system

Abstract

We provide the system. [Solution] A means of receiving size data and fashion preferences from users and generating personal profiles, A means of suggesting clothing that matches the user's profile based on multiple fashion data stored in a database, A means of generating and outputting positive feedback for the clothing selected by the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, there is a problem that individuals lack confidence in their fashion choices. Also, it is difficult to find appropriate clothing from a vast number of options, and users may feel stressed. Furthermore, it is difficult for all family members to enjoy fashion with a sense of unity, and there is a demand for precise fitting and personalized advice tailored to individuals.

Means for Solving the Problems

[0005] To address this challenge, we provide a system that receives user size data and fashion preferences and generates a personal profile. Based on multiple fashion data stored in a database, this system suggests clothing that matches the user's profile. Furthermore, it generates and outputs positive feedback for the clothing selected by the user. In addition, it generates family-level profiles and suggests matching outfits for all family members, enabling the whole family to enjoy fashion. It also provides a function that suggests clothing in a virtual space, allowing users to experience virtual try-on.

[0006] "Size data" refers to information about the user's body measurements, which is used to optimize the fit of clothing.

[0007] "Fashion preferences" refer to information that indicates the style and design tendencies that a user likes, and are used to select clothing that is individually suitable for them.

[0008] A "personal profile" is a set of information that integrates each user's size data and fashion preferences, and it forms the basis for providing the most suitable fashion suggestions to the user.

[0009] A "database" is a system that systematically stores multiple fashion data points and serves as a source of information for suggesting and analyzing clothing.

[0010] "Positive feedback" refers to information aimed at boosting user confidence by providing positive evaluations and encouraging messages regarding the user's choices.

[0011] A "family-unit profile" is a set of information that integrates the size data and fashion preferences of all family members, and is used to provide consistent fashion suggestions for the entire family.

[0012] A "virtual space" refers to a digital environment constructed using computer technology, a virtual space that users can experience visually.

[0013] "Virtual try-on" refers to the experience of users trying on clothes in a virtual space, a function that allows them to visually check the fit before actually wearing the clothes. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] [[ID=I4]] First, the terms used in the following description will be explained. [[ID=I6]]

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory where information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the 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 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the 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 processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] The system of this invention is implemented using a terminal and a server, with the aim of providing users with a personalized fashion experience. The user inputs their size data and fashion preferences into the terminal. The terminal transmits the input data to the server, which generates a personal profile based on this data. This profile, consisting of size data and fashion preferences, serves as the foundation for providing optimal fashion suggestions to the user.

[0036] The server analyzes the latest fashion data in the database and selects clothing that matches the user's profile. The selected clothing is sent to the terminal as suggestions and presented to the user. The user can then choose their preferred items from the suggested clothing.

[0037] For each selected garment, the server generates a positive feedback message and sends it to the device. The device displays this message, helping the user gain confidence in their choice. For example, a message like, "That shirt suits your style very well," might be provided.

[0038] Furthermore, to provide family-based fashion suggestions, users can input their family's size data and fashion preferences into the device. Based on this information, the server suggests matching outfits for all family members, and the device displays these suggestions to the user. This allows the whole family to enjoy coordinated fashion choices.

[0039] Furthermore, this system also supports virtual fashion experiences. The server generates visual feedback for the user to try on clothes selected in the virtual space, and the terminal provides this feedback to the user. Through virtual try-on, the user can check the fit of the clothes before actually wearing them.

[0040] In implementing the present invention, these elements work together to function as a system that provides a seamless fashion experience.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user logs into the system using a terminal. The terminal provides the user with an interface for entering size data and fashion preferences. The user enters their height, weight, preferred style, etc.

[0044] Step 2:

[0045] The device sends the data entered by the user to the server. The server receives this data and generates a personal profile. This profile records the user's size information and fashion preferences.

[0046] Step 3:

[0047] The server accesses the database and analyzes multiple fashion data points. Based on the user's profile, it generates a list of suitable clothing items. This list includes clothing that matches the size and style.

[0048] Step 4:

[0049] The server sends the generated clothing list to the terminal. The terminal displays this list to the user and provides an interface for the user to make selections.

[0050] Step 5:

[0051] The user selects clothing items they are interested in. The device sends the selection information to the server. The server generates a positive feedback message for the selected clothing items.

[0052] Step 6:

[0053] The server sends the generated feedback message to the terminal. The terminal displays it to the user, allowing the user to gain confidence in their choice by seeing the positive feedback they received.

[0054] Step 7:

[0055] If the user wishes, they can enter family information into the device. The device sends this data to the server. The server generates a family profile and suggests matching outfits for all family members.

[0056] Step 8:

[0057] The server generates a family outfit coordination suggestion and sends it to the device. The device then presents this suggestion to the user, allowing the whole family to enjoy matching fashion.

[0058] Step 9:

[0059] If a user requests a virtual try-on, the server generates feedback data in a virtual space. The terminal provides the user with a virtual try-on interface, allowing the user to have a digital try-on experience.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] Modern consumers struggle to quickly and efficiently find fashion that suits their preferences and size. They also face challenges in coordinating outfits for the whole family and are hesitant to make purchase decisions without trying on clothes beforehand. The lack of personalized suggestions and virtual try-on experiences is a particular problem.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for receiving biometric information and fashion preferences from the user and generating a personal profile; means for selecting and suggesting clothing that matches the user's profile based on multiple style information stored in an information repository; and means for generating positive messages based on the selection using a generative AI model. This makes it possible to provide the user with personalized fashion suggestions, give them confidence in their choices, and allow them to confirm their choices before purchase through a virtual try-on experience.

[0065] "Biometric information" refers to data that indicates a user's physical characteristics, including height, weight, shoulder width, and waist measurement.

[0066] "Fashion preferences" refer to information that indicates a user's personal fashion tastes and style, including favorite colors, styles, and budget.

[0067] A "personal profile" is a data structure generated based on a user's biometric information and fashion preferences, designed to clarify the user's fashion preferences.

[0068] An "information repository" is a collection of information, including various fashion styles and trends, that is stored in the form of databases or similar media.

[0069] "Style information" refers to detailed data about clothing and fashion accessories, including design, materials, and trending fashions.

[0070] A "generative AI model" is an artificial intelligence program that uses data and employs machine learning and deep learning technologies to automatically generate new information and messages.

[0071] A "positive message" is text that provides positive feedback on the clothing and fashion items selected by the user, thereby increasing their satisfaction and confidence in their choice.

[0072] A "virtual space" is a digital environment created by a computer, where users can interact through digital avatars.

[0073] A "try-on experience" is a simulation process that allows users to virtually check the appearance and fit of the clothing they have selected.

[0074] The system of the present invention is configured using a terminal and a server to provide users with a personalized fashion experience.

[0075] The terminal functions as an input device that receives the user's biometric information (e.g., height, weight, shoulder width, waist measurement, etc.) and fashion preferences (e.g., favorite colors, styles, budget, etc.). The terminal formats this data appropriately and sends it to the server.

[0076] The server generates a personal profile using the received biometric information and fashion preferences. This profile generation utilizes a generative AI model running within the server. The generative AI model analyzes the data through prompt messages and selects the most suitable clothing for the user, taking into account the latest fashion styles and trends.

[0077] The server uses network communication to send selected clothing information to the terminal. This communication takes place, for example, via the Internet Protocol. The server also uses an AI model to generate positive feedback messages for the clothing selected by the user. This helps the user feel confident in their selection and supports their purchase decision.

[0078] As a concrete example, a prompt message might read: "Based on the user's biometric information and fashion preferences, suggest clothing items. Also, generate a positive feedback message for the selected clothing items."

[0079] Furthermore, to enable users to have a fashion experience in a virtual space, the server generates visual feedback for virtual try-ons. This feedback is displayed on the user's device using 3D modeling technology. This allows users to check the fit of the clothes before actually wearing them.

[0080] When these elements are integrated and the server and terminal work together seamlessly, a system is created that provides users with a consistent, personalized, and highly interactive fashion selection experience.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] Users input their biometric information and fashion preferences into the device. The input data includes the user's size (height, weight, shoulder width, waist measurement, etc.) and preferences (favorite colors, styles, budget, etc.).

[0084] In terms of specific actions, the application on the device displays an input form to the user and collects the necessary information.

[0085] Step 2:

[0086] The device organizes the collected biometric information and fashion preferences and sends them to the server as structured data.

[0087] Input: Biometric information and fashion preferences entered by the user.

[0088] Output: Structured data sent to the server

[0089] Specifically, the terminal formats the data and sends it to the server using a secure communication protocol.

[0090] Step 3:

[0091] The server generates a personal profile of the user based on the received data.

[0092] Input: Structured data sent from the device

[0093] Output: Personal Profile

[0094] As part of the data processing, a generative AI model analyzes the data using prompt sentences to derive the optimal fashion style for the user.

[0095] Step 4:

[0096] The server analyzes multiple style records in the database and selects clothing that matches the user's profile.

[0097] Input: User's personal profile and style information in the database

[0098] Output: A list of clothing items recommended for the user.

[0099] Specifically, the server uses a generated AI model to search the database and select the most suitable style.

[0100] Step 5:

[0101] The server transmits information about the selected clothing items to the terminal and presents it to the user.

[0102] Input: List of recommended clothing items

[0103] Output: Clothing options displayed on the device

[0104] In terms of specific operations, the server sends data containing images of clothing and detailed product information to the terminal.

[0105] Step 6:

[0106] The user selects their preferred clothing item from those displayed on the device.

[0107] Input: Clothing options displayed on the device

[0108] Output: User-selected clothing

[0109] In terms of specific actions, the user checks the product details and then makes a selection based on their purchase intent.

[0110] Step 7:

[0111] The server generates a positive feedback message about the selected clothing item and sends it to the terminal.

[0112] Input: Information about the clothing selected by the user

[0113] Output: Feedback message

[0114] Using a generative AI model, messages such as "That blue jacket perfectly matches your style" are generated.

[0115] Step 8:

[0116] The terminal displays feedback messages received from the server to the user.

[0117] Input: Feedback message sent from the server

[0118] Output: Feedback messages viewed by the user

[0119] Specifically, a message pops up on the device to support the user's confidence in their choice.

[0120] (Application Example 1)

[0121] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0122] Traditionally, it has been difficult for consumers to easily and intuitively select fashion that suits their individual needs, and virtual try-on experiences have lacked realism. Therefore, there is a need for technology that allows consumers to confidently choose their own style and to have a realistic try-on experience in a virtual space.

[0123] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0124] This invention includes a server, a method for receiving size information and fashion preferences from a user and generating an individual profile; means for selecting clothing that matches the user's profile based on a large amount of stored fashion information; a method for generating and displaying positive feedback for the clothing selected by the user; and a device for providing a three-dimensional virtual experience for the user to try on clothing using augmented reality technology. This enables consumers to make more appropriate and confident fashion choices and to have a realistic and attractive try-on experience in a virtual space.

[0125] A "user" is someone who uses the system to receive personalized fashion suggestions and virtual try-on experiences.

[0126] "Size information" refers to data about the user's physical dimensions and clothing size.

[0127] "Fashion preferences" refer to information that indicates a user's tastes and preferences regarding style.

[0128] A "personal profile" is a personalized dataset generated based on a user's size information and fashion preferences.

[0129] "Clothing" refers to clothing and fashion items that are suggested to the user.

[0130] "Positive feedback" refers to encouraging user choices and increasing satisfaction through positive messages.

[0131] Augmented reality technology is a technology that overlays digital information onto the real world, integrating virtual information into the user's real-world field of vision.

[0132] A "three-dimensional virtual experience" is a three-dimensional try-on experience that allows users to feel realistically within a virtual space.

[0133] "Device" refers to the hardware and software used by users to visually experience virtual try-on.

[0134] The system that realizes this invention operates by combining various hardware and software to provide users with a personalized fashion experience. The main hardware used is a visual device such as smart glasses equipped with augmented reality technology that provides users with a virtual try-on experience. For example, smart glasses overlay digital information onto the real field of view, enabling a realistic three-dimensional virtual experience.

[0135] The device receives size information and fashion preferences from the user and sends this information to a server. The server is located in the cloud and uses the received data to generate a personal profile. An AI analysis engine is used to generate this profile, supporting the selection of fashion items that match the user's preferences.

[0136] Next, the server analyzes a large amount of stored fashion information and selects the optimal clothing based on the user's profile. This selection process is highly personalized using a generative AI model. The selected clothing information is sent to the device, allowing the user to virtually try on a series of outfits through smart glasses. Once the user selects an item, the device immediately displays positive feedback to boost their confidence in their choice.

[0137] As a concrete example, imagine a scenario where a user wears smart glasses, accesses a virtual store, and selects a casual shirt and jeans. At this point, feedback such as, "This digital shirt complements your everyday style," is displayed. This allows consumers to make more appropriate and confident choices. An example of a prompt might be, "Woman in her 30s, elegant fashion, size L, office casual."

[0138] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0139] Step 1:

[0140] The device starts up and receives size information and fashion preferences as input from the user. This input is done through an input screen on the device. This involves the user entering their measurements and preferred style into a form displayed on the screen.

[0141] Step 2:

[0142] The terminal sends user input to the server. The server receives this data and generates a personal profile based on the input data. Using a generation AI model, the received data is analyzed and a profile reflecting the user's size and fashion preferences is output. In this process, the AI ​​engine performs calculations to create the profile based on the user data.

[0143] Step 3:

[0144] The server searches a stored fashion information database and selects clothing that matches the user's profile. In this step, the server uses an AI algorithm to extract relevant fashion items from the database and generates the selection results as output. This includes leveraging the latest trend information within the database.

[0145] Step 4:

[0146] The selected clothing list is sent to the device, and the user visually confirms it through smart glasses. This involves the user virtually trying on clothes using augmented reality technology via the glasses device, and seeing themselves in the virtual image.

[0147] Step 5:

[0148] When a user selects a specific outfit, the device sends that selection information to the server. The server generates positive feedback for the selected clothing and outputs a message to the device. The device displays this message, indicating to the user that the selection is appropriate. In this step, a generative AI model performs calculations to generate a positive prompt statement about the selected item.

[0149] Step 6:

[0150] The entire system process is finalized. Log data is saved to the server to record that the user made a satisfactory choice and to incorporate feedback into future suggestions. This involves the terminal interacting with the server to record the user's selection data and use it in subsequent suggestion processes.

[0151] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0152] This invention is a system that incorporates an emotion engine to enhance the user's fashion experience, and is implemented using a terminal and a server. The user inputs their size data and fashion preferences through the terminal. The terminal sends this information to the server, which generates a personal profile. This profile serves as the basis for suggesting the most suitable clothing for the user.

[0153] The server is equipped with an emotion engine that analyzes the user's emotional state during input and selection. The emotion engine infers the user's emotions from their choices and responses while they interact with the device. This information is analyzed in real time and reflected in the fashion suggestions. The server references fashion data in a database and selects the most suitable clothing based on the user's profile and emotional state. The selected clothing list is sent to the device and presented to the user.

[0154] After the user selects clothing, the server considers the emotional information obtained by the emotion engine and dynamically generates positive feedback messages. Specifically, it customizes the feedback message based on the emotional state the user was in when they selected the particular clothing item and sends it to the device. For example, it might provide detailed feedback such as, "This color will refresh your mood!"

[0155] Furthermore, when a user enters family information into their device, the server also uses emotional data to generate family-specific profiles. Based on each member's emotional state, it generates and sends appropriate outfits and feedback for the entire family to the device, providing a cohesive fashion experience.

[0156] This system also supports virtual try-on experiences. An emotion engine recognizes the user's emotions during virtual try-on and uses this information to provide suggestions within the virtual space. This allows users to check fittings without physical try-on and find styles that match their emotions. By specifically implementing this invention, users can obtain a fashion experience that takes their emotions into consideration.

[0157] The following describes the processing flow.

[0158] Step 1:

[0159] The user logs into the system using a terminal and enters size data and fashion preferences. The terminal collects this data and prompts for confirmation of the input through the user interface.

[0160] Step 2:

[0161] The device sends the collected size data and fashion preferences to the server. The server receives this data and generates a personal profile of the user. The profile includes the user's body measurements and style preferences.

[0162] Step 3:

[0163] The server's emotion engine analyzes the user's initial emotional state based on their input and actions. The emotion engine infers the user's emotions based on factors such as the language used and the speed at which choices are made.

[0164] Step 4:

[0165] The server searches the database and, based on the generated profile and sentiment data obtained from the sentiment engine, creates a list of clothing suitable for the user. This list includes items that match the size and style.

[0166] Step 5:

[0167] The server sends a suggested clothing list to the terminal. The terminal displays the list and gives the user the opportunity to make a selection. At the same time, it displays an emotion meter to record the user's feelings at the time of selection.

[0168] Step 6:

[0169] The user selects an item of clothing from a suggested list. The device sends the selection data and emotion meter information to the server. The server updates the emotion data related to the user's selection.

[0170] Step 7:

[0171] The server uses an emotion engine to generate positive feedback messages based on the user's choices. The generated feedback takes the user's emotional state into account, making it more personalized.

[0172] Step 8:

[0173] The server sends the generated feedback message to the terminal. The terminal displays the feedback to the user, providing support to increase confidence in their choice.

[0174] Step 9:

[0175] When a user enters family information, the device collects this information and sends it to the server. The server generates a family-based profile and suggests coordination and feedback based on each member's emotional state.

[0176] Step 10:

[0177] If the user wishes, they can start a virtual try-on. The terminal displays the virtual try-on interface, and the server's emotion engine analyzes the user's emotions during the virtual try-on, enabling more precise fitting suggestions.

[0178] (Example 2)

[0179] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0180] In today's fashion market, while there is a demand for personalized clothing suggestions based on individual user size data and preferences, there are challenges in providing more sophisticated suggestions that take into account the user's emotional state, coordinating outfits for the entire family, and realizing new experiences such as virtual try-on. This challenge makes it difficult for consumers to make the best fashion choices for themselves.

[0181] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0182] In this invention, the server includes means for collecting dimensional information and fashion preferences from the user and generating an individual profile; means for suggesting clothing that suits the user profile based on multiple clothing-related data stored in an information storage device; and means for analyzing the emotional state from the user's actions and selections. This enables personalized clothing suggestions that are in line with the user's emotions.

[0183] "Dimensional information" refers to information about the measured size and dimensions of the user's body.

[0184] A "personalized profile" refers to a personalized dataset based on a user's specific size, preferences, and emotional state.

[0185] "Information storage device" refers to a device for storing and preserving digital information, and includes databases and hard disks.

[0186] "Clothing-related data" refers to information about various clothing items, including attribute information such as design, color, and material.

[0187] "Emotional state" refers to the emotional state a user exhibits in a particular situation, and is a psychological state that influences their behavior and choices.

[0188] A "virtual domain" refers to a visual or conceptual virtual space constructed using computer technology.

[0189] "Personalization" refers to adjusting or customizing something according to the individual characteristics and preferences of the user.

[0190] To implement this system, a server and terminals form the basic communication infrastructure. The server collects user size information and fashion preferences and performs central data processing to create individual user experiences. This system uses an "information storage device" as a database management system, with SQL databases being a specific example.

[0191] The server uses a generative AI model, such as a "natural language processing engine," to analyze the user's emotional state. This AI model has the ability to analyze the user's past choices and input data to infer emotions in real time.

[0192] The terminal is a device that provides an interface with the user, and can specifically be a smartphone or a computer. The terminal sends data from the user to the server and displays personalized clothing suggestions received from the server.

[0193] A concrete example involves a user using their smartphone at home, opening the app, and entering their preferences. If the user prefers a particular color or style, they can enter data related to that preference. This data is encrypted and securely transmitted to the server.

[0194] Specific examples of prompt messages include "Which color suits your mood?" or "Try choosing a style that perfectly matches your mood today." This makes it easier for users to input their emotions more naturally, and the system's suggestions become more appropriate and personalized.

[0195] This system configuration takes into account the user's emotions and size profile, and can also implement features such as family-based and virtual try-on. As a result, it becomes possible to provide a more comprehensive and personalized fashion experience, thereby increasing user satisfaction.

[0196] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0197] Step 1:

[0198] The user inputs their dimensions and fashion preferences using a terminal. The terminal receives this information as input data, packets it, and sends it to the server. Specifically, the user fills in the information in the input form and presses the submit button.

[0199] Step 2:

[0200] The server analyzes the input data received from the terminal and generates individual profiles. This generation process uses a database management system to store the data and create a new profile for each user. Based on the input data, a dataset is created that takes into account the user's preferences and size.

[0201] Step 3:

[0202] The server searches for suitable clothing from a clothing-related database in its information storage device, based on the generated profile. Using database queries, it selects fashion items that match the user's preferences and size. As a result of this process, a list of recommended clothing items is output.

[0203] Step 4:

[0204] The server uses a generative AI model to analyze the user's emotional state. This analysis is based on the user's past selection history and input data, and performs data calculations to estimate the appropriate emotional state. In this process, the attributes most relevant to the user's emotions are extracted.

[0205] Step 5:

[0206] The server takes emotional states into account and dynamically adjusts clothing suggestions. This is done by adding real-time emotional data to the selected clothing list. This process results in more personalized suggestions.

[0207] Step 6:

[0208] The terminal presents the user with the final list of suggestions received from the server. A visual interface is used for this display, allowing the user to review and select the suggested clothing. The user then selects specific items and considers the details.

[0209] Step 7:

[0210] After the user makes a selection, the server generates a positive feedback message. This message is customized based on the emotional state analyzed by the generating AI model. For example, feedback such as "This color suits you well today!" might be output.

[0211] (Application Example 2)

[0212] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0213] Modern consumers demand personalized fashion suggestions tailored to their emotions and preferences, but traditional systems fail to adequately meet this need. Furthermore, if the virtual experience feels unrealistic, consumer satisfaction may decrease. This makes it difficult for consumers to easily make fashion choices that match their emotional state, highlighting the challenge of providing personalized fashion experiences.

[0214] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0215] This invention includes a server that provides means for receiving biometric data and preference information from a user and generating an integrated profile; means for recommending clothing that matches the user's profile and emotional state based on various decorative information stored in a memory device; means for analyzing the user's emotional data and generating and outputting dynamic feedback messages for the selected clothing; and means for providing the user with a virtual try-on experience through an interactive augmented reality environment. This enables the user to have a realistic and personalized fashion experience that is tailored to their own emotions and preferences.

[0216] "Biometric data" refers to information that reflects a user's physical characteristics and emotional state.

[0217] "Preference information" refers to information that indicates the style, colors, and fashion trends that a user prefers.

[0218] An "integrated profile" is a dataset that represents an individual's characteristics, generated based on the user's biometric data and preference information.

[0219] A "storage device" is a computer device used to store and access various data related to fashion and accessories.

[0220] "Decorative information" refers to information about various fashion items and styles.

[0221] "Emotional state" refers to the state of a user's real-time emotional response while they are accessing a website.

[0222] "Clothing" refers to all the clothing and accessories that the user wears.

[0223] A "dynamic feedback message" is a message that is generated and output in real time in response to the user's choices and emotions.

[0224] An "interactive augmented reality environment" is a platform that allows users to enjoy an integrated and bidirectional experience of trying on clothes in both the real world and a virtual environment.

[0225] A "virtual try-on experience" is an experience that allows users to simulate how clothes and accessories feel to wear in a virtual space without physically trying them on.

[0226] This invention provides a system for users to obtain a personalized fashion experience in a virtual store. The system consists of a user terminal, a server that manages a database, and an emotion analysis engine. Each component is described in detail below.

[0227] The terminals used include smartphones, smart glasses, and head-mounted displays, and their role is to receive biometric data and preference information from the user. This information is transmitted from the terminal to a server. Specifically, the biometric data includes facial expression data captured using a camera, which is used to analyze the emotional state.

[0228] The server uses an emotion analysis API, such as Microsoft® Azure® Emotion API, to analyze the user's emotional state from the received biometric data. Based on the emotional state and preference information, the server selects the most suitable clothing from various fashion data stored in its storage device. This enables personalized fashion suggestions tailored to the user's emotions and preferences.

[0229] Furthermore, it generates dynamic feedback messages based on the user's choices. This feedback is customized according to the sentiment analysis results, providing a more personalized and interactive experience. For example, the user might be presented with a message such as, "This color will refresh your mood!"

[0230] Furthermore, it is built to allow users to experience virtual try-ons through an interactive augmented reality environment. This means users can enjoy a realistic try-on experience without physically going to a store, and can check the fit before purchasing.

[0231] An example of a prompt might be, "If the user is determined to be relaxed, suggest a recommended casual style." Such prompts form the basis for the generative AI model to provide optimal fashion suggestions.

[0232] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0233] Step 1:

[0234] The user accesses the device and enters biometric data and preference information. The entered biometric data is facial expression data captured via the camera. The device then sends this data to the server.

[0235] Step 2:

[0236] The server uses the Microsoft Azure Emotion API to analyze the user's emotional state based on the received biometric data. This analysis identifies the user's current emotion (e.g., joy, surprise, relaxation).

[0237] Step 3:

[0238] The server integrates user preference information with analyzed emotional data and selects the most suitable clothing from a fashion database stored in memory. Here, prompts are input to a generative AI model, which generates fashion suggestions tailored to the user's emotions and preferences.

[0239] Step 4:

[0240] The selected clothing items are sent to the terminal and presented to the user. The user can then virtually try them on. The terminal provides a virtual environment that simulates the fit and appearance of the clothing.

[0241] Step 5:

[0242] When a user selects clothing, the server generates a dynamic feedback message based on the results of sentiment analysis. The generated feedback is sent to the user's device and presented to the user as a positive reminder.

[0243] Step 6:

[0244] If a user decides to make a purchase, the result is fed back to the server, and the final suggestion data is updated. This feedback is used to optimize future fashion suggestions.

[0245] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0246] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0247] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0248] [Second Embodiment]

[0249] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0250] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0251] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0252] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0253] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0254] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0255] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0256] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0257] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0258] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0259] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0260] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0261] The system of this invention is implemented using a terminal and a server, with the aim of providing users with a personalized fashion experience. The user inputs their size data and fashion preferences into the terminal. The terminal transmits the input data to the server, which generates a personal profile based on this data. This profile, consisting of size data and fashion preferences, serves as the foundation for providing optimal fashion suggestions to the user.

[0262] The server analyzes the latest fashion data in the database and selects clothing that matches the user's profile. The selected clothing is sent to the terminal as suggestions and presented to the user. The user can then choose their preferred items from the suggested clothing.

[0263] For each selected garment, the server generates a positive feedback message and sends it to the device. The device displays this message, helping the user gain confidence in their choice. For example, a message like, "That shirt suits your style very well," might be provided.

[0264] Furthermore, to provide family-based fashion suggestions, users can input their family's size data and fashion preferences into the device. Based on this information, the server suggests matching outfits for all family members, and the device displays these suggestions to the user. This allows the whole family to enjoy coordinated fashion choices.

[0265] Furthermore, this system also supports virtual fashion experiences. The server generates visual feedback for the user to try on clothes selected in the virtual space, and the terminal provides this feedback to the user. Through virtual try-on, the user can check the fit of the clothes before actually wearing them.

[0266] In implementing the present invention, these elements work together to function as a system that provides a seamless fashion experience.

[0267] The following describes the processing flow.

[0268] Step 1:

[0269] The user logs into the system using a terminal. The terminal provides the user with an interface for entering size data and fashion preferences. The user enters their height, weight, preferred style, etc.

[0270] Step 2:

[0271] The device sends the data entered by the user to the server. The server receives this data and generates a personal profile. This profile records the user's size information and fashion preferences.

[0272] Step 3:

[0273] The server accesses the database and analyzes multiple fashion data points. Based on the user's profile, it generates a list of suitable clothing items. This list includes clothing that matches the size and style.

[0274] Step 4:

[0275] The server sends the generated clothing list to the terminal. The terminal displays this list to the user and provides an interface for the user to make selections.

[0276] Step 5:

[0277] The user selects clothing items they are interested in. The device sends the selection information to the server. The server generates a positive feedback message for the selected clothing items.

[0278] Step 6:

[0279] The server sends the generated feedback message to the terminal. The terminal displays it to the user, allowing the user to gain confidence in their choice by seeing the positive feedback they received.

[0280] Step 7:

[0281] If the user wishes, they can enter family information into the device. The device sends this data to the server. The server generates a family profile and suggests matching outfits for all family members.

[0282] Step 8:

[0283] The server transmits the family coordinates generated to the terminal. The terminal provides this proposal to the user, and all family members can enjoy the coordinated fashion.

[0284] Step 9:

[0285] When the user desires virtual try-on, the server generates feedback data in the virtual space. The terminal provides the user with an interface for virtual try-on, and the user experiences digital try-on.

[0286] (Example 1)

[0287] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0288] Modern consumers have difficulty quickly and efficiently finding fashion that suits their preferences and sizes. There are also concerns about enjoying coordinated fashion for the whole family and making purchase decisions without prior try-on. In particular, the lack of individually customized proposals and try-on experiences in the virtual space is a problem.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0290] In this invention, the server includes means for receiving biometric information and fashion preferences from the user and generating a personal profile; means for selecting and suggesting clothing that matches the user's profile based on multiple style information stored in an information repository; and means for generating positive messages based on the selection using a generative AI model. This makes it possible to provide the user with personalized fashion suggestions, give them confidence in their choices, and allow them to confirm their choices before purchase through a virtual try-on experience.

[0291] "Biometric information" refers to data that indicates a user's physical characteristics, including height, weight, shoulder width, and waist measurement.

[0292] "Fashion preferences" refer to information that indicates a user's personal fashion tastes and style, including favorite colors, styles, and budget.

[0293] A "personal profile" is a data structure generated based on a user's biometric information and fashion preferences, designed to clarify the user's fashion preferences.

[0294] An "information repository" is a collection of information, including various fashion styles and trends, that is stored in the form of databases or similar media.

[0295] "Style information" refers to detailed data about clothing and fashion accessories, including design, materials, and trending fashions.

[0296] A "generative AI model" is an artificial intelligence program that uses data and employs machine learning and deep learning technologies to automatically generate new information and messages.

[0297] A "positive message" is text that provides positive feedback on the clothing and fashion items selected by the user, thereby increasing their satisfaction and confidence in their choice.

[0298] A "virtual space" is a digital environment created by a computer, where users can interact through digital avatars.

[0299] A "try-on experience" is a simulation process that allows users to virtually check the appearance and fit of the clothing they have selected.

[0300] The system of the present invention is configured using a terminal and a server to provide users with a personalized fashion experience.

[0301] The terminal functions as an input device that receives the user's biometric information (e.g., height, weight, shoulder width, waist measurement, etc.) and fashion preferences (e.g., favorite colors, styles, budget, etc.). The terminal formats this data appropriately and sends it to the server.

[0302] The server generates a personal profile using the received biometric information and fashion preferences. This profile generation utilizes a generative AI model running within the server. The generative AI model analyzes the data through prompt messages and selects the most suitable clothing for the user, taking into account the latest fashion styles and trends.

[0303] The server uses network communication to send selected clothing information to the terminal. This communication takes place, for example, via the Internet Protocol. The server also uses an AI model to generate positive feedback messages for the clothing selected by the user. This helps the user feel confident in their selection and supports their purchase decision.

[0304] As a concrete example, a prompt message might read: "Based on the user's biometric information and fashion preferences, suggest clothing items. Also, generate a positive feedback message for the selected clothing items."

[0305] Furthermore, to enable users to have a fashion experience in the virtual space, the server generates visual feedback for virtual try-on. This feedback is displayed on the user's terminal using 3D modeling technology. Thus, users can check the fitting of clothes before actually wearing them.

[0306] By integrating these elements and enabling seamless cooperation between the server and the terminal, a system is realized that provides users with a consistent, personalized, and highly interactive fashion selection experience.

[0307] The flow of specific processing in Example 1 will be described using FIG. 11.

[0308] Step 1:

[0309] The user inputs their biometric information and fashion preferences into the terminal. The input data includes the user's size (height, weight, shoulder width, waist size, etc.) and preferences (favorite colors, styles, budget, etc.).

[0310] As a specific operation, the application on the terminal displays an input form to the user and collects the necessary information.

[0311] Step 2:

[0312] The terminal organizes the collected biometric information and fashion preferences and transmits them to the server as structured data.

[0313] Input: Biometric information and fashion preferences input by the user

[0314] Output: Structured data transmitted to the server

[0315] As a specific operation, the terminal formats the data and transmits it to the server using a secure communication protocol.

[0316] Step 3:

[0317] The server generates a personal profile of the user based on the received data.

[0318] Input: Structured data sent from the device

[0319] Output: Personal Profile

[0320] As part of the data processing, a generative AI model analyzes the data using prompt sentences to derive the optimal fashion style for the user.

[0321] Step 4:

[0322] The server analyzes multiple style records in the database and selects clothing that matches the user's profile.

[0323] Input: User's personal profile and style information in the database

[0324] Output: A list of clothing items recommended for the user.

[0325] Specifically, the server uses a generated AI model to search the database and select the most suitable style.

[0326] Step 5:

[0327] The server transmits information about the selected clothing items to the terminal and presents it to the user.

[0328] Input: List of recommended clothing items

[0329] Output: Clothing options displayed on the device

[0330] In terms of specific operations, the server sends data containing images of clothing and detailed product information to the terminal.

[0331] Step 6:

[0332] The user selects their preferred clothing item from those displayed on the device.

[0333] Input: Clothing options displayed on the device

[0334] Output: User-selected clothing

[0335] In terms of specific actions, the user checks the product details and then makes a selection based on their purchase intent.

[0336] Step 7:

[0337] The server generates a positive feedback message about the selected clothing item and sends it to the terminal.

[0338] Input: Information about the clothing selected by the user

[0339] Output: Feedback message

[0340] Using a generative AI model, messages such as "That blue jacket perfectly matches your style" are generated.

[0341] Step 8:

[0342] The terminal displays feedback messages received from the server to the user.

[0343] Input: Feedback message sent from the server

[0344] Output: Feedback messages viewed by the user

[0345] Specifically, a message pops up on the device to support the user's confidence in their choice.

[0346] (Application Example 1)

[0347] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0348] Traditionally, it has been difficult for consumers to easily and intuitively select fashion that suits their individual needs, and virtual try-on experiences have lacked realism. Therefore, there is a need for technology that allows consumers to confidently choose their own style and to have a realistic try-on experience in a virtual space.

[0349] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0350] This invention includes a server, a method for receiving size information and fashion preferences from a user and generating an individual profile; means for selecting clothing that matches the user's profile based on a large amount of stored fashion information; a method for generating and displaying positive feedback for the clothing selected by the user; and a device for providing a three-dimensional virtual experience for the user to try on clothing using augmented reality technology. This enables consumers to make more appropriate and confident fashion choices and to have a realistic and attractive try-on experience in a virtual space.

[0351] A "user" is someone who uses the system to receive personalized fashion suggestions and virtual try-on experiences.

[0352] "Size information" refers to data about the user's physical dimensions and clothing size.

[0353] "Fashion preferences" refer to information that indicates a user's tastes and preferences regarding style.

[0354] A "personal profile" is a personalized dataset generated based on a user's size information and fashion preferences.

[0355] "Clothing" refers to clothing and fashion items that are suggested to the user.

[0356] "Positive feedback" refers to encouraging user choices and increasing satisfaction through positive messages.

[0357] Augmented reality technology is a technology that overlays digital information onto the real world, integrating virtual information into the user's real-world field of vision.

[0358] A "three-dimensional virtual experience" is a three-dimensional try-on experience that allows users to feel realistically within a virtual space.

[0359] "Device" refers to the hardware and software used by users to visually experience virtual try-on.

[0360] The system that realizes this invention operates by combining various hardware and software to provide users with a personalized fashion experience. The main hardware used is a visual device such as smart glasses equipped with augmented reality technology that provides users with a virtual try-on experience. For example, smart glasses overlay digital information onto the real field of view, enabling a realistic three-dimensional virtual experience.

[0361] The device receives size information and fashion preferences from the user and sends this information to a server. The server is located in the cloud and uses the received data to generate a personal profile. An AI analysis engine is used to generate this profile, supporting the selection of fashion items that match the user's preferences.

[0362] Next, the server analyzes a large amount of stored fashion information and selects the optimal clothing based on the user's profile. This selection process is highly personalized using a generative AI model. The selected clothing information is sent to the device, allowing the user to virtually try on a series of outfits through smart glasses. Once the user selects an item, the device immediately displays positive feedback to boost their confidence in their choice.

[0363] As a concrete example, imagine a scenario where a user wears smart glasses, accesses a virtual store, and selects a casual shirt and jeans. At this point, feedback such as, "This digital shirt complements your everyday style," is displayed. This allows consumers to make more appropriate and confident choices. An example of a prompt might be, "Woman in her 30s, elegant fashion, size L, office casual."

[0364] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0365] Step 1:

[0366] The device starts up and receives size information and fashion preferences as input from the user. This input is done through an input screen on the device. This involves the user entering their measurements and preferred style into a form displayed on the screen.

[0367] Step 2:

[0368] The terminal sends user input to the server. The server receives this data and generates a personal profile based on the input data. Using a generation AI model, the received data is analyzed and a profile reflecting the user's size and fashion preferences is output. In this process, the AI ​​engine performs calculations to create the profile based on the user data.

[0369] Step 3:

[0370] The server searches a stored fashion information database and selects clothing that matches the user's profile. In this step, the server uses an AI algorithm to extract relevant fashion items from the database and generates the selection results as output. This includes leveraging the latest trend information within the database.

[0371] Step 4:

[0372] The selected clothing list is sent to the device, and the user visually confirms it through smart glasses. This involves the user virtually trying on clothes using augmented reality technology via the glasses device, and seeing themselves in the virtual image.

[0373] Step 5:

[0374] When a user selects a specific outfit, the device sends that selection information to the server. The server generates positive feedback for the selected clothing and outputs a message to the device. The device displays this message, indicating to the user that the selection is appropriate. In this step, a generative AI model performs calculations to generate a positive prompt statement about the selected item.

[0375] Step 6:

[0376] The entire system process is finalized. Log data is saved to the server to record that the user made a satisfactory choice and to incorporate feedback into future suggestions. This involves the terminal interacting with the server to record the user's selection data and use it in subsequent suggestion processes.

[0377] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0378] This invention is a system that incorporates an emotion engine to enhance the user's fashion experience, and is implemented using a terminal and a server. The user inputs their size data and fashion preferences through the terminal. The terminal sends this information to the server, which generates a personal profile. This profile serves as the basis for suggesting the most suitable clothing for the user.

[0379] The server is equipped with an emotion engine that analyzes the user's emotional state during input and selection. The emotion engine infers the user's emotions from their choices and responses while they interact with the device. This information is analyzed in real time and reflected in the fashion suggestions. The server references fashion data in a database and selects the most suitable clothing based on the user's profile and emotional state. The selected clothing list is sent to the device and presented to the user.

[0380] After the user selects clothing, the server considers the emotional information obtained by the emotion engine and dynamically generates positive feedback messages. Specifically, it customizes the feedback message based on the emotional state the user was in when they selected the particular clothing item and sends it to the device. For example, it might provide detailed feedback such as, "This color will refresh your mood!"

[0381] Furthermore, when a user enters family information into their device, the server also uses emotional data to generate family-specific profiles. Based on each member's emotional state, it generates and sends appropriate outfits and feedback for the entire family to the device, providing a cohesive fashion experience.

[0382] This system also supports virtual try-on experiences. An emotion engine recognizes the user's emotions during virtual try-on and uses this information to provide suggestions within the virtual space. This allows users to check fittings without physical try-on and find styles that match their emotions. By specifically implementing this invention, users can obtain a fashion experience that takes their emotions into consideration.

[0383] The following describes the processing flow.

[0384] Step 1:

[0385] The user logs into the system using a terminal and enters size data and fashion preferences. The terminal collects this data and prompts for confirmation of the input through the user interface.

[0386] Step 2:

[0387] The device sends the collected size data and fashion preferences to the server. The server receives this data and generates a personal profile of the user. The profile includes the user's body measurements and style preferences.

[0388] Step 3:

[0389] The server's emotion engine analyzes the user's initial emotional state based on their input and actions. The emotion engine infers the user's emotions based on factors such as the language used and the speed at which choices are made.

[0390] Step 4:

[0391] The server searches the database and, based on the generated profile and sentiment data obtained from the sentiment engine, creates a list of clothing suitable for the user. This list includes items that match the size and style.

[0392] Step 5:

[0393] The server sends a suggested clothing list to the terminal. The terminal displays the list and gives the user the opportunity to make a selection. At the same time, it displays an emotion meter to record the user's feelings at the time of selection.

[0394] Step 6:

[0395] The user selects an item of clothing from a suggested list. The device sends the selection data and emotion meter information to the server. The server updates the emotion data related to the user's selection.

[0396] Step 7:

[0397] The server uses an emotion engine to generate positive feedback messages based on the user's choices. The generated feedback takes the user's emotional state into account, making it more personalized.

[0398] Step 8:

[0399] The server sends the generated feedback message to the terminal. The terminal displays the feedback to the user, providing support to increase confidence in their choice.

[0400] Step 9:

[0401] When a user enters family information, the device collects this information and sends it to the server. The server generates a family-based profile and suggests coordination and feedback based on each member's emotional state.

[0402] Step 10:

[0403] If the user wishes, they can start a virtual try-on. The terminal displays the virtual try-on interface, and the server's emotion engine analyzes the user's emotions during the virtual try-on, enabling more precise fitting suggestions.

[0404] (Example 2)

[0405] Next, we will describe Example 2. 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".

[0406] In today's fashion market, while there is a demand for personalized clothing suggestions based on individual user size data and preferences, there are challenges in providing more sophisticated suggestions that take into account the user's emotional state, coordinating outfits for the entire family, and realizing new experiences such as virtual try-on. This challenge makes it difficult for consumers to make the best fashion choices for themselves.

[0407] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0408] In this invention, the server includes means for collecting dimensional information and fashion preferences from the user and generating an individual profile; means for suggesting clothing that suits the user profile based on multiple clothing-related data stored in an information storage device; and means for analyzing the emotional state from the user's actions and selections. This enables personalized clothing suggestions that are in line with the user's emotions.

[0409] "Dimensional information" refers to information about the measured size and dimensions of the user's body.

[0410] A "personalized profile" refers to a personalized dataset based on a user's specific size, preferences, and emotional state.

[0411] "Information storage device" refers to a device for storing and preserving digital information, and includes databases and hard disks.

[0412] "Clothing-related data" refers to information about various clothing items, including attribute information such as design, color, and material.

[0413] "Emotional state" refers to the emotional state a user exhibits in a particular situation, and is a psychological state that influences their behavior and choices.

[0414] A "virtual domain" refers to a visual or conceptual virtual space constructed using computer technology.

[0415] "Personalization" refers to adjusting or customizing something according to the individual characteristics and preferences of the user.

[0416] To implement this system, a server and terminals form the basic communication infrastructure. The server collects user size information and fashion preferences and performs central data processing to create individual user experiences. This system uses an "information storage device" as a database management system, with SQL databases being a specific example.

[0417] The server uses a generative AI model, such as a "natural language processing engine," to analyze the user's emotional state. This AI model has the ability to analyze the user's past choices and input data to infer emotions in real time.

[0418] The terminal is a device that provides an interface with the user, and can specifically be a smartphone or a computer. The terminal sends data from the user to the server and displays personalized clothing suggestions received from the server.

[0419] A concrete example involves a user using their smartphone at home, opening the app, and entering their preferences. If the user prefers a particular color or style, they can enter data related to that preference. This data is encrypted and securely transmitted to the server.

[0420] Specific examples of prompt messages include "Which color suits your mood?" or "Try choosing a style that perfectly matches your mood today." This makes it easier for users to input their emotions more naturally, and the system's suggestions become more appropriate and personalized.

[0421] This system configuration takes into account the user's emotions and size profile, and can also implement features such as family-based and virtual try-on. As a result, it becomes possible to provide a more comprehensive and personalized fashion experience, thereby increasing user satisfaction.

[0422] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0423] Step 1:

[0424] The user inputs their dimensions and fashion preferences using a terminal. The terminal receives this information as input data, packets it, and sends it to the server. Specifically, the user fills in the information in the input form and presses the submit button.

[0425] Step 2:

[0426] The server analyzes the input data received from the terminal and generates individual profiles. This generation process uses a database management system to store the data and create a new profile for each user. Based on the input data, a dataset is created that takes into account the user's preferences and size.

[0427] Step 3:

[0428] The server searches for suitable clothing from a clothing-related database in its information storage device, based on the generated profile. Using database queries, it selects fashion items that match the user's preferences and size. As a result of this process, a list of recommended clothing items is output.

[0429] Step 4:

[0430] The server uses a generative AI model to analyze the user's emotional state. This analysis is based on the user's past selection history and input data, and performs data calculations to estimate the appropriate emotional state. In this process, the attributes most relevant to the user's emotions are extracted.

[0431] Step 5:

[0432] The server takes emotional states into account and dynamically adjusts clothing suggestions. This is done by adding real-time emotional data to the selected clothing list. This process results in more personalized suggestions.

[0433] Step 6:

[0434] The terminal presents the user with the final list of suggestions received from the server. A visual interface is used for this display, allowing the user to review and select the suggested clothing. The user then selects specific items and considers the details.

[0435] Step 7:

[0436] After the user makes a selection, the server generates a positive feedback message. This message is customized based on the emotional state analyzed by the generating AI model. For example, feedback such as "This color suits you well today!" might be output.

[0437] (Application Example 2)

[0438] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0439] Modern consumers demand personalized fashion suggestions tailored to their emotions and preferences, but traditional systems fail to adequately meet this need. Furthermore, if the virtual experience feels unrealistic, consumer satisfaction may decrease. This makes it difficult for consumers to easily make fashion choices that match their emotional state, highlighting the challenge of providing personalized fashion experiences.

[0440] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0441] This invention includes a server that provides means for receiving biometric data and preference information from a user and generating an integrated profile; means for recommending clothing that matches the user's profile and emotional state based on various decorative information stored in a memory device; means for analyzing the user's emotional data and generating and outputting dynamic feedback messages for the selected clothing; and means for providing the user with a virtual try-on experience through an interactive augmented reality environment. This enables the user to have a realistic and personalized fashion experience that is tailored to their own emotions and preferences.

[0442] "Biometric data" refers to information that reflects a user's physical characteristics and emotional state.

[0443] "Preference information" refers to information that indicates the style, colors, and fashion trends that a user prefers.

[0444] An "integrated profile" is a dataset that represents an individual's characteristics, generated based on the user's biometric data and preference information.

[0445] A "storage device" is a computer device used to store and access various data related to fashion and accessories.

[0446] "Decorative information" refers to information about various fashion items and styles.

[0447] "Emotional state" refers to the state of a user's real-time emotional response while they are accessing a website.

[0448] "Clothing" refers to all the clothing and accessories that the user wears.

[0449] A "dynamic feedback message" is a message that is generated and output in real time in response to the user's choices and emotions.

[0450] An "interactive augmented reality environment" is a platform that allows users to enjoy an integrated and bidirectional experience of trying on clothes in both the real world and a virtual environment.

[0451] A "virtual try-on experience" is an experience that allows users to simulate how clothes and accessories feel to wear in a virtual space without physically trying them on.

[0452] This invention provides a system for users to obtain a personalized fashion experience in a virtual store. The system consists of a user terminal, a server that manages a database, and an emotion analysis engine. Each component is described in detail below.

[0453] The terminals used include smartphones, smart glasses, and head-mounted displays, and their role is to receive biometric data and preference information from the user. This information is transmitted from the terminal to a server. Specifically, the biometric data includes facial expression data captured using a camera, which is used to analyze the emotional state.

[0454] The server uses an emotion analysis API, such as the Microsoft Azure Emotion API, to analyze the user's emotional state from the received biometric data. Based on the emotional state and preference information, the server selects the most suitable clothing from various fashion data stored in its memory. This enables personalized fashion suggestions tailored to the user's emotions and preferences.

[0455] Furthermore, it generates dynamic feedback messages based on the user's choices. This feedback is customized according to the sentiment analysis results, providing a more personalized and interactive experience. For example, the user might be presented with a message such as, "This color will refresh your mood!"

[0456] Furthermore, it is built to allow users to experience virtual try-ons through an interactive augmented reality environment. This means users can enjoy a realistic try-on experience without physically going to a store, and can check the fit before purchasing.

[0457] An example of a prompt might be, "If the user is determined to be relaxed, suggest a recommended casual style." Such prompts form the basis for the generative AI model to provide optimal fashion suggestions.

[0458] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0459] Step 1:

[0460] The user accesses the device and enters biometric data and preference information. The entered biometric data is facial expression data captured via the camera. The device then sends this data to the server.

[0461] Step 2:

[0462] The server uses the Microsoft Azure Emotion API to analyze the user's emotional state based on the received biometric data. This analysis identifies the user's current emotion (e.g., joy, surprise, relaxation).

[0463] Step 3:

[0464] The server integrates user preference information with analyzed emotional data and selects the most suitable clothing from a fashion database stored in memory. Here, prompts are input to a generative AI model, which generates fashion suggestions tailored to the user's emotions and preferences.

[0465] Step 4:

[0466] The selected clothing items are sent to the terminal and presented to the user. The user can then virtually try them on. The terminal provides a virtual environment that simulates the fit and appearance of the clothing.

[0467] Step 5:

[0468] When a user selects clothing, the server generates a dynamic feedback message based on the results of sentiment analysis. The generated feedback is sent to the user's device and presented to the user as a positive reminder.

[0469] Step 6:

[0470] If a user decides to make a purchase, the result is fed back to the server, and the final suggestion data is updated. This feedback is used to optimize future fashion suggestions.

[0471] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0472] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0473] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0474] [Third Embodiment]

[0475] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0476] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0477] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0478] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0479] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0480] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0481] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0482] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0483] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0484] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0485] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0486] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0487] The system of this invention is implemented using a terminal and a server, with the aim of providing users with a personalized fashion experience. The user inputs their size data and fashion preferences into the terminal. The terminal transmits the input data to the server, which generates a personal profile based on this data. This profile, consisting of size data and fashion preferences, serves as the foundation for providing optimal fashion suggestions to the user.

[0488] The server analyzes the latest fashion data in the database and selects clothing that matches the user's profile. The selected clothing is sent to the terminal as suggestions and presented to the user. The user can then choose their preferred items from the suggested clothing.

[0489] For each selected garment, the server generates a positive feedback message and sends it to the device. The device displays this message, helping the user gain confidence in their choice. For example, a message like, "That shirt suits your style very well," might be provided.

[0490] Furthermore, to provide family-based fashion suggestions, users can input their family's size data and fashion preferences into the device. Based on this information, the server suggests matching outfits for all family members, and the device displays these suggestions to the user. This allows the whole family to enjoy coordinated fashion choices.

[0491] Furthermore, this system also supports virtual fashion experiences. The server generates visual feedback for the user to try on clothes selected in the virtual space, and the terminal provides this feedback to the user. Through virtual try-on, the user can check the fit of the clothes before actually wearing them.

[0492] In implementing the present invention, these elements work together to function as a system that provides a seamless fashion experience.

[0493] The following describes the processing flow.

[0494] Step 1:

[0495] The user logs into the system using a terminal. The terminal provides the user with an interface for entering size data and fashion preferences. The user enters their height, weight, preferred style, etc.

[0496] Step 2:

[0497] The device sends the data entered by the user to the server. The server receives this data and generates a personal profile. This profile records the user's size information and fashion preferences.

[0498] Step 3:

[0499] The server accesses the database and analyzes multiple fashion data points. Based on the user's profile, it generates a list of suitable clothing items. This list includes clothing that matches the size and style.

[0500] Step 4:

[0501] The server sends the generated clothing list to the terminal. The terminal displays this list to the user and provides an interface for the user to make selections.

[0502] Step 5:

[0503] The user selects clothing items they are interested in. The device sends the selection information to the server. The server generates a positive feedback message for the selected clothing items.

[0504] Step 6:

[0505] The server sends the generated feedback message to the terminal. The terminal displays it to the user, allowing the user to gain confidence in their choice by seeing the positive feedback they received.

[0506] Step 7:

[0507] If the user wishes, they can enter family information into the device. The device sends this data to the server. The server generates a family profile and suggests matching outfits for all family members.

[0508] Step 8:

[0509] The server generates a family outfit coordination suggestion and sends it to the device. The device then presents this suggestion to the user, allowing the whole family to enjoy matching fashion.

[0510] Step 9:

[0511] If a user requests a virtual try-on, the server generates feedback data in a virtual space. The terminal provides the user with a virtual try-on interface, allowing the user to have a digital try-on experience.

[0512] (Example 1)

[0513] Next, we will describe Example 1. 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."

[0514] Modern consumers struggle to quickly and efficiently find fashion that suits their preferences and size. They also face challenges in coordinating outfits for the whole family and are hesitant to make purchase decisions without trying on clothes beforehand. The lack of personalized suggestions and virtual try-on experiences is a particular problem.

[0515] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0516] In this invention, the server includes means for receiving biometric information and fashion preferences from the user and generating a personal profile; means for selecting and suggesting clothing that matches the user's profile based on multiple style information stored in an information repository; and means for generating positive messages based on the selection using a generative AI model. This makes it possible to provide the user with personalized fashion suggestions, give them confidence in their choices, and allow them to confirm their choices before purchase through a virtual try-on experience.

[0517] "Biometric information" refers to data that indicates a user's physical characteristics, including height, weight, shoulder width, and waist measurement.

[0518] "Fashion preferences" refer to information that indicates a user's personal fashion tastes and style, including favorite colors, styles, and budget.

[0519] A "personal profile" is a data structure generated based on a user's biometric information and fashion preferences, designed to clarify the user's fashion preferences.

[0520] An "information repository" is a collection of information, including various fashion styles and trends, that is stored in the form of databases or similar media.

[0521] "Style information" refers to detailed data about clothing and fashion accessories, including design, materials, and trending fashions.

[0522] A "generative AI model" is an artificial intelligence program that uses data and employs machine learning and deep learning technologies to automatically generate new information and messages.

[0523] A "positive message" is text that provides positive feedback on the clothing and fashion items selected by the user, thereby increasing their satisfaction and confidence in their choice.

[0524] A "virtual space" is a digital environment created by a computer, where users can interact through digital avatars.

[0525] A "try-on experience" is a simulation process that allows users to virtually check the appearance and fit of the clothing they have selected.

[0526] The system of the present invention is configured using a terminal and a server to provide users with a personalized fashion experience.

[0527] The terminal functions as an input device that receives the user's biometric information (e.g., height, weight, shoulder width, waist measurement, etc.) and fashion preferences (e.g., favorite colors, styles, budget, etc.). The terminal formats this data appropriately and sends it to the server.

[0528] The server generates a personal profile using the received biometric information and fashion preferences. This profile generation utilizes a generative AI model running within the server. The generative AI model analyzes the data through prompt messages and selects the most suitable clothing for the user, taking into account the latest fashion styles and trends.

[0529] The server uses network communication to send selected clothing information to the terminal. This communication takes place, for example, via the Internet Protocol. The server also uses an AI model to generate positive feedback messages for the clothing selected by the user. This helps the user feel confident in their selection and supports their purchase decision.

[0530] As a concrete example, a prompt message might read: "Based on the user's biometric information and fashion preferences, suggest clothing items. Also, generate a positive feedback message for the selected clothing items."

[0531] Furthermore, to enable users to have a fashion experience in a virtual space, the server generates visual feedback for virtual try-ons. This feedback is displayed on the user's device using 3D modeling technology. This allows users to check the fit of the clothes before actually wearing them.

[0532] When these elements are integrated and the server and terminal work together seamlessly, a system is created that provides users with a consistent, personalized, and highly interactive fashion selection experience.

[0533] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0534] Step 1:

[0535] Users input their biometric information and fashion preferences into the device. The input data includes the user's size (height, weight, shoulder width, waist measurement, etc.) and preferences (favorite colors, styles, budget, etc.).

[0536] In terms of specific actions, the application on the device displays an input form to the user and collects the necessary information.

[0537] Step 2:

[0538] The device organizes the collected biometric information and fashion preferences and sends them to the server as structured data.

[0539] Input: Biometric information and fashion preferences entered by the user.

[0540] Output: Structured data sent to the server

[0541] Specifically, the terminal formats the data and sends it to the server using a secure communication protocol.

[0542] Step 3:

[0543] The server generates a personal profile of the user based on the received data.

[0544] Input: Structured data sent from the device

[0545] Output: Personal Profile

[0546] As part of the data processing, a generative AI model analyzes the data using prompt sentences to derive the optimal fashion style for the user.

[0547] Step 4:

[0548] The server analyzes multiple style records in the database and selects clothing that matches the user's profile.

[0549] Input: User's personal profile and style information in the database

[0550] Output: A list of clothing items recommended for the user.

[0551] Specifically, the server uses a generated AI model to search the database and select the most suitable style.

[0552] Step 5:

[0553] The server transmits information about the selected clothing items to the terminal and presents it to the user.

[0554] Input: List of recommended clothing items

[0555] Output: Clothing options displayed on the device

[0556] In terms of specific operations, the server sends data containing images of clothing and detailed product information to the terminal.

[0557] Step 6:

[0558] The user selects their preferred clothing item from those displayed on the device.

[0559] Input: Clothing options displayed on the device

[0560] Output: User-selected clothing

[0561] In terms of specific actions, the user checks the product details and then makes a selection based on their purchase intent.

[0562] Step 7:

[0563] The server generates a positive feedback message about the selected clothing item and sends it to the terminal.

[0564] Input: Information about the clothing selected by the user

[0565] Output: Feedback message

[0566] Using a generative AI model, messages such as "That blue jacket perfectly matches your style" are generated.

[0567] Step 8:

[0568] The terminal displays feedback messages received from the server to the user.

[0569] Input: Feedback message sent from the server

[0570] Output: Feedback messages viewed by the user

[0571] Specifically, a message pops up on the device to support the user's confidence in their choice.

[0572] (Application Example 1)

[0573] Next, we will explain Application Example 1. In the following explanation, 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."

[0574] Traditionally, it has been difficult for consumers to easily and intuitively select fashion that suits their individual needs, and virtual try-on experiences have lacked realism. Therefore, there is a need for technology that allows consumers to confidently choose their own style and to have a realistic try-on experience in a virtual space.

[0575] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0576] This invention includes a server, a method for receiving size information and fashion preferences from a user and generating an individual profile; means for selecting clothing that matches the user's profile based on a large amount of stored fashion information; a method for generating and displaying positive feedback for the clothing selected by the user; and a device for providing a three-dimensional virtual experience for the user to try on clothing using augmented reality technology. This enables consumers to make more appropriate and confident fashion choices and to have a realistic and attractive try-on experience in a virtual space.

[0577] A "user" is someone who uses the system to receive personalized fashion suggestions and virtual try-on experiences.

[0578] "Size information" refers to data about the user's physical dimensions and clothing size.

[0579] "Fashion preferences" refer to information that indicates a user's tastes and preferences regarding style.

[0580] A "personal profile" is a personalized dataset generated based on a user's size information and fashion preferences.

[0581] "Clothing" refers to clothing and fashion items that are suggested to the user.

[0582] "Positive feedback" refers to encouraging user choices and increasing satisfaction through positive messages.

[0583] Augmented reality technology is a technology that overlays digital information onto the real world, integrating virtual information into the user's real-world field of vision.

[0584] A "three-dimensional virtual experience" is a three-dimensional try-on experience that allows users to feel realistically within a virtual space.

[0585] "Device" refers to the hardware and software used by users to visually experience virtual try-on.

[0586] The system that realizes this invention operates by combining various hardware and software to provide users with a personalized fashion experience. The main hardware used is a visual device such as smart glasses equipped with augmented reality technology that provides users with a virtual try-on experience. For example, smart glasses overlay digital information onto the real field of view, enabling a realistic three-dimensional virtual experience.

[0587] The device receives size information and fashion preferences from the user and sends this information to a server. The server is located in the cloud and uses the received data to generate a personal profile. An AI analysis engine is used to generate this profile, supporting the selection of fashion items that match the user's preferences.

[0588] Next, the server analyzes a large amount of stored fashion information and selects the optimal clothing based on the user's profile. This selection process is highly personalized using a generative AI model. The selected clothing information is sent to the device, allowing the user to virtually try on a series of outfits through smart glasses. Once the user selects an item, the device immediately displays positive feedback to boost their confidence in their choice.

[0589] As a concrete example, imagine a scenario where a user wears smart glasses, accesses a virtual store, and selects a casual shirt and jeans. At this point, feedback such as, "This digital shirt complements your everyday style," is displayed. This allows consumers to make more appropriate and confident choices. An example of a prompt might be, "Woman in her 30s, elegant fashion, size L, office casual."

[0590] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0591] Step 1:

[0592] The device starts up and receives size information and fashion preferences as input from the user. This input is done through an input screen on the device. This involves the user entering their measurements and preferred style into a form displayed on the screen.

[0593] Step 2:

[0594] The terminal sends user input to the server. The server receives this data and generates a personal profile based on the input data. Using a generation AI model, the received data is analyzed and a profile reflecting the user's size and fashion preferences is output. In this process, the AI ​​engine performs calculations to create the profile based on the user data.

[0595] Step 3:

[0596] The server searches a stored fashion information database and selects clothing that matches the user's profile. In this step, the server uses an AI algorithm to extract relevant fashion items from the database and generates the selection results as output. This includes leveraging the latest trend information within the database.

[0597] Step 4:

[0598] The selected clothing list is sent to the device, and the user visually confirms it through smart glasses. This involves the user virtually trying on clothes using augmented reality technology via the glasses device, and seeing themselves in the virtual image.

[0599] Step 5:

[0600] When a user selects a specific outfit, the device sends that selection information to the server. The server generates positive feedback for the selected clothing and outputs a message to the device. The device displays this message, indicating to the user that the selection is appropriate. In this step, a generative AI model performs calculations to generate a positive prompt statement about the selected item.

[0601] Step 6:

[0602] The entire system process is finalized. Log data is saved to the server to record that the user made a satisfactory choice and to incorporate feedback into future suggestions. This involves the terminal interacting with the server to record the user's selection data and use it in subsequent suggestion processes.

[0603] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0604] This invention is a system that incorporates an emotion engine to enhance the user's fashion experience, and is implemented using a terminal and a server. The user inputs their size data and fashion preferences through the terminal. The terminal sends this information to the server, which generates a personal profile. This profile serves as the basis for suggesting the most suitable clothing for the user.

[0605] The server is equipped with an emotion engine that analyzes the user's emotional state during input and selection. The emotion engine infers the user's emotions from their choices and responses while they interact with the device. This information is analyzed in real time and reflected in the fashion suggestions. The server references fashion data in a database and selects the most suitable clothing based on the user's profile and emotional state. The selected clothing list is sent to the device and presented to the user.

[0606] After the user selects clothing, the server considers the emotional information obtained by the emotion engine and dynamically generates positive feedback messages. Specifically, it customizes the feedback message based on the emotional state the user was in when they selected the particular clothing item and sends it to the device. For example, it might provide detailed feedback such as, "This color will refresh your mood!"

[0607] Furthermore, when a user enters family information into their device, the server also uses emotional data to generate family-specific profiles. Based on each member's emotional state, it generates and sends appropriate outfits and feedback for the entire family to the device, providing a cohesive fashion experience.

[0608] This system also supports virtual try-on experiences. An emotion engine recognizes the user's emotions during virtual try-on and uses this information to provide suggestions within the virtual space. This allows users to check fittings without physical try-on and find styles that match their emotions. By specifically implementing this invention, users can obtain a fashion experience that takes their emotions into consideration.

[0609] The following describes the processing flow.

[0610] Step 1:

[0611] The user logs into the system using a terminal and enters size data and fashion preferences. The terminal collects this data and prompts for confirmation of the input through the user interface.

[0612] Step 2:

[0613] The device sends the collected size data and fashion preferences to the server. The server receives this data and generates a personal profile of the user. The profile includes the user's body measurements and style preferences.

[0614] Step 3:

[0615] The server's emotion engine analyzes the user's initial emotional state based on their input and actions. The emotion engine infers the user's emotions based on factors such as the language used and the speed at which choices are made.

[0616] Step 4:

[0617] The server searches the database and, based on the generated profile and sentiment data obtained from the sentiment engine, creates a list of clothing suitable for the user. This list includes items that match the size and style.

[0618] Step 5:

[0619] The server sends a suggested clothing list to the terminal. The terminal displays the list and gives the user the opportunity to make a selection. At the same time, it displays an emotion meter to record the user's feelings at the time of selection.

[0620] Step 6:

[0621] The user selects an item of clothing from a suggested list. The device sends the selection data and emotion meter information to the server. The server updates the emotion data related to the user's selection.

[0622] Step 7:

[0623] The server uses an emotion engine to generate positive feedback messages based on the user's choices. The generated feedback takes the user's emotional state into account, making it more personalized.

[0624] Step 8:

[0625] The server sends the generated feedback message to the terminal. The terminal displays the feedback to the user, providing support to increase confidence in their choice.

[0626] Step 9:

[0627] When a user enters family information, the device collects this information and sends it to the server. The server generates a family-based profile and suggests coordination and feedback based on each member's emotional state.

[0628] Step 10:

[0629] If the user wishes, they can start a virtual try-on. The terminal displays the virtual try-on interface, and the server's emotion engine analyzes the user's emotions during the virtual try-on, enabling more precise fitting suggestions.

[0630] (Example 2)

[0631] Next, we will describe Example 2. 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."

[0632] In today's fashion market, while there is a demand for personalized clothing suggestions based on individual user size data and preferences, there are challenges in providing more sophisticated suggestions that take into account the user's emotional state, coordinating outfits for the entire family, and realizing new experiences such as virtual try-on. This challenge makes it difficult for consumers to make the best fashion choices for themselves.

[0633] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0634] In this invention, the server includes means for collecting dimensional information and fashion preferences from the user and generating an individual profile; means for suggesting clothing that suits the user profile based on multiple clothing-related data stored in an information storage device; and means for analyzing the emotional state from the user's actions and selections. This enables personalized clothing suggestions that are in line with the user's emotions.

[0635] "Dimensional information" refers to information about the measured size and dimensions of the user's body.

[0636] A "personalized profile" refers to a personalized dataset based on a user's specific size, preferences, and emotional state.

[0637] "Information storage device" refers to a device for storing and preserving digital information, and includes databases and hard disks.

[0638] "Clothing-related data" refers to information about various clothing items, including attribute information such as design, color, and material.

[0639] "Emotional state" refers to the emotional state a user exhibits in a particular situation, and is a psychological state that influences their behavior and choices.

[0640] A "virtual domain" refers to a visual or conceptual virtual space constructed using computer technology.

[0641] "Personalization" refers to adjusting or customizing something according to the individual characteristics and preferences of the user.

[0642] To implement this system, a server and terminals form the basic communication infrastructure. The server collects user size information and fashion preferences and performs central data processing to create individual user experiences. This system uses an "information storage device" as a database management system, with SQL databases being a specific example.

[0643] The server uses a generative AI model, such as a "natural language processing engine," to analyze the user's emotional state. This AI model has the ability to analyze the user's past choices and input data to infer emotions in real time.

[0644] The terminal is a device that provides an interface with the user, and can specifically be a smartphone or a computer. The terminal sends data from the user to the server and displays personalized clothing suggestions received from the server.

[0645] A concrete example involves a user using their smartphone at home, opening the app, and entering their preferences. If the user prefers a particular color or style, they can enter data related to that preference. This data is encrypted and securely transmitted to the server.

[0646] Specific examples of prompt messages include "Which color suits your mood?" or "Try choosing a style that perfectly matches your mood today." This makes it easier for users to input their emotions more naturally, and the system's suggestions become more appropriate and personalized.

[0647] This system configuration takes into account the user's emotions and size profile, and can also implement features such as family-based and virtual try-on. As a result, it becomes possible to provide a more comprehensive and personalized fashion experience, thereby increasing user satisfaction.

[0648] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0649] Step 1:

[0650] The user inputs their dimensions and fashion preferences using a terminal. The terminal receives this information as input data, packets it, and sends it to the server. Specifically, the user fills in the information in the input form and presses the submit button.

[0651] Step 2:

[0652] The server analyzes the input data received from the terminal and generates individual profiles. This generation process uses a database management system to store the data and create a new profile for each user. Based on the input data, a dataset is created that takes into account the user's preferences and size.

[0653] Step 3:

[0654] The server searches for suitable clothing from a clothing-related database in its information storage device, based on the generated profile. Using database queries, it selects fashion items that match the user's preferences and size. As a result of this process, a list of recommended clothing items is output.

[0655] Step 4:

[0656] The server uses a generative AI model to analyze the user's emotional state. This analysis is based on the user's past selection history and input data, and performs data calculations to estimate the appropriate emotional state. In this process, the attributes most relevant to the user's emotions are extracted.

[0657] Step 5:

[0658] The server takes emotional states into account and dynamically adjusts clothing suggestions. This is done by adding real-time emotional data to the selected clothing list. This process results in more personalized suggestions.

[0659] Step 6:

[0660] The terminal presents the user with the final list of suggestions received from the server. A visual interface is used for this display, allowing the user to review and select the suggested clothing. The user then selects specific items and considers the details.

[0661] Step 7:

[0662] After the user makes a selection, the server generates a positive feedback message. This message is customized based on the emotional state analyzed by the generating AI model. For example, feedback such as "This color suits you well today!" might be output.

[0663] (Application Example 2)

[0664] Next, we will explain application example 2. In the following explanation, 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."

[0665] Modern consumers demand personalized fashion suggestions tailored to their emotions and preferences, but traditional systems fail to adequately meet this need. Furthermore, if the virtual experience feels unrealistic, consumer satisfaction may decrease. This makes it difficult for consumers to easily make fashion choices that match their emotional state, highlighting the challenge of providing personalized fashion experiences.

[0666] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0667] This invention includes a server that provides means for receiving biometric data and preference information from a user and generating an integrated profile; means for recommending clothing that matches the user's profile and emotional state based on various decorative information stored in a memory device; means for analyzing the user's emotional data and generating and outputting dynamic feedback messages for the selected clothing; and means for providing the user with a virtual try-on experience through an interactive augmented reality environment. This enables the user to have a realistic and personalized fashion experience that is tailored to their own emotions and preferences.

[0668] "Biometric data" refers to information that reflects a user's physical characteristics and emotional state.

[0669] "Preference information" refers to information that indicates the style, colors, and fashion trends that a user prefers.

[0670] An "integrated profile" is a dataset that represents an individual's characteristics, generated based on the user's biometric data and preference information.

[0671] A "storage device" is a computer device used to store and access various data related to fashion and accessories.

[0672] "Decorative information" refers to information about various fashion items and styles.

[0673] "Emotional state" refers to the state of a user's real-time emotional response while they are accessing a website.

[0674] "Clothing" refers to all the clothing and accessories that the user wears.

[0675] A "dynamic feedback message" is a message that is generated and output in real time in response to the user's choices and emotions.

[0676] An "interactive augmented reality environment" is a platform that allows users to enjoy an integrated and bidirectional experience of trying on clothes in both the real world and a virtual environment.

[0677] A "virtual try-on experience" is an experience that allows users to simulate how clothes and accessories feel to wear in a virtual space without physically trying them on.

[0678] This invention provides a system for users to obtain a personalized fashion experience in a virtual store. The system consists of a user terminal, a server that manages a database, and an emotion analysis engine. Each component is described in detail below.

[0679] The terminals used include smartphones, smart glasses, and head-mounted displays, and their role is to receive biometric data and preference information from the user. This information is transmitted from the terminal to a server. Specifically, the biometric data includes facial expression data captured using a camera, which is used to analyze the emotional state.

[0680] The server uses an emotion analysis API, such as the Microsoft Azure Emotion API, to analyze the user's emotional state from the received biometric data. Based on the emotional state and preference information, the server selects the most suitable clothing from various fashion data stored in its memory. This enables personalized fashion suggestions tailored to the user's emotions and preferences.

[0681] Furthermore, it generates dynamic feedback messages based on the user's choices. This feedback is customized according to the sentiment analysis results, providing a more personalized and interactive experience. For example, the user might be presented with a message such as, "This color will refresh your mood!"

[0682] Furthermore, it is built to allow users to experience virtual try-ons through an interactive augmented reality environment. This means users can enjoy a realistic try-on experience without physically going to a store, and can check the fit before purchasing.

[0683] An example of a prompt might be, "If the user is determined to be relaxed, suggest a recommended casual style." Such prompts form the basis for the generative AI model to provide optimal fashion suggestions.

[0684] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0685] Step 1:

[0686] The user accesses the device and enters biometric data and preference information. The entered biometric data is facial expression data captured via the camera. The device then sends this data to the server.

[0687] Step 2:

[0688] The server uses the Microsoft Azure Emotion API to analyze the user's emotional state based on the received biometric data. This analysis identifies the user's current emotion (e.g., joy, surprise, relaxation).

[0689] Step 3:

[0690] The server integrates user preference information with analyzed emotional data and selects the most suitable clothing from a fashion database stored in memory. Here, prompts are input to a generative AI model, which generates fashion suggestions tailored to the user's emotions and preferences.

[0691] Step 4:

[0692] The selected clothing items are sent to the terminal and presented to the user. The user can then virtually try them on. The terminal provides a virtual environment that simulates the fit and appearance of the clothing.

[0693] Step 5:

[0694] When a user selects clothing, the server generates a dynamic feedback message based on the results of sentiment analysis. The generated feedback is sent to the user's device and presented to the user as a positive reminder.

[0695] Step 6:

[0696] If a user decides to make a purchase, the result is fed back to the server, and the final suggestion data is updated. This feedback is used to optimize future fashion suggestions.

[0697] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0698] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0699] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0700] [Fourth Embodiment]

[0701] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0702] As shown in Figure 7, the 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.

[0703] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0704] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0705] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0706] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0707] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0708] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0709] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0710] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0711] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0712] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0713] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0714] The system of this invention is implemented using a terminal and a server, with the aim of providing users with a personalized fashion experience. The user inputs their size data and fashion preferences into the terminal. The terminal transmits the input data to the server, which generates a personal profile based on this data. This profile, consisting of size data and fashion preferences, serves as the foundation for providing optimal fashion suggestions to the user.

[0715] The server analyzes the latest fashion data in the database and selects clothing that matches the user's profile. The selected clothing is sent to the terminal as suggestions and presented to the user. The user can then choose their preferred items from the suggested clothing.

[0716] For each selected garment, the server generates a positive feedback message and sends it to the device. The device displays this message, helping the user gain confidence in their choice. For example, a message like, "That shirt suits your style very well," might be provided.

[0717] Furthermore, to provide family-based fashion suggestions, users can input their family's size data and fashion preferences into the device. Based on this information, the server suggests matching outfits for all family members, and the device displays these suggestions to the user. This allows the whole family to enjoy coordinated fashion choices.

[0718] Furthermore, this system also supports virtual fashion experiences. The server generates visual feedback for the user to try on clothes selected in the virtual space, and the terminal provides this feedback to the user. Through virtual try-on, the user can check the fit of the clothes before actually wearing them.

[0719] In implementing the present invention, these elements work together to function as a system that provides a seamless fashion experience.

[0720] The following describes the processing flow.

[0721] Step 1:

[0722] The user logs into the system using a terminal. The terminal provides the user with an interface for entering size data and fashion preferences. The user enters their height, weight, preferred style, etc.

[0723] Step 2:

[0724] The device sends the data entered by the user to the server. The server receives this data and generates a personal profile. This profile records the user's size information and fashion preferences.

[0725] Step 3:

[0726] The server accesses the database and analyzes multiple fashion data points. Based on the user's profile, it generates a list of suitable clothing items. This list includes clothing that matches the size and style.

[0727] Step 4:

[0728] The server sends the generated clothing list to the terminal. The terminal displays this list to the user and provides an interface for the user to make selections.

[0729] Step 5:

[0730] The user selects clothing items they are interested in. The device sends the selection information to the server. The server generates a positive feedback message for the selected clothing items.

[0731] Step 6:

[0732] The server sends the generated feedback message to the terminal. The terminal displays it to the user, allowing the user to gain confidence in their choice by seeing the positive feedback they received.

[0733] Step 7:

[0734] If the user wishes, they can enter family information into the device. The device sends this data to the server. The server generates a family profile and suggests matching outfits for all family members.

[0735] Step 8:

[0736] The server generates a family outfit coordination suggestion and sends it to the device. The device then presents this suggestion to the user, allowing the whole family to enjoy matching fashion.

[0737] Step 9:

[0738] If a user requests a virtual try-on, the server generates feedback data in a virtual space. The terminal provides the user with a virtual try-on interface, allowing the user to have a digital try-on experience.

[0739] (Example 1)

[0740] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0741] Modern consumers struggle to quickly and efficiently find fashion that suits their preferences and size. They also face challenges in coordinating outfits for the whole family and are hesitant to make purchase decisions without trying on clothes beforehand. The lack of personalized suggestions and virtual try-on experiences is a particular problem.

[0742] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0743] In this invention, the server includes means for receiving biometric information and fashion preferences from the user and generating a personal profile; means for selecting and suggesting clothing that matches the user's profile based on multiple style information stored in an information repository; and means for generating positive messages based on the selection using a generative AI model. This makes it possible to provide the user with personalized fashion suggestions, give them confidence in their choices, and allow them to confirm their choices before purchase through a virtual try-on experience.

[0744] "Biometric information" refers to data that indicates a user's physical characteristics, including height, weight, shoulder width, and waist measurement.

[0745] "Fashion preferences" refer to information that indicates a user's personal fashion tastes and style, including favorite colors, styles, and budget.

[0746] A "personal profile" is a data structure generated based on a user's biometric information and fashion preferences, designed to clarify the user's fashion preferences.

[0747] An "information repository" is a collection of information, including various fashion styles and trends, that is stored in the form of databases or similar media.

[0748] "Style information" refers to detailed data about clothing and fashion accessories, including design, materials, and trending fashions.

[0749] A "generative AI model" is an artificial intelligence program that uses data and employs machine learning and deep learning technologies to automatically generate new information and messages.

[0750] A "positive message" is text that provides positive feedback on the clothing and fashion items selected by the user, thereby increasing their satisfaction and confidence in their choice.

[0751] A "virtual space" is a digital environment created by a computer, where users can interact through digital avatars.

[0752] A "try-on experience" is a simulation process that allows users to virtually check the appearance and fit of the clothing they have selected.

[0753] The system of the present invention is configured using a terminal and a server to provide users with a personalized fashion experience.

[0754] The terminal functions as an input device that receives the user's biometric information (e.g., height, weight, shoulder width, waist measurement, etc.) and fashion preferences (e.g., favorite colors, styles, budget, etc.). The terminal formats this data appropriately and sends it to the server.

[0755] The server generates a personal profile using the received biometric information and fashion preferences. This profile generation utilizes a generative AI model running within the server. The generative AI model analyzes the data through prompt messages and selects the most suitable clothing for the user, taking into account the latest fashion styles and trends.

[0756] The server uses network communication to send selected clothing information to the terminal. This communication takes place, for example, via the Internet Protocol. The server also uses an AI model to generate positive feedback messages for the clothing selected by the user. This helps the user feel confident in their selection and supports their purchase decision.

[0757] As a concrete example, a prompt message might read: "Based on the user's biometric information and fashion preferences, suggest clothing items. Also, generate a positive feedback message for the selected clothing items."

[0758] Furthermore, to enable users to have a fashion experience in a virtual space, the server generates visual feedback for virtual try-ons. This feedback is displayed on the user's device using 3D modeling technology. This allows users to check the fit of the clothes before actually wearing them.

[0759] When these elements are integrated and the server and terminal work together seamlessly, a system is created that provides users with a consistent, personalized, and highly interactive fashion selection experience.

[0760] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0761] Step 1:

[0762] Users input their biometric information and fashion preferences into the device. The input data includes the user's size (height, weight, shoulder width, waist measurement, etc.) and preferences (favorite colors, styles, budget, etc.).

[0763] In terms of specific actions, the application on the device displays an input form to the user and collects the necessary information.

[0764] Step 2:

[0765] The device organizes the collected biometric information and fashion preferences and sends them to the server as structured data.

[0766] Input: Biometric information and fashion preferences entered by the user.

[0767] Output: Structured data sent to the server

[0768] Specifically, the terminal formats the data and sends it to the server using a secure communication protocol.

[0769] Step 3:

[0770] The server generates a personal profile of the user based on the received data.

[0771] Input: Structured data sent from the device

[0772] Output: Personal Profile

[0773] As part of the data processing, a generative AI model analyzes the data using prompt sentences to derive the optimal fashion style for the user.

[0774] Step 4:

[0775] The server analyzes multiple style records in the database and selects clothing that matches the user's profile.

[0776] Input: User's personal profile and style information in the database

[0777] Output: A list of clothing items recommended for the user.

[0778] Specifically, the server uses a generated AI model to search the database and select the most suitable style.

[0779] Step 5:

[0780] The server transmits information about the selected clothing items to the terminal and presents it to the user.

[0781] Input: List of recommended clothing items

[0782] Output: Clothing options displayed on the device

[0783] In terms of specific operations, the server sends data containing images of clothing and detailed product information to the terminal.

[0784] Step 6:

[0785] The user selects their preferred clothing item from those displayed on the device.

[0786] Input: Clothing options displayed on the device

[0787] Output: User-selected clothing

[0788] In terms of specific actions, the user checks the product details and then makes a selection based on their purchase intent.

[0789] Step 7:

[0790] The server generates a positive feedback message about the selected clothing item and sends it to the terminal.

[0791] Input: Information about the clothing selected by the user

[0792] Output: Feedback message

[0793] Using a generative AI model, messages such as "That blue jacket perfectly matches your style" are generated.

[0794] Step 8:

[0795] The terminal displays feedback messages received from the server to the user.

[0796] Input: Feedback message sent from the server

[0797] Output: Feedback messages viewed by the user

[0798] Specifically, a message pops up on the device to support the user's confidence in their choice.

[0799] (Application Example 1)

[0800] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0801] Traditionally, it has been difficult for consumers to easily and intuitively select fashion that suits their individual needs, and virtual try-on experiences have lacked realism. Therefore, there is a need for technology that allows consumers to confidently choose their own style and to have a realistic try-on experience in a virtual space.

[0802] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0803] This invention includes a server, a method for receiving size information and fashion preferences from a user and generating an individual profile; means for selecting clothing that matches the user's profile based on a large amount of stored fashion information; a method for generating and displaying positive feedback for the clothing selected by the user; and a device for providing a three-dimensional virtual experience for the user to try on clothing using augmented reality technology. This enables consumers to make more appropriate and confident fashion choices and to have a realistic and attractive try-on experience in a virtual space.

[0804] A "user" is someone who uses the system to receive personalized fashion suggestions and virtual try-on experiences.

[0805] "Size information" refers to data about the user's physical dimensions and clothing size.

[0806] "Fashion preferences" refer to information that indicates a user's tastes and preferences regarding style.

[0807] A "personal profile" is a personalized dataset generated based on a user's size information and fashion preferences.

[0808] "Clothing" refers to clothing and fashion items that are suggested to the user.

[0809] "Positive feedback" refers to encouraging user choices and increasing satisfaction through positive messages.

[0810] Augmented reality technology is a technology that overlays digital information onto the real world, integrating virtual information into the user's real-world field of vision.

[0811] A "three-dimensional virtual experience" is a three-dimensional try-on experience that allows users to feel realistically within a virtual space.

[0812] "Device" refers to the hardware and software used by users to visually experience virtual try-on.

[0813] The system that realizes this invention operates by combining various hardware and software to provide users with a personalized fashion experience. The main hardware used is a visual device such as smart glasses equipped with augmented reality technology that provides users with a virtual try-on experience. For example, smart glasses overlay digital information onto the real field of view, enabling a realistic three-dimensional virtual experience.

[0814] The device receives size information and fashion preferences from the user and sends this information to a server. The server is located in the cloud and uses the received data to generate a personal profile. An AI analysis engine is used to generate this profile, supporting the selection of fashion items that match the user's preferences.

[0815] Next, the server analyzes a large amount of stored fashion information and selects the optimal clothing based on the user's profile. This selection process is highly personalized using a generative AI model. The selected clothing information is sent to the device, allowing the user to virtually try on a series of outfits through smart glasses. Once the user selects an item, the device immediately displays positive feedback to boost their confidence in their choice.

[0816] As a concrete example, imagine a scenario where a user wears smart glasses, accesses a virtual store, and selects a casual shirt and jeans. At this point, feedback such as, "This digital shirt complements your everyday style," is displayed. This allows consumers to make more appropriate and confident choices. An example of a prompt might be, "Woman in her 30s, elegant fashion, size L, office casual."

[0817] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0818] Step 1:

[0819] The device starts up and receives size information and fashion preferences as input from the user. This input is done through an input screen on the device. This involves the user entering their measurements and preferred style into a form displayed on the screen.

[0820] Step 2:

[0821] The terminal sends user input to the server. The server receives this data and generates a personal profile based on the input data. Using a generation AI model, the received data is analyzed and a profile reflecting the user's size and fashion preferences is output. In this process, the AI ​​engine performs calculations to create the profile based on the user data.

[0822] Step 3:

[0823] The server searches a stored fashion information database and selects clothing that matches the user's profile. In this step, the server uses an AI algorithm to extract relevant fashion items from the database and generates the selection results as output. This includes leveraging the latest trend information within the database.

[0824] Step 4:

[0825] The selected clothing list is sent to the device, and the user visually confirms it through smart glasses. This involves the user virtually trying on clothes using augmented reality technology via the glasses device, and seeing themselves in the virtual image.

[0826] Step 5:

[0827] When a user selects a specific outfit, the device sends that selection information to the server. The server generates positive feedback for the selected clothing and outputs a message to the device. The device displays this message, indicating to the user that the selection is appropriate. In this step, a generative AI model performs calculations to generate a positive prompt statement about the selected item.

[0828] Step 6:

[0829] The entire system process is finalized. Log data is saved to the server to record that the user made a satisfactory choice and to incorporate feedback into future suggestions. This involves the terminal interacting with the server to record the user's selection data and use it in subsequent suggestion processes.

[0830] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0831] This invention is a system that incorporates an emotion engine to enhance the user's fashion experience, and is implemented using a terminal and a server. The user inputs their size data and fashion preferences through the terminal. The terminal sends this information to the server, which generates a personal profile. This profile serves as the basis for suggesting the most suitable clothing for the user.

[0832] The server is equipped with an emotion engine that analyzes the user's emotional state during input and selection. The emotion engine infers the user's emotions from their choices and responses while they interact with the device. This information is analyzed in real time and reflected in the fashion suggestions. The server references fashion data in a database and selects the most suitable clothing based on the user's profile and emotional state. The selected clothing list is sent to the device and presented to the user.

[0833] After the user selects clothing, the server considers the emotional information obtained by the emotion engine and dynamically generates positive feedback messages. Specifically, it customizes the feedback message based on the emotional state the user was in when they selected the particular clothing item and sends it to the device. For example, it might provide detailed feedback such as, "This color will refresh your mood!"

[0834] Furthermore, when a user enters family information into their device, the server also uses emotional data to generate family-specific profiles. Based on each member's emotional state, it generates and sends appropriate outfits and feedback for the entire family to the device, providing a cohesive fashion experience.

[0835] This system also supports virtual try-on experiences. An emotion engine recognizes the user's emotions during virtual try-on and uses this information to provide suggestions within the virtual space. This allows users to check fittings without physical try-on and find styles that match their emotions. By specifically implementing this invention, users can obtain a fashion experience that takes their emotions into consideration.

[0836] The following describes the processing flow.

[0837] Step 1:

[0838] The user logs into the system using a terminal and enters size data and fashion preferences. The terminal collects this data and prompts for confirmation of the input through the user interface.

[0839] Step 2:

[0840] The device sends the collected size data and fashion preferences to the server. The server receives this data and generates a personal profile of the user. The profile includes the user's body measurements and style preferences.

[0841] Step 3:

[0842] The server's emotion engine analyzes the user's initial emotional state based on their input and actions. The emotion engine infers the user's emotions based on factors such as the language used and the speed at which choices are made.

[0843] Step 4:

[0844] The server searches the database and, based on the generated profile and sentiment data obtained from the sentiment engine, creates a list of clothing suitable for the user. This list includes items that match the size and style.

[0845] Step 5:

[0846] The server sends a suggested clothing list to the terminal. The terminal displays the list and gives the user the opportunity to make a selection. At the same time, it displays an emotion meter to record the user's feelings at the time of selection.

[0847] Step 6:

[0848] The user selects an item of clothing from a suggested list. The device sends the selection data and emotion meter information to the server. The server updates the emotion data related to the user's selection.

[0849] Step 7:

[0850] The server uses an emotion engine to generate positive feedback messages based on the user's choices. The generated feedback takes the user's emotional state into account, making it more personalized.

[0851] Step 8:

[0852] The server sends the generated feedback message to the terminal. The terminal displays the feedback to the user, providing support to increase confidence in their choice.

[0853] Step 9:

[0854] When a user enters family information, the device collects this information and sends it to the server. The server generates a family-based profile and suggests coordination and feedback based on each member's emotional state.

[0855] Step 10:

[0856] If the user wishes, they can start a virtual try-on. The terminal displays the virtual try-on interface, and the server's emotion engine analyzes the user's emotions during the virtual try-on, enabling more precise fitting suggestions.

[0857] (Example 2)

[0858] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0859] In today's fashion market, while there is a demand for personalized clothing suggestions based on individual user size data and preferences, there are challenges in providing more sophisticated suggestions that take into account the user's emotional state, coordinating outfits for the entire family, and realizing new experiences such as virtual try-on. This challenge makes it difficult for consumers to make the best fashion choices for themselves.

[0860] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0861] In this invention, the server includes means for collecting dimensional information and fashion preferences from the user and generating an individual profile; means for suggesting clothing that suits the user profile based on multiple clothing-related data stored in an information storage device; and means for analyzing the emotional state from the user's actions and selections. This enables personalized clothing suggestions that are in line with the user's emotions.

[0862] "Dimensional information" refers to information about the measured size and dimensions of the user's body.

[0863] A "personalized profile" refers to a personalized dataset based on a user's specific size, preferences, and emotional state.

[0864] "Information storage device" refers to a device for storing and preserving digital information, and includes databases and hard disks.

[0865] "Clothing-related data" refers to information about various clothing items, including attribute information such as design, color, and material.

[0866] "Emotional state" refers to the emotional state a user exhibits in a particular situation, and is a psychological state that influences their behavior and choices.

[0867] A "virtual domain" refers to a visual or conceptual virtual space constructed using computer technology.

[0868] "Personalization" refers to adjusting or customizing something according to the individual characteristics and preferences of the user.

[0869] To implement this system, a server and terminals form the basic communication infrastructure. The server collects user size information and fashion preferences and performs central data processing to create individual user experiences. This system uses an "information storage device" as a database management system, with SQL databases being a specific example.

[0870] The server uses a generative AI model, such as a "natural language processing engine," to analyze the user's emotional state. This AI model has the ability to analyze the user's past choices and input data to infer emotions in real time.

[0871] The terminal is a device that provides an interface with the user, and can specifically be a smartphone or a computer. The terminal sends data from the user to the server and displays personalized clothing suggestions received from the server.

[0872] A concrete example involves a user using their smartphone at home, opening the app, and entering their preferences. If the user prefers a particular color or style, they can enter data related to that preference. This data is encrypted and securely transmitted to the server.

[0873] Specific examples of prompt messages include "Which color suits your mood?" or "Try choosing a style that perfectly matches your mood today." This makes it easier for users to input their emotions more naturally, and the system's suggestions become more appropriate and personalized.

[0874] This system configuration takes into account the user's emotions and size profile, and can also implement features such as family-based and virtual try-on. As a result, it becomes possible to provide a more comprehensive and personalized fashion experience, thereby increasing user satisfaction.

[0875] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0876] Step 1:

[0877] The user inputs their dimensions and fashion preferences using a terminal. The terminal receives this information as input data, packets it, and sends it to the server. Specifically, the user fills in the information in the input form and presses the submit button.

[0878] Step 2:

[0879] The server analyzes the input data received from the terminal and generates individual profiles. This generation process uses a database management system to store the data and create a new profile for each user. Based on the input data, a dataset is created that takes into account the user's preferences and size.

[0880] Step 3:

[0881] The server searches for suitable clothing from a clothing-related database in its information storage device, based on the generated profile. Using database queries, it selects fashion items that match the user's preferences and size. As a result of this process, a list of recommended clothing items is output.

[0882] Step 4:

[0883] The server uses a generative AI model to analyze the user's emotional state. This analysis is based on the user's past selection history and input data, and performs data calculations to estimate the appropriate emotional state. In this process, the attributes most relevant to the user's emotions are extracted.

[0884] Step 5:

[0885] The server takes emotional states into account and dynamically adjusts clothing suggestions. This is done by adding real-time emotional data to the selected clothing list. This process results in more personalized suggestions.

[0886] Step 6:

[0887] The terminal presents the user with the final list of suggestions received from the server. A visual interface is used for this display, allowing the user to review and select the suggested clothing. The user then selects specific items and considers the details.

[0888] Step 7:

[0889] After the user makes a selection, the server generates a positive feedback message. This message is customized based on the emotional state analyzed by the generating AI model. For example, feedback such as "This color suits you well today!" might be output.

[0890] (Application Example 2)

[0891] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0892] Modern consumers demand personalized fashion suggestions tailored to their emotions and preferences, but traditional systems fail to adequately meet this need. Furthermore, if the virtual experience feels unrealistic, consumer satisfaction may decrease. This makes it difficult for consumers to easily make fashion choices that match their emotional state, highlighting the challenge of providing personalized fashion experiences.

[0893] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0894] This invention includes a server that provides means for receiving biometric data and preference information from a user and generating an integrated profile; means for recommending clothing that matches the user's profile and emotional state based on various decorative information stored in a memory device; means for analyzing the user's emotional data and generating and outputting dynamic feedback messages for the selected clothing; and means for providing the user with a virtual try-on experience through an interactive augmented reality environment. This enables the user to have a realistic and personalized fashion experience that is tailored to their own emotions and preferences.

[0895] "Biometric data" refers to information that reflects a user's physical characteristics and emotional state.

[0896] "Preference information" refers to information that indicates the style, colors, and fashion trends that a user prefers.

[0897] An "integrated profile" is a dataset that represents an individual's characteristics, generated based on the user's biometric data and preference information.

[0898] A "storage device" is a computer device used to store and access various data related to fashion and accessories.

[0899] "Decorative information" refers to information about various fashion items and styles.

[0900] "Emotional state" refers to the state of a user's real-time emotional response while they are accessing a website.

[0901] "Clothing" refers to all the clothing and accessories that the user wears.

[0902] A "dynamic feedback message" is a message that is generated and output in real time in response to the user's choices and emotions.

[0903] An "interactive augmented reality environment" is a platform that allows users to enjoy an integrated and bidirectional experience of trying on clothes in both the real world and a virtual environment.

[0904] A "virtual try-on experience" is an experience that allows users to simulate how clothes and accessories feel to wear in a virtual space without physically trying them on.

[0905] This invention provides a system for users to obtain a personalized fashion experience in a virtual store. The system consists of a user terminal, a server that manages a database, and an emotion analysis engine. Each component is described in detail below.

[0906] The terminals used include smartphones, smart glasses, and head-mounted displays, and their role is to receive biometric data and preference information from the user. This information is transmitted from the terminal to a server. Specifically, the biometric data includes facial expression data captured using a camera, which is used to analyze the emotional state.

[0907] The server uses an emotion analysis API, such as the Microsoft Azure Emotion API, to analyze the user's emotional state from the received biometric data. Based on the emotional state and preference information, the server selects the most suitable clothing from various fashion data stored in its memory. This enables personalized fashion suggestions tailored to the user's emotions and preferences.

[0908] Furthermore, it generates dynamic feedback messages based on the user's choices. This feedback is customized according to the sentiment analysis results, providing a more personalized and interactive experience. For example, the user might be presented with a message such as, "This color will refresh your mood!"

[0909] Furthermore, it is built to allow users to experience virtual try-ons through an interactive augmented reality environment. This means users can enjoy a realistic try-on experience without physically going to a store, and can check the fit before purchasing.

[0910] An example of a prompt might be, "If the user is determined to be relaxed, suggest a recommended casual style." Such prompts form the basis for the generative AI model to provide optimal fashion suggestions.

[0911] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0912] Step 1:

[0913] The user accesses the device and enters biometric data and preference information. The entered biometric data is facial expression data captured via the camera. The device then sends this data to the server.

[0914] Step 2:

[0915] The server uses the Microsoft Azure Emotion API to analyze the user's emotional state based on the received biometric data. This analysis identifies the user's current emotion (e.g., joy, surprise, relaxation).

[0916] Step 3:

[0917] The server integrates user preference information with analyzed emotional data and selects the most suitable clothing from a fashion database stored in memory. Here, prompts are input to a generative AI model, which generates fashion suggestions tailored to the user's emotions and preferences.

[0918] Step 4:

[0919] The selected clothing items are sent to the terminal and presented to the user. The user can then virtually try them on. The terminal provides a virtual environment that simulates the fit and appearance of the clothing.

[0920] Step 5:

[0921] When a user selects clothing, the server generates a dynamic feedback message based on the results of sentiment analysis. The generated feedback is sent to the user's device and presented to the user as a positive reminder.

[0922] Step 6:

[0923] If a user decides to make a purchase, the result is fed back to the server, and the final suggestion data is updated. This feedback is used to optimize future fashion suggestions.

[0924] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0925] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0926] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0927] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0928] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0929] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0930] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0931] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0932] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0933] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0934] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0935] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0936] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0937] 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.

[0938] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0939] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0940] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0941] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0942] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0943] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0944] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0945] The following is further disclosed regarding the embodiments described above.

[0946] (Claim 1)

[0947] A means of receiving size data and fashion preferences from users and generating personal profiles,

[0948] A means of suggesting clothing that matches the user's profile based on multiple fashion data stored in a database,

[0949] A means of generating and outputting positive feedback for the clothing selected by the user,

[0950] A system that includes this.

[0951] (Claim 2)

[0952] The system according to claim 1, comprising means for generating family-based profiles and suggesting matching outfits for all family members.

[0953] (Claim 3)

[0954] The system according to claim 1, comprising means for suggesting clothing in a virtual space and enabling the user to experience virtual try-on.

[0955] "Example 1"

[0956] (Claim 1)

[0957] A means of receiving biometric information and fashion preferences from users and generating personal profiles,

[0958] A means of selecting and suggesting clothing that matches the user's profile based on multiple style information stored in an information repository,

[0959] A means for generating and displaying a positive response to the clothing item selected by the user from among the selected items,

[0960] A means of generating positive messages based on choices using a generative AI model,

[0961] A system that includes this.

[0962] (Claim 2)

[0963] The system according to claim 1, comprising means for generating a profile for the entire unit and presenting costume suggestions that match all members.

[0964] (Claim 3)

[0965] The system according to claim 1, which includes a function that suggests clothing in a virtual realm and allows the user to experience virtual try-on.

[0966] "Application Example 1"

[0967] (Claim 1)

[0968] A method for receiving size information and fashion preferences from users and generating personal profiles.

[0969] A means for selecting clothing that matches the user's profile based on a large amount of stored fashion information,

[0970] A method for generating and displaying positive feedback for clothing selected by the user,

[0971] A device that uses augmented reality technology to provide users with a three-dimensional virtual experience of trying on clothing,

[0972] A system that includes this.

[0973] (Claim 2)

[0974] The system according to claim 1, comprising means for generating family-unit profiles and providing harmonious coordination for all family members.

[0975] (Claim 3)

[0976] The system according to claim 1, comprising means for displaying selected clothing superimposed on the user's field of view using augmented reality technology.

[0977] "Example 2 of combining an emotion engine"

[0978] (Claim 1)

[0979] A means of collecting dimensional information and fashion preferences from users and generating individual profiles,

[0980] A means for suggesting clothing that suits a user profile based on multiple clothing-related data stored in an information storage device,

[0981] A means for generating and outputting a positive response to the clothing selected by the user,

[0982] A means for analyzing the emotional state from the user's actions and selections,

[0983] A means of dynamically adjusting the proposed content based on sentiment analysis,

[0984] A system that includes this.

[0985] (Claim 2)

[0986] The system according to claim 1, comprising means for generating a profile of the entire family and suggesting clothing suitable for all family members.

[0987] (Claim 3)

[0988] The system according to claim 1, comprising means for suggesting clothing within a virtual domain and enabling a user to experience virtual try-on.

[0989] "Application example 2 when combining with an emotional engine"

[0990] (Claim 1)

[0991] A means of receiving biometric data and preference information from users and generating an integrated profile,

[0992] A means for recommending clothing that matches the user's profile and emotional state based on diverse decorative information stored in a memory device,

[0993] A means for analyzing user emotional data and generating and outputting dynamic feedback messages for selected clothing,

[0994] A means of providing users with a virtual try-on experience through an interactive augmented reality environment,

[0995] A system that includes this.

[0996] (Claim 2)

[0997] The system according to claim 1, comprising means for generating multiple user-based profiles and suggesting styling that matches all members of the group.

[0998] (Claim 3)

[0999] The system according to claim 1, comprising means for proposing clothing in a virtual environment and enabling the user to experience an immersive try-on. [Explanation of Symbols]

[1000] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving size data and fashion preferences from users and generating personal profiles, A means of suggesting clothing that matches the user's profile based on multiple fashion data stored in a database, A means of generating and outputting positive feedback for the clothing selected by the user, A system that includes this.

2. The system according to claim 1, comprising means for generating family-based profiles and suggesting matching outfits for all family members.

3. The system according to claim 1, comprising means for suggesting clothing in a virtual space and enabling the user to experience virtual try-on.

Images