System

Abstract

A system is provided.SOLUTION: A system, comprising: means for capturing an image; means for sending the captured image to a server; means for the server to analyze the image and extract features of a user's face or whole body; means for transforming the image into a costume play costume or character figure using a generative AI based on the extracted features; means for sending the transformed image back to a user device for display; and means for the user to save and share the image.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] The cosplay market has high barriers to entry for many people due to the high costs of costume production and photography. Furthermore, cosplay requires time and effort to prepare costumes and put on makeup, making it enjoyable for only a select few. For this reason, there is a demand for a way to enjoy cosplay more easily. [Means for solving the problem]

[0005] This invention provides a system that utilizes generative AI technology to allow users to easily enjoy cosplay. The system of the present invention includes a means for capturing an image, a means for transmitting the captured image to a server, a means for the server to analyze the image and extract the user's facial and full-body features, a means for converting the image into a cosplay costume or character appearance using generative AI based on the extracted features, a means for returning and displaying the converted image to a user terminal, and a means for the user to save and share the image. The system also includes a generative AI model for analyzing image features and an interface for the user to select a cosplay costume or character. In this way, a system that allows anyone to easily enjoy cosplay can be realized.

[0006] "Means for taking images" refers to the functionality that allows users to take their own photos using a smartphone or camera.

[0007] "Means for sending captured images to a server" refers to protocols and functions that allow users to upload captured image data to a server via the Internet.

[0008] "Means for the server to analyze images and extract the user's facial and full-body features" refers to the function in which the AI ​​model in the server analyzes the image data it receives and identifies important features such as facial features and the contours of the entire body.

[0009] "Means of using generative AI to convert images into cosplay costumes or character appearances based on extracted features" refers to a function that uses generative AI technology to convert a user's image into a specified cosplay costume or character based on analyzed features.

[0010] "Means for returning and displaying the converted image to the user's terminal" refers to the function of sending the image converted on the server side to the user's terminal and displaying the image on the terminal.

[0011] "Means for users to save and share images" refers to the ability for users to save the final image to their own device and share it on social media or other platforms.

[0012] "Generative AI model for analyzing image features" refers to an artificial intelligence model that is specially trained for image analysis and generation.

[0013] "Interface for users to select cosplay costumes and characters" refers to the graphical user interface (GUI) that allows users to select and specify various cosplay costumes and characters on the app. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention provides a system that uses AI generation technology to allow users to easily enjoy cosplay. Specific embodiments for carrying out the present invention will be described below.

[0036] First, the user launches the smartphone app, which provides an interface for selecting cosplay costumes and characters. Using this interface, the user selects the cosplay look they want to wear.

[0037] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the smartphone (device) captures the photo and temporarily saves the data in its internal storage. The user checks the image and taps the upload button to send it to the server.

[0038] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which then begins analysis. The AI ​​analysis module extracts the user's facial and body features from the image and identifies detailed feature points. These extraction results are used as base data for the generative AI model.

[0039] The server then uses the extracted features to convert the image into the cosplay costume and character selected by the user. The generative AI model uses this data to convert the user's image into the specified cosplay costume and character in real time. The converted image data is then sent back from the server to the user's device.

[0040] The device displays the converted image that the user has received, allowing the user to review it. The user can then review the converted image and request re-editing if necessary. For example, the user can send a request to change the color of the costume or the position of accessories.

[0041] The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it, allowing the process to be repeated, fine-tuning the image until the user is finally satisfied.

[0042] Finally, once a user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[0043] For example, a user can choose an anime character's costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing them to make fine adjustments until they are satisfied. In this way, users can easily generate high-quality cosplay images.

[0044] This system will significantly reduce the costs and effort required to enjoy cosplay, making it easier for many people to enjoy cosplay.

[0045] The processing flow will be explained below.

[0046] Step 1:

[0047] The user launches the smartphone app and opens the photo capture screen.

[0048] Step 2:

[0049] The user takes a photo of themselves using the smartphone camera.

[0050] Step 3:

[0051] The device temporarily stores the captured photos in its internal storage.

[0052] Step 4:

[0053] The user reviews the photos they have taken and, if they are satisfied, taps the "Upload" button.

[0054] Step 5:

[0055] The device encrypts the photo and sends it to the application server.

[0056] Step 6:

[0057] The server receives the uploaded photos and temporarily stores them in a database.

[0058] Step 7:

[0059] The server passes the photo data to the AI ​​analysis module and begins image analysis.

[0060] Step 8:

[0061] The AI ​​analysis module extracts the user's facial and body features from the photo and identifies detailed feature points.

[0062] Step 9:

[0063] The server generates base data for optimal costume transformation based on the extracted features.

[0064] Step 10:

[0065] Users select cosplay costumes and characters within the app.

[0066] Step 11:

[0067] The terminal transmits data of the costume and character selected by the user to the server.

[0068] Step 12:

[0069] The server combines the received selection information with the analysis results and inputs them into the image generation AI model.

[0070] Step 13:

[0071] Based on the analysis results and selected information, the generative AI model converts the user's original photo into the specified cosplay costume or character appearance.

[0072] Step 14:

[0073] The server temporarily stores the generated converted image and transmits it to the terminal.

[0074] Step 15:

[0075] The terminal displays the converted image received from the server to the user.

[0076] Step 16:

[0077] The user can check the converted image in real time and request re-editing if necessary.

[0078] Step 17:

[0079] The terminal transmits the user's re-editing request to the server.

[0080] Step 18:

[0081] The server again uses the generative AI model to generate a new transformed image based on the request and sends it to the device.

[0082] Step 19:

[0083] When the user is finally satisfied with the transformed image, he taps the "Save" button.

[0084] Step 20:

[0085] The device saves the converted image in local storage.

[0086] Step 21:

[0087] Users can share saved images on social media platforms.

[0088] Example 1

[0089] 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."

[0090] In recent years, cosplay has become popular among many people, but it takes a lot of time and money to actually purchase cosplay costumes, apply makeup, and take photos. Furthermore, the quality of cosplay depends on the individual's skill and financial resources, making it difficult for beginners to participate. Furthermore, there is a demand for a way to easily enjoy cosplay at home without attending an event. The purpose of this invention is to solve these problems.

[0091] 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.

[0092] In this invention, the server includes means for analyzing images and extracting the user's facial and whole-body features, means for converting the images into cosplay costumes or character appearances using a generation AI based on the extracted features, and means for returning and displaying the converted images to the user's terminal, thereby enabling users to easily generate and enjoy cosplay images.

[0093] The "means for taking pictures" refers to the functions and devices that allow a user to take pictures using a terminal.

[0094] The "means for transmitting captured images to a server" is a communication means for uploading image data from a user's terminal to a server.

[0095] "Means for the server to analyze images and extract the user's facial and body features" refers to analytical technologies and algorithms for identifying the user's facial and body features based on the image data received by the server.

[0096] "Method of transforming an image into a cosplay costume or character appearance using generative AI based on extracted features" refers to the process and technology of using analyzed feature data as input and a generative AI model to transform an image into any cosplay costume or character.

[0097] The "means for returning the converted image to the user terminal and displaying it" refers to a communication and display function for transmitting the generated cosplay image to the user terminal and displaying it on the terminal.

[0098] "Means for users to save and share images" refers to a function that allows users to save the final generated image on their device and easily share it on social media or other platforms.

[0099] The "means for a user to request re-editing of a converted image" refers to an interface and communication means for a user to request additional changes or modifications to a converted image and to repeat the generation process.

[0100] This invention provides a system that uses AI generation technology to allow users to easily enjoy cosplay. This system is composed of a terminal such as a smartphone, a server, and advanced AI analysis and generation functions. Specific embodiments for implementing the invention are described below.

[0101] First, the user launches the app on their smartphone. The app provides an interface for selecting cosplay costumes and characters. Using this interface, the user selects the cosplay look they want to wear. Next, the user takes a photo using the app's camera function. When the user taps the capture button, the device captures the photo and temporarily saves the data in internal storage. The user then checks the image they have taken and taps the upload button to send it to the server.

[0102] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to an AI analysis module, which begins analysis. This AI analysis module combines facial recognition and body feature extraction technologies. The server extracts the user's facial and body features through analysis and inputs them into a generative AI model (e.g., GANs or VAE). This generative AI model then converts the user's image into the specified cosplay costume or character in real time based on the extracted features.

[0103] The generated transformed image is sent from the server to the user's device. The device displays the received transformed image for the user to review. The user can review the transformed image and request re-editing if necessary. For example, the user can request corrections to the color of the costume or the position of accessories. The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it. This process can be repeated, allowing the user to make fine adjustments until they are finally satisfied.

[0104] Finally, once the user is satisfied with the resulting image, the device saves it to its internal storage, where it can be easily shared on social media platforms with just one tap within the app.

[0105] Specific operation example

[0106] For example, a user can choose an anime character's costume, take a photo, and the image is analyzed on the server and transformed into the character's appearance using a generative AI model. The result is sent back to the user's device in real time, allowing them to fine-tune it until they are satisfied. When the user is finally satisfied, the image is saved on their device and can be easily shared on social media.

[0107] An example of a prompt is, "Based on the photo below, please transform it into the specified anime character's appearance. Use blue hair, a red outfit, and a smiling face." In this way, users can easily generate high-quality cosplay images.

[0108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0109] Step 1:

[0110] The user launches the app on their smartphone and selects a cosplay costume and character.

[0111] Input: User actions

[0112] What it does: The user launches the app and selects a cosplay costume and character from the interface provided. The app saves the selection information to its internal storage.

[0113] Output: Selected cosplay costume and character information

[0114] Step 2:

[0115] The user takes a photo using the camera function within the app.

[0116] Input: A photo taken by the user

[0117] Specific operation: The user taps the capture button, the device camera takes a photo, and the captured image data is temporarily stored in the internal storage.

[0118] Output: Captured image data

[0119] Step 3:

[0120] The user checks the image they have taken, taps the upload button, and sends the image data to the server.

[0121] Input: Captured image data, user operations

[0122] Specific operation: After taking a photo, the user checks the image displayed on the screen and taps the upload button. The device then sends the image data to the server.

[0123] Output: Image data uploaded to the server

[0124] Step 4:

[0125] The server receives the uploaded images and temporarily stores them in a database.

[0126] Input: Uploaded image data

[0127] Specific operation: The server temporarily stores the received image data in a database. After storing it, it prepares it for analysis.

[0128] Output: Image data stored in a database

[0129] Step 5:

[0130] The server passes the image data to an AI analysis module, which extracts the user's facial and body features.

[0131] Input: Image data stored in a database

[0132] How it works: The server uses an AI analysis module to analyze the image data and extract the user's facial and body features. The analysis uses facial recognition technology and body feature extraction algorithms.

[0133] Output: Extracted feature data

[0134] Step 6:

[0135] Based on the extracted feature data, the server uses a generative AI model to convert the image into a cosplay costume or character appearance.

[0136] Input: Extracted feature data, selected cosplay costume and character information

[0137] How it works: The server uses generative AI models such as GANs and VAE to convert the user's image into the specified cosplay costume or character. During this process, the extracted feature data is used as base data.

[0138] Output: The converted image data

[0139] Step 7:

[0140] The server transmits the converted image data to the user's terminal, which displays it.

[0141] Input: Transformed image data

[0142] Specific operation: The server sends the converted image data back to the user's device, and the device displays the received image within the app.

[0143] Output: The converted image displayed on the user's device

[0144] Step 8:

[0145] The user may check the converted image and send a request for re-editing.

[0146] Input: Converted image data, user operations

[0147] Specific operation: The user checks the displayed converted image and, if any changes are necessary, sends a request for re-editing, such as inputting a prompt to modify the color of the costume or the position of accessories.

[0148] Output: Re-edit request (prompt text)

[0149] Step 9:

[0150] The server again uses the generative AI model to generate and resend a new transformed image based on the re-editing request.

[0151] Input: Reedit request, initial converted image data

[0152] Specific operation: The server re-runs the generative AI model based on the re-editing request to generate a new converted image, which is then sent back to the user's device.

[0153] Output: Re-edited image data, new image sent to user's device

[0154] Step 10:

[0155] When an image that the user is finally satisfied with is generated, the terminal stores the image.

[0156] Input: Final converted image data, user operations

[0157] Specific operation: The user confirms the final image they are satisfied with, and the device saves this image in its internal storage.

[0158] Output: Image data stored in internal storage

[0159] Step 11:

[0160] Users can share the saved images on social media etc.

[0161] Input: Image data stored in the internal storage, user operations

[0162] Specific operation: The user taps the share button within the app and posts the saved image to social media etc. The entire sharing process is designed to be easily performed within the app.

[0163] Output: Image data posted on social media etc.

[0164] (Application example 1)

[0165] 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."

[0166] Current cosplay try-on systems do not allow users to try on costumes or character appearances in real time before actually purchasing them. Furthermore, they lack an interface that allows for fine adjustments such as the color of the try-on image or the position of accessories, preventing users from achieving high satisfaction. A system that solves this issue and allows many users to easily enjoy a high-quality cosplay experience is needed.

[0167] 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.

[0168] In this invention, the server includes means for [analyzing an image and extracting the user's facial and whole-body features], means for [using generative AI to convert the image into a specific outfit or character appearance based on the extracted features], and means for [providing an interface for the user to adjust the color and position of accessories in the image]. This allows the user to try out specific outfits or character appearances in real time, make fine adjustments, and regenerate them as many times as necessary until they are satisfied.

[0169] The "means for taking an image" refers to a camera function and its control interface for capturing an image of the user's face or whole body.

[0170] The "means for transmitting captured images to a server" refers to a communication function and protocol for uploading acquired image data to a server via the Internet.

[0171] "Means for the server to analyze images and extract features of the user's face and body" refers to the process of using an AI analysis module to identify features of the user's face and body from uploaded images and store them in a database.

[0172] "Means of using generative AI to transform an image into a specific costume or character appearance based on extracted features" refers to the process in which a generative AI model transforms an image based on the user's feature point data and selected costume or character information.

[0173] The "means for returning and displaying the converted image to the user's terminal" refers to a communication and display function for sending the generated cosplay image to the user's device and displaying it on the application.

[0174] "Means for providing an interface for users to adjust the color of an image or the position of accessories" refers to an operation screen and control functions that allow users to fine-tune the color and position of clothing in an image.

[0175] "Means for regenerating images until the user is satisfied" refers to the process of reapplying the generative AI model in response to the user's adjustment requests to generate an updated image.

[0176] "Means for users to save and share images" refers to a function that allows users to save the final generated image on their device and share it on external services such as social networking sites.

[0177] MODE FOR CARRYING OUT THE INVENTION

[0178] The system for implementing this invention provides users with the experience of enjoying cosplay, and includes the following elements.

[0179] Hardware and Software

[0180] Hardware:

[0181] Smartphones (e.g. iPhone, Android devices)

[0182] Head-mounted displays (e.g., Oculus Quest, HTC Vive)

[0183] Server (for back-end processing)

[0184] software:

[0185] AI analysis module: TensorFlow, PyTorch

[0186] Image processing: OpenCV

[0187] Server: Node.js, Python (Flask, Django)

[0188] Front-end frameworks: React Native, Swift (iOS), Kotlin (Android)

[0189] Virtual / AR: ARKit (iOS), ARCore (Android)

[0190] System processing overview

[0191] Users launch the app on their smartphone, select the cosplay costume and character they want to try on, take a picture of themselves using the app's camera, and send the image to the server.

[0192] The server passes the received image to an AI analysis module, which extracts facial and full-body features. Based on these features, the generative AI model converts the image into the selected costume and character appearance, and sends it back to the user's device in real time. The returned image is displayed within the app for the user to review.

[0193] Additionally, users can use the provided interface to adjust the image's color, the position of decorations, etc. Then, they can again manipulate the generative AI model to generate a new image, and the process is repeated. Finally, once an image that satisfies the user is generated, they can save it using the app's save and share functions and share it on social media.

[0194] Specific examples

[0195] For example, let's say a user wants to choose a costume for a famous anime character. In that case, they launch the smartphone application and select the desired character costume from a list. Next, they take a photo of themselves using their camera and send the image to the server. The server then analyzes the image using an AI analysis module, extracts feature points, and converts them into the character's appearance using a generative AI model.

[0196] The converted image is sent back to the user's smartphone and can be viewed on the application. If the user wants to fine-tune the color of the outfit or the position of the accessories, they can easily do so using the interface, and then the generative AI model can generate a new image for them to view.

[0197] Prompt Sentence Examples

[0198] "Turn on your smartphone camera and select a specific character's outfit. Tap the capture button to view the converted image. Adjust the color tone, generate the final image again, and share it on social media."

[0199] This invention allows users to easily enjoy a high-quality cosplay experience, and allows them to adjust the details of color and design. The server performs image analysis and conversion in real time, allowing users to instantly see the results and optimize until they are satisfied.

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

[0201] Program processing steps

[0202] Step 1:

[0203] The user launches the smartphone application. Using the provided interface, the user selects the cosplay costume and character they want to try on. The input is information about the costume and character selected by the user, and the output is saved on the device.

[0204] Step 2:

[0205] The user takes a photo of themselves using the device's camera function. Images of the user's face and whole body are obtained as input, and the image data is temporarily saved in the device's internal storage as output. Specifically, the user taps the capture button, which activates the camera and takes the photo.

[0206] Step 3:

[0207] The user taps the upload button to send the captured image to the server. Image data stored on the device is obtained as input, and the image data is transferred to the server via the network as output. Specifically, the image file is sent to the server via an HTTP request.

[0208] Step 4:

[0209] The server passes the received image data to the AI ​​analysis module, which extracts the user's facial and whole-body features. The received image data is taken as input, and feature point data is generated as output. Specifically, the AI ​​analysis module uses TensorFlow and PyTorch to identify feature points within the image and store them in a database.

[0210] Step 5:

[0211] Based on the extracted feature point data, the server uses a generative AI model to convert the image into a specific costume or character appearance. The input is the feature point data and the costume and character information selected by the user, and the converted image data is generated as the output. Specifically, the generative AI model uses the feature point data to convert the image.

[0212] Step 6:

[0213] The server returns the converted image data to the user's device, which then displays it. The converted image data is obtained as input, and the converted image is displayed on the device's display as output. Specifically, the server sends the image data as an HTTP response, and the device displays the received image on the screen.

[0214] Step 7:

[0215] The user adjusts the color of the image and the position of decorations using the provided interface. The user's adjustment instructions are received as input, and the adjusted parameters are saved on the device as output. Specifically, the user operates the controls on the interface to make adjustments.

[0216] Step 8:

[0217] The server again uses the generative AI model to generate a new image based on the user's adjustment instructions and sends it to the user's device. The adjusted parameters are obtained as input, and adjusted image data is generated as output. Specifically, the server uses the adjustment parameters and feature point data to generate a new image using the generative AI model and send it to the device.

[0218] Step 9:

[0219] Once a final image that satisfies the user is generated, the user saves it to their device and shares it. The final image data is obtained as input, and the image is saved to the device's local storage as output, ready to be shared. Specifically, the user taps the save button, and the image data is saved to the device. The user can also tap the share button to upload the image to social media sites, etc.

[0220] 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.

[0221] This invention combines generative AI technology with an emotion engine to provide a system that allows users to easily enjoy cosplay. Specific embodiments for carrying out the invention will be described below.

[0222] First, the user launches the smartphone app. The app provides an interface for selecting cosplay costumes and characters. The app also has an emotion engine that recognizes emotions from the user's facial expressions and voice. Using this interface, the user can select the cosplay look they want to wear, or use the options suggested by the emotion engine.

[0223] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the smartphone (device) captures the photo and temporarily saves the data in its internal storage. The user checks the image and taps the upload button to send it to the server.

[0224] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which then begins analysis. The AI ​​analysis module extracts the user's facial and body features from the image and identifies detailed feature points. These extraction results are used as base data for the generative AI model.

[0225] The server then uses the extracted features to convert the image into the cosplay costume and character selected by the user. The generative AI model uses this data to convert the user's image into the specified cosplay costume and character in real time. The converted image data is then sent back from the server to the user's device.

[0226] The device displays the converted image that the user has received, allowing the user to review it. The user can then review the converted image and request re-editing if necessary. For example, the user can send a request to change the color of the costume or the position of accessories.

[0227] The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it, allowing the process to be repeated, fine-tuning the image until the user is finally satisfied.

[0228] The emotion engine analyzes the user's emotions from their facial expressions and voice and sends that data to the server. Based on the emotional data, the server can learn what kind of cosplay costumes and characters the user chooses, and make optimal suggestions for future selections.

[0229] Finally, once a user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[0230] For example, a user can choose an anime character costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing them to make fine adjustments until they are satisfied. An emotion engine then reads the user's facial expressions and optimizes the suggestions for the next cosplay. In this way, users can easily generate high-quality cosplay images.

[0231] This system will significantly reduce the cost and effort required to enjoy cosplay, making it easier for many people to enjoy cosplay. It will also take user emotions into consideration, making it possible to provide a more personalized experience.

[0232] The processing flow will be explained below.

[0233] Step 1:

[0234] The user launches the app on their smartphone and opens the photo-taking screen. The app has an interface for selecting cosplay costumes and characters, as well as an emotion engine.

[0235] Step 2:

[0236] The emotion engine acquires the user's facial information and voice data in real time and begins emotion analysis.

[0237] Step 3:

[0238] Based on the analysis results of the emotion engine, the device will suggest the most suitable cosplay costumes and characters for the user. The user can then follow the suggestions or choose their own preferred costumes and characters.

[0239] Step 4:

[0240] The user takes a photo of themselves using the smartphone camera.

[0241] Step 5:

[0242] The device temporarily stores the captured photos in its internal storage.

[0243] Step 6:

[0244] The user reviews the photos they have taken and, if they are satisfied, taps the "Upload" button.

[0245] Step 7:

[0246] The device encrypts the photo and sends it to the application server.

[0247] Step 8:

[0248] The server receives the uploaded photos and temporarily stores them in a database.

[0249] Step 9:

[0250] The server passes the photo data to the AI ​​analysis module and begins image analysis.

[0251] Step 10:

[0252] The AI ​​analysis module extracts the user's facial and body features from the photo and identifies detailed feature points.

[0253] Step 11:

[0254] The server generates base data for optimal costume transformation based on the extracted features.

[0255] Step 12:

[0256] The device receives the analysis results from the server and converts the image using a generative AI model based on the generated base data.

[0257] Step 13:

[0258] Based on the analysis results and selected information, the generative AI model converts the user's original photo into the specified cosplay costume or character appearance.

[0259] Step 14:

[0260] The server temporarily stores the generated converted image and transmits it to the terminal.

[0261] Step 15:

[0262] The terminal displays the converted image received from the server to the user.

[0263] Step 16:

[0264] The user can check the converted image in real time and request re-editing if necessary.

[0265] Step 17:

[0266] The terminal transmits the user's re-editing request to the server.

[0267] Step 18:

[0268] The server again uses the generative AI model to generate a new transformed image based on the request and sends it to the device.

[0269] Step 19:

[0270] When the user is finally satisfied with the transformed image, he taps the "Save" button.

[0271] Step 20:

[0272] The device saves the converted image in local storage.

[0273] Step 21:

[0274] The device transmits the emotion data analyzed by the emotion engine to the server.

[0275] Step 22:

[0276] The server learns the user's preferences based on the emotional data and reflects them in future suggestions.

[0277] Step 23:

[0278] Users can share saved images on social media platforms.

[0279] Example 2

[0280] 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."

[0281] Conventional cosplay experience provision systems require users to acquire costumes, wear them, and take photos themselves, which is time-consuming. Furthermore, the images must be manually edited, requiring specialized knowledge and skills, making it difficult for anyone to easily obtain high-quality cosplay images. Furthermore, the lack of personalized suggestions based on the user's emotions and preferences limits the user experience. Therefore, there is a need for a system that allows users to easily generate high-quality cosplay images and provides a personalized experience in the process.

[0282] 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.

[0283] In this invention, the server includes means for [analyzing images and extracting the user's facial and whole-body features], means for [using generative AI to convert the image into a cosplay costume or character appearance based on the extracted features], and means for [analyzing the user's facial expressions and voice using an emotion engine to suggest cosplay costumes and characters]. This enables [users to easily obtain high-quality cosplay images without requiring specialized knowledge or skills, and furthermore, to receive personalized suggestions tailored to each individual user].

[0284] "Means for taking images" means [a device or function that provides a camera function for users to take images of themselves].

[0285] "Means for sending captured images to a server" refers to a communication function that allows a user to send captured image data to a remote server.

[0286] "The means by which the server analyzes images and extracts the user's facial and body features" refers to an AI analysis module that identifies and analyzes the user's facial and body features from the image data received by the server.

[0287] "Means of using generative AI to transform images into cosplay costumes or character appearances based on extracted features" means "a function that uses a generative AI model to transform a user's image into a cosplay costume or character appearance in real time based on extracted features."

[0288] "Means for returning and displaying the converted image to the user's device" refers to the communication and display function for sending the image data converted by the generating AI to the user's device and displaying it on that device.

[0289] "Means for users to save and share images" refers to a function that allows users to save images they are satisfied with to internal storage and easily share them on social media, etc.

[0290] "A means of analyzing the user's facial expressions and voice using an emotion engine to suggest cosplay costumes and characters" means "a function that uses an emotion engine to analyze the user's facial expressions and voice data, and suggests appropriate cosplay costumes and characters based on the results."

[0291] "A means by which a user can submit a re-editing request and re-generate the image using the generative AI model" is [a process by which a user can request changes to an image and re-run the generative AI model to re-generate the image].

[0292] This invention is a system that allows users to easily enjoy cosplay, and combines generative AI technology with an emotion engine. To implement this invention, the following specific steps are taken.

[0293] First, the user launches the smartphone app, which provides an interface for selecting cosplay costumes and characters. The app also includes an emotion engine that recognizes emotions from the user's facial expressions and voice.

[0294] Using this interface, users can select the cosplay look they want to wear or use options suggested by the emotion engine, which will then make optimal suggestions based on the user's previous choices and facial expression data.

[0295] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the device captures the photo and temporarily saves the data in the internal storage. The user checks the captured image and taps the upload button to send it to the server.

[0296] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which extracts the user's facial and body features from the image and identifies detailed feature points.

[0297] Based on the extracted features, the server then uses a generative AI model to transform the user's image into the specified cosplay costume and character, which is designed to accurately reflect the user's features.

[0298] The converted image data is sent back from the server to the user's device. The device displays the converted image so that the user can review it. The user can review the converted image and request re-editing if necessary. For example, this could include changing the color of the costume or the position of accessories.

[0299] The server re-runs the generative AI model based on the user's re-editing request to generate a new transformed image, then re-submits the re-generated image. This process is repeated until the user is finally satisfied.

[0300] The emotion engine analyzes the user's emotions from their facial expressions and voice and sends that data to the server, which uses this data to learn what kind of cosplay costumes and characters the user chooses, and can make optimal suggestions the next time they choose.

[0301] Finally, once the user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[0302] For example, a user can choose an anime character costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing the user to make fine adjustments until satisfied. The emotion engine then reads the user's facial expressions and optimizes the suggestions for the next cosplay. In this way, users can easily generate high-quality cosplay images.

[0303] An example of a prompt is, "I would like you to select a cosplay costume of the anime character 'Naruto' and take a photo of it, and have it transformed in real time." This allows the server to generate a transformed image based on the user's request in real time and send it to the device.

[0304] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0305] Step 1:

[0306] The user launches the dedicated app.

[0307] Specific operation: The user taps the dedicated app icon on the smartphone to launch the application. The app's startup screen is displayed.

[0308] Step 2:

[0309] The user selects a cosplay.

[0310] How it works: Users select the character they want to become from a list of cosplay costumes and characters displayed within the app. The emotion engine may suggest the most suitable cosplay based on the user's past choices and facial expression data.

[0311] Input: User selection or emotion engine suggestion

[0312] Output: Data of selected cosplay characters and costumes

[0313] Step 3:

[0314] The user takes a photo.

[0315] Specific operation: The user takes a photo of themselves using the camera function in the app. When the user taps the capture button, the device acquires the photo data and temporarily stores it in the internal storage.

[0316] Input: A photo taken by the user

[0317] Output: Photo data temporarily saved in the internal storage

[0318] Step 4:

[0319] The user sends the photo to the server.

[0320] Specific operation: The user checks the photos they have taken and taps the upload button to send them to the server. The device uses its Internet connection to send the photo data to the server.

[0321] Input: Photo data stored on the device

[0322] Output: Photo data sent to the server

[0323] Step 5:

[0324] The server receives and stores the images.

[0325] Specific operation: The server receives the photos sent by the user and temporarily stores them in a database, which allows subsequent analysis and processing.

[0326] Input: Photo data sent from the device

[0327] Output: Photo data stored in a database

[0328] Step 6:

[0329] The server performs the AI ​​analysis.

[0330] How it works: The server passes the stored image data to the AI ​​analysis module, which then begins analyzing the image. This module extracts the user's facial and body features and identifies detailed feature points.

[0331] Input: Photo data stored in the database

[0332] Output: Extracted facial and body feature data

[0333] Step 7:

[0334] The server converts the image.

[0335] How it works: The server uses a generative AI model based on the extracted feature data to transform the user's image into the specified cosplay costume or character, accurately reflecting the user's features.

[0336] Input: Extracted facial and body feature data, selected cosplay character data

[0337] Output: Image data converted to cosplay

[0338] Step 8:

[0339] The server transmits the converted image to the user terminal.

[0340] Specific operation: The converted image data is sent from the server to the user's device, and the user can check the converted image in real time.

[0341] Input: Image data converted to cosplay

[0342] Output: The converted image data sent to the terminal

[0343] Step 9:

[0344] The device displays the image and accepts requests for re-editing.

[0345] Specific operation: The device displays the received converted image for the user to review. If the user needs to re-edit it, they can submit a re-edit request, such as changing the color of the costume or the position of accessories.

[0346] Input: Converted image data sent from the server

[0347] Output: User's edit request

[0348] Step 10:

[0349] The server will regenerate and resend.

[0350] Specific operation: The server re-runs the generative AI model based on the user's request to generate a new transformed image. It then sends the re-generated image back to the user's device. This process is repeated until the user is satisfied.

[0351] Input: User re-edit request

[0352] Output: Regenerated transformed image data

[0353] Step 11:

[0354] The emotion engine performs analysis and data transmission.

[0355] How it works: The emotion engine analyzes the user's emotions from their facial expressions and voice, and sends that data to the server, which uses it to make the next recommendation.

[0356] Input: User's facial expressions and voice data

[0357] Output: Sentiment analysis data

[0358] Step 12:

[0359] Save and share the final image.

[0360] How it works: Once a final image is created that the user is happy with, the device saves it to internal storage. This image can then be easily shared on social media platforms with just one tap within the app.

[0361] Input: Regenerated final transformed image data

[0362] Output: Final image data saved and shared

[0363] (Application example 2)

[0364] 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."

[0365] Conventional try-on systems and cosplay experiences require users to physically try on costumes, which can be time-consuming and expensive. Users typically spend a lot of time and effort searching for a costume that suits them best. Furthermore, sharing the results of a try-on with friends and family requires additional steps, such as taking photos and uploading them to social media. The present invention aims to solve these problems by providing a system that allows users to try on costumes more easily and quickly and share the results.

[0366] 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 capturing an image, means for transmitting the captured image to the server, means for the server to analyze the image and extract the user's facial and whole-body features, means for converting the image into an outfit or character appearance using a generative AI based on the extracted features, means for returning the converted image to the user terminal and displaying it, means for the user to save and share the image, and means for analyzing emotions from the user's facial expressions and voice using an emotion engine and suggesting outfits based on the emotions. This allows the user to quickly and easily try on outfits without actually physically wearing them, and to check and share the results in real time.

[0367] "Means for taking images" refers to a mechanism that allows a user to take still images or videos using a device such as a camera.

[0368] The "means for transmitting captured images to a server" refers to a method and mechanism for transferring captured image data to a remote server via a network.

[0369] "Means for the server to analyze the image and extract the user's facial and body features" refers to algorithms and computer programs that process the transmitted image data and identify the user's facial shape, body shape, and other features.

[0370] "Method of converting an image into a costume or character appearance using generative AI based on extracted features" refers to a technology that uses a generative AI model to virtually change an image into a costume or character appearance, using the user's facial and body features.

[0371] The "means for returning and displaying the converted image to the user terminal" is a mechanism for transmitting the converted image data to the user's device over the network and displaying it on the display of that device.

[0372] "Means for users to save and share images" refers to the mechanism by which the converted image data is saved in the user's device storage and then shared with others on platforms such as social media.

[0373] "A means of using an emotion engine to analyze emotions from a user's facial expressions and voice, and suggest outfits based on those emotions" is a technology that recognizes emotions from a user's facial expressions and voice data, and automatically suggests optimal outfits based on the results.

[0374] The present invention is a system that allows users to easily enjoy cosplaying as costumes and characters. Detailed embodiments of the invention are described below.

[0375] First, the user launches an application installed on a device such as a smartphone, tablet, or smart glasses. The application provides an interface for selecting costumes and characters. The user uses this interface to select the costume or character they want to try on. Once the selection is complete, the user takes a picture of themselves using the device's camera.

[0376] Once the image is captured, the device temporarily stores the image data in its internal storage. The image data is then sent over the network to a server, which analyzes the received image data and extracts the user's facial and body features, often using the dlib library.

[0377] Once the analysis is complete, a generative AI model transforms the image based on the extracted feature data. The generative AI model is implemented using deep learning frameworks such as Keras and TensorFlow, and converts the user's image into the specified outfit or character. An emotion engine is also used to analyze the user's emotions from facial expressions and voice data, and then suggests the optimal outfit based on those emotions.

[0378] The converted image data is sent back to the user's device from the server and displayed on the device's screen. The user can review the results and make further fine adjustments, such as the color of the outfit or the position of the accessories. The device then sends a re-editing request to the server, which then uses the generative AI model to generate and return a new converted image. This process is repeated until the user is satisfied.

[0379] Finally, once a satisfactory image is generated, it is saved in the device's internal storage. The image can then be shared on social media platforms with a single tap. The emotion engine also learns from the user's selection and emotion data to optimize future suggestions.

[0380] Below are some examples of specific usage scenarios and prompts:

[0381] Specific usage scenarios:

[0382] 1. The user wears smart glasses installed in a physical store.

[0383] 2. The camera in the smart glasses captures the user's image and the app performs emotion analysis.

[0384] 3. Emotional data is analyzed to show that the user has a happy expression, and the suggested outfit is a party dress.

[0385] 4. Once the user selects a dress, the generative AI overlays the dress onto the user's video in real time.

[0386] 5. Share your try-on results on social media.

[0387] Example prompt sentence:

[0388] Choose the perfect dress for your birthday party and generate a real-time overlay image that will make your user look happy and smiling.

[0389] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0390] Step 1:

[0391] A user launches an application installed on a device such as a smartphone, tablet, or smart glasses. Using the application's interface, the user selects the costume or character they want to try on. The input is the user's selection data, and the output is information about the selected costume or character.

[0392] Step 2:

[0393] The device's camera is used to capture images of the user. When the user taps the capture button, the device temporarily stores still images and videos captured from the camera in its internal storage. The input is the user's real-time video, and the output is the captured image data.

[0394] Step 3:

[0395] The terminal sends the temporarily stored image data to the server via the network. At this time, the image data is encoded into an appropriate format and sent using a protocol that takes security into consideration (e.g., HTTPS). The input is the image data, and the output is the data transfer status to the server.

[0396] Step 4:

[0397] The server analyzes the received image data and extracts the user's facial and body features. Specifically, it uses the dlib library to detect facial landmarks (feature points) and then identifies the user's facial and body features based on those landmarks. The input is the received image data, and the output is the extracted facial and body feature data.

[0398] Step 5:

[0399] The server uses a generative AI model based on the extracted feature data to convert the image into a costume or character appearance. This generative AI model is implemented using deep learning frameworks such as Keras and TensorFlow, and takes face and body shape data as input to generate an image converted into the specified costume or character. The input is feature data and costume information, and the output is the converted image data.

[0400] Step 6:

[0401] The converted image data is sent back to the user's device from the server and displayed on the device's screen, allowing the user to check the conversion results in real time. The input is the converted image data, and the output is the real-time image displayed on the user's device.

[0402] Step 7:

[0403] The user can check the conversion results through the application and request re-editing if necessary. Re-editing requests include changes to the color of the costume or the position of accessories. This request data is sent to the server. The input is the user's re-editing request, and the output is the request data sent to the server.

[0404] Step 8:

[0405] The server receives the re-editing request, again uses the generative AI model to generate a new transformed image and sends it back to the device. This process is repeated until the user is satisfied. The input is the re-editing request data, and the output is the newly transformed image data.

[0406] Step 9:

[0407] Finally, once a satisfactory image is generated, the device saves it to its internal storage. This image can then be shared on social media platforms with a single tap from within the application. The input is the final, verified image data, and the output is the saved image data and a link for sharing.

[0408] Examples:

[0409] Example prompt: "Choose the perfect dress for a birthday party and generate a real-time overlay image. The user will look happy and smiling."

[0410] 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.

[0411] 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.

[0412] 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.

[0413] [Second embodiment]

[0414] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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).

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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."

[0426] The present invention provides a system that uses AI generation technology to allow users to easily enjoy cosplay. Specific embodiments for carrying out the present invention will be described below.

[0427] First, the user launches the smartphone app, which provides an interface for selecting cosplay costumes and characters. Using this interface, the user selects the cosplay look they want to wear.

[0428] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the smartphone (device) captures the photo and temporarily saves the data in its internal storage. The user checks the image and taps the upload button to send it to the server.

[0429] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which then begins analysis. The AI ​​analysis module extracts the user's facial and body features from the image and identifies detailed feature points. These extraction results are used as base data for the generative AI model.

[0430] The server then uses the extracted features to convert the image into the cosplay costume and character selected by the user. The generative AI model uses this data to convert the user's image into the specified cosplay costume and character in real time. The converted image data is then sent back from the server to the user's device.

[0431] The device displays the converted image that the user has received, allowing the user to review it. The user can then review the converted image and request re-editing if necessary. For example, the user can send a request to change the color of the costume or the position of accessories.

[0432] The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it, allowing the process to be repeated, fine-tuning the image until the user is finally satisfied.

[0433] Finally, once a user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[0434] For example, a user can choose an anime character's costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing them to make fine adjustments until they are satisfied. In this way, users can easily generate high-quality cosplay images.

[0435] This system will significantly reduce the costs and effort required to enjoy cosplay, making it easier for many people to enjoy cosplay.

[0436] The processing flow will be explained below.

[0437] Step 1:

[0438] The user launches the smartphone app and opens the photo capture screen.

[0439] Step 2:

[0440] The user takes a photo of themselves using the smartphone camera.

[0441] Step 3:

[0442] The device temporarily stores the captured photos in its internal storage.

[0443] Step 4:

[0444] The user reviews the photos they have taken and, if they are satisfied, taps the "Upload" button.

[0445] Step 5:

[0446] The device encrypts the photo and sends it to the application server.

[0447] Step 6:

[0448] The server receives the uploaded photos and temporarily stores them in a database.

[0449] Step 7:

[0450] The server passes the photo data to the AI ​​analysis module and begins image analysis.

[0451] Step 8:

[0452] The AI ​​analysis module extracts the user's facial and body features from the photo and identifies detailed feature points.

[0453] Step 9:

[0454] The server generates base data for optimal costume transformation based on the extracted features.

[0455] Step 10:

[0456] Users select cosplay costumes and characters within the app.

[0457] Step 11:

[0458] The terminal transmits data of the costume and character selected by the user to the server.

[0459] Step 12:

[0460] The server combines the received selection information with the analysis results and inputs them into the image generation AI model.

[0461] Step 13:

[0462] Based on the analysis results and selected information, the generative AI model converts the user's original photo into the specified cosplay costume or character appearance.

[0463] Step 14:

[0464] The server temporarily stores the generated converted image and transmits it to the terminal.

[0465] Step 15:

[0466] The terminal displays the converted image received from the server to the user.

[0467] Step 16:

[0468] The user can check the converted image in real time and request re-editing if necessary.

[0469] Step 17:

[0470] The terminal transmits the user's re-editing request to the server.

[0471] Step 18:

[0472] The server again uses the generative AI model to generate a new transformed image based on the request and sends it to the device.

[0473] Step 19:

[0474] When the user is finally satisfied with the transformed image, he taps the "Save" button.

[0475] Step 20:

[0476] The device saves the converted image in local storage.

[0477] Step 21:

[0478] Users can share saved images on social media platforms.

[0479] Example 1

[0480] 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."

[0481] In recent years, cosplay has become popular among many people, but it takes a lot of time and money to actually purchase cosplay costumes, apply makeup, and take photos. Furthermore, the quality of cosplay depends on the individual's skill and financial resources, making it difficult for beginners to participate. Furthermore, there is a demand for a way to easily enjoy cosplay at home without attending an event. The purpose of this invention is to solve these problems.

[0482] 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.

[0483] In this invention, the server includes means for analyzing images and extracting the user's facial and whole-body features, means for converting the images into cosplay costumes or character appearances using a generation AI based on the extracted features, and means for returning and displaying the converted images to the user's terminal, thereby enabling users to easily generate and enjoy cosplay images.

[0484] The "means for taking pictures" refers to the functions and devices that allow a user to take pictures using a terminal.

[0485] The "means for transmitting captured images to a server" is a communication means for uploading image data from a user's terminal to a server.

[0486] "Means for the server to analyze images and extract the user's facial and body features" refers to analytical technologies and algorithms for identifying the user's facial and body features based on the image data received by the server.

[0487] "Method of transforming an image into a cosplay costume or character appearance using generative AI based on extracted features" refers to the process and technology of using analyzed feature data as input and a generative AI model to transform an image into any cosplay costume or character.

[0488] The "means for returning the converted image to the user terminal and displaying it" refers to a communication and display function for transmitting the generated cosplay image to the user terminal and displaying it on the terminal.

[0489] "Means for users to save and share images" refers to a function that allows users to save the final generated image on their device and easily share it on social media or other platforms.

[0490] The "means for a user to request re-editing of a converted image" refers to an interface and communication means for a user to request additional changes or modifications to a converted image and to repeat the generation process.

[0491] This invention provides a system that uses AI generation technology to allow users to easily enjoy cosplay. This system is composed of a terminal such as a smartphone, a server, and advanced AI analysis and generation functions. Specific embodiments for implementing the invention are described below.

[0492] First, the user launches the app on their smartphone. The app provides an interface for selecting cosplay costumes and characters. Using this interface, the user selects the cosplay look they want to wear. Next, the user takes a photo using the app's camera function. When the user taps the capture button, the device captures the photo and temporarily saves the data in internal storage. The user then checks the image they have taken and taps the upload button to send it to the server.

[0493] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to an AI analysis module, which begins analysis. This AI analysis module combines facial recognition and body feature extraction technologies. The server extracts the user's facial and body features through analysis and inputs them into a generative AI model (e.g., GANs or VAE). This generative AI model then converts the user's image into the specified cosplay costume or character in real time based on the extracted features.

[0494] The generated transformed image is sent from the server to the user's device. The device displays the received transformed image for the user to review. The user can review the transformed image and request re-editing if necessary. For example, the user can request corrections to the color of the costume or the position of accessories. The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it. This process can be repeated, allowing the user to make fine adjustments until they are finally satisfied.

[0495] Finally, once the user is satisfied with the resulting image, the device saves it to its internal storage, where it can be easily shared on social media platforms with just one tap within the app.

[0496] Specific operation example

[0497] For example, a user can choose an anime character's costume, take a photo, and the image is analyzed on the server and transformed into the character's appearance using a generative AI model. The result is sent back to the user's device in real time, allowing them to fine-tune it until they are satisfied. When the user is finally satisfied, the image is saved on their device and can be easily shared on social media.

[0498] An example of a prompt is, "Based on the photo below, please transform it into the specified anime character's appearance. Use blue hair, a red outfit, and a smiling face." In this way, users can easily generate high-quality cosplay images.

[0499] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0500] Step 1:

[0501] The user launches the app on their smartphone and selects a cosplay costume and character.

[0502] Input: User actions

[0503] What it does: The user launches the app and selects a cosplay costume and character from the interface provided. The app saves the selection information to its internal storage.

[0504] Output: Selected cosplay costume and character information

[0505] Step 2:

[0506] The user takes a photo using the camera function within the app.

[0507] Input: A photo taken by the user

[0508] Specific operation: The user taps the capture button, the device camera takes a photo, and the captured image data is temporarily stored in the internal storage.

[0509] Output: Captured image data

[0510] Step 3:

[0511] The user checks the image they have taken, taps the upload button, and sends the image data to the server.

[0512] Input: Captured image data, user operations

[0513] Specific operation: After taking a photo, the user checks the image displayed on the screen and taps the upload button. The device then sends the image data to the server.

[0514] Output: Image data uploaded to the server

[0515] Step 4:

[0516] The server receives the uploaded images and temporarily stores them in a database.

[0517] Input: Uploaded image data

[0518] Specific operation: The server temporarily stores the received image data in a database. After storing it, it prepares it for analysis.

[0519] Output: Image data stored in a database

[0520] Step 5:

[0521] The server passes the image data to an AI analysis module, which extracts the user's facial and body features.

[0522] Input: Image data stored in a database

[0523] How it works: The server uses an AI analysis module to analyze the image data and extract the user's facial and body features. The analysis uses facial recognition technology and body feature extraction algorithms.

[0524] Output: Extracted feature data

[0525] Step 6:

[0526] Based on the extracted feature data, the server uses a generative AI model to convert the image into a cosplay costume or character appearance.

[0527] Input: Extracted feature data, selected cosplay costume and character information

[0528] How it works: The server uses generative AI models such as GANs and VAE to convert the user's image into the specified cosplay costume or character. During this process, the extracted feature data is used as base data.

[0529] Output: The converted image data

[0530] Step 7:

[0531] The server transmits the converted image data to the user's terminal, which displays it.

[0532] Input: Transformed image data

[0533] Specific operation: The server sends the converted image data back to the user's device, and the device displays the received image within the app.

[0534] Output: The converted image displayed on the user's device

[0535] Step 8:

[0536] The user may check the converted image and send a request for re-editing.

[0537] Input: Converted image data, user operations

[0538] Specific operation: The user checks the displayed converted image and, if any changes are necessary, sends a request for re-editing, such as inputting a prompt to modify the color of the costume or the position of accessories.

[0539] Output: Re-edit request (prompt text)

[0540] Step 9:

[0541] The server again uses the generative AI model to generate and resend a new transformed image based on the re-editing request.

[0542] Input: Reedit request, initial converted image data

[0543] Specific operation: The server re-runs the generative AI model based on the re-editing request to generate a new converted image, which is then sent back to the user's device.

[0544] Output: Re-edited image data, new image sent to user's device

[0545] Step 10:

[0546] When an image that the user is finally satisfied with is generated, the terminal stores the image.

[0547] Input: Final converted image data, user operations

[0548] Specific operation: The user confirms the final image they are satisfied with, and the device saves this image in its internal storage.

[0549] Output: Image data stored in internal storage

[0550] Step 11:

[0551] Users can share the saved images on social media etc.

[0552] Input: Image data stored in the internal storage, user operations

[0553] Specific operation: The user taps the share button within the app and posts the saved image to social media etc. The entire sharing process is designed to be easily performed within the app.

[0554] Output: Image data posted on social media etc.

[0555] (Application example 1)

[0556] 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."

[0557] Current cosplay try-on systems do not allow users to try on costumes or character appearances in real time before actually purchasing them. Furthermore, they lack an interface that allows for fine adjustments such as the color of the try-on image or the position of accessories, preventing users from achieving high satisfaction. A system that solves this issue and allows many users to easily enjoy a high-quality cosplay experience is needed.

[0558] 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.

[0559] In this invention, the server includes means for [analyzing an image and extracting the user's facial and whole-body features], means for [using generative AI to convert the image into a specific outfit or character appearance based on the extracted features], and means for [providing an interface for the user to adjust the color and position of accessories in the image]. This allows the user to try out specific outfits or character appearances in real time, make fine adjustments, and regenerate them as many times as necessary until they are satisfied.

[0560] The "means for taking an image" refers to a camera function and its control interface for capturing an image of the user's face or whole body.

[0561] The "means for transmitting captured images to a server" refers to a communication function and protocol for uploading acquired image data to a server via the Internet.

[0562] "Means for the server to analyze images and extract features of the user's face and body" refers to the process of using an AI analysis module to identify features of the user's face and body from uploaded images and store them in a database.

[0563] "Means of using generative AI to transform an image into a specific costume or character appearance based on extracted features" refers to the process in which a generative AI model transforms an image based on the user's feature point data and selected costume or character information.

[0564] The "means for returning and displaying the converted image to the user's terminal" refers to a communication and display function for sending the generated cosplay image to the user's device and displaying it on the application.

[0565] "Means for providing an interface for users to adjust the color of an image or the position of accessories" refers to an operation screen and control functions that allow users to fine-tune the color and position of clothing in an image.

[0566] "Means for regenerating images until the user is satisfied" refers to the process of reapplying the generative AI model in response to the user's adjustment requests to generate an updated image.

[0567] "Means for users to save and share images" refers to a function that allows users to save the final generated image on their device and share it on external services such as social networking sites.

[0568] MODE FOR CARRYING OUT THE INVENTION

[0569] The system for implementing this invention provides users with the experience of enjoying cosplay, and includes the following elements.

[0570] Hardware and Software

[0571] Hardware:

[0572] Smartphones (e.g. iPhone, Android devices)

[0573] Head-mounted displays (e.g., Oculus Quest, HTC Vive)

[0574] Server (for back-end processing)

[0575] software:

[0576] AI analysis module: TensorFlow, PyTorch

[0577] Image processing: OpenCV

[0578] Server: Node.js, Python (Flask, Django)

[0579] Front-end frameworks: React Native, Swift (iOS), Kotlin (Android)

[0580] Virtual / AR: ARKit (iOS), ARCore (Android)

[0581] System processing overview

[0582] Users launch the app on their smartphone, select the cosplay costume and character they want to try on, take a picture of themselves using the app's camera, and send the image to the server.

[0583] The server passes the received image to an AI analysis module, which extracts facial and full-body features. Based on these features, the generative AI model converts the image into the selected costume and character appearance, and sends it back to the user's device in real time. The returned image is displayed within the app for the user to review.

[0584] Additionally, users can use the provided interface to adjust the image's color, the position of decorations, etc. Then, they can again manipulate the generative AI model to generate a new image, and the process is repeated. Finally, once an image that satisfies the user is generated, they can save it using the app's save and share functions and share it on social media.

[0585] Specific examples

[0586] For example, let's say a user wants to choose a costume for a famous anime character. In that case, they launch the smartphone application and select the desired character costume from a list. Next, they take a photo of themselves using their camera and send the image to the server. The server then analyzes the image using an AI analysis module, extracts feature points, and converts them into the character's appearance using a generative AI model.

[0587] The converted image is sent back to the user's smartphone and can be viewed on the application. If the user wants to fine-tune the color of the outfit or the position of the accessories, they can easily do so using the interface, and then the generative AI model can generate a new image for them to view.

[0588] Prompt Sentence Examples

[0589] "Turn on your smartphone camera and select a specific character's outfit. Tap the capture button to view the converted image. Adjust the color tone, generate the final image again, and share it on social media."

[0590] This invention allows users to easily enjoy a high-quality cosplay experience, and allows them to adjust the details of color and design. The server performs image analysis and conversion in real time, allowing users to instantly see the results and optimize until they are satisfied.

[0591] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0592] Program processing steps

[0593] Step 1:

[0594] The user launches the smartphone application. Using the provided interface, the user selects the cosplay costume and character they want to try on. The input is information about the costume and character selected by the user, and the output is saved on the device.

[0595] Step 2:

[0596] The user takes a photo of themselves using the device's camera function. Images of the user's face and whole body are obtained as input, and the image data is temporarily saved in the device's internal storage as output. Specifically, the user taps the capture button, which activates the camera and takes the photo.

[0597] Step 3:

[0598] The user taps the upload button to send the captured image to the server. Image data stored on the device is obtained as input, and the image data is transferred to the server via the network as output. Specifically, the image file is sent to the server via an HTTP request.

[0599] Step 4:

[0600] The server passes the received image data to the AI ​​analysis module, which extracts the user's facial and whole-body features. The received image data is taken as input, and feature point data is generated as output. Specifically, the AI ​​analysis module uses TensorFlow and PyTorch to identify feature points within the image and store them in a database.

[0601] Step 5:

[0602] Based on the extracted feature point data, the server uses a generative AI model to convert the image into a specific costume or character appearance. The input is the feature point data and the costume and character information selected by the user, and the converted image data is generated as the output. Specifically, the generative AI model uses the feature point data to convert the image.

[0603] Step 6:

[0604] The server returns the converted image data to the user's device, which then displays it. The converted image data is obtained as input, and the converted image is displayed on the device's display as output. Specifically, the server sends the image data as an HTTP response, and the device displays the received image on the screen.

[0605] Step 7:

[0606] The user adjusts the color of the image and the position of decorations using the provided interface. The user's adjustment instructions are received as input, and the adjusted parameters are saved on the device as output. Specifically, the user operates the controls on the interface to make adjustments.

[0607] Step 8:

[0608] The server again uses the generative AI model to generate a new image based on the user's adjustment instructions and sends it to the user's device. The adjusted parameters are obtained as input, and adjusted image data is generated as output. Specifically, the server uses the adjustment parameters and feature point data to generate a new image using the generative AI model and send it to the device.

[0609] Step 9:

[0610] Once a final image that satisfies the user is generated, the user saves it to their device and shares it. The final image data is obtained as input, and the image is saved to the device's local storage as output, ready to be shared. Specifically, the user taps the save button, and the image data is saved to the device. The user can also tap the share button to upload the image to social media sites, etc.

[0611] 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.

[0612] This invention combines generative AI technology with an emotion engine to provide a system that allows users to easily enjoy cosplay. Specific embodiments for carrying out the invention will be described below.

[0613] First, the user launches the smartphone app. The app provides an interface for selecting cosplay costumes and characters. The app also has an emotion engine that recognizes emotions from the user's facial expressions and voice. Using this interface, the user can select the cosplay look they want to wear, or use the options suggested by the emotion engine.

[0614] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the smartphone (device) captures the photo and temporarily saves the data in its internal storage. The user checks the image and taps the upload button to send it to the server.

[0615] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which then begins analysis. The AI ​​analysis module extracts the user's facial and body features from the image and identifies detailed feature points. These extraction results are used as base data for the generative AI model.

[0616] The server then uses the extracted features to convert the image into the cosplay costume and character selected by the user. The generative AI model uses this data to convert the user's image into the specified cosplay costume and character in real time. The converted image data is then sent back from the server to the user's device.

[0617] The device displays the converted image that the user has received, allowing the user to review it. The user can then review the converted image and request re-editing if necessary. For example, the user can send a request to change the color of the costume or the position of accessories.

[0618] The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it, allowing the process to be repeated, fine-tuning the image until the user is finally satisfied.

[0619] The emotion engine analyzes the user's emotions from their facial expressions and voice and sends that data to the server. Based on the emotional data, the server can learn what kind of cosplay costumes and characters the user chooses, and make optimal suggestions for future selections.

[0620] Finally, once a user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[0621] For example, a user can choose an anime character costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing them to make fine adjustments until they are satisfied. An emotion engine then reads the user's facial expressions and optimizes the suggestions for the next cosplay. In this way, users can easily generate high-quality cosplay images.

[0622] This system will significantly reduce the cost and effort required to enjoy cosplay, making it easier for many people to enjoy cosplay. It will also take user emotions into consideration, making it possible to provide a more personalized experience.

[0623] The processing flow will be explained below.

[0624] Step 1:

[0625] The user launches the app on their smartphone and opens the photo-taking screen. The app has an interface for selecting cosplay costumes and characters, as well as an emotion engine.

[0626] Step 2:

[0627] The emotion engine acquires the user's facial information and voice data in real time and begins emotion analysis.

[0628] Step 3:

[0629] Based on the analysis results of the emotion engine, the device will suggest the most suitable cosplay costumes and characters for the user. The user can then follow the suggestions or choose their own preferred costumes and characters.

[0630] Step 4:

[0631] The user takes a photo of themselves using the smartphone camera.

[0632] Step 5:

[0633] The device temporarily stores the captured photos in its internal storage.

[0634] Step 6:

[0635] The user reviews the photos they have taken and, if they are satisfied, taps the "Upload" button.

[0636] Step 7:

[0637] The device encrypts the photo and sends it to the application server.

[0638] Step 8:

[0639] The server receives the uploaded photos and temporarily stores them in a database.

[0640] Step 9:

[0641] The server passes the photo data to the AI ​​analysis module and begins image analysis.

[0642] Step 10:

[0643] The AI ​​analysis module extracts the user's facial and body features from the photo and identifies detailed feature points.

[0644] Step 11:

[0645] The server generates base data for optimal costume transformation based on the extracted features.

[0646] Step 12:

[0647] The device receives the analysis results from the server and converts the image using a generative AI model based on the generated base data.

[0648] Step 13:

[0649] Based on the analysis results and selected information, the generative AI model converts the user's original photo into the specified cosplay costume or character appearance.

[0650] Step 14:

[0651] The server temporarily stores the generated converted image and transmits it to the terminal.

[0652] Step 15:

[0653] The terminal displays the converted image received from the server to the user.

[0654] Step 16:

[0655] The user can check the converted image in real time and request re-editing if necessary.

[0656] Step 17:

[0657] The terminal transmits the user's re-editing request to the server.

[0658] Step 18:

[0659] The server again uses the generative AI model to generate a new transformed image based on the request and sends it to the device.

[0660] Step 19:

[0661] When the user is finally satisfied with the transformed image, he taps the "Save" button.

[0662] Step 20:

[0663] The device saves the converted image in local storage.

[0664] Step 21:

[0665] The device transmits the emotion data analyzed by the emotion engine to the server.

[0666] Step 22:

[0667] The server learns the user's preferences based on the emotional data and reflects them in future suggestions.

[0668] Step 23:

[0669] Users can share saved images on social media platforms.

[0670] Example 2

[0671] 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."

[0672] Conventional cosplay experience provision systems require users to acquire costumes, wear them, and take photos themselves, which is time-consuming. Furthermore, the images must be manually edited, requiring specialized knowledge and skills, making it difficult for anyone to easily obtain high-quality cosplay images. Furthermore, the lack of personalized suggestions based on the user's emotions and preferences limits the user experience. Therefore, there is a need for a system that allows users to easily generate high-quality cosplay images and provides a personalized experience in the process.

[0673] 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.

[0674] In this invention, the server includes means for [analyzing images and extracting the user's facial and whole-body features], means for [using generative AI to convert the image into a cosplay costume or character appearance based on the extracted features], and means for [analyzing the user's facial expressions and voice using an emotion engine to suggest cosplay costumes and characters]. This enables [users to easily obtain high-quality cosplay images without requiring specialized knowledge or skills, and furthermore, to receive personalized suggestions tailored to each individual user].

[0675] "Means for taking images" means [a device or function that provides a camera function for users to take images of themselves].

[0676] "Means for sending captured images to a server" refers to a communication function that allows a user to send captured image data to a remote server.

[0677] "The means by which the server analyzes images and extracts the user's facial and body features" refers to an AI analysis module that identifies and analyzes the user's facial and body features from the image data received by the server.

[0678] "Means of using generative AI to transform images into cosplay costumes or character appearances based on extracted features" means "a function that uses a generative AI model to transform a user's image into a cosplay costume or character appearance in real time based on extracted features."

[0679] "Means for returning and displaying the converted image to the user's device" refers to the communication and display function for sending the image data converted by the generating AI to the user's device and displaying it on that device.

[0680] "Means for users to save and share images" refers to a function that allows users to save images they are satisfied with to internal storage and easily share them on social media, etc.

[0681] "A means of analyzing the user's facial expressions and voice using an emotion engine to suggest cosplay costumes and characters" means "a function that uses an emotion engine to analyze the user's facial expressions and voice data, and suggests appropriate cosplay costumes and characters based on the results."

[0682] "A means by which a user can submit a re-editing request and re-generate the image using the generative AI model" is [a process by which a user can request changes to an image and re-run the generative AI model to re-generate the image].

[0683] This invention is a system that allows users to easily enjoy cosplay, and combines generative AI technology with an emotion engine. To implement this invention, the following specific steps are taken.

[0684] First, the user launches the smartphone app, which provides an interface for selecting cosplay costumes and characters. The app also includes an emotion engine that recognizes emotions from the user's facial expressions and voice.

[0685] Using this interface, users can select the cosplay look they want to wear or use options suggested by the emotion engine, which will then make optimal suggestions based on the user's previous choices and facial expression data.

[0686] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the device captures the photo and temporarily saves the data in the internal storage. The user checks the captured image and taps the upload button to send it to the server.

[0687] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which extracts the user's facial and body features from the image and identifies detailed feature points.

[0688] Based on the extracted features, the server then uses a generative AI model to transform the user's image into the specified cosplay costume and character, which is designed to accurately reflect the user's features.

[0689] The converted image data is sent back from the server to the user's device. The device displays the converted image so that the user can review it. The user can review the converted image and request re-editing if necessary. For example, this could include changing the color of the costume or the position of accessories.

[0690] The server re-runs the generative AI model based on the user's re-editing request to generate a new transformed image, then re-submits the re-generated image. This process is repeated until the user is finally satisfied.

[0691] The emotion engine analyzes the user's emotions from their facial expressions and voice and sends that data to the server, which uses this data to learn what kind of cosplay costumes and characters the user chooses, and can make optimal suggestions the next time they choose.

[0692] Finally, once the user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[0693] For example, a user can choose an anime character costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing the user to make fine adjustments until satisfied. The emotion engine then reads the user's facial expressions and optimizes the suggestions for the next cosplay. In this way, users can easily generate high-quality cosplay images.

[0694] An example of a prompt is, "I would like you to select a cosplay costume of the anime character 'Naruto' and take a photo of it, and have it transformed in real time." This allows the server to generate a transformed image based on the user's request in real time and send it to the device.

[0695] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0696] Step 1:

[0697] The user launches the dedicated app.

[0698] Specific operation: The user taps the dedicated app icon on the smartphone to launch the application. The app's startup screen is displayed.

[0699] Step 2:

[0700] The user selects a cosplay.

[0701] How it works: Users select the character they want to become from a list of cosplay costumes and characters displayed within the app. The emotion engine may suggest the most suitable cosplay based on the user's past choices and facial expression data.

[0702] Input: User selection or emotion engine suggestion

[0703] Output: Data of selected cosplay characters and costumes

[0704] Step 3:

[0705] The user takes a photo.

[0706] Specific operation: The user takes a photo of themselves using the camera function in the app. When the user taps the capture button, the device acquires the photo data and temporarily stores it in the internal storage.

[0707] Input: A photo taken by the user

[0708] Output: Photo data temporarily saved in the internal storage

[0709] Step 4:

[0710] The user sends the photo to the server.

[0711] Specific operation: The user checks the photos they have taken and taps the upload button to send them to the server. The device uses its Internet connection to send the photo data to the server.

[0712] Input: Photo data stored on the device

[0713] Output: Photo data sent to the server

[0714] Step 5:

[0715] The server receives and stores the images.

[0716] Specific operation: The server receives the photos sent by the user and temporarily stores them in a database, which allows subsequent analysis and processing.

[0717] Input: Photo data sent from the device

[0718] Output: Photo data stored in a database

[0719] Step 6:

[0720] The server performs the AI ​​analysis.

[0721] How it works: The server passes the stored image data to the AI ​​analysis module, which then begins analyzing the image. This module extracts the user's facial and body features and identifies detailed feature points.

[0722] Input: Photo data stored in the database

[0723] Output: Extracted facial and body feature data

[0724] Step 7:

[0725] The server converts the image.

[0726] How it works: The server uses a generative AI model based on the extracted feature data to transform the user's image into the specified cosplay costume or character, accurately reflecting the user's features.

[0727] Input: Extracted facial and body feature data, selected cosplay character data

[0728] Output: Image data converted to cosplay

[0729] Step 8:

[0730] The server transmits the converted image to the user terminal.

[0731] Specific operation: The converted image data is sent from the server to the user's device, and the user can check the converted image in real time.

[0732] Input: Image data converted to cosplay

[0733] Output: The converted image data sent to the terminal

[0734] Step 9:

[0735] The device displays the image and accepts requests for re-editing.

[0736] Specific operation: The device displays the received converted image for the user to review. If the user needs to re-edit it, they can submit a re-edit request, such as changing the color of the costume or the position of accessories.

[0737] Input: Converted image data sent from the server

[0738] Output: User's edit request

[0739] Step 10:

[0740] The server will regenerate and resend.

[0741] Specific operation: The server re-runs the generative AI model based on the user's request to generate a new transformed image. It then sends the re-generated image back to the user's device. This process is repeated until the user is satisfied.

[0742] Input: User re-edit request

[0743] Output: Regenerated transformed image data

[0744] Step 11:

[0745] The emotion engine performs analysis and data transmission.

[0746] How it works: The emotion engine analyzes the user's emotions from their facial expressions and voice, and sends that data to the server, which uses it to make the next recommendation.

[0747] Input: User's facial expressions and voice data

[0748] Output: Sentiment analysis data

[0749] Step 12:

[0750] Save and share the final image.

[0751] How it works: Once a final image is created that the user is happy with, the device saves it to internal storage. This image can then be easily shared on social media platforms with just one tap within the app.

[0752] Input: Regenerated final transformed image data

[0753] Output: Final image data saved and shared

[0754] (Application example 2)

[0755] 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."

[0756] Conventional try-on systems and cosplay experiences require users to physically try on costumes, which can be time-consuming and expensive. Users typically spend a lot of time and effort searching for a costume that suits them best. Furthermore, sharing the results of a try-on with friends and family requires additional steps, such as taking photos and uploading them to social media. The present invention aims to solve these problems by providing a system that allows users to try on costumes more easily and quickly and share the results.

[0757] 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 capturing an image, means for transmitting the captured image to the server, means for the server to analyze the image and extract the user's facial and whole-body features, means for converting the image into an outfit or character appearance using a generative AI based on the extracted features, means for returning the converted image to the user terminal and displaying it, means for the user to save and share the image, and means for analyzing emotions from the user's facial expressions and voice using an emotion engine and suggesting outfits based on the emotions. This allows the user to quickly and easily try on outfits without actually physically wearing them, and to check and share the results in real time.

[0758] "Means for taking images" refers to a mechanism that allows a user to take still images or videos using a device such as a camera.

[0759] The "means for transmitting captured images to a server" refers to a method and mechanism for transferring captured image data to a remote server via a network.

[0760] "Means for the server to analyze the image and extract the user's facial and body features" refers to algorithms and computer programs that process the transmitted image data and identify the user's facial shape, body shape, and other features.

[0761] "Method of converting an image into a costume or character appearance using generative AI based on extracted features" refers to a technology that uses a generative AI model to virtually change an image into a costume or character appearance, using the user's facial and body features.

[0762] The "means for returning and displaying the converted image to the user terminal" is a mechanism for transmitting the converted image data to the user's device over the network and displaying it on the display of that device.

[0763] "Means for users to save and share images" refers to the mechanism by which the converted image data is saved in the user's device storage and then shared with others on platforms such as social media.

[0764] "A means of using an emotion engine to analyze emotions from a user's facial expressions and voice, and suggest outfits based on those emotions" is a technology that recognizes emotions from a user's facial expressions and voice data, and automatically suggests optimal outfits based on the results.

[0765] The present invention is a system that allows users to easily enjoy cosplaying as costumes and characters. Detailed embodiments of the invention are described below.

[0766] First, the user launches an application installed on a device such as a smartphone, tablet, or smart glasses. The application provides an interface for selecting costumes and characters. The user uses this interface to select the costume or character they want to try on. Once the selection is complete, the user takes a picture of themselves using the device's camera.

[0767] Once the image is captured, the device temporarily stores the image data in its internal storage. The image data is then sent over the network to a server, which analyzes the received image data and extracts the user's facial and body features, often using the dlib library.

[0768] Once the analysis is complete, a generative AI model transforms the image based on the extracted feature data. The generative AI model is implemented using deep learning frameworks such as Keras and TensorFlow, and converts the user's image into the specified outfit or character. An emotion engine is also used to analyze the user's emotions from facial expressions and voice data, and then suggests the optimal outfit based on those emotions.

[0769] The converted image data is sent back to the user's device from the server and displayed on the device's screen. The user can review the results and make further fine adjustments, such as the color of the outfit or the position of the accessories. The device then sends a re-editing request to the server, which then uses the generative AI model to generate and return a new converted image. This process is repeated until the user is satisfied.

[0770] Finally, once a satisfactory image is generated, it is saved in the device's internal storage. The image can then be shared on social media platforms with a single tap. The emotion engine also learns from the user's selection and emotion data to optimize future suggestions.

[0771] Below are some examples of specific usage scenarios and prompts:

[0772] Specific usage scenarios:

[0773] 1. The user wears smart glasses installed in a physical store.

[0774] 2. The camera in the smart glasses captures the user's image and the app performs emotion analysis.

[0775] 3. Emotional data is analyzed to show that the user has a happy expression, and the suggested outfit is a party dress.

[0776] 4. Once the user selects a dress, the generative AI overlays the dress onto the user's video in real time.

[0777] 5. Share your try-on results on social media.

[0778] Example prompt sentence:

[0779] Choose the perfect dress for your birthday party and generate a real-time overlay image that will make your user look happy and smiling.

[0780] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0781] Step 1:

[0782] A user launches an application installed on a device such as a smartphone, tablet, or smart glasses. Using the application's interface, the user selects the costume or character they want to try on. The input is the user's selection data, and the output is information about the selected costume or character.

[0783] Step 2:

[0784] The device's camera is used to capture images of the user. When the user taps the capture button, the device temporarily stores still images and videos captured from the camera in its internal storage. The input is the user's real-time video, and the output is the captured image data.

[0785] Step 3:

[0786] The terminal sends the temporarily stored image data to the server via the network. At this time, the image data is encoded into an appropriate format and sent using a protocol that takes security into consideration (e.g., HTTPS). The input is the image data, and the output is the data transfer status to the server.

[0787] Step 4:

[0788] The server analyzes the received image data and extracts the user's facial and body features. Specifically, it uses the dlib library to detect facial landmarks (feature points) and then identifies the user's facial and body features based on those landmarks. The input is the received image data, and the output is the extracted facial and body feature data.

[0789] Step 5:

[0790] The server uses a generative AI model based on the extracted feature data to convert the image into a costume or character appearance. This generative AI model is implemented using deep learning frameworks such as Keras and TensorFlow, and takes face and body shape data as input to generate an image converted into the specified costume or character. The input is feature data and costume information, and the output is the converted image data.

[0791] Step 6:

[0792] The converted image data is sent back to the user's device from the server and displayed on the device's screen, allowing the user to check the conversion results in real time. The input is the converted image data, and the output is the real-time image displayed on the user's device.

[0793] Step 7:

[0794] The user can check the conversion results through the application and request re-editing if necessary. Re-editing requests include changes to the color of the costume or the position of accessories. This request data is sent to the server. The input is the user's re-editing request, and the output is the request data sent to the server.

[0795] Step 8:

[0796] The server receives the re-editing request, again uses the generative AI model to generate a new transformed image and sends it back to the device. This process is repeated until the user is satisfied. The input is the re-editing request data, and the output is the newly transformed image data.

[0797] Step 9:

[0798] Finally, once a satisfactory image is generated, the device saves it to its internal storage. This image can then be shared on social media platforms with a single tap from within the application. The input is the final, verified image data, and the output is the saved image data and a link for sharing.

[0799] Examples:

[0800] Example prompt: "Choose the perfect dress for a birthday party and generate a real-time overlay image. The user will look happy and smiling."

[0801] 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.

[0802] 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.

[0803] 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.

[0804] [Third embodiment]

[0805] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0806] 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.

[0807] 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).

[0808] 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.

[0809] 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.

[0810] 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).

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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."

[0817] The present invention provides a system that uses AI generation technology to allow users to easily enjoy cosplay. Specific embodiments for carrying out the present invention will be described below.

[0818] First, the user launches the smartphone app, which provides an interface for selecting cosplay costumes and characters. Using this interface, the user selects the cosplay look they want to wear.

[0819] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the smartphone (device) captures the photo and temporarily saves the data in its internal storage. The user checks the image and taps the upload button to send it to the server.

[0820] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which then begins analysis. The AI ​​analysis module extracts the user's facial and body features from the image and identifies detailed feature points. These extraction results are used as base data for the generative AI model.

[0821] The server then uses the extracted features to convert the image into the cosplay costume and character selected by the user. The generative AI model uses this data to convert the user's image into the specified cosplay costume and character in real time. The converted image data is then sent back from the server to the user's device.

[0822] The device displays the converted image that the user has received, allowing the user to review it. The user can then review the converted image and request re-editing if necessary. For example, the user can send a request to change the color of the costume or the position of accessories.

[0823] The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it, allowing the process to be repeated, fine-tuning the image until the user is finally satisfied.

[0824] Finally, once a user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[0825] For example, a user can choose an anime character's costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing them to make fine adjustments until they are satisfied. In this way, users can easily generate high-quality cosplay images.

[0826] This system will significantly reduce the costs and effort required to enjoy cosplay, making it easier for many people to enjoy cosplay.

[0827] The processing flow will be explained below.

[0828] Step 1:

[0829] The user launches the smartphone app and opens the photo capture screen.

[0830] Step 2:

[0831] The user takes a photo of themselves using the smartphone camera.

[0832] Step 3:

[0833] The device temporarily stores the captured photos in its internal storage.

[0834] Step 4:

[0835] The user reviews the photos they have taken and, if they are satisfied, taps the "Upload" button.

[0836] Step 5:

[0837] The device encrypts the photo and sends it to the application server.

[0838] Step 6:

[0839] The server receives the uploaded photos and temporarily stores them in a database.

[0840] Step 7:

[0841] The server passes the photo data to the AI ​​analysis module and begins image analysis.

[0842] Step 8:

[0843] The AI ​​analysis module extracts the user's facial and body features from the photo and identifies detailed feature points.

[0844] Step 9:

[0845] The server generates base data for optimal costume transformation based on the extracted features.

[0846] Step 10:

[0847] Users select cosplay costumes and characters within the app.

[0848] Step 11:

[0849] The terminal transmits data of the costume and character selected by the user to the server.

[0850] Step 12:

[0851] The server combines the received selection information with the analysis results and inputs them into the image generation AI model.

[0852] Step 13:

[0853] Based on the analysis results and selected information, the generative AI model converts the user's original photo into the specified cosplay costume or character appearance.

[0854] Step 14:

[0855] The server temporarily stores the generated converted image and transmits it to the terminal.

[0856] Step 15:

[0857] The terminal displays the converted image received from the server to the user.

[0858] Step 16:

[0859] The user can check the converted image in real time and request re-editing if necessary.

[0860] Step 17:

[0861] The terminal transmits the user's re-editing request to the server.

[0862] Step 18:

[0863] The server again uses the generative AI model to generate a new transformed image based on the request and sends it to the device.

[0864] Step 19:

[0865] When the user is finally satisfied with the transformed image, he taps the "Save" button.

[0866] Step 20:

[0867] The device saves the converted image in local storage.

[0868] Step 21:

[0869] Users can share saved images on social media platforms.

[0870] Example 1

[0871] 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."

[0872] In recent years, cosplay has become popular among many people, but it takes a lot of time and money to actually purchase cosplay costumes, apply makeup, and take photos. Furthermore, the quality of cosplay depends on the individual's skill and financial resources, making it difficult for beginners to participate. Furthermore, there is a demand for a way to easily enjoy cosplay at home without attending an event. The purpose of this invention is to solve these problems.

[0873] 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.

[0874] In this invention, the server includes means for analyzing images and extracting the user's facial and whole-body features, means for converting the images into cosplay costumes or character appearances using a generation AI based on the extracted features, and means for returning and displaying the converted images to the user's terminal, thereby enabling users to easily generate and enjoy cosplay images.

[0875] The "means for taking pictures" refers to the functions and devices that allow a user to take pictures using a terminal.

[0876] The "means for transmitting captured images to a server" is a communication means for uploading image data from a user's terminal to a server.

[0877] "Means for the server to analyze images and extract the user's facial and body features" refers to analytical technologies and algorithms for identifying the user's facial and body features based on the image data received by the server.

[0878] "Method of transforming an image into a cosplay costume or character appearance using generative AI based on extracted features" refers to the process and technology of using analyzed feature data as input and a generative AI model to transform an image into any cosplay costume or character.

[0879] The "means for returning the converted image to the user terminal and displaying it" refers to a communication and display function for transmitting the generated cosplay image to the user terminal and displaying it on the terminal.

[0880] "Means for users to save and share images" refers to a function that allows users to save the final generated image on their device and easily share it on social media or other platforms.

[0881] The "means for a user to request re-editing of a converted image" refers to an interface and communication means for a user to request additional changes or modifications to a converted image and to repeat the generation process.

[0882] This invention provides a system that uses AI generation technology to allow users to easily enjoy cosplay. This system is composed of a terminal such as a smartphone, a server, and advanced AI analysis and generation functions. Specific embodiments for implementing the invention are described below.

[0883] First, the user launches the app on their smartphone. The app provides an interface for selecting cosplay costumes and characters. Using this interface, the user selects the cosplay look they want to wear. Next, the user takes a photo using the app's camera function. When the user taps the capture button, the device captures the photo and temporarily saves the data in internal storage. The user then checks the image they have taken and taps the upload button to send it to the server.

[0884] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to an AI analysis module, which begins analysis. This AI analysis module combines facial recognition and body feature extraction technologies. The server extracts the user's facial and body features through analysis and inputs them into a generative AI model (e.g., GANs or VAE). This generative AI model then converts the user's image into the specified cosplay costume or character in real time based on the extracted features.

[0885] The generated transformed image is sent from the server to the user's device. The device displays the received transformed image for the user to review. The user can review the transformed image and request re-editing if necessary. For example, the user can request corrections to the color of the costume or the position of accessories. The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it. This process can be repeated, allowing the user to make fine adjustments until they are finally satisfied.

[0886] Finally, once the user is satisfied with the resulting image, the device saves it to its internal storage, where it can be easily shared on social media platforms with just one tap within the app.

[0887] Specific operation example

[0888] For example, a user can choose an anime character's costume, take a photo, and the image is analyzed on the server and transformed into the character's appearance using a generative AI model. The result is sent back to the user's device in real time, allowing them to fine-tune it until they are satisfied. When the user is finally satisfied, the image is saved on their device and can be easily shared on social media.

[0889] An example of a prompt is, "Based on the photo below, please transform it into the specified anime character's appearance. Use blue hair, a red outfit, and a smiling face." In this way, users can easily generate high-quality cosplay images.

[0890] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0891] Step 1:

[0892] The user launches the app on their smartphone and selects a cosplay costume and character.

[0893] Input: User actions

[0894] What it does: The user launches the app and selects a cosplay costume and character from the interface provided. The app saves the selection information to its internal storage.

[0895] Output: Selected cosplay costume and character information

[0896] Step 2:

[0897] The user takes a photo using the camera function within the app.

[0898] Input: A photo taken by the user

[0899] Specific operation: The user taps the capture button, the device camera takes a photo, and the captured image data is temporarily stored in the internal storage.

[0900] Output: Captured image data

[0901] Step 3:

[0902] The user checks the image they have taken, taps the upload button, and sends the image data to the server.

[0903] Input: Captured image data, user operations

[0904] Specific operation: After taking a photo, the user checks the image displayed on the screen and taps the upload button. The device then sends the image data to the server.

[0905] Output: Image data uploaded to the server

[0906] Step 4:

[0907] The server receives the uploaded images and temporarily stores them in a database.

[0908] Input: Uploaded image data

[0909] Specific operation: The server temporarily stores the received image data in a database. After storing it, it prepares it for analysis.

[0910] Output: Image data stored in a database

[0911] Step 5:

[0912] The server passes the image data to an AI analysis module, which extracts the user's facial and body features.

[0913] Input: Image data stored in a database

[0914] How it works: The server uses an AI analysis module to analyze the image data and extract the user's facial and body features. The analysis uses facial recognition technology and body feature extraction algorithms.

[0915] Output: Extracted feature data

[0916] Step 6:

[0917] Based on the extracted feature data, the server uses a generative AI model to convert the image into a cosplay costume or character appearance.

[0918] Input: Extracted feature data, selected cosplay costume and character information

[0919] How it works: The server uses generative AI models such as GANs and VAE to convert the user's image into the specified cosplay costume or character. During this process, the extracted feature data is used as base data.

[0920] Output: The converted image data

[0921] Step 7:

[0922] The server transmits the converted image data to the user's terminal, which displays it.

[0923] Input: Transformed image data

[0924] Specific operation: The server sends the converted image data back to the user's device, and the device displays the received image within the app.

[0925] Output: The converted image displayed on the user's device

[0926] Step 8:

[0927] The user may check the converted image and send a request for re-editing.

[0928] Input: Converted image data, user operations

[0929] Specific operation: The user checks the displayed converted image and, if any changes are necessary, sends a request for re-editing, such as inputting a prompt to modify the color of the costume or the position of accessories.

[0930] Output: Re-edit request (prompt text)

[0931] Step 9:

[0932] The server again uses the generative AI model to generate and resend a new transformed image based on the re-editing request.

[0933] Input: Reedit request, initial converted image data

[0934] Specific operation: The server re-runs the generative AI model based on the re-editing request to generate a new converted image, which is then sent back to the user's device.

[0935] Output: Re-edited image data, new image sent to user's device

[0936] Step 10:

[0937] When an image that the user is finally satisfied with is generated, the terminal stores the image.

[0938] Input: Final converted image data, user operations

[0939] Specific operation: The user confirms the final image they are satisfied with, and the device saves this image in its internal storage.

[0940] Output: Image data stored in internal storage

[0941] Step 11:

[0942] Users can share the saved images on social media etc.

[0943] Input: Image data stored in the internal storage, user operations

[0944] Specific operation: The user taps the share button within the app and posts the saved image to social media etc. The entire sharing process is designed to be easily performed within the app.

[0945] Output: Image data posted on social media etc.

[0946] (Application example 1)

[0947] 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."

[0948] Current cosplay try-on systems do not allow users to try on costumes or character appearances in real time before actually purchasing them. Furthermore, they lack an interface that allows for fine adjustments such as the color of the try-on image or the position of accessories, preventing users from achieving high satisfaction. A system that solves this issue and allows many users to easily enjoy a high-quality cosplay experience is needed.

[0949] 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.

[0950] In this invention, the server includes means for [analyzing an image and extracting the user's facial and whole-body features], means for [using generative AI to convert the image into a specific outfit or character appearance based on the extracted features], and means for [providing an interface for the user to adjust the color and position of accessories in the image]. This allows the user to try out specific outfits or character appearances in real time, make fine adjustments, and regenerate them as many times as necessary until they are satisfied.

[0951] The "means for taking an image" refers to a camera function and its control interface for capturing an image of the user's face or whole body.

[0952] The "means for transmitting captured images to a server" refers to a communication function and protocol for uploading acquired image data to a server via the Internet.

[0953] "Means for the server to analyze images and extract features of the user's face and body" refers to the process of using an AI analysis module to identify features of the user's face and body from uploaded images and store them in a database.

[0954] "Means of using generative AI to transform an image into a specific costume or character appearance based on extracted features" refers to the process in which a generative AI model transforms an image based on the user's feature point data and selected costume or character information.

[0955] The "means for returning and displaying the converted image to the user's terminal" refers to a communication and display function for sending the generated cosplay image to the user's device and displaying it on the application.

[0956] "Means for providing an interface for users to adjust the color of an image or the position of accessories" refers to an operation screen and control functions that allow users to fine-tune the color and position of clothing in an image.

[0957] "Means for regenerating images until the user is satisfied" refers to the process of reapplying the generative AI model in response to the user's adjustment requests to generate an updated image.

[0958] "Means for users to save and share images" refers to a function that allows users to save the final generated image on their device and share it on external services such as social networking sites.

[0959] MODE FOR CARRYING OUT THE INVENTION

[0960] The system for implementing this invention provides users with the experience of enjoying cosplay, and includes the following elements.

[0961] Hardware and Software

[0962] Hardware:

[0963] Smartphones (e.g. iPhone, Android devices)

[0964] Head-mounted displays (e.g., Oculus Quest, HTC Vive)

[0965] Server (for back-end processing)

[0966] software:

[0967] AI analysis module: TensorFlow, PyTorch

[0968] Image processing: OpenCV

[0969] Server: Node.js, Python (Flask, Django)

[0970] Front-end frameworks: React Native, Swift (iOS), Kotlin (Android)

[0971] Virtual / AR: ARKit (iOS), ARCore (Android)

[0972] System processing overview

[0973] Users launch the app on their smartphone, select the cosplay costume and character they want to try on, take a picture of themselves using the app's camera, and send the image to the server.

[0974] The server passes the received image to an AI analysis module, which extracts facial and full-body features. Based on these features, the generative AI model converts the image into the selected costume and character appearance, and sends it back to the user's device in real time. The returned image is displayed within the app for the user to review.

[0975] Additionally, users can use the provided interface to adjust the image's color, the position of decorations, etc. Then, they can again manipulate the generative AI model to generate a new image, and the process is repeated. Finally, once an image that satisfies the user is generated, they can save it using the app's save and share functions and share it on social media.

[0976] Specific examples

[0977] For example, let's say a user wants to choose a costume for a famous anime character. In that case, they launch the smartphone application and select the desired character costume from a list. Next, they take a photo of themselves using their camera and send the image to the server. The server then analyzes the image using an AI analysis module, extracts feature points, and converts them into the character's appearance using a generative AI model.

[0978] The converted image is sent back to the user's smartphone and can be viewed on the application. If the user wants to fine-tune the color of the outfit or the position of the accessories, they can easily do so using the interface, and then the generative AI model can generate a new image for them to view.

[0979] Prompt Sentence Examples

[0980] "Turn on your smartphone camera and select a specific character's outfit. Tap the capture button to view the converted image. Adjust the color tone, generate the final image again, and share it on social media."

[0981] This invention allows users to easily enjoy a high-quality cosplay experience, and allows them to adjust the details of color and design. The server performs image analysis and conversion in real time, allowing users to instantly see the results and optimize until they are satisfied.

[0982] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0983] Program processing steps

[0984] Step 1:

[0985] The user launches the smartphone application. Using the provided interface, the user selects the cosplay costume and character they want to try on. The input is information about the costume and character selected by the user, and the output is saved on the device.

[0986] Step 2:

[0987] The user takes a photo of themselves using the device's camera function. Images of the user's face and whole body are obtained as input, and the image data is temporarily saved in the device's internal storage as output. Specifically, the user taps the capture button, which activates the camera and takes the photo.

[0988] Step 3:

[0989] The user taps the upload button to send the captured image to the server. Image data stored on the device is obtained as input, and the image data is transferred to the server via the network as output. Specifically, the image file is sent to the server via an HTTP request.

[0990] Step 4:

[0991] The server passes the received image data to the AI ​​analysis module, which extracts the user's facial and whole-body features. The received image data is taken as input, and feature point data is generated as output. Specifically, the AI ​​analysis module uses TensorFlow and PyTorch to identify feature points within the image and store them in a database.

[0992] Step 5:

[0993] Based on the extracted feature point data, the server uses a generative AI model to convert the image into a specific costume or character appearance. The input is the feature point data and the costume and character information selected by the user, and the converted image data is generated as the output. Specifically, the generative AI model uses the feature point data to convert the image.

[0994] Step 6:

[0995] The server returns the converted image data to the user's device, which then displays it. The converted image data is obtained as input, and the converted image is displayed on the device's display as output. Specifically, the server sends the image data as an HTTP response, and the device displays the received image on the screen.

[0996] Step 7:

[0997] The user adjusts the color of the image and the position of decorations using the provided interface. The user's adjustment instructions are received as input, and the adjusted parameters are saved on the device as output. Specifically, the user operates the controls on the interface to make adjustments.

[0998] Step 8:

[0999] The server again uses the generative AI model to generate a new image based on the user's adjustment instructions and sends it to the user's device. The adjusted parameters are obtained as input, and adjusted image data is generated as output. Specifically, the server uses the adjustment parameters and feature point data to generate a new image using the generative AI model and send it to the device.

[1000] Step 9:

[1001] Once a final image that satisfies the user is generated, the user saves it to their device and shares it. The final image data is obtained as input, and the image is saved to the device's local storage as output, ready to be shared. Specifically, the user taps the save button, and the image data is saved to the device. The user can also tap the share button to upload the image to social media sites, etc.

[1002] 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.

[1003] This invention combines generative AI technology with an emotion engine to provide a system that allows users to easily enjoy cosplay. Specific embodiments for carrying out the invention will be described below.

[1004] First, the user launches the smartphone app. The app provides an interface for selecting cosplay costumes and characters. The app also has an emotion engine that recognizes emotions from the user's facial expressions and voice. Using this interface, the user can select the cosplay look they want to wear, or use the options suggested by the emotion engine.

[1005] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the smartphone (device) captures the photo and temporarily saves the data in its internal storage. The user checks the image and taps the upload button to send it to the server.

[1006] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which then begins analysis. The AI ​​analysis module extracts the user's facial and body features from the image and identifies detailed feature points. These extraction results are used as base data for the generative AI model.

[1007] The server then uses the extracted features to convert the image into the cosplay costume and character selected by the user. The generative AI model uses this data to convert the user's image into the specified cosplay costume and character in real time. The converted image data is then sent back from the server to the user's device.

[1008] The device displays the converted image that the user has received, allowing the user to review it. The user can then review the converted image and request re-editing if necessary. For example, the user can send a request to change the color of the costume or the position of accessories.

[1009] The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it, allowing the process to be repeated, fine-tuning the image until the user is finally satisfied.

[1010] The emotion engine analyzes the user's emotions from their facial expressions and voice and sends that data to the server. Based on the emotional data, the server can learn what kind of cosplay costumes and characters the user chooses, and make optimal suggestions for future selections.

[1011] Finally, once a user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[1012] For example, a user can choose an anime character costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing them to make fine adjustments until they are satisfied. An emotion engine then reads the user's facial expressions and optimizes the suggestions for the next cosplay. In this way, users can easily generate high-quality cosplay images.

[1013] This system will significantly reduce the cost and effort required to enjoy cosplay, making it easier for many people to enjoy cosplay. It will also take user emotions into consideration, making it possible to provide a more personalized experience.

[1014] The processing flow will be explained below.

[1015] Step 1:

[1016] The user launches the app on their smartphone and opens the photo-taking screen. The app has an interface for selecting cosplay costumes and characters, as well as an emotion engine.

[1017] Step 2:

[1018] The emotion engine acquires the user's facial information and voice data in real time and begins emotion analysis.

[1019] Step 3:

[1020] Based on the analysis results of the emotion engine, the device will suggest the most suitable cosplay costumes and characters for the user. The user can then follow the suggestions or choose their own preferred costumes and characters.

[1021] Step 4:

[1022] The user takes a photo of themselves using the smartphone camera.

[1023] Step 5:

[1024] The device temporarily stores the captured photos in its internal storage.

[1025] Step 6:

[1026] The user reviews the photos they have taken and, if they are satisfied, taps the "Upload" button.

[1027] Step 7:

[1028] The device encrypts the photo and sends it to the application server.

[1029] Step 8:

[1030] The server receives the uploaded photos and temporarily stores them in a database.

[1031] Step 9:

[1032] The server passes the photo data to the AI ​​analysis module and begins image analysis.

[1033] Step 10:

[1034] The AI ​​analysis module extracts the user's facial and body features from the photo and identifies detailed feature points.

[1035] Step 11:

[1036] The server generates base data for optimal costume transformation based on the extracted features.

[1037] Step 12:

[1038] The device receives the analysis results from the server and converts the image using a generative AI model based on the generated base data.

[1039] Step 13:

[1040] Based on the analysis results and selected information, the generative AI model converts the user's original photo into the specified cosplay costume or character appearance.

[1041] Step 14:

[1042] The server temporarily stores the generated converted image and transmits it to the terminal.

[1043] Step 15:

[1044] The terminal displays the converted image received from the server to the user.

[1045] Step 16:

[1046] The user can check the converted image in real time and request re-editing if necessary.

[1047] Step 17:

[1048] The terminal transmits the user's re-editing request to the server.

[1049] Step 18:

[1050] The server again uses the generative AI model to generate a new transformed image based on the request and sends it to the device.

[1051] Step 19:

[1052] When the user is finally satisfied with the transformed image, he taps the "Save" button.

[1053] Step 20:

[1054] The device saves the converted image in local storage.

[1055] Step 21:

[1056] The device transmits the emotion data analyzed by the emotion engine to the server.

[1057] Step 22:

[1058] The server learns the user's preferences based on the emotional data and reflects them in future suggestions.

[1059] Step 23:

[1060] Users can share saved images on social media platforms.

[1061] Example 2

[1062] 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."

[1063] Conventional cosplay experience provision systems require users to acquire costumes, wear them, and take photos themselves, which is time-consuming. Furthermore, the images must be manually edited, requiring specialized knowledge and skills, making it difficult for anyone to easily obtain high-quality cosplay images. Furthermore, the lack of personalized suggestions based on the user's emotions and preferences limits the user experience. Therefore, there is a need for a system that allows users to easily generate high-quality cosplay images and provides a personalized experience in the process.

[1064] 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.

[1065] In this invention, the server includes means for [analyzing images and extracting the user's facial and whole-body features], means for [using generative AI to convert the image into a cosplay costume or character appearance based on the extracted features], and means for [analyzing the user's facial expressions and voice using an emotion engine to suggest cosplay costumes and characters]. This enables [users to easily obtain high-quality cosplay images without requiring specialized knowledge or skills, and furthermore, to receive personalized suggestions tailored to each individual user].

[1066] "Means for taking images" means [a device or function that provides a camera function for users to take images of themselves].

[1067] "Means for sending captured images to a server" refers to a communication function that allows a user to send captured image data to a remote server.

[1068] "The means by which the server analyzes images and extracts the user's facial and body features" refers to an AI analysis module that identifies and analyzes the user's facial and body features from the image data received by the server.

[1069] "Means of using generative AI to transform images into cosplay costumes or character appearances based on extracted features" means "a function that uses a generative AI model to transform a user's image into a cosplay costume or character appearance in real time based on extracted features."

[1070] "Means for returning and displaying the converted image to the user's device" refers to the communication and display function for sending the image data converted by the generating AI to the user's device and displaying it on that device.

[1071] "Means for users to save and share images" refers to a function that allows users to save images they are satisfied with to internal storage and easily share them on social media, etc.

[1072] "A means of analyzing the user's facial expressions and voice using an emotion engine to suggest cosplay costumes and characters" means "a function that uses an emotion engine to analyze the user's facial expressions and voice data, and suggests appropriate cosplay costumes and characters based on the results."

[1073] "A means by which a user can submit a re-editing request and re-generate the image using the generative AI model" is [a process by which a user can request changes to an image and re-run the generative AI model to re-generate the image].

[1074] This invention is a system that allows users to easily enjoy cosplay, and combines generative AI technology with an emotion engine. To implement this invention, the following specific steps are taken.

[1075] First, the user launches the smartphone app, which provides an interface for selecting cosplay costumes and characters. The app also includes an emotion engine that recognizes emotions from the user's facial expressions and voice.

[1076] Using this interface, users can select the cosplay look they want to wear or use options suggested by the emotion engine, which will then make optimal suggestions based on the user's previous choices and facial expression data.

[1077] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the device captures the photo and temporarily saves the data in the internal storage. The user checks the captured image and taps the upload button to send it to the server.

[1078] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which extracts the user's facial and body features from the image and identifies detailed feature points.

[1079] Based on the extracted features, the server then uses a generative AI model to transform the user's image into the specified cosplay costume and character, which is designed to accurately reflect the user's features.

[1080] The converted image data is sent back from the server to the user's device. The device displays the converted image so that the user can review it. The user can review the converted image and request re-editing if necessary. For example, this could include changing the color of the costume or the position of accessories.

[1081] The server re-runs the generative AI model based on the user's re-editing request to generate a new transformed image, then re-submits the re-generated image. This process is repeated until the user is finally satisfied.

[1082] The emotion engine analyzes the user's emotions from their facial expressions and voice and sends that data to the server, which uses this data to learn what kind of cosplay costumes and characters the user chooses, and can make optimal suggestions the next time they choose.

[1083] Finally, once the user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[1084] For example, a user can choose an anime character costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing the user to make fine adjustments until satisfied. The emotion engine then reads the user's facial expressions and optimizes the suggestions for the next cosplay. In this way, users can easily generate high-quality cosplay images.

[1085] An example of a prompt is, "I would like you to select a cosplay costume of the anime character 'Naruto' and take a photo of it, and have it transformed in real time." This allows the server to generate a transformed image based on the user's request in real time and send it to the device.

[1086] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1087] Step 1:

[1088] The user launches the dedicated app.

[1089] Specific operation: The user taps the dedicated app icon on the smartphone to launch the application. The app's startup screen is displayed.

[1090] Step 2:

[1091] The user selects a cosplay.

[1092] How it works: Users select the character they want to become from a list of cosplay costumes and characters displayed within the app. The emotion engine may suggest the most suitable cosplay based on the user's past choices and facial expression data.

[1093] Input: User selection or emotion engine suggestion

[1094] Output: Data of selected cosplay characters and costumes

[1095] Step 3:

[1096] The user takes a photo.

[1097] Specific operation: The user takes a photo of themselves using the camera function in the app. When the user taps the capture button, the device acquires the photo data and temporarily stores it in the internal storage.

[1098] Input: A photo taken by the user

[1099] Output: Photo data temporarily saved in the internal storage

[1100] Step 4:

[1101] The user sends the photo to the server.

[1102] Specific operation: The user checks the photos they have taken and taps the upload button to send them to the server. The device uses its Internet connection to send the photo data to the server.

[1103] Input: Photo data stored on the device

[1104] Output: Photo data sent to the server

[1105] Step 5:

[1106] The server receives and stores the images.

[1107] Specific operation: The server receives the photos sent by the user and temporarily stores them in a database, which allows subsequent analysis and processing.

[1108] Input: Photo data sent from the device

[1109] Output: Photo data stored in a database

[1110] Step 6:

[1111] The server performs the AI ​​analysis.

[1112] How it works: The server passes the stored image data to the AI ​​analysis module, which then begins analyzing the image. This module extracts the user's facial and body features and identifies detailed feature points.

[1113] Input: Photo data stored in the database

[1114] Output: Extracted facial and body feature data

[1115] Step 7:

[1116] The server converts the image.

[1117] How it works: The server uses a generative AI model based on the extracted feature data to transform the user's image into the specified cosplay costume or character, accurately reflecting the user's features.

[1118] Input: Extracted facial and body feature data, selected cosplay character data

[1119] Output: Image data converted to cosplay

[1120] Step 8:

[1121] The server transmits the converted image to the user terminal.

[1122] Specific operation: The converted image data is sent from the server to the user's device, and the user can check the converted image in real time.

[1123] Input: Image data converted to cosplay

[1124] Output: The converted image data sent to the terminal

[1125] Step 9:

[1126] The device displays the image and accepts requests for re-editing.

[1127] Specific operation: The device displays the received converted image for the user to review. If the user needs to re-edit it, they can submit a re-edit request, such as changing the color of the costume or the position of accessories.

[1128] Input: Converted image data sent from the server

[1129] Output: User's edit request

[1130] Step 10:

[1131] The server will regenerate and resend.

[1132] Specific operation: The server re-runs the generative AI model based on the user's request to generate a new transformed image. It then sends the re-generated image back to the user's device. This process is repeated until the user is satisfied.

[1133] Input: User re-edit request

[1134] Output: Regenerated transformed image data

[1135] Step 11:

[1136] The emotion engine performs analysis and data transmission.

[1137] How it works: The emotion engine analyzes the user's emotions from their facial expressions and voice, and sends that data to the server, which uses it to make the next recommendation.

[1138] Input: User's facial expressions and voice data

[1139] Output: Sentiment analysis data

[1140] Step 12:

[1141] Save and share the final image.

[1142] How it works: Once a final image is created that the user is happy with, the device saves it to internal storage. This image can then be easily shared on social media platforms with just one tap within the app.

[1143] Input: Regenerated final transformed image data

[1144] Output: Final image data saved and shared

[1145] (Application example 2)

[1146] 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."

[1147] Conventional try-on systems and cosplay experiences require users to physically try on costumes, which can be time-consuming and expensive. Users typically spend a lot of time and effort searching for a costume that suits them best. Furthermore, sharing the results of a try-on with friends and family requires additional steps, such as taking photos and uploading them to social media. The present invention aims to solve these problems by providing a system that allows users to try on costumes more easily and quickly and share the results.

[1148] 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 capturing an image, means for transmitting the captured image to the server, means for the server to analyze the image and extract the user's facial and whole-body features, means for converting the image into an outfit or character appearance using a generative AI based on the extracted features, means for returning the converted image to the user terminal and displaying it, means for the user to save and share the image, and means for analyzing emotions from the user's facial expressions and voice using an emotion engine and suggesting outfits based on the emotions. This allows the user to quickly and easily try on outfits without actually physically wearing them, and to check and share the results in real time.

[1149] "Means for taking images" refers to a mechanism that allows a user to take still images or videos using a device such as a camera.

[1150] The "means for transmitting captured images to a server" refers to a method and mechanism for transferring captured image data to a remote server via a network.

[1151] "Means for the server to analyze the image and extract the user's facial and body features" refers to algorithms and computer programs that process the transmitted image data and identify the user's facial shape, body shape, and other features.

[1152] "Method of converting an image into a costume or character appearance using generative AI based on extracted features" refers to a technology that uses a generative AI model to virtually change an image into a costume or character appearance, using the user's facial and body features.

[1153] The "means for returning and displaying the converted image to the user terminal" is a mechanism for transmitting the converted image data to the user's device over the network and displaying it on the display of that device.

[1154] "Means for users to save and share images" refers to the mechanism by which the converted image data is saved in the user's device storage and then shared with others on platforms such as social media.

[1155] "A means of using an emotion engine to analyze emotions from a user's facial expressions and voice, and suggest outfits based on those emotions" is a technology that recognizes emotions from a user's facial expressions and voice data, and automatically suggests optimal outfits based on the results.

[1156] The present invention is a system that allows users to easily enjoy cosplaying as costumes and characters. Detailed embodiments of the invention are described below.

[1157] First, the user launches an application installed on a device such as a smartphone, tablet, or smart glasses. The application provides an interface for selecting costumes and characters. The user uses this interface to select the costume or character they want to try on. Once the selection is complete, the user takes a picture of themselves using the device's camera.

[1158] Once the image is captured, the device temporarily stores the image data in its internal storage. The image data is then sent over the network to a server, which analyzes the received image data and extracts the user's facial and body features, often using the dlib library.

[1159] Once the analysis is complete, a generative AI model transforms the image based on the extracted feature data. The generative AI model is implemented using deep learning frameworks such as Keras and TensorFlow, and converts the user's image into the specified outfit or character. An emotion engine is also used to analyze the user's emotions from facial expressions and voice data, and then suggests the optimal outfit based on those emotions.

[1160] The converted image data is sent back to the user's device from the server and displayed on the device's screen. The user can review the results and make further fine adjustments, such as the color of the outfit or the position of the accessories. The device then sends a re-editing request to the server, which then uses the generative AI model to generate and return a new converted image. This process is repeated until the user is satisfied.

[1161] Finally, once a satisfactory image is generated, it is saved in the device's internal storage. The image can then be shared on social media platforms with a single tap. The emotion engine also learns from the user's selection and emotion data to optimize future suggestions.

[1162] Below are some examples of specific usage scenarios and prompts:

[1163] Specific usage scenarios:

[1164] 1. The user wears smart glasses installed in a physical store.

[1165] 2. The camera in the smart glasses captures the user's image and the app performs emotion analysis.

[1166] 3. Emotional data is analyzed to show that the user has a happy expression, and the suggested outfit is a party dress.

[1167] 4. Once the user selects a dress, the generative AI overlays the dress onto the user's video in real time.

[1168] 5. Share your try-on results on social media.

[1169] Example prompt sentence:

[1170] Choose the perfect dress for your birthday party and generate a real-time overlay image that will make your user look happy and smiling.

[1171] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1172] Step 1:

[1173] A user launches an application installed on a device such as a smartphone, tablet, or smart glasses. Using the application's interface, the user selects the costume or character they want to try on. The input is the user's selection data, and the output is information about the selected costume or character.

[1174] Step 2:

[1175] The device's camera is used to capture images of the user. When the user taps the capture button, the device temporarily stores still images and videos captured from the camera in its internal storage. The input is the user's real-time video, and the output is the captured image data.

[1176] Step 3:

[1177] The terminal sends the temporarily stored image data to the server via the network. At this time, the image data is encoded into an appropriate format and sent using a protocol that takes security into consideration (e.g., HTTPS). The input is the image data, and the output is the data transfer status to the server.

[1178] Step 4:

[1179] The server analyzes the received image data and extracts the user's facial and body features. Specifically, it uses the dlib library to detect facial landmarks (feature points) and then identifies the user's facial and body features based on those landmarks. The input is the received image data, and the output is the extracted facial and body feature data.

[1180] Step 5:

[1181] The server uses a generative AI model based on the extracted feature data to convert the image into a costume or character appearance. This generative AI model is implemented using deep learning frameworks such as Keras and TensorFlow, and takes face and body shape data as input to generate an image converted into the specified costume or character. The input is feature data and costume information, and the output is the converted image data.

[1182] Step 6:

[1183] The converted image data is sent back to the user's device from the server and displayed on the device's screen, allowing the user to check the conversion results in real time. The input is the converted image data, and the output is the real-time image displayed on the user's device.

[1184] Step 7:

[1185] The user can check the conversion results through the application and request re-editing if necessary. Re-editing requests include changes to the color of the costume or the position of accessories. This request data is sent to the server. The input is the user's re-editing request, and the output is the request data sent to the server.

[1186] Step 8:

[1187] The server receives the re-editing request, again uses the generative AI model to generate a new transformed image and sends it back to the device. This process is repeated until the user is satisfied. The input is the re-editing request data, and the output is the newly transformed image data.

[1188] Step 9:

[1189] Finally, once a satisfactory image is generated, the device saves it to its internal storage. This image can then be shared on social media platforms with a single tap from within the application. The input is the final, verified image data, and the output is the saved image data and a link for sharing.

[1190] Examples:

[1191] Example prompt: "Choose the perfect dress for a birthday party and generate a real-time overlay image. The user will look happy and smiling."

[1192] 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.

[1193] 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.

[1194] 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.

[1195] [Fourth embodiment]

[1196] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1197] 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.

[1198] 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).

[1199] 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.

[1200] 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.

[1201] 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).

[1202] 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.

[1203] 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.

[1204] 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.

[1205] 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.

[1206] 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.

[1207] 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.

[1208] 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."

[1209] The present invention provides a system that uses AI generation technology to allow users to easily enjoy cosplay. Specific embodiments for carrying out the present invention will be described below.

[1210] First, the user launches the smartphone app, which provides an interface for selecting cosplay costumes and characters. Using this interface, the user selects the cosplay look they want to wear.

[1211] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the smartphone (device) captures the photo and temporarily saves the data in its internal storage. The user checks the image and taps the upload button to send it to the server.

[1212] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which then begins analysis. The AI ​​analysis module extracts the user's facial and body features from the image and identifies detailed feature points. These extraction results are used as base data for the generative AI model.

[1213] The server then uses the extracted features to convert the image into the cosplay costume and character selected by the user. The generative AI model uses this data to convert the user's image into the specified cosplay costume and character in real time. The converted image data is then sent back from the server to the user's device.

[1214] The device displays the converted image that the user has received, allowing the user to review it. The user can then review the converted image and request re-editing if necessary. For example, the user can send a request to change the color of the costume or the position of accessories.

[1215] The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it, allowing the process to be repeated, fine-tuning the image until the user is finally satisfied.

[1216] Finally, once a user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[1217] For example, a user can choose an anime character's costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing them to make fine adjustments until they are satisfied. In this way, users can easily generate high-quality cosplay images.

[1218] This system will significantly reduce the costs and effort required to enjoy cosplay, making it easier for many people to enjoy cosplay.

[1219] The processing flow will be explained below.

[1220] Step 1:

[1221] The user launches the smartphone app and opens the photo capture screen.

[1222] Step 2:

[1223] The user takes a photo of themselves using the smartphone camera.

[1224] Step 3:

[1225] The device temporarily stores the captured photos in its internal storage.

[1226] Step 4:

[1227] The user reviews the photos they have taken and, if they are satisfied, taps the "Upload" button.

[1228] Step 5:

[1229] The device encrypts the photo and sends it to the application server.

[1230] Step 6:

[1231] The server receives the uploaded photos and temporarily stores them in a database.

[1232] Step 7:

[1233] The server passes the photo data to the AI ​​analysis module and begins image analysis.

[1234] Step 8:

[1235] The AI ​​analysis module extracts the user's facial and body features from the photo and identifies detailed feature points.

[1236] Step 9:

[1237] The server generates base data for optimal costume transformation based on the extracted features.

[1238] Step 10:

[1239] Users select cosplay costumes and characters within the app.

[1240] Step 11:

[1241] The terminal transmits data of the costume and character selected by the user to the server.

[1242] Step 12:

[1243] The server combines the received selection information with the analysis results and inputs them into the image generation AI model.

[1244] Step 13:

[1245] Based on the analysis results and selected information, the generative AI model converts the user's original photo into the specified cosplay costume or character appearance.

[1246] Step 14:

[1247] The server temporarily stores the generated converted image and transmits it to the terminal.

[1248] Step 15:

[1249] The terminal displays the converted image received from the server to the user.

[1250] Step 16:

[1251] The user can check the converted image in real time and request re-editing if necessary.

[1252] Step 17:

[1253] The terminal transmits the user's re-editing request to the server.

[1254] Step 18:

[1255] The server again uses the generative AI model to generate a new transformed image based on the request and sends it to the device.

[1256] Step 19:

[1257] When the user is finally satisfied with the transformed image, he taps the "Save" button.

[1258] Step 20:

[1259] The device saves the converted image in local storage.

[1260] Step 21:

[1261] Users can share saved images on social media platforms.

[1262] Example 1

[1263] 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."

[1264] In recent years, cosplay has become popular among many people, but it takes a lot of time and money to actually purchase cosplay costumes, apply makeup, and take photos. Furthermore, the quality of cosplay depends on the individual's skill and financial resources, making it difficult for beginners to participate. Furthermore, there is a demand for a way to easily enjoy cosplay at home without attending an event. The purpose of this invention is to solve these problems.

[1265] 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.

[1266] In this invention, the server includes means for analyzing images and extracting the user's facial and whole-body features, means for converting the images into cosplay costumes or character appearances using a generation AI based on the extracted features, and means for returning and displaying the converted images to the user's terminal, thereby enabling users to easily generate and enjoy cosplay images.

[1267] The "means for taking pictures" refers to the functions and devices that allow a user to take pictures using a terminal.

[1268] The "means for transmitting captured images to a server" is a communication means for uploading image data from a user's terminal to a server.

[1269] "Means for the server to analyze images and extract the user's facial and body features" refers to analytical technologies and algorithms for identifying the user's facial and body features based on the image data received by the server.

[1270] "Method of transforming an image into a cosplay costume or character appearance using generative AI based on extracted features" refers to the process and technology of using analyzed feature data as input and a generative AI model to transform an image into any cosplay costume or character.

[1271] The "means for returning the converted image to the user terminal and displaying it" refers to a communication and display function for transmitting the generated cosplay image to the user terminal and displaying it on the terminal.

[1272] "Means for users to save and share images" refers to a function that allows users to save the final generated image on their device and easily share it on social media or other platforms.

[1273] The "means for a user to request re-editing of a converted image" refers to an interface and communication means for a user to request additional changes or modifications to a converted image and to repeat the generation process.

[1274] This invention provides a system that uses AI generation technology to allow users to easily enjoy cosplay. This system is composed of a terminal such as a smartphone, a server, and advanced AI analysis and generation functions. Specific embodiments for implementing the invention are described below.

[1275] First, the user launches the app on their smartphone. The app provides an interface for selecting cosplay costumes and characters. Using this interface, the user selects the cosplay look they want to wear. Next, the user takes a photo using the app's camera function. When the user taps the capture button, the device captures the photo and temporarily saves the data in internal storage. The user then checks the image they have taken and taps the upload button to send it to the server.

[1276] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to an AI analysis module, which begins analysis. This AI analysis module combines facial recognition and body feature extraction technologies. The server extracts the user's facial and body features through analysis and inputs them into a generative AI model (e.g., GANs or VAE). This generative AI model then converts the user's image into the specified cosplay costume or character in real time based on the extracted features.

[1277] The generated transformed image is sent from the server to the user's device. The device displays the received transformed image for the user to review. The user can review the transformed image and request re-editing if necessary. For example, the user can request corrections to the color of the costume or the position of accessories. The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it. This process can be repeated, allowing the user to make fine adjustments until they are finally satisfied.

[1278] Finally, once the user is satisfied with the resulting image, the device saves it to its internal storage, where it can be easily shared on social media platforms with just one tap within the app.

[1279] Specific operation example

[1280] For example, a user can choose an anime character's costume, take a photo, and the image is analyzed on the server and transformed into the character's appearance using a generative AI model. The result is sent back to the user's device in real time, allowing them to fine-tune it until they are satisfied. When the user is finally satisfied, the image is saved on their device and can be easily shared on social media.

[1281] An example of a prompt is, "Based on the photo below, please transform it into the specified anime character's appearance. Use blue hair, a red outfit, and a smiling face." In this way, users can easily generate high-quality cosplay images.

[1282] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1283] Step 1:

[1284] The user launches the app on their smartphone and selects a cosplay costume and character.

[1285] Input: User actions

[1286] What it does: The user launches the app and selects a cosplay costume and character from the interface provided. The app saves the selection information to its internal storage.

[1287] Output: Selected cosplay costume and character information

[1288] Step 2:

[1289] The user takes a photo using the camera function within the app.

[1290] Input: A photo taken by the user

[1291] Specific operation: The user taps the capture button, the device camera takes a photo, and the captured image data is temporarily stored in the internal storage.

[1292] Output: Captured image data

[1293] Step 3:

[1294] The user checks the image they have taken, taps the upload button, and sends the image data to the server.

[1295] Input: Captured image data, user operations

[1296] Specific operation: After taking a photo, the user checks the image displayed on the screen and taps the upload button. The device then sends the image data to the server.

[1297] Output: Image data uploaded to the server

[1298] Step 4:

[1299] The server receives the uploaded images and temporarily stores them in a database.

[1300] Input: Uploaded image data

[1301] Specific operation: The server temporarily stores the received image data in a database. After storing it, it prepares it for analysis.

[1302] Output: Image data stored in a database

[1303] Step 5:

[1304] The server passes the image data to an AI analysis module, which extracts the user's facial and body features.

[1305] Input: Image data stored in a database

[1306] How it works: The server uses an AI analysis module to analyze the image data and extract the user's facial and body features. The analysis uses facial recognition technology and body feature extraction algorithms.

[1307] Output: Extracted feature data

[1308] Step 6:

[1309] Based on the extracted feature data, the server uses a generative AI model to convert the image into a cosplay costume or character appearance.

[1310] Input: Extracted feature data, selected cosplay costume and character information

[1311] How it works: The server uses generative AI models such as GANs and VAE to convert the user's image into the specified cosplay costume or character. During this process, the extracted feature data is used as base data.

[1312] Output: The converted image data

[1313] Step 7:

[1314] The server transmits the converted image data to the user's terminal, which displays it.

[1315] Input: Transformed image data

[1316] Specific operation: The server sends the converted image data back to the user's device, and the device displays the received image within the app.

[1317] Output: The converted image displayed on the user's device

[1318] Step 8:

[1319] The user may check the converted image and send a request for re-editing.

[1320] Input: Converted image data, user operations

[1321] Specific operation: The user checks the displayed converted image and, if any changes are necessary, sends a request for re-editing, such as inputting a prompt to modify the color of the costume or the position of accessories.

[1322] Output: Re-edit request (prompt text)

[1323] Step 9:

[1324] The server again uses the generative AI model to generate and resend a new transformed image based on the re-editing request.

[1325] Input: Reedit request, initial converted image data

[1326] Specific operation: The server re-runs the generative AI model based on the re-editing request to generate a new converted image, which is then sent back to the user's device.

[1327] Output: Re-edited image data, new image sent to user's device

[1328] Step 10:

[1329] When an image that the user is finally satisfied with is generated, the terminal stores the image.

[1330] Input: Final converted image data, user operations

[1331] Specific operation: The user confirms the final image they are satisfied with, and the device saves this image in its internal storage.

[1332] Output: Image data stored in internal storage

[1333] Step 11:

[1334] Users can share the saved images on social media etc.

[1335] Input: Image data stored in the internal storage, user operations

[1336] Specific operation: The user taps the share button within the app and posts the saved image to social media etc. The entire sharing process is designed to be easily performed within the app.

[1337] Output: Image data posted on social media etc.

[1338] (Application example 1)

[1339] 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."

[1340] Current cosplay try-on systems do not allow users to try on costumes or character appearances in real time before actually purchasing them. Furthermore, they lack an interface that allows for fine adjustments such as the color of the try-on image or the position of accessories, preventing users from achieving high satisfaction. A system that solves this issue and allows many users to easily enjoy a high-quality cosplay experience is needed.

[1341] 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.

[1342] In this invention, the server includes means for [analyzing an image and extracting the user's facial and whole-body features], means for [using generative AI to convert the image into a specific outfit or character appearance based on the extracted features], and means for [providing an interface for the user to adjust the color and position of accessories in the image]. This allows the user to try out specific outfits or character appearances in real time, make fine adjustments, and regenerate them as many times as necessary until they are satisfied.

[1343] The "means for taking an image" refers to a camera function and its control interface for capturing an image of the user's face or whole body.

[1344] The "means for transmitting captured images to a server" refers to a communication function and protocol for uploading acquired image data to a server via the Internet.

[1345] "Means for the server to analyze images and extract features of the user's face and body" refers to the process of using an AI analysis module to identify features of the user's face and body from uploaded images and store them in a database.

[1346] "Means of using generative AI to transform an image into a specific costume or character appearance based on extracted features" refers to the process in which a generative AI model transforms an image based on the user's feature point data and selected costume or character information.

[1347] The "means for returning and displaying the converted image to the user's terminal" refers to a communication and display function for sending the generated cosplay image to the user's device and displaying it on the application.

[1348] "Means for providing an interface for users to adjust the color of an image or the position of accessories" refers to an operation screen and control functions that allow users to fine-tune the color and position of clothing in an image.

[1349] "Means for regenerating images until the user is satisfied" refers to the process of reapplying the generative AI model in response to the user's adjustment requests to generate an updated image.

[1350] "Means for users to save and share images" refers to a function that allows users to save the final generated image on their device and share it on external services such as social networking sites.

[1351] MODE FOR CARRYING OUT THE INVENTION

[1352] The system for implementing this invention provides users with the experience of enjoying cosplay, and includes the following elements.

[1353] Hardware and Software

[1354] Hardware:

[1355] Smartphones (e.g. iPhone, Android devices)

[1356] Head-mounted displays (e.g., Oculus Quest, HTC Vive)

[1357] Server (for back-end processing)

[1358] software:

[1359] AI analysis module: TensorFlow, PyTorch

[1360] Image processing: OpenCV

[1361] Server: Node.js, Python (Flask, Django)

[1362] Front-end frameworks: React Native, Swift (iOS), Kotlin (Android)

[1363] Virtual / AR: ARKit (iOS), ARCore (Android)

[1364] System processing overview

[1365] Users launch the app on their smartphone, select the cosplay costume and character they want to try on, take a picture of themselves using the app's camera, and send the image to the server.

[1366] The server passes the received image to an AI analysis module, which extracts facial and full-body features. Based on these features, the generative AI model converts the image into the selected costume and character appearance, and sends it back to the user's device in real time. The returned image is displayed within the app for the user to review.

[1367] Additionally, users can use the provided interface to adjust the image's color, the position of decorations, etc. Then, they can again manipulate the generative AI model to generate a new image, and the process is repeated. Finally, once an image that satisfies the user is generated, they can save it using the app's save and share functions and share it on social media.

[1368] Specific examples

[1369] For example, let's say a user wants to choose a costume for a famous anime character. In that case, they launch the smartphone application and select the desired character costume from a list. Next, they take a photo of themselves using their camera and send the image to the server. The server then analyzes the image using an AI analysis module, extracts feature points, and converts them into the character's appearance using a generative AI model.

[1370] The converted image is sent back to the user's smartphone and can be viewed on the application. If the user wants to fine-tune the color of the outfit or the position of the accessories, they can easily do so using the interface, and then the generative AI model can generate a new image for them to view.

[1371] Prompt Sentence Examples

[1372] "Turn on your smartphone camera and select a specific character's outfit. Tap the capture button to view the converted image. Adjust the color tone, generate the final image again, and share it on social media."

[1373] This invention allows users to easily enjoy a high-quality cosplay experience, and allows them to adjust the details of color and design. The server performs image analysis and conversion in real time, allowing users to instantly see the results and optimize until they are satisfied.

[1374] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1375] Program processing steps

[1376] Step 1:

[1377] The user launches the smartphone application. Using the provided interface, the user selects the cosplay costume and character they want to try on. The input is information about the costume and character selected by the user, and the output is saved on the device.

[1378] Step 2:

[1379] The user takes a photo of themselves using the device's camera function. Images of the user's face and whole body are obtained as input, and the image data is temporarily saved in the device's internal storage as output. Specifically, the user taps the capture button, which activates the camera and takes the photo.

[1380] Step 3:

[1381] The user taps the upload button to send the captured image to the server. Image data stored on the device is obtained as input, and the image data is transferred to the server via the network as output. Specifically, the image file is sent to the server via an HTTP request.

[1382] Step 4:

[1383] The server passes the received image data to the AI ​​analysis module, which extracts the user's facial and whole-body features. The received image data is taken as input, and feature point data is generated as output. Specifically, the AI ​​analysis module uses TensorFlow and PyTorch to identify feature points within the image and store them in a database.

[1384] Step 5:

[1385] Based on the extracted feature point data, the server uses a generative AI model to convert the image into a specific costume or character appearance. The input is the feature point data and the costume and character information selected by the user, and the converted image data is generated as the output. Specifically, the generative AI model uses the feature point data to convert the image.

[1386] Step 6:

[1387] The server returns the converted image data to the user's device, which then displays it. The converted image data is obtained as input, and the converted image is displayed on the device's display as output. Specifically, the server sends the image data as an HTTP response, and the device displays the received image on the screen.

[1388] Step 7:

[1389] The user adjusts the color of the image and the position of decorations using the provided interface. The user's adjustment instructions are received as input, and the adjusted parameters are saved on the device as output. Specifically, the user operates the controls on the interface to make adjustments.

[1390] Step 8:

[1391] The server again uses the generative AI model to generate a new image based on the user's adjustment instructions and sends it to the user's device. The adjusted parameters are obtained as input, and adjusted image data is generated as output. Specifically, the server uses the adjustment parameters and feature point data to generate a new image using the generative AI model and send it to the device.

[1392] Step 9:

[1393] Once a final image that satisfies the user is generated, the user saves it to their device and shares it. The final image data is obtained as input, and the image is saved to the device's local storage as output, ready to be shared. Specifically, the user taps the save button, and the image data is saved to the device. The user can also tap the share button to upload the image to social media sites, etc.

[1394] 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.

[1395] This invention combines generative AI technology with an emotion engine to provide a system that allows users to easily enjoy cosplay. Specific embodiments for carrying out the invention will be described below.

[1396] First, the user launches the smartphone app. The app provides an interface for selecting cosplay costumes and characters. The app also has an emotion engine that recognizes emotions from the user's facial expressions and voice. Using this interface, the user can select the cosplay look they want to wear, or use the options suggested by the emotion engine.

[1397] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the smartphone (device) captures the photo and temporarily saves the data in its internal storage. The user checks the image and taps the upload button to send it to the server.

[1398] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which then begins analysis. The AI ​​analysis module extracts the user's facial and body features from the image and identifies detailed feature points. These extraction results are used as base data for the generative AI model.

[1399] The server then uses the extracted features to convert the image into the cosplay costume and character selected by the user. The generative AI model uses this data to convert the user's image into the specified cosplay costume and character in real time. The converted image data is then sent back from the server to the user's device.

[1400] The device displays the converted image that the user has received, allowing the user to review it. The user can then review the converted image and request re-editing if necessary. For example, the user can send a request to change the color of the costume or the position of accessories.

[1401] The server then uses the generative AI model again to generate a new transformed image based on the user's request and resends it, allowing the process to be repeated, fine-tuning the image until the user is finally satisfied.

[1402] The emotion engine analyzes the user's emotions from their facial expressions and voice and sends that data to the server. Based on the emotional data, the server can learn what kind of cosplay costumes and characters the user chooses, and make optimal suggestions for future selections.

[1403] Finally, once a user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[1404] For example, a user can choose an anime character costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing them to make fine adjustments until they are satisfied. An emotion engine then reads the user's facial expressions and optimizes the suggestions for the next cosplay. In this way, users can easily generate high-quality cosplay images.

[1405] This system will significantly reduce the cost and effort required to enjoy cosplay, making it easier for many people to enjoy cosplay. It will also take user emotions into consideration, making it possible to provide a more personalized experience.

[1406] The processing flow will be explained below.

[1407] Step 1:

[1408] The user launches the app on their smartphone and opens the photo-taking screen. The app has an interface for selecting cosplay costumes and characters, as well as an emotion engine.

[1409] Step 2:

[1410] The emotion engine acquires the user's facial information and voice data in real time and begins emotion analysis.

[1411] Step 3:

[1412] Based on the analysis results of the emotion engine, the device will suggest the most suitable cosplay costumes and characters for the user. The user can then follow the suggestions or choose their own preferred costumes and characters.

[1413] Step 4:

[1414] The user takes a photo of themselves using the smartphone camera.

[1415] Step 5:

[1416] The device temporarily stores the captured photos in its internal storage.

[1417] Step 6:

[1418] The user reviews the photos they have taken and, if they are satisfied, taps the "Upload" button.

[1419] Step 7:

[1420] The device encrypts the photo and sends it to the application server.

[1421] Step 8:

[1422] The server receives the uploaded photos and temporarily stores them in a database.

[1423] Step 9:

[1424] The server passes the photo data to the AI ​​analysis module and begins image analysis.

[1425] Step 10:

[1426] The AI ​​analysis module extracts the user's facial and body features from the photo and identifies detailed feature points.

[1427] Step 11:

[1428] The server generates base data for optimal costume transformation based on the extracted features.

[1429] Step 12:

[1430] The device receives the analysis results from the server and converts the image using a generative AI model based on the generated base data.

[1431] Step 13:

[1432] Based on the analysis results and selected information, the generative AI model converts the user's original photo into the specified cosplay costume or character appearance.

[1433] Step 14:

[1434] The server temporarily stores the generated converted image and transmits it to the terminal.

[1435] Step 15:

[1436] The terminal displays the converted image received from the server to the user.

[1437] Step 16:

[1438] The user can check the converted image in real time and request re-editing if necessary.

[1439] Step 17:

[1440] The terminal transmits the user's re-editing request to the server.

[1441] Step 18:

[1442] The server again uses the generative AI model to generate a new transformed image based on the request and sends it to the device.

[1443] Step 19:

[1444] When the user is finally satisfied with the transformed image, he taps the "Save" button.

[1445] Step 20:

[1446] The device saves the converted image in local storage.

[1447] Step 21:

[1448] The device transmits the emotion data analyzed by the emotion engine to the server.

[1449] Step 22:

[1450] The server learns the user's preferences based on the emotional data and reflects them in future suggestions.

[1451] Step 23:

[1452] Users can share saved images on social media platforms.

[1453] Example 2

[1454] 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."

[1455] Conventional cosplay experience provision systems require users to acquire costumes, wear them, and take photos themselves, which is time-consuming. Furthermore, the images must be manually edited, requiring specialized knowledge and skills, making it difficult for anyone to easily obtain high-quality cosplay images. Furthermore, the lack of personalized suggestions based on the user's emotions and preferences limits the user experience. Therefore, there is a need for a system that allows users to easily generate high-quality cosplay images and provides a personalized experience in the process.

[1456] 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.

[1457] In this invention, the server includes means for [analyzing images and extracting the user's facial and whole-body features], means for [using generative AI to convert the image into a cosplay costume or character appearance based on the extracted features], and means for [analyzing the user's facial expressions and voice using an emotion engine to suggest cosplay costumes and characters]. This enables [users to easily obtain high-quality cosplay images without requiring specialized knowledge or skills, and furthermore, to receive personalized suggestions tailored to each individual user].

[1458] "Means for taking images" means [a device or function that provides a camera function for users to take images of themselves].

[1459] "Means for sending captured images to a server" refers to a communication function that allows a user to send captured image data to a remote server.

[1460] "The means by which the server analyzes images and extracts the user's facial and body features" refers to an AI analysis module that identifies and analyzes the user's facial and body features from the image data received by the server.

[1461] "Means of using generative AI to transform images into cosplay costumes or character appearances based on extracted features" means "a function that uses a generative AI model to transform a user's image into a cosplay costume or character appearance in real time based on extracted features."

[1462] "Means for returning and displaying the converted image to the user's device" refers to the communication and display function for sending the image data converted by the generating AI to the user's device and displaying it on that device.

[1463] "Means for users to save and share images" refers to a function that allows users to save images they are satisfied with to internal storage and easily share them on social media, etc.

[1464] "A means of analyzing the user's facial expressions and voice using an emotion engine to suggest cosplay costumes and characters" means "a function that uses an emotion engine to analyze the user's facial expressions and voice data, and suggests appropriate cosplay costumes and characters based on the results."

[1465] "A means by which a user can submit a re-editing request and re-generate the image using the generative AI model" is [a process by which a user can request changes to an image and re-run the generative AI model to re-generate the image].

[1466] This invention is a system that allows users to easily enjoy cosplay, and combines generative AI technology with an emotion engine. To implement this invention, the following specific steps are taken.

[1467] First, the user launches the smartphone app, which provides an interface for selecting cosplay costumes and characters. The app also includes an emotion engine that recognizes emotions from the user's facial expressions and voice.

[1468] Using this interface, users can select the cosplay look they want to wear or use options suggested by the emotion engine, which will then make optimal suggestions based on the user's previous choices and facial expression data.

[1469] Next, the user takes a photo using the camera function in the app. When the user taps the capture button, the device captures the photo and temporarily saves the data in the internal storage. The user checks the captured image and taps the upload button to send it to the server.

[1470] The server receives the uploaded image and temporarily stores it in a database. The server then passes the image data to the AI ​​analysis module, which extracts the user's facial and body features from the image and identifies detailed feature points.

[1471] Based on the extracted features, the server then uses a generative AI model to transform the user's image into the specified cosplay costume and character, which is designed to accurately reflect the user's features.

[1472] The converted image data is sent back from the server to the user's device. The device displays the converted image so that the user can review it. The user can review the converted image and request re-editing if necessary. For example, this could include changing the color of the costume or the position of accessories.

[1473] The server re-runs the generative AI model based on the user's re-editing request to generate a new transformed image, then re-submits the re-generated image. This process is repeated until the user is finally satisfied.

[1474] The emotion engine analyzes the user's emotions from their facial expressions and voice and sends that data to the server, which uses this data to learn what kind of cosplay costumes and characters the user chooses, and can make optimal suggestions the next time they choose.

[1475] Finally, once the user is satisfied with the resulting image, it is saved to the device's internal storage and can be easily shared on social media platforms with just one tap within the app.

[1476] For example, a user can choose an anime character costume and take a photo. The image is then analyzed on the server and converted into the character's appearance using a generative AI model. The results are sent back to the user's device in real time, allowing the user to make fine adjustments until satisfied. The emotion engine then reads the user's facial expressions and optimizes the suggestions for the next cosplay. In this way, users can easily generate high-quality cosplay images.

[1477] An example of a prompt is, "I would like you to select a cosplay costume of the anime character 'Naruto' and take a photo of it, and have it transformed in real time." This allows the server to generate a transformed image based on the user's request in real time and send it to the device.

[1478] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1479] Step 1:

[1480] The user launches the dedicated app.

[1481] Specific operation: The user taps the dedicated app icon on the smartphone to launch the application. The app's startup screen is displayed.

[1482] Step 2:

[1483] The user selects a cosplay.

[1484] How it works: Users select the character they want to become from a list of cosplay costumes and characters displayed within the app. The emotion engine may suggest the most suitable cosplay based on the user's past choices and facial expression data.

[1485] Input: User selection or emotion engine suggestion

[1486] Output: Data of selected cosplay characters and costumes

[1487] Step 3:

[1488] The user takes a photo.

[1489] Specific operation: The user takes a photo of themselves using the camera function in the app. When the user taps the capture button, the device acquires the photo data and temporarily stores it in the internal storage.

[1490] Input: A photo taken by the user

[1491] Output: Photo data temporarily saved in the internal storage

[1492] Step 4:

[1493] The user sends the photo to the server.

[1494] Specific operation: The user checks the photos they have taken and taps the upload button to send them to the server. The device uses its Internet connection to send the photo data to the server.

[1495] Input: Photo data stored on the device

[1496] Output: Photo data sent to the server

[1497] Step 5:

[1498] The server receives and stores the images.

[1499] Specific operation: The server receives the photos sent by the user and temporarily stores them in a database, which allows subsequent analysis and processing.

[1500] Input: Photo data sent from the device

[1501] Output: Photo data stored in a database

[1502] Step 6:

[1503] The server performs the AI ​​analysis.

[1504] How it works: The server passes the stored image data to the AI ​​analysis module, which then begins analyzing the image. This module extracts the user's facial and body features and identifies detailed feature points.

[1505] Input: Photo data stored in the database

[1506] Output: Extracted facial and body feature data

[1507] Step 7:

[1508] The server converts the image.

[1509] How it works: The server uses a generative AI model based on the extracted feature data to transform the user's image into the specified cosplay costume or character, accurately reflecting the user's features.

[1510] Input: Extracted facial and body feature data, selected cosplay character data

[1511] Output: Image data converted to cosplay

[1512] Step 8:

[1513] The server transmits the converted image to the user terminal.

[1514] Specific operation: The converted image data is sent from the server to the user's device, and the user can check the converted image in real time.

[1515] Input: Image data converted to cosplay

[1516] Output: The converted image data sent to the terminal

[1517] Step 9:

[1518] The device displays the image and accepts requests for re-editing.

[1519] Specific operation: The device displays the received converted image for the user to review. If the user needs to re-edit it, they can submit a re-edit request, such as changing the color of the costume or the position of accessories.

[1520] Input: Converted image data sent from the server

[1521] Output: User's edit request

[1522] Step 10:

[1523] The server will regenerate and resend.

[1524] Specific operation: The server re-runs the generative AI model based on the user's request to generate a new transformed image. It then sends the re-generated image back to the user's device. This process is repeated until the user is satisfied.

[1525] Input: User re-edit request

[1526] Output: Regenerated transformed image data

[1527] Step 11:

[1528] The emotion engine performs analysis and data transmission.

[1529] How it works: The emotion engine analyzes the user's emotions from their facial expressions and voice, and sends that data to the server, which uses it to make the next recommendation.

[1530] Input: User's facial expressions and voice data

[1531] Output: Sentiment analysis data

[1532] Step 12:

[1533] Save and share the final image.

[1534] How it works: Once a final image is created that the user is happy with, the device saves it to internal storage. This image can then be easily shared on social media platforms with just one tap within the app.

[1535] Input: Regenerated final transformed image data

[1536] Output: Final image data saved and shared

[1537] (Application example 2)

[1538] 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."

[1539] Conventional try-on systems and cosplay experiences require users to physically try on costumes, which can be time-consuming and expensive. Users typically spend a lot of time and effort searching for a costume that suits them best. Furthermore, sharing the results of a try-on with friends and family requires additional steps, such as taking photos and uploading them to social media. The present invention aims to solve these problems by providing a system that allows users to try on costumes more easily and quickly and share the results.

[1540] 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 capturing an image, means for transmitting the captured image to the server, means for the server to analyze the image and extract the user's facial and whole-body features, means for converting the image into an outfit or character appearance using a generative AI based on the extracted features, means for returning the converted image to the user terminal and displaying it, means for the user to save and share the image, and means for analyzing emotions from the user's facial expressions and voice using an emotion engine and suggesting outfits based on the emotions. This allows the user to quickly and easily try on outfits without actually physically wearing them, and to check and share the results in real time.

[1541] "Means for taking images" refers to a mechanism that allows a user to take still images or videos using a device such as a camera.

[1542] The "means for transmitting captured images to a server" refers to a method and mechanism for transferring captured image data to a remote server via a network.

[1543] "Means for the server to analyze the image and extract the user's facial and body features" refers to algorithms and computer programs that process the transmitted image data and identify the user's facial shape, body shape, and other features.

[1544] "Method of converting an image into a costume or character appearance using generative AI based on extracted features" refers to a technology that uses a generative AI model to virtually change an image into a costume or character appearance, using the user's facial and body features.

[1545] The "means for returning and displaying the converted image to the user terminal" is a mechanism for transmitting the converted image data to the user's device over the network and displaying it on the display of that device.

[1546] "Means for users to save and share images" refers to the mechanism by which the converted image data is saved in the user's device storage and then shared with others on platforms such as social media.

[1547] "A means of using an emotion engine to analyze emotions from a user's facial expressions and voice, and suggest outfits based on those emotions" is a technology that recognizes emotions from a user's facial expressions and voice data, and automatically suggests optimal outfits based on the results.

[1548] The present invention is a system that allows users to easily enjoy cosplaying as costumes and characters. Detailed embodiments of the invention are described below.

[1549] First, the user launches an application installed on a device such as a smartphone, tablet, or smart glasses. The application provides an interface for selecting costumes and characters. The user uses this interface to select the costume or character they want to try on. Once the selection is complete, the user takes a picture of themselves using the device's camera.

[1550] Once the image is captured, the device temporarily stores the image data in its internal storage. The image data is then sent over the network to a server, which analyzes the received image data and extracts the user's facial and body features, often using the dlib library.

[1551] Once the analysis is complete, a generative AI model transforms the image based on the extracted feature data. The generative AI model is implemented using deep learning frameworks such as Keras and TensorFlow, and converts the user's image into the specified outfit or character. An emotion engine is also used to analyze the user's emotions from facial expressions and voice data, and then suggests the optimal outfit based on those emotions.

[1552] The converted image data is sent back to the user's device from the server and displayed on the device's screen. The user can review the results and make further fine adjustments, such as the color of the outfit or the position of the accessories. The device then sends a re-editing request to the server, which then uses the generative AI model to generate and return a new converted image. This process is repeated until the user is satisfied.

[1553] Finally, once a satisfactory image is generated, it is saved in the device's internal storage. The image can then be shared on social media platforms with a single tap. The emotion engine also learns from the user's selection and emotion data to optimize future suggestions.

[1554] Below are some examples of specific usage scenarios and prompts:

[1555] Specific usage scenarios:

[1556] 1. The user wears smart glasses installed in a physical store.

[1557] 2. The camera in the smart glasses captures the user's image and the app performs emotion analysis.

[1558] 3. Emotional data is analyzed to show that the user has a happy expression, and the suggested outfit is a party dress.

[1559] 4. Once the user selects a dress, the generative AI overlays the dress onto the user's video in real time.

[1560] 5. Share your try-on results on social media.

[1561] Example prompt sentence:

[1562] Choose the perfect dress for your birthday party and generate a real-time overlay image that will make your user look happy and smiling.

[1563] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1564] Step 1:

[1565] A user launches an application installed on a device such as a smartphone, tablet, or smart glasses. Using the application's interface, the user selects the costume or character they want to try on. The input is the user's selection data, and the output is information about the selected costume or character.

[1566] Step 2:

[1567] The device's camera is used to capture images of the user. When the user taps the capture button, the device temporarily stores still images and videos captured from the camera in its internal storage. The input is the user's real-time video, and the output is the captured image data.

[1568] Step 3:

[1569] The terminal sends the temporarily stored image data to the server via the network. At this time, the image data is encoded into an appropriate format and sent using a protocol that takes security into consideration (e.g., HTTPS). The input is the image data, and the output is the data transfer status to the server.

[1570] Step 4:

[1571] The server analyzes the received image data and extracts the user's facial and body features. Specifically, it uses the dlib library to detect facial landmarks (feature points) and then identifies the user's facial and body features based on those landmarks. The input is the received image data, and the output is the extracted facial and body feature data.

[1572] Step 5:

[1573] The server uses a generative AI model based on the extracted feature data to convert the image into a costume or character appearance. This generative AI model is implemented using deep learning frameworks such as Keras and TensorFlow, and takes face and body shape data as input to generate an image converted into the specified costume or character. The input is feature data and costume information, and the output is the converted image data.

[1574] Step 6:

[1575] The converted image data is sent back to the user's device from the server and displayed on the device's screen, allowing the user to check the conversion results in real time. The input is the converted image data, and the output is the real-time image displayed on the user's device.

[1576] Step 7:

[1577] The user can check the conversion results through the application and request re-editing if necessary. Re-editing requests include changes to the color of the costume or the position of accessories. This request data is sent to the server. The input is the user's re-editing request, and the output is the request data sent to the server.

[1578] Step 8:

[1579] The server receives the re-editing request, again uses the generative AI model to generate a new transformed image and sends it back to the device. This process is repeated until the user is satisfied. The input is the re-editing request data, and the output is the newly transformed image data.

[1580] Step 9:

[1581] Finally, once a satisfactory image is generated, the device saves it to its internal storage. This image can then be shared on social media platforms with a single tap from within the application. The input is the final, verified image data, and the output is the saved image data and a link for sharing.

[1582] Examples:

[1583] Example prompt: "Choose the perfect dress for a birthday party and generate a real-time overlay image. The user will look happy and smiling."

[1584] 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.

[1585] 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.

[1586] 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.

[1587] 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.

[1588] 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.

[1589] 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.

[1590] 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).

[1591] 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.

[1592] 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."

[1593] 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.

[1594] 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).

[1595] 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.

[1596] 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.

[1597] 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.

[1598] 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.

[1599] 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.

[1600] 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.

[1601] 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.

[1602] 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.

[1603] 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.

[1604] 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.

[1605] The following is further disclosed regarding the above embodiment.

[1606] (Claim 1)

[1607] a means for capturing an image;

[1608] A means for sending the captured image to the server;

[1609] The server analyzes the image and extracts the user's facial and body features.

[1610] [Using generative AI to convert images into cosplay costumes or character appearances based on extracted features], and

[1611] A means for returning the converted image to the user's device and displaying it; and

[1612] a means for users to save and share images;

[1613] A system including:

[1614] (Claim 2)

[1615] 10. The system of claim 1 [including a generative AI model for analyzing image features].

[1616] (Claim 3)

[1617] The system of claim 1 [including an interface for the user to select a cosplay costume and character].

[1618] "Example 1"

[1619] (Claim 1)

[1620] a means for capturing an image;

[1621] A means for sending the captured image to the server;

[1622] The server analyzes the image and extracts the user's facial and body features.

[1623] [Using generative AI to convert images into cosplay costumes or character appearances based on extracted features], and

[1624] means for returning the converted image to the user terminal and displaying it;

[1625] a means for users to save and share images;

[1626] A system including a means for a user to request re-editing of a transformed image.

[1627] (Claim 2)

[1628] 10. The system of claim 1 [including a generative AI model for analyzing image features].

[1629] (Claim 3)

[1630] The system of claim 1 [including an interface for the user to select a cosplay costume or character].

[1631] "Application Example 1"

[1632] (Claim 1)

[1633] a means for capturing an image;

[1634] A means for sending the captured image to the server;

[1635] The server analyzes the image and extracts the user's facial and body features.

[1636] [Using generative AI to transform images into specific costumes or character appearances based on extracted features];

[1637] A means for returning the converted image to the user's device and displaying it; and

[1638] [Providing an interface for users to adjust the color and position of ornaments on the image]; and

[1639] A way to regenerate the image until the user is satisfied, and

[1640] a means for users to save and share images;

[1641] A system including:

[1642] (Claim 2)

[1643] 10. The system of claim 1 [including a generative AI model for analyzing image features].

[1644] (Claim 3)

[1645] The system of claim 1 [including an interface for the user to select a particular costume or character].

[1646] "Example 2: Combining Emotion Engines"

[1647] (Claim 1)

[1648] a means for capturing an image;

[1649] A means for sending the captured image to the server;

[1650] The server analyzes the image and extracts the user's facial and body features.

[1651] [Using generative AI to convert images into cosplay costumes or character appearances based on extracted features], and

[1652] A means for returning the converted image to the user's device and displaying it; and

[1653] a means for users to save and share images;

[1654] [Using an emotion engine to analyze the user's facial expressions and voice and suggest cosplay costumes and characters]

[1655] [Users can submit a re-editing request and regenerate the image using the re-generative AI model];

[1656] A system including:

[1657] (Claim 2)

[1658] 10. The system of claim 1 [including a generative AI model for analyzing image features].

[1659] (Claim 3)

[1660] The system of claim 1 [including an interface for the user to select a cosplay costume and character].

[1661] "Application example 2 when combining emotion engines"

[1662] (Claim 1)

[1663] a means for capturing an image;

[1664] A means for sending the captured image to the server;

[1665] The server analyzes the image and extracts the user's facial and body features.

[1666] [Using generative AI to transform images into costumes and character appearances based on extracted features];

[1667] A means for returning the converted image to the user's device and displaying it; and

[1668] a means for users to save and share images;

[1669] [Using an emotion engine to analyze emotions from the user's facial expressions and voice, and suggest outfits based on those emotions]

[1670] A system including:

[1671] (Claim 2)

[1672] 10. The system of claim 1 [including a generative AI model for analyzing image features].

[1673] (Claim 3)

[1674] The system of claim 1 [including an interface for the user to select an outfit and character]. [Explanation of symbols]

[1675] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for capturing an image; A means for transmitting the captured image to a server; The server analyzes the image and extracts the user's facial and body features. A method to convert images into cosplay costumes or character appearances using generative AI based on extracted features, and means for returning and displaying the converted image to the user terminal; A means for users to save and share images; A system including:

2. 10. The system of claim 1, including a generative AI model for analyzing image features.

3. The system of claim 1 further comprising an interface for a user to select a cosplay costume and a character.

Images