state of "joy." In this case, the system will generate a nail design that incorporates bright colors and positive design elements to reflect the user's joy. The prompt sentence to be input into the generative AI model in this example is as follows:

[0760] "A user uploads a cheerful image of popular artist X, and they are in the emotional state of 'joy.' Extract the color, shape, and distinctive motifs from the image and generate a nail design that incorporates positive design elements in cheerful tones."

[0761] In this way, the present invention is a system that automatically generates and provides personalized nail designs that reflect the user's emotional state, and is capable of providing a service that is highly satisfying to users.

[0762] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0763] Step 1: Start the user terminal and enter data

[0764] The user launches the application and uploads image data of their favorite idol or character on the main screen. The user inputs their preferred settings, such as the color tone and style of their nail design, and provides the app with a face photo and voice data to recognize their emotional state. In this step, the application obtains "image data," "preferred settings," and "emotional data" as input data. These data are then sent to the next step.

[0765] Step 2: Emotional state analysis by the emotion engine

[0766] The device uses an emotion engine to analyze the user's emotional state based on the facial photo and voice data provided by the user. Specifically, facial expressions are recognized using Microsoft Azure's Face API, and voice data is analyzed through Amazon Rekognition. For example, the emotional state may be recognized as "joy." The input data is a "face photo" and "voice data," and the output is an "emotional state."

[0767] Step 3: Sending data

[0768] The device sends the user's input data ("image data," "preferred settings") and the "emotional state" recognized by the emotion engine to the server. The server receives this data and temporarily stores it. It receives "image data," "preferred settings," and "emotional state" as input data and sends them to the server.

[0769] Step 4: Image analysis and feature extraction

[0770] On the server side, the image analysis module uses the Google Cloud Vision API to analyze the image data and extract features such as color, shape, and motif. Specifically, it analyzes the image data at the pixel level to identify dominant color tones, shape patterns, and unique motifs. For example, the color blue and a star-shaped motif are extracted from an image of "Idol X." It uses "image data" as input data and obtains "feature data" as output.

[0771] Step 5: Generate nail designs using AI models

[0772] An AI model on the server generates new nail designs based on the extracted "feature data," the user's "preference settings," and their "emotional state." This is done using a custom model using TensorFlow and PyTorch. For example, a nail design incorporating bright colors and positive design elements is generated based on the color "blue," a "star-shaped motif," and an emotional state of "joy." The input data are "feature data," "preference settings," and "emotional state," and the output is a "generated nail design."

[0773] Step 6: Providing the generated results

[0774] The server sends the generated "nail design" to the terminal, which then displays the design proposals to the user in a list format. The user can then confirm the generated design. The input data is the "generated nail design," and the output is a "list display of designs."

[0775] Step 7: Verify and regenerate users

[0776] The user can check the generated design and request regeneration if necessary. In the case of regeneration, a different design is generated based on the new feature data and sent again by the server to the device. In this step, the "regeneration request" is received as input data, and the "generated nail design" is obtained again.

[0777] Step 8: Decide on the final design and output

[0778] The user finally selects the design they like, and the device displays the option to provide the selected design in a format suitable for nail salons or self-nail care. The user saves the final design data and downloads it as needed. The device receives the "final design selection" as input data and provides the "nail salon format" or "self-nail format" as output.

[0779] The above is an explanation of the processing steps of the program implemented based on the patent, as well as the specific operations and inputs / outputs of each.

[0780] 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.

[0781] 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.

[0782] 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.

[0783] [Third embodiment]

[0784] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0785] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0786] 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).

[0787] 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.

[0788] 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.

[0789] 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).

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] 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."

[0796] The system of the present invention allows users to easily and conveniently enjoy nail designs of their favorite idols or characters. The system automatically generates and provides nail designs using an AI model when the user provides the system with specific image data and preferred settings.

[0797] System configuration

[0798] The system consists of the following main components:

[0799] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0800] Server: A cloud-based server system containing the AI ​​model

[0801] Program processing (natural language)

[0802] The system operates in the following steps:

[0803] 1. Receiving user input data

[0804] The user launches the nail design generation application on the device.

[0805] An interface will appear that allows users to upload an image of their favorite character.

[0806] Users upload image data and set preferences such as the color and style of the nail design they want.

[0807] 2. Sending input data

[0808] The device sends the image data and user preferences to a server, usually over the Internet.

[0809] 3. Image analysis and feature extraction

[0810] The server then enters the phase of analyzing the received image data.

[0811] The server's image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs.

[0812] 4. Nail design generation

[0813] The AI ​​model on the server generates multiple nail designs based on the extracted features and the user's preferences.

[0814] The generated designs look generic at first glance, but upon closer inspection you'll see that motifs of your favorite character have been cleverly incorporated.

[0815] 5. Providing the generated results

[0816] The server returns the generated nail designs to the terminal.

[0817] The device displays a list of nail designs to the user, which is the first time the user sees the designs.

[0818] 6. User Verification and Regeneration

[0819] Users will have the ability to review the generated design and request a regeneration if necessary.

[0820] If the user wishes to regenerate, a request to generate a new design is sent to the server.

[0821] 7. Final design and output

[0822] Users choose the design they like.

[0823] The device will then present you with the option to download the selected design in a format suitable for taking to a nail salon or for self-nail application.

[0824] The user saves the final design data.

[0825] Specific examples

[0826] For example, consider a case where a user uploads an image of "Idol X" and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "Pastel" in the color settings. The system receives the image data and performs image analysis on the server to extract specific colors and symbols. The AI ​​model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X."

[0827] In this way, the system of the present invention allows users to easily enjoy unique and personalized nail designs.

[0828] The processing flow will be explained below.

[0829] Step 1:

[0830] The user launches the nail design generation application on their device. When the application is launched, a user interface appears, presenting input fields for uploading an image of their favorite character and setting options.

[0831] Step 2:

[0832] Users upload an image of their favorite character to their device. They then set their preferences for the nail design, such as color, style, and level of simplicity. This input data (image data and preference settings) is used as the initial data for the next step.

[0833] Step 3:

[0834] The device sends the image data and user preferences as data packets to a server, typically via secure internet communication.

[0835] Step 4:

[0836] The server receives the data packets sent from the device, and the received image data and preference settings are passed on to the next analysis process.

[0837] Step 5:

[0838] The server launches an image analysis module to analyze the image data. The image analysis module uses machine learning algorithms and image recognition technology to extract features such as color, shape, and motif.

[0839] Step 6:

[0840] The server inputs the extracted feature data, such as color, shape, and motif, into a generative AI model. The generative AI model generates multiple nail designs based on this feature data and the user's preferences. The generated designs are set up so that, upon closer inspection, the motif of the user's favorite idol is hidden.

[0841] Step 7:

[0842] The server sends multiple nail designs generated by the generative AI model to the device as data packets, in a format that can be viewed by the user.

[0843] Step 8:

[0844] The device displays the received nail design data in a list format to the user, allowing the user to compare and check multiple designs from the list.

[0845] Step 9:

[0846] The user checks the generated design and requests regeneration if necessary. The regeneration request is sent to the server in the form of another design being generated.

[0847] Step 10:

[0848] The server receives the regeneration request and runs the process again to generate a new design. Once the new design is generated, it sends the data back to the device and redisplays it.

[0849] Step 11:

[0850] The user selects the final design they like and downloads it using the appropriate save option displayed on their device.

[0851] Step 12:

[0852] The device saves the selected nail design in a format for download (e.g. PNG, JPEG, PDF, etc.) The saved design data can be used to take to a nail salon or as a guide for self-nail design.

[0853] In this way, each step is tailored to the user's preferences and goes through a process to automatically generate and provide top-quality nail designs.

[0854] Example 1

[0855] 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."

[0856] The problem that this invention aims to solve is to provide a system that allows users to easily enjoy unique and personalized nail designs that incorporate elements of their favorite idols or characters, and also to provide a highly convenient system that can respond to changes in users' preferences and additional requests, and has regeneration functions and flexibility in saving and outputting.

[0857] 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.

[0858] In this invention, the server includes means for receiving image data and preference settings from a user, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using a generative AI model to generate nail designs based on the extracted features, means for inputting a prompt to the generative AI model, means for providing the generated nail designs to the user, means for generating different nail designs in response to a regeneration request and providing them again to the user, and means for saving the generated nail designs and providing them in a format that can be output. This allows users to easily generate and regenerate personalized nail designs incorporating elements of their favorite idols, and further save and output them.

[0859] "Image data" refers to visual information such as photographs and illustrations uploaded by users.

[0860] "Preference settings" refers to information about individual preferences, such as colors and design styles, specified by the user.

[0861] "Means for extracting features" refers to technology that uses AI models and algorithms to analyze and extract features such as color, shape, and motifs from image data.

[0862] A "generative AI model" refers to an artificial intelligence model that generates new nail designs based on extracted features and user preferences.

[0863] A "prompt sentence" refers to an input sentence that provides specific instructions or conditions to a generative AI model.

[0864] "Regeneration Request" refers to a request to generate a new design when a user is not satisfied with an existing design.

[0865] "Outputable format" means saving the generated nail design and providing it in a printable format (e.g. PNG, JPEG) for use in a nail salon or for self-nail design.

[0866] "Device" refers to an electronic device used by a user, such as a desktop computer, laptop, tablet, or smartphone.

[0867] "Server" refers to the computer system on which the cloud-based system, including the AI ​​model, runs.

[0868] The present invention is a system that allows users to easily create nail designs incorporating elements of their favorite idols or characters. The system includes a process in which a user provides specific image data and preferred settings, and an AI model is used to automatically generate and provide nail designs.

[0869] System configuration

[0870] The system consists of the following main components:

[0871] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0872] Server: A cloud-based server system containing the AI ​​model

[0873] Program processing

[0874] The program of this system operates as follows.

[0875] Receiving user input data

[0876] The user launches the nail design generation application on their device. The application displays an interface for uploading an image of their favorite character. The user uploads the image data and sets preferences such as the color and style of the desired nail design.

[0877] Sending input data

[0878] The device sends the image data and user preferences to a server, usually over the Internet.

[0879] Image analysis and feature extraction

[0880] The server then enters the analysis phase of the received image data. The server's image analysis module analyzes the image data and uses deep learning technology to extract features such as color, shape, and unique motifs.

[0881] Nail design generation

[0882] The generative AI model on the server generates multiple nail designs based on the extracted features and the user's preferences. Specifically, the extracted data is used as a prompt. For example, a prompt could be, "Generate a pastel-toned nail design incorporating the colors and motifs of idol X."

[0883] Providing generated results

[0884] The server returns the generated nail designs to the terminal, which displays the nail designs to the user in a list format, allowing the user to confirm each design.

[0885] Verify and regenerate users

[0886] The user is given the ability to review the generated design and request a regeneration if necessary, and the server will generate a new design upon request.

[0887] Final design decision and output

[0888] The user selects a design they like. The device displays an option to download the selected design in a format suitable for taking to a nail salon or for self-nail care. The user saves the final design data.

[0889] Specific example explanation

[0890] For example, consider a case where a user uploads an image of "Idol X" and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "Pastel" in the color settings. The system receives the image data and performs image analysis on the server to extract specific colors and symbols. The generative AI model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X."

[0891] Prompt Sentence Examples

[0892] "Create a pastel-colored nail design based on a photo of idol X. Subtly incorporate motifs of your favorite idol into the design."

[0893] In this way, the system of the present invention allows users to easily enjoy unique and personalized nail designs.

[0894] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0895] Step 1:

[0896] The user launches the nail design generation application on their device. The application displays an interface for uploading an image of their favorite character. The user taps the "Upload Image" button and selects an image of their favorite character from their gallery. Options for color and style selection are then displayed, allowing the user to make the settings.

[0897] Input: User-selected image data and preferred settings (color tone, style).

[0898] Output: Send the prepared image data and your preferred settings to the server.

[0899] Step 2:

[0900] The device sends the image data and preferred settings entered by the user to a server, usually over the Internet. When the user taps the "Send" button, an app on the device consolidates the data and sends it over the Internet to the server.

[0901] Input: Ready image data and your preferred settings.

[0902] Output: Data sent to server completed.

[0903] Step 3:

[0904] The server then enters the analysis phase of the received image data. The server's image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs. Specifically, it uses a deep learning model to extract features such as color and shape.

[0905] Input: Image data received by the server.

[0906] Output: Data with extracted features such as color, shape, and motif.

[0907] Step 4:

[0908] The server-based generative AI model generates multiple nail designs based on the extracted features and the user's preferences, using the extracted data as prompts, such as "Generate a pastel nail design incorporating the colors and motifs of idol X."

[0909] Input: Parsed feature data and user preference data.

[0910] Output: Generated multiple nail design data.

[0911] Step 5:

[0912] The server sends the generated nail designs back to the device. The device application receives this data and displays a list-style design selection screen on the GUI. The user can swipe to view multiple designs.

[0913] Input: Each generated nail design data.

[0914] Output: Multiple nail designs displayed on the user's device.

[0915] Step 6:

[0916] The user can review the generated design and request a regeneration if necessary. The regeneration request is sent to the server and the process of generating a new design is repeated. When the user taps the "Regenerate" button, the request is sent to the server.

[0917] Input: The user's regeneration request.

[0918] Output: Generation and presentation of new nail design data.

[0919] Step 7:

[0920] The user selects a design they like. The device displays an option to download the selected design in a format suitable for taking to a nail salon or for self-nail care. When the user taps the "Download" button, the device saves the design data.

[0921] Input: Selected nail design.

[0922] Output: The final nail design data saved on your device.

[0923] (Application example 1)

[0924] 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."

[0925] The present invention relates to a system that allows users to easily create and visually confirm individual nail designs based on their favorite characters or idols. Conventional nail design creation methods have faced challenges such as communication gaps between nail technicians and users, and the difficulty of reviewing designs in real time. Additionally, there is a lack of means for customers to intuitively understand and adjust specific designs.

[0926] 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.

[0927] In this invention, the server includes means for receiving image data and preference settings from a user, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using a generative AI model to generate a nail design based on the extracted features, means for providing the generated nail design to the user, and means for displaying the generated nail design in real time through the smart glasses, thereby enabling the user to check the generated nail design in real time through the smart glasses and make adjustments in collaboration with the manicurist.

[0928] "User" means an individual who uses the system to create and review nail designs.

[0929] "Image data" refers to image files of favorite characters, idols, etc. provided by users.

[0930] "Preference settings" is information that indicates specific design requests, such as the color tone and style of the nail design desired by the user.

[0931] "Characteristics such as color, shape, and motif" are visual features analyzed from image data and serve as materials for nail design.

[0932] A "generative AI model" is an artificial intelligence model that automatically generates nail designs based on image data and the user's preferences.

[0933] "Smart glasses" are wearable devices that are glasses-type devices equipped with a display that can display information in real time.

[0934] "Real-time" is a term that refers to processing and reactions occurring almost immediately, with results being displayed immediately.

[0935] A "regeneration request" is an instruction to request the AI ​​model to generate a new design when the user is dissatisfied with the existing nail design or wants a new design.

[0936] The system of the present invention allows users to create and view their favorite nail designs in real time. The system is configured using a user terminal, a server, and smart glasses.

[0937] System configuration

[0938] 1. User Device

[0939] User devices include smartphones, tablets, desktop computers, and laptops.

[0940] It provides an interface for users to input image data and preference settings.

[0941] 2. Server

[0942] The cloud-based server analyzes the received image data and generates nail designs using a generative AI model.

[0943] The server has the ability to extract features such as color, shape, and motif based on the received image data and user preferences.

[0944] After feature extraction, the generative AI model automatically generates multiple nail designs.

[0945] Generated nail designs can also be regenerated upon request, allowing you to regenerate different designs.

[0946] 3. Smart Glasses

[0947] The smart glasses include a display that displays the generated nail designs to the user in real time.

[0948] Users can check the nail design generated through the smart glasses by overlaying it on the image of their hands.

[0949] Program processing (natural language)

[0950] The user launches a nail design generation application on their device. They upload image data of their favorite character or idol and select their preferred color and style. The device then sends this data to the server. The server analyzes the image, extracts features, and generates a nail design using a generative AI model. The generated nail design is sent back from the server to the device and simultaneously displayed on the smart glasses. The user can view the design in real time through the smart glasses and make any adjustments in consultation with the manicurist.

[0951] Technology and hardware used

[0952] AI models: Machine learning frameworks such as TensorFlow and PyTorch

[0953] Cloud services: AWS, Google Cloud, Microsoft Azure, etc.

[0954] Smart glasses: Google Glass, Microsoft HoloLens, etc.

[0955] User devices: iOS, Android, Windows, macOS

[0956] Specific examples

[0957] For example, consider the case where a user uploads an image of their favorite character, "Idol X," and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "pastel" in the color setting. The server receives the image data, and the AI ​​model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X." The generated nail design is displayed in real time on the user's hand via smart glasses.

[0958] Prompt Sentence Examples

[0959] Upload an image of "Idol X" and generate a nail design with a pastel design.

[0960] In this way, the system of the present invention allows users to create and check nail designs easily and intuitively.

[0961] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0962] Step 1:

[0963] A user launches a nail design generation application on their device. They upload an image of their favorite character or idol and input their preferred settings (e.g., color tone and style). The device then receives and temporarily stores the image data and preferred settings.

[0964] Step 2:

[0965] The device sends the image data and user preferences entered by the user to the server. This communication is typically over the Internet. The device sends the uploaded image data and user preferences as an HTTP request.

[0966] Step 3:

[0967] The server analyzes the image data it receives and extracts features such as color, shape, and motif. The server's image analysis module applies an image processing algorithm (e.g., CNN) to the received image data, converts the extracted features into an internal format, and saves them.

[0968] Input: Image data received by the server

[0969] Output: Extracted feature data

[0970] Step 4:

[0971] The server generates nail designs using a generative AI model based on the extracted feature data and the user's preference settings. The AI ​​model (e.g., using TensorFlow or PyTorch) receives the features and preference settings as prompts and generates nail design images.

[0972] Input: extracted feature data and preference settings

[0973] Output: Generated nail design

[0974] Step 5:

[0975] The server returns the generated nail design to the user's device and also transmits it to the smart glasses so that it can be displayed in real time.The server's communication module sends the design data as an HTTP response and simultaneously transmits it to the smart glasses in a compatible format.

[0976] Input: Generated nail design

[0977] Output: Nail design displayed on user device and smart glasses

[0978] Step 6:

[0979] The user checks the generated nail design in real time through the smart glasses. The user checks the design and requests regeneration if necessary. This input is sent back to the server via the terminal.

[0980] Input: Nail design displayed on smart glasses

[0981] Output: User confirmation and regeneration request

[0982] Step 7:

[0983] The server receives the regeneration request and regenerates a new nail design. The regenerated nail design is then sent to the user device and smart glasses. The server then uses the AI ​​model to generate a different nail design and sends it through the endpoint.

[0984] Input: Regeneration request

[0985] Output: Regenerated nail design

[0986] Step 8:

[0987] The user selects their final nail design and saves it on the device, which then displays an option to download the final design in a printable format for use at a nail salon or for self-nail care.

[0988] Input: Final selection by user

[0989] Output: Saved final nail design

[0990] Through these processing steps, users can easily and intuitively create, check, and save unique nail designs.

[0991] 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.

[0992] The system of the present invention allows users to easily and conveniently enjoy nail designs of their favorite idols or characters. Furthermore, by combining it with an emotion engine that recognizes the user's emotional state and adjusts the nail design based on that emotion, it is possible to propose more personalized designs.

[0993] System configuration

[0994] The system consists of the following main components:

[0995] User devices: desktop computers, laptops, tablets, smartphones, etc.

[0996] Server: A cloud-based server system containing the AI ​​model

[0997] Emotion Engine: An engine for analyzing and recognizing user emotions

[0998] Program processing (natural language)

[0999] The system operates in the following steps:

[1000] 1. Receiving user input data

[1001] The user launches the nail design generation application on the device.

[1002] An interface will appear that allows users to upload an image of their favorite character.

[1003] Users upload image data and set preferences such as the color and style of the nail design they want.

[1004] 2. Recognizing emotional states

[1005] The emotion engine analyzes the image data uploaded by the user, as well as the voice and facial expression data while the user is using the app, to recognize the user's emotional state.

[1006] The recognized emotions are classified into categories such as "happiness," "sadness," "surprise," and "calmness."

[1007] 3. Sending input data

[1008] The terminal transmits the user's input data (image data and preference settings) and the emotional state recognized by the emotion engine to the server.

[1009] 4. Image analysis and feature extraction

[1010] The server then enters the phase of analyzing the received image data.

[1011] The image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs.

[1012] 5. Nail design generation

[1013] The server-based AI model generates nail designs based on the extracted features, the user's preference settings, and the perceived emotional state.

[1014] The generated design is set up so that, upon closer inspection, motifs of the favorite idol are hidden. The color tone and style of the design are adjusted according to the emotional state.

[1015] 6. Providing the generated results

[1016] The server transmits the generated nail design to the terminal.

[1017] The device displays a list of nail designs to the user, where the user can review the designs.

[1018] 7. User Verification and Regeneration

[1019] The user can review the generated design and request a regeneration if necessary, which sends a request to the server to generate another design.

[1020] 8. Final design and output

[1021] The user selects the final design they like.

[1022] The device will then display an option to download the selected design in a format suitable for salon or self-nail use.

[1023] The user saves the final design data.

[1024] Specific examples

[1025] For example, if a user uploads an image of "Idol X" and requests a nail design that matches that image, the system will recognize that the user is in a "joy" emotional state. In this case, the system will generate a nail design incorporating bright colors and positive design elements to reflect the user's joy. As a result, the generated nail design combines the user's emotional state with the characteristics of the idol, providing a more personalized and optimal design.

[1026] In this way, the system of the present invention can improve user satisfaction by automatically generating and providing unique and personalized nail designs while recognizing and reflecting the user's emotional state.

[1027] The processing flow will be explained below.

[1028] Step 1:

[1029] The user launches the nail design generation application on their device. When the application is launched, a user interface appears, presenting input fields for uploading an image of their favorite character and setting options.

[1030] Step 2:

[1031] Users upload an image of their favorite character to their device. They then set their preferences for the nail design, such as color, style, and level of simplicity. This input data (image data and preference settings) is used as the initial data for the next step.

[1032] Step 3:

[1033] The emotion engine starts working and analyzes the input data to recognize the user's emotional state. The input data may include the user's facial image data and voice data during activities. The emotion engine analyzes this data and identifies the user's emotion (e.g., "happiness," "sadness," "surprise," etc.).

[1034] Step 4:

[1035] The device sends the image data and preferences entered by the user, as well as the emotional state recognized by the emotion engine, as data packets to the server. Communication is typically securely carried out over the Internet.

[1036] Step 5:

[1037] The server receives the data packets sent from the terminal, and the received image data, preference settings, and recognized emotional state are passed on to the next analysis process.

[1038] Step 6:

[1039] The server launches an image analysis module to analyze the image data. The image analysis module uses machine learning algorithms and image recognition technology to extract features such as color, shape, and motif.

[1040] Step 7:

[1041] The server inputs extracted feature data such as color, shape, and motif, along with the user's preference settings and recognized emotional state, into a generative AI model. The generative AI model generates multiple nail designs based on this data. The generated designs are set up so that the motif of the user's favorite idol is hidden upon closer inspection, and the color tone and style of the design are adjusted according to the user's emotional state.

[1042] Step 8:

[1043] The server sends multiple nail designs generated by the generative AI model to the device as data packets, in a format that can be viewed by the user.

[1044] Step 9:

[1045] The device displays the received nail design data in a list format to the user, allowing the user to compare and check multiple designs from the list.

[1046] Step 10:

[1047] The user checks the generated design and requests regeneration if necessary. The regeneration request is sent to the server in the form of another design being generated.

[1048] Step 11:

[1049] The server receives the regeneration request and runs the process again to generate a new design. Once the new design is generated, it sends the data back to the device and redisplays it.

[1050] Step 12:

[1051] The user selects the final design they like and downloads it using the appropriate save option displayed on their device.

[1052] Step 13:

[1053] The device saves the selected nail design in a format for download (e.g. PNG, JPEG, PDF, etc.) The saved design data can be used to take to a nail salon or as a guide for self-nail design.

[1054] In this way, each step corresponds to the user's preferences and emotional state, and the process is carried out to automatically generate and provide top-quality personalized nail designs.

[1055] Example 2

[1056] 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."

[1057] In the modern nail design market, many users desire personalized designs based on their preferences and emotional state. However, conventional systems face challenges in recognizing users' diverse emotional states and adjusting designs accordingly, making it difficult to provide optimal designs for each individual user. Furthermore, if users are dissatisfied with a generated design, the process for requesting a regeneration is often complicated. This results in poor usability and dissatisfaction for many users.

[1058] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1059] In this invention, the server includes a means for recognizing a user's emotional state, a means for adjusting a nail design based on the recognized emotional state, and a means for using a generative AI model to generate a nail design based on the extracted features. This allows a design to be generated by incorporating the user's emotional state into its composition. Furthermore, automatic adjustment of the motif and color tone of the user's favorite character included in the generated design can increase user satisfaction. Furthermore, adding a function for easily generating and providing different designs in response to a regeneration request improves the user experience and eliminates the cumbersome regeneration procedure.

[1060] "User" means an individual who intends to use the system to generate a nail design.

[1061] "Image data" refers to image files of favorite characters or idols uploaded by users.

[1062] "Preference settings" include individual specifications such as the color tone and style of the nail design desired by the user.

[1063] "Means for receiving" refers to a method for obtaining image data and preference settings from a user as input.

[1064] "Means for analysis" refers to the method of analyzing the received image data and extracting features such as color, shape, and motif.

[1065] "Emotional state" is data that indicates the user's emotions, extracted from the user's facial expressions, voice data, etc.

[1066] "Means for recognition" refers to a method for analyzing a user's emotional state and classifying it into a specific emotional category.

[1067] "Adjusting means" refers to methods of changing the color tone or style of a nail design based on a perceived emotional state.

[1068] "Means for generating" refers to a method for using an AI model to generate nail designs based on the extracted features and the user's preferences and emotional state.

[1069] "Means for providing" refers to a method for displaying the generated nail design to the user and making it viewable.

[1070] A "regeneration request" refers to a request to generate a different design again for a design that the user does not like.

[1071] "Means for saving" refers to a method for saving the generated nail design in a file format for later use.

[1072] "Outputable format" refers to a file format in which the generated nail design is suitable for use at a nail salon or for self-nail design.

[1073] The present invention is a system for users to create personalized nail designs according to their preferences and emotions. The system is broadly composed of the following main components:

[1074] User devices: desktop computers, laptops, tablets, smartphones, etc.

[1075] Server: A cloud-based server system containing the generative AI model

[1076] Emotion Engine: An engine for analyzing and recognizing user emotions

[1077] The operation of the system will now be described in detail.

[1078] User device roles

[1079] First, the user launches the nail design generation application on their device. They upload an image of their favorite character and set their desired nail design preferences. The emotion engine acquires the user's facial expressions and voice data on the device and recognizes their emotional state.

[1080] Server Roles

[1081] The device sends input data and emotional state to a server. The server uses an image analysis module to analyze the received image data and extract features such as color, shape, and distinctive motifs. A generative AI model then generates a nail design based on the extracted features, the user's preference settings, and the user's emotional state. The generated nail design is individually adjusted in color and style depending on the user's emotional state.

[1082] System Operation

[1083] The server sends the generated nail design to the terminal, which displays the result to the user. If the user is dissatisfied with the result, the server can generate a different design and provide it again by making a regeneration request.

[1084] Specific operation examples

[1085] For example, if a user uploads an image of "Idol X" and requests a nail design to match that image, the system will recognize that the user is in a "joy" emotional state. In this case, the system will generate a nail design incorporating bright colors and positive design elements to reflect the user's joy. This provides a unique and personalized design that combines the user's emotional state with the characteristics of their favorite character.

[1086] Prompt Sentence Examples

[1087] You can simulate real-world behavior by feeding the following prompts into the generative AI model:

[1088] "You're a fan of idol X. Imagine a situation that makes you feel particularly happy. Based on that emotion, generate a brightly colored nail design with idol X as the motif."

[1089] The system can improve user satisfaction by recognizing the user's emotional state and generating personalized nail designs based on it.

[1090] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1091] Step 1:

[1092] The user launches the nail design generation application on their device. An interface is displayed for the user to upload image data of their favorite character. The user selects the character image file and sets preferences such as color tone and style. The input is the image data of the favorite character and preferences for the desired nail design, and the output is a state in which these input data are ready to be passed to the next processing step.

[1093] Step 2:

[1094] The emotion engine acquires the user's facial expression and voice data and recognizes their emotional state. Specifically, it uses the device's camera and microphone to collect the user's facial expressions and voice in real time. The input is the user's facial expression data and voice data, and the output is data that classifies the recognized emotional state into categories. The data is classified into specific emotional categories such as "happiness," "sadness," "surprise," and "calm."

[1095] Step 3:

[1096] The device sends the user's input data (image data and preference settings) and the emotional state recognized by the emotion engine to the server. The input here is the user's preference data and the recognized emotional data, and the output is that these data are sent to the server. It is required that the device transmits the data accurately to the server.

[1097] Step 4:

[1098] The server analyzes the image data it receives. An image analysis module within the server analyzes the image data and extracts color tones, shapes, distinctive motifs, etc. The input is the image data sent from the device, and the output is the extracted image feature data. Specifically, the process uses an image recognition algorithm to extract and analyze each element of the image.

[1099] Step 5:

[1100] A generative AI model on the server generates nail designs based on the extracted features, the user's preference settings, and the recognized emotional state. The input is feature data, user preference information, and emotional state data, and the output is the generated nail design. The AI ​​model fine-tunes the color tone and style depending on the user's emotional state.

[1101] Step 6:

[1102] The server sends the generated nail design to the terminal. The input is the generated nail design data, and the output is receiving the design data on the terminal side. The server sends the design data to the terminal in an appropriate format.

[1103] Step 7:

[1104] The terminal displays the received nail designs to the user in a list format. The user confirms the generated designs. The input is the nail design data sent from the server, and the output is a list of designs displayed on the user's screen. The user previews the generated designs at this stage.

[1105] Step 8:

[1106] If the user does not like the design, they can request a regeneration. The device sends the regeneration request to the server. The input is the user's regeneration request, and the output is a regeneration instruction sent to the server. The server generates a new design and sends it to the device again.

[1107] Step 9:

[1108] At the final decision stage, the user selects the final design they like, and the device provides the selected design in a storable format. The input is the design selected by the user, and the output is the saved design data. The user can download this data and use it at a nail salon or for self-nail care.

[1109] (Application example 2)

[1110] 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."

[1111] Conventional nail design generation systems generate designs without considering the user's emotional state, resulting in insufficient personalized suggestions. This makes it impossible to provide the highly satisfying, individualized designs desired by users. Furthermore, the nail design regeneration function does not reflect the user's emotional state, making it difficult to fully meet the user's needs.

[1112] The specific processing by the specific 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 receiving image data and preference settings from a user, means for using an emotion engine that recognizes the user's emotions, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using an AI model that generates a nail design based on the extracted features and the recognized emotion, and means for providing the generated nail design to the user. This makes it possible to automatically generate and provide a personalized nail design that reflects the user's emotional state.

[1113] "User terminal" means a device used by a User, including a smartphone, tablet, laptop, or desktop computer.

[1114] "Image data" refers to image files uploaded by users, including images of their favorite idols or characters.

[1115] "Preference settings" refers to individual preference information such as the color tone and style of the nail design desired by the user.

[1116] The "emotion engine" is a module for recognizing and analyzing the user's emotional state, and has the ability to classify emotions through facial expression analysis, voice analysis, etc.

[1117] "Feature extraction" refers to the process of analyzing and extracting attributes such as color, shape, and distinctive motifs from image data.

[1118] An "AI model" is a model that uses artificial intelligence and includes algorithms that generate new nail designs based on feature extraction and sentiment analysis.

[1119] "Nail designs" are designs or patterns for the purpose of decorating fingertips, which are generated and individually provided based on the user's preferences and feelings.

[1120] A "regeneration request" is an action in which a user is not satisfied with an already generated nail design and requests the system to generate a new design.

[1121] The "nail salon format" is digital data in a format that allows a professional nail artist to apply the generated nail design.

[1122] The "self-nail format" is digital data in a format that allows the user to create the generated nail design at home.

[1123] "Server" means a cloud-based computer system that includes hardware and software for processing data sent from user devices and generating and providing nail designs using AI models.

[1124] The system that realizes this invention mainly consists of the following components: a user terminal, an emotion engine, and a server. The detailed functions and processing of each component are explained below.

[1125] System configuration and program processing

[1126] 1. User Device:

[1127] The user device is a device used by the user, such as a smartphone, tablet, laptop, or desktop computer. This device collects image data from the user and works with the emotion engine to analyze the user's emotional state. It also transmits the data from the device to the server and provides the generated nail design to the user.

[1128] 2. Emotion Engine:

[1129] The emotion engine is a module that recognizes emotions by analyzing the user's facial expressions and voice data. This is achieved using Microsoft Azure's Face API and Amazon Rekognition. The engine classifies emotions into categories such as "happiness," "sadness," "surprise," and "calmness." For example, if a user smiles into the smartphone camera, the emotion engine will recognize this as "happiness."

[1130] 3. Server:

[1131] The server is a cloud-based computer system that processes data sent from user devices. The server has the following main functions:

[1132] Processing and storage of received data: Receives and temporarily stores image data and preference settings sent by the user, as well as the emotional state recognized by the emotion engine.

[1133] Image analysis module: Analyzes image data using Google Cloud Vision API and other tools to extract features such as color, shape, and motif.

[1134] AI model design generation: A custom AI model using TensorFlow or PyTorch generates novel nail designs based on extracted features, the user's preference settings, and the perceived emotional state. For example, based on an image of "Idol X" and the emotion "joy," the model might incorporate bright colors and positive design elements.

[1135] Providing results: The generated nail design is sent to the user's device and the results are provided to the user.

[1136] Specific examples

[1137] For example, if a user uploads an image of "Popular Artist X" and requests a nail design that matches that image, the system will further recognize that the user is in an emotional state of "joy." In this case, the system will generate a nail design that incorporates bright colors and positive design elements to reflect the user's joy. The prompt sentence to be input into the generative AI model in this example is as follows:

[1138] "A user uploads a cheerful image of popular artist X, and they are in the emotional state of 'joy.' Extract the color, shape, and distinctive motifs from the image and generate a nail design that incorporates positive design elements in cheerful tones."

[1139] In this way, the present invention is a system that automatically generates and provides personalized nail designs that reflect the user's emotional state, and is capable of providing a service that is highly satisfying to users.

[1140] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1141] Step 1: Start the user terminal and enter data

[1142] The user launches the application and uploads image data of their favorite idol or character on the main screen. The user inputs their preferred settings, such as the color tone and style of their nail design, and provides the app with a face photo and voice data to recognize their emotional state. In this step, the application obtains "image data," "preferred settings," and "emotional data" as input data. These data are then sent to the next step.

[1143] Step 2: Emotional state analysis by the emotion engine

[1144] The device uses an emotion engine to analyze the user's emotional state based on the facial photo and voice data provided by the user. Specifically, facial expressions are recognized using Microsoft Azure's Face API, and voice data is analyzed through Amazon Rekognition. For example, the emotional state may be recognized as "joy." The input data is a "face photo" and "voice data," and the output is an "emotional state."

[1145] Step 3: Sending data

[1146] The device sends the user's input data ("image data," "preferred settings") and the "emotional state" recognized by the emotion engine to the server. The server receives this data and temporarily stores it. It receives "image data," "preferred settings," and "emotional state" as input data and sends them to the server.

[1147] Step 4: Image analysis and feature extraction

[1148] On the server side, the image analysis module uses the Google Cloud Vision API to analyze the image data and extract features such as color, shape, and motif. Specifically, it analyzes the image data at the pixel level to identify dominant color tones, shape patterns, and unique motifs. For example, the color blue and a star-shaped motif are extracted from an image of "Idol X." It uses "image data" as input data and obtains "feature data" as output.

[1149] Step 5: Generate nail designs using AI models

[1150] An AI model on the server generates new nail designs based on the extracted "feature data," the user's "preference settings," and their "emotional state." This is done using a custom model using TensorFlow and PyTorch. For example, a nail design incorporating bright colors and positive design elements is generated based on the color "blue," a "star-shaped motif," and an emotional state of "joy." The input data are "feature data," "preference settings," and "emotional state," and the output is a "generated nail design."

[1151] Step 6: Providing the generated results

[1152] The server sends the generated "nail design" to the terminal, which then displays the design proposals to the user in a list format. The user can then confirm the generated design. The input data is the "generated nail design," and the output is a "list display of designs."

[1153] Step 7: Verify and regenerate users

[1154] The user can check the generated design and request regeneration if necessary. In the case of regeneration, a different design is generated based on the new feature data and sent again by the server to the device. In this step, the "regeneration request" is received as input data, and the "generated nail design" is obtained again.

[1155] Step 8: Decide on the final design and output

[1156] The user finally selects the design they like, and the device displays the option to provide the selected design in a format suitable for nail salons or self-nail care. The user saves the final design data and downloads it as needed. The device receives the "final design selection" as input data and provides the "nail salon format" or "self-nail format" as output.

[1157] The above is an explanation of the processing steps of the program implemented based on the patent, as well as the specific operations and inputs / outputs of each.

[1158] 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.

[1159] 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.

[1160] 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.

[1161] [Fourth embodiment]

[1162] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1163] 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.

[1164] 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).

[1165] 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.

[1166] 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.

[1167] 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).

[1168] 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.

[1169] 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.

[1170] 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.

[1171] 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.

[1172] 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.

[1173] 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.

[1174] 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."

[1175] The system of the present invention allows users to easily and conveniently enjoy nail designs of their favorite idols or characters. The system automatically generates and provides nail designs using an AI model when the user provides the system with specific image data and preferred settings.

[1176] System configuration

[1177] The system consists of the following main components:

[1178] User devices: desktop computers, laptops, tablets, smartphones, etc.

[1179] Server: A cloud-based server system containing the AI ​​model

[1180] Program processing (natural language)

[1181] The system operates in the following steps:

[1182] 1. Receiving user input data

[1183] The user launches the nail design generation application on the device.

[1184] An interface will appear that allows users to upload an image of their favorite character.

[1185] Users upload image data and set preferences such as the color and style of the nail design they want.

[1186] 2. Sending input data

[1187] The device sends the image data and user preferences to a server, usually over the Internet.

[1188] 3. Image analysis and feature extraction

[1189] The server then enters the phase of analyzing the received image data.

[1190] The server's image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs.

[1191] 4. Nail design generation

[1192] The AI ​​model on the server generates multiple nail designs based on the extracted features and the user's preferences.

[1193] The generated designs look generic at first glance, but upon closer inspection you'll see that motifs of your favorite character have been cleverly incorporated.

[1194] 5. Providing the generated results

[1195] The server returns the generated nail designs to the terminal.

[1196] The device displays a list of nail designs to the user, which is the first time the user sees the designs.

[1197] 6. User Verification and Regeneration

[1198] Users will have the ability to review the generated design and request a regeneration if necessary.

[1199] If the user wishes to regenerate, a request to generate a new design is sent to the server.

[1200] 7. Final design and output

[1201] Users choose the design they like.

[1202] The device will then present you with the option to download the selected design in a format suitable for taking to a nail salon or for self-nail application.

[1203] The user saves the final design data.

[1204] Specific examples

[1205] For example, consider a case where a user uploads an image of "Idol X" and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "Pastel" in the color settings. The system receives the image data and performs image analysis on the server to extract specific colors and symbols. The AI ​​model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X."

[1206] In this way, the system of the present invention allows users to easily enjoy unique and personalized nail designs.

[1207] The processing flow will be explained below.

[1208] Step 1:

[1209] The user launches the nail design generation application on their device. When the application is launched, a user interface appears, presenting input fields for uploading an image of their favorite character and setting options.

[1210] Step 2:

[1211] Users upload an image of their favorite character to their device. They then set their preferences for the nail design, such as color, style, and level of simplicity. This input data (image data and preference settings) is used as the initial data for the next step.

[1212] Step 3:

[1213] The device sends the image data and user preferences as data packets to a server, typically via secure internet communication.

[1214] Step 4:

[1215] The server receives the data packets sent from the device, and the received image data and preference settings are passed on to the next analysis process.

[1216] Step 5:

[1217] The server launches an image analysis module to analyze the image data. The image analysis module uses machine learning algorithms and image recognition technology to extract features such as color, shape, and motif.

[1218] Step 6:

[1219] The server inputs the extracted feature data, such as color, shape, and motif, into a generative AI model. The generative AI model generates multiple nail designs based on this feature data and the user's preferences. The generated designs are set up so that, upon closer inspection, the motif of the user's favorite idol is hidden.

[1220] Step 7:

[1221] The server sends multiple nail designs generated by the generative AI model to the device as data packets, in a format that can be viewed by the user.

[1222] Step 8:

[1223] The device displays the received nail design data in a list format to the user, allowing the user to compare and check multiple designs from the list.

[1224] Step 9:

[1225] The user checks the generated design and requests regeneration if necessary. The regeneration request is sent to the server in the form of another design being generated.

[1226] Step 10:

[1227] The server receives the regeneration request and runs the process again to generate a new design. Once the new design is generated, it sends the data back to the device and redisplays it.

[1228] Step 11:

[1229] The user selects the final design they like and downloads it using the appropriate save option displayed on their device.

[1230] Step 12:

[1231] The device saves the selected nail design in a format for download (e.g. PNG, JPEG, PDF, etc.) The saved design data can be used to take to a nail salon or as a guide for self-nail design.

[1232] In this way, each step is tailored to the user's preferences and goes through a process to automatically generate and provide top-quality nail designs.

[1233] Example 1

[1234] 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."

[1235] The problem that this invention aims to solve is to provide a system that allows users to easily enjoy unique and personalized nail designs that incorporate elements of their favorite idols or characters, and also to provide a highly convenient system that can respond to changes in users' preferences and additional requests, and has regeneration functions and flexibility in saving and outputting.

[1236] 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.

[1237] In this invention, the server includes means for receiving image data and preference settings from a user, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using a generative AI model to generate nail designs based on the extracted features, means for inputting a prompt to the generative AI model, means for providing the generated nail designs to the user, means for generating different nail designs in response to a regeneration request and providing them again to the user, and means for saving the generated nail designs and providing them in a format that can be output. This allows users to easily generate and regenerate personalized nail designs incorporating elements of their favorite idols, and further save and output them.

[1238] "Image data" refers to visual information such as photographs and illustrations uploaded by users.

[1239] "Preference settings" refers to information about individual preferences, such as colors and design styles, specified by the user.

[1240] "Means for extracting features" refers to technology that uses AI models and algorithms to analyze and extract features such as color, shape, and motifs from image data.

[1241] A "generative AI model" refers to an artificial intelligence model that generates new nail designs based on extracted features and user preferences.

[1242] A "prompt sentence" refers to an input sentence that provides specific instructions or conditions to a generative AI model.

[1243] "Regeneration Request" refers to a request to generate a new design when a user is not satisfied with an existing design.

[1244] "Outputable format" means saving the generated nail design and providing it in a printable format (e.g. PNG, JPEG) for use in a nail salon or for self-nail design.

[1245] "Device" refers to an electronic device used by a user, such as a desktop computer, laptop, tablet, or smartphone.

[1246] "Server" refers to the computer system on which the cloud-based system, including the AI ​​model, runs.

[1247] The present invention is a system that allows users to easily create nail designs incorporating elements of their favorite idols or characters. The system includes a process in which a user provides specific image data and preferred settings, and an AI model is used to automatically generate and provide nail designs.

[1248] System configuration

[1249] The system consists of the following main components:

[1250] User devices: desktop computers, laptops, tablets, smartphones, etc.

[1251] Server: A cloud-based server system containing the AI ​​model

[1252] Program processing

[1253] The program of this system operates as follows.

[1254] Receiving user input data

[1255] The user launches the nail design generation application on their device. The application displays an interface for uploading an image of their favorite character. The user uploads the image data and sets preferences such as the color and style of the desired nail design.

[1256] Sending input data

[1257] The device sends the image data and user preferences to a server, usually over the Internet.

[1258] Image analysis and feature extraction

[1259] The server then enters the analysis phase of the received image data. The server's image analysis module analyzes the image data and uses deep learning technology to extract features such as color, shape, and unique motifs.

[1260] Nail design generation

[1261] The generative AI model on the server generates multiple nail designs based on the extracted features and the user's preferences. Specifically, the extracted data is used as a prompt. For example, a prompt could be, "Generate a pastel-toned nail design incorporating the colors and motifs of idol X."

[1262] Providing generated results

[1263] The server returns the generated nail designs to the terminal, which displays the nail designs to the user in a list format, allowing the user to confirm each design.

[1264] Verify and regenerate users

[1265] The user is given the ability to review the generated design and request a regeneration if necessary, and the server will generate a new design upon request.

[1266] Final design decision and output

[1267] The user selects a design they like. The device displays an option to download the selected design in a format suitable for taking to a nail salon or for self-nail care. The user saves the final design data.

[1268] Specific example explanation

[1269] For example, consider a case where a user uploads an image of "Idol X" and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "Pastel" in the color settings. The system receives the image data and performs image analysis on the server to extract specific colors and symbols. The generative AI model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X."

[1270] Prompt Sentence Examples

[1271] "Create a pastel-colored nail design based on a photo of idol X. Subtly incorporate motifs of your favorite idol into the design."

[1272] In this way, the system of the present invention allows users to easily enjoy unique and personalized nail designs.

[1273] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1274] Step 1:

[1275] The user launches the nail design generation application on their device. The application displays an interface for uploading an image of their favorite character. The user taps the "Upload Image" button and selects an image of their favorite character from their gallery. Options for color and style selection are then displayed, allowing the user to make the settings.

[1276] Input: User-selected image data and preferred settings (color tone, style).

[1277] Output: Send the prepared image data and your preferred settings to the server.

[1278] Step 2:

[1279] The device sends the image data and preferred settings entered by the user to a server, usually over the Internet. When the user taps the "Send" button, an app on the device consolidates the data and sends it over the Internet to the server.

[1280] Input: Ready image data and your preferred settings.

[1281] Output: Data sent to server completed.

[1282] Step 3:

[1283] The server then enters the analysis phase of the received image data. The server's image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs. Specifically, it uses a deep learning model to extract features such as color and shape.

[1284] Input: Image data received by the server.

[1285] Output: Data with extracted features such as color, shape, and motif.

[1286] Step 4:

[1287] The server-based generative AI model generates multiple nail designs based on the extracted features and the user's preferences, using the extracted data as prompts, such as "Generate a pastel nail design incorporating the colors and motifs of idol X."

[1288] Input: Parsed feature data and user preference data.

[1289] Output: Generated multiple nail design data.

[1290] Step 5:

[1291] The server sends the generated nail designs back to the device. The device application receives this data and displays a list-style design selection screen on the GUI. The user can swipe to view multiple designs.

[1292] Input: Each generated nail design data.

[1293] Output: Multiple nail designs displayed on the user's device.

[1294] Step 6:

[1295] The user can review the generated design and request a regeneration if necessary. The regeneration request is sent to the server and the process of generating a new design is repeated. When the user taps the "Regenerate" button, the request is sent to the server.

[1296] Input: The user's regeneration request.

[1297] Output: Generation and presentation of new nail design data.

[1298] Step 7:

[1299] The user selects a design they like. The device displays an option to download the selected design in a format suitable for taking to a nail salon or for self-nail care. When the user taps the "Download" button, the device saves the design data.

[1300] Input: Selected nail design.

[1301] Output: The final nail design data saved on your device.

[1302] (Application example 1)

[1303] 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."

[1304] The present invention relates to a system that allows users to easily create and visually confirm individual nail designs based on their favorite characters or idols. Conventional nail design creation methods have faced challenges such as communication gaps between nail technicians and users, and the difficulty of reviewing designs in real time. Additionally, there is a lack of means for customers to intuitively understand and adjust specific designs.

[1305] 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.

[1306] In this invention, the server includes means for receiving image data and preference settings from a user, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using a generative AI model to generate a nail design based on the extracted features, means for providing the generated nail design to the user, and means for displaying the generated nail design in real time through the smart glasses, thereby enabling the user to check the generated nail design in real time through the smart glasses and make adjustments in collaboration with the manicurist.

[1307] "User" means an individual who uses the system to create and review nail designs.

[1308] "Image data" refers to image files of favorite characters, idols, etc. provided by users.

[1309] "Preference settings" is information that indicates specific design requests, such as the color tone and style of the nail design desired by the user.

[1310] "Characteristics such as color, shape, and motif" are visual features analyzed from image data and serve as materials for nail design.

[1311] A "generative AI model" is an artificial intelligence model that automatically generates nail designs based on image data and the user's preferences.

[1312] "Smart glasses" are wearable devices that are glasses-type devices equipped with a display that can display information in real time.

[1313] "Real-time" is a term that refers to processing and reactions occurring almost immediately, with results being displayed immediately.

[1314] A "regeneration request" is an instruction to request the AI ​​model to generate a new design when the user is dissatisfied with the existing nail design or wants a new design.

[1315] The system of the present invention allows users to create and view their favorite nail designs in real time. The system is configured using a user terminal, a server, and smart glasses.

[1316] System configuration

[1317] 1. User Device

[1318] User devices include smartphones, tablets, desktop computers, and laptops.

[1319] It provides an interface for users to input image data and preference settings.

[1320] 2. Server

[1321] The cloud-based server analyzes the received image data and generates nail designs using a generative AI model.

[1322] The server has the ability to extract features such as color, shape, and motif based on the received image data and user preferences.

[1323] After feature extraction, the generative AI model automatically generates multiple nail designs.

[1324] Generated nail designs can also be regenerated upon request, allowing you to regenerate different designs.

[1325] 3. Smart Glasses

[1326] The smart glasses include a display that displays the generated nail designs to the user in real time.

[1327] Users can check the nail design generated through the smart glasses by overlaying it on the image of their hands.

[1328] Program processing (natural language)

[1329] The user launches a nail design generation application on their device. They upload image data of their favorite character or idol and select their preferred color and style. The device then sends this data to the server. The server analyzes the image, extracts features, and generates a nail design using a generative AI model. The generated nail design is sent back from the server to the device and simultaneously displayed on the smart glasses. The user can view the design in real time through the smart glasses and make any adjustments in consultation with the manicurist.

[1330] Technology and hardware used

[1331] AI models: Machine learning frameworks such as TensorFlow and PyTorch

[1332] Cloud services: AWS, Google Cloud, Microsoft Azure, etc.

[1333] Smart glasses: Google Glass, Microsoft HoloLens, etc.

[1334] User devices: iOS, Android, Windows, macOS

[1335] Specific examples

[1336] For example, consider the case where a user uploads an image of their favorite character, "Idol X," and requests a pastel-toned nail design to match the image. In this case, the user uploads the image of "Idol X" to the system via their device and selects "pastel" in the color setting. The server receives the image data, and the AI ​​model uses these features to generate a pastel-toned nail design that subtly incorporates motifs from "Idol X." The generated nail design is displayed in real time on the user's hand via smart glasses.

[1337] Prompt Sentence Examples

[1338] Upload an image of "Idol X" and generate a nail design with a pastel design.

[1339] In this way, the system of the present invention allows users to create and check nail designs easily and intuitively.

[1340] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1341] Step 1:

[1342] A user launches a nail design generation application on their device. They upload an image of their favorite character or idol and input their preferred settings (e.g., color tone and style). The device then receives and temporarily stores the image data and preferred settings.

[1343] Step 2:

[1344] The device sends the image data and user preferences entered by the user to the server. This communication is typically over the Internet. The device sends the uploaded image data and user preferences as an HTTP request.

[1345] Step 3:

[1346] The server analyzes the image data it receives and extracts features such as color, shape, and motif. The server's image analysis module applies an image processing algorithm (e.g., CNN) to the received image data, converts the extracted features into an internal format, and saves them.

[1347] Input: Image data received by the server

[1348] Output: Extracted feature data

[1349] Step 4:

[1350] The server generates nail designs using a generative AI model based on the extracted feature data and the user's preference settings. The AI ​​model (e.g., using TensorFlow or PyTorch) receives the features and preference settings as prompts and generates nail design images.

[1351] Input: extracted feature data and preference settings

[1352] Output: Generated nail design

[1353] Step 5:

[1354] The server returns the generated nail design to the user's device and also transmits it to the smart glasses so that it can be displayed in real time.The server's communication module sends the design data as an HTTP response and simultaneously transmits it to the smart glasses in a compatible format.

[1355] Input: Generated nail design

[1356] Output: Nail design displayed on user device and smart glasses

[1357] Step 6:

[1358] The user checks the generated nail design in real time through the smart glasses. The user checks the design and requests regeneration if necessary. This input is sent back to the server via the terminal.

[1359] Input: Nail design displayed on smart glasses

[1360] Output: User confirmation and regeneration request

[1361] Step 7:

[1362] The server receives the regeneration request and regenerates a new nail design. The regenerated nail design is then sent to the user device and smart glasses. The server then uses the AI ​​model to generate a different nail design and sends it through the endpoint.

[1363] Input: Regeneration request

[1364] Output: Regenerated nail design

[1365] Step 8:

[1366] The user selects their final nail design and saves it on the device, which then displays an option to download the final design in a printable format for use at a nail salon or for self-nail care.

[1367] Input: Final selection by user

[1368] Output: Saved final nail design

[1369] Through these processing steps, users can easily and intuitively create, check, and save unique nail designs.

[1370] 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.

[1371] The system of the present invention allows users to easily and conveniently enjoy nail designs of their favorite idols or characters. Furthermore, by combining it with an emotion engine that recognizes the user's emotional state and adjusts the nail design based on that emotion, it is possible to propose more personalized designs.

[1372] System configuration

[1373] The system consists of the following main components:

[1374] User devices: desktop computers, laptops, tablets, smartphones, etc.

[1375] Server: A cloud-based server system containing the AI ​​model

[1376] Emotion Engine: An engine for analyzing and recognizing user emotions

[1377] Program processing (natural language)

[1378] The system operates in the following steps:

[1379] 1. Receiving user input data

[1380] The user launches the nail design generation application on the device.

[1381] An interface will appear that allows users to upload an image of their favorite character.

[1382] Users upload image data and set preferences such as the color and style of the nail design they want.

[1383] 2. Recognizing emotional states

[1384] The emotion engine analyzes the image data uploaded by the user, as well as the voice and facial expression data while the user is using the app, to recognize the user's emotional state.

[1385] The recognized emotions are classified into categories such as "happiness," "sadness," "surprise," and "calmness."

[1386] 3. Sending input data

[1387] The terminal transmits the user's input data (image data and preference settings) and the emotional state recognized by the emotion engine to the server.

[1388] 4. Image analysis and feature extraction

[1389] The server then enters the phase of analyzing the received image data.

[1390] The image analysis module analyzes the image data and extracts features such as color, shape, and unique motifs.

[1391] 5. Nail design generation

[1392] The server-based AI model generates nail designs based on the extracted features, the user's preference settings, and the perceived emotional state.

[1393] The generated design is set up so that, upon closer inspection, motifs of the favorite idol are hidden. The color tone and style of the design are adjusted according to the emotional state.

[1394] 6. Providing the generated results

[1395] The server transmits the generated nail design to the terminal.

[1396] The device displays a list of nail designs to the user, where the user can review the designs.

[1397] 7. User Verification and Regeneration

[1398] The user can review the generated design and request a regeneration if necessary, which sends a request to the server to generate another design.

[1399] 8. Final design and output

[1400] The user selects the final design they like.

[1401] The device will then display an option to download the selected design in a format suitable for salon or self-nail use.

[1402] The user saves the final design data.

[1403] Specific examples

[1404] For example, if a user uploads an image of "Idol X" and requests a nail design that matches that image, the system will recognize that the user is in a "joy" emotional state. In this case, the system will generate a nail design incorporating bright colors and positive design elements to reflect the user's joy. As a result, the generated nail design combines the user's emotional state with the characteristics of the idol, providing a more personalized and optimal design.

[1405] In this way, the system of the present invention can improve user satisfaction by automatically generating and providing unique and personalized nail designs while recognizing and reflecting the user's emotional state.

[1406] The processing flow will be explained below.

[1407] Step 1:

[1408] The user launches the nail design generation application on their device. When the application is launched, a user interface appears, presenting input fields for uploading an image of their favorite character and setting options.

[1409] Step 2:

[1410] Users upload an image of their favorite character to their device. They then set their preferences for the nail design, such as color, style, and level of simplicity. This input data (image data and preference settings) is used as the initial data for the next step.

[1411] Step 3:

[1412] The emotion engine starts working and analyzes the input data to recognize the user's emotional state. The input data may include the user's facial image data and voice data during activities. The emotion engine analyzes this data and identifies the user's emotion (e.g., "happiness," "sadness," "surprise," etc.).

[1413] Step 4:

[1414] The device sends the image data and preferences entered by the user, as well as the emotional state recognized by the emotion engine, as data packets to the server. Communication is typically securely carried out over the Internet.

[1415] Step 5:

[1416] The server receives the data packets sent from the terminal, and the received image data, preference settings, and recognized emotional state are passed on to the next analysis process.

[1417] Step 6:

[1418] The server launches an image analysis module to analyze the image data. The image analysis module uses machine learning algorithms and image recognition technology to extract features such as color, shape, and motif.

[1419] Step 7:

[1420] The server inputs extracted feature data such as color, shape, and motif, along with the user's preference settings and recognized emotional state, into a generative AI model. The generative AI model generates multiple nail designs based on this data. The generated designs are set up so that the motif of the user's favorite idol is hidden upon closer inspection, and the color tone and style of the design are adjusted according to the user's emotional state.

[1421] Step 8:

[1422] The server sends multiple nail designs generated by the generative AI model to the device as data packets, in a format that can be viewed by the user.

[1423] Step 9:

[1424] The device displays the received nail design data in a list format to the user, allowing the user to compare and check multiple designs from the list.

[1425] Step 10:

[1426] The user checks the generated design and requests regeneration if necessary. The regeneration request is sent to the server in the form of another design being generated.

[1427] Step 11:

[1428] The server receives the regeneration request and runs the process again to generate a new design. Once the new design is generated, it sends the data back to the device and redisplays it.

[1429] Step 12:

[1430] The user selects the final design they like and downloads it using the appropriate save option displayed on their device.

[1431] Step 13:

[1432] The device saves the selected nail design in a format for download (e.g. PNG, JPEG, PDF, etc.) The saved design data can be used to take to a nail salon or as a guide for self-nail design.

[1433] In this way, each step corresponds to the user's preferences and emotional state, and the process is carried out to automatically generate and provide top-quality personalized nail designs.

[1434] Example 2

[1435] 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."

[1436] In the modern nail design market, many users desire personalized designs based on their preferences and emotional state. However, conventional systems face challenges in recognizing users' diverse emotional states and adjusting designs accordingly, making it difficult to provide optimal designs for each individual user. Furthermore, if users are dissatisfied with a generated design, the process for requesting a regeneration is often complicated. This results in poor usability and dissatisfaction for many users.

[1437] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1438] In this invention, the server includes a means for recognizing a user's emotional state, a means for adjusting a nail design based on the recognized emotional state, and a means for using a generative AI model to generate a nail design based on the extracted features. This allows a design to be generated by incorporating the user's emotional state into its composition. Furthermore, automatic adjustment of the motif and color tone of the user's favorite character included in the generated design can increase user satisfaction. Furthermore, adding a function for easily generating and providing different designs in response to a regeneration request improves the user experience and eliminates the cumbersome regeneration procedure.

[1439] "User" means an individual who intends to use the system to generate a nail design.

[1440] "Image data" refers to image files of favorite characters or idols uploaded by users.

[1441] "Preference settings" include individual specifications such as the color tone and style of the nail design desired by the user.

[1442] "Means for receiving" refers to a method for obtaining image data and preference settings from a user as input.

[1443] "Means for analysis" refers to the method of analyzing the received image data and extracting features such as color, shape, and motif.

[1444] "Emotional state" is data that indicates the user's emotions, extracted from the user's facial expressions, voice data, etc.

[1445] "Means for recognition" refers to a method for analyzing a user's emotional state and classifying it into a specific emotional category.

[1446] "Adjusting means" refers to methods of changing the color tone or style of a nail design based on a perceived emotional state.

[1447] "Means for generating" refers to a method for using an AI model to generate nail designs based on the extracted features and the user's preferences and emotional state.

[1448] "Means for providing" refers to a method for displaying the generated nail design to the user and making it viewable.

[1449] A "regeneration request" refers to a request to generate a different design again for a design that the user does not like.

[1450] "Means for saving" refers to a method for saving the generated nail design in a file format for later use.

[1451] "Outputable format" refers to a file format in which the generated nail design is suitable for use at a nail salon or for self-nail design.

[1452] The present invention is a system for users to create personalized nail designs according to their preferences and emotions. The system is broadly composed of the following main components:

[1453] User devices: desktop computers, laptops, tablets, smartphones, etc.

[1454] Server: A cloud-based server system containing the generative AI model

[1455] Emotion Engine: An engine for analyzing and recognizing user emotions

[1456] The operation of the system will now be described in detail.

[1457] User device roles

[1458] First, the user launches the nail design generation application on their device. They upload an image of their favorite character and set their desired nail design preferences. The emotion engine acquires the user's facial expressions and voice data on the device and recognizes their emotional state.

[1459] Server Roles

[1460] The device sends input data and emotional state to a server. The server uses an image analysis module to analyze the received image data and extract features such as color, shape, and distinctive motifs. A generative AI model then generates a nail design based on the extracted features, the user's preference settings, and the user's emotional state. The generated nail design is individually adjusted in color and style depending on the user's emotional state.

[1461] System Operation

[1462] The server sends the generated nail design to the terminal, which displays the result to the user. If the user is dissatisfied with the result, the server can generate a different design and provide it again by making a regeneration request.

[1463] Specific operation examples

[1464] For example, if a user uploads an image of "Idol X" and requests a nail design to match that image, the system will recognize that the user is in a "joy" emotional state. In this case, the system will generate a nail design incorporating bright colors and positive design elements to reflect the user's joy. This provides a unique and personalized design that combines the user's emotional state with the characteristics of their favorite character.

[1465] Prompt Sentence Examples

[1466] You can simulate real-world behavior by feeding the following prompts into the generative AI model:

[1467] "You're a fan of idol X. Imagine a situation that makes you feel particularly happy. Based on that emotion, generate a brightly colored nail design with idol X as the motif."

[1468] The system can improve user satisfaction by recognizing the user's emotional state and generating personalized nail designs based on it.

[1469] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1470] Step 1:

[1471] The user launches the nail design generation application on their device. An interface is displayed for the user to upload image data of their favorite character. The user selects the character image file and sets preferences such as color tone and style. The input is the image data of the favorite character and preferences for the desired nail design, and the output is a state in which these input data are ready to be passed to the next processing step.

[1472] Step 2:

[1473] The emotion engine acquires the user's facial expression and voice data and recognizes their emotional state. Specifically, it uses the device's camera and microphone to collect the user's facial expressions and voice in real time. The input is the user's facial expression data and voice data, and the output is data that classifies the recognized emotional state into categories. The data is classified into specific emotional categories such as "happiness," "sadness," "surprise," and "calm."

[1474] Step 3:

[1475] The device sends the user's input data (image data and preference settings) and the emotional state recognized by the emotion engine to the server. The input here is the user's preference data and the recognized emotional data, and the output is that these data are sent to the server. It is required that the device transmits the data accurately to the server.

[1476] Step 4:

[1477] The server analyzes the image data it receives. An image analysis module within the server analyzes the image data and extracts color tones, shapes, distinctive motifs, etc. The input is the image data sent from the device, and the output is the extracted image feature data. Specifically, the process uses an image recognition algorithm to extract and analyze each element of the image.

[1478] Step 5:

[1479] A generative AI model on the server generates nail designs based on the extracted features, the user's preference settings, and the recognized emotional state. The input is feature data, user preference information, and emotional state data, and the output is the generated nail design. The AI ​​model fine-tunes the color tone and style depending on the user's emotional state.

[1480] Step 6:

[1481] The server sends the generated nail design to the terminal. The input is the generated nail design data, and the output is receiving the design data on the terminal side. The server sends the design data to the terminal in an appropriate format.

[1482] Step 7:

[1483] The terminal displays the received nail designs to the user in a list format. The user confirms the generated designs. The input is the nail design data sent from the server, and the output is a list of designs displayed on the user's screen. The user previews the generated designs at this stage.

[1484] Step 8:

[1485] If the user does not like the design, they can request a regeneration. The device sends the regeneration request to the server. The input is the user's regeneration request, and the output is a regeneration instruction sent to the server. The server generates a new design and sends it to the device again.

[1486] Step 9:

[1487] At the final decision stage, the user selects the final design they like, and the device provides the selected design in a storable format. The input is the design selected by the user, and the output is the saved design data. The user can download this data and use it at a nail salon or for self-nail care.

[1488] (Application example 2)

[1489] 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."

[1490] Conventional nail design generation systems generate designs without considering the user's emotional state, resulting in insufficient personalized suggestions. This makes it impossible to provide the highly satisfying, individualized designs desired by users. Furthermore, the nail design regeneration function does not reflect the user's emotional state, making it difficult to fully meet the user's needs.

[1491] The specific processing by the specific 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 receiving image data and preference settings from a user, means for using an emotion engine that recognizes the user's emotions, means for analyzing the received image data and extracting features such as color, shape, and motif, means for using an AI model that generates a nail design based on the extracted features and the recognized emotion, and means for providing the generated nail design to the user. This makes it possible to automatically generate and provide a personalized nail design that reflects the user's emotional state.

[1492] "User terminal" means a device used by a User, including a smartphone, tablet, laptop, or desktop computer.

[1493] "Image data" refers to image files uploaded by users, including images of their favorite idols or characters.

[1494] "Preference settings" refers to individual preference information such as the color tone and style of the nail design desired by the user.

[1495] The "emotion engine" is a module for recognizing and analyzing the user's emotional state, and has the ability to classify emotions through facial expression analysis, voice analysis, etc.

[1496] "Feature extraction" refers to the process of analyzing and extracting attributes such as color, shape, and distinctive motifs from image data.

[1497] An "AI model" is a model that uses artificial intelligence and includes algorithms that generate new nail designs based on feature extraction and sentiment analysis.

[1498] "Nail designs" are designs or patterns for the purpose of decorating fingertips, which are generated and individually provided based on the user's preferences and feelings.

[1499] A "regeneration request" is an action in which a user is not satisfied with an already generated nail design and requests the system to generate a new design.

[1500] The "nail salon format" is digital data in a format that allows a professional nail artist to apply the generated nail design.

[1501] The "self-nail format" is digital data in a format that allows the user to create the generated nail design at home.

[1502] "Server" means a cloud-based computer system that includes hardware and software for processing data sent from user devices and generating and providing nail designs using AI models.

[1503] The system that realizes this invention mainly consists of the following components: a user terminal, an emotion engine, and a server. The detailed functions and processing of each component are explained below.

[1504] System configuration and program processing

[1505] 1. User Device:

[1506] The user device is a device used by the user, such as a smartphone, tablet, laptop, or desktop computer. This device collects image data from the user and works with the emotion engine to analyze the user's emotional state. It also transmits the data from the device to the server and provides the generated nail design to the user.

[1507] 2. Emotion Engine:

[1508] The emotion engine is a module that recognizes emotions by analyzing the user's facial expressions and voice data. This is achieved using Microsoft Azure's Face API and Amazon Rekognition. The engine classifies emotions into categories such as "happiness," "sadness," "surprise," and "calmness." For example, if a user smiles into the smartphone camera, the emotion engine will recognize this as "happiness."

[1509] 3. Server:

[1510] The server is a cloud-based computer system that processes data sent from user devices. The server has the following main functions:

[1511] Processing and storage of received data: Receives and temporarily stores image data and preference settings sent by the user, as well as the emotional state recognized by the emotion engine.

[1512] Image analysis module: Analyzes image data using Google Cloud Vision API and other tools to extract features such as color, shape, and motif.

[1513] AI model design generation: A custom AI model using TensorFlow or PyTorch generates novel nail designs based on extracted features, the user's preference settings, and the perceived emotional state. For example, based on an image of "Idol X" and the emotion "joy," the model might incorporate bright colors and positive design elements.

[1514] Providing results: The generated nail design is sent to the user's device and the results are provided to the user.

[1515] Specific examples

[1516] For example, if a user uploads an image of "Popular Artist X" and requests a nail design that matches that image, the system will further recognize that the user is in an emotional state of "joy." In this case, the system will generate a nail design that incorporates bright colors and positive design elements to reflect the user's joy. The prompt sentence to be input into the generative AI model in this example is as follows:

[1517] "A user uploads a cheerful image of popular artist X, and they are in the emotional state of 'joy.' Extract the color, shape, and distinctive motifs from the image and generate a nail design that incorporates positive design elements in cheerful tones."

[1518] In this way, the present invention is a system that automatically generates and provides personalized nail designs that reflect the user's emotional state, and is capable of providing a service that is highly satisfying to users.

[1519] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1520] Step 1: Start the user terminal and enter data

[1521] The user launches the application and uploads image data of their favorite idol or character on the main screen. The user inputs their preferred settings, such as the color tone and style of their nail design, and provides the app with a face photo and voice data to recognize their emotional state. In this step, the application obtains "image data," "preferred settings," and "emotional data" as input data. These data are then sent to the next step.

[1522] Step 2: Emotional state analysis by the emotion engine

[1523] The device uses an emotion engine to analyze the user's emotional state based on the facial photo and voice data provided by the user. Specifically, facial expressions are recognized using Microsoft Azure's Face API, and voice data is analyzed through Amazon Rekognition. For example, the emotional state may be recognized as "joy." The input data is a "face photo" and "voice data," and the output is an "emotional state."

[1524] Step 3: Sending data

[1525] The device sends the user's input data ("image data," "preferred settings") and the "emotional state" recognized by the emotion engine to the server. The server receives this data and temporarily stores it. It receives "image data," "preferred settings," and "emotional state" as input data and sends them to the server.

[1526] Step 4: Image analysis and feature extraction

[1527] On the server side, the image analysis module uses the Google Cloud Vision API to analyze the image data and extract features such as color, shape, and motif. Specifically, it analyzes the image data at the pixel level to identify dominant color tones, shape patterns, and unique motifs. For example, the color blue and a star-shaped motif are extracted from an image of "Idol X." It uses "image data" as input data and obtains "feature data" as output.

[1528] Step 5: Generate nail designs using AI models

[1529] An AI model on the server generates new nail designs based on the extracted "feature data," the user's "preference settings," and their "emotional state." This is done using a custom model using TensorFlow and PyTorch. For example, a nail design incorporating bright colors and positive design elements is generated based on the color "blue," a "star-shaped motif," and an emotional state of "joy." The input data are "feature data," "preference settings," and "emotional state," and the output is a "generated nail design."

[1530] Step 6: Providing the generated results

[1531] The server sends the generated "nail design" to the terminal, which then displays the design proposals to the user in a list format. The user can then confirm the generated design. The input data is the "generated nail design," and the output is a "list display of designs."

[1532] Step 7: Verify and regenerate users

[1533] The user can check the generated design and request regeneration if necessary. In the case of regeneration, a different design is generated based on the new feature data and sent again by the server to the device. In this step, the "regeneration request" is received as input data, and the "generated nail design" is obtained again.

[1534] Step 8: Decide on the final design and output

[1535] The user finally selects the design they like, and the device displays the option to provide the selected design in a format suitable for nail salons or self-nail care. The user saves the final design data and downloads it as needed. The device receives the "final design selection" as input data and provides the "nail salon format" or "self-nail format" as output.

[1536] The above is an explanation of the processing steps of the program implemented based on the patent, as well as the specific operations and inputs / outputs of each.

[1537] 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.

[1538] 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.

[1539] 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.

[1540] 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.

[1541] 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.

[1542] 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.

[1543] 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).

[1544] 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.

[1545] 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."

[1546] 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.

[1547] 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).

[1548] 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.

[1549] 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.

[1550] 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.

[1551] 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.

[1552] 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.

[1553] 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.

[1554] 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.

[1555] 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.

[1556] 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.

[1557] 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.

[1558] The following is further disclosed regarding the above embodiment.

[1559] (Claim 1)

[1560] means for receiving image data and preference settings from a user;

[1561] A means of analyzing the received image data and extracting features such as color, shape, and motif, and

[1562] Using an AI model to generate nail designs based on extracted features;

[1563] a means for providing the generated nail design to a user;

[1564] A system including:

[1565] (Claim 2)

[1566] 10. The system of claim 1, further comprising means for generating and re-offering to the user a different nail design in response to a re-generation request.

[1567] (Claim 3)

[1568] 10. The system of claim 1, further comprising means for saving the generated nail design and providing it in a format that can be output for use at a nail salon or for self-nail care.

[1569] "Example 1"

[1570] (Claim 1)

[1571] means for receiving image data and preference settings from a user;

[1572] A means of analyzing the received image data and extracting features such as color, shape, and motif, and

[1573] using a generative AI model to generate nail designs based on the extracted features;

[1574] a means for inputting a prompt to the generative AI model;

[1575] a means for providing the generated nail design to a user;

[1576] A means for generating different nail designs in response to a regeneration request and providing them to the user again;

[1577] means for saving and providing the generated nail design in a printable format;

[1578] A system including:

[1579] (Claim 2)

[1580] 10. The system of claim 1, further comprising means for a user to communicate with the system using a terminal to send and receive data.

[1581] (Claim 3)

[1582] 10. The system of claim 1, further comprising means for saving the nail design in a downloadable format in response to a user selection.

[1583] "Application Example 1"

[1584] (Claim 1)

[1585] means for receiving image data and preference settings from a user;

[1586] A means of analyzing the received image data and extracting features such as color, shape, and motif, and

[1587] using a generative AI model to generate nail designs based on the extracted features;

[1588] a means for providing the generated nail design to a user;

[1589] A means for displaying the nail design generated in real time through smart glasses;

[1590] A system including:

[1591] (Claim 2)

[1592] 10. The system of claim 1, further comprising means for generating and re-offering to the user a different nail design in response to a re-generation request.

[1593] (Claim 3)

[1594] 10. The system of claim 1, further comprising means for saving the generated nail design and providing it in a format that can be output for use at a nail salon or for self-nail care.

[1595] "Example 2: Combining Emotion Engines"

[1596] (Claim 1)

[1597] means for receiving image data and preference settings from a user;

[1598] A means of analyzing the received image data and extracting features such as color, shape, and motif, and

[1599] a means for recognizing the emotional state of a user;

[1600] a means for adjusting a nail design based on the perceived emotional state;

[1601] using a generative AI model to generate nail designs based on the extracted features;

[1602] a means for providing the generated nail design to a user;

[1603] A system including:

[1604] (Claim 2)

[1605] 10. The system of claim 1, further comprising means for generating and re-offering to the user a different nail design in response to a re-generation request.

[1606] (Claim 3)

[1607] 10. The system of claim 1, further comprising means for saving the generated nail design and providing it in a format that can be output for use at a nail salon or for self-nail care.

[1608] "Application example 2 when combining emotion engines"

[1609] (Claim 1)

[1610] means for receiving image data and preference settings from a user;

[1611] using an emotion engine to recognize the emotion of a user;

[1612] A means of analyzing the received image data and extracting characteristics such as color, shape, and motif;

[1613] using an AI model to generate nail designs based on the extracted features and the recognized emotions;

[1614] a means for providing the generated nail design to a user;

[1615] A system including:

[1616] (Claim 2)

[1617] 10. The system of claim 1, further comprising means for generating and re-offering to the user a different nail design in response to a re-generation request.

[1618] (Claim 3)

[1619] 10. The system of claim 1, further comprising means for saving the generated nail design and providing it in a format that can be output for use at a nail salon or for self-nail care. [Explanation of symbols]

[1620] 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. means for receiving image data and preference settings from a user; A means of analyzing the received image data and extracting features such as color, shape, and motif, and Using an AI model to generate nail designs based on extracted features; a means for providing the generated nail design to a user; A system including:

2. 10. The system of claim 1, further comprising means for generating and re-offering to the user different nail designs in response to a re-generation request.

3. 10. The system of claim 1, further comprising means for saving the generated nail design and providing it in a format that can be output for use at a nail salon or for self-nail care.

Images