system

Abstract

Provide a system. 【Solution means】 Means for acquiring user's body information, Means for diagnosing the skeletal type and color type based on the acquired body information, Means for acquiring product information from a plurality of information providing platforms based on the diagnosis result, Means for filtering the product information acquired based on the diagnosis result and selecting products suitable for the user, Means for proposing beauty information in association with the selected products, Means for displaying the proposed beauty information and product information, Means for experiencing the proposed products and beauty methods in a physical store, A system including the above.

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 and includes 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 existing fashion and makeup selection systems, there is a problem that it is difficult to make an optimal selection based on individual body information and color characteristics of users. There are also problems with methods for efficiently screening appropriate products from online shopping sites. Furthermore, when a user hopes for styling considering a specific scene, the proposed accessories and makeup may be inappropriate.

Means for Solving the Problems

[0005] This invention provides a system that acquires a user's physical information and performs a diagnosis regarding their skeletal structure and color. It then acquires product information from multiple shopping sites and filters products suitable for the user based on the diagnosis results. Furthermore, it provides means for suggesting optimal makeup information related to the selected products and displaying this information comprehensively, thereby offering personalized styling suggestions to the user.

[0006] "Means for acquiring user physical information" refers to an interface for users to input information about their body shape and color, and a system for processing this information.

[0007] A "means for diagnosing skeletal type and color type" refers to a system equipped with algorithms and logic that determine the characteristics related to the user's skeletal structure and the color characteristics related to the individual's skin, hair, and eye color, based on the acquired physical information of the user.

[0008] "Means for acquiring product information" refers to a system that executes a process of receiving product-related data from multiple purchasing sites through a program.

[0009] "A means of filtering product information and selecting products suitable for the user" refers to a system equipped with evaluation criteria and algorithms for selecting products appropriate for the user from acquired product information based on the skeletal structure and color type obtained through diagnosis.

[0010] A "means for suggesting cosmetic information" refers to a system that extracts and presents information to provide users with cosmetics and cosmetic techniques related to selected fashion items.

[0011] "Means for displaying product information and cosmetic information" refers to a system equipped with a display or interface that displays information about selected products and suggested cosmetics in a format that can be viewed by the user. [Brief explanation of the drawing]

[0012] [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] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a 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 disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] 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).

[0019] 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."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] This invention is a system that acquires a user's physical information and proposes individually optimized fashion and makeup based on that information. This system is operated in cooperation with the user, server, and terminal.

[0034] First, the user inputs their physical information through the terminal's user interface. Specifically, this includes body type, skin color, and hair color. This information is sent to a server, which then uses it to diagnose the user's skeletal type and color type. The diagnosis uses existing algorithms and databases to accurately determine the user's characteristics.

[0035] After obtaining the diagnostic results, the server retrieves product information through APIs of multiple shopping sites specified by the user. This product information includes clothing, accessories, and other fashion items. Based on the user's diagnostic results, the server filters the retrieved products and selects the one that is most suitable for the user.

[0036] Based on the selected fashion items, the server suggests cosmetics and makeup techniques to the user. These suggestions are designed to harmonize with the style and color of the chosen clothing. Specific manufacturers, product names, and usage instructions are retrieved from the database and transmitted to the terminal as information.

[0037] Furthermore, depending on the context the user enters, the server can offer additional suggestions regarding styling and accessories. This enables the creation of a comprehensive fashion and makeup coordinated look that is best suited to a specific occasion.

[0038] Finally, the terminal displays the information sent from the server to the user in a highly visualized format. This allows the user to review the details of the selected items and decide whether to purchase or use them as needed. This entire process enables the user to quickly find the styling that best suits them.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user enters their physical information using the terminal's interface. This includes data such as body type, skin color, and hair color, which are entered into a form.

[0042] Step 2:

[0043] The terminal transmits the entered physical information to the server. This data forms the basis for the diagnostic process.

[0044] Step 3:

[0045] The server uses the received physical information to diagnose skeletal type and color type. This is done by applying a pre-programmed diagnostic algorithm.

[0046] Step 4:

[0047] Based on the diagnostic results, the server retrieves product information using the purchasing site's API. Here, it collects data on fashion items from the online shop specified by the user.

[0048] Step 5:

[0049] The server filters the retrieved product information based on the diagnostic results, selecting products that match the user's bone structure and color preferences.

[0050] Step 6:

[0051] The server searches the database for cosmetic information related to the selected fashion items and generates makeup suggestions suitable for the user.

[0052] Step 7:

[0053] The user inputs specific situations (work, leisure, date, etc.) through their device. This information is sent to the server.

[0054] Step 8:

[0055] The server optimizes styling by suggesting accessories and adjusting makeup based on the input scene.

[0056] Step 9:

[0057] The device receives information from the server and displays recommended fashion, makeup, and accessory information on the user interface.

[0058] (Example 1)

[0059] 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."

[0060] To meet the diverse needs of today's consumers, it is crucial to suggest appropriate fashion and beauty items based on each individual's physical characteristics. However, many current systems do not adequately select products according to each user's physical characteristics, and the lack of automation often limits the available options. Furthermore, efficiently obtaining appropriate product information from different e-commerce platforms is difficult. As a result, the process of providing personalized services is cumbersome, and it is challenging to help users make the best choices.

[0061] 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.

[0062] In this invention, the server includes a device for collecting the user's physical characteristics, a device for diagnosing the structural type and hue type based on the collected physical characteristics, and a device for acquiring product information from multiple e-commerce platforms based on the diagnosis results. This makes it possible to efficiently suggest products and related beauty information optimized for the user's individual characteristics.

[0063] "User physical characteristics" refer to the user's physical or physiological features, such as body type, skin color, and hair color.

[0064] A "data collection device" is a device that uses a user interface or camera to acquire the user's physical characteristics and transmit the necessary information to a server.

[0065] A "device for diagnosing structural type and hue type" is a system that uses AI and algorithms to analyze the user's physical characteristics to determine their skeletal type and skin color, and then outputs the results.

[0066] A "device for acquiring product information" is a component that has interfaces with multiple e-commerce platforms and uses APIs, etc., to collect product data.

[0067] A "device for selecting and determining suitable products for users" is a system equipped with the function of filtering product information collected based on diagnostic results and selecting the most suitable product for the user.

[0068] "Beauty information" refers to information related to cosmetics and makeup techniques that complement or enhance a user's appearance.

[0069] A "display device" is a device that shows the suggested results on the terminal screen so that the user can visually confirm the information on the spot.

[0070] This invention is a system that provides recommendations for fashion and beauty items customized based on the user's physical characteristics. This system involves the cooperation of the user, a terminal, and a server. The following describes specific embodiments for carrying out the invention.

[0071] First, the user inputs their physical characteristics using a device. The device utilizes its camera function to take a photo of the user's face, and then uses AI technology to automatically recognize the user's skin tone. As a result, the user can easily input information such as body type and hair color. The device collects this information and transmits it to a server via a communication network.

[0072] The server uses machine learning algorithms implemented in Python or R to diagnose the user's skeletal type and color type based on their physical characteristics. For this purpose, it utilizes a pre-collected and analyzed database. This diagnosis is processed in real time by a specific algorithm.

[0073] Once the diagnostic results are obtained, the server retrieves product information using APIs from multiple e-commerce platforms. This includes common e-commerce sites. The server filters the retrieved information against the diagnostic results to identify the product best suited to the user.

[0074] Next, the server suggests beauty information related to the selected product. This information is obtained from a database and includes cosmetic ingredient information and application methods. This information is tailored to the user's physical characteristics and provides detailed instructions on optimal usage.

[0075] Finally, the device displays this data to the user. This display utilizes AR technology and 3D rendering, allowing the user to interactively review the suggested styles. The user can then choose to purchase the suggested items as needed.

[0076] As a concrete example, suppose a user inputs physical characteristics such as "slim build, light-toned skin, dark brown hair" and selects "business casual." In this case, the server automatically selects relevant fashion items and beauty products and displays them on the device. Furthermore, the following prompts can be entered into the generating AI model.

[0077] "The user has a slim build, light skin tone, and dark brown hair. Please suggest the optimal combination of fashion and makeup for a business setting."

[0078] In this way, users can quickly receive personalized fashion and beauty advice.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] Users input their physical characteristics through the device's user interface. Specifically, users take a photo of their face using the device's camera and manually or automatically record features such as body shape, skin color, and hair color. This input data is directly stored on the device and temporarily prepared for analysis.

[0082] Step 2:

[0083] The terminal sends the entered physical characteristics data to the server. Once the user's data reaches the server, the server analyzes the data and compares it with past data in the database. In this process, machine learning algorithms are used to diagnose the user's skeletal type and color type by comparing it with the information in the database. Based on this input data, a diagnosis result specific to the user is output.

[0084] Step 3:

[0085] The server retrieves product information through APIs of multiple e-commerce platforms based on the diagnostic results. The server uses the diagnostic results as filtering criteria to select the product information. The data processing performed here is to select the most suitable product based on the diagnosis. This process matches the list of products to the user's physical characteristics, and the selected product information is output.

[0086] Step 4:

[0087] The server retrieves beauty information from the database that matches the selected product, and further adjusts this information based on the user's characteristics. The generated beauty information is then sent from the server to the terminal. Data processing includes selecting cosmetics that match the user's skin tone and fashion style. As a result, beauty information is output.

[0088] Step 5:

[0089] The terminal visually displays product and beauty information received from the server to the user. Using AR technology and 3D rendering, the terminal allows the user to intuitively confirm suggested styles. In this data display process, information is output in a format that the user can actually see and select.

[0090] (Application Example 1)

[0091] 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."

[0092] Modern consumers have a need to quickly and accurately obtain fashion and beauty information that suits their physical characteristics. However, the amount of product information available online and in physical stores is vast, making it time-consuming and laborious to make the best individual choices. Furthermore, there is a lack of opportunities to actually experience the suggested items and beauty methods firsthand.

[0093] 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.

[0094] In this invention, the server includes means for acquiring the user's physical information, means for diagnosing the skeletal type and color type based on the acquired physical information, means for acquiring product information from multiple information provision platforms based on the diagnosis results, means for filtering the acquired product information based on the diagnosis results to select products suitable for the user, means for suggesting beauty information associated with the selected products, means for displaying the suggested beauty information and product information, and means for experiencing the suggested products and beauty methods in a physical store. This enables consumers to efficiently and effectively acquire individually optimized fashion and beauty information and to actually experience it on the spot.

[0095] "User body information" refers to data on personal characteristics necessary for optimizing fashion and beauty, such as an individual's body shape, skin color, and hair color.

[0096] "Skeletal type" refers to information that indicates the structural characteristics of the body, classified based on the user's body shape.

[0097] "Color type" refers to information that describes the characteristics of color tones, classified based on factors such as the user's skin and hair color.

[0098] An "information provision platform" is a digital system that provides users with information about products and services online.

[0099] "Product information" refers to detailed data related to fashion items such as clothing and accessories.

[0100] "Beauty information" refers to detailed data about specific cosmetics or beauty techniques, which is used to improve the user's appearance.

[0101] "Filtering" is an information processing technique that selects the best option from multiple choices based on specific conditions.

[0102] "Means of experiencing in a physical store" refers to means that enable customers to actually use or try out the proposed product or method in a physical store.

[0103] The system for implementing this invention acquires the user's physical information and optimizes fashion and beauty based on that information. The system's foundation consists of computer terminals, including smartphones, a central server, and interactive display devices within physical stores.

[0104] The server receives physical information entered by the user through the terminal. This input data includes body type, skin color, and hair color. Based on this information, the server uses internal algorithms and a database to diagnose the user's skeletal type and color type. This allows for a precise analysis of the user's characteristics and guides them towards the most suitable fashion and beauty choices.

[0105] Next, the server uses multiple information provision platform APIs to collect product information based on the diagnostic results. This allows it to import and filter data for suitable products. The filtered product information is then selected as the optimal item linked to the user's physical characteristics. Furthermore, relevant beauty information is also suggested, including specific instructions on how to use cosmetics and detailed beauty methods.

[0106] The terminal visually presents information provided by the server to the user. Users can view and experience suggested products and beauty information on their smartphones or displays in physical stores. For example, in certain fitting rooms, users can actually try on clothes suggested by the AI ​​system and immediately see the effect. An example of a prompt message is, "If the user has a slim build, olive skin tone, and black hair, what fashion items and makeup would be best suited for them?"

[0107] The specific hardware used includes, for example, smartphones running iOS or Android® OS, and interactive displays such as large screens for displaying information in physical stores. The software uses a mobile application based on React Native, Node.js as the backend service, and Firebase for data management. These elements work together organically to provide users with a continuous and personalized experience.

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The user uses their smartphone to enter physical information into the application on the device. This information includes body type, skin color, hair color, etc. This data is then sent from the device to the server.

[0111] Step 2:

[0112] The server uses an internal algorithm to diagnose the user's skeletal type and color type based on the received physical information. This process compares the input data with an existing database and analyzes the user's characteristics. As a result, it generates data for the diagnosed skeletal type and color type.

[0113] Step 3:

[0114] Based on the diagnostic results, the server retrieves product information using multiple information provision platform APIs. The input data here is the diagnostic results, and the output is a list of retrieved products. By accessing the information provision platform APIs in real time, the range of product options tailored to the user's characteristics expands.

[0115] Step 4:

[0116] The server filters the retrieved product information and selects products suitable for the user. This process executes a specific filtering algorithm to extract product attributes that match the diagnostic results. As a result of this filtering, an optimal product list is generated.

[0117] Step 5:

[0118] The server generates beauty information associated with the selected product. This beauty information includes appropriate makeup techniques and cosmetic usage methods tailored to the suggested fashion. This generation process combines information by referencing product characteristics and related beauty databases. As a result, a list of beauty information is generated.

[0119] Step 6:

[0120] The terminal displays a list of optimal products and beauty information received from the server to the user. Here, information is presented through a visual interface, allowing the user to visually confirm the content. Input is information from the server, and output is as visual data that the user can confirm.

[0121] Step 7:

[0122] Based on the displayed information, users try on products and experience beauty techniques using interactive displays in physical stores. During this process, the display provides feedback on products relevant to the user's selections, and they then try them on and use them. Finally, the user evaluates the experience and can choose to purchase the products on the spot.

[0123] 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.

[0124] This invention is a system that proposes personalized fashion and makeup based on the user's physical information, and further makes more appropriate suggestions by recognizing the user's emotions using an emotion engine. This system is implemented via the user, server, and terminal.

[0125] Users input physical information about their body type and color preferences using a terminal. The server then diagnoses their skeletal type and color type. This diagnostic information is essential for providing fashion and makeup suggestions.

[0126] The server uses the diagnostic results to retrieve information on fashion items through the purchasing site's API. The retrieved product information is filtered to narrow down to items that match the user's diagnostic results. In addition, an emotion engine recognizes the user's emotions and makes emotional adjustments to the suggested items and related information. For example, if the user is feeling relaxed, items in calming colors and soft materials will be recommended.

[0127] Furthermore, the server suggests cosmetics and makeup techniques that match the color and style of the selected product. Based on the results of the emotion engine's recognition, the suggested makeup is also adjusted to suit the user's mood. For example, if the user desires an energetic impression, bright and vibrant makeup tones will be recommended.

[0128] Users can input specific scenarios through their devices, and the server combines this information with the results of an emotion engine analysis to further optimize styling suggestions for those specific scenarios. This makes it easy for users to choose fashion and makeup that suits a particular situation.

[0129] All of these features are presented in a visualized form on the device, allowing users to review suggestions and easily purchase or utilize them. This process enables users to find the style that best suits their mood and purpose for the day.

[0130] The following describes the processing flow.

[0131] Step 1:

[0132] Users enter their physical information using the terminal's interface. This information includes body type, skin tone, and hair color, which they fill out on a form.

[0133] Step 2:

[0134] The terminal sends the entered physical information to the server. The server receives this data and uses it for diagnosis in the next step.

[0135] Step 3:

[0136] The server uses the received physical information to diagnose the skeletal type and color type. The algorithm analyzes the physical characteristics and determines the user's skeletal characteristics and personal color.

[0137] Step 4:

[0138] Based on the diagnostic results, the server accesses APIs from multiple shopping sites to retrieve product information. The items retrieved include clothing and accessories, and include current fashion data.

[0139] Step 5:

[0140] Based on the diagnostic results, the server filters the acquired product information to select products suitable for the user. The selection criteria include the degree of match with the diagnostic results, such as shape, color, and material.

[0141] Step 6:

[0142] When a user inputs or records their emotions using the device's camera and microphone, the device sends that information to a server. The server uses an emotion engine to analyze this information and determine the user's emotional state.

[0143] Step 7:

[0144] The server adjusts filtered fashion item and cosmetic item suggestions based on the results of the emotion engine's analysis. For example, when a user is feeling down, it suggests brightly colored items and uplifting makeup.

[0145] Step 8:

[0146] The user enters the specific occasion for which they want to go out (business, casual, date, etc.) via their device. This information is sent to the server.

[0147] Step 9:

[0148] The server combines scene information and sentiment analysis to suggest accessories and additional styling elements that are appropriate for the specific scene.

[0149] Step 10:

[0150] The device receives final suggestions from the server and visually presents the user with information on fashion, makeup, and accessories. The user can use this information to make the best choice without stress.

[0151] (Example 2)

[0152] 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".

[0153] In fashion and makeup choices, there is a challenge in providing personalized suggestions that appropriately reflect the user's physical characteristics and emotional state. Furthermore, providing optimal styling for different situations requires the flexible use of user input information.

[0154] 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.

[0155] In this invention, the server includes means for acquiring data about the user's body, means for acquiring product data from multiple sites based on the diagnostic results, and means for recognizing the user's emotions and making emotional adjustments to the suggested products and information about cosmetics. This makes it possible to suggest personalized fashion and makeup based on the user's physical characteristics and emotional state.

[0156] A "user" is someone who uses the system to receive fashion and makeup suggestions based on their own physical information and emotional state.

[0157] "Physical data" refers to information such as the user's height, body type, skin color, and hair color, which serves as the basis for providing personalized suggestions.

[0158] "Skeletal characteristics" are features diagnosed based on the user's body type and skeletal structure, and are a factor that helps in fashion choices.

[0159] "Color characteristics" refer to the color type derived from the user's skin tone, eye color, hair color, etc., and are elements that serve as a basis for styling.

[0160] "Product data" refers to information about purchasable fashion items, and is a collection of information obtained from multiple websites.

[0161] "Information about cosmetics" refers to information about cosmetics and makeup techniques suggested to users.

[0162] "Emotional state" refers to the user's feelings and is an element recognized by the system.

[0163] "Emotional adjustment" refers to the process of responding to suggested fashion and makeup based on the user's perceived emotions.

[0164] This system consists of three elements: user, server, and terminal, and each element works together to provide the user with the most suitable fashion and makeup suggestions.

[0165] First, users input data about their bodies using a device. Common devices such as smartphones and tablets are used, and users input data through a dedicated application or web interface. This data includes height, body type, skin color, and hair color.

[0166] Next, the terminal sends the input data to the server, which uses this data to activate a generative AI model. The generative AI model is a tool for diagnosing the user's skeletal and color characteristics, analyzing the input numerical data and forming prompt sentences. These prompt sentences might be something like, "Diagnose the user's skeletal characteristics and color type, and suggest fashion and makeup that emphasizes relaxation."

[0167] Subsequently, the server retrieves product data from multiple online marketplaces based on the diagnostic results. The APIs used here are standard ones for retrieving general product information. The retrieved data is filtered by a generative AI model to select items suitable for the user.

[0168] Furthermore, the device uses built-in sensors to read the user's emotional state from their facial expressions and voice. This emotional information is sent to a server and analyzed by AI.

[0169] The server makes emotional adjustments to the product and cosmetic information it suggests based on the perceived emotional state. For example, if the user wants to relax, items with calming colors and materials will be selected.

[0170] Finally, the processed suggestions are visualized on the device, allowing the user to view the suggestions and choose whether or not to purchase their preferred items. A concrete example of how the system can be used is that by receiving suggestions tailored to the user's situation, users can quickly choose the optimal fashion and makeup.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] The user uses a device to input data about their body (e.g., height, body type, skin color). The device then sends this input data to the server. Specifically, the user enters information into an application form and presses the submit button. The data entered represents the individual's physical characteristics.

[0174] Step 2:

[0175] The server supplies the received data to a generating AI model to diagnose the user's skeletal and color characteristics. Specifically, the AI ​​model analyzes the input data and generates prompt sentences. The output at this stage is a diagnostic result summarizing the user's characteristics.

[0176] Step 3:

[0177] The server calls APIs from multiple online marketplaces based on the diagnostic results to retrieve product data. The input is the diagnostic results, and the output is a list of product information suitable for the user. Specifically, the server queries the database of each marketplace via the APIs.

[0178] Step 4:

[0179] The device uses sensors to capture the user's facial expressions and voice, and analyzes their emotional state. This data is sent to a server. Specifically, the camera and microphone on the device capture data in real time and pass it to an analysis program. The output is data indicating the user's emotional state.

[0180] Step 5:

[0181] The server combines acquired product information with emotional states to make emotional adjustments to the suggestions. Specifically, the AI ​​prioritizes colors and styles that match the user's mood. The input is a product list and emotional data, and the output is adjusted fashion and makeup suggestions.

[0182] Step 6:

[0183] The device displays the adjusted suggestions to the user in a visual format. The user then uses this to make a purchase decision. Specifically, the device displays the suggestions on the screen using graphics and text, and provides a purchase link. The output is visual suggestion content for the user.

[0184] (Application Example 2)

[0185] 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".

[0186] Modern consumers tend to seek personalized fashion and makeup, but existing systems do not adequately consider the user's physical information and emotions when making suggestions. Furthermore, users cannot receive personalized suggestions tailored to their current emotions or specific situations, making it difficult for them to determine what fashion and makeup are appropriate.

[0187] 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.

[0188] In this invention, the server includes means for acquiring the user's physical information and diagnosing their skeletal type and color type, means for acquiring and filtering product information based on the diagnosis results, and means for analyzing the user's emotions using a data acquisition device and reflecting that information in the suggestions. This enables personalized suggestions based on the user's physical and emotional state.

[0189] "User body information" refers to individual information necessary for fashion and makeup suggestions, such as the user's body type and skin tone.

[0190] "Body type and color type diagnosis" is a classification process that analyzes the user's acquired physical information to determine the most suitable fashion and makeup.

[0191] "Means of acquiring product information" refers to technology that collects information on relevant fashion items and cosmetics from purchasing websites based on the diagnostic results.

[0192] "Methods for filtering product information" refers to the process of narrowing down acquired product information to only those that match the user's individual diagnostic results.

[0193] A "means of suggesting cosmetic information" refers to a system that recommends suitable cosmetics and makeup methods to the user based on the selected product.

[0194] A "data acquisition device" is an electronic device used to receive input from the user and plays the role of collecting information.

[0195] "Methods for analyzing emotions" refers to technologies that determine emotions from input such as user voices and reflect the results in the proposed content.

[0196] The system that realizes this invention operates via a user-owned device and a server. The user's device scans the user's physical information using data acquisition devices such as a camera and acquires voice tone and emotions using a microphone. This acquired data is transmitted to the server.

[0197] The server analyzes the received physical information to diagnose the user's skeletal type and color type. OpenCV and numpy are used for image data processing and numerical analysis during the diagnosis. Furthermore, the Google® Speech-to-Text API is used to analyze the user's emotions from their voice and generate emotion-based advice.

[0198] Subsequently, the server uses the purchasing site's API to retrieve information on relevant fashion items and cosmetics based on the diagnostic results. This information is filtered according to the user's diagnostic results and sentiment analysis. This allows the system to suggest the most suitable fashion and makeup combinations for the user.

[0199] Users can visually review these suggestions on their device and make specific makeup and clothing choices through voice feedback. Through this process, users can easily choose styles that suit their mood or specific occasion, making their daily clothing and makeup decisions more personalized.

[0200] For example, if a user feels like "I want to feel energetic today," the server will suggest brightly colored clothing and makeup that gives an energetic impression. Examples of prompts for the generative AI model include the following:

[0201] "The user desires an energetic image, has a slim build, and prefers autumn colors. Please suggest the most suitable fashion and makeup."

[0202] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0203] Step 1:

[0204] The user uses a device to acquire their own physical information and voice through the camera and microphone. The camera captures the user's body shape and color, and the microphone records the tone of their voice. These inputs are sent to the server. The output is the user's physical information and voice data.

[0205] Step 2:

[0206] The server uses OpenCV and NumPy with the received physical information to diagnose the user's skeletal type and color type. The data is processed through image processing and numerical analysis, and a diagnostic result is output that forms the basis of the user's fashion style.

[0207] Step 3:

[0208] The server uses the Google Speech-to-Text API to analyze the user's emotions from their voice. It converts the audio data into text and analyzes it using an emotion recognition algorithm to output the user's current emotional state.

[0209] Step 4:

[0210] The server retrieves relevant product information via the purchasing site's API based on the diagnostic results and emotional state. It processes the product information according to pre-configured filtering criteria based on the input data and outputs information on the items most suitable for the user.

[0211] Step 5:

[0212] The server uses a generative AI model to suggest makeup information based on the obtained product information. By generating prompt messages and inputting them into the AI ​​model, it outputs customized makeup suggestions for the user.

[0213] Step 6:

[0214] The user's device visualizes fashion and makeup suggestions received from the server. Information is displayed on the device's screen, and advice is provided as voice feedback. This allows the user to gain concrete options regarding their own style.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] [Second Embodiment]

[0219] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] 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.

[0224] 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).

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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".

[0231] This invention is a system that acquires a user's physical information and proposes individually optimized fashion and makeup based on that information. This system is operated in cooperation with the user, server, and terminal.

[0232] First, the user inputs their physical information through the terminal's user interface. Specifically, this includes body type, skin color, and hair color. This information is sent to a server, which then uses it to diagnose the user's skeletal type and color type. The diagnosis uses existing algorithms and databases to accurately determine the user's characteristics.

[0233] After obtaining the diagnostic results, the server retrieves product information through APIs of multiple shopping sites specified by the user. This product information includes clothing, accessories, and other fashion items. Based on the user's diagnostic results, the server filters the retrieved products and selects the one that is most suitable for the user.

[0234] Based on the selected fashion items, the server suggests cosmetics and makeup techniques to the user. These suggestions are designed to harmonize with the style and color of the chosen clothing. Specific manufacturers, product names, and usage instructions are retrieved from the database and transmitted to the terminal as information.

[0235] Furthermore, depending on the context the user enters, the server can offer additional suggestions regarding styling and accessories. This enables the creation of a comprehensive fashion and makeup coordinated look that is best suited to a specific occasion.

[0236] Finally, the terminal displays the information sent from the server to the user in a highly visualized format. This allows the user to review the details of the selected items and decide whether to purchase or use them as needed. This entire process enables the user to quickly find the styling that best suits them.

[0237] The following describes the processing flow.

[0238] Step 1:

[0239] The user enters their physical information using the terminal's interface. This includes data such as body type, skin color, and hair color, which are entered into a form.

[0240] Step 2:

[0241] The terminal transmits the entered physical information to the server. This data forms the basis for the diagnostic process.

[0242] Step 3:

[0243] The server uses the received physical information to diagnose skeletal type and color type. This is done by applying a pre-programmed diagnostic algorithm.

[0244] Step 4:

[0245] Based on the diagnostic results, the server retrieves product information using the purchasing site's API. Here, it collects data on fashion items from the online shop specified by the user.

[0246] Step 5:

[0247] The server filters the retrieved product information based on the diagnostic results, selecting products that match the user's bone structure and color preferences.

[0248] Step 6:

[0249] The server searches the database for cosmetic information related to the selected fashion items and generates makeup suggestions suitable for the user.

[0250] Step 7:

[0251] The user inputs specific situations (work, leisure, date, etc.) through their device. This information is sent to the server.

[0252] Step 8:

[0253] The server optimizes styling by suggesting accessories and adjusting makeup based on the input scene.

[0254] Step 9:

[0255] The device receives information from the server and displays recommended fashion, makeup, and accessory information on the user interface.

[0256] (Example 1)

[0257] 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 glasses 214 will be referred to as the "terminal".

[0258] To meet the diverse needs of today's consumers, it is crucial to suggest appropriate fashion and beauty items based on each individual's physical characteristics. However, many current systems do not adequately select products according to each user's physical characteristics, and the lack of automation often limits the available options. Furthermore, efficiently obtaining appropriate product information from different e-commerce platforms is difficult. As a result, the process of providing personalized services is cumbersome, and it is challenging to help users make the best choices.

[0259] 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.

[0260] In this invention, the server includes a device for collecting the user's physical characteristics, a device for diagnosing the structural type and hue type based on the collected physical characteristics, and a device for acquiring product information from multiple e-commerce platforms based on the diagnosis results. This makes it possible to efficiently suggest products and related beauty information optimized for the user's individual characteristics.

[0261] "User physical characteristics" refer to the user's physical or physiological features, such as body type, skin color, and hair color.

[0262] A "data collection device" is a device that uses a user interface or camera to acquire the user's physical characteristics and transmit the necessary information to a server.

[0263] A "device for diagnosing structural type and hue type" is a system that uses AI and algorithms to analyze the user's physical characteristics to determine their skeletal type and skin color, and then outputs the results.

[0264] A "device for acquiring product information" is a component that has interfaces with multiple e-commerce platforms and uses APIs, etc., to collect product data.

[0265] A "device for selecting and determining suitable products for users" is a system equipped with the function of filtering product information collected based on diagnostic results and selecting the most suitable product for the user.

[0266] "Beauty information" refers to information related to cosmetics and makeup techniques that complement or enhance a user's appearance.

[0267] A "display device" is a device that shows the suggested results on the terminal screen so that the user can visually confirm the information on the spot.

[0268] This invention is a system that provides recommendations for fashion and beauty items customized based on the user's physical characteristics. This system involves the cooperation of the user, a terminal, and a server. The following describes specific embodiments for carrying out the invention.

[0269] First, the user inputs their physical characteristics using a device. The device utilizes its camera function to take a photo of the user's face, and then uses AI technology to automatically recognize the user's skin tone. As a result, the user can easily input information such as body type and hair color. The device collects this information and transmits it to a server via a communication network.

[0270] The server uses machine learning algorithms implemented in Python or R to diagnose the user's skeletal type and color type based on their physical characteristics. For this purpose, it utilizes a pre-collected and analyzed database. This diagnosis is processed in real time by a specific algorithm.

[0271] Once the diagnostic results are obtained, the server retrieves product information using APIs from multiple e-commerce platforms. This includes common e-commerce sites. The server filters the retrieved information against the diagnostic results to identify the product best suited to the user.

[0272] Next, the server suggests beauty information related to the selected product. This information is obtained from a database and includes cosmetic ingredient information and application methods. This information is tailored to the user's physical characteristics and provides detailed instructions on optimal usage.

[0273] Finally, the device displays this data to the user. This display utilizes AR technology and 3D rendering, allowing the user to interactively review the suggested styles. The user can then choose to purchase the suggested items as needed.

[0274] As a concrete example, suppose a user inputs physical characteristics such as "slim build, light-toned skin, dark brown hair" and selects "business casual." In this case, the server automatically selects relevant fashion items and beauty products and displays them on the device. Furthermore, the following prompts can be entered into the generating AI model.

[0275] "The user has a slim build, light skin tone, and dark brown hair. Please suggest the optimal combination of fashion and makeup for a business setting."

[0276] In this way, users can quickly receive personalized fashion and beauty advice.

[0277] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0278] Step 1:

[0279] The user inputs physical characteristics through the user interface of the terminal. Specifically, the user uses the camera of the terminal to take a photo of the face and manually or automatically records features such as body shape, skin color, and hair color. This input data is directly saved in the terminal and temporarily prepared for analysis.

[0280] Step 2:

[0281] The terminal sends the input physical characteristic data to the server. When the user's data reaches the server, the server analyzes the data and compares it with the past data in the database. In this process, machine learning algorithms are used to compare with the information in the database to diagnose the user's bone type and hue type. Specific diagnostic results for the user are output based on this input data.

[0282] Step 3:

[0283] The server obtains product information through the APIs of multiple e-commerce trading platforms based on the diagnostic results. The server uses the diagnostic results as filtering conditions to screen the product information. The data processing performed here is for selecting the most suitable products based on the diagnosis. This process matches the list of products to the user's physical characteristics, and the selected product information is output.

[0284] Step 4:

[0285] The server retrieves beauty information suitable for the selected products from the database and further adjusts this information in a form based on user characteristics. The generated beauty information is sent from the server to the terminal. The data processing includes the selection of cosmetics according to the user's skin color and fashion style. As a result, beauty information is output.

[0286] Step 5:

[0287] The terminal visually displays product and beauty information received from the server to the user. Using AR technology and 3D rendering, the terminal allows the user to intuitively confirm suggested styles. In this data display process, information is output in a format that the user can actually see and select.

[0288] (Application Example 1)

[0289] 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."

[0290] Modern consumers have a need to quickly and accurately obtain fashion and beauty information that suits their physical characteristics. However, the amount of product information available online and in physical stores is vast, making it time-consuming and laborious to make the best individual choices. Furthermore, there is a lack of opportunities to actually experience the suggested items and beauty methods firsthand.

[0291] 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.

[0292] In this invention, the server includes means for acquiring the user's physical information, means for diagnosing the skeletal type and color type based on the acquired physical information, means for acquiring product information from multiple information provision platforms based on the diagnosis results, means for filtering the acquired product information based on the diagnosis results to select products suitable for the user, means for suggesting beauty information associated with the selected products, means for displaying the suggested beauty information and product information, and means for experiencing the suggested products and beauty methods in a physical store. This enables consumers to efficiently and effectively acquire individually optimized fashion and beauty information and to actually experience it on the spot.

[0293] "User body information" refers to data on personal characteristics necessary for optimizing fashion and beauty, such as an individual's body shape, skin color, and hair color.

[0294] "Skeletal type" refers to information that indicates the structural characteristics of the body, classified based on the user's body shape.

[0295] "Color type" refers to information that describes the characteristics of color tones, classified based on factors such as the user's skin and hair color.

[0296] An "information provision platform" is a digital system that provides users with information about products and services online.

[0297] "Product information" refers to detailed data related to fashion items such as clothing and accessories.

[0298] "Beauty information" refers to detailed data about specific cosmetics or beauty techniques, which is used to improve the user's appearance.

[0299] "Filtering" is an information processing technique that selects the best option from multiple choices based on specific conditions.

[0300] "Means of experiencing in a physical store" refers to means that enable customers to actually use or try out the proposed product or method in a physical store.

[0301] The system for implementing this invention acquires the user's physical information and optimizes fashion and beauty based on that information. The system's foundation consists of computer terminals, including smartphones, a central server, and interactive display devices within physical stores.

[0302] The server receives physical information entered by the user through the terminal. This input data includes body type, skin color, and hair color. Based on this information, the server uses internal algorithms and a database to diagnose the user's skeletal type and color type. This allows for a precise analysis of the user's characteristics and guides them towards the most suitable fashion and beauty choices.

[0303] Next, based on the diagnosis result, the server collects product information using multiple information - providing platform APIs. By doing so, it captures data on suitable products and performs filtering. The filtered product information is selected as the optimal items in conjunction with the user's physical characteristics. Additionally, relevant beauty information is also proposed, which includes the specific usage methods of cosmetics and details of beauty techniques.

[0304] The terminal visually presents the information provided by the server to the user. The user can view and experience the proposed products and beauty information on a smartphone or a display within a physical store. For example, in a specific fitting room, one can actually try on the clothes proposed by the AI system and immediately confirm the effect. An example of a prompt sentence is, "When the user has a slender build, olive - colored skin, and black hair, please propose what fashion items and makeup are optimal."

[0305] Specific hardware to be used includes, for example, smartphones equipped with iOS or Android OS, and large - sized screens for displaying information on interactive displays within physical stores. Software includes mobile applications using React Native, Node.js as the backend service, and Firebase for data management. These are organically linked to enable the provision of a continuous and personalized experience to the user.

[0306] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0307] Step 1:

[0308] The user uses a smartphone to input physical information into the terminal's application. This information includes body type, skin color, hair color, etc. These data are transmitted from the terminal to the server.

[0309] Step 2:

[0310] The server uses an internal algorithm to diagnose the user's skeletal type and color type based on the received physical information. This process compares the input data with an existing database and analyzes the user's characteristics. As a result, it generates data for the diagnosed skeletal type and color type.

[0311] Step 3:

[0312] Based on the diagnostic results, the server retrieves product information using multiple information provision platform APIs. The input data here is the diagnostic results, and the output is a list of retrieved products. By accessing the information provision platform APIs in real time, the range of product options tailored to the user's characteristics expands.

[0313] Step 4:

[0314] The server filters the retrieved product information and selects products suitable for the user. This process executes a specific filtering algorithm to extract product attributes that match the diagnostic results. As a result of this filtering, an optimal product list is generated.

[0315] Step 5:

[0316] The server generates beauty information associated with the selected product. This beauty information includes appropriate makeup techniques and cosmetic usage methods tailored to the suggested fashion. This generation process combines information by referencing product characteristics and related beauty databases. As a result, a list of beauty information is generated.

[0317] Step 6:

[0318] The terminal displays a list of optimal products and beauty information received from the server to the user. Here, information is presented through a visual interface, allowing the user to visually confirm the content. Input is information from the server, and output is as visual data that the user can confirm.

[0319] Step 7:

[0320] Based on the displayed information, users try on products and experience beauty techniques using interactive displays in physical stores. During this process, the display provides feedback on products relevant to the user's selections, and they then try them on and use them. Finally, the user evaluates the experience and can choose to purchase the products on the spot.

[0321] 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.

[0322] This invention is a system that proposes personalized fashion and makeup based on the user's physical information, and further makes more appropriate suggestions by recognizing the user's emotions using an emotion engine. This system is implemented via the user, server, and terminal.

[0323] Users input physical information about their body type and color preferences using a terminal. The server then diagnoses their skeletal type and color type. This diagnostic information is essential for providing fashion and makeup suggestions.

[0324] The server uses the diagnostic results to retrieve information on fashion items through the purchasing site's API. The retrieved product information is filtered to narrow down to items that match the user's diagnostic results. In addition, an emotion engine recognizes the user's emotions and makes emotional adjustments to the suggested items and related information. For example, if the user is feeling relaxed, items in calming colors and soft materials will be recommended.

[0325] Furthermore, the server suggests cosmetics and makeup techniques that match the color and style of the selected product. Based on the results of the emotion engine's recognition, the suggested makeup is also adjusted to suit the user's mood. For example, if the user desires an energetic impression, bright and vibrant makeup tones will be recommended.

[0326] Users can input specific scenarios through their devices, and the server combines this information with the results of an emotion engine analysis to further optimize styling suggestions for those specific scenarios. This makes it easy for users to choose fashion and makeup that suits a particular situation.

[0327] All of these features are presented in a visualized form on the device, allowing users to review suggestions and easily purchase or utilize them. This process enables users to find the style that best suits their mood and purpose for the day.

[0328] The following describes the processing flow.

[0329] Step 1:

[0330] Users enter their physical information using the terminal's interface. This information includes body type, skin tone, and hair color, which they fill out on a form.

[0331] Step 2:

[0332] The terminal sends the entered physical information to the server. The server receives this data and uses it for diagnosis in the next step.

[0333] Step 3:

[0334] The server uses the received physical information to diagnose the skeletal type and color type. The algorithm analyzes the physical characteristics and determines the user's skeletal characteristics and personal color.

[0335] Step 4:

[0336] Based on the diagnostic results, the server accesses APIs from multiple shopping sites to retrieve product information. The items retrieved include clothing and accessories, and include current fashion data.

[0337] Step 5:

[0338] Based on the diagnostic results, the server filters the acquired product information to select products suitable for the user. The selection criteria include the degree of match with the diagnostic results, such as shape, color, and material.

[0339] Step 6:

[0340] When a user inputs or records their emotions using the device's camera and microphone, the device sends that information to a server. The server uses an emotion engine to analyze this information and determine the user's emotional state.

[0341] Step 7:

[0342] The server adjusts filtered fashion item and cosmetic item suggestions based on the results of the emotion engine's analysis. For example, when a user is feeling down, it suggests brightly colored items and uplifting makeup.

[0343] Step 8:

[0344] The user enters the specific occasion for which they want to go out (business, casual, date, etc.) via their device. This information is sent to the server.

[0345] Step 9:

[0346] The server combines scene information and sentiment analysis to suggest accessories and additional styling elements that are appropriate for the specific scene.

[0347] Step 10:

[0348] The device receives final suggestions from the server and visually presents the user with information on fashion, makeup, and accessories. The user can use this information to make the best choice without stress.

[0349] (Example 2)

[0350] 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".

[0351] In fashion and makeup choices, there is a challenge in providing personalized suggestions that appropriately reflect the user's physical characteristics and emotional state. Furthermore, providing optimal styling for different situations requires the flexible use of user input information.

[0352] 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.

[0353] In this invention, the server includes means for acquiring data about the user's body, means for acquiring product data from multiple sites based on the diagnostic results, and means for recognizing the user's emotions and making emotional adjustments to the suggested products and information about cosmetics. This makes it possible to suggest personalized fashion and makeup based on the user's physical characteristics and emotional state.

[0354] A "user" is someone who uses the system to receive fashion and makeup suggestions based on their own physical information and emotional state.

[0355] "Physical data" refers to information such as the user's height, body type, skin color, and hair color, which serves as the basis for providing personalized suggestions.

[0356] "Skeletal characteristics" are features diagnosed based on the user's body type and skeletal structure, and are a factor that helps in fashion choices.

[0357] "Color characteristics" refer to the color type derived from the user's skin tone, eye color, hair color, etc., and are elements that serve as a basis for styling.

[0358] "Product data" refers to information about purchasable fashion items, and is a collection of information obtained from multiple websites.

[0359] "Information about cosmetics" refers to information about cosmetics and makeup techniques suggested to users.

[0360] "Emotional state" refers to the user's feelings and is an element recognized by the system.

[0361] "Emotional adjustment" refers to the process of responding to suggested fashion and makeup based on the user's perceived emotions.

[0362] This system consists of three elements: user, server, and terminal, and each element works together to provide the user with the most suitable fashion and makeup suggestions.

[0363] First, users input data about their bodies using a device. Common devices such as smartphones and tablets are used, and users input data through a dedicated application or web interface. This data includes height, body type, skin color, and hair color.

[0364] Next, the terminal sends the input data to the server, which uses this data to activate a generative AI model. The generative AI model is a tool for diagnosing the user's skeletal and color characteristics, analyzing the input numerical data and forming prompt sentences. These prompt sentences might be something like, "Diagnose the user's skeletal characteristics and color type, and suggest fashion and makeup that emphasizes relaxation."

[0365] Subsequently, the server retrieves product data from multiple online marketplaces based on the diagnostic results. The APIs used here are standard ones for retrieving general product information. The retrieved data is filtered by a generative AI model to select items suitable for the user.

[0366] Furthermore, the device uses built-in sensors to read the user's emotional state from their facial expressions and voice. This emotional information is sent to a server and analyzed by AI.

[0367] The server makes emotional adjustments to the product and cosmetic information it suggests based on the perceived emotional state. For example, if the user wants to relax, items with calming colors and materials will be selected.

[0368] Finally, the processed suggestions are visualized on the device, allowing the user to view the suggestions and choose whether or not to purchase their preferred items. A concrete example of how the system can be used is that by receiving suggestions tailored to the user's situation, users can quickly choose the optimal fashion and makeup.

[0369] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0370] Step 1:

[0371] The user uses a device to input data about their body (e.g., height, body type, skin color). The device then sends this input data to the server. Specifically, the user enters information into an application form and presses the submit button. The data entered represents the individual's physical characteristics.

[0372] Step 2:

[0373] The server supplies the received data to a generating AI model to diagnose the user's skeletal and color characteristics. Specifically, the AI ​​model analyzes the input data and generates prompt sentences. The output at this stage is a diagnostic result summarizing the user's characteristics.

[0374] Step 3:

[0375] The server calls APIs from multiple online marketplaces based on the diagnostic results to retrieve product data. The input is the diagnostic results, and the output is a list of product information suitable for the user. Specifically, the server queries the database of each marketplace via the APIs.

[0376] Step 4:

[0377] The device uses sensors to capture the user's facial expressions and voice, and analyzes their emotional state. This data is sent to a server. Specifically, the camera and microphone on the device capture data in real time and pass it to an analysis program. The output is data indicating the user's emotional state.

[0378] Step 5:

[0379] The server combines acquired product information with emotional states to make emotional adjustments to the suggestions. Specifically, the AI ​​prioritizes colors and styles that match the user's mood. The input is a product list and emotional data, and the output is adjusted fashion and makeup suggestions.

[0380] Step 6:

[0381] The device displays the adjusted suggestions to the user in a visual format. The user then uses this to make a purchase decision. Specifically, the device displays the suggestions on the screen using graphics and text, and provides a purchase link. The output is visual suggestion content for the user.

[0382] (Application Example 2)

[0383] 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."

[0384] Modern consumers tend to seek personalized fashion and makeup, but existing systems do not adequately consider the user's physical information and emotions when making suggestions. Furthermore, users cannot receive personalized suggestions tailored to their current emotions or specific situations, making it difficult for them to determine what fashion and makeup are appropriate.

[0385] 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.

[0386] In this invention, the server includes means for acquiring the user's physical information and diagnosing their skeletal type and color type, means for acquiring and filtering product information based on the diagnosis results, and means for analyzing the user's emotions using a data acquisition device and reflecting that information in the suggestions. This enables personalized suggestions based on the user's physical and emotional state.

[0387] "User body information" refers to individual information necessary for fashion and makeup suggestions, such as the user's body type and skin tone.

[0388] "Body type and color type diagnosis" is a classification process that analyzes the user's acquired physical information to determine the most suitable fashion and makeup.

[0389] "Means of acquiring product information" refers to technology that collects information on relevant fashion items and cosmetics from purchasing websites based on the diagnostic results.

[0390] "Methods for filtering product information" refers to the process of narrowing down acquired product information to only those that match the user's individual diagnostic results.

[0391] A "means of suggesting cosmetic information" refers to a system that recommends suitable cosmetics and makeup methods to the user based on the selected product.

[0392] A "data acquisition device" is an electronic device used to receive input from the user and plays the role of collecting information.

[0393] "Methods for analyzing emotions" refers to technologies that determine emotions from input such as user voices and reflect the results in the proposed content.

[0394] The system that realizes this invention operates via a user-owned device and a server. The user's device scans the user's physical information using data acquisition devices such as a camera and acquires voice tone and emotions using a microphone. This acquired data is transmitted to the server.

[0395] The server analyzes the received physical information to diagnose the user's skeletal type and color type. OpenCV and NumPy are used for image data processing and numerical analysis during the diagnosis. Additionally, the Google Speech-to-Text API is used to analyze the user's emotions from their voice and generate emotion-based advice.

[0396] Subsequently, the server uses the purchasing site's API to retrieve information on relevant fashion items and cosmetics based on the diagnostic results. This information is filtered according to the user's diagnostic results and sentiment analysis. This allows the system to suggest the most suitable fashion and makeup combinations for the user.

[0397] Users can visually review these suggestions on their device and make specific makeup and clothing choices through voice feedback. Through this process, users can easily choose styles that suit their mood or specific occasion, making their daily clothing and makeup decisions more personalized.

[0398] For example, if a user feels like "I want to feel energetic today," the server will suggest brightly colored clothing and makeup that gives an energetic impression. Examples of prompts for the generative AI model include the following:

[0399] "The user desires an energetic image, has a slim build, and prefers autumn colors. Please suggest the most suitable fashion and makeup."

[0400] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0401] Step 1:

[0402] The user uses a device to acquire their own physical information and voice through the camera and microphone. The camera captures the user's body shape and color, and the microphone records the tone of their voice. These inputs are sent to the server. The output is the user's physical information and voice data.

[0403] Step 2:

[0404] The server uses OpenCV and NumPy with the received physical information to diagnose the user's skeletal type and color type. The data is processed through image processing and numerical analysis, and a diagnostic result is output that forms the basis of the user's fashion style.

[0405] Step 3:

[0406] The server uses the Google Speech-to-Text API to analyze the user's emotions from their voice. It converts the audio data into text and analyzes it using an emotion recognition algorithm to output the user's current emotional state.

[0407] Step 4:

[0408] The server retrieves relevant product information via the purchasing site's API based on the diagnostic results and emotional state. It processes the product information according to pre-configured filtering criteria based on the input data and outputs information on the items most suitable for the user.

[0409] Step 5:

[0410] The server uses a generative AI model to suggest makeup information based on the obtained product information. By generating prompt messages and inputting them into the AI ​​model, it outputs customized makeup suggestions for the user.

[0411] Step 6:

[0412] The user's device visualizes fashion and makeup suggestions received from the server. Information is displayed on the device's screen, and advice is provided as voice feedback. This allows the user to gain concrete options regarding their own style.

[0413] 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.

[0414] 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.

[0415] 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.

[0416] [Third Embodiment]

[0417] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0418] 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.

[0419] 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).

[0420] 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.

[0421] 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.

[0422] 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).

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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".

[0429] This invention is a system that acquires a user's physical information and proposes individually optimized fashion and makeup based on that information. This system is operated in cooperation with the user, server, and terminal.

[0430] First, the user inputs their physical information through the terminal's user interface. Specifically, this includes body type, skin color, and hair color. This information is sent to a server, which then uses it to diagnose the user's skeletal type and color type. The diagnosis uses existing algorithms and databases to accurately determine the user's characteristics.

[0431] After obtaining the diagnostic results, the server retrieves product information through APIs of multiple shopping sites specified by the user. This product information includes clothing, accessories, and other fashion items. Based on the user's diagnostic results, the server filters the retrieved products and selects the one that is most suitable for the user.

[0432] Based on the selected fashion items, the server suggests cosmetics and makeup techniques to the user. These suggestions are designed to harmonize with the style and color of the chosen clothing. Specific manufacturers, product names, and usage instructions are retrieved from the database and transmitted to the terminal as information.

[0433] Furthermore, depending on the context the user enters, the server can offer additional suggestions regarding styling and accessories. This enables the creation of a comprehensive fashion and makeup coordinated look that is best suited to a specific occasion.

[0434] Finally, the terminal displays the information sent from the server to the user in a highly visualized format. This allows the user to review the details of the selected items and decide whether to purchase or use them as needed. This entire process enables the user to quickly find the styling that best suits them.

[0435] The following describes the processing flow.

[0436] Step 1:

[0437] The user enters their physical information using the terminal's interface. This includes data such as body type, skin color, and hair color, which are entered into a form.

[0438] Step 2:

[0439] The terminal transmits the entered physical information to the server. This data forms the basis for the diagnostic process.

[0440] Step 3:

[0441] The server uses the received physical information to diagnose skeletal type and color type. This is done by applying a pre-programmed diagnostic algorithm.

[0442] Step 4:

[0443] Based on the diagnostic results, the server retrieves product information using the purchasing site's API. Here, it collects data on fashion items from the online shop specified by the user.

[0444] Step 5:

[0445] The server filters the retrieved product information based on the diagnostic results, selecting products that match the user's bone structure and color preferences.

[0446] Step 6:

[0447] The server searches the database for cosmetic information related to the selected fashion items and generates makeup suggestions suitable for the user.

[0448] Step 7:

[0449] The user inputs specific situations (work, leisure, date, etc.) through their device. This information is sent to the server.

[0450] Step 8:

[0451] The server optimizes styling by suggesting accessories and adjusting makeup based on the input scene.

[0452] Step 9:

[0453] The device receives information from the server and displays recommended fashion, makeup, and accessory information on the user interface.

[0454] (Example 1)

[0455] 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."

[0456] To meet the diverse needs of today's consumers, it is crucial to suggest appropriate fashion and beauty items based on each individual's physical characteristics. However, many current systems do not adequately select products according to each user's physical characteristics, and the lack of automation often limits the available options. Furthermore, efficiently obtaining appropriate product information from different e-commerce platforms is difficult. As a result, the process of providing personalized services is cumbersome, and it is challenging to help users make the best choices.

[0457] 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.

[0458] In this invention, the server includes a device for collecting the user's physical characteristics, a device for diagnosing the structural type and hue type based on the collected physical characteristics, and a device for acquiring product information from multiple e-commerce platforms based on the diagnosis results. This makes it possible to efficiently suggest products and related beauty information optimized for the user's individual characteristics.

[0459] "User physical characteristics" refer to the user's physical or physiological features, such as body type, skin color, and hair color.

[0460] A "data collection device" is a device that uses a user interface or camera to acquire the user's physical characteristics and transmit the necessary information to a server.

[0461] A "device for diagnosing structural type and hue type" is a system that uses AI and algorithms to analyze the user's physical characteristics to determine their skeletal type and skin color, and then outputs the results.

[0462] A "device for acquiring product information" is a component that has interfaces with multiple e-commerce platforms and uses APIs, etc., to collect product data.

[0463] A "device for selecting and determining suitable products for users" is a system equipped with the function of filtering product information collected based on diagnostic results and selecting the most suitable product for the user.

[0464] "Beauty information" refers to information related to cosmetics and makeup techniques that complement or enhance a user's appearance.

[0465] A "display device" is a device that shows the suggested results on the terminal screen so that the user can visually confirm the information on the spot.

[0466] This invention is a system that provides recommendations for fashion and beauty items customized based on the user's physical characteristics. This system involves the cooperation of the user, a terminal, and a server. The following describes specific embodiments for carrying out the invention.

[0467] First, the user inputs their physical characteristics using a device. The device utilizes its camera function to take a photo of the user's face, and then uses AI technology to automatically recognize the user's skin tone. As a result, the user can easily input information such as body type and hair color. The device collects this information and transmits it to a server via a communication network.

[0468] The server uses machine learning algorithms implemented in Python or R to diagnose the user's skeletal type and color type based on their physical characteristics. For this purpose, it utilizes a pre-collected and analyzed database. This diagnosis is processed in real time by a specific algorithm.

[0469] Once the diagnostic results are obtained, the server retrieves product information using APIs from multiple e-commerce platforms. This includes common e-commerce sites. The server filters the retrieved information against the diagnostic results to identify the product best suited to the user.

[0470] Next, the server suggests beauty information related to the selected product. This information is obtained from a database and includes cosmetic ingredient information and application methods. This information is tailored to the user's physical characteristics and provides detailed instructions on optimal usage.

[0471] Finally, the device displays this data to the user. This display utilizes AR technology and 3D rendering, allowing the user to interactively review the suggested styles. The user can then choose to purchase the suggested items as needed.

[0472] As a concrete example, suppose a user inputs physical characteristics such as "slim build, light-toned skin, dark brown hair" and selects "business casual." In this case, the server automatically selects relevant fashion items and beauty products and displays them on the device. Furthermore, the following prompts can be entered into the generating AI model.

[0473] "The user has a slim build, light skin tone, and dark brown hair. Please suggest the optimal combination of fashion and makeup for a business setting."

[0474] In this way, users can quickly receive personalized fashion and beauty advice.

[0475] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0476] Step 1:

[0477] Users input their physical characteristics through the device's user interface. Specifically, users take a photo of their face using the device's camera and manually or automatically record features such as body shape, skin color, and hair color. This input data is directly stored on the device and temporarily prepared for analysis.

[0478] Step 2:

[0479] The terminal sends the entered physical characteristics data to the server. Once the user's data reaches the server, the server analyzes the data and compares it with past data in the database. In this process, machine learning algorithms are used to diagnose the user's skeletal type and color type by comparing it with the information in the database. Based on this input data, a diagnosis result specific to the user is output.

[0480] Step 3:

[0481] The server retrieves product information through APIs of multiple e-commerce platforms based on the diagnostic results. The server uses the diagnostic results as filtering criteria to select the product information. The data processing performed here is to select the most suitable product based on the diagnosis. This process matches the list of products to the user's physical characteristics, and the selected product information is output.

[0482] Step 4:

[0483] The server retrieves beauty information from the database that matches the selected product, and further adjusts this information based on the user's characteristics. The generated beauty information is then sent from the server to the terminal. Data processing includes selecting cosmetics that match the user's skin tone and fashion style. As a result, beauty information is output.

[0484] Step 5:

[0485] The terminal visually displays product and beauty information received from the server to the user. Using AR technology and 3D rendering, the terminal allows the user to intuitively confirm suggested styles. In this data display process, information is output in a format that the user can actually see and select.

[0486] (Application Example 1)

[0487] 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."

[0488] Modern consumers have a need to quickly and accurately obtain fashion and beauty information that suits their physical characteristics. However, the amount of product information available online and in physical stores is vast, making it time-consuming and laborious to make the best individual choices. Furthermore, there is a lack of opportunities to actually experience the suggested items and beauty methods firsthand.

[0489] 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.

[0490] In this invention, the server includes means for acquiring the user's physical information, means for diagnosing the skeletal type and color type based on the acquired physical information, means for acquiring product information from multiple information provision platforms based on the diagnosis results, means for filtering the acquired product information based on the diagnosis results to select products suitable for the user, means for suggesting beauty information associated with the selected products, means for displaying the suggested beauty information and product information, and means for experiencing the suggested products and beauty methods in a physical store. This enables consumers to efficiently and effectively acquire individually optimized fashion and beauty information and to actually experience it on the spot.

[0491] "User body information" refers to data on personal characteristics necessary for optimizing fashion and beauty, such as an individual's body shape, skin color, and hair color.

[0492] "Skeletal type" refers to information that indicates the structural characteristics of the body, classified based on the user's body shape.

[0493] "Color type" refers to information that describes the characteristics of color tones, classified based on factors such as the user's skin and hair color.

[0494] An "information provision platform" is a digital system that provides users with information about products and services online.

[0495] "Product information" refers to detailed data related to fashion items such as clothing and accessories.

[0496] "Beauty information" refers to detailed data about specific cosmetics or beauty techniques, which is used to improve the user's appearance.

[0497] "Filtering" is an information processing technique that selects the best option from multiple choices based on specific conditions.

[0498] "Means of experiencing in a physical store" refers to means that enable customers to actually use or try out the proposed product or method in a physical store.

[0499] The system for implementing this invention acquires the user's physical information and optimizes fashion and beauty based on that information. The system's foundation consists of computer terminals, including smartphones, a central server, and interactive display devices within physical stores.

[0500] The server receives physical information entered by the user through the terminal. This input data includes body type, skin color, and hair color. Based on this information, the server uses internal algorithms and a database to diagnose the user's skeletal type and color type. This allows for a precise analysis of the user's characteristics and guides them towards the most suitable fashion and beauty choices.

[0501] Next, the server uses multiple information provision platform APIs to collect product information based on the diagnostic results. This allows it to import and filter data for suitable products. The filtered product information is then selected as the optimal item linked to the user's physical characteristics. Furthermore, relevant beauty information is also suggested, including specific instructions on how to use cosmetics and detailed beauty methods.

[0502] The terminal visually presents information provided by the server to the user. Users can view and experience suggested products and beauty information on their smartphones or displays in physical stores. For example, in certain fitting rooms, users can actually try on clothes suggested by the AI ​​system and immediately see the effect. An example of a prompt message is, "If the user has a slim build, olive skin tone, and black hair, what fashion items and makeup would be best suited for them?"

[0503] The specific hardware used includes, for example, smartphones running iOS or Android OS, and interactive displays such as large screens for displaying information in physical stores. The software consists of a mobile application using React Native, Node.js as the backend service, and Firebase for data management. These elements work together organically to provide users with a continuous and personalized experience.

[0504] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0505] Step 1:

[0506] The user uses their smartphone to enter physical information into the application on the device. This information includes body type, skin color, hair color, etc. This data is then sent from the device to the server.

[0507] Step 2:

[0508] The server uses an internal algorithm to diagnose the user's skeletal type and color type based on the received physical information. This process compares the input data with an existing database and analyzes the user's characteristics. As a result, it generates data for the diagnosed skeletal type and color type.

[0509] Step 3:

[0510] Based on the diagnostic results, the server retrieves product information using multiple information provision platform APIs. The input data here is the diagnostic results, and the output is a list of retrieved products. By accessing the information provision platform APIs in real time, the range of product options tailored to the user's characteristics expands.

[0511] Step 4:

[0512] The server filters the retrieved product information and selects products suitable for the user. This process executes a specific filtering algorithm to extract product attributes that match the diagnostic results. As a result of this filtering, an optimal product list is generated.

[0513] Step 5:

[0514] The server generates beauty information associated with the selected product. This beauty information includes appropriate makeup techniques and cosmetic usage methods tailored to the suggested fashion. This generation process combines information by referencing product characteristics and related beauty databases. As a result, a list of beauty information is generated.

[0515] Step 6:

[0516] The terminal displays a list of optimal products and beauty information received from the server to the user. Here, information is presented through a visual interface, allowing the user to visually confirm the content. Input is information from the server, and output is as visual data that the user can confirm.

[0517] Step 7:

[0518] Based on the displayed information, users try on products and experience beauty techniques using interactive displays in physical stores. During this process, the display provides feedback on products relevant to the user's selections, and they then try them on and use them. Finally, the user evaluates the experience and can choose to purchase the products on the spot.

[0519] 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.

[0520] This invention is a system that proposes personalized fashion and makeup based on the user's physical information, and further makes more appropriate suggestions by recognizing the user's emotions using an emotion engine. This system is implemented via the user, server, and terminal.

[0521] Users input physical information about their body type and color preferences using a terminal. The server then diagnoses their skeletal type and color type. This diagnostic information is essential for providing fashion and makeup suggestions.

[0522] The server uses the diagnostic results to retrieve information on fashion items through the purchasing site's API. The retrieved product information is filtered to narrow down to items that match the user's diagnostic results. In addition, an emotion engine recognizes the user's emotions and makes emotional adjustments to the suggested items and related information. For example, if the user is feeling relaxed, items in calming colors and soft materials will be recommended.

[0523] Furthermore, the server suggests cosmetics and makeup techniques that match the color and style of the selected product. Based on the results of the emotion engine's recognition, the suggested makeup is also adjusted to suit the user's mood. For example, if the user desires an energetic impression, bright and vibrant makeup tones will be recommended.

[0524] Users can input specific scenarios through their devices, and the server combines this information with the results of an emotion engine analysis to further optimize styling suggestions for those specific scenarios. This makes it easy for users to choose fashion and makeup that suits a particular situation.

[0525] All of these features are presented in a visualized form on the device, allowing users to review suggestions and easily purchase or utilize them. This process enables users to find the style that best suits their mood and purpose for the day.

[0526] The following describes the processing flow.

[0527] Step 1:

[0528] Users enter their physical information using the terminal's interface. This information includes body type, skin tone, and hair color, which they fill out on a form.

[0529] Step 2:

[0530] The terminal sends the entered physical information to the server. The server receives this data and uses it for diagnosis in the next step.

[0531] Step 3:

[0532] The server uses the received physical information to diagnose the skeletal type and color type. The algorithm analyzes the physical characteristics and determines the user's skeletal characteristics and personal color.

[0533] Step 4:

[0534] Based on the diagnostic results, the server accesses APIs from multiple shopping sites to retrieve product information. The items retrieved include clothing and accessories, and include current fashion data.

[0535] Step 5:

[0536] Based on the diagnostic results, the server filters the acquired product information to select products suitable for the user. The selection criteria include the degree of match with the diagnostic results, such as shape, color, and material.

[0537] Step 6:

[0538] When a user inputs or records their emotions using the device's camera and microphone, the device sends that information to a server. The server uses an emotion engine to analyze this information and determine the user's emotional state.

[0539] Step 7:

[0540] The server adjusts filtered fashion item and cosmetic item suggestions based on the results of the emotion engine's analysis. For example, when a user is feeling down, it suggests brightly colored items and uplifting makeup.

[0541] Step 8:

[0542] The user enters the specific occasion for which they want to go out (business, casual, date, etc.) via their device. This information is sent to the server.

[0543] Step 9:

[0544] The server combines scene information and sentiment analysis to suggest accessories and additional styling elements that are appropriate for the specific scene.

[0545] Step 10:

[0546] The device receives final suggestions from the server and visually presents the user with information on fashion, makeup, and accessories. The user can use this information to make the best choice without stress.

[0547] (Example 2)

[0548] 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."

[0549] In fashion and makeup choices, there is a challenge in providing personalized suggestions that appropriately reflect the user's physical characteristics and emotional state. Furthermore, providing optimal styling for different situations requires the flexible use of user input information.

[0550] 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.

[0551] In this invention, the server includes means for acquiring data about the user's body, means for acquiring product data from multiple sites based on the diagnostic results, and means for recognizing the user's emotions and making emotional adjustments to the suggested products and information about cosmetics. This makes it possible to suggest personalized fashion and makeup based on the user's physical characteristics and emotional state.

[0552] A "user" is someone who uses the system to receive fashion and makeup suggestions based on their own physical information and emotional state.

[0553] "Physical data" refers to information such as the user's height, body type, skin color, and hair color, which serves as the basis for providing personalized suggestions.

[0554] "Skeletal characteristics" are features diagnosed based on the user's body type and skeletal structure, and are a factor that helps in fashion choices.

[0555] "Color characteristics" refer to the color type derived from the user's skin tone, eye color, hair color, etc., and are elements that serve as a basis for styling.

[0556] "Product data" refers to information about purchasable fashion items, and is a collection of information obtained from multiple websites.

[0557] "Information about cosmetics" refers to information about cosmetics and makeup techniques suggested to users.

[0558] "Emotional state" refers to the user's feelings and is an element recognized by the system.

[0559] "Emotional adjustment" refers to the process of responding to suggested fashion and makeup based on the user's perceived emotions.

[0560] This system consists of three elements: user, server, and terminal, and each element works together to provide the user with the most suitable fashion and makeup suggestions.

[0561] First, users input data about their bodies using a device. Common devices such as smartphones and tablets are used, and users input data through a dedicated application or web interface. This data includes height, body type, skin color, and hair color.

[0562] Next, the terminal sends the input data to the server, which uses this data to activate a generative AI model. The generative AI model is a tool for diagnosing the user's skeletal and color characteristics, analyzing the input numerical data and forming prompt sentences. These prompt sentences might be something like, "Diagnose the user's skeletal characteristics and color type, and suggest fashion and makeup that emphasizes relaxation."

[0563] Subsequently, the server retrieves product data from multiple online marketplaces based on the diagnostic results. The APIs used here are standard ones for retrieving general product information. The retrieved data is filtered by a generative AI model to select items suitable for the user.

[0564] Furthermore, the device uses built-in sensors to read the user's emotional state from their facial expressions and voice. This emotional information is sent to a server and analyzed by AI.

[0565] The server makes emotional adjustments to the product and cosmetic information it suggests based on the perceived emotional state. For example, if the user wants to relax, items with calming colors and materials will be selected.

[0566] Finally, the processed suggestions are visualized on the device, allowing the user to view the suggestions and choose whether or not to purchase their preferred items. A concrete example of how the system can be used is that by receiving suggestions tailored to the user's situation, users can quickly choose the optimal fashion and makeup.

[0567] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0568] Step 1:

[0569] The user uses a device to input data about their body (e.g., height, body type, skin color). The device then sends this input data to the server. Specifically, the user enters information into an application form and presses the submit button. The data entered represents the individual's physical characteristics.

[0570] Step 2:

[0571] The server supplies the received data to a generating AI model to diagnose the user's skeletal and color characteristics. Specifically, the AI ​​model analyzes the input data and generates prompt sentences. The output at this stage is a diagnostic result summarizing the user's characteristics.

[0572] Step 3:

[0573] The server calls APIs from multiple online marketplaces based on the diagnostic results to retrieve product data. The input is the diagnostic results, and the output is a list of product information suitable for the user. Specifically, the server queries the database of each marketplace via the APIs.

[0574] Step 4:

[0575] The device uses sensors to capture the user's facial expressions and voice, and analyzes their emotional state. This data is sent to a server. Specifically, the camera and microphone on the device capture data in real time and pass it to an analysis program. The output is data indicating the user's emotional state.

[0576] Step 5:

[0577] The server combines acquired product information with emotional states to make emotional adjustments to the suggestions. Specifically, the AI ​​prioritizes colors and styles that match the user's mood. The input is a product list and emotional data, and the output is adjusted fashion and makeup suggestions.

[0578] Step 6:

[0579] The device displays the adjusted suggestions to the user in a visual format. The user then uses this to make a purchase decision. Specifically, the device displays the suggestions on the screen using graphics and text, and provides a purchase link. The output is visual suggestion content for the user.

[0580] (Application Example 2)

[0581] 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."

[0582] Modern consumers tend to seek personalized fashion and makeup, but existing systems do not adequately consider the user's physical information and emotions when making suggestions. Furthermore, users cannot receive personalized suggestions tailored to their current emotions or specific situations, making it difficult for them to determine what fashion and makeup are appropriate.

[0583] 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.

[0584] In this invention, the server includes means for acquiring the user's physical information and diagnosing their skeletal type and color type, means for acquiring and filtering product information based on the diagnosis results, and means for analyzing the user's emotions using a data acquisition device and reflecting that information in the suggestions. This enables personalized suggestions based on the user's physical and emotional state.

[0585] "User body information" refers to individual information necessary for fashion and makeup suggestions, such as the user's body type and skin tone.

[0586] "Body type and color type diagnosis" is a classification process that analyzes the user's acquired physical information to determine the most suitable fashion and makeup.

[0587] "Means of acquiring product information" refers to technology that collects information on relevant fashion items and cosmetics from purchasing websites based on the diagnostic results.

[0588] "Methods for filtering product information" refers to the process of narrowing down acquired product information to only those that match the user's individual diagnostic results.

[0589] A "means of suggesting cosmetic information" refers to a system that recommends suitable cosmetics and makeup methods to the user based on the selected product.

[0590] A "data acquisition device" is an electronic device used to receive input from the user and plays the role of collecting information.

[0591] "Methods for analyzing emotions" refers to technologies that determine emotions from input such as user voices and reflect the results in the proposed content.

[0592] The system that realizes this invention operates via a user-owned device and a server. The user's device scans the user's physical information using data acquisition devices such as a camera and acquires voice tone and emotions using a microphone. This acquired data is transmitted to the server.

[0593] The server analyzes the received physical information to diagnose the user's skeletal type and color type. OpenCV and NumPy are used for image data processing and numerical analysis during the diagnosis. Additionally, the Google Speech-to-Text API is used to analyze the user's emotions from their voice and generate emotion-based advice.

[0594] Subsequently, the server uses the purchasing site's API to retrieve information on relevant fashion items and cosmetics based on the diagnostic results. This information is filtered according to the user's diagnostic results and sentiment analysis. This allows the system to suggest the most suitable fashion and makeup combinations for the user.

[0595] Users can visually review these suggestions on their device and make specific makeup and clothing choices through voice feedback. Through this process, users can easily choose styles that suit their mood or specific occasion, making their daily clothing and makeup decisions more personalized.

[0596] For example, if a user feels like "I want to feel energetic today," the server will suggest brightly colored clothing and makeup that gives an energetic impression. Examples of prompts for the generative AI model include the following:

[0597] "The user desires an energetic image, has a slim build, and prefers autumn colors. Please suggest the most suitable fashion and makeup."

[0598] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0599] Step 1:

[0600] The user uses a device to acquire their own physical information and voice through the camera and microphone. The camera captures the user's body shape and color, and the microphone records the tone of their voice. These inputs are sent to the server. The output is the user's physical information and voice data.

[0601] Step 2:

[0602] The server uses OpenCV and NumPy with the received physical information to diagnose the user's skeletal type and color type. The data is processed through image processing and numerical analysis, and a diagnostic result is output that forms the basis of the user's fashion style.

[0603] Step 3:

[0604] The server uses the Google Speech-to-Text API to analyze the user's emotions from their voice. It converts the audio data into text and analyzes it using an emotion recognition algorithm to output the user's current emotional state.

[0605] Step 4:

[0606] The server retrieves relevant product information via the purchasing site's API based on the diagnostic results and emotional state. It processes the product information according to pre-configured filtering criteria based on the input data and outputs information on the items most suitable for the user.

[0607] Step 5:

[0608] The server uses a generative AI model to suggest makeup information based on the obtained product information. By generating prompt messages and inputting them into the AI ​​model, it outputs customized makeup suggestions for the user.

[0609] Step 6:

[0610] The user's device visualizes fashion and makeup suggestions received from the server. Information is displayed on the device's screen, and advice is provided as voice feedback. This allows the user to gain concrete options regarding their own style.

[0611] 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.

[0612] 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.

[0613] 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.

[0614] [Fourth Embodiment]

[0615] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0616] 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.

[0617] 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).

[0618] 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.

[0619] 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.

[0620] 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).

[0621] 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.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] 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.

[0627] 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".

[0628] This invention is a system that acquires a user's physical information and proposes individually optimized fashion and makeup based on that information. This system is operated in cooperation with the user, server, and terminal.

[0629] First, the user inputs their physical information through the terminal's user interface. Specifically, this includes body type, skin color, and hair color. This information is sent to a server, which then uses it to diagnose the user's skeletal type and color type. The diagnosis uses existing algorithms and databases to accurately determine the user's characteristics.

[0630] After obtaining the diagnostic results, the server retrieves product information through APIs of multiple shopping sites specified by the user. This product information includes clothing, accessories, and other fashion items. Based on the user's diagnostic results, the server filters the retrieved products and selects the one that is most suitable for the user.

[0631] Based on the selected fashion items, the server suggests cosmetics and makeup techniques to the user. These suggestions are designed to harmonize with the style and color of the chosen clothing. Specific manufacturers, product names, and usage instructions are retrieved from the database and transmitted to the terminal as information.

[0632] Furthermore, depending on the context the user enters, the server can offer additional suggestions regarding styling and accessories. This enables the creation of a comprehensive fashion and makeup coordinated look that is best suited to a specific occasion.

[0633] Finally, the terminal displays the information sent from the server to the user in a highly visualized format. This allows the user to review the details of the selected items and decide whether to purchase or use them as needed. This entire process enables the user to quickly find the styling that best suits them.

[0634] The following describes the processing flow.

[0635] Step 1:

[0636] The user enters their physical information using the terminal's interface. This includes data such as body type, skin color, and hair color, which are entered into a form.

[0637] Step 2:

[0638] The terminal transmits the entered physical information to the server. This data forms the basis for the diagnostic process.

[0639] Step 3:

[0640] The server uses the received physical information to diagnose skeletal type and color type. This is done by applying a pre-programmed diagnostic algorithm.

[0641] Step 4:

[0642] Based on the diagnostic results, the server retrieves product information using the purchasing site's API. Here, it collects data on fashion items from the online shop specified by the user.

[0643] Step 5:

[0644] The server filters the retrieved product information based on the diagnostic results, selecting products that match the user's bone structure and color preferences.

[0645] Step 6:

[0646] The server searches the database for cosmetic information related to the selected fashion items and generates makeup suggestions suitable for the user.

[0647] Step 7:

[0648] The user inputs specific situations (work, leisure, date, etc.) through their device. This information is sent to the server.

[0649] Step 8:

[0650] The server optimizes styling by suggesting accessories and adjusting makeup based on the input scene.

[0651] Step 9:

[0652] The device receives information from the server and displays recommended fashion, makeup, and accessory information on the user interface.

[0653] (Example 1)

[0654] 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".

[0655] To meet the diverse needs of today's consumers, it is crucial to suggest appropriate fashion and beauty items based on each individual's physical characteristics. However, many current systems do not adequately select products according to each user's physical characteristics, and the lack of automation often limits the available options. Furthermore, efficiently obtaining appropriate product information from different e-commerce platforms is difficult. As a result, the process of providing personalized services is cumbersome, and it is challenging to help users make the best choices.

[0656] 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.

[0657] In this invention, the server includes a device for collecting the user's physical characteristics, a device for diagnosing the structural type and hue type based on the collected physical characteristics, and a device for acquiring product information from multiple e-commerce platforms based on the diagnosis results. This makes it possible to efficiently suggest products and related beauty information optimized for the user's individual characteristics.

[0658] "User physical characteristics" refer to the user's physical or physiological features, such as body type, skin color, and hair color.

[0659] A "data collection device" is a device that uses a user interface or camera to acquire the user's physical characteristics and transmit the necessary information to a server.

[0660] A "device for diagnosing structural type and hue type" is a system that uses AI and algorithms to analyze the user's physical characteristics to determine their skeletal type and skin color, and then outputs the results.

[0661] A "device for acquiring product information" is a component that has interfaces with multiple e-commerce platforms and uses APIs, etc., to collect product data.

[0662] A "device for selecting and determining suitable products for users" is a system equipped with the function of filtering product information collected based on diagnostic results and selecting the most suitable product for the user.

[0663] "Beauty information" refers to information related to cosmetics and makeup techniques that complement or enhance a user's appearance.

[0664] A "display device" is a device that shows the suggested results on the terminal screen so that the user can visually confirm the information on the spot.

[0665] This invention is a system that provides recommendations for fashion and beauty items customized based on the user's physical characteristics. This system involves the cooperation of the user, a terminal, and a server. The following describes specific embodiments for carrying out the invention.

[0666] First, the user inputs their physical characteristics using a device. The device utilizes its camera function to take a photo of the user's face, and then uses AI technology to automatically recognize the user's skin tone. As a result, the user can easily input information such as body type and hair color. The device collects this information and transmits it to a server via a communication network.

[0667] The server uses machine learning algorithms implemented in Python or R to diagnose the user's skeletal type and color type based on their physical characteristics. For this purpose, it utilizes a pre-collected and analyzed database. This diagnosis is processed in real time by a specific algorithm.

[0668] Once the diagnostic results are obtained, the server retrieves product information using APIs from multiple e-commerce platforms. This includes common e-commerce sites. The server filters the retrieved information against the diagnostic results to identify the product best suited to the user.

[0669] Next, the server suggests beauty information related to the selected product. This information is obtained from a database and includes cosmetic ingredient information and application methods. This information is tailored to the user's physical characteristics and provides detailed instructions on optimal usage.

[0670] Finally, the device displays this data to the user. This display utilizes AR technology and 3D rendering, allowing the user to interactively review the suggested styles. The user can then choose to purchase the suggested items as needed.

[0671] As a concrete example, suppose a user inputs physical characteristics such as "slim build, light-toned skin, dark brown hair" and selects "business casual." In this case, the server automatically selects relevant fashion items and beauty products and displays them on the device. Furthermore, the following prompts can be entered into the generating AI model.

[0672] "The user has a slim build, light skin tone, and dark brown hair. Please suggest the optimal combination of fashion and makeup for a business setting."

[0673] In this way, users can quickly receive personalized fashion and beauty advice.

[0674] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0675] Step 1:

[0676] Users input their physical characteristics through the device's user interface. Specifically, users take a photo of their face using the device's camera and manually or automatically record features such as body shape, skin color, and hair color. This input data is directly stored on the device and temporarily prepared for analysis.

[0677] Step 2:

[0678] The terminal sends the entered physical characteristics data to the server. Once the user's data reaches the server, the server analyzes the data and compares it with past data in the database. In this process, machine learning algorithms are used to diagnose the user's skeletal type and color type by comparing it with the information in the database. Based on this input data, a diagnosis result specific to the user is output.

[0679] Step 3:

[0680] The server retrieves product information through APIs of multiple e-commerce platforms based on the diagnostic results. The server uses the diagnostic results as filtering criteria to select the product information. The data processing performed here is to select the most suitable product based on the diagnosis. This process matches the list of products to the user's physical characteristics, and the selected product information is output.

[0681] Step 4:

[0682] The server retrieves beauty information from the database that matches the selected product, and further adjusts this information based on the user's characteristics. The generated beauty information is then sent from the server to the terminal. Data processing includes selecting cosmetics that match the user's skin tone and fashion style. As a result, beauty information is output.

[0683] Step 5:

[0684] The terminal visually displays product and beauty information received from the server to the user. Using AR technology and 3D rendering, the terminal allows the user to intuitively confirm suggested styles. In this data display process, information is output in a format that the user can actually see and select.

[0685] (Application Example 1)

[0686] 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".

[0687] Modern consumers have a need to quickly and accurately obtain fashion and beauty information that suits their physical characteristics. However, the amount of product information available online and in physical stores is vast, making it time-consuming and laborious to make the best individual choices. Furthermore, there is a lack of opportunities to actually experience the suggested items and beauty methods firsthand.

[0688] 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.

[0689] In this invention, the server includes means for acquiring the user's physical information, means for diagnosing the skeletal type and color type based on the acquired physical information, means for acquiring product information from multiple information provision platforms based on the diagnosis results, means for filtering the acquired product information based on the diagnosis results to select products suitable for the user, means for suggesting beauty information associated with the selected products, means for displaying the suggested beauty information and product information, and means for experiencing the suggested products and beauty methods in a physical store. This enables consumers to efficiently and effectively acquire individually optimized fashion and beauty information and to actually experience it on the spot.

[0690] "User body information" refers to data on personal characteristics necessary for optimizing fashion and beauty, such as an individual's body shape, skin color, and hair color.

[0691] "Skeletal type" refers to information that indicates the structural characteristics of the body, classified based on the user's body shape.

[0692] "Color type" refers to information that describes the characteristics of color tones, classified based on factors such as the user's skin and hair color.

[0693] An "information provision platform" is a digital system that provides users with information about products and services online.

[0694] "Product information" refers to detailed data related to fashion items such as clothing and accessories.

[0695] "Beauty information" refers to detailed data about specific cosmetics or beauty techniques, which is used to improve the user's appearance.

[0696] "Filtering" is an information processing technique that selects the best option from multiple choices based on specific conditions.

[0697] "Means of experiencing in a physical store" refers to means that enable customers to actually use or try out the proposed product or method in a physical store.

[0698] The system for implementing this invention acquires the user's physical information and optimizes fashion and beauty based on that information. The system's foundation consists of computer terminals, including smartphones, a central server, and interactive display devices within physical stores.

[0699] The server receives physical information entered by the user through the terminal. This input data includes body type, skin color, and hair color. Based on this information, the server uses internal algorithms and a database to diagnose the user's skeletal type and color type. This allows for a precise analysis of the user's characteristics and guides them towards the most suitable fashion and beauty choices.

[0700] Next, the server uses multiple information provision platform APIs to collect product information based on the diagnostic results. This allows it to import and filter data for suitable products. The filtered product information is then selected as the optimal item linked to the user's physical characteristics. Furthermore, relevant beauty information is also suggested, including specific instructions on how to use cosmetics and detailed beauty methods.

[0701] The terminal visually presents information provided by the server to the user. Users can view and experience suggested products and beauty information on their smartphones or displays in physical stores. For example, in certain fitting rooms, users can actually try on clothes suggested by the AI ​​system and immediately see the effect. An example of a prompt message is, "If the user has a slim build, olive skin tone, and black hair, what fashion items and makeup would be best suited for them?"

[0702] The specific hardware used includes, for example, smartphones running iOS or Android OS, and interactive displays such as large screens for displaying information in physical stores. The software consists of a mobile application using React Native, Node.js as the backend service, and Firebase for data management. These elements work together organically to provide users with a continuous and personalized experience.

[0703] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0704] Step 1:

[0705] The user uses their smartphone to enter physical information into the application on the device. This information includes body type, skin color, hair color, etc. This data is then sent from the device to the server.

[0706] Step 2:

[0707] The server uses an internal algorithm to diagnose the user's skeletal type and color type based on the received physical information. This process compares the input data with an existing database and analyzes the user's characteristics. As a result, it generates data for the diagnosed skeletal type and color type.

[0708] Step 3:

[0709] Based on the diagnostic results, the server retrieves product information using multiple information provision platform APIs. The input data here is the diagnostic results, and the output is a list of retrieved products. By accessing the information provision platform APIs in real time, the range of product options tailored to the user's characteristics expands.

[0710] Step 4:

[0711] The server filters the retrieved product information and selects products suitable for the user. This process executes a specific filtering algorithm to extract product attributes that match the diagnostic results. As a result of this filtering, an optimal product list is generated.

[0712] Step 5:

[0713] The server generates beauty information associated with the selected product. This beauty information includes appropriate makeup techniques and cosmetic usage methods tailored to the suggested fashion. This generation process combines information by referencing product characteristics and related beauty databases. As a result, a list of beauty information is generated.

[0714] Step 6:

[0715] The terminal displays a list of optimal products and beauty information received from the server to the user. Here, information is presented through a visual interface, allowing the user to visually confirm the content. Input is information from the server, and output is as visual data that the user can confirm.

[0716] Step 7:

[0717] Based on the displayed information, users try on products and experience beauty techniques using interactive displays in physical stores. During this process, the display provides feedback on products relevant to the user's selections, and they then try them on and use them. Finally, the user evaluates the experience and can choose to purchase the products on the spot.

[0718] 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.

[0719] This invention is a system that proposes personalized fashion and makeup based on the user's physical information, and further makes more appropriate suggestions by recognizing the user's emotions using an emotion engine. This system is implemented via the user, server, and terminal.

[0720] Users input physical information about their body type and color preferences using a terminal. The server then diagnoses their skeletal type and color type. This diagnostic information is essential for providing fashion and makeup suggestions.

[0721] The server uses the diagnostic results to retrieve information on fashion items through the purchasing site's API. The retrieved product information is filtered to narrow down to items that match the user's diagnostic results. In addition, an emotion engine recognizes the user's emotions and makes emotional adjustments to the suggested items and related information. For example, if the user is feeling relaxed, items in calming colors and soft materials will be recommended.

[0722] Furthermore, the server suggests cosmetics and makeup techniques that match the color and style of the selected product. Based on the results of the emotion engine's recognition, the suggested makeup is also adjusted to suit the user's mood. For example, if the user desires an energetic impression, bright and vibrant makeup tones will be recommended.

[0723] Users can input specific scenarios through their devices, and the server combines this information with the results of an emotion engine analysis to further optimize styling suggestions for those specific scenarios. This makes it easy for users to choose fashion and makeup that suits a particular situation.

[0724] All of these features are presented in a visualized form on the device, allowing users to review suggestions and easily purchase or utilize them. This process enables users to find the style that best suits their mood and purpose for the day.

[0725] The following describes the processing flow.

[0726] Step 1:

[0727] Users enter their physical information using the terminal's interface. This information includes body type, skin tone, and hair color, which they fill out on a form.

[0728] Step 2:

[0729] The terminal sends the entered physical information to the server. The server receives this data and uses it for diagnosis in the next step.

[0730] Step 3:

[0731] The server uses the received physical information to diagnose the skeletal type and color type. The algorithm analyzes the physical characteristics and determines the user's skeletal characteristics and personal color.

[0732] Step 4:

[0733] Based on the diagnostic results, the server accesses APIs from multiple shopping sites to retrieve product information. The items retrieved include clothing and accessories, and include current fashion data.

[0734] Step 5:

[0735] Based on the diagnostic results, the server filters the acquired product information to select products suitable for the user. The selection criteria include the degree of match with the diagnostic results, such as shape, color, and material.

[0736] Step 6:

[0737] When a user inputs or records their emotions using the device's camera and microphone, the device sends that information to a server. The server uses an emotion engine to analyze this information and determine the user's emotional state.

[0738] Step 7:

[0739] The server adjusts filtered fashion item and cosmetic item suggestions based on the results of the emotion engine's analysis. For example, when a user is feeling down, it suggests brightly colored items and uplifting makeup.

[0740] Step 8:

[0741] The user enters the specific occasion for which they want to go out (business, casual, date, etc.) via their device. This information is sent to the server.

[0742] Step 9:

[0743] The server combines scene information and sentiment analysis to suggest accessories and additional styling elements that are appropriate for the specific scene.

[0744] Step 10:

[0745] The device receives final suggestions from the server and visually presents the user with information on fashion, makeup, and accessories. The user can use this information to make the best choice without stress.

[0746] (Example 2)

[0747] 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".

[0748] In fashion and makeup choices, there is a challenge in providing personalized suggestions that appropriately reflect the user's physical characteristics and emotional state. Furthermore, providing optimal styling for different situations requires the flexible use of user input information.

[0749] 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.

[0750] In this invention, the server includes means for acquiring data about the user's body, means for acquiring product data from multiple sites based on the diagnostic results, and means for recognizing the user's emotions and making emotional adjustments to the suggested products and information about cosmetics. This makes it possible to suggest personalized fashion and makeup based on the user's physical characteristics and emotional state.

[0751] A "user" is someone who uses the system to receive fashion and makeup suggestions based on their own physical information and emotional state.

[0752] "Physical data" refers to information such as the user's height, body type, skin color, and hair color, which serves as the basis for providing personalized suggestions.

[0753] "Skeletal characteristics" are features diagnosed based on the user's body type and skeletal structure, and are a factor that helps in fashion choices.

[0754] "Color characteristics" refer to the color type derived from the user's skin tone, eye color, hair color, etc., and are elements that serve as a basis for styling.

[0755] "Product data" refers to information about purchasable fashion items, and is a collection of information obtained from multiple websites.

[0756] "Information about cosmetics" refers to information about cosmetics and makeup techniques suggested to users.

[0757] "Emotional state" refers to the user's feelings and is an element recognized by the system.

[0758] "Emotional adjustment" refers to the process of responding to suggested fashion and makeup based on the user's perceived emotions.

[0759] This system consists of three elements: user, server, and terminal, and each element works together to provide the user with the most suitable fashion and makeup suggestions.

[0760] First, users input data about their bodies using a device. Common devices such as smartphones and tablets are used, and users input data through a dedicated application or web interface. This data includes height, body type, skin color, and hair color.

[0761] Next, the terminal sends the input data to the server, which uses this data to activate a generative AI model. The generative AI model is a tool for diagnosing the user's skeletal and color characteristics, analyzing the input numerical data and forming prompt sentences. These prompt sentences might be something like, "Diagnose the user's skeletal characteristics and color type, and suggest fashion and makeup that emphasizes relaxation."

[0762] Subsequently, the server retrieves product data from multiple online marketplaces based on the diagnostic results. The APIs used here are standard ones for retrieving general product information. The retrieved data is filtered by a generative AI model to select items suitable for the user.

[0763] Furthermore, the device uses built-in sensors to read the user's emotional state from their facial expressions and voice. This emotional information is sent to a server and analyzed by AI.

[0764] The server makes emotional adjustments to the product and cosmetic information it suggests based on the perceived emotional state. For example, if the user wants to relax, items with calming colors and materials will be selected.

[0765] Finally, the processed suggestions are visualized on the device, allowing the user to view the suggestions and choose whether or not to purchase their preferred items. A concrete example of how the system can be used is that by receiving suggestions tailored to the user's situation, users can quickly choose the optimal fashion and makeup.

[0766] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0767] Step 1:

[0768] The user uses a device to input data about their body (e.g., height, body type, skin color). The device then sends this input data to the server. Specifically, the user enters information into an application form and presses the submit button. The data entered represents the individual's physical characteristics.

[0769] Step 2:

[0770] The server supplies the received data to a generating AI model to diagnose the user's skeletal and color characteristics. Specifically, the AI ​​model analyzes the input data and generates prompt sentences. The output at this stage is a diagnostic result summarizing the user's characteristics.

[0771] Step 3:

[0772] The server calls APIs from multiple online marketplaces based on the diagnostic results to retrieve product data. The input is the diagnostic results, and the output is a list of product information suitable for the user. Specifically, the server queries the database of each marketplace via the APIs.

[0773] Step 4:

[0774] The device uses sensors to capture the user's facial expressions and voice, and analyzes their emotional state. This data is sent to a server. Specifically, the camera and microphone on the device capture data in real time and pass it to an analysis program. The output is data indicating the user's emotional state.

[0775] Step 5:

[0776] The server combines acquired product information with emotional states to make emotional adjustments to the suggestions. Specifically, the AI ​​prioritizes colors and styles that match the user's mood. The input is a product list and emotional data, and the output is adjusted fashion and makeup suggestions.

[0777] Step 6:

[0778] The device displays the adjusted suggestions to the user in a visual format. The user then uses this to make a purchase decision. Specifically, the device displays the suggestions on the screen using graphics and text, and provides a purchase link. The output is visual suggestion content for the user.

[0779] (Application Example 2)

[0780] 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".

[0781] Modern consumers tend to seek personalized fashion and makeup, but existing systems do not adequately consider the user's physical information and emotions when making suggestions. Furthermore, users cannot receive personalized suggestions tailored to their current emotions or specific situations, making it difficult for them to determine what fashion and makeup are appropriate.

[0782] 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.

[0783] In this invention, the server includes means for acquiring the user's physical information and diagnosing their skeletal type and color type, means for acquiring and filtering product information based on the diagnosis results, and means for analyzing the user's emotions using a data acquisition device and reflecting that information in the suggestions. This enables personalized suggestions based on the user's physical and emotional state.

[0784] "User body information" refers to individual information necessary for fashion and makeup suggestions, such as the user's body type and skin tone.

[0785] "Body type and color type diagnosis" is a classification process that analyzes the user's acquired physical information to determine the most suitable fashion and makeup.

[0786] "Means of acquiring product information" refers to technology that collects information on relevant fashion items and cosmetics from purchasing websites based on the diagnostic results.

[0787] "Methods for filtering product information" refers to the process of narrowing down acquired product information to only those that match the user's individual diagnostic results.

[0788] A "means of suggesting cosmetic information" refers to a system that recommends suitable cosmetics and makeup methods to the user based on the selected product.

[0789] A "data acquisition device" is an electronic device used to receive input from the user and plays the role of collecting information.

[0790] "Methods for analyzing emotions" refers to technologies that determine emotions from input such as user voices and reflect the results in the proposed content.

[0791] The system that realizes this invention operates via a user-owned device and a server. The user's device scans the user's physical information using data acquisition devices such as a camera and acquires voice tone and emotions using a microphone. This acquired data is transmitted to the server.

[0792] The server analyzes the received physical information to diagnose the user's skeletal type and color type. OpenCV and NumPy are used for image data processing and numerical analysis during the diagnosis. Additionally, the Google Speech-to-Text API is used to analyze the user's emotions from their voice and generate emotion-based advice.

[0793] Subsequently, the server uses the purchasing site's API to retrieve information on relevant fashion items and cosmetics based on the diagnostic results. This information is filtered according to the user's diagnostic results and sentiment analysis. This allows the system to suggest the most suitable fashion and makeup combinations for the user.

[0794] Users can visually review these suggestions on their device and make specific makeup and clothing choices through voice feedback. Through this process, users can easily choose styles that suit their mood or specific occasion, making their daily clothing and makeup decisions more personalized.

[0795] For example, if a user feels like "I want to feel energetic today," the server will suggest brightly colored clothing and makeup that gives an energetic impression. Examples of prompts for the generative AI model include the following:

[0796] "The user desires an energetic image, has a slim build, and prefers autumn colors. Please suggest the most suitable fashion and makeup."

[0797] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0798] Step 1:

[0799] The user uses a device to acquire their own physical information and voice through the camera and microphone. The camera captures the user's body shape and color, and the microphone records the tone of their voice. These inputs are sent to the server. The output is the user's physical information and voice data.

[0800] Step 2:

[0801] The server uses OpenCV and NumPy with the received physical information to diagnose the user's skeletal type and color type. The data is processed through image processing and numerical analysis, and a diagnostic result is output that forms the basis of the user's fashion style.

[0802] Step 3:

[0803] The server uses the Google Speech-to-Text API to analyze the user's emotions from their voice. It converts the audio data into text and analyzes it using an emotion recognition algorithm to output the user's current emotional state.

[0804] Step 4:

[0805] The server retrieves relevant product information via the purchasing site's API based on the diagnostic results and emotional state. It processes the product information according to pre-configured filtering criteria based on the input data and outputs information on the items most suitable for the user.

[0806] Step 5:

[0807] The server uses a generative AI model to suggest makeup information based on the obtained product information. By generating prompt messages and inputting them into the AI ​​model, it outputs customized makeup suggestions for the user.

[0808] Step 6:

[0809] The user's device visualizes fashion and makeup suggestions received from the server. Information is displayed on the device's screen, and advice is provided as voice feedback. This allows the user to gain concrete options regarding their own style.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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."

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] The following is further disclosed regarding the embodiments described above.

[0832] (Claim 1)

[0833] Means for obtaining the user's physical information,

[0834] A means for diagnosing skeletal type and color type based on acquired physical information,

[0835] Based on the diagnostic results, a method for obtaining product information from multiple purchasing sites,

[0836] A method for filtering product information obtained based on diagnostic results to select products suitable for the user,

[0837] A means of suggesting cosmetic information in relation to the selected product,

[0838] A means for displaying proposed cosmetic information and product information,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, which proposes decorative items for a specific occasion based on product information obtained from a purchasing site.

[0842] (Claim 3)

[0843] The system according to claim 1, further comprising means for incorporating motivation into makeup information based on a specific scene entered by the user.

[0844] "Example 1"

[0845] (Claim 1)

[0846] A device for collecting the user's physical characteristics,

[0847] A device that diagnoses structural type and hue type based on collected physical characteristics,

[0848] A device that acquires product information from multiple e-commerce platforms based on the diagnostic results,

[0849] A device that sorts product information obtained based on diagnostic results and determines products suitable for the user,

[0850] A device that suggests beauty information in relation to the selected product,

[0851] A device that displays proposed beauty information and product information,

[0852] A device that automatically analyzes hue from collected physical characteristics,

[0853] Methods for optimizing information requests to e-commerce platforms,

[0854] A system that includes this.

[0855] (Claim 2)

[0856] The system according to claim 1, which proposes decorative items for a specific situation based on product information obtained from an e-commerce platform.

[0857] (Claim 3)

[0858] The system according to claim 1, further comprising a device for incorporating motivation into beauty information based on specific circumstances entered by the user.

[0859] "Application Example 1"

[0860] (Claim 1)

[0861] Means for obtaining the user's physical information,

[0862] A means for diagnosing skeletal type and color type based on acquired physical information,

[0863] Based on the diagnostic results, a means of obtaining product information from multiple information provision platforms,

[0864] A method for filtering product information obtained based on diagnostic results to select products suitable for the user,

[0865] A means of suggesting beauty information related to the selected product,

[0866] A means of displaying proposed beauty information and product information,

[0867] In-store, a means to experience the suggested products and beauty methods,

[0868] A system that includes this.

[0869] (Claim 2)

[0870] The system according to claim 1, which proposes decorative items for a specific situation based on product information obtained from an information provision platform.

[0871] (Claim 3)

[0872] The system according to claim 1, further comprising means for incorporating motivation into beauty information based on specific circumstances entered by the user.

[0873] "Example 2 of combining an emotion engine"

[0874] (Claim 1)

[0875] A means of acquiring data about the user's body,

[0876] A means for diagnosing skeletal characteristics and color characteristics based on acquired physical data,

[0877] Based on the diagnostic results, a means of obtaining product data from multiple sites,

[0878] A method for processing product data obtained based on diagnostic results to select products suitable for the user,

[0879] A means of suggesting information about cosmetics in relation to the selected product,

[0880] A means of recognizing user emotions and making emotional adjustments to suggested products and information about cosmetics,

[0881] A means for displaying information and product data related to the proposed cosmetics,

[0882] A system that includes this.

[0883] (Claim 2)

[0884] The system according to claim 1, further comprising means for optimizing product data and information related to cosmetics based on a specific scene entered by the user.

[0885] (Claim 3)

[0886] The system according to claim 1, further comprising means for integrating motivation into the information regarding the proposed makeup and making adjustments appropriate to the user's emotional state.

[0887] "Application example 2 when combining with an emotional engine"

[0888] (Claim 1)

[0889] Means for obtaining the user's physical information,

[0890] A means for diagnosing skeletal type and color type based on acquired physical information,

[0891] Based on the diagnostic results, a method for obtaining product information from multiple purchasing sites,

[0892] A method for filtering product information obtained based on diagnostic results to select products suitable for the user,

[0893] A means of suggesting cosmetic information in relation to the selected product,

[0894] A means for displaying proposed cosmetic information and product information,

[0895] A means of analyzing user emotions using a data acquisition device and incorporating emotional factors into the proposed content,

[0896] Methods for analyzing emotional information from user feedback,

[0897] A system that includes this.

[0898] (Claim 2)

[0899] The system according to claim 1, which proposes decorative items for specific occasions based on product information obtained from a purchasing site, and makes personalized suggestions using the user's emotional information.

[0900] (Claim 3)

[0901] The system according to claim 1, further comprising means for incorporating motivation into makeup information that takes emotional information into account, based on a specific scene entered by the user. [Explanation of symbols]

[0902] 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. Means for obtaining the user's physical information, A means for diagnosing skeletal type and color type based on acquired physical information, Based on the diagnostic results, a means of obtaining product information from multiple information provision platforms, A method for filtering product information obtained based on diagnostic results to select products suitable for the user, A means of suggesting beauty information related to the selected product, A means of displaying proposed beauty information and product information, In-store, a means to experience the suggested products and beauty methods, A system that includes this.

2. The system according to claim 1, which proposes decorative items for a specific situation based on product information obtained from an information provision platform.

3. The system according to claim 1, further comprising means for incorporating motivation into beauty information based on specific circumstances entered by the user.

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