System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to upload a facial picture; means for receiving and storing the uploaded facial picture; means for using a facial recognition model to analyze the stored facial picture; means for matching the analysis result with a stored hairstyle database; means for selecting an optimal hairstyle based on the matched result; and means for presenting the selected hairstyle and its details to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Many people, especially women, find it difficult to find the hairstyle that best suits them, and it takes a lot of time and effort. Traditional methods involve researching through magazines and the Internet and consulting with hairdressers, but many still fail to find the perfect hairstyle. There is a need for a way to solve this problem and find a hairstyle that suits them efficiently and quickly. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system comprising the following means: means for a user to upload a facial photo, means for receiving and storing the uploaded facial photo, means for using a facial recognition model to analyze the stored facial photo, means for comparing the analysis result with an accumulated hairstyle database, means for selecting an optimal hairstyle based on the comparison result, and means for presenting the selected hairstyle and its details to the user. The system also includes means for displaying specific styling advice and maintenance methods for the selected hairstyle based on the comparison result, and means for presenting multiple optimal hairstyles based on the user's facial pattern. In this way, the user can quickly and efficiently find the hairstyle that best suits them and how to maintain it.

[0006] 1. "User" means an individual who uses the Application to upload a photo of their face and receive hairstyle suggestions.

[0007] 2. "Face photo" means image data that shows the user's face.

[0008] 3. "Uploading" refers to the act of a user sending a photo of their face from their device to a server via the Internet.

[0009] 4. A "means" is a method or device used to achieve a particular purpose.

[0010] 5. "Server" means a computer system that processes data received from a User and returns the results to the User.

[0011] 6. "Facial recognition model" means algorithms or software that uses artificial intelligence to analyze facial patterns and features.

[0012] 7. "Analysis" is the process of extracting facial features from a facial photograph and processing them as numerical data.

[0013] 8. A "hairstyle database" is a collection of data that stores detailed information about various hairstyles.

[0014] 9. "Matching" is the process of comparing the analyzed facial feature data with a hairstyle database to select the most suitable hairstyle.

[0015] 10. "Selection" means the act of determining the hairstyle that best suits the user based on the matching results.

[0016] 11. "Presentation" means the act of displaying information about the selected hairstyle to the user.

[0017] 12. "Styling Advice" means advice on specific methods and product applications for maintaining a selected hairstyle. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention relates to a system that helps users quickly and efficiently find the hairstyle that best suits them. The system mainly involves a process in which a user uploads a facial photo, a server analyzes the facial photo, and then suggests the most suitable hairstyle.

[0040] Specific implementation methods of the system

[0041] User interface (terminal side)

[0042] First, the user launches the application. For user convenience, the application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user can then take a photo of their face or select an existing photo and upload it to the application.

[0043] Server Processing

[0044] The device then sends the user's selected facial photo to the server, which receives the photo and stores the data, then requests a facial recognition model to analyze the photo.

[0045] The facial recognition model performs a detailed analysis of facial features based on the received photograph. Specifically, it extracts features such as face shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth, and stores them as numerical data. Once the analysis is complete, the results are compared with the accumulated hairstyle database.

[0046] The hairstyle database stores detailed information about various hairstyles, and also lists which facial features each style is suited to. The server compares the analysis results with the information in the database and selects multiple hairstyles that are best suited to the user.

[0047] Response (terminal side)

[0048] Finally, the server sends the selected hairstyle and its details back to the device. The device receives this and suggests it to the user. Specifically, it displays a list of multiple hairstyles that are best suited to the user's facial pattern, complete with images. In addition, each hairstyle is accompanied by a comment such as "This style is best suited to oval faces" and a reason for the recommendation.

[0049] Additionally, styling advice and maintenance methods for the selected hairstyle are also displayed. For example, specific advice is provided such as, "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers."

[0050] Specific examples

[0051] For example, let's say User A uses this system and uploads a photo of their face. The server receives User A's photo and uses a facial recognition model to extract the characteristic "oval face." The server then selects from a database the hairstyles most suitable for oval faces, suggesting short hair, bob, long waves, etc. The device displays these styles to User A along with images and provides specific styling advice.

[0052] This system allows users to quickly and efficiently find the hairstyle that best suits them and how to maintain it. It is expected that user satisfaction will be greatly improved as they can easily try out styles at home without having to visit a specific beauty salon.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] The user launches the application and the device prompts them to take a photo of their face or upload an existing photo.

[0056] Step 2:

[0057] The user takes a photo of their face or selects and uploads an existing photo, and the device sends the selected photo to the server.

[0058] Step 3:

[0059] The server receives the facial photo sent from the device, temporarily stores it, and then passes the example facial photo to the facial recognition model.

[0060] Step 4:

[0061] The facial recognition model receives a photo and performs a detailed analysis of facial features, including facial shape (round, oval, angular, etc.) and the position and size of the eyes, nose, and mouth.

[0062] Step 5:

[0063] The server then compares the analysis results with a hairstyle database, which contains detailed information about various hairstyles and which facial features each style is suited to.

[0064] Step 6:

[0065] Based on the matching results, the server selects multiple hairstyles that best suit the user, and information about the selected hairstyle is generated and sent to the device.

[0066] Step 7:

[0067] The device displays the received hairstyle suggestions and detailed information to the user. Based on the user's facial pattern, multiple optimal hairstyles are displayed in a list with images.

[0068] Step 8:

[0069] For each hairstyle, the device will also provide specific styling and maintenance advice, such as "To maintain this short hairstyle, it is recommended to use wax to add volume."

[0070] Step 9:

[0071] Based on the presented hairstyles and advice, users can choose and try out the hairstyle that best suits them. This process allows users to efficiently and quickly find a hairstyle that suits them.

[0072] Example 1

[0073] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0074] In conventional methods, users often need a lot of time and effort to find the hairstyle that best suits them. Furthermore, advice from hairdressers depends on their individual experience, making it difficult to guarantee a consistent level of quality. The present invention aims to provide a system that helps users quickly and efficiently find the hairstyle that best suits them.

[0075] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0076] In this invention, the server includes means for users to upload facial photographs, means for receiving and saving the uploaded facial photographs, means for using a facial feature recognition model to analyze the saved facial photographs, means for extracting features such as facial shape and the positions and sizes of the eyes, nose, and mouth and saving them as numerical data, means for comparing the analysis results with an accumulated hairstyle database, means for selecting an optimal hairstyle based on the comparison results, and means for presenting the selected hairstyle and its details to the user, thereby enabling the user to quickly and efficiently find the optimal hairstyle for themselves and how to maintain it.

[0077] "User" refers to an individual who uses the system to find the hairstyle that best suits them.

[0078] "Facial photo" refers to image data of a user's face.

[0079] "Upload" refers to the act of a user using a device to send a photo of their face to the system.

[0080] "Receiving" refers to the act of the server receiving the facial photo sent by the user.

[0081] "Storage" refers to the act of the server retaining the received facial photo data in data storage.

[0082] A "facial feature recognition model" refers to an algorithm or software used to analyze facial features such as the shape of the face and the position and size of the eyes, nose, and mouth from a photograph.

[0083] "Numerical data" refers to quantitative data obtained by analyzing facial features using a facial feature recognition model.

[0084] A "hairstyle database" refers to a database that records detailed information about various hairstyles and which facial features each one is suited to.

[0085] "Matching" refers to the process of comparing the numerical data of the analysis results with information in a hairstyle database to find a matching hairstyle.

[0086] "Selection" refers to the act of choosing the hairstyle that best suits the user based on the matching results.

[0087] "Presenting" refers to the act of displaying the selected hairstyle and its detailed information to the user.

[0088] The present invention relates to a system that helps users quickly and efficiently find the hairstyle that best suits them. The system mainly involves a process in which a user uploads a facial photo, and a server analyzes the facial photo and suggests the most suitable hairstyle.

[0089] User interface (terminal side)

[0090] First, the user launches the dedicated application. The application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user then takes a photo of their face or selects an existing photo and uploads it to the application.

[0091] Server Processing

[0092] Next, the device sends the uploaded facial photo to a server. The server saves the facial photo in a data storage device for receiving and saving facial photos. The server then launches a facial feature recognition model (e.g., OpenCV or AWS Rekognition) to analyze the facial photo. This model extracts features such as the shape of the face and the position and size of the eyes, nose, and mouth, and stores them as numerical data. The server then uses the numerical data resulting from the analysis to compare it with a hairstyle database. This database stores information about which hairstyles are suitable for which facial features.

[0093] Proposal Procedure

[0094] The server selects the optimal hairstyle for the user based on the matching results. It then returns the selected hairstyle and detailed information (e.g., reason for recommendation, styling advice, etc.) to the device. The device then makes suggestions to the user based on the received information. The displayed information includes which face shapes each hairstyle is suitable for, as well as specific styling and maintenance methods.

[0095] Specific examples

[0096] For example, consider the case where User A uses this system and uploads a photo of his / her face. The server receives the photo and uses a facial feature recognition model to extract the characteristic "oval face." The server then selects the hairstyle best suited to an oval face (e.g., short hair, bob, long waves) from a hairstyle database. Based on this information, the device makes suggestions to User A with images and provides specific styling advice.

[0097] Prompt Sentence Examples

[0098] Here are some example prompts to input to the generative AI model:

[0099] Please explain the process of the system that allows users to upload a face photo and quickly and efficiently suggest the best hairstyle based on that photo. Please explain the specific operations, model, and database used for each processing step (face photo upload, face photo analysis, hairstyle selection, and hairstyle suggestion).

[0100] This prompt allows the generative AI model to generate more specific explanations of the system's detailed processing.

[0101] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0102] Step 1:

[0103] Users upload a photo of their face

[0104] Users launch the application and either take a photo of their face or select an existing photo.

[0105] Users can import a photo of their face and click the upload button to save the photo to their device.

[0106] Input: A user-selected face photo

[0107] Output: Facial photo data stored on the device

[0108] Step 2:

[0109] The device sends a photo of the face to the server

[0110] The device packages the stored facial photo data and generates an HTTP request to send it to the server.

[0111] The terminal sends the request to the server.

[0112] Input: Facial photo data stored on the device

[0113] Output: Facial photo data received by the server

[0114] Step 3:

[0115] The server stores the face photo.

[0116] The server validates the received facial photo data to ensure it is in the correct format.

[0117] Store face photo data in a file system or database.

[0118] Input: Received facial photo data

[0119] Output: Facial photo data stored on the server

[0120] Step 4:

[0121] The server analyzes the facial photo

[0122] The server runs a facial feature recognition model (e.g., OpenCV, AWS Rekognition) to analyze the face photo.

[0123] The facial recognition model extracts features such as the shape of the face and the position and size of the eyes, nose, and mouth, and stores them as numerical data.

[0124] Input: Facial photo data stored on the server

[0125] Output: Extracted facial feature data

[0126] Step 5:

[0127] The server compares the analysis results with the hairstyle database.

[0128] The server searches a hairstyle database based on the facial feature data.

[0129] Calculate the suitability of each hairstyle and select the most suitable style.

[0130] Input: extracted facial feature data, hairstyle database

[0131] Output: Selected optimal hairstyle data

[0132] Step 6:

[0133] The server sends the selected hairstyle back to the device.

[0134] The server packages the selected hairstyle and its detailed information (e.g., recommendation reason, styling advice) for transmission back to the terminal.

[0135] The server transmits the package to the terminal.

[0136] Input: Selected optimal hairstyle data

[0137] Output: Hairstyle suggestion data sent to the device

[0138] Step 7:

[0139] The device will display hairstyle suggestions to the user.

[0140] The terminal analyzes the received hairstyle suggestion data and updates the user interface.

[0141] It displays a list of hairstyles that best suit the user's face photo, along with a description and styling advice for each hairstyle.

[0142] Input: Hairstyle suggestion data received from the server

[0143] Output: Best hairstyles and styling advice displayed to the user

[0144] The above is the flow of the system program processing. At each step, specific operations and data flows are explained in detail, and the functionality of the entire system is clarified.

[0145] (Application example 1)

[0146] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] As autonomous vehicles become more widespread, there is a demand for enhanced in-car entertainment and relaxation. However, current systems do not allow users to find hairstyles that suit them, which means they are unable to make effective use of their time while driving autonomously. In addition, there is a lack of a concrete platform to improve the user experience in selecting hairstyles.

[0148] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0149] In this invention, the server includes: means for a user to upload a facial photo; means for receiving and saving the uploaded facial photo; means for using a facial recognition model to analyze the saved facial photo; means for comparing the analysis result with an accumulated hairstyle database; means for selecting an optimal hairstyle based on the comparison result; means for presenting the selected hairstyle and its details to the user; means for taking or uploading a facial photo using a display in the autonomous vehicle or a smartphone app; means for transmitting the facial photo to the server via an in-vehicle communication network; and means for displaying a list of selected hairstyles with images on an in-vehicle display. This allows users to easily find a hairstyle that suits them even during autonomous driving, making effective use of their time in the car.

[0150] A "User" is an individual who wishes to use the system to upload a photo of their face and find a hairstyle that suits them.

[0151] A "face photo" is image data that captures the user's facial features in detail.

[0152] An "uploading means" is a device or interface for taking a facial photograph or selecting an existing photograph and sending it to the system.

[0153] The "means for receiving and storing" is a data storage function for storing uploaded facial photos on a server.

[0154] A "facial recognition model" is a machine learning algorithm or software that analyzes photographs of faces and extracts facial features.

[0155] A "hairstyle database" is a database that stores various hairstyles and their characteristics.

[0156] The "matching means" is the process of comparing the analyzed facial features with a hairstyle database and selecting a suitable hairstyle.

[0157] The "best hairstyle" is the hairstyle that is determined to best suit the user's facial features.

[0158] The "presentation means" refers to a display or application for visually displaying an image and detailed information of the selected hairstyle to the user.

[0159] An "autonomous vehicle" is a vehicle that has the ability to automatically perform driving operations.

[0160] "Display" refers to a display device installed in the vehicle to visually display information from the system.

[0161] A "smartphone app" is an application that is installed on a smartphone and that uploads facial photos and displays analysis results as part of the system's functions.

[0162] The "communication network" is an internet connection means for sending facial photos from inside the vehicle to a server.

[0163] The "means for displaying with an image" is a display means for providing the user with visual information about the selected hairstyle.

[0164] This invention is a system that allows users to efficiently find the hairstyle that best suits them in an autonomous vehicle. The system configuration is mainly divided into three parts: the user interface, server processing, and in-car display.

[0165] User Interface

[0166] Users first access the system using the in-car display or their smartphone app. Once they access the system, a screen appears prompting them to either take a photo of their face or upload an existing photo. Users can then take a photo of their face or select an existing photo to upload.

[0167] Server Processing

[0168] The uploaded facial photo is sent to the server via the in-car communication network, and the server processes it using the following procedure.

[0169] 1. Save your face photo

[0170] The server stores the received facial photos in a database.

[0171] 2. Analysis using face recognition model

[0172] The server uses a facial recognition model (e.g., TensorFlow or OpenCV) to analyze the facial photo and extract facial features (shape, position of eyes and nose, etc.).

[0173] 3. Matching with hairstyle database

[0174] Based on the extracted facial features, the server compares them with a hairstyle database and selects multiple suitable hairstyles, each of which includes detailed information about which facial features are best suited to that style.

[0175] 4. Returning the results

[0176] The server then sends a list of selected hairstyles, along with detailed information and styling advice, back to the user's device.

[0177] Display on the in-car display

[0178] The results are then displayed on a display in the car or on a smartphone screen. Users can then choose from a selection of hairstyles based on their facial features. Each hairstyle comes with specific styling advice and maintenance instructions.

[0179] Specific examples

[0180] For example, suppose a user uploads a photo of their face while in the car. The server receives the photo and analyzes it using a facial recognition model. As a result of the analysis, characteristics such as an "oval face" are extracted. The server then selects a hairstyle from a hairstyle database that is best suited to an oval face, such as short hair, bob, or long waves. The selected hairstyle is then displayed on the in-car display along with styling advice.

[0181] Prompt Sentence Examples

[0182] "What are the characteristics of short hairstyles suitable for oval faces?"

[0183] The system allows users to easily find the hairstyle that best suits them even while driving autonomously, enabling them to make effective use of their time in the car. The present invention improves the quality of entertainment and relaxation in the car, further enriching the user experience.

[0184] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0185] Step 1:

[0186] Initializing the user interface

[0187] Users open the in-car display or smartphone app, and the startup screen prompts them to either take a photo of themselves or upload an existing photo.

[0188] Input: Launch app

[0189] Output: Shows option to take or upload a photo of your face

[0190] Step 2:

[0191] Acquiring a facial photo

[0192] Users can take a photo of themselves or upload an existing photo.

[0193] Input: User selects a photo of their face (takes or uploads)

[0194] Output: Facial photo data taken or uploaded

[0195] Step 3:

[0196] Send a photo of your face

[0197] The terminal transmits the acquired facial photograph to a server via the in-car communication network.

[0198] Input: Facial photo data

[0199] Output: Facial photo data transferred to the server

[0200] Step 4:

[0201] Save face photo

[0202] The server stores the received facial photos in data storage (e.g., AWS S3 bucket).

[0203] Input: Facial photo data sent to the server

[0204] Output: Saved face photo data

[0205] Step 5:

[0206] Analysis using face recognition models

[0207] The server analyzes the stored facial photos using a facial recognition model (e.g., TensorFlow or OpenCV), extracting features such as the shape of the face, and the position and size of the eyes, nose, and mouth, and converting them into numerical data.

[0208] Input: Saved face photo data

[0209] Output: Extracted facial feature data

[0210] Step 6:

[0211] Matching with a hairstyle database

[0212] The server compares the extracted facial feature data with a hairstyle database and selects multiple suitable hairstyles.

[0213] Input: Facial feature data

[0214] Output: A list of selected hairstyles

[0215] Step 7:

[0216] Returning the results

[0217] The server returns the selected hairstyle list, along with detailed information and styling advice, to the user's device.

[0218] Input: A list of selected hairstyles

[0219] Output: Returning the results to the user's device

[0220] Step 8:

[0221] Display on the in-car display

[0222] The device displays the received results on the in-car display or smartphone, presenting the user with multiple hairstyle options and styling advice.

[0223] Input: Returned result data

[0224] Output: Hairstyle options and advice displayed on the screen

[0225] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0226] The present invention relates to a system that helps users quickly and efficiently select the most suitable hairstyle, and also to a system that makes optimal suggestions taking into account the user's emotions. This system involves a process in which a user takes and uploads a facial photo, and a server not only analyzes the facial photo but also recognizes the user's emotions.

[0227] Specific implementation methods of the system

[0228] User interface (terminal side)

[0229] First, the user launches the application. For user convenience, the application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user can then take a photo of their face or select an existing photo and upload it to the application.

[0230] Server Processing

[0231] The device then sends the user's selected facial photo to the server, which receives the photo and stores the data, then requests a facial recognition model to analyze the photo.

[0232] The facial recognition model performs a detailed analysis of facial features based on the received photograph. Specifically, it extracts features such as face shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth, and stores them as numerical data. Once the analysis is complete, the results are compared with the accumulated hairstyle database.

[0233] The hairstyle database stores detailed information about various hairstyles, and also lists which facial features each style is suited to. The server compares the analysis results with the information in the database and selects multiple hairstyles that are best suited to the user.

[0234] Introducing the Emotion Engine

[0235] In addition, in order for the emotion engine to recognize the user's emotions, the server adds a process to analyze the user's facial expressions and voice before suggesting a style. This engine analyzes the user's current emotional state from facial expressions and tone of voice.

[0236] Based on the analysis results of the emotion engine, the system can choose a hairstyle that best suits the user's emotions at that time. For example, if the user is in a good mood, it can suggest a challenging hairstyle, and if the user is in a bad mood, it can suggest a more stable hairstyle.

[0237] Response (terminal side)

[0238] Finally, the server sends the selected hairstyle and its details back to the device. The device receives this and suggests it to the user. Specifically, it displays a list of multiple optimal hairstyles with images based on the user's facial pattern and emotions. In addition, each hairstyle includes a comment such as "This style is perfect for your current mood" and the reason for the recommendation.

[0239] Additionally, styling advice and maintenance methods for the selected hairstyle are also displayed. For example, specific advice is provided such as, "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers."

[0240] Specific examples

[0241] For example, suppose User B uses this system and uploads a photo of his face. The server receives User B's photo and uses a facial recognition model to extract the characteristic "oval face." Furthermore, the emotion engine analyzes the photo and determines that User B is in a relaxed mood. Based on this information, the server suggests hairstyles (e.g., long waves or natural straight hair) that are optimal for an oval face and match a relaxed mood. The device displays these styles with images to User B and provides specific styling advice.

[0242] The system allows users to quickly and efficiently find hairstyles that suit not only their face shape but also their current mood, as well as how to maintain them, allowing them to easily try out styles at home without having to visit a specific hair salon.

[0243] The processing flow will be explained below.

[0244] Step 1:

[0245] The user launches the application and the device prompts them to take a photo of their face or upload an existing photo.

[0246] Step 2:

[0247] The user takes a photo of their face or selects and uploads an existing photo, and the device sends the selected photo to the server.

[0248] Step 3:

[0249] The server receives the facial photo sent from the device, temporarily stores it, and passes it to a facial recognition model.

[0250] Step 4:

[0251] The facial recognition model receives a photo and performs a detailed analysis of facial features, including facial shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth.

[0252] Step 5:

[0253] The server then compares the analysis results with a hairstyle database, which contains detailed information about various hairstyles and which facial features each style is suited to.

[0254] Step 6:

[0255] Based on the matching results, the server selects multiple hairstyles that best suit the user.

[0256] Step 7:

[0257] The emotion engine analyzes facial expressions and tone of voice to recognize the user's emotions, and users can also provide photos, video clips, and audio.

[0258] Step 8:

[0259] The server obtains the user's emotional state recognized by the emotion engine, for example, the emotion engine indicates the user's emotional state such as "relaxed" or "tense."

[0260] Step 9:

[0261] The server considers the analysis results and the emotion recognition results from the emotion engine to reselect the most suitable hairstyle. For example, it can suggest a natural hairstyle for a relaxed user, and a stable hairstyle for a nervous user.

[0262] Step 10:

[0263] The server sends the selected hairstyle and its details to the device, which receives it and presents it to the user.

[0264] Step 11:

[0265] The device then displays the received hairstyle suggestions and detailed information to the user, displaying a list of multiple hairstyles with images that are most suitable for the user based on their facial pattern and emotions.

[0266] Step 12:

[0267] For each hairstyle selected, the device will also provide specific styling and maintenance advice, such as "To maintain this short hairstyle, it is recommended to use wax to add volume."

[0268] Step 13:

[0269] Based on the presented hairstyles and advice, users can choose and try out the hairstyle that best suits them. This process allows users to efficiently and quickly find a hairstyle that suits them.

[0270] Example 2

[0271] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0272] Conventional hairstyle suggestion systems only consider the user's face shape, which means they are unable to suggest styles that match the user's emotions or mood. This can prevent users from choosing the hairstyle that best suits their mood at the time, leading to a decrease in satisfaction.

[0273] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0274] In this invention, the server includes means for allowing a user to upload a facial photo, means for receiving and storing the uploaded facial photo, means for using an image recognition model to analyze the stored facial photo, means for comparing the analysis result with an accumulated hairstyle database, means for using an emotion recognition engine to analyze the user's emotion, means for selecting an optimal hairstyle based on the user's emotional state and facial features, and means for presenting the selected hairstyle and its details to the user, thereby enabling the user to know the optimal hairstyle based not only on the shape of their face but also on their current mood.

[0275] "User" means an individual who uses the System.

[0276] A "face photo" is image data of a user's face.

[0277] "Means for uploading" refers to the function that allows a user to send data from a terminal to a server.

[0278] "Means for receiving and storing" refers to the function by which the server receives data from the terminal and stores it.

[0279] An "image recognition model" is an algorithm or software used to analyze facial photographs.

[0280] "Means for matching" is a function for comparing the analysis results with information in the database.

[0281] An "emotion recognition engine" is an algorithm or software for analyzing a user's emotions.

[0282] "Emotional state" is information that indicates the user's current psychological state.

[0283] A "hairstyle database" is a collection of data that records various hairstyles and the facial features and emotional states that are suitable for each hairstyle.

[0284] The "best hairstyle" is the hairstyle that best suits the user's facial features and emotional state.

[0285] The "means for presenting details" is a function for displaying information about the selected hairstyle to the user.

[0286] The present invention relates to a system that assists a user in quickly and efficiently selecting an optimal hairstyle, and further relates to a system that makes optimal suggestions taking into account the user's feelings.

[0287] First, the user launches the application on their device. The application provides an interface for the user to take a photo of their face or upload an existing photo. Once the user has taken or uploaded a photo of their face, the device sends the photo data to a server. The data is securely transmitted using encryption protocols such as TLS (Transport Layer Security).

[0288] The server receives the facial photo data sent from the device and stores it in a database. The server then analyzes the facial photo using an image recognition model. This image recognition model uses a facial recognition API provided by a common cloud service (such as Azure Face API). Through the analysis, facial features such as the shape of the face and the position of the eyes, nose, and mouth are extracted and stored as numerical data.

[0289] The server then uses an emotion recognition engine, such as Google Cloud Natural Language API or IBM Watson's Tone Analyzer, to analyze the user's emotional state by analyzing their facial expressions and tone of voice.

[0290] The server then compares the results of these analyses with a database of accumulated hairstyles, which contains a variety of hairstyles and which facial features and emotional states each style is suited to. By comparing the results with the analysis, the server selects the hairstyle that best suits the user. The selected style also includes detailed information and styling advice.

[0291] The server sends information about the selected hairstyle back to the device, which receives it and presents it to the user. The information presented includes an image of the selected hairstyle, the reason for the recommendation, and specific styling and maintenance methods. For example, advice such as "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers" is also provided.

[0292] For example, when User A uses the app and uploads a photo of their face, the server receives the photo and extracts the characteristic "oval face" using the Azure Face API. Furthermore, it determines that the user is in a relaxed mood using the Google Cloud Natural Language API. Based on this information, the server selects a hairstyle, such as long waves or natural straight, that is best suited to a relaxed mood and presents it to User A along with detailed styling advice.

[0293] An example of a prompt to be input to a generative AI model might be, "Describe a system that suggests the best hairstyle based on a face photo uploaded by a user. The system combines facial recognition and emotion recognition to suggest a style that matches the user's current mood. Please also mention what software and hardware you use."

[0294] The system allows users to quickly and efficiently find the perfect hairstyle based not only on their face shape but also on their current mood.

[0295] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0296] Step 1:

[0297] When a user launches the application, the device displays a screen prompting the user to take a photo of their face or upload an existing photo. Once the user takes or selects a photo of their face, the image data is temporarily stored on the device.

[0298] Input: Facial photo data taken or selected by the user.

[0299] Output: Temporarily saved face photo data.

[0300] Step 2:

[0301] When the user selects a face photo and presses the upload button, the device sends the face photo data to the server using encrypted data communication, using protocols such as TLS (Transport Layer Security).

[0302] Input: Temporarily saved facial photo data.

[0303] Output: Facial photo data sent to the server.

[0304] Step 3:

[0305] The server receives the facial photo data sent from the device and stores it in a database.

[0306] Input: Facial photo data sent from the device.

[0307] Output: Facial photo data stored in a database.

[0308] Step 4:

[0309] The server sends the stored facial photo data to a facial recognition model (e.g., an image recognition API) for analysis, where features such as the shape of the face and the position of the eyes, nose, and mouth are extracted as numerical data.

[0310] Input: Facial photo data stored in the database.

[0311] Output: Numerical data representing facial features.

[0312] Step 5:

[0313] The server uses an emotion recognition engine (e.g., an emotion analysis API) to analyze the user's emotions. It analyzes the user's facial expressions and tone of voice to determine their current emotional state.

[0314] Input: Facial photo data stored in a database and real-time audio data (if required).

[0315] Output: Parsed user emotional state data.

[0316] Step 6:

[0317] The server compares the numerical data obtained from the facial recognition model and the emotional state data obtained from the emotion recognition engine with a hairstyle database. The database contains multiple hairstyles and the facial features and emotional states that are suitable for each. The server then selects the most suitable hairstyle.

[0318] Input: Numerical data representing facial features and emotional state data.

[0319] Output: Data on the results of selecting the best hairstyle.

[0320] Step 7:

[0321] The server then returns detailed information about the selected hairstyle to the device, including an image of the selected hairstyle, the reason for its recommendation, and specific styling and maintenance methods.

[0322] Input: Data on the results of selecting the best hairstyle.

[0323] Output: Hairstyle information returned to the device.

[0324] Step 8:

[0325] The device receives the selected hairstyle information returned from the server, and based on the received information, displays a list of hairstyle images to the user, along with the reasons why each style is recommended and specific styling advice.

[0326] Input: Hairstyle information returned from the server.

[0327] Output: A list of hairstyle images and advice information presented to the user.

[0328] (Application example 2)

[0329] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0330] Conventional hairstyle suggestion systems only considered the user's facial features when proposing hairstyles, making it impossible to provide optimal suggestions that reflected the user's current emotional state. Furthermore, the suggested hairstyles could only be applied to individual devices or at home, making them difficult to use in physical stores. There was a need to solve these problems and realize hairstyle suggestions that better meet the user's needs.

[0331] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to upload a facial photo, means for receiving and saving the uploaded facial photo, means for using a face recognition model to analyze the saved facial photo, means for analyzing the emotional state of the user using an emotion recognition model, means for suggesting an optimal hairstyle based on the user's facial features and emotional state, and means for displaying hairstyles in real time using a device installed in a physical store. This makes it possible to suggest an optimal hairstyle taking into account the user's emotional state, further promoting use in physical stores.

[0332] "Means for users to upload facial photos" refers to terminals or applications that provide the functionality for users to take a photo of their face and send it to the system.

[0333] "Means for receiving and storing uploaded facial photographs" refers to software or systems that provide the function of receiving and storing facial photographs uploaded by users on the server side.

[0334] The "means for using a facial recognition model to analyze stored facial photographs" is a function that uses a facial recognition algorithm to analyze stored facial photographs and extract facial features.

[0335] "Means for selecting the most suitable hairstyle based on the comparison results" refers to a function that compares the results of facial recognition analysis with a hairstyle database and selects the most suitable hairstyle.

[0336] The "means for presenting the selected hairstyle and its details to the user" is an interface that has the function of displaying an image and information about the selected hairstyle to the user.

[0337] The "means for analyzing the emotional state of a user using an emotion recognition model" is an emotion recognition algorithm for identifying the emotional state of a user through analysis of the user's facial expressions and voice.

[0338] "Means for suggesting the most suitable hairstyle based on the user's facial features and emotional state" is a function that comprehensively evaluates the user's facial shape and emotional state, and selects and suggests the most suitable hairstyle.

[0339] "Means for displaying hairstyles in real time using devices installed in physical stores" refers to a function that displays hairstyle suggestions in real time using devices such as mirrors and tablets installed in physical stores.

[0340] The present invention is a system that helps users quickly and efficiently select the most suitable hairstyle, and also provides optimal suggestions taking into account the user's emotions. This system operates through a smart mirror system installed in a physical store. Specific embodiments of the system are described below.

[0341] User interface (terminal side)

[0342] First, the user stands in front of a smart mirror installed in a brick-and-mortar store, which has a built-in camera that automatically takes a photo of the user's face, which is then uploaded to the system.

[0343] Server Processing

[0344] The server receives and stores the uploaded face photo. It then uses a facial recognition model (e.g., OpenCV, Dlib) to analyze the face photo and extract detailed facial features, including face shape (e.g., round, oval, angular). It then uses an emotion recognition model (e.g., Microsoft Azure Face API, Amazon Rekognition) to analyze the user's current emotional state from their facial expressions and voice.

[0345] Once the facial features and emotional state have been analyzed, the results are compared against a hairstyle database that contains detailed information about various hairstyles and which styles suit which facial features.

[0346] Selection and proposal

[0347] The server compares the analysis results with the database information and selects multiple hairstyles that are best suited to the user. Furthermore, based on the analysis results of the emotion engine, it selects the most suitable hairstyle taking into account the user's emotions at the time. For example, if the user is relaxed, it suggests a hairstyle that gives a sense of stability.

[0348] Response (terminal side)

[0349] Finally, the server sends the selected hairstyle and its details back to the smart mirror. The smart mirror receives this and displays suggestions to the user in real time. Specifically, it displays multiple optimal hairstyles based on the user's facial patterns and emotions, along with images. In addition, for each hairstyle, comments such as "This style is perfect for your current mood" and reasons for the recommendation are included. Styling advice and maintenance methods for the selected hairstyle are also displayed.

[0350] Specific examples

[0351] For example, when a user stands in front of a smart mirror, a photo of their face is automatically taken and uploaded to the system. The server receives the photo and uses a facial recognition model to extract the characteristic of an "oval face." An emotion recognition model analyzes the user's state as relaxed. Based on this information, the server selects a hairstyle (e.g., soft waves or a bob) that best suits the user's face shape and relaxed mood. The results are displayed in real time on the smart mirror, allowing the user to instantly see the optimal hairstyle and styling method.

[0352] Example prompts for generative AI models

[0353] "A 40-year-old woman comes into the salon looking for a stylish hairstyle, but wants to maintain a calm look. She has an oval face and is currently relaxed. We suggest the best hairstyle and styling method for her."

[0354] The system allows users to quickly and efficiently find hairstyles that suit their face shape and current mood, allowing them to easily try out styles at home or in a brick-and-mortar store without having to visit a specific salon.

[0355] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0356] Step 1:

[0357] A user stands in front of a smart mirror installed in a physical store and takes a photo of their face. When the user stands in front of the smart mirror, the smart mirror automatically takes a photo of their face using its built-in camera and collects the data. The input at this point is the user's face photo, and the image data is sent to the server.

[0358] Step 2:

[0359] The server receives and stores the facial photo sent from the smart mirror. This stores the facial photo data in the server and prepares it for analysis. The input is the facial photo data sent in step 1, and the output is the stored facial photo data.

[0360] Step 3:

[0361] The server uses a facial recognition model to analyze the stored facial photos. This facial recognition model (e.g., OpenCV, Dlib) analyzes facial features (round, oval, angular, etc.) in detail and extracts them as numerical data. The input is the stored facial photo data, and the output is facial feature data.

[0362] Step 4:

[0363] The server uses the facial feature data extracted by the facial recognition model to analyze the user's emotional state using an emotion recognition model (e.g., Microsoft Azure Face API, Amazon Rekognition). The emotion recognition model analyzes the user's facial expressions and voice to identify their emotional state, such as relaxed or excited. The input is facial feature data and facial expression / voice data, and the output is emotional state data.

[0364] Step 5:

[0365] The server compares the facial feature data and emotional state data with the hairstyle database. Based on the comparison results, it selects the most suitable hairstyle. The hairstyle database contains information on which facial features and emotional state each hairstyle is suited to. The input is facial feature data and emotional state data, and the output is the most suitable hairstyle data.

[0366] Step 6:

[0367] The server sends the selected hairstyle and its details back to the smart mirror, which now includes an image of the selected hairstyle and styling advice. The input is the optimal hairstyle data, and the output is the suggestion data sent to the smart mirror.

[0368] Step 7:

[0369] The smart mirror displays hairstyle suggestions received from the server to the user in real time. The user can then select the best hairstyle from the multiple hairstyles displayed. The displayed content includes an image of the selected hairstyle, detailed information, and styling advice. The input is the suggestion data sent from the server, and the output is the information visually presented to the user.

[0370] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0371] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0372] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0373] [Second embodiment]

[0374] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0375] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0376] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0377] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0378] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0379] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0380] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0381] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0382] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0383] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0384] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0385] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0386] The present invention relates to a system that helps users quickly and efficiently find the hairstyle that best suits them. The system mainly involves a process in which a user uploads a facial photo, a server analyzes the facial photo, and then suggests the most suitable hairstyle.

[0387] Specific implementation methods of the system

[0388] User interface (terminal side)

[0389] First, the user launches the application. For user convenience, the application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user can then take a photo of their face or select an existing photo and upload it to the application.

[0390] Server Processing

[0391] The device then sends the user's selected facial photo to the server, which receives the photo and stores the data, then requests a facial recognition model to analyze the photo.

[0392] The facial recognition model performs a detailed analysis of facial features based on the received photograph. Specifically, it extracts features such as face shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth, and stores them as numerical data. Once the analysis is complete, the results are compared with the accumulated hairstyle database.

[0393] The hairstyle database stores detailed information about various hairstyles, and also lists which facial features each style is suited to. The server compares the analysis results with the information in the database and selects multiple hairstyles that are best suited to the user.

[0394] Response (terminal side)

[0395] Finally, the server sends the selected hairstyle and its details back to the device. The device receives this and suggests it to the user. Specifically, it displays a list of multiple hairstyles that are best suited to the user's facial pattern, complete with images. In addition, each hairstyle is accompanied by a comment such as "This style is best suited to oval faces" and a reason for the recommendation.

[0396] Additionally, styling advice and maintenance methods for the selected hairstyle are also displayed. For example, specific advice is provided such as, "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers."

[0397] Specific examples

[0398] For example, let's say User A uses this system and uploads a photo of their face. The server receives User A's photo and uses a facial recognition model to extract the characteristic "oval face." The server then selects from a database the hairstyles most suitable for oval faces, suggesting short hair, bob, long waves, etc. The device displays these styles to User A along with images and provides specific styling advice.

[0399] This system allows users to quickly and efficiently find the hairstyle that best suits them and how to maintain it. It is expected that user satisfaction will be greatly improved as they can easily try out styles at home without having to visit a specific beauty salon.

[0400] The processing flow will be explained below.

[0401] Step 1:

[0402] The user launches the application and the device prompts them to take a photo of their face or upload an existing photo.

[0403] Step 2:

[0404] The user takes a photo of their face or selects and uploads an existing photo, and the device sends the selected photo to the server.

[0405] Step 3:

[0406] The server receives the facial photo sent from the device, temporarily stores it, and then passes the example facial photo to the facial recognition model.

[0407] Step 4:

[0408] The facial recognition model receives a photo and performs a detailed analysis of facial features, including facial shape (round, oval, angular, etc.) and the position and size of the eyes, nose, and mouth.

[0409] Step 5:

[0410] The server then compares the analysis results with a hairstyle database, which contains detailed information about various hairstyles and which facial features each style is suited to.

[0411] Step 6:

[0412] Based on the matching results, the server selects multiple hairstyles that best suit the user, and information about the selected hairstyle is generated and sent to the device.

[0413] Step 7:

[0414] The device displays the received hairstyle suggestions and detailed information to the user. Based on the user's facial pattern, multiple optimal hairstyles are displayed in a list with images.

[0415] Step 8:

[0416] For each hairstyle, the device will also provide specific styling and maintenance advice, such as "To maintain this short hairstyle, it is recommended to use wax to add volume."

[0417] Step 9:

[0418] Based on the presented hairstyles and advice, users can choose and try out the hairstyle that best suits them. This process allows users to efficiently and quickly find a hairstyle that suits them.

[0419] Example 1

[0420] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0421] In conventional methods, users often need a lot of time and effort to find the hairstyle that best suits them. Furthermore, advice from hairdressers depends on their individual experience, making it difficult to guarantee a consistent level of quality. The present invention aims to provide a system that helps users quickly and efficiently find the hairstyle that best suits them.

[0422] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0423] In this invention, the server includes means for users to upload facial photographs, means for receiving and saving the uploaded facial photographs, means for using a facial feature recognition model to analyze the saved facial photographs, means for extracting features such as facial shape and the positions and sizes of the eyes, nose, and mouth and saving them as numerical data, means for comparing the analysis results with an accumulated hairstyle database, means for selecting an optimal hairstyle based on the comparison results, and means for presenting the selected hairstyle and its details to the user, thereby enabling the user to quickly and efficiently find the optimal hairstyle for themselves and how to maintain it.

[0424] "User" refers to an individual who uses the system to find the hairstyle that best suits them.

[0425] "Facial photo" refers to image data of a user's face.

[0426] "Upload" refers to the act of a user using a device to send a photo of their face to the system.

[0427] "Receiving" refers to the act of the server receiving the facial photo sent by the user.

[0428] "Storage" refers to the act of the server retaining the received facial photo data in data storage.

[0429] A "facial feature recognition model" refers to an algorithm or software used to analyze facial features such as the shape of the face and the position and size of the eyes, nose, and mouth from a photograph.

[0430] "Numerical data" refers to quantitative data obtained by analyzing facial features using a facial feature recognition model.

[0431] A "hairstyle database" refers to a database that records detailed information about various hairstyles and which facial features each one is suited to.

[0432] "Matching" refers to the process of comparing the numerical data of the analysis results with information in a hairstyle database to find a matching hairstyle.

[0433] "Selection" refers to the act of choosing the hairstyle that best suits the user based on the matching results.

[0434] "Presenting" refers to the act of displaying the selected hairstyle and its detailed information to the user.

[0435] The present invention relates to a system that helps users quickly and efficiently find the hairstyle that best suits them. The system mainly involves a process in which a user uploads a facial photo, and a server analyzes the facial photo and suggests the most suitable hairstyle.

[0436] User interface (terminal side)

[0437] First, the user launches the dedicated application. The application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user then takes a photo of their face or selects an existing photo and uploads it to the application.

[0438] Server Processing

[0439] Next, the device sends the uploaded facial photo to a server. The server saves the facial photo in a data storage device for receiving and saving facial photos. The server then launches a facial feature recognition model (e.g., OpenCV or AWS Rekognition) to analyze the facial photo. This model extracts features such as the shape of the face and the position and size of the eyes, nose, and mouth, and stores them as numerical data. The server then uses the numerical data resulting from the analysis to compare it with a hairstyle database. This database stores information about which hairstyles are suitable for which facial features.

[0440] Proposal Procedure

[0441] The server selects the optimal hairstyle for the user based on the matching results. It then returns the selected hairstyle and detailed information (e.g., reason for recommendation, styling advice, etc.) to the device. The device then makes suggestions to the user based on the received information. The displayed information includes which face shapes each hairstyle is suitable for, as well as specific styling and maintenance methods.

[0442] Specific examples

[0443] For example, consider the case where User A uses this system and uploads a photo of his / her face. The server receives the photo and uses a facial feature recognition model to extract the characteristic "oval face." The server then selects the hairstyle best suited to an oval face (e.g., short hair, bob, long waves) from a hairstyle database. Based on this information, the device makes suggestions to User A with images and provides specific styling advice.

[0444] Prompt Sentence Examples

[0445] Here are some example prompts to input to the generative AI model:

[0446] Please explain the process of the system that allows users to upload a face photo and quickly and efficiently suggest the best hairstyle based on that photo. Please explain the specific operations, model, and database used for each processing step (face photo upload, face photo analysis, hairstyle selection, and hairstyle suggestion).

[0447] This prompt allows the generative AI model to generate more specific explanations of the system's detailed processing.

[0448] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0449] Step 1:

[0450] Users upload a photo of their face

[0451] Users launch the application and either take a photo of their face or select an existing photo.

[0452] Users can import a photo of their face and click the upload button to save the photo to their device.

[0453] Input: A user-selected face photo

[0454] Output: Facial photo data stored on the device

[0455] Step 2:

[0456] The device sends a photo of the face to the server

[0457] The device packages the stored facial photo data and generates an HTTP request to send it to the server.

[0458] The terminal sends the request to the server.

[0459] Input: Facial photo data stored on the device

[0460] Output: Facial photo data received by the server

[0461] Step 3:

[0462] The server stores the face photo.

[0463] The server validates the received facial photo data to ensure it is in the correct format.

[0464] Store face photo data in a file system or database.

[0465] Input: Received facial photo data

[0466] Output: Facial photo data stored on the server

[0467] Step 4:

[0468] The server analyzes the facial photo

[0469] The server runs a facial feature recognition model (e.g., OpenCV, AWS Rekognition) to analyze the face photo.

[0470] The facial recognition model extracts features such as the shape of the face and the position and size of the eyes, nose, and mouth, and stores them as numerical data.

[0471] Input: Facial photo data stored on the server

[0472] Output: Extracted facial feature data

[0473] Step 5:

[0474] The server compares the analysis results with the hairstyle database.

[0475] The server searches a hairstyle database based on the facial feature data.

[0476] Calculate the suitability of each hairstyle and select the most suitable style.

[0477] Input: extracted facial feature data, hairstyle database

[0478] Output: Selected optimal hairstyle data

[0479] Step 6:

[0480] The server sends the selected hairstyle back to the device.

[0481] The server packages the selected hairstyle and its detailed information (e.g., recommendation reason, styling advice) for transmission back to the terminal.

[0482] The server transmits the package to the terminal.

[0483] Input: Selected optimal hairstyle data

[0484] Output: Hairstyle suggestion data sent to the device

[0485] Step 7:

[0486] The device will display hairstyle suggestions to the user.

[0487] The terminal analyzes the received hairstyle suggestion data and updates the user interface.

[0488] It displays a list of hairstyles that best suit the user's face photo, along with a description and styling advice for each hairstyle.

[0489] Input: Hairstyle suggestion data received from the server

[0490] Output: Best hairstyles and styling advice displayed to the user

[0491] The above is the flow of the system program processing. At each step, specific operations and data flows are explained in detail, and the functionality of the entire system is clarified.

[0492] (Application example 1)

[0493] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0494] As autonomous vehicles become more widespread, there is a demand for enhanced in-car entertainment and relaxation. However, current systems do not allow users to find hairstyles that suit them, which means they are unable to make effective use of their time while driving autonomously. In addition, there is a lack of a concrete platform to improve the user experience in selecting hairstyles.

[0495] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0496] In this invention, the server includes: means for a user to upload a facial photo; means for receiving and saving the uploaded facial photo; means for using a facial recognition model to analyze the saved facial photo; means for comparing the analysis result with an accumulated hairstyle database; means for selecting an optimal hairstyle based on the comparison result; means for presenting the selected hairstyle and its details to the user; means for taking or uploading a facial photo using a display in the autonomous vehicle or a smartphone app; means for transmitting the facial photo to the server via an in-vehicle communication network; and means for displaying a list of selected hairstyles with images on an in-vehicle display. This allows users to easily find a hairstyle that suits them even during autonomous driving, making effective use of their time in the car.

[0497] A "User" is an individual who wishes to use the system to upload a photo of their face and find a hairstyle that suits them.

[0498] A "face photo" is image data that captures the user's facial features in detail.

[0499] An "uploading means" is a device or interface for taking a facial photograph or selecting an existing photograph and sending it to the system.

[0500] The "means for receiving and storing" is a data storage function for storing uploaded facial photos on a server.

[0501] A "facial recognition model" is a machine learning algorithm or software that analyzes photographs of faces and extracts facial features.

[0502] A "hairstyle database" is a database that stores various hairstyles and their characteristics.

[0503] The "matching means" is the process of comparing the analyzed facial features with a hairstyle database and selecting a suitable hairstyle.

[0504] The "best hairstyle" is the hairstyle that is determined to best suit the user's facial features.

[0505] The "presentation means" refers to a display or application for visually displaying an image and detailed information of the selected hairstyle to the user.

[0506] An "autonomous vehicle" is a vehicle that has the ability to automatically perform driving operations.

[0507] "Display" refers to a display device installed in the vehicle to visually display information from the system.

[0508] A "smartphone app" is an application that is installed on a smartphone and that uploads facial photos and displays analysis results as part of the system's functions.

[0509] The "communication network" is an internet connection means for sending facial photos from inside the vehicle to a server.

[0510] The "means for displaying with an image" is a display means for providing the user with visual information about the selected hairstyle.

[0511] This invention is a system that allows users to efficiently find the hairstyle that best suits them in an autonomous vehicle. The system configuration is mainly divided into three parts: the user interface, server processing, and in-car display.

[0512] User Interface

[0513] Users first access the system using the in-car display or their smartphone app. Once they access the system, a screen appears prompting them to either take a photo of their face or upload an existing photo. Users can then take a photo of their face or select an existing photo to upload.

[0514] Server Processing

[0515] The uploaded facial photo is sent to the server via the in-car communication network, and the server processes it using the following procedure.

[0516] 1. Save your face photo

[0517] The server stores the received facial photos in a database.

[0518] 2. Analysis using face recognition model

[0519] The server uses a facial recognition model (e.g., TensorFlow or OpenCV) to analyze the facial photo and extract facial features (shape, position of eyes and nose, etc.).

[0520] 3. Matching with hairstyle database

[0521] Based on the extracted facial features, the server compares them with a hairstyle database and selects multiple suitable hairstyles, each of which includes detailed information about which facial features are best suited to that style.

[0522] 4. Returning the results

[0523] The server then sends a list of selected hairstyles, along with detailed information and styling advice, back to the user's device.

[0524] Display on the in-car display

[0525] The results are then displayed on a display in the car or on a smartphone screen. Users can then choose from a selection of hairstyles based on their facial features. Each hairstyle comes with specific styling advice and maintenance instructions.

[0526] Specific examples

[0527] For example, suppose a user uploads a photo of their face while in the car. The server receives the photo and analyzes it using a facial recognition model. As a result of the analysis, characteristics such as an "oval face" are extracted. The server then selects a hairstyle from a hairstyle database that is best suited to an oval face, such as short hair, bob, or long waves. The selected hairstyle is then displayed on the in-car display along with styling advice.

[0528] Prompt Sentence Examples

[0529] "What are the characteristics of short hairstyles suitable for oval faces?"

[0530] The system allows users to easily find the hairstyle that best suits them even while driving autonomously, enabling them to make effective use of their time in the car. The present invention improves the quality of entertainment and relaxation in the car, further enriching the user experience.

[0531] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0532] Step 1:

[0533] Initializing the user interface

[0534] Users open the in-car display or smartphone app, and the startup screen prompts them to either take a photo of themselves or upload an existing photo.

[0535] Input: Launch app

[0536] Output: Shows option to take or upload a photo of your face

[0537] Step 2:

[0538] Acquiring a facial photo

[0539] Users can take a photo of themselves or upload an existing photo.

[0540] Input: User selects a photo of their face (takes or uploads)

[0541] Output: Facial photo data taken or uploaded

[0542] Step 3:

[0543] Send a photo of your face

[0544] The terminal transmits the acquired facial photograph to a server via the in-car communication network.

[0545] Input: Facial photo data

[0546] Output: Facial photo data transferred to the server

[0547] Step 4:

[0548] Save face photo

[0549] The server stores the received facial photos in data storage (e.g., AWS S3 bucket).

[0550] Input: Facial photo data sent to the server

[0551] Output: Saved face photo data

[0552] Step 5:

[0553] Analysis using face recognition models

[0554] The server analyzes the stored facial photos using a facial recognition model (e.g., TensorFlow or OpenCV), extracting features such as the shape of the face, and the position and size of the eyes, nose, and mouth, and converting them into numerical data.

[0555] Input: Saved face photo data

[0556] Output: Extracted facial feature data

[0557] Step 6:

[0558] Matching with a hairstyle database

[0559] The server compares the extracted facial feature data with a hairstyle database and selects multiple suitable hairstyles.

[0560] Input: Facial feature data

[0561] Output: A list of selected hairstyles

[0562] Step 7:

[0563] Returning the results

[0564] The server returns the selected hairstyle list, along with detailed information and styling advice, to the user's device.

[0565] Input: A list of selected hairstyles

[0566] Output: Returning the results to the user's device

[0567] Step 8:

[0568] Display on the in-car display

[0569] The device displays the received results on the in-car display or smartphone, presenting the user with multiple hairstyle options and styling advice.

[0570] Input: Returned result data

[0571] Output: Hairstyle options and advice displayed on the screen

[0572] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0573] The present invention relates to a system that helps users quickly and efficiently select the most suitable hairstyle, and also to a system that makes optimal suggestions taking into account the user's emotions. This system involves a process in which a user takes and uploads a facial photo, and a server not only analyzes the facial photo but also recognizes the user's emotions.

[0574] Specific implementation methods of the system

[0575] User interface (terminal side)

[0576] First, the user launches the application. For user convenience, the application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user can then take a photo of their face or select an existing photo and upload it to the application.

[0577] Server Processing

[0578] The device then sends the user's selected facial photo to the server, which receives the photo and stores the data, then requests a facial recognition model to analyze the photo.

[0579] The facial recognition model performs a detailed analysis of facial features based on the received photograph. Specifically, it extracts features such as face shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth, and stores them as numerical data. Once the analysis is complete, the results are compared with the accumulated hairstyle database.

[0580] The hairstyle database stores detailed information about various hairstyles, and also lists which facial features each style is suited to. The server compares the analysis results with the information in the database and selects multiple hairstyles that are best suited to the user.

[0581] Introducing the Emotion Engine

[0582] In addition, in order for the emotion engine to recognize the user's emotions, the server adds a process to analyze the user's facial expressions and voice before suggesting a style. This engine analyzes the user's current emotional state from facial expressions and tone of voice.

[0583] Based on the analysis results of the emotion engine, the system can choose a hairstyle that best suits the user's emotions at that time. For example, if the user is in a good mood, it can suggest a challenging hairstyle, and if the user is in a bad mood, it can suggest a more stable hairstyle.

[0584] Response (terminal side)

[0585] Finally, the server sends the selected hairstyle and its details back to the device. The device receives this and suggests it to the user. Specifically, it displays a list of multiple optimal hairstyles with images based on the user's facial pattern and emotions. In addition, each hairstyle includes a comment such as "This style is perfect for your current mood" and the reason for the recommendation.

[0586] Additionally, styling advice and maintenance methods for the selected hairstyle are also displayed. For example, specific advice is provided such as, "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers."

[0587] Specific examples

[0588] For example, suppose User B uses this system and uploads a photo of his face. The server receives User B's photo and uses a facial recognition model to extract the characteristic "oval face." Furthermore, the emotion engine analyzes the photo and determines that User B is in a relaxed mood. Based on this information, the server suggests hairstyles (e.g., long waves or natural straight hair) that are optimal for an oval face and match a relaxed mood. The device displays these styles with images to User B and provides specific styling advice.

[0589] The system allows users to quickly and efficiently find hairstyles that suit not only their face shape but also their current mood, as well as how to maintain them, allowing them to easily try out styles at home without having to visit a specific hair salon.

[0590] The processing flow will be explained below.

[0591] Step 1:

[0592] The user launches the application and the device prompts them to take a photo of their face or upload an existing photo.

[0593] Step 2:

[0594] The user takes a photo of their face or selects and uploads an existing photo, and the device sends the selected photo to the server.

[0595] Step 3:

[0596] The server receives the facial photo sent from the device, temporarily stores it, and passes it to a facial recognition model.

[0597] Step 4:

[0598] The facial recognition model receives a photo and performs a detailed analysis of facial features, including facial shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth.

[0599] Step 5:

[0600] The server then compares the analysis results with a hairstyle database, which contains detailed information about various hairstyles and which facial features each style is suited to.

[0601] Step 6:

[0602] Based on the matching results, the server selects multiple hairstyles that best suit the user.

[0603] Step 7:

[0604] The emotion engine analyzes facial expressions and tone of voice to recognize the user's emotions, and users can also provide photos, video clips, and audio.

[0605] Step 8:

[0606] The server obtains the user's emotional state recognized by the emotion engine, for example, the emotion engine indicates the user's emotional state such as "relaxed" or "tense."

[0607] Step 9:

[0608] The server considers the analysis results and the emotion recognition results from the emotion engine to reselect the most suitable hairstyle. For example, it can suggest a natural hairstyle for a relaxed user, and a stable hairstyle for a nervous user.

[0609] Step 10:

[0610] The server sends the selected hairstyle and its details to the device, which receives it and presents it to the user.

[0611] Step 11:

[0612] The device then displays the received hairstyle suggestions and detailed information to the user, displaying a list of multiple hairstyles with images that are most suitable for the user based on their facial pattern and emotions.

[0613] Step 12:

[0614] For each hairstyle selected, the device will also provide specific styling and maintenance advice, such as "To maintain this short hairstyle, it is recommended to use wax to add volume."

[0615] Step 13:

[0616] Based on the presented hairstyles and advice, users can choose and try out the hairstyle that best suits them. This process allows users to efficiently and quickly find a hairstyle that suits them.

[0617] Example 2

[0618] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0619] Conventional hairstyle suggestion systems only consider the user's face shape, which means they are unable to suggest styles that match the user's emotions or mood. This can prevent users from choosing the hairstyle that best suits their mood at the time, leading to a decrease in satisfaction.

[0620] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0621] In this invention, the server includes means for allowing a user to upload a facial photo, means for receiving and storing the uploaded facial photo, means for using an image recognition model to analyze the stored facial photo, means for comparing the analysis result with an accumulated hairstyle database, means for using an emotion recognition engine to analyze the user's emotion, means for selecting an optimal hairstyle based on the user's emotional state and facial features, and means for presenting the selected hairstyle and its details to the user, thereby enabling the user to know the optimal hairstyle based not only on the shape of their face but also on their current mood.

[0622] "User" means an individual who uses the System.

[0623] A "face photo" is image data of a user's face.

[0624] "Means for uploading" refers to the function that allows a user to send data from a terminal to a server.

[0625] "Means for receiving and storing" refers to the function by which the server receives data from the terminal and stores it.

[0626] An "image recognition model" is an algorithm or software used to analyze facial photographs.

[0627] "Means for matching" is a function for comparing the analysis results with information in the database.

[0628] An "emotion recognition engine" is an algorithm or software for analyzing a user's emotions.

[0629] "Emotional state" is information that indicates the user's current psychological state.

[0630] A "hairstyle database" is a collection of data that records various hairstyles and the facial features and emotional states that are suitable for each hairstyle.

[0631] The "best hairstyle" is the hairstyle that best suits the user's facial features and emotional state.

[0632] The "means for presenting details" is a function for displaying information about the selected hairstyle to the user.

[0633] The present invention relates to a system that assists a user in quickly and efficiently selecting an optimal hairstyle, and further relates to a system that makes optimal suggestions taking into account the user's feelings.

[0634] First, the user launches the application on their device. The application provides an interface for the user to take a photo of their face or upload an existing photo. Once the user has taken or uploaded a photo of their face, the device sends the photo data to a server. The data is securely transmitted using encryption protocols such as TLS (Transport Layer Security).

[0635] The server receives the facial photo data sent from the device and stores it in a database. The server then analyzes the facial photo using an image recognition model. This image recognition model uses a facial recognition API provided by a common cloud service (such as Azure Face API). Through the analysis, facial features such as the shape of the face and the position of the eyes, nose, and mouth are extracted and stored as numerical data.

[0636] The server then uses an emotion recognition engine, such as Google Cloud Natural Language API or IBM Watson's Tone Analyzer, to analyze the user's emotional state by analyzing their facial expressions and tone of voice.

[0637] The server then compares the results of these analyses with a database of accumulated hairstyles, which contains a variety of hairstyles and which facial features and emotional states each style is suited to. By comparing the results with the analysis, the server selects the hairstyle that best suits the user. The selected style also includes detailed information and styling advice.

[0638] The server sends information about the selected hairstyle back to the device, which receives it and presents it to the user. The information presented includes an image of the selected hairstyle, the reason for the recommendation, and specific styling and maintenance methods. For example, advice such as "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers" is also provided.

[0639] For example, when User A uses the app and uploads a photo of their face, the server receives the photo and extracts the characteristic "oval face" using the Azure Face API. Furthermore, it determines that the user is in a relaxed mood using the Google Cloud Natural Language API. Based on this information, the server selects a hairstyle, such as long waves or natural straight, that is best suited to a relaxed mood and presents it to User A along with detailed styling advice.

[0640] An example of a prompt to be input to a generative AI model might be, "Describe a system that suggests the best hairstyle based on a face photo uploaded by a user. The system combines facial recognition and emotion recognition to suggest a style that matches the user's current mood. Please also mention what software and hardware you use."

[0641] The system allows users to quickly and efficiently find the perfect hairstyle based not only on their face shape but also on their current mood.

[0642] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0643] Step 1:

[0644] When a user launches the application, the device displays a screen prompting the user to take a photo of their face or upload an existing photo. Once the user takes or selects a photo of their face, the image data is temporarily stored on the device.

[0645] Input: Facial photo data taken or selected by the user.

[0646] Output: Temporarily saved face photo data.

[0647] Step 2:

[0648] When the user selects a face photo and presses the upload button, the device sends the face photo data to the server using encrypted data communication, using protocols such as TLS (Transport Layer Security).

[0649] Input: Temporarily saved facial photo data.

[0650] Output: Facial photo data sent to the server.

[0651] Step 3:

[0652] The server receives the facial photo data sent from the device and stores it in a database.

[0653] Input: Facial photo data sent from the device.

[0654] Output: Facial photo data stored in a database.

[0655] Step 4:

[0656] The server sends the stored facial photo data to a facial recognition model (e.g., an image recognition API) for analysis, where features such as the shape of the face and the position of the eyes, nose, and mouth are extracted as numerical data.

[0657] Input: Facial photo data stored in the database.

[0658] Output: Numerical data representing facial features.

[0659] Step 5:

[0660] The server uses an emotion recognition engine (e.g., an emotion analysis API) to analyze the user's emotions. It analyzes the user's facial expressions and tone of voice to determine their current emotional state.

[0661] Input: Facial photo data stored in a database and real-time audio data (if required).

[0662] Output: Parsed user emotional state data.

[0663] Step 6:

[0664] The server compares the numerical data obtained from the facial recognition model and the emotional state data obtained from the emotion recognition engine with a hairstyle database. The database contains multiple hairstyles and the facial features and emotional states that are suitable for each. The server then selects the most suitable hairstyle.

[0665] Input: Numerical data representing facial features and emotional state data.

[0666] Output: Data on the results of selecting the best hairstyle.

[0667] Step 7:

[0668] The server then returns detailed information about the selected hairstyle to the device, including an image of the selected hairstyle, the reason for its recommendation, and specific styling and maintenance methods.

[0669] Input: Data on the results of selecting the best hairstyle.

[0670] Output: Hairstyle information returned to the device.

[0671] Step 8:

[0672] The device receives the selected hairstyle information returned from the server, and based on the received information, displays a list of hairstyle images to the user, along with the reasons why each style is recommended and specific styling advice.

[0673] Input: Hairstyle information returned from the server.

[0674] Output: A list of hairstyle images and advice information presented to the user.

[0675] (Application example 2)

[0676] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0677] Conventional hairstyle suggestion systems only considered the user's facial features when proposing hairstyles, making it impossible to provide optimal suggestions that reflected the user's current emotional state. Furthermore, the suggested hairstyles could only be applied to individual devices or at home, making them difficult to use in physical stores. There was a need to solve these problems and realize hairstyle suggestions that better meet the user's needs.

[0678] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to upload a facial photo, means for receiving and saving the uploaded facial photo, means for using a face recognition model to analyze the saved facial photo, means for analyzing the emotional state of the user using an emotion recognition model, means for suggesting an optimal hairstyle based on the user's facial features and emotional state, and means for displaying hairstyles in real time using a device installed in a physical store. This makes it possible to suggest an optimal hairstyle taking into account the user's emotional state, further promoting use in physical stores.

[0679] "Means for users to upload facial photos" refers to terminals or applications that provide the functionality for users to take a photo of their face and send it to the system.

[0680] "Means for receiving and storing uploaded facial photographs" refers to software or systems that provide the function of receiving and storing facial photographs uploaded by users on the server side.

[0681] The "means for using a facial recognition model to analyze stored facial photographs" is a function that uses a facial recognition algorithm to analyze stored facial photographs and extract facial features.

[0682] "Means for selecting the most suitable hairstyle based on the comparison results" refers to a function that compares the results of facial recognition analysis with a hairstyle database and selects the most suitable hairstyle.

[0683] The "means for presenting the selected hairstyle and its details to the user" is an interface that has the function of displaying an image and information about the selected hairstyle to the user.

[0684] The "means for analyzing the emotional state of a user using an emotion recognition model" is an emotion recognition algorithm for identifying the emotional state of a user through analysis of the user's facial expressions and voice.

[0685] "Means for suggesting the most suitable hairstyle based on the user's facial features and emotional state" is a function that comprehensively evaluates the user's facial shape and emotional state, and selects and suggests the most suitable hairstyle.

[0686] "Means for displaying hairstyles in real time using devices installed in physical stores" refers to a function that displays hairstyle suggestions in real time using devices such as mirrors and tablets installed in physical stores.

[0687] The present invention is a system that helps users quickly and efficiently select the most suitable hairstyle, and also provides optimal suggestions taking into account the user's emotions. This system operates through a smart mirror system installed in a physical store. Specific embodiments of the system are described below.

[0688] User interface (terminal side)

[0689] First, the user stands in front of a smart mirror installed in a brick-and-mortar store, which has a built-in camera that automatically takes a photo of the user's face, which is then uploaded to the system.

[0690] Server Processing

[0691] The server receives and stores the uploaded face photo. It then uses a facial recognition model (e.g., OpenCV, Dlib) to analyze the face photo and extract detailed facial features, including face shape (e.g., round, oval, angular). It then uses an emotion recognition model (e.g., Microsoft Azure Face API, Amazon Rekognition) to analyze the user's current emotional state from their facial expressions and voice.

[0692] Once the facial features and emotional state have been analyzed, the results are compared against a hairstyle database that contains detailed information about various hairstyles and which styles suit which facial features.

[0693] Selection and proposal

[0694] The server compares the analysis results with the database information and selects multiple hairstyles that are best suited to the user. Furthermore, based on the analysis results of the emotion engine, it selects the most suitable hairstyle taking into account the user's emotions at the time. For example, if the user is relaxed, it suggests a hairstyle that gives a sense of stability.

[0695] Response (terminal side)

[0696] Finally, the server sends the selected hairstyle and its details back to the smart mirror. The smart mirror receives this and displays suggestions to the user in real time. Specifically, it displays multiple optimal hairstyles based on the user's facial patterns and emotions, along with images. In addition, for each hairstyle, comments such as "This style is perfect for your current mood" and reasons for the recommendation are included. Styling advice and maintenance methods for the selected hairstyle are also displayed.

[0697] Specific examples

[0698] For example, when a user stands in front of a smart mirror, a photo of their face is automatically taken and uploaded to the system. The server receives the photo and uses a facial recognition model to extract the characteristic of an "oval face." An emotion recognition model analyzes the user's state as relaxed. Based on this information, the server selects a hairstyle (e.g., soft waves or a bob) that best suits the user's face shape and relaxed mood. The results are displayed in real time on the smart mirror, allowing the user to instantly see the optimal hairstyle and styling method.

[0699] Example prompts for generative AI models

[0700] "A 40-year-old woman comes into the salon looking for a stylish hairstyle, but wants to maintain a calm look. She has an oval face and is currently relaxed. We suggest the best hairstyle and styling method for her."

[0701] The system allows users to quickly and efficiently find hairstyles that suit their face shape and current mood, allowing them to easily try out styles at home or in a brick-and-mortar store without having to visit a specific salon.

[0702] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0703] Step 1:

[0704] A user stands in front of a smart mirror installed in a physical store and takes a photo of their face. When the user stands in front of the smart mirror, the smart mirror automatically takes a photo of their face using its built-in camera and collects the data. The input at this point is the user's face photo, and the image data is sent to the server.

[0705] Step 2:

[0706] The server receives and stores the facial photo sent from the smart mirror. This stores the facial photo data in the server and prepares it for analysis. The input is the facial photo data sent in step 1, and the output is the stored facial photo data.

[0707] Step 3:

[0708] The server uses a facial recognition model to analyze the stored facial photos. This facial recognition model (e.g., OpenCV, Dlib) analyzes facial features (round, oval, angular, etc.) in detail and extracts them as numerical data. The input is the stored facial photo data, and the output is facial feature data.

[0709] Step 4:

[0710] The server uses the facial feature data extracted by the facial recognition model to analyze the user's emotional state using an emotion recognition model (e.g., Microsoft Azure Face API, Amazon Rekognition). The emotion recognition model analyzes the user's facial expressions and voice to identify their emotional state, such as relaxed or excited. The input is facial feature data and facial expression / voice data, and the output is emotional state data.

[0711] Step 5:

[0712] The server compares the facial feature data and emotional state data with the hairstyle database. Based on the comparison results, it selects the most suitable hairstyle. The hairstyle database contains information on which facial features and emotional state each hairstyle is suited to. The input is facial feature data and emotional state data, and the output is the most suitable hairstyle data.

[0713] Step 6:

[0714] The server sends the selected hairstyle and its details back to the smart mirror, which now includes an image of the selected hairstyle and styling advice. The input is the optimal hairstyle data, and the output is the suggestion data sent to the smart mirror.

[0715] Step 7:

[0716] The smart mirror displays hairstyle suggestions received from the server to the user in real time. The user can then select the best hairstyle from the multiple hairstyles displayed. The displayed content includes an image of the selected hairstyle, detailed information, and styling advice. The input is the suggestion data sent from the server, and the output is the information visually presented to the user.

[0717] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0718] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0719] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0720] [Third embodiment]

[0721] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0722] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0723] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0724] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0725] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0726] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0727] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0728] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0729] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0730] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0731] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0732] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0733] The present invention relates to a system that helps users quickly and efficiently find the hairstyle that best suits them. The system mainly involves a process in which a user uploads a facial photo, a server analyzes the facial photo, and then suggests the most suitable hairstyle.

[0734] Specific implementation methods of the system

[0735] User interface (terminal side)

[0736] First, the user launches the application. For user convenience, the application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user can then take a photo of their face or select an existing photo and upload it to the application.

[0737] Server Processing

[0738] The device then sends the user's selected facial photo to the server, which receives the photo and stores the data, then requests a facial recognition model to analyze the photo.

[0739] The facial recognition model performs a detailed analysis of facial features based on the received photograph. Specifically, it extracts features such as face shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth, and stores them as numerical data. Once the analysis is complete, the results are compared with the accumulated hairstyle database.

[0740] The hairstyle database stores detailed information about various hairstyles, and also lists which facial features each style is suited to. The server compares the analysis results with the information in the database and selects multiple hairstyles that are best suited to the user.

[0741] Response (terminal side)

[0742] Finally, the server sends the selected hairstyle and its details back to the device. The device receives this and suggests it to the user. Specifically, it displays a list of multiple hairstyles that are best suited to the user's facial pattern, complete with images. In addition, each hairstyle is accompanied by a comment such as "This style is best suited to oval faces" and a reason for the recommendation.

[0743] Additionally, styling advice and maintenance methods for the selected hairstyle are also displayed. For example, specific advice is provided such as, "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers."

[0744] Specific examples

[0745] For example, let's say User A uses this system and uploads a photo of their face. The server receives User A's photo and uses a facial recognition model to extract the characteristic "oval face." The server then selects from a database the hairstyles most suitable for oval faces, suggesting short hair, bob, long waves, etc. The device displays these styles to User A along with images and provides specific styling advice.

[0746] This system allows users to quickly and efficiently find the hairstyle that best suits them and how to maintain it. It is expected that user satisfaction will be greatly improved as they can easily try out styles at home without having to visit a specific beauty salon.

[0747] The processing flow will be explained below.

[0748] Step 1:

[0749] The user launches the application and the device prompts them to take a photo of their face or upload an existing photo.

[0750] Step 2:

[0751] The user takes a photo of their face or selects and uploads an existing photo, and the device sends the selected photo to the server.

[0752] Step 3:

[0753] The server receives the facial photo sent from the device, temporarily stores it, and then passes the example facial photo to the facial recognition model.

[0754] Step 4:

[0755] The facial recognition model receives a photo and performs a detailed analysis of facial features, including facial shape (round, oval, angular, etc.) and the position and size of the eyes, nose, and mouth.

[0756] Step 5:

[0757] The server then compares the analysis results with a hairstyle database, which contains detailed information about various hairstyles and which facial features each style is suited to.

[0758] Step 6:

[0759] Based on the matching results, the server selects multiple hairstyles that best suit the user, and information about the selected hairstyle is generated and sent to the device.

[0760] Step 7:

[0761] The device displays the received hairstyle suggestions and detailed information to the user. Based on the user's facial pattern, multiple optimal hairstyles are displayed in a list with images.

[0762] Step 8:

[0763] For each hairstyle, the device will also provide specific styling and maintenance advice, such as "To maintain this short hairstyle, it is recommended to use wax to add volume."

[0764] Step 9:

[0765] Based on the presented hairstyles and advice, users can choose and try out the hairstyle that best suits them. This process allows users to efficiently and quickly find a hairstyle that suits them.

[0766] Example 1

[0767] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0768] In conventional methods, users often need a lot of time and effort to find the hairstyle that best suits them. Furthermore, advice from hairdressers depends on their individual experience, making it difficult to guarantee a consistent level of quality. The present invention aims to provide a system that helps users quickly and efficiently find the hairstyle that best suits them.

[0769] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0770] In this invention, the server includes means for users to upload facial photographs, means for receiving and saving the uploaded facial photographs, means for using a facial feature recognition model to analyze the saved facial photographs, means for extracting features such as facial shape and the positions and sizes of the eyes, nose, and mouth and saving them as numerical data, means for comparing the analysis results with an accumulated hairstyle database, means for selecting an optimal hairstyle based on the comparison results, and means for presenting the selected hairstyle and its details to the user, thereby enabling the user to quickly and efficiently find the optimal hairstyle for themselves and how to maintain it.

[0771] "User" refers to an individual who uses the system to find the hairstyle that best suits them.

[0772] "Facial photo" refers to image data of a user's face.

[0773] "Upload" refers to the act of a user using a device to send a photo of their face to the system.

[0774] "Receiving" refers to the act of the server receiving the facial photo sent by the user.

[0775] "Storage" refers to the act of the server retaining the received facial photo data in data storage.

[0776] A "facial feature recognition model" refers to an algorithm or software used to analyze facial features such as the shape of the face and the position and size of the eyes, nose, and mouth from a photograph.

[0777] "Numerical data" refers to quantitative data obtained by analyzing facial features using a facial feature recognition model.

[0778] A "hairstyle database" refers to a database that records detailed information about various hairstyles and which facial features each one is suited to.

[0779] "Matching" refers to the process of comparing the numerical data of the analysis results with information in a hairstyle database to find a matching hairstyle.

[0780] "Selection" refers to the act of choosing the hairstyle that best suits the user based on the matching results.

[0781] "Presenting" refers to the act of displaying the selected hairstyle and its detailed information to the user.

[0782] The present invention relates to a system that helps users quickly and efficiently find the hairstyle that best suits them. The system mainly involves a process in which a user uploads a facial photo, and a server analyzes the facial photo and suggests the most suitable hairstyle.

[0783] User interface (terminal side)

[0784] First, the user launches the dedicated application. The application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user then takes a photo of their face or selects an existing photo and uploads it to the application.

[0785] Server Processing

[0786] Next, the device sends the uploaded facial photo to a server. The server saves the facial photo in a data storage device for receiving and saving facial photos. The server then launches a facial feature recognition model (e.g., OpenCV or AWS Rekognition) to analyze the facial photo. This model extracts features such as the shape of the face and the position and size of the eyes, nose, and mouth, and stores them as numerical data. The server then uses the numerical data resulting from the analysis to compare it with a hairstyle database. This database stores information about which hairstyles are suitable for which facial features.

[0787] Proposal Procedure

[0788] The server selects the optimal hairstyle for the user based on the matching results. It then returns the selected hairstyle and detailed information (e.g., reason for recommendation, styling advice, etc.) to the device. The device then makes suggestions to the user based on the received information. The displayed information includes which face shapes each hairstyle is suitable for, as well as specific styling and maintenance methods.

[0789] Specific examples

[0790] For example, consider the case where User A uses this system and uploads a photo of his / her face. The server receives the photo and uses a facial feature recognition model to extract the characteristic "oval face." The server then selects the hairstyle best suited to an oval face (e.g., short hair, bob, long waves) from a hairstyle database. Based on this information, the device makes suggestions to User A with images and provides specific styling advice.

[0791] Prompt Sentence Examples

[0792] Here are some example prompts to input to the generative AI model:

[0793] Please explain the process of the system that allows users to upload a face photo and quickly and efficiently suggest the best hairstyle based on that photo. Please explain the specific operations, model, and database used for each processing step (face photo upload, face photo analysis, hairstyle selection, and hairstyle suggestion).

[0794] This prompt allows the generative AI model to generate more specific explanations of the system's detailed processing.

[0795] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0796] Step 1:

[0797] Users upload a photo of their face

[0798] Users launch the application and either take a photo of their face or select an existing photo.

[0799] Users can import a photo of their face and click the upload button to save the photo to their device.

[0800] Input: A user-selected face photo

[0801] Output: Facial photo data stored on the device

[0802] Step 2:

[0803] The device sends a photo of the face to the server

[0804] The device packages the stored facial photo data and generates an HTTP request to send it to the server.

[0805] The terminal sends the request to the server.

[0806] Input: Facial photo data stored on the device

[0807] Output: Facial photo data received by the server

[0808] Step 3:

[0809] The server stores the face photo.

[0810] The server validates the received facial photo data to ensure it is in the correct format.

[0811] Store face photo data in a file system or database.

[0812] Input: Received facial photo data

[0813] Output: Facial photo data stored on the server

[0814] Step 4:

[0815] The server analyzes the facial photo

[0816] The server runs a facial feature recognition model (e.g., OpenCV, AWS Rekognition) to analyze the face photo.

[0817] The facial recognition model extracts features such as the shape of the face and the position and size of the eyes, nose, and mouth, and stores them as numerical data.

[0818] Input: Facial photo data stored on the server

[0819] Output: Extracted facial feature data

[0820] Step 5:

[0821] The server compares the analysis results with the hairstyle database.

[0822] The server searches a hairstyle database based on the facial feature data.

[0823] Calculate the suitability of each hairstyle and select the most suitable style.

[0824] Input: extracted facial feature data, hairstyle database

[0825] Output: Selected optimal hairstyle data

[0826] Step 6:

[0827] The server sends the selected hairstyle back to the device.

[0828] The server packages the selected hairstyle and its detailed information (e.g., recommendation reason, styling advice) for transmission back to the terminal.

[0829] The server transmits the package to the terminal.

[0830] Input: Selected optimal hairstyle data

[0831] Output: Hairstyle suggestion data sent to the device

[0832] Step 7:

[0833] The device will display hairstyle suggestions to the user.

[0834] The terminal analyzes the received hairstyle suggestion data and updates the user interface.

[0835] It displays a list of hairstyles that best suit the user's face photo, along with a description and styling advice for each hairstyle.

[0836] Input: Hairstyle suggestion data received from the server

[0837] Output: Best hairstyles and styling advice displayed to the user

[0838] The above is the flow of the system program processing. At each step, specific operations and data flows are explained in detail, and the functionality of the entire system is clarified.

[0839] (Application example 1)

[0840] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0841] As autonomous vehicles become more widespread, there is a demand for enhanced in-car entertainment and relaxation. However, current systems do not allow users to find hairstyles that suit them, which means they are unable to make effective use of their time while driving autonomously. In addition, there is a lack of a concrete platform to improve the user experience in selecting hairstyles.

[0842] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0843] In this invention, the server includes: means for a user to upload a facial photo; means for receiving and saving the uploaded facial photo; means for using a facial recognition model to analyze the saved facial photo; means for comparing the analysis result with an accumulated hairstyle database; means for selecting an optimal hairstyle based on the comparison result; means for presenting the selected hairstyle and its details to the user; means for taking or uploading a facial photo using a display in the autonomous vehicle or a smartphone app; means for transmitting the facial photo to the server via an in-vehicle communication network; and means for displaying a list of selected hairstyles with images on an in-vehicle display. This allows users to easily find a hairstyle that suits them even during autonomous driving, making effective use of their time in the car.

[0844] A "User" is an individual who wishes to use the system to upload a photo of their face and find a hairstyle that suits them.

[0845] A "face photo" is image data that captures the user's facial features in detail.

[0846] An "uploading means" is a device or interface for taking a facial photograph or selecting an existing photograph and sending it to the system.

[0847] The "means for receiving and storing" is a data storage function for storing uploaded facial photos on a server.

[0848] A "facial recognition model" is a machine learning algorithm or software that analyzes photographs of faces and extracts facial features.

[0849] A "hairstyle database" is a database that stores various hairstyles and their characteristics.

[0850] The "matching means" is the process of comparing the analyzed facial features with a hairstyle database and selecting a suitable hairstyle.

[0851] The "best hairstyle" is the hairstyle that is determined to best suit the user's facial features.

[0852] The "presentation means" refers to a display or application for visually displaying an image and detailed information of the selected hairstyle to the user.

[0853] An "autonomous vehicle" is a vehicle that has the ability to automatically perform driving operations.

[0854] "Display" refers to a display device installed in the vehicle to visually display information from the system.

[0855] A "smartphone app" is an application that is installed on a smartphone and that uploads facial photos and displays analysis results as part of the system's functions.

[0856] The "communication network" is an internet connection means for sending facial photos from inside the vehicle to a server.

[0857] The "means for displaying with an image" is a display means for providing the user with visual information about the selected hairstyle.

[0858] This invention is a system that allows users to efficiently find the hairstyle that best suits them in an autonomous vehicle. The system configuration is mainly divided into three parts: the user interface, server processing, and in-car display.

[0859] User Interface

[0860] Users first access the system using the in-car display or their smartphone app. Once they access the system, a screen appears prompting them to either take a photo of their face or upload an existing photo. Users can then take a photo of their face or select an existing photo to upload.

[0861] Server Processing

[0862] The uploaded facial photo is sent to the server via the in-car communication network, and the server processes it using the following procedure.

[0863] 1. Save your face photo

[0864] The server stores the received facial photos in a database.

[0865] 2. Analysis using face recognition model

[0866] The server uses a facial recognition model (e.g., TensorFlow or OpenCV) to analyze the facial photo and extract facial features (shape, position of eyes and nose, etc.).

[0867] 3. Matching with hairstyle database

[0868] Based on the extracted facial features, the server compares them with a hairstyle database and selects multiple suitable hairstyles, each of which includes detailed information about which facial features are best suited to that style.

[0869] 4. Returning the results

[0870] The server then sends a list of selected hairstyles, along with detailed information and styling advice, back to the user's device.

[0871] Display on the in-car display

[0872] The results are then displayed on a display in the car or on a smartphone screen. Users can then choose from a selection of hairstyles based on their facial features. Each hairstyle comes with specific styling advice and maintenance instructions.

[0873] Specific examples

[0874] For example, suppose a user uploads a photo of their face while in the car. The server receives the photo and analyzes it using a facial recognition model. As a result of the analysis, characteristics such as an "oval face" are extracted. The server then selects a hairstyle from a hairstyle database that is best suited to an oval face, such as short hair, bob, or long waves. The selected hairstyle is then displayed on the in-car display along with styling advice.

[0875] Prompt Sentence Examples

[0876] "What are the characteristics of short hairstyles suitable for oval faces?"

[0877] The system allows users to easily find the hairstyle that best suits them even while driving autonomously, enabling them to make effective use of their time in the car. The present invention improves the quality of entertainment and relaxation in the car, further enriching the user experience.

[0878] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0879] Step 1:

[0880] Initializing the user interface

[0881] Users open the in-car display or smartphone app, and the startup screen prompts them to either take a photo of themselves or upload an existing photo.

[0882] Input: Launch app

[0883] Output: Shows option to take or upload a photo of your face

[0884] Step 2:

[0885] Acquiring a facial photo

[0886] Users can take a photo of themselves or upload an existing photo.

[0887] Input: User selects a photo of their face (takes or uploads)

[0888] Output: Facial photo data taken or uploaded

[0889] Step 3:

[0890] Send a photo of your face

[0891] The terminal transmits the acquired facial photograph to a server via the in-car communication network.

[0892] Input: Facial photo data

[0893] Output: Facial photo data transferred to the server

[0894] Step 4:

[0895] Save face photo

[0896] The server stores the received facial photos in data storage (e.g., AWS S3 bucket).

[0897] Input: Facial photo data sent to the server

[0898] Output: Saved face photo data

[0899] Step 5:

[0900] Analysis using face recognition models

[0901] The server analyzes the stored facial photos using a facial recognition model (e.g., TensorFlow or OpenCV), extracting features such as the shape of the face, and the position and size of the eyes, nose, and mouth, and converting them into numerical data.

[0902] Input: Saved face photo data

[0903] Output: Extracted facial feature data

[0904] Step 6:

[0905] Matching with a hairstyle database

[0906] The server compares the extracted facial feature data with a hairstyle database and selects multiple suitable hairstyles.

[0907] Input: Facial feature data

[0908] Output: A list of selected hairstyles

[0909] Step 7:

[0910] Returning the results

[0911] The server returns the selected hairstyle list, along with detailed information and styling advice, to the user's device.

[0912] Input: A list of selected hairstyles

[0913] Output: Returning the results to the user's device

[0914] Step 8:

[0915] Display on the in-car display

[0916] The device displays the received results on the in-car display or smartphone, presenting the user with multiple hairstyle options and styling advice.

[0917] Input: Returned result data

[0918] Output: Hairstyle options and advice displayed on the screen

[0919] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0920] The present invention relates to a system that helps users quickly and efficiently select the most suitable hairstyle, and also to a system that makes optimal suggestions taking into account the user's emotions. This system involves a process in which a user takes and uploads a facial photo, and a server not only analyzes the facial photo but also recognizes the user's emotions.

[0921] Specific implementation methods of the system

[0922] User interface (terminal side)

[0923] First, the user launches the application. For user convenience, the application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user can then take a photo of their face or select an existing photo and upload it to the application.

[0924] Server Processing

[0925] The device then sends the user's selected facial photo to the server, which receives the photo and stores the data, then requests a facial recognition model to analyze the photo.

[0926] The facial recognition model performs a detailed analysis of facial features based on the received photograph. Specifically, it extracts features such as face shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth, and stores them as numerical data. Once the analysis is complete, the results are compared with the accumulated hairstyle database.

[0927] The hairstyle database stores detailed information about various hairstyles, and also lists which facial features each style is suited to. The server compares the analysis results with the information in the database and selects multiple hairstyles that are best suited to the user.

[0928] Introducing the Emotion Engine

[0929] In addition, in order for the emotion engine to recognize the user's emotions, the server adds a process to analyze the user's facial expressions and voice before suggesting a style. This engine analyzes the user's current emotional state from facial expressions and tone of voice.

[0930] Based on the analysis results of the emotion engine, the system can choose a hairstyle that best suits the user's emotions at that time. For example, if the user is in a good mood, it can suggest a challenging hairstyle, and if the user is in a bad mood, it can suggest a more stable hairstyle.

[0931] Response (terminal side)

[0932] Finally, the server sends the selected hairstyle and its details back to the device. The device receives this and suggests it to the user. Specifically, it displays a list of multiple optimal hairstyles with images based on the user's facial pattern and emotions. In addition, each hairstyle includes a comment such as "This style is perfect for your current mood" and the reason for the recommendation.

[0933] Additionally, styling advice and maintenance methods for the selected hairstyle are also displayed. For example, specific advice is provided such as, "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers."

[0934] Specific examples

[0935] For example, suppose User B uses this system and uploads a photo of his face. The server receives User B's photo and uses a facial recognition model to extract the characteristic "oval face." Furthermore, the emotion engine analyzes the photo and determines that User B is in a relaxed mood. Based on this information, the server suggests hairstyles (e.g., long waves or natural straight hair) that are optimal for an oval face and match a relaxed mood. The device displays these styles with images to User B and provides specific styling advice.

[0936] The system allows users to quickly and efficiently find hairstyles that suit not only their face shape but also their current mood, as well as how to maintain them, allowing them to easily try out styles at home without having to visit a specific hair salon.

[0937] The processing flow will be explained below.

[0938] Step 1:

[0939] The user launches the application and the device prompts them to take a photo of their face or upload an existing photo.

[0940] Step 2:

[0941] The user takes a photo of their face or selects and uploads an existing photo, and the device sends the selected photo to the server.

[0942] Step 3:

[0943] The server receives the facial photo sent from the device, temporarily stores it, and passes it to a facial recognition model.

[0944] Step 4:

[0945] The facial recognition model receives a photo and performs a detailed analysis of facial features, including facial shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth.

[0946] Step 5:

[0947] The server then compares the analysis results with a hairstyle database, which contains detailed information about various hairstyles and which facial features each style is suited to.

[0948] Step 6:

[0949] Based on the matching results, the server selects multiple hairstyles that best suit the user.

[0950] Step 7:

[0951] The emotion engine analyzes facial expressions and tone of voice to recognize the user's emotions, and users can also provide photos, video clips, and audio.

[0952] Step 8:

[0953] The server obtains the user's emotional state recognized by the emotion engine, for example, the emotion engine indicates the user's emotional state such as "relaxed" or "tense."

[0954] Step 9:

[0955] The server considers the analysis results and the emotion recognition results from the emotion engine to reselect the most suitable hairstyle. For example, it can suggest a natural hairstyle for a relaxed user, and a stable hairstyle for a nervous user.

[0956] Step 10:

[0957] The server sends the selected hairstyle and its details to the device, which receives it and presents it to the user.

[0958] Step 11:

[0959] The device then displays the received hairstyle suggestions and detailed information to the user, displaying a list of multiple hairstyles with images that are most suitable for the user based on their facial pattern and emotions.

[0960] Step 12:

[0961] For each hairstyle selected, the device will also provide specific styling and maintenance advice, such as "To maintain this short hairstyle, it is recommended to use wax to add volume."

[0962] Step 13:

[0963] Based on the presented hairstyles and advice, users can choose and try out the hairstyle that best suits them. This process allows users to efficiently and quickly find a hairstyle that suits them.

[0964] Example 2

[0965] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0966] Conventional hairstyle suggestion systems only consider the user's face shape, which means they are unable to suggest styles that match the user's emotions or mood. This can prevent users from choosing the hairstyle that best suits their mood at the time, leading to a decrease in satisfaction.

[0967] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0968] In this invention, the server includes means for allowing a user to upload a facial photo, means for receiving and storing the uploaded facial photo, means for using an image recognition model to analyze the stored facial photo, means for comparing the analysis result with an accumulated hairstyle database, means for using an emotion recognition engine to analyze the user's emotion, means for selecting an optimal hairstyle based on the user's emotional state and facial features, and means for presenting the selected hairstyle and its details to the user, thereby enabling the user to know the optimal hairstyle based not only on the shape of their face but also on their current mood.

[0969] "User" means an individual who uses the System.

[0970] A "face photo" is image data of a user's face.

[0971] "Means for uploading" refers to the function that allows a user to send data from a terminal to a server.

[0972] "Means for receiving and storing" refers to the function by which the server receives data from the terminal and stores it.

[0973] An "image recognition model" is an algorithm or software used to analyze facial photographs.

[0974] "Means for matching" is a function for comparing the analysis results with information in the database.

[0975] An "emotion recognition engine" is an algorithm or software for analyzing a user's emotions.

[0976] "Emotional state" is information that indicates the user's current psychological state.

[0977] A "hairstyle database" is a collection of data that records various hairstyles and the facial features and emotional states that are suitable for each hairstyle.

[0978] The "best hairstyle" is the hairstyle that best suits the user's facial features and emotional state.

[0979] The "means for presenting details" is a function for displaying information about the selected hairstyle to the user.

[0980] The present invention relates to a system that assists a user in quickly and efficiently selecting an optimal hairstyle, and further relates to a system that makes optimal suggestions taking into account the user's feelings.

[0981] First, the user launches the application on their device. The application provides an interface for the user to take a photo of their face or upload an existing photo. Once the user has taken or uploaded a photo of their face, the device sends the photo data to a server. The data is securely transmitted using encryption protocols such as TLS (Transport Layer Security).

[0982] The server receives the facial photo data sent from the device and stores it in a database. The server then analyzes the facial photo using an image recognition model. This image recognition model uses a facial recognition API provided by a common cloud service (such as Azure Face API). Through the analysis, facial features such as the shape of the face and the position of the eyes, nose, and mouth are extracted and stored as numerical data.

[0983] The server then uses an emotion recognition engine, such as Google Cloud Natural Language API or IBM Watson's Tone Analyzer, to analyze the user's emotional state by analyzing their facial expressions and tone of voice.

[0984] The server then compares the results of these analyses with a database of accumulated hairstyles, which contains a variety of hairstyles and which facial features and emotional states each style is suited to. By comparing the results with the analysis, the server selects the hairstyle that best suits the user. The selected style also includes detailed information and styling advice.

[0985] The server sends information about the selected hairstyle back to the device, which receives it and presents it to the user. The information presented includes an image of the selected hairstyle, the reason for the recommendation, and specific styling and maintenance methods. For example, advice such as "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers" is also provided.

[0986] For example, when User A uses the app and uploads a photo of their face, the server receives the photo and extracts the characteristic "oval face" using the Azure Face API. Furthermore, it determines that the user is in a relaxed mood using the Google Cloud Natural Language API. Based on this information, the server selects a hairstyle, such as long waves or natural straight, that is best suited to a relaxed mood and presents it to User A along with detailed styling advice.

[0987] An example of a prompt to be input to a generative AI model might be, "Describe a system that suggests the best hairstyle based on a face photo uploaded by a user. The system combines facial recognition and emotion recognition to suggest a style that matches the user's current mood. Please also mention what software and hardware you use."

[0988] The system allows users to quickly and efficiently find the perfect hairstyle based not only on their face shape but also on their current mood.

[0989] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0990] Step 1:

[0991] When a user launches the application, the device displays a screen prompting the user to take a photo of their face or upload an existing photo. Once the user takes or selects a photo of their face, the image data is temporarily stored on the device.

[0992] Input: Facial photo data taken or selected by the user.

[0993] Output: Temporarily saved face photo data.

[0994] Step 2:

[0995] When the user selects a face photo and presses the upload button, the device sends the face photo data to the server using encrypted data communication, using protocols such as TLS (Transport Layer Security).

[0996] Input: Temporarily saved facial photo data.

[0997] Output: Facial photo data sent to the server.

[0998] Step 3:

[0999] The server receives the facial photo data sent from the device and stores it in a database.

[1000] Input: Facial photo data sent from the device.

[1001] Output: Facial photo data stored in a database.

[1002] Step 4:

[1003] The server sends the stored facial photo data to a facial recognition model (e.g., an image recognition API) for analysis, where features such as the shape of the face and the position of the eyes, nose, and mouth are extracted as numerical data.

[1004] Input: Facial photo data stored in the database.

[1005] Output: Numerical data representing facial features.

[1006] Step 5:

[1007] The server uses an emotion recognition engine (e.g., an emotion analysis API) to analyze the user's emotions. It analyzes the user's facial expressions and tone of voice to determine their current emotional state.

[1008] Input: Facial photo data stored in a database and real-time audio data (if required).

[1009] Output: Parsed user emotional state data.

[1010] Step 6:

[1011] The server compares the numerical data obtained from the facial recognition model and the emotional state data obtained from the emotion recognition engine with a hairstyle database. The database contains multiple hairstyles and the facial features and emotional states that are suitable for each. The server then selects the most suitable hairstyle.

[1012] Input: Numerical data representing facial features and emotional state data.

[1013] Output: Data on the results of selecting the best hairstyle.

[1014] Step 7:

[1015] The server then returns detailed information about the selected hairstyle to the device, including an image of the selected hairstyle, the reason for its recommendation, and specific styling and maintenance methods.

[1016] Input: Data on the results of selecting the best hairstyle.

[1017] Output: Hairstyle information returned to the device.

[1018] Step 8:

[1019] The device receives the selected hairstyle information returned from the server, and based on the received information, displays a list of hairstyle images to the user, along with the reasons why each style is recommended and specific styling advice.

[1020] Input: Hairstyle information returned from the server.

[1021] Output: A list of hairstyle images and advice information presented to the user.

[1022] (Application example 2)

[1023] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1024] Conventional hairstyle suggestion systems only considered the user's facial features when proposing hairstyles, making it impossible to provide optimal suggestions that reflected the user's current emotional state. Furthermore, the suggested hairstyles could only be applied to individual devices or at home, making them difficult to use in physical stores. There was a need to solve these problems and realize hairstyle suggestions that better meet the user's needs.

[1025] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to upload a facial photo, means for receiving and saving the uploaded facial photo, means for using a face recognition model to analyze the saved facial photo, means for analyzing the emotional state of the user using an emotion recognition model, means for suggesting an optimal hairstyle based on the user's facial features and emotional state, and means for displaying hairstyles in real time using a device installed in a physical store. This makes it possible to suggest an optimal hairstyle taking into account the user's emotional state, further promoting use in physical stores.

[1026] "Means for users to upload facial photos" refers to terminals or applications that provide the functionality for users to take a photo of their face and send it to the system.

[1027] "Means for receiving and storing uploaded facial photographs" refers to software or systems that provide the function of receiving and storing facial photographs uploaded by users on the server side.

[1028] The "means for using a facial recognition model to analyze stored facial photographs" is a function that uses a facial recognition algorithm to analyze stored facial photographs and extract facial features.

[1029] "Means for selecting the most suitable hairstyle based on the comparison results" refers to a function that compares the results of facial recognition analysis with a hairstyle database and selects the most suitable hairstyle.

[1030] The "means for presenting the selected hairstyle and its details to the user" is an interface that has the function of displaying an image and information about the selected hairstyle to the user.

[1031] The "means for analyzing the emotional state of a user using an emotion recognition model" is an emotion recognition algorithm for identifying the emotional state of a user through analysis of the user's facial expressions and voice.

[1032] "Means for suggesting the most suitable hairstyle based on the user's facial features and emotional state" is a function that comprehensively evaluates the user's facial shape and emotional state, and selects and suggests the most suitable hairstyle.

[1033] "Means for displaying hairstyles in real time using devices installed in physical stores" refers to a function that displays hairstyle suggestions in real time using devices such as mirrors and tablets installed in physical stores.

[1034] The present invention is a system that helps users quickly and efficiently select the most suitable hairstyle, and also provides optimal suggestions taking into account the user's emotions. This system operates through a smart mirror system installed in a physical store. Specific embodiments of the system are described below.

[1035] User interface (terminal side)

[1036] First, the user stands in front of a smart mirror installed in a brick-and-mortar store, which has a built-in camera that automatically takes a photo of the user's face, which is then uploaded to the system.

[1037] Server Processing

[1038] The server receives and stores the uploaded face photo. It then uses a facial recognition model (e.g., OpenCV, Dlib) to analyze the face photo and extract detailed facial features, including face shape (e.g., round, oval, angular). It then uses an emotion recognition model (e.g., Microsoft Azure Face API, Amazon Rekognition) to analyze the user's current emotional state from their facial expressions and voice.

[1039] Once the facial features and emotional state have been analyzed, the results are compared against a hairstyle database that contains detailed information about various hairstyles and which styles suit which facial features.

[1040] Selection and proposal

[1041] The server compares the analysis results with the database information and selects multiple hairstyles that are best suited to the user. Furthermore, based on the analysis results of the emotion engine, it selects the most suitable hairstyle taking into account the user's emotions at the time. For example, if the user is relaxed, it suggests a hairstyle that gives a sense of stability.

[1042] Response (terminal side)

[1043] Finally, the server sends the selected hairstyle and its details back to the smart mirror. The smart mirror receives this and displays suggestions to the user in real time. Specifically, it displays multiple optimal hairstyles based on the user's facial patterns and emotions, along with images. In addition, for each hairstyle, comments such as "This style is perfect for your current mood" and reasons for the recommendation are included. Styling advice and maintenance methods for the selected hairstyle are also displayed.

[1044] Specific examples

[1045] For example, when a user stands in front of a smart mirror, a photo of their face is automatically taken and uploaded to the system. The server receives the photo and uses a facial recognition model to extract the characteristic of an "oval face." An emotion recognition model analyzes the user's state as relaxed. Based on this information, the server selects a hairstyle (e.g., soft waves or a bob) that best suits the user's face shape and relaxed mood. The results are displayed in real time on the smart mirror, allowing the user to instantly see the optimal hairstyle and styling method.

[1046] Example prompts for generative AI models

[1047] "A 40-year-old woman comes into the salon looking for a stylish hairstyle, but wants to maintain a calm look. She has an oval face and is currently relaxed. We suggest the best hairstyle and styling method for her."

[1048] The system allows users to quickly and efficiently find hairstyles that suit their face shape and current mood, allowing them to easily try out styles at home or in a brick-and-mortar store without having to visit a specific salon.

[1049] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1050] Step 1:

[1051] A user stands in front of a smart mirror installed in a physical store and takes a photo of their face. When the user stands in front of the smart mirror, the smart mirror automatically takes a photo of their face using its built-in camera and collects the data. The input at this point is the user's face photo, and the image data is sent to the server.

[1052] Step 2:

[1053] The server receives and stores the facial photo sent from the smart mirror. This stores the facial photo data in the server and prepares it for analysis. The input is the facial photo data sent in step 1, and the output is the stored facial photo data.

[1054] Step 3:

[1055] The server uses a facial recognition model to analyze the stored facial photos. This facial recognition model (e.g., OpenCV, Dlib) analyzes facial features (round, oval, angular, etc.) in detail and extracts them as numerical data. The input is the stored facial photo data, and the output is facial feature data.

[1056] Step 4:

[1057] The server uses the facial feature data extracted by the facial recognition model to analyze the user's emotional state using an emotion recognition model (e.g., Microsoft Azure Face API, Amazon Rekognition). The emotion recognition model analyzes the user's facial expressions and voice to identify their emotional state, such as relaxed or excited. The input is facial feature data and facial expression / voice data, and the output is emotional state data.

[1058] Step 5:

[1059] The server compares the facial feature data and emotional state data with the hairstyle database. Based on the comparison results, it selects the most suitable hairstyle. The hairstyle database contains information on which facial features and emotional state each hairstyle is suited to. The input is facial feature data and emotional state data, and the output is the most suitable hairstyle data.

[1060] Step 6:

[1061] The server sends the selected hairstyle and its details back to the smart mirror, which now includes an image of the selected hairstyle and styling advice. The input is the optimal hairstyle data, and the output is the suggestion data sent to the smart mirror.

[1062] Step 7:

[1063] The smart mirror displays hairstyle suggestions received from the server to the user in real time. The user can then select the best hairstyle from the multiple hairstyles displayed. The displayed content includes an image of the selected hairstyle, detailed information, and styling advice. The input is the suggestion data sent from the server, and the output is the information visually presented to the user.

[1064] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1065] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1066] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1067] [Fourth embodiment]

[1068] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1069] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1070] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1071] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1072] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1073] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1074] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1075] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1076] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1077] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1078] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1079] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1080] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1081] The present invention relates to a system that helps users quickly and efficiently find the hairstyle that best suits them. The system mainly involves a process in which a user uploads a facial photo, a server analyzes the facial photo, and then suggests the most suitable hairstyle.

[1082] Specific implementation methods of the system

[1083] User interface (terminal side)

[1084] First, the user launches the application. For user convenience, the application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user can then take a photo of their face or select an existing photo and upload it to the application.

[1085] Server Processing

[1086] The device then sends the user's selected facial photo to the server, which receives the photo and stores the data, then requests a facial recognition model to analyze the photo.

[1087] The facial recognition model performs a detailed analysis of facial features based on the received photograph. Specifically, it extracts features such as face shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth, and stores them as numerical data. Once the analysis is complete, the results are compared with the accumulated hairstyle database.

[1088] The hairstyle database stores detailed information about various hairstyles, and also lists which facial features each style is suited to. The server compares the analysis results with the information in the database and selects multiple hairstyles that are best suited to the user.

[1089] Response (terminal side)

[1090] Finally, the server sends the selected hairstyle and its details back to the device. The device receives this and suggests it to the user. Specifically, it displays a list of multiple hairstyles that are best suited to the user's facial pattern, complete with images. In addition, each hairstyle is accompanied by a comment such as "This style is best suited to oval faces" and a reason for the recommendation.

[1091] Additionally, styling advice and maintenance methods for the selected hairstyle are also displayed. For example, specific advice is provided such as, "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers."

[1092] Specific examples

[1093] For example, let's say User A uses this system and uploads a photo of their face. The server receives User A's photo and uses a facial recognition model to extract the characteristic "oval face." The server then selects from a database the hairstyles most suitable for oval faces, suggesting short hair, bob, long waves, etc. The device displays these styles to User A along with images and provides specific styling advice.

[1094] This system allows users to quickly and efficiently find the hairstyle that best suits them and how to maintain it. It is expected that user satisfaction will be greatly improved as they can easily try out styles at home without having to visit a specific beauty salon.

[1095] The processing flow will be explained below.

[1096] Step 1:

[1097] The user launches the application and the device prompts them to take a photo of their face or upload an existing photo.

[1098] Step 2:

[1099] The user takes a photo of their face or selects and uploads an existing photo, and the device sends the selected photo to the server.

[1100] Step 3:

[1101] The server receives the facial photo sent from the device, temporarily stores it, and then passes the example facial photo to the facial recognition model.

[1102] Step 4:

[1103] The facial recognition model receives a photo and performs a detailed analysis of facial features, including facial shape (round, oval, angular, etc.) and the position and size of the eyes, nose, and mouth.

[1104] Step 5:

[1105] The server then compares the analysis results with a hairstyle database, which contains detailed information about various hairstyles and which facial features each style is suited to.

[1106] Step 6:

[1107] Based on the matching results, the server selects multiple hairstyles that best suit the user, and information about the selected hairstyle is generated and sent to the device.

[1108] Step 7:

[1109] The device displays the received hairstyle suggestions and detailed information to the user. Based on the user's facial pattern, multiple optimal hairstyles are displayed in a list with images.

[1110] Step 8:

[1111] For each hairstyle, the device will also provide specific styling and maintenance advice, such as "To maintain this short hairstyle, it is recommended to use wax to add volume."

[1112] Step 9:

[1113] Based on the presented hairstyles and advice, users can choose and try out the hairstyle that best suits them. This process allows users to efficiently and quickly find a hairstyle that suits them.

[1114] Example 1

[1115] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1116] In conventional methods, users often need a lot of time and effort to find the hairstyle that best suits them. Furthermore, advice from hairdressers depends on their individual experience, making it difficult to guarantee a consistent level of quality. The present invention aims to provide a system that helps users quickly and efficiently find the hairstyle that best suits them.

[1117] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1118] In this invention, the server includes means for users to upload facial photographs, means for receiving and saving the uploaded facial photographs, means for using a facial feature recognition model to analyze the saved facial photographs, means for extracting features such as facial shape and the positions and sizes of the eyes, nose, and mouth and saving them as numerical data, means for comparing the analysis results with an accumulated hairstyle database, means for selecting an optimal hairstyle based on the comparison results, and means for presenting the selected hairstyle and its details to the user, thereby enabling the user to quickly and efficiently find the optimal hairstyle for themselves and how to maintain it.

[1119] "User" refers to an individual who uses the system to find the hairstyle that best suits them.

[1120] "Facial photo" refers to image data of a user's face.

[1121] "Upload" refers to the act of a user using a device to send a photo of their face to the system.

[1122] "Receiving" refers to the act of the server receiving the facial photo sent by the user.

[1123] "Storage" refers to the act of the server retaining the received facial photo data in data storage.

[1124] A "facial feature recognition model" refers to an algorithm or software used to analyze facial features such as the shape of the face and the position and size of the eyes, nose, and mouth from a photograph.

[1125] "Numerical data" refers to quantitative data obtained by analyzing facial features using a facial feature recognition model.

[1126] A "hairstyle database" refers to a database that records detailed information about various hairstyles and which facial features each one is suited to.

[1127] "Matching" refers to the process of comparing the numerical data of the analysis results with information in a hairstyle database to find a matching hairstyle.

[1128] "Selection" refers to the act of choosing the hairstyle that best suits the user based on the matching results.

[1129] "Presenting" refers to the act of displaying the selected hairstyle and its detailed information to the user.

[1130] The present invention relates to a system that helps users quickly and efficiently find the hairstyle that best suits them. The system mainly involves a process in which a user uploads a facial photo, and a server analyzes the facial photo and suggests the most suitable hairstyle.

[1131] User interface (terminal side)

[1132] First, the user launches the dedicated application. The application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user then takes a photo of their face or selects an existing photo and uploads it to the application.

[1133] Server Processing

[1134] Next, the device sends the uploaded facial photo to a server. The server saves the facial photo in a data storage device for receiving and saving facial photos. The server then launches a facial feature recognition model (e.g., OpenCV or AWS Rekognition) to analyze the facial photo. This model extracts features such as the shape of the face and the position and size of the eyes, nose, and mouth, and stores them as numerical data. The server then uses the numerical data resulting from the analysis to compare it with a hairstyle database. This database stores information about which hairstyles are suitable for which facial features.

[1135] Proposal Procedure

[1136] The server selects the optimal hairstyle for the user based on the matching results. It then returns the selected hairstyle and detailed information (e.g., reason for recommendation, styling advice, etc.) to the device. The device then makes suggestions to the user based on the received information. The displayed information includes which face shapes each hairstyle is suitable for, as well as specific styling and maintenance methods.

[1137] Specific examples

[1138] For example, consider the case where User A uses this system and uploads a photo of his / her face. The server receives the photo and uses a facial feature recognition model to extract the characteristic "oval face." The server then selects the hairstyle best suited to an oval face (e.g., short hair, bob, long waves) from a hairstyle database. Based on this information, the device makes suggestions to User A with images and provides specific styling advice.

[1139] Prompt Sentence Examples

[1140] Here are some example prompts to input to the generative AI model:

[1141] Please explain the process of the system that allows users to upload a face photo and quickly and efficiently suggest the best hairstyle based on that photo. Please explain the specific operations, model, and database used for each processing step (face photo upload, face photo analysis, hairstyle selection, and hairstyle suggestion).

[1142] This prompt allows the generative AI model to generate more specific explanations of the system's detailed processing.

[1143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1144] Step 1:

[1145] Users upload a photo of their face

[1146] Users launch the application and either take a photo of their face or select an existing photo.

[1147] Users can import a photo of their face and click the upload button to save the photo to their device.

[1148] Input: A user-selected face photo

[1149] Output: Facial photo data stored on the device

[1150] Step 2:

[1151] The device sends a photo of the face to the server

[1152] The device packages the stored facial photo data and generates an HTTP request to send it to the server.

[1153] The terminal sends the request to the server.

[1154] Input: Facial photo data stored on the device

[1155] Output: Facial photo data received by the server

[1156] Step 3:

[1157] The server stores the face photo.

[1158] The server validates the received facial photo data to ensure it is in the correct format.

[1159] Store face photo data in a file system or database.

[1160] Input: Received facial photo data

[1161] Output: Facial photo data stored on the server

[1162] Step 4:

[1163] The server analyzes the facial photo

[1164] The server runs a facial feature recognition model (e.g., OpenCV, AWS Rekognition) to analyze the face photo.

[1165] The facial recognition model extracts features such as the shape of the face and the position and size of the eyes, nose, and mouth, and stores them as numerical data.

[1166] Input: Facial photo data stored on the server

[1167] Output: Extracted facial feature data

[1168] Step 5:

[1169] The server compares the analysis results with the hairstyle database.

[1170] The server searches a hairstyle database based on the facial feature data.

[1171] Calculate the suitability of each hairstyle and select the most suitable style.

[1172] Input: extracted facial feature data, hairstyle database

[1173] Output: Selected optimal hairstyle data

[1174] Step 6:

[1175] The server sends the selected hairstyle back to the device.

[1176] The server packages the selected hairstyle and its detailed information (e.g., recommendation reason, styling advice) for transmission back to the terminal.

[1177] The server transmits the package to the terminal.

[1178] Input: Selected optimal hairstyle data

[1179] Output: Hairstyle suggestion data sent to the device

[1180] Step 7:

[1181] The device will display hairstyle suggestions to the user.

[1182] The terminal analyzes the received hairstyle suggestion data and updates the user interface.

[1183] It displays a list of hairstyles that best suit the user's face photo, along with a description and styling advice for each hairstyle.

[1184] Input: Hairstyle suggestion data received from the server

[1185] Output: Best hairstyles and styling advice displayed to the user

[1186] The above is the flow of the system program processing. At each step, specific operations and data flows are explained in detail, and the functionality of the entire system is clarified.

[1187] (Application example 1)

[1188] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1189] As autonomous vehicles become more widespread, there is a demand for enhanced in-car entertainment and relaxation. However, current systems do not allow users to find hairstyles that suit them, which means they are unable to make effective use of their time while driving autonomously. In addition, there is a lack of a concrete platform to improve the user experience in selecting hairstyles.

[1190] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1191] In this invention, the server includes: means for a user to upload a facial photo; means for receiving and saving the uploaded facial photo; means for using a facial recognition model to analyze the saved facial photo; means for comparing the analysis result with an accumulated hairstyle database; means for selecting an optimal hairstyle based on the comparison result; means for presenting the selected hairstyle and its details to the user; means for taking or uploading a facial photo using a display in the autonomous vehicle or a smartphone app; means for transmitting the facial photo to the server via an in-vehicle communication network; and means for displaying a list of selected hairstyles with images on an in-vehicle display. This allows users to easily find a hairstyle that suits them even during autonomous driving, making effective use of their time in the car.

[1192] A "User" is an individual who wishes to use the system to upload a photo of their face and find a hairstyle that suits them.

[1193] A "face photo" is image data that captures the user's facial features in detail.

[1194] An "uploading means" is a device or interface for taking a facial photograph or selecting an existing photograph and sending it to the system.

[1195] The "means for receiving and storing" is a data storage function for storing uploaded facial photos on a server.

[1196] A "facial recognition model" is a machine learning algorithm or software that analyzes photographs of faces and extracts facial features.

[1197] A "hairstyle database" is a database that stores various hairstyles and their characteristics.

[1198] The "matching means" is the process of comparing the analyzed facial features with a hairstyle database and selecting a suitable hairstyle.

[1199] The "best hairstyle" is the hairstyle that is determined to best suit the user's facial features.

[1200] The "presentation means" refers to a display or application for visually displaying an image and detailed information of the selected hairstyle to the user.

[1201] An "autonomous vehicle" is a vehicle that has the ability to automatically perform driving operations.

[1202] "Display" refers to a display device installed in the vehicle to visually display information from the system.

[1203] A "smartphone app" is an application that is installed on a smartphone and that uploads facial photos and displays analysis results as part of the system's functions.

[1204] The "communication network" is an internet connection means for sending facial photos from inside the vehicle to a server.

[1205] The "means for displaying with an image" is a display means for providing the user with visual information about the selected hairstyle.

[1206] This invention is a system that allows users to efficiently find the hairstyle that best suits them in an autonomous vehicle. The system configuration is mainly divided into three parts: the user interface, server processing, and in-car display.

[1207] User Interface

[1208] Users first access the system using the in-car display or their smartphone app. Once they access the system, a screen appears prompting them to either take a photo of their face or upload an existing photo. Users can then take a photo of their face or select an existing photo to upload.

[1209] Server Processing

[1210] The uploaded facial photo is sent to the server via the in-car communication network, and the server processes it using the following procedure.

[1211] 1. Save your face photo

[1212] The server stores the received facial photos in a database.

[1213] 2. Analysis using face recognition model

[1214] The server uses a facial recognition model (e.g., TensorFlow or OpenCV) to analyze the facial photo and extract facial features (shape, position of eyes and nose, etc.).

[1215] 3. Matching with hairstyle database

[1216] Based on the extracted facial features, the server compares them with a hairstyle database and selects multiple suitable hairstyles, each of which includes detailed information about which facial features are best suited to that style.

[1217] 4. Returning the results

[1218] The server then sends a list of selected hairstyles, along with detailed information and styling advice, back to the user's device.

[1219] Display on the in-car display

[1220] The results are then displayed on a display in the car or on a smartphone screen. Users can then choose from a selection of hairstyles based on their facial features. Each hairstyle comes with specific styling advice and maintenance instructions.

[1221] Specific examples

[1222] For example, suppose a user uploads a photo of their face while in the car. The server receives the photo and analyzes it using a facial recognition model. As a result of the analysis, characteristics such as an "oval face" are extracted. The server then selects a hairstyle from a hairstyle database that is best suited to an oval face, such as short hair, bob, or long waves. The selected hairstyle is then displayed on the in-car display along with styling advice.

[1223] Prompt Sentence Examples

[1224] "What are the characteristics of short hairstyles suitable for oval faces?"

[1225] The system allows users to easily find the hairstyle that best suits them even while driving autonomously, enabling them to make effective use of their time in the car. The present invention improves the quality of entertainment and relaxation in the car, further enriching the user experience.

[1226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1227] Step 1:

[1228] Initializing the user interface

[1229] Users open the in-car display or smartphone app, and the startup screen prompts them to either take a photo of themselves or upload an existing photo.

[1230] Input: Launch app

[1231] Output: Shows option to take or upload a photo of your face

[1232] Step 2:

[1233] Acquiring a facial photo

[1234] Users can take a photo of themselves or upload an existing photo.

[1235] Input: User selects a photo of their face (takes or uploads)

[1236] Output: Facial photo data taken or uploaded

[1237] Step 3:

[1238] Send a photo of your face

[1239] The terminal transmits the acquired facial photograph to a server via the in-car communication network.

[1240] Input: Facial photo data

[1241] Output: Facial photo data transferred to the server

[1242] Step 4:

[1243] Save face photo

[1244] The server stores the received facial photos in data storage (e.g., AWS S3 bucket).

[1245] Input: Facial photo data sent to the server

[1246] Output: Saved face photo data

[1247] Step 5:

[1248] Analysis using face recognition models

[1249] The server analyzes the stored facial photos using a facial recognition model (e.g., TensorFlow or OpenCV), extracting features such as the shape of the face, and the position and size of the eyes, nose, and mouth, and converting them into numerical data.

[1250] Input: Saved face photo data

[1251] Output: Extracted facial feature data

[1252] Step 6:

[1253] Matching with a hairstyle database

[1254] The server compares the extracted facial feature data with a hairstyle database and selects multiple suitable hairstyles.

[1255] Input: Facial feature data

[1256] Output: A list of selected hairstyles

[1257] Step 7:

[1258] Returning the results

[1259] The server returns the selected hairstyle list, along with detailed information and styling advice, to the user's device.

[1260] Input: A list of selected hairstyles

[1261] Output: Returning the results to the user's device

[1262] Step 8:

[1263] Display on the in-car display

[1264] The device displays the received results on the in-car display or smartphone, presenting the user with multiple hairstyle options and styling advice.

[1265] Input: Returned result data

[1266] Output: Hairstyle options and advice displayed on the screen

[1267] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1268] The present invention relates to a system that helps users quickly and efficiently select the most suitable hairstyle, and also to a system that makes optimal suggestions taking into account the user's emotions. This system involves a process in which a user takes and uploads a facial photo, and a server not only analyzes the facial photo but also recognizes the user's emotions.

[1269] Specific implementation methods of the system

[1270] User interface (terminal side)

[1271] First, the user launches the application. For user convenience, the application displays a screen prompting the user to take a photo of their face or upload an existing photo. The user can then take a photo of their face or select an existing photo and upload it to the application.

[1272] Server Processing

[1273] The device then sends the user's selected facial photo to the server, which receives the photo and stores the data, then requests a facial recognition model to analyze the photo.

[1274] The facial recognition model performs a detailed analysis of facial features based on the received photograph. Specifically, it extracts features such as face shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth, and stores them as numerical data. Once the analysis is complete, the results are compared with the accumulated hairstyle database.

[1275] The hairstyle database stores detailed information about various hairstyles, and also lists which facial features each style is suited to. The server compares the analysis results with the information in the database and selects multiple hairstyles that are best suited to the user.

[1276] Introducing the Emotion Engine

[1277] In addition, in order for the emotion engine to recognize the user's emotions, the server adds a process to analyze the user's facial expressions and voice before suggesting a style. This engine analyzes the user's current emotional state from facial expressions and tone of voice.

[1278] Based on the analysis results of the emotion engine, the system can choose a hairstyle that best suits the user's emotions at that time. For example, if the user is in a good mood, it can suggest a challenging hairstyle, and if the user is in a bad mood, it can suggest a more stable hairstyle.

[1279] Response (terminal side)

[1280] Finally, the server sends the selected hairstyle and its details back to the device. The device receives this and suggests it to the user. Specifically, it displays a list of multiple optimal hairstyles with images based on the user's facial pattern and emotions. In addition, each hairstyle includes a comment such as "This style is perfect for your current mood" and the reason for the recommendation.

[1281] Additionally, styling advice and maintenance methods for the selected hairstyle are also displayed. For example, specific advice is provided such as, "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers."

[1282] Specific examples

[1283] For example, suppose User B uses this system and uploads a photo of his face. The server receives User B's photo and uses a facial recognition model to extract the characteristic "oval face." Furthermore, the emotion engine analyzes the photo and determines that User B is in a relaxed mood. Based on this information, the server suggests hairstyles (e.g., long waves or natural straight hair) that are optimal for an oval face and match a relaxed mood. The device displays these styles with images to User B and provides specific styling advice.

[1284] The system allows users to quickly and efficiently find hairstyles that suit not only their face shape but also their current mood, as well as how to maintain them, allowing them to easily try out styles at home without having to visit a specific hair salon.

[1285] The processing flow will be explained below.

[1286] Step 1:

[1287] The user launches the application and the device prompts them to take a photo of their face or upload an existing photo.

[1288] Step 2:

[1289] The user takes a photo of their face or selects and uploads an existing photo, and the device sends the selected photo to the server.

[1290] Step 3:

[1291] The server receives the facial photo sent from the device, temporarily stores it, and passes it to a facial recognition model.

[1292] Step 4:

[1293] The facial recognition model receives a photo and performs a detailed analysis of facial features, including facial shape (round, oval, angular, etc.), and the position and size of the eyes, nose, and mouth.

[1294] Step 5:

[1295] The server then compares the analysis results with a hairstyle database, which contains detailed information about various hairstyles and which facial features each style is suited to.

[1296] Step 6:

[1297] Based on the matching results, the server selects multiple hairstyles that best suit the user.

[1298] Step 7:

[1299] The emotion engine analyzes facial expressions and tone of voice to recognize the user's emotions, and users can also provide photos, video clips, and audio.

[1300] Step 8:

[1301] The server obtains the user's emotional state recognized by the emotion engine, for example, the emotion engine indicates the user's emotional state such as "relaxed" or "tense."

[1302] Step 9:

[1303] The server considers the analysis results and the emotion recognition results from the emotion engine to reselect the most suitable hairstyle. For example, it can suggest a natural hairstyle for a relaxed user, and a stable hairstyle for a nervous user.

[1304] Step 10:

[1305] The server sends the selected hairstyle and its details to the device, which receives it and presents it to the user.

[1306] Step 11:

[1307] The device then displays the received hairstyle suggestions and detailed information to the user, displaying a list of multiple hairstyles with images that are most suitable for the user based on their facial pattern and emotions.

[1308] Step 12:

[1309] For each hairstyle selected, the device will also provide specific styling and maintenance advice, such as "To maintain this short hairstyle, it is recommended to use wax to add volume."

[1310] Step 13:

[1311] Based on the presented hairstyles and advice, users can choose and try out the hairstyle that best suits them. This process allows users to efficiently and quickly find a hairstyle that suits them.

[1312] Example 2

[1313] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1314] Conventional hairstyle suggestion systems only consider the user's face shape, which means they are unable to suggest styles that match the user's emotions or mood. This can prevent users from choosing the hairstyle that best suits their mood at the time, leading to a decrease in satisfaction.

[1315] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1316] In this invention, the server includes means for allowing a user to upload a facial photo, means for receiving and storing the uploaded facial photo, means for using an image recognition model to analyze the stored facial photo, means for comparing the analysis result with an accumulated hairstyle database, means for using an emotion recognition engine to analyze the user's emotion, means for selecting an optimal hairstyle based on the user's emotional state and facial features, and means for presenting the selected hairstyle and its details to the user, thereby enabling the user to know the optimal hairstyle based not only on the shape of their face but also on their current mood.

[1317] "User" means an individual who uses the System.

[1318] A "face photo" is image data of a user's face.

[1319] "Means for uploading" refers to the function that allows a user to send data from a terminal to a server.

[1320] "Means for receiving and storing" refers to the function by which the server receives data from the terminal and stores it.

[1321] An "image recognition model" is an algorithm or software used to analyze facial photographs.

[1322] "Means for matching" is a function for comparing the analysis results with information in the database.

[1323] An "emotion recognition engine" is an algorithm or software for analyzing a user's emotions.

[1324] "Emotional state" is information that indicates the user's current psychological state.

[1325] A "hairstyle database" is a collection of data that records various hairstyles and the facial features and emotional states that are suitable for each hairstyle.

[1326] The "best hairstyle" is the hairstyle that best suits the user's facial features and emotional state.

[1327] The "means for presenting details" is a function for displaying information about the selected hairstyle to the user.

[1328] The present invention relates to a system that assists a user in quickly and efficiently selecting an optimal hairstyle, and further relates to a system that makes optimal suggestions taking into account the user's feelings.

[1329] First, the user launches the application on their device. The application provides an interface for the user to take a photo of their face or upload an existing photo. Once the user has taken or uploaded a photo of their face, the device sends the photo data to a server. The data is securely transmitted using encryption protocols such as TLS (Transport Layer Security).

[1330] The server receives the facial photo data sent from the device and stores it in a database. The server then analyzes the facial photo using an image recognition model. This image recognition model uses a facial recognition API provided by a common cloud service (such as Azure Face API). Through the analysis, facial features such as the shape of the face and the position of the eyes, nose, and mouth are extracted and stored as numerical data.

[1331] The server then uses an emotion recognition engine, such as Google Cloud Natural Language API or IBM Watson's Tone Analyzer, to analyze the user's emotional state by analyzing their facial expressions and tone of voice.

[1332] The server then compares the results of these analyses with a database of accumulated hairstyles, which contains a variety of hairstyles and which facial features and emotional states each style is suited to. By comparing the results with the analysis, the server selects the hairstyle that best suits the user. The selected style also includes detailed information and styling advice.

[1333] The server sends information about the selected hairstyle back to the device, which receives it and presents it to the user. The information presented includes an image of the selected hairstyle, the reason for the recommendation, and specific styling and maintenance methods. For example, advice such as "To maintain this short hairstyle, we recommend using wax to add volume. Apply a thin layer of wax to your hair and style it quickly with your fingers" is also provided.

[1334] For example, when User A uses the app and uploads a photo of their face, the server receives the photo and extracts the characteristic "oval face" using the Azure Face API. Furthermore, it determines that the user is in a relaxed mood using the Google Cloud Natural Language API. Based on this information, the server selects a hairstyle, such as long waves or natural straight, that is best suited to a relaxed mood and presents it to User A along with detailed styling advice.

[1335] An example of a prompt to be input to a generative AI model might be, "Describe a system that suggests the best hairstyle based on a face photo uploaded by a user. The system combines facial recognition and emotion recognition to suggest a style that matches the user's current mood. Please also mention what software and hardware you use."

[1336] The system allows users to quickly and efficiently find the perfect hairstyle based not only on their face shape but also on their current mood.

[1337] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1338] Step 1:

[1339] When a user launches the application, the device displays a screen prompting the user to take a photo of their face or upload an existing photo. Once the user takes or selects a photo of their face, the image data is temporarily stored on the device.

[1340] Input: Facial photo data taken or selected by the user.

[1341] Output: Temporarily saved face photo data.

[1342] Step 2:

[1343] When the user selects a face photo and presses the upload button, the device sends the face photo data to the server using encrypted data communication, using protocols such as TLS (Transport Layer Security).

[1344] Input: Temporarily saved facial photo data.

[1345] Output: Facial photo data sent to the server.

[1346] Step 3:

[1347] The server receives the facial photo data sent from the device and stores it in a database.

[1348] Input: Facial photo data sent from the device.

[1349] Output: Facial photo data stored in a database.

[1350] Step 4:

[1351] The server sends the stored facial photo data to a facial recognition model (e.g., an image recognition API) for analysis, where features such as the shape of the face and the position of the eyes, nose, and mouth are extracted as numerical data.

[1352] Input: Facial photo data stored in the database.

[1353] Output: Numerical data representing facial features.

[1354] Step 5:

[1355] The server uses an emotion recognition engine (e.g., an emotion analysis API) to analyze the user's emotions. It analyzes the user's facial expressions and tone of voice to determine their current emotional state.

[1356] Input: Facial photo data stored in a database and real-time audio data (if required).

[1357] Output: Parsed user emotional state data.

[1358] Step 6:

[1359] The server compares the numerical data obtained from the facial recognition model and the emotional state data obtained from the emotion recognition engine with a hairstyle database. The database contains multiple hairstyles and the facial features and emotional states that are suitable for each. The server then selects the most suitable hairstyle.

[1360] Input: Numerical data representing facial features and emotional state data.

[1361] Output: Data on the results of selecting the best hairstyle.

[1362] Step 7:

[1363] The server then returns detailed information about the selected hairstyle to the device, including an image of the selected hairstyle, the reason for its recommendation, and specific styling and maintenance methods.

[1364] Input: Data on the results of selecting the best hairstyle.

[1365] Output: Hairstyle information returned to the device.

[1366] Step 8:

[1367] The device receives the selected hairstyle information returned from the server, and based on the received information, displays a list of hairstyle images to the user, along with the reasons why each style is recommended and specific styling advice.

[1368] Input: Hairstyle information returned from the server.

[1369] Output: A list of hairstyle images and advice information presented to the user.

[1370] (Application example 2)

[1371] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1372] Conventional hairstyle suggestion systems only considered the user's facial features when proposing hairstyles, making it impossible to provide optimal suggestions that reflected the user's current emotional state. Furthermore, the suggested hairstyles could only be applied to individual devices or at home, making them difficult to use in physical stores. There was a need to solve these problems and realize hairstyle suggestions that better meet the user's needs.

[1373] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for a user to upload a facial photo, means for receiving and saving the uploaded facial photo, means for using a face recognition model to analyze the saved facial photo, means for analyzing the emotional state of the user using an emotion recognition model, means for suggesting an optimal hairstyle based on the user's facial features and emotional state, and means for displaying hairstyles in real time using a device installed in a physical store. This makes it possible to suggest an optimal hairstyle taking into account the user's emotional state, further promoting use in physical stores.

[1374] "Means for users to upload facial photos" refers to terminals or applications that provide the functionality for users to take a photo of their face and send it to the system.

[1375] "Means for receiving and storing uploaded facial photographs" refers to software or systems that provide the function of receiving and storing facial photographs uploaded by users on the server side.

[1376] The "means for using a facial recognition model to analyze stored facial photographs" is a function that uses a facial recognition algorithm to analyze stored facial photographs and extract facial features.

[1377] "Means for selecting the most suitable hairstyle based on the comparison results" refers to a function that compares the results of facial recognition analysis with a hairstyle database and selects the most suitable hairstyle.

[1378] The "means for presenting the selected hairstyle and its details to the user" is an interface that has the function of displaying an image and information about the selected hairstyle to the user.

[1379] The "means for analyzing the emotional state of a user using an emotion recognition model" is an emotion recognition algorithm for identifying the emotional state of a user through analysis of the user's facial expressions and voice.

[1380] "Means for suggesting the most suitable hairstyle based on the user's facial features and emotional state" is a function that comprehensively evaluates the user's facial shape and emotional state, and selects and suggests the most suitable hairstyle.

[1381] "Means for displaying hairstyles in real time using devices installed in physical stores" refers to a function that displays hairstyle suggestions in real time using devices such as mirrors and tablets installed in physical stores.

[1382] The present invention is a system that helps users quickly and efficiently select the most suitable hairstyle, and also provides optimal suggestions taking into account the user's emotions. This system operates through a smart mirror system installed in a physical store. Specific embodiments of the system are described below.

[1383] User interface (terminal side)

[1384] First, the user stands in front of a smart mirror installed in a brick-and-mortar store, which has a built-in camera that automatically takes a photo of the user's face, which is then uploaded to the system.

[1385] Server Processing

[1386] The server receives and stores the uploaded face photo. It then uses a facial recognition model (e.g., OpenCV, Dlib) to analyze the face photo and extract detailed facial features, including face shape (e.g., round, oval, angular). It then uses an emotion recognition model (e.g., Microsoft Azure Face API, Amazon Rekognition) to analyze the user's current emotional state from their facial expressions and voice.

[1387] Once the facial features and emotional state have been analyzed, the results are compared against a hairstyle database that contains detailed information about various hairstyles and which styles suit which facial features.

[1388] Selection and proposal

[1389] The server compares the analysis results with the database information and selects multiple hairstyles that are best suited to the user. Furthermore, based on the analysis results of the emotion engine, it selects the most suitable hairstyle taking into account the user's emotions at the time. For example, if the user is relaxed, it suggests a hairstyle that gives a sense of stability.

[1390] Response (terminal side)

[1391] Finally, the server sends the selected hairstyle and its details back to the smart mirror. The smart mirror receives this and displays suggestions to the user in real time. Specifically, it displays multiple optimal hairstyles based on the user's facial patterns and emotions, along with images. In addition, for each hairstyle, comments such as "This style is perfect for your current mood" and reasons for the recommendation are included. Styling advice and maintenance methods for the selected hairstyle are also displayed.

[1392] Specific examples

[1393] For example, when a user stands in front of a smart mirror, a photo of their face is automatically taken and uploaded to the system. The server receives the photo and uses a facial recognition model to extract the characteristic of an "oval face." An emotion recognition model analyzes the user's state as relaxed. Based on this information, the server selects a hairstyle (e.g., soft waves or a bob) that best suits the user's face shape and relaxed mood. The results are displayed in real time on the smart mirror, allowing the user to instantly see the optimal hairstyle and styling method.

[1394] Example prompts for generative AI models

[1395] "A 40-year-old woman comes into the salon looking for a stylish hairstyle, but wants to maintain a calm look. She has an oval face and is currently relaxed. We suggest the best hairstyle and styling method for her."

[1396] The system allows users to quickly and efficiently find hairstyles that suit their face shape and current mood, allowing them to easily try out styles at home or in a brick-and-mortar store without having to visit a specific salon.

[1397] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1398] Step 1:

[1399] A user stands in front of a smart mirror installed in a physical store and takes a photo of their face. When the user stands in front of the smart mirror, the smart mirror automatically takes a photo of their face using its built-in camera and collects the data. The input at this point is the user's face photo, and the image data is sent to the server.

[1400] Step 2:

[1401] The server receives and stores the facial photo sent from the smart mirror. This stores the facial photo data in the server and prepares it for analysis. The input is the facial photo data sent in step 1, and the output is the stored facial photo data.

[1402] Step 3:

[1403] The server uses a facial recognition model to analyze the stored facial photos. This facial recognition model (e.g., OpenCV, Dlib) analyzes facial features (round, oval, angular, etc.) in detail and extracts them as numerical data. The input is the stored facial photo data, and the output is facial feature data.

[1404] Step 4:

[1405] The server uses the facial feature data extracted by the facial recognition model to analyze the user's emotional state using an emotion recognition model (e.g., Microsoft Azure Face API, Amazon Rekognition). The emotion recognition model analyzes the user's facial expressions and voice to identify their emotional state, such as relaxed or excited. The input is facial feature data and facial expression / voice data, and the output is emotional state data.

[1406] Step 5:

[1407] The server compares the facial feature data and emotional state data with the hairstyle database. Based on the comparison results, it selects the most suitable hairstyle. The hairstyle database contains information on which facial features and emotional state each hairstyle is suited to. The input is facial feature data and emotional state data, and the output is the most suitable hairstyle data.

[1408] Step 6:

[1409] The server sends the selected hairstyle and its details back to the smart mirror, which now includes an image of the selected hairstyle and styling advice. The input is the optimal hairstyle data, and the output is the suggestion data sent to the smart mirror.

[1410] Step 7:

[1411] The smart mirror displays hairstyle suggestions received from the server to the user in real time. The user can then select the best hairstyle from the multiple hairstyles displayed. The displayed content includes an image of the selected hairstyle, detailed information, and styling advice. The input is the suggestion data sent from the server, and the output is the information visually presented to the user.

[1412] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1413] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1414] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1415] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1416] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1417] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1418] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1419] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1420] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1421] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1422] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1423] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1424] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1425] 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.

[1426] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1427] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1428] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1429] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1430] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1431] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1432] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1433] The following is further disclosed regarding the above embodiment.

[1434] (Claim 1)

[1435] A means for users to upload a photo of their face;

[1436] a means for receiving and storing the uploaded facial photograph;

[1437] means for using a facial recognition model to analyze the stored facial photograph;

[1438] means for comparing the analysis results with an accumulated hairstyle database;

[1439] A means for selecting an optimal hairstyle based on the collated results;

[1440] A means for presenting the selected hairstyle and its details to the user;

[1441] A system including:

[1442] (Claim 2)

[1443] The system according to claim 1, wherein specific styling advice and maintenance methods for the selected hairstyle are displayed based on the matching results.

[1444] (Claim 3)

[1445] 10. The system of claim 1, further comprising: means for suggesting a plurality of optimal hairstyles based on a facial pattern of the user.

[1446] "Example 1"

[1447] (Claim 1)

[1448] A means for users to upload a photo of their face;

[1449] a means for receiving and storing the uploaded facial photograph;

[1450] means for using a facial feature recognition model to analyze the stored facial photograph;

[1451] A method to extract features such as the shape of the face, and the position and size of the eyes, nose, and mouth, and store them as numerical data.

[1452] means for comparing the analysis results with an accumulated hairstyle database;

[1453] A means for selecting an optimal hairstyle based on the collation result;

[1454] A means for presenting the selected hairstyle and its details to the user;

[1455] A system including:

[1456] (Claim 2)

[1457] The system according to claim 1, wherein specific styling advice and maintenance methods for the selected hairstyle are displayed based on the matching results.

[1458] (Claim 3)

[1459] 10. The system of claim 1, further comprising: means for suggesting a plurality of optimal hairstyles based on a facial pattern of the user.

[1460] "Application Example 1"

[1461] (Claim 1)

[1462] A means for users to upload a photo of their face;

[1463] a means for receiving and storing the uploaded facial photograph;

[1464] means for using a facial recognition model to analyze the stored facial photograph;

[1465] means for comparing the analysis results with an accumulated hairstyle database;

[1466] A means for selecting an optimal hairstyle based on the collated results;

[1467] A means for presenting the selected hairstyle and its details to the user;

[1468] A means for taking or uploading a facial photograph using a display in the autonomous vehicle or a smartphone app;

[1469] A means for transmitting a facial photograph to a server via an in-vehicle communication network;

[1470] A means for displaying a list of selected hairstyles with images on an in-car display;

[1471] A system including:

[1472] (Claim 2)

[1473] The system according to claim 1, wherein specific styling advice and maintenance methods for the selected hairstyle are displayed based on the matching results.

[1474] (Claim 3)

[1475] 10. The system of claim 1, further comprising: means for suggesting a plurality of optimal hairstyles based on a facial pattern of the user.

[1476] "Example 2: Combining Emotion Engines"

[1477] (Claim 1)

[1478] A means for users to upload a photo of their face;

[1479] a means for receiving and storing the uploaded facial photograph;

[1480] means for using an image recognition model to analyze the stored facial photograph;

[1481] means for comparing the analysis results with an accumulated hairstyle database;

[1482] a means for using an emotion recognition engine to analyze the emotion of the user;

[1483] a means for selecting an optimal hairstyle based on emotional state and facial features;

[1484] A means for presenting the selected hairstyle and its details to the user;

[1485] A system including:

[1486] (Claim 2)

[1487] The system according to claim 1, wherein specific styling advice and maintenance methods for the selected hairstyle are displayed based on the matching results.

[1488] (Claim 3)

[1489] 10. The system of claim 1, further comprising means for suggesting a plurality of optimal hairstyles based on the user's facial features and emotional state.

[1490] "Application example 2 when combining emotion engines"

[1491] (Claim 1)

[1492] A means for users to upload a photo of their face;

[1493] a means for receiving and storing the uploaded facial photograph;

[1494] means for using a facial recognition model to analyze the stored facial photograph;

[1495] means for comparing the analysis results with an accumulated hairstyle database;

[1496] A means for selecting an optimal hairstyle based on the collated results;

[1497] A means for presenting the selected hairstyle and its details to the user;

[1498] means for analyzing the emotional state of a user using an emotion recognition model;

[1499] A means for suggesting the best hairstyle based on the user's facial features and emotional state;

[1500] A means of displaying hairstyles in real time using devices installed in physical stores;

[1501] A system including:

[1502] (Claim 2)

[1503] The system according to claim 1, wherein specific styling advice and maintenance methods for the selected hairstyle are displayed based on the matching results.

[1504] (Claim 3)

[1505] 10. The system of claim 1, further comprising: means for suggesting a plurality of optimal hairstyles based on the user's face shape and emotional state. [Explanation of symbols]

[1506] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to upload a photo of their face; a means for receiving and storing the uploaded facial photograph; means for using a facial recognition model to analyze the stored facial photograph; means for comparing the analysis results with an accumulated hairstyle database; A means for selecting an optimal hairstyle based on the collated results; A means for presenting the selected hairstyle and its details to the user; A system including:

2. The system according to claim 1, wherein specific styling advice and maintenance methods for the selected hairstyle are displayed based on the collation results.

3. The system of claim 1 , further comprising: means for presenting a plurality of optimal hairstyles based on the user's facial pattern.

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