System

Abstract

A system is provided.SOLUTION: A system comprising: a means for a user to take a photograph of his / her own face and upload the photograph; a means for analyzing the uploaded face photograph to identify the contour of the face, the hair type, and the length of hair; a means for fusing the analysis result and a hairstyle selected by the user to generate an optimal cutting method and a finished image; a means for displaying the generated finished image; a means for obtaining feedback by checking the displayed finished image; and a means for storing data of the final finished image and the cutting method and presenting the data to a hairdresser.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] In traditional beauty salons and barber shops, when a customer communicates their desired hairstyle, there is often a large discrepancy between the actual result and the image they have in mind. This communication gap arises from a lack of mutual understanding between the hairdresser and the customer, resulting in reduced customer satisfaction. The present invention aims to solve this problem by providing a method and system that allows customers to check their desired style in advance. [Means for solving the problem]

[0005] The present invention solves the aforementioned problems by providing a system that includes: a means for a user to take a photo of their face and upload the photo; a means for analyzing the uploaded photo and identifying the facial contours, hair type, and hair length; a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image; a means for displaying the generated finished image; a means for the user to check the displayed finished image and receive feedback; and a means for the user to save data on the final finished image and haircut method and present it to the hairdresser. This reduces the communication gap between the user and the hairdresser, making it possible to achieve the desired hairstyle.

[0006] "User" refers to an individual who uses the system to take a photo of themselves and select a hairstyle.

[0007] "Mouthshot" means a digital image of a user's face.

[0008] "Uploading" refers to the act of a user sending a photograph of their face to the system.

[0009] "Analysis" refers to the process by which an artificial intelligence model identifies facial features such as facial contours, hair type, and hair length from a facial photo.

[0010] "Hairstyle" refers to the hair shape or design desired by the user.

[0011] "Fusion" refers to the process of combining the analysis results with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[0012] "Cutting method" refers to the specific way in which hair is cut to achieve the hairstyle desired by the user.

[0013] "Finished image" refers to the rendering of the finished product generated by the AI ​​model based on the user's desired hairstyle.

[0014] "Display" refers to the process of visually showing the generated finished image on the user's device.

[0015] "Feedback" refers to the act of the user providing opinions or confirmations regarding the displayed finished image.

[0016] "Saving" refers to the act of recording the final image of the finished product and cutting method data that the user has confirmed on the terminal.

[0017] "Presenting" refers to the act of showing the saved cutting information to the hairdresser.

[0018] "System" refers to a device or software that includes a series of functions that allow a user to preview the desired hairstyle. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

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

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] This invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that photo. The following elements are required to implement this system: a device such as a smartphone or tablet, a server, and a dedicated application.

[0041] System configuration

[0042] Take and upload a photo of your face

[0043] User: Take a photo of their face using the camera function on their smartphone. After taking the photo, the user presses the upload button in the application to send the photo to the server.

[0044] Device: The application sends the captured face photo and user ID to the server.

[0045] Server: Receives facial photos and user information and prepares the facial photos to be input into the AI ​​model.

[0046] Face photo analysis and hairstyle selection

[0047] Server: The received facial photo is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length, which allows customization according to the user's hair condition.

[0048] User: Select the hairstyle they want on the hairstyle selection screen. After selection, the information is also sent to the server.

[0049] AI-based cutting method and finished image generation

[0050] Server: Based on the analysis of the facial photo and the hairstyle selected by the user, the AI ​​model generates the optimal cutting method and finished image, allowing users to simulate the actual image after the haircut.

[0051] Server: Sends the generated finished image and cutting method data to the terminal.

[0052] View the final image and get feedback

[0053] Device: The received image of the finished hairstyle is displayed to the user within the application. The user checks the displayed image and presses the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again.

[0054] Sharing information with hairdressers

[0055] User: Save the final image of the finished look and cutting method that they are satisfied with, and then go to the salon and present this. Specifically, they can show the screen of their smartphone to the hairdresser, or if necessary, bring a printed copy of the data with them.

[0056] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method.

[0057] Specific examples

[0058] For example, a specific example will be given where the user desires a "bob cut."

[0059] 1. User: Take a photo of their face with their smartphone camera and upload it to the application.

[0060] 2. Device: Sends a photo of the face and basic information to the server.

[0061] 3. Server: Analyzes the facial photo and identifies facial contours, hair type, and hair length.

[0062] 4. User: Choose a bob cut style.

[0063] 5. Server: The analysis results are combined with the bob cut data, and the AI ​​model generates the optimal finished image.

[0064] 6. Server: Sends the generated finished image to the device.

[0065] 7. Device: The finished image is displayed in the app and the user is asked to confirm.

[0066] 8. User: Once satisfied with the image, presses the "OK" button to save the data.

[0067] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[0068] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[0069] This system reduces the gap in results between the user and the hairdresser, allowing them to achieve their ideal hairstyle.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] User: Use the camera on your smartphone to take a photo of yourself, preferably a high-resolution image.

[0073] Step 2:

[0074] Device: Check the captured facial photo and press the upload button in the application to send the facial photo and user ID to the server.

[0075] Step 3:

[0076] Server: Stores the received facial photos and user IDs and prepares to send the facial photos to the AI ​​analysis unit.

[0077] Step 4:

[0078] Server: The AI ​​analysis unit analyzes the facial photo to identify facial contours, hair type, and hair length, sometimes using external systems or cloud services.

[0079] Step 5:

[0080] User: Within the application, select the desired hairstyle from the thumbnails of multiple hairstyles displayed.

[0081] Step 6:

[0082] Device: Sends the selected hairstyle information to the server.

[0083] Step 7:

[0084] Server: The AI ​​model combines the analysis results with the hairstyle information selected by the user to generate the optimal cutting method and finished image.

[0085] Step 8:

[0086] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[0087] Step 9:

[0088] Terminal: The received finished image and cutting method data are displayed within the application.

[0089] Step 10:

[0090] User: Check the displayed image of the finished look, and if you are satisfied, press the "OK" button. If you are not satisfied, select another hairstyle and repeat the steps from step 5.

[0091] Step 11:

[0092] Device: When the user presses the "OK" button, the final finished image and cutting method data are saved on the device.

[0093] Step 12:

[0094] User: Go to the hair salon and show the hairdresser the finished image and cutting method data saved on the smartphone screen. If necessary, you can also print it out and bring it with you.

[0095] Step 13:

[0096] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method data.

[0097] Example 1

[0098] 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."

[0099] Conventional hairstyle selection systems have had the problem that it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, leading to dissatisfaction with the finished product. Also, few systems allow users to simulate the finished hairstyle in advance based on a photo of their own face. As a result, a communication gap occurs between the user and the hairdresser, making it difficult to achieve the ideal hairstyle.

[0100] 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.

[0101] In this invention, the server includes a means for a user to take a photo of their face and upload the photo, a means for analyzing the uploaded photo of their face to identify the facial contours, hair type, and hair length, and a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image. This allows the user to check in advance the finished image of the hairstyle based on their face photo, and makes it possible to present specific haircut information to the hairdresser.

[0102] "User" refers to an individual who uses the system to take a photo of themselves and select the hairstyle they desire.

[0103] "Terminal" refers to a device used by a user, such as a smartphone or tablet.

[0104] "Server" means the computer system that has the central function of receiving and processing uploaded photos and selected hairstyles.

[0105] "Taking and uploading a photo of your face" refers to the process in which a user takes a photo of their face using the device's camera and sends the photo to the server.

[0106] "Facial photo analysis" refers to the process of identifying facial contours, hair type, and hair length based on a facial photo uploaded to a server.

[0107] The "analysis results" are data obtained from facial photos processed by AI, and include information such as facial contours, hair type, and hair length.

[0108] "Hairstyle selection" refers to the act of a user selecting the hairstyle they want within a dedicated application.

[0109] "Hairstyle information" is data relating to the hairstyle selected by the user, and the cutting method and finished image are generated based on this information.

[0110] "Cutting method" refers to the haircutting method and treatment procedure suggested according to the hairstyle selected by the user.

[0111] "Finished Image" refers to an image generated by the AI ​​model that shows how the selected hairstyle will look on the user's face.

[0112] "Getting feedback" refers to the process of users checking their satisfaction with the displayed finished image and obtaining the results.

[0113] "Generative AI model" refers to artificial intelligence technology that generates the optimal cutting method and finished image based on a facial photo and hairstyle information.

[0114] "Means of presenting to the hairdresser on a smartphone or in printed form" refers to the means by which the user can show the hairdresser the haircut information saved by the user, including using the screen of a digital device or a paper printout.

[0115] "Artificial intelligence" refers to the technology that analyzes facial photos and performs computational processing to generate cutting methods and finished images.

[0116] This invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that photo. The following elements are required to implement this system: a device such as a smartphone or tablet, a server, and a dedicated application.

[0117] System configuration

[0118] Take and upload a photo of your face

[0119] User: Uses the camera function of the smartphone to take a photo of his / her face. After taking the photo, he / she presses the "upload" button in the dedicated application to send the photo to the server.

[0120] Device: The application sends the user's face photo data and user ID to the server. The photo is sent in JPEG or PNG format.

[0121] Preparation for facial photo analysis

[0122] Server: Stores the received face photo and user ID in a database. Then, it performs pre-processing to input the photo data into the AI ​​analysis unit. This pre-processing includes image resizing and noise removal.

[0123] Facial photo analysis

[0124] Server: The AI ​​analysis unit is used to analyze the facial features of the photo, specifically identifying facial contours, hair type, hair length, etc. The analysis results are saved in JSON format for subsequent processing.

[0125] Hairstyle selection

[0126] User: Select the desired hairstyle on the hairstyle selection screen of the dedicated application. For example, select "Bob Cut." After selecting, press the "Send" button to send the information to the server.

[0127] Terminal: Sends hairstyle information to the server. The selected hairstyle information is sent as text data.

[0128] AI-based cutting method and finished image generation

[0129] Server: Based on the analysis results of the facial photo and the hairstyle selected by the user, the generative AI model generates the optimal haircut method and finished image. Specifically, the prompt "Based on the facial photo and the selected hairstyle, please generate the optimal haircut method and finished image" is input to the AI.

[0130] Server: The generated finished image and cutting method data are encoded in JPEG or PNG format and sent to the user's device.

[0131] View the final image and get feedback

[0132] Device: The received finished image is displayed in the dedicated application. After checking the displayed image, the user can save the image by pressing the "OK" button, or return to the hairstyle selection screen by pressing the "Reselect" button.

[0133] User: If you are satisfied with the final image, press the "OK" button to save the data, but if you are not satisfied, select the hairstyle again.

[0134] Sharing information with hairdressers

[0135] User: Saves the final image of the finished look and cutting method data in a dedicated application, and shows the screen on their smartphone to the hairdresser when they visit the salon.

[0136] Hairdresser: Cuts the customer's hair according to their wishes, based on the presented image of the finished look and cutting method.

[0137] Specific examples

[0138] For example, a specific example will be given where the user desires a "bob cut."

[0139] User: Take a photo of their face with their smartphone camera and upload it to the application.

[0140] Device: Sends a photo of your face and basic information to the server.

[0141] Server: Analyzes facial photos to identify facial contours, hair type, and hair length.

[0142] User: Select "BobCut" on the application selection screen.

[0143] Server: The analysis results are combined with the "bob cut" style data, and the generative AI model generates the optimal finished image. Example prompt: "Generate the best bob cut style for this user based on their face photo."

[0144] Server: Sends the finished image generated by the AI ​​model to the user's device.

[0145] On device: The finished image is displayed in the app and the user is asked to confirm.

[0146] User: Once satisfied with the image, presses the "OK" button to save the data.

[0147] User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[0148] Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[0149] This reduces the gap in the results between the user and the hairdresser, allowing them to achieve their ideal hairstyle.

[0150] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0151] Step 1:

[0152] User: Activates the camera function of the smartphone and takes a photo of his / her face. After taking the photo, he / she presses the "upload" button in the dedicated application to send the photo to the server.

[0153] Input: A photo of the user's face (JPEG or PNG format).

[0154] Output: A request to upload a face photo to the server.

[0155] Specific operation: Take a photo with your smartphone camera and use the app's upload function to send the photo to the server.

[0156] Step 2:

[0157] On the device, the application sends the user's face photo data and user ID to the server. The photo is sent using the HTTPS protocol.

[0158] Input: User's face photo data, user ID.

[0159] Output: Send face photo data to the server.

[0160] What it does: The application converts the face photo data and user ID into a binary format and sends it securely to the server using the HTTPS protocol.

[0161] Step 3:

[0162] Server: Stores the received face photo and user ID in a database, then performs preprocessing to input the photo data into the AI ​​analysis unit.

[0163] Input: Face photo data, user ID.

[0164] Output: Preprocessed facial photo data.

[0165] Specific operation: The server resizes the facial photo data, removes noise, and stores it in the database.

[0166] Step 4:

[0167] Server: Uses an AI analysis unit to analyze the facial features of the photo, specifically identifying facial contours, hair type, hair length, etc.

[0168] Input: Preprocessed facial photo data.

[0169] Output: Feature data such as facial contours, hair type, and hair length (JSON format).

[0170] Specific operation: The AI ​​analysis unit uses deep learning technology to analyze facial photos and extract feature data.

[0171] Step 5:

[0172] User: Select the desired hairstyle on the hairstyle selection screen of the dedicated application. For example, select "Bob Cut." After selecting, press the "Send" button to send the information to the server.

[0173] Enter: hairstyle selection.

[0174] Output: Request to send hairstyle information.

[0175] Specific actions: Scroll through the hairstyle thumbnails in the application, select "Bob Cut," and press the "Submit" button to submit the hairstyle information.

[0176] Step 6:

[0177] Terminal: Sends hairstyle information to the server. The selected hairstyle information is sent as text data.

[0178] Input: Hairstyle information.

[0179] Output: Sending hairstyle information to the server.

[0180] What it does: The application converts the selected hairstyle information into text format and sends it to the server using the HTTPS protocol.

[0181] Step 7:

[0182] Server: Based on the analysis results of the facial photo and the hairstyle selected by the user, the generative AI model generates the optimal haircut method and finished image. Specifically, the prompt "Based on the facial photo and the selected hairstyle, please generate the optimal haircut method and finished image" is input to the AI.

[0183] Input: Analysis result feature data, selected hairstyle information.

[0184] Output: The generated cutting method and finished image.

[0185] Specific operation: The server inputs the analysis results and selected hairstyle information into the generative AI model, and generates a finished image based on the prompt text.

[0186] Step 8:

[0187] Server: The generated finished image and cutting method data are encoded in JPEG or PNG format and sent to the user's device.

[0188] Input: Generated cutting method and finished image.

[0189] Output: Sends the finished image and cutting method data to the user's device.

[0190] What happens: The server encodes the generated data and sends it to the user's device using the HTTPS protocol.

[0191] Step 9:

[0192] Device: The received finished image is displayed in the dedicated application. After checking the displayed image, the user can save the image by pressing the "OK" button, or return to the hairstyle selection screen by pressing the "Reselect" button.

[0193] Input: Finished image and cutting method data.

[0194] Output: Saved image or hairstyle reselection request.

[0195] Specific behavior: The application displays the received data and performs the save or reselection process depending on the user's selection.

[0196] Step 10:

[0197] User: Saves the final image of the finished look and cutting method data in a dedicated application, and shows the screen on their smartphone to the hairdresser when they visit the salon.

[0198] Input: Saved finished image and cutting method data.

[0199] Output: Presentation to hairdresser.

[0200] Specific operation: Display the data stored in the dedicated application and show it to the hairdresser, or print out the data and bring it with you if necessary.

[0201] Step 11:

[0202] Hairdresser: Cuts the customer's hair according to their wishes, based on the presented image of the finished look and cutting method.

[0203] Input: The proposed finished image and cutting method data.

[0204] Output: The actual haircut.

[0205] Specific operation: Cuts hair based on the provided data to achieve the hairstyle desired by the user.

[0206] (Application example 1)

[0207] 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."

[0208] The present invention aims to provide a system that allows users to check the finished hairstyle in advance, and to provide a means for smoothly and effectively sharing information with actual beauty salons and facilitating communication with hairdressers. Another objective is to improve the reliability of the user's desired hairstyle and to increase the accuracy of guidelines for hairdressers when performing the cut.

[0209] 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.

[0210] In this invention, the server includes a means for a user to take a photo of their face and upload the photo, a means for analyzing the uploaded photo of their face to identify the facial contours, hair type, and hair length, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, and a means for displaying and sharing this information with the hairdresser via a smartphone at the hair salon. This allows the user to check the optimal hairstyle in advance and to smoothly share information with the hairdresser when the hairstyle is performed at the hair salon.

[0211] "User" refers to ordinary consumers who use the system, and in particular to those who take a photo of their own face to check the final hairstyle.

[0212] "Facial photo" refers to image data of a face that is taken by a user using a device such as a smartphone and uploaded to the system.

[0213] "Means for uploading" refers to the part of the application that includes the function to send a photograph of a user's face to a server via the Internet.

[0214] "Means of analysis" refers to the function of using an artificial intelligence model to identify facial contours, hair type, hair length, etc. from the facial photo received by the server.

[0215] "Means for generating the optimal cutting method and finished image" refers to the function in which the AI ​​model combines the hairstyle selected by the user with the analysis results of the facial photo, simulates the optimal hairstyle finish, and generates the results as data.

[0216] "Means for displaying" refers to the function of displaying the generated finished image on the user's smartphone or tablet, allowing the user to visually check it.

[0217] "Means for obtaining feedback" refers to the function that allows the user to input opinions and comments, including the level of satisfaction with the displayed finished image, through the application and transmit them to the server.

[0218] "A means of saving the final image of the finished look and data on the cutting method, and presenting it to the hairdresser" refers to the function of saving the image of the hairstyle that the user is satisfied with as digital data, and showing it to the hairdresser at the salon on the screen of a device such as a smartphone, or presenting it in printed form if necessary.

[0219] "A means of displaying and sharing this information with hairdressers via smartphones at beauty salons" refers to the function of displaying and sharing the finished image and cutting method saved by the user on a smartphone so that the hairdresser can visually confirm it at the beauty salon.

[0220] "Artificial intelligence model" refers to a machine learning algorithm used to simulate the outcome of a hairstyle, and in this invention is used in particular to analyze the features of a facial photograph and generate an optimal hairstyle.

[0221] "Server" refers to the central computer system that receives and analyzes the User's facial photograph and feedback, and stores and transmits the generated finished images.

[0222] This invention is a system that allows users to take a photo of themselves using a device such as a smartphone or tablet and check in advance how their desired hairstyle will look based on that photo. The following elements are required to implement this system: a device, a server, and a dedicated application.

[0223] System configuration

[0224] 1. Take and upload a photo of your face

[0225] Users take a photo of their face using the camera on their smartphone, and then press the upload button in the application to send the photo to the server.

[0226] The device sends the captured facial photo and user ID to the server via the application.

[0227] The server receives the facial photo and user information, converts the facial photo into a format suitable for analysis, and prepares it for input into the artificial intelligence model.

[0228] 2. Face photo analysis and hairstyle selection

[0229] The server inputs the received facial photo into an AI analysis unit to identify features such as facial contours, hair type, and hair length, which allows customization according to the user's hair condition.

[0230] The user selects the hairstyle they want on the hairstyle selection screen, and after selection, the information is also sent to the server.

[0231] 3. AI-based cutting method and finished image generation

[0232] The server uses an AI model to generate the optimal haircut method and finished image based on the analysis of the facial photo and the hairstyle selected by the user, allowing users to simulate the actual image after the haircut.

[0233] The server again transmits the generated finished image and cutting method data to the terminal.

[0234] 4. View the final image and get feedback

[0235] The device will then display the received image of the finished look to the user within the application. The user can check the image and press the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again.

[0236] 5. Sharing information with hairdressers

[0237] Users can save the final image of the finished look and cutting method they are satisfied with, and then go to the salon and present this information to the hairdresser. Specifically, they can show the screen on their smartphone to the hairdresser, or if necessary, bring a printout of the data with them.

[0238] The hairdresser will cut the customer's hair based on the presented image of the finished look and cutting method.

[0239] Hardware and software used

[0240] Hardware: Smartphone (ANDROID (registered trademark) / iOS), server equipped with high-performance CPU / GPU

[0241] Software: Smartphone app (iOS: Swift, Android: Kotlin), server side (Flask, Keras, OpenCV)

[0242] Specific examples

[0243] For example, consider the case where a user desires a shortcut.

[0244] The user is prompted to "Simulate the style of the shortcut."

[0245] The server receives the prompt, analyzes the facial photo, and generates the optimal shortcut image.

[0246] The server sends the generated finished image and cutting instructions to the user's terminal.

[0247] The user shows the image to the hairdresser at the salon and a specific cut plan is drawn up.

[0248] Prompt Sentence Examples

[0249] 1. Prompt: "Simulate a shortcut style based on a photo of the user's face."

[0250] 2. Prompt: "Generate the best possible finished image based on the user's desired hairstyle."

[0251] This allows users and hairdressers to smoothly share information to achieve their ideal hairstyle.

[0252] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0253] Step 1:

[0254] The user takes a photo of their face using the camera function of their smartphone and then presses the upload button in the application to send the photo to the server. The input data is the face photo and user ID, and the output is the image data sent to the server.

[0255] Step 2:

[0256] The server receives the uploaded facial photo and user information and converts the facial photo into a format suitable for analysis. This process mainly involves resizing and standardizing the image. The input data is the user's facial photo, and the output is image data in a format suitable for analysis.

[0257] Step 3:

[0258] The server analyzes facial photos. It inputs the image data into an artificial intelligence model (using Keras) to identify features such as facial contours, hair type, and hair length. The input data is resized and standardized image data, and the output is facial feature data.

[0259] Step 4:

[0260] The user selects the desired hairstyle on the application's hairstyle selection screen and sends the information to the server. The input data is the hairstyle ID selected by the user, and the output is the hairstyle data sent to the server.

[0261] Step 5:

[0262] The server uses an artificial intelligence model to generate the optimal haircut method and finished image based on the analysis of the facial photo and the hairstyle ID selected by the user. This process uses data analysis and a generative AI model to combine facial feature data and selected hairstyle data. The input data is facial feature data and hairstyle ID, and the output is the generated finished image and haircut method data.

[0263] Step 6:

[0264] The server then sends the generated finished image and cutting instructions to the user's device. The input data is the finished image and cutting instructions, and the output is the visual data sent to the user's smartphone.

[0265] Step 7:

[0266] The terminal displays the received finished image to the user in the application. The user checks the displayed image and presses the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again. The input data is the finished image received from the server, and the output is the user's feedback.

[0267] Step 8:

[0268] The user saves the final image of the finished look and data on the cutting method that they are satisfied with, and then goes to the salon and presents this. Specifically, they show the screen of their smartphone to the hairdresser, or if necessary, they bring a printed copy of the data. The input data is the saved image and cutting method data, and the output is what is presented at the salon.

[0269] Step 9:

[0270] The hairdresser cuts the user's hair based on the presented image of the finished look and cutting method. The input data is the image of the finished look and cutting method presented by the user, and the output is the actual hairstyle.

[0271] 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.

[0272] This invention is a system that allows users to take a photo of their face and check in advance how their desired hairstyle will look based on that photo, and it also combines an emotion engine that recognizes and reflects the user's emotions. To implement this system, the following elements are required: a device such as a smartphone or tablet, a server, a dedicated application, and an emotion engine.

[0273] System configuration

[0274] Take and upload a photo of your face

[0275] User: Take a photo of their face using the camera function on their smartphone. After taking the photo, the user presses the upload button in the application to send the photo to the server.

[0276] Device: The application sends the captured face photo and user ID to the server.

[0277] Server: Receives facial photos and user information and prepares the facial photos to be input into the AI ​​analysis unit.

[0278] Face photo analysis and hairstyle selection

[0279] Server: The received facial photo is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length. The facial photo is also analyzed to analyze the user's facial expressions, and the emotion engine recognizes the user's emotions.

[0280] User: Select the hairstyle they want on the hairstyle selection screen. After selection, the information is also sent to the server.

[0281] AI-based cutting method and finished image generation

[0282] Server: Based on the analysis of the facial photo, data on the user's emotions, and the hairstyle information selected by the user, the AI ​​model generates the optimal cutting method and finished image. By using the emotion engine, it can make adjustments based on the user's emotions.

[0283] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[0284] View the final image and get feedback

[0285] Device: The received finished image and cutting method data are displayed within the application, while the user's facial expression is recognized again and analyzed using the emotion engine.

[0286] User: Check the displayed image of the finished hairstyle and press the "OK" button if satisfied. If a negative emotion is detected from a change in facial expression, the system can automatically suggest an alternative hairstyle.

[0287] Sharing information with hairdressers

[0288] User: Save the final image of the finished look and cutting method that they are satisfied with, and then go to the salon and present this. Specifically, they can show the screen of their smartphone to the hairdresser, or if necessary, bring a printed copy of the data with them.

[0289] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method.

[0290] Specific examples

[0291] For example, a specific example will be given where the user desires a "bob cut."

[0292] 1. User: Take a photo of their face with their smartphone camera and upload it to the application. The emotion engine analyzes the user's facial expressions and identifies emotions such as joy, excitement, or anxiety.

[0293] 2. Device: Sends a photo of the face and basic information to the server.

[0294] 3. Server: Analyzes the facial photo to identify facial contours, hair type, and hair length, and then adds emotional information using an emotion engine.

[0295] 4. User: Selects a bob cut style. The emotion engine detects the user's emotion and sends emotional feedback for the selected style to the server.

[0296] 5. Server: The AI ​​model combines the analysis results, emotional information, and bob cut data to generate the optimal finished image.

[0297] 6. Server: Sends the generated finished image to the device.

[0298] 7. Device: The finished image is displayed in the app, and the emotion engine checks the user's facial expressions again.

[0299] 8. User: If satisfied with the image, press the "OK" button to save the data. Based on the emotional feedback, the system can suggest other styles.

[0300] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[0301] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[0302] This system reduces the gap between the user and the hairdresser, allowing them to achieve their ideal hairstyle. By using an emotion engine, it is possible to suggest styles based on the user's emotions, providing even higher satisfaction.

[0303] The processing flow will be explained below.

[0304] Step 1:

[0305] User: Use the camera on your smartphone to take a photo of yourself, preferably a high-resolution image.

[0306] Step 2:

[0307] Device: Check the captured facial photo and press the upload button in the application to send the facial photo and user ID to the server.

[0308] Step 3:

[0309] Server: Stores the received facial photos and user IDs and prepares to send the facial photos to the AI ​​analysis unit.

[0310] Step 4:

[0311] Server: The AI ​​analysis unit analyzes the facial photo and, in addition to facial contours, hair type, and hair length, the emotion engine recognizes emotions from the user's facial expressions.

[0312] Step 5:

[0313] Server: Stores the facial feature data including the recognized emotion data and proceeds to the next step.

[0314] Step 6:

[0315] Server: The system generates thumbnails of multiple standard hairstyles and sends the data to the device.

[0316] Step 7:

[0317] Device: Displays thumbnail images of multiple hairstyles so the user can choose the hairstyle they want.

[0318] Step 8:

[0319] User: Selects the hairstyle they want. After selection, this information is also sent to the server.

[0320] Step 9:

[0321] Server: The AI ​​model combines the analysis results, emotional data, and information about the hairstyle selected by the user to generate the optimal cutting method and finished image.

[0322] Step 10:

[0323] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[0324] Step 11:

[0325] Device: The received finished image and cutting method data are displayed within the application, while the emotion engine analyzes the user's facial expression again.

[0326] Step 12:

[0327] User: Check the displayed image of the finished product. If it is acceptable, press the "OK" button. If it is not, provide feedback and proceed to the next step.

[0328] Step 13:

[0329] Device: Sends user feedback and emotion engine analysis results to the server.

[0330] Step 14:

[0331] Server: Based on the feedback and sentiment data obtained, the AI ​​model suggests other hairstyles that would suit the user.

[0332] Step 15:

[0333] Server: Sends data on new suggested hairstyles to the device.

[0334] Step 16:

[0335] Terminal: Shows the proposed new hairstyle image.

[0336] Step 17:

[0337] User: Review the new final image and if satisfied, press the "OK" button. If not, provide further feedback and repeat the process from step 13.

[0338] Step 18:

[0339] Device: When the user presses the "OK" button, the final finished image and cutting method data are saved on the device.

[0340] Step 19:

[0341] User: Go to the hair salon and show the hairdresser the finished image and cutting method data saved on the smartphone screen. If necessary, you can also print it out and bring it with you.

[0342] Step 20:

[0343] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method data.

[0344] This detailed processing step allows users to receive hairstyle suggestions based on their emotions using the emotion engine, and also provides feedback on the final result, resulting in a highly satisfying haircut.

[0345] Example 2

[0346] 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."

[0347] When a user tells a hair salon what hairstyle they want, the actual result often differs from their expectations. This leads to lower user satisfaction and a lack of smooth communication with the hairdresser. Furthermore, conventional systems have difficulty proposing hairstyles that take the user's emotions into account, making it difficult to provide optimal suggestions for each individual user.

[0348] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to take a facial image of themselves and transmit the image, a means for transmitting the taken facial image to the server using a terminal, a means for the server to store the received facial image in a database and perform preprocessing, a means for analyzing the uploaded facial image and identifying the facial contour, hair type, and hair length, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, a means for transferring the generated finished image to the terminal and displaying it, a means for the user to check the displayed finished image and obtain feedback, and a means for the user to save the final finished image and data on the haircut method and present it to the service provider. This allows the user to check the desired hairstyle in advance and enables hairstyle suggestions based on their emotions, thereby improving user satisfaction and facilitating smoother communication with the hairdresser.

[0349] A "user" is an individual who uses the system to take a picture of their face and select a hairstyle.

[0350] A "face image" is a digital image of a user's face that is uploaded to the system.

[0351] The "server" is a computer system that analyzes the facial image received from the user and generates an image of the optimal hairstyle.

[0352] A "terminal" is a device used by a user to take a facial image and send it to a server, such as a smartphone or tablet.

[0353] A "database" is a system that manages data such as facial images, analysis results, and user information stored on a server.

[0354] "Preprocessing" refers to the process by which the server converts the facial images it receives into an appropriate format and prepares them for analysis.

[0355] The "AI Analysis Unit" is a system that uses artificial intelligence to analyze facial images and identify facial contours, hair type, hair length, etc.

[0356] The "emotion engine" is a technology that analyzes emotions from a user's facial image and reflects them in hairstyle suggestions.

[0357] The "cutting method" is a specific haircutting method to achieve the ideal result based on the hairstyle selected by the user.

[0358] The "finished image" is an image of the hairstyle applied to the user's face, generated based on the analysis results and the hairstyle selected by the user.

[0359] "Feedback" refers to the user's evaluation and opinions on the displayed finished video, and is information that the system uses to reflect in its next suggestions and corrections.

[0360] A "service provider" is a professional, such as a hairdresser or barber, who actually provides haircutting services to users.

[0361] The present invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that image. Furthermore, by combining it with an emotion engine that recognizes and reflects the user's emotions, it is possible to achieve more sophisticated and personalized hairstyle suggestions. The specific configuration and procedures for implementing this system are as follows.

[0362] System Configuration

[0363] 1. User Device

[0364] Users take a photo of their face using a device such as a smartphone or tablet. A dedicated application is installed on the device, and they have the means to upload the image to the server through this application. At this time, the emotion engine analyzes the user's facial expressions and identifies the user's emotions.

[0365] 2. Server

[0366] The server has several functions:

[0367] Image reception and preprocessing: Receives the face image and user ID sent from the user's device and performs preprocessing such as image resizing and format conversion.

[0368] AI Analysis Unit: The pre-processed facial image is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length. The emotion engine then analyzes the user's facial expressions to obtain emotional information.

[0369] Hairstyle generation: Based on the analysis results, the user's emotional data, and the hairstyle information selected by the user, the generative AI model generates the optimal cutting method and finished image.

[0370] Data transfer: The generated finished image and cutting method data are sent to the user's device.

[0371] 3. Database

[0372] The database runs on a server and stores and manages the user's facial image, analysis results, emotional data, generated finished footage, and cutting method data.

[0373] Specific examples

[0374] Step-by-step process example

[0375] Below is a specific example of when a user wants a bob cut.

[0376] 1. User: Takes a picture of their face with their smartphone camera and uploads it to the application. The emotion engine analyzes the user's facial expressions and identifies emotions such as joy, excitement, or anxiety.

[0377] 2. Device: Sends face image and basic information to the server.

[0378] 3. Server: Analyzes the facial image to identify facial contours, hair type, and hair length, and then adds emotional information using an emotion engine.

[0379] 4. User: Selects a bob cut style. The emotion engine detects the user's emotion and sends emotional feedback for the selected style to the server.

[0380] 5. Server: The analysis results, emotional information, and bob cut data are combined, and the generative AI model generates the optimal finished video.

[0381] 6. Server: Sends the generated finished video to the terminal.

[0382] 7. Device: The finished video is displayed in the app, and the emotion engine checks the user's facial expressions again.

[0383] 8. User: If satisfied with the image, press the "OK" button to save the data. Based on the emotional feedback, the system can suggest other styles.

[0384] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[0385] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[0386] Prompt Sentence Examples

[0387] For example, if the user wants a bob cut, the prompt text is:

[0388] "I would like a bob cut. My current hair length is shoulder-length and wavy. I'm excited."

[0389] This system reduces the gap between the user and the hairdresser, allowing them to see their ideal hairstyle in advance. By using an emotion engine, it is possible to suggest styles based on the user's emotions, improving user satisfaction.

[0390] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0391] Step 1:

[0392] User: Take a picture of their face using their smartphone camera.

[0393] Specific actions: Open the camera app and adjust it so that your entire face is clearly visible under good lighting conditions.

[0394] Input: A face image.

[0395] Output: The captured face image.

[0396] Step 2:

[0397] Device: Uses a dedicated application to send the captured facial image to the server.

[0398] Specific operation: Press the upload button in the application to send data including the face image and user ID to the server via HTTPS protocol.

[0399] Input: A captured face image and user ID.

[0400] Output: Spatial transfer successful message to server.

[0401] Step 3:

[0402] Server: Stores the received face images and user IDs in a database and performs preprocessing.

[0403] Specific operation: Convert the facial image to a standard resolution and format (e.g., resize to 256x256 pixels).

[0404] Input: Face image and user ID.

[0405] Output: Preprocessed face image.

[0406] Step 4:

[0407] Server: The pre-processed facial image is input into the AI ​​analysis unit to identify features such as facial contours, hair type, and hair length.

[0408] Specific operation: Uses a deep learning model to extract facial features and output analysis results.

[0409] Input: Preprocessed face image.

[0410] Output: Facial feature data (shape, hair type, hair length, etc.).

[0411] Step 5:

[0412] Server: The emotion engine analyzes facial expressions in the facial images to identify the user's emotional state.

[0413] Specific behavior: Use a facial expression recognition algorithm to generate emotion labels such as happiness, excitement, and anxiety.

[0414] Input: Preprocessed face image.

[0415] Output: Emotion data (happiness, excitement, anxiety, etc.).

[0416] Step 6:

[0417] User: Selects the desired hairstyle through the user interface (e.g., bob cut).

[0418] Specific operations: Select the desired hairstyle on the hairstyle selection screen of the application and press the decision button.

[0419] Input: Your desired hairstyle selection information.

[0420] Output: Selected hairstyle information.

[0421] Step 7:

[0422] Server: The generative AI model combines the analysis results, the user's emotional data, and the selected hairstyle information to generate the optimal cutting method and a video of the finished product.

[0423] Specific operation: All data (facial feature data, emotional data, hairstyle information) is input and the AI ​​model generates the optimal finished image.

[0424] Input: Facial feature data, emotion data, hairstyle information.

[0425] Output: Optimal cutting method and finished image.

[0426] Step 8:

[0427] Server: Transfers the generated finished video and cutting method data to the terminal.

[0428] Specific operation: The generated data is sent to the terminal using the HTTPS protocol.

[0429] Input: Optimal cutting method and finished footage.

[0430] Output: A transmission completion message.

[0431] Step 9:

[0432] Terminal: The received finished image and cutting method data are displayed within the application.

[0433] Specific operation: The finished video is displayed on the mobile application screen and an interface is provided for collecting feedback.

[0434] Input: Received finished footage and cutting method.

[0435] Output: The application display screen.

[0436] Step 10:

[0437] User: Check the displayed finished image, and if satisfied, press the "OK" button to send feedback to the system.

[0438] Specific actions: Check the finished video in detail, and if you are satisfied, press the "OK" button. If necessary, enter feedback comments.

[0439] Input: Feedback on how the hairstyle turned out.

[0440] Output: Feedback information.

[0441] Step 11:

[0442] User: Save the final image and cutting method data and present it when going to the hair salon.

[0443] Specific actions: View the saved data on your smartphone screen and show it to your hairdresser, or print it out and bring it with you if necessary.

[0444] Input: Final footage and cutting data.

[0445] Output: Presentation to hairdresser.

[0446] Step 12:

[0447] Hairdresser: Cuts the user's hair according to their wishes, based on the information provided.

[0448] Specific actions: Based on the presented data, confirm the cutting method and then perform the actual cutting based on that.

[0449] Input: User-provided cutting method and finished footage.

[0450] Output: The finished hairstyle.

[0451] (Application example 2)

[0452] 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."

[0453] Conventional hairstyle simulation systems were unable to suggest hairstyles that reflected the user's emotions, and were unable to sufficiently increase user satisfaction. Furthermore, the lack of a system that effectively utilized user feedback to make new suggestions made the process of finding the optimal hairstyle cumbersome. Therefore, there was a need for a system that could suggest optimal hairstyles based on the user's emotions and efficiently utilize feedback to make further suggestions.

[0454] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0455] In this invention, the server includes a means for recognizing the user's emotions and adding that information to the analysis results, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, and a means for displaying the generated finished image and reanalyzing the user's facial expression to obtain feedback. This makes it possible to propose an optimal hairstyle based on the user's emotions. Furthermore, by automatically proposing new hairstyles based on the feedback, the user can efficiently find their ideal hairstyle.

[0456] A "user" is an individual who uses the system to simulate their own hairstyle.

[0457] A "face photo" is an image of a face taken by a user using an information processing device such as a smartphone.

[0458] The "means for uploading" is a function that allows a user to send a photograph of their face taken to a server via the Internet.

[0459] "Means for analysis" refers to software or algorithms that analyze uploaded facial photos and identify facial features such as facial contours, hair type, and hair length.

[0460] "Emotion recognition means" refers to technology that analyzes facial expressions in facial photos and feedback to identify the user's emotional state (happiness, anxiety, excitement, etc.).

[0461] The "means of fusion" is a function that combines analyzed facial feature information with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[0462] The "means of generation" is an algorithm that uses an AI model to create the optimal hairstyle cutting method and finished image based on the fused data.

[0463] The "display means" is a method for displaying the generated finished image on the display of the user's information processing device.

[0464] The "means for reanalyzing and obtaining feedback" is a technique for reanalyzing the facial expressions shown by the user in response to the displayed finished image and obtaining emotional feedback.

[0465] "Automatic suggestion method" is a function in which AI suggests alternative optimal hairstyles based on user feedback.

[0466] The "means for saving" is a method for saving the finished image and cutting method data that the user is satisfied with in a digital format in a recording device.

[0467] The "presenting means" is a means for displaying the saved cut information on the screen of an information processing device or on a recording medium to show it to the hairdresser.

[0468] An "information processing device" is a device that processes digital data, such as a smartphone, tablet, or personal computer.

[0469] A "recording medium" is a physical medium used to store or record data, such as paper, a USB memory stick, or a CD.

[0470] "Server" means a remote computing device that receives, analyzes, and stores uploaded user facial photographs and associated data.

[0471] To build a system that realizes this application example, the following hardware and software are used.

[0472] Hardware

[0473] User device: Information processing device such as smartphone, tablet, PC, etc.

[0474] Server: A remote computing device that analyzes facial photos, recognizes emotions, and generates hairstyles.

[0475] software

[0476] Facial recognition software: Libraries for extracting facial features, such as OpenCV or dlib.

[0477] Emotion Recognition Engine: A library for analyzing facial expressions and recognizing user emotions. It uses machine learning models using TENSORFLOW (registered trademark) and Keras.

[0478] Hairstyle Generation Model: Uses an AI model to generate optimal hairstyles based on facial features and emotional information. Utilizes TensorFlow and PyTorch.

[0479] Specific methods for data processing and calculation

[0480] Taking and uploading a photo of your face

[0481] Users take a photo of themselves using their smartphone camera and upload it to the server through the application interface, along with their user ID.

[0482] Facial photo analysis and emotion recognition

[0483] The server uses facial recognition software to analyze the uploaded facial photo and extract features such as facial contours, hair type, and hair length, while simultaneously using an emotion recognition engine to identify emotions from the user's facial expressions.

[0484] Hairstyle generation

[0485] The system combines the user's selected hairstyle with facial features and emotional information, and uses a hairstyle generation model to generate the optimal cutting method and finished image. This image is generated using an AI model and is also adjusted according to the user's emotions.

[0486] Display and feedback of the finished image

[0487] The server then sends the resulting image to the user's device, where it is displayed within the application. The user's facial expressions are analyzed again to obtain feedback. If a negative emotion is detected, the system automatically suggests an alternative hairstyle.

[0488] Saving and presenting the final image

[0489] Once the user is satisfied with the final look and cutting method, the data is saved and when they go to the salon, they can show the smartphone screen or bring a printed copy of the data to communicate their wishes to the hairdresser.

[0490] Specific examples

[0491] For example, if the user enters the following prompt sentence, the system will suggest suitable hairstyles:

[0492] Example prompt sentence:

[0493] Users take a photo of themselves with their smartphone and upload it to the application. The application analyzes the user's photo and provides the ability to try out various hairstyles. It also has an assistant function that recognizes the user's emotions and recommends the best hairstyle based on that emotion.

[0494] This allows users to check the optimal hairstyle based on their facial photo and emotions, and efficiently request a haircut at a salon. This system not only increases user satisfaction, but also facilitates smooth communication with hairdressers.

[0495] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0496] Step 1:

[0497] The user takes a photo of their face using the smartphone camera. Once the photo is taken, they press the upload button in the application. This causes the device to send the photo and user ID to the server. The input includes the photo and user ID, and the output includes the photo and user ID sent to the server.

[0498] Step 2:

[0499] The server analyzes the received facial photo using facial recognition software (e.g., OpenCV). Specifically, it extracts features such as facial contours, hair type, and hair length. At the same time, it uses an emotion recognition engine (e.g., using TensorFlow or Keras) to identify emotions from the user's facial expressions. The facial photo is given as input, and facial feature data and emotion data are generated as output.

[0500] Step 3:

[0501] The user selects the desired hairstyle on the hairstyle selection screen. The selected hairstyle information is sent from the terminal to the server. The user's hairstyle selection is the input, and the selected hairstyle information is sent to the server as the output.

[0502] Step 4:

[0503] The server combines the analyzed facial feature data, emotion data, and the user-selected hairstyle information. This allows a hairstyle generation model (using, for example, TensorFlow or PyTorch) to generate the optimal haircutting method and finished image. Given the facial feature data, emotion data, and selected hairstyle information as input, the generated finished image and haircutting method data are obtained as output.

[0504] Step 5:

[0505] The server transmits the generated finished image and cutting method data to the terminal. The generated finished image and cutting method data are included as input, and these data are transmitted to the terminal as output.

[0506] Step 6:

[0507] The device displays the received finished image in the application for the user to confirm. It then analyzes the user's facial expression again to obtain emotional feedback. If the server detects a negative emotion based on this feedback, it automatically suggests a different hairstyle. The user's facial expression is given as input, and emotional feedback and a new hairstyle suggestion are obtained as output.

[0508] Step 7:

[0509] When the user is satisfied with the final image and cutting method, the data is saved. By presenting the saved data when visiting the salon, the user can accurately convey their wishes to the hairdresser. The finalized image of the final image and cutting method data are given as input, and these data are saved as output.

[0510] 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.

[0511] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0512] 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.

[0513] [Second embodiment]

[0514] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0515] 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.

[0516] 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).

[0517] 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.

[0518] 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.

[0519] 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).

[0520] 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.

[0521] 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.

[0522] 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.

[0523] 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.

[0524] 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.

[0525] 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."

[0526] This invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that photo. The following elements are required to implement this system: a device such as a smartphone or tablet, a server, and a dedicated application.

[0527] System configuration

[0528] Take and upload a photo of your face

[0529] User: Take a photo of their face using the camera function on their smartphone. After taking the photo, the user presses the upload button in the application to send the photo to the server.

[0530] Device: The application sends the captured face photo and user ID to the server.

[0531] Server: Receives facial photos and user information and prepares the facial photos to be input into the AI ​​model.

[0532] Face photo analysis and hairstyle selection

[0533] Server: The received facial photo is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length, which allows customization according to the user's hair condition.

[0534] User: Select the hairstyle they want on the hairstyle selection screen. After selection, the information is also sent to the server.

[0535] AI-based cutting method and finished image generation

[0536] Server: Based on the analysis of the facial photo and the hairstyle selected by the user, the AI ​​model generates the optimal cutting method and finished image, allowing users to simulate the actual image after the haircut.

[0537] Server: Sends the generated finished image and cutting method data to the terminal.

[0538] View the final image and get feedback

[0539] Device: The received image of the finished hairstyle is displayed to the user within the application. The user checks the displayed image and presses the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again.

[0540] Sharing information with hairdressers

[0541] User: Save the final image of the finished look and cutting method that they are satisfied with, and then go to the salon and present this. Specifically, they can show the screen of their smartphone to the hairdresser, or if necessary, bring a printed copy of the data with them.

[0542] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method.

[0543] Specific examples

[0544] For example, a specific example will be given where the user desires a "bob cut."

[0545] 1. User: Take a photo of their face with their smartphone camera and upload it to the application.

[0546] 2. Device: Sends a photo of the face and basic information to the server.

[0547] 3. Server: Analyzes the facial photo and identifies facial contours, hair type, and hair length.

[0548] 4. User: Choose a bob cut style.

[0549] 5. Server: The analysis results are combined with the bob cut data, and the AI ​​model generates the optimal finished image.

[0550] 6. Server: Sends the generated finished image to the device.

[0551] 7. Device: The finished image is displayed in the app and the user is asked to confirm.

[0552] 8. User: Once satisfied with the image, presses the "OK" button to save the data.

[0553] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[0554] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[0555] This system reduces the gap in results between the user and the hairdresser, allowing them to achieve their ideal hairstyle.

[0556] The processing flow will be explained below.

[0557] Step 1:

[0558] User: Use the camera on your smartphone to take a photo of yourself, preferably a high-resolution image.

[0559] Step 2:

[0560] Device: Check the captured facial photo and press the upload button in the application to send the facial photo and user ID to the server.

[0561] Step 3:

[0562] Server: Stores the received facial photos and user IDs and prepares to send the facial photos to the AI ​​analysis unit.

[0563] Step 4:

[0564] Server: The AI ​​analysis unit analyzes the facial photo to identify facial contours, hair type, and hair length, sometimes using external systems or cloud services.

[0565] Step 5:

[0566] User: Within the application, select the desired hairstyle from the thumbnails of multiple hairstyles displayed.

[0567] Step 6:

[0568] Device: Sends the selected hairstyle information to the server.

[0569] Step 7:

[0570] Server: The AI ​​model combines the analysis results with the hairstyle information selected by the user to generate the optimal cutting method and finished image.

[0571] Step 8:

[0572] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[0573] Step 9:

[0574] Terminal: The received finished image and cutting method data are displayed within the application.

[0575] Step 10:

[0576] User: Check the displayed image of the finished look, and if you are satisfied, press the "OK" button. If you are not satisfied, select another hairstyle and repeat the steps from step 5.

[0577] Step 11:

[0578] Device: When the user presses the "OK" button, the final finished image and cutting method data are saved on the device.

[0579] Step 12:

[0580] User: Go to the hair salon and show the hairdresser the finished image and cutting method data saved on the smartphone screen. If necessary, you can also print it out and bring it with you.

[0581] Step 13:

[0582] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method data.

[0583] Example 1

[0584] 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."

[0585] Conventional hairstyle selection systems have had the problem that it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, leading to dissatisfaction with the finished product. Also, few systems allow users to simulate the finished hairstyle in advance based on a photo of their own face. As a result, a communication gap occurs between the user and the hairdresser, making it difficult to achieve the ideal hairstyle.

[0586] 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.

[0587] In this invention, the server includes a means for a user to take a photo of their face and upload the photo, a means for analyzing the uploaded photo of their face to identify the facial contours, hair type, and hair length, and a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image. This allows the user to check in advance the finished image of the hairstyle based on their face photo, and makes it possible to present specific haircut information to the hairdresser.

[0588] "User" refers to an individual who uses the system to take a photo of themselves and select the hairstyle they desire.

[0589] "Terminal" refers to a device used by a user, such as a smartphone or tablet.

[0590] "Server" means the computer system that has the central function of receiving and processing uploaded photos and selected hairstyles.

[0591] "Taking and uploading a photo of your face" refers to the process in which a user takes a photo of their face using the device's camera and sends the photo to the server.

[0592] "Facial photo analysis" refers to the process of identifying facial contours, hair type, and hair length based on a facial photo uploaded to a server.

[0593] The "analysis results" are data obtained from facial photos processed by AI, and include information such as facial contours, hair type, and hair length.

[0594] "Hairstyle selection" refers to the act of a user selecting the hairstyle they want within a dedicated application.

[0595] "Hairstyle information" is data relating to the hairstyle selected by the user, and the cutting method and finished image are generated based on this information.

[0596] "Cutting method" refers to the haircutting method and treatment procedure suggested according to the hairstyle selected by the user.

[0597] "Finished Image" refers to an image generated by the AI ​​model that shows how the selected hairstyle will look on the user's face.

[0598] "Getting feedback" refers to the process of users checking their satisfaction with the displayed finished image and obtaining the results.

[0599] "Generative AI model" refers to artificial intelligence technology that generates the optimal cutting method and finished image based on a facial photo and hairstyle information.

[0600] "Means of presenting to the hairdresser on a smartphone or in printed form" refers to the means by which the user can show the hairdresser the haircut information saved by the user, including using the screen of a digital device or a paper printout.

[0601] "Artificial intelligence" refers to the technology that analyzes facial photos and performs computational processing to generate cutting methods and finished images.

[0602] This invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that photo. The following elements are required to implement this system: a device such as a smartphone or tablet, a server, and a dedicated application.

[0603] System configuration

[0604] Take and upload a photo of your face

[0605] User: Uses the camera function of the smartphone to take a photo of his / her face. After taking the photo, he / she presses the "upload" button in the dedicated application to send the photo to the server.

[0606] Device: The application sends the user's face photo data and user ID to the server. The photo is sent in JPEG or PNG format.

[0607] Preparation for facial photo analysis

[0608] Server: Stores the received face photo and user ID in a database. Then, it performs pre-processing to input the photo data into the AI ​​analysis unit. This pre-processing includes image resizing and noise removal.

[0609] Facial photo analysis

[0610] Server: The AI ​​analysis unit is used to analyze the facial features of the photo, specifically identifying facial contours, hair type, hair length, etc. The analysis results are saved in JSON format for subsequent processing.

[0611] Hairstyle selection

[0612] User: Select the desired hairstyle on the hairstyle selection screen of the dedicated application. For example, select "Bob Cut." After selecting, press the "Send" button to send the information to the server.

[0613] Terminal: Sends hairstyle information to the server. The selected hairstyle information is sent as text data.

[0614] AI-based cutting method and finished image generation

[0615] Server: Based on the analysis results of the facial photo and the hairstyle selected by the user, the generative AI model generates the optimal haircut method and finished image. Specifically, the prompt "Based on the facial photo and the selected hairstyle, please generate the optimal haircut method and finished image" is input to the AI.

[0616] Server: The generated finished image and cutting method data are encoded in JPEG or PNG format and sent to the user's device.

[0617] View the final image and get feedback

[0618] Device: The received finished image is displayed in the dedicated application. After checking the displayed image, the user can save the image by pressing the "OK" button, or return to the hairstyle selection screen by pressing the "Reselect" button.

[0619] User: If you are satisfied with the final image, press the "OK" button to save the data, but if you are not satisfied, select the hairstyle again.

[0620] Sharing information with hairdressers

[0621] User: Saves the final image of the finished look and cutting method data in a dedicated application, and shows the screen on their smartphone to the hairdresser when they visit the salon.

[0622] Hairdresser: Cuts the customer's hair according to their wishes, based on the presented image of the finished look and cutting method.

[0623] Specific examples

[0624] For example, a specific example will be given where the user desires a "bob cut."

[0625] User: Take a photo of their face with their smartphone camera and upload it to the application.

[0626] Device: Sends a photo of your face and basic information to the server.

[0627] Server: Analyzes facial photos to identify facial contours, hair type, and hair length.

[0628] User: Select "BobCut" on the application selection screen.

[0629] Server: The analysis results are combined with the "bob cut" style data, and the generative AI model generates the optimal finished image. Example prompt: "Generate the best bob cut style for this user based on their face photo."

[0630] Server: Sends the finished image generated by the AI ​​model to the user's device.

[0631] On device: The finished image is displayed in the app and the user is asked to confirm.

[0632] User: Once satisfied with the image, presses the "OK" button to save the data.

[0633] User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[0634] Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[0635] This reduces the gap in the results between the user and the hairdresser, allowing them to achieve their ideal hairstyle.

[0636] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0637] Step 1:

[0638] User: Activates the camera function of the smartphone and takes a photo of his / her face. After taking the photo, he / she presses the "upload" button in the dedicated application to send the photo to the server.

[0639] Input: A photo of the user's face (JPEG or PNG format).

[0640] Output: A request to upload a face photo to the server.

[0641] Specific operation: Take a photo with your smartphone camera and use the app's upload function to send the photo to the server.

[0642] Step 2:

[0643] On the device, the application sends the user's face photo data and user ID to the server. The photo is sent using the HTTPS protocol.

[0644] Input: User's face photo data, user ID.

[0645] Output: Send face photo data to the server.

[0646] What it does: The application converts the face photo data and user ID into a binary format and sends it securely to the server using the HTTPS protocol.

[0647] Step 3:

[0648] Server: Stores the received face photo and user ID in a database, then performs preprocessing to input the photo data into the AI ​​analysis unit.

[0649] Input: Face photo data, user ID.

[0650] Output: Preprocessed facial photo data.

[0651] Specific operation: The server resizes the facial photo data, removes noise, and stores it in the database.

[0652] Step 4:

[0653] Server: Uses an AI analysis unit to analyze the facial features of the photo, specifically identifying facial contours, hair type, hair length, etc.

[0654] Input: Preprocessed facial photo data.

[0655] Output: Feature data such as facial contours, hair type, and hair length (JSON format).

[0656] Specific operation: The AI ​​analysis unit uses deep learning technology to analyze facial photos and extract feature data.

[0657] Step 5:

[0658] User: Select the desired hairstyle on the hairstyle selection screen of the dedicated application. For example, select "Bob Cut." After selecting, press the "Send" button to send the information to the server.

[0659] Enter: hairstyle selection.

[0660] Output: Request to send hairstyle information.

[0661] Specific actions: Scroll through the hairstyle thumbnails in the application, select "Bob Cut," and press the "Submit" button to submit the hairstyle information.

[0662] Step 6:

[0663] Terminal: Sends hairstyle information to the server. The selected hairstyle information is sent as text data.

[0664] Input: Hairstyle information.

[0665] Output: Sending hairstyle information to the server.

[0666] What it does: The application converts the selected hairstyle information into text format and sends it to the server using the HTTPS protocol.

[0667] Step 7:

[0668] Server: Based on the analysis results of the facial photo and the hairstyle selected by the user, the generative AI model generates the optimal haircut method and finished image. Specifically, the prompt "Based on the facial photo and the selected hairstyle, please generate the optimal haircut method and finished image" is input to the AI.

[0669] Input: Analysis result feature data, selected hairstyle information.

[0670] Output: The generated cutting method and finished image.

[0671] Specific operation: The server inputs the analysis results and selected hairstyle information into the generative AI model, and generates a finished image based on the prompt text.

[0672] Step 8:

[0673] Server: The generated finished image and cutting method data are encoded in JPEG or PNG format and sent to the user's device.

[0674] Input: Generated cutting method and finished image.

[0675] Output: Sends the finished image and cutting method data to the user's device.

[0676] What happens: The server encodes the generated data and sends it to the user's device using the HTTPS protocol.

[0677] Step 9:

[0678] Device: The received finished image is displayed in the dedicated application. After checking the displayed image, the user can save the image by pressing the "OK" button, or return to the hairstyle selection screen by pressing the "Reselect" button.

[0679] Input: Finished image and cutting method data.

[0680] Output: Saved image or hairstyle reselection request.

[0681] Specific behavior: The application displays the received data and performs the save or reselection process depending on the user's selection.

[0682] Step 10:

[0683] User: Saves the final image of the finished look and cutting method data in a dedicated application, and shows the screen on their smartphone to the hairdresser when they visit the salon.

[0684] Input: Saved finished image and cutting method data.

[0685] Output: Presentation to hairdresser.

[0686] Specific operation: Display the data stored in the dedicated application and show it to the hairdresser, or print out the data and bring it with you if necessary.

[0687] Step 11:

[0688] Hairdresser: Cuts the customer's hair according to their wishes, based on the presented image of the finished look and cutting method.

[0689] Input: The proposed finished image and cutting method data.

[0690] Output: The actual haircut.

[0691] Specific operation: Cuts hair based on the provided data to achieve the hairstyle desired by the user.

[0692] (Application example 1)

[0693] 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."

[0694] The present invention aims to provide a system that allows users to check the finished hairstyle in advance, and to provide a means for smoothly and effectively sharing information with actual beauty salons and facilitating communication with hairdressers. Another objective is to improve the reliability of the user's desired hairstyle and to increase the accuracy of guidelines for hairdressers when performing the cut.

[0695] 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.

[0696] In this invention, the server includes a means for a user to take a photo of their face and upload the photo, a means for analyzing the uploaded photo of their face to identify the facial contours, hair type, and hair length, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, and a means for displaying and sharing this information with the hairdresser via a smartphone at the hair salon. This allows the user to check the optimal hairstyle in advance and to smoothly share information with the hairdresser when the hairstyle is performed at the hair salon.

[0697] "User" refers to ordinary consumers who use the system, and in particular to those who take a photo of their own face to check the final hairstyle.

[0698] "Facial photo" refers to image data of a face that is taken by a user using a device such as a smartphone and uploaded to the system.

[0699] "Means for uploading" refers to the part of the application that includes the function to send a photograph of a user's face to a server via the Internet.

[0700] "Means of analysis" refers to the function of using an artificial intelligence model to identify facial contours, hair type, hair length, etc. from the facial photo received by the server.

[0701] "Means for generating the optimal cutting method and finished image" refers to the function in which the AI ​​model combines the hairstyle selected by the user with the analysis results of the facial photo, simulates the optimal hairstyle finish, and generates the results as data.

[0702] "Means for displaying" refers to the function of displaying the generated finished image on the user's smartphone or tablet, allowing the user to visually check it.

[0703] "Means for obtaining feedback" refers to the function that allows the user to input opinions and comments, including the level of satisfaction with the displayed finished image, through the application and transmit them to the server.

[0704] "A means of saving the final image of the finished look and data on the cutting method, and presenting it to the hairdresser" refers to the function of saving the image of the hairstyle that the user is satisfied with as digital data, and showing it to the hairdresser at the salon on the screen of a device such as a smartphone, or presenting it in printed form if necessary.

[0705] "A means of displaying and sharing this information with hairdressers via smartphones at beauty salons" refers to the function of displaying and sharing the finished image and cutting method saved by the user on a smartphone so that the hairdresser can visually confirm it at the beauty salon.

[0706] "Artificial intelligence model" refers to a machine learning algorithm used to simulate the outcome of a hairstyle, and in this invention is used in particular to analyze the features of a facial photograph and generate an optimal hairstyle.

[0707] "Server" refers to the central computer system that receives and analyzes the User's facial photograph and feedback, and stores and transmits the generated finished images.

[0708] This invention is a system that allows users to take a photo of themselves using a device such as a smartphone or tablet and check in advance how their desired hairstyle will look based on that photo. The following elements are required to implement this system: a device, a server, and a dedicated application.

[0709] System configuration

[0710] 1. Take and upload a photo of your face

[0711] Users take a photo of their face using the camera on their smartphone, and then press the upload button in the application to send the photo to the server.

[0712] The device sends the captured facial photo and user ID to the server via the application.

[0713] The server receives the facial photo and user information, converts the facial photo into a format suitable for analysis, and prepares it for input into the artificial intelligence model.

[0714] 2. Face photo analysis and hairstyle selection

[0715] The server inputs the received facial photo into an AI analysis unit to identify features such as facial contours, hair type, and hair length, which allows customization according to the user's hair condition.

[0716] The user selects the hairstyle they want on the hairstyle selection screen, and after selection, the information is also sent to the server.

[0717] 3. AI-based cutting method and finished image generation

[0718] The server uses an AI model to generate the optimal haircut method and finished image based on the analysis of the facial photo and the hairstyle selected by the user, allowing users to simulate the actual image after the haircut.

[0719] The server again transmits the generated finished image and cutting method data to the terminal.

[0720] 4. View the final image and get feedback

[0721] The device will then display the received image of the finished look to the user within the application. The user can check the image and press the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again.

[0722] 5. Sharing information with hairdressers

[0723] Users can save the final image of the finished look and cutting method they are satisfied with, and then go to the salon and present this information to the hairdresser. Specifically, they can show the screen on their smartphone to the hairdresser, or if necessary, bring a printout of the data with them.

[0724] The hairdresser will cut the customer's hair based on the presented image of the finished look and cutting method.

[0725] Hardware and software used

[0726] Hardware: Smartphone (Android / iOS), server with high-performance CPU / GPU

[0727] Software: Smartphone app (iOS: Swift, Android: Kotlin), server side (Flask, Keras, OpenCV)

[0728] Specific examples

[0729] For example, consider the case where a user desires a shortcut.

[0730] The user is prompted to "Simulate the style of the shortcut."

[0731] The server receives the prompt, analyzes the facial photo, and generates the optimal shortcut image.

[0732] The server sends the generated finished image and cutting instructions to the user's terminal.

[0733] The user shows the image to the hairdresser at the salon and a specific cut plan is drawn up.

[0734] Prompt Sentence Examples

[0735] 1. Prompt: "Simulate a shortcut style based on a photo of the user's face."

[0736] 2. Prompt: "Generate the best possible finished image based on the user's desired hairstyle."

[0737] This allows users and hairdressers to smoothly share information to achieve their ideal hairstyle.

[0738] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0739] Step 1:

[0740] The user takes a photo of their face using the camera function of their smartphone and then presses the upload button in the application to send the photo to the server. The input data is the face photo and user ID, and the output is the image data sent to the server.

[0741] Step 2:

[0742] The server receives the uploaded facial photo and user information and converts the facial photo into a format suitable for analysis. This process mainly involves resizing and standardizing the image. The input data is the user's facial photo, and the output is image data in a format suitable for analysis.

[0743] Step 3:

[0744] The server analyzes facial photos. It inputs the image data into an artificial intelligence model (using Keras) to identify features such as facial contours, hair type, and hair length. The input data is resized and standardized image data, and the output is facial feature data.

[0745] Step 4:

[0746] The user selects the desired hairstyle on the application's hairstyle selection screen and sends the information to the server. The input data is the hairstyle ID selected by the user, and the output is the hairstyle data sent to the server.

[0747] Step 5:

[0748] The server uses an artificial intelligence model to generate the optimal haircut method and finished image based on the analysis of the facial photo and the hairstyle ID selected by the user. This process uses data analysis and a generative AI model to combine facial feature data and selected hairstyle data. The input data is facial feature data and hairstyle ID, and the output is the generated finished image and haircut method data.

[0749] Step 6:

[0750] The server then sends the generated finished image and cutting instructions to the user's device. The input data is the finished image and cutting instructions, and the output is the visual data sent to the user's smartphone.

[0751] Step 7:

[0752] The terminal displays the received finished image to the user in the application. The user checks the displayed image and presses the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again. The input data is the finished image received from the server, and the output is the user's feedback.

[0753] Step 8:

[0754] The user saves the final image of the finished look and data on the cutting method that they are satisfied with, and then goes to the salon and presents this. Specifically, they show the screen of their smartphone to the hairdresser, or if necessary, they bring a printed copy of the data. The input data is the saved image and cutting method data, and the output is what is presented at the salon.

[0755] Step 9:

[0756] The hairdresser cuts the user's hair based on the presented image of the finished look and cutting method. The input data is the image of the finished look and cutting method presented by the user, and the output is the actual hairstyle.

[0757] 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.

[0758] This invention is a system that allows users to take a photo of their face and check in advance how their desired hairstyle will look based on that photo, and it also combines an emotion engine that recognizes and reflects the user's emotions. To implement this system, the following elements are required: a device such as a smartphone or tablet, a server, a dedicated application, and an emotion engine.

[0759] System configuration

[0760] Take and upload a photo of your face

[0761] User: Take a photo of their face using the camera function on their smartphone. After taking the photo, the user presses the upload button in the application to send the photo to the server.

[0762] Device: The application sends the captured face photo and user ID to the server.

[0763] Server: Receives facial photos and user information and prepares the facial photos to be input into the AI ​​analysis unit.

[0764] Face photo analysis and hairstyle selection

[0765] Server: The received facial photo is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length. The facial photo is also analyzed to analyze the user's facial expressions, and the emotion engine recognizes the user's emotions.

[0766] User: Select the hairstyle they want on the hairstyle selection screen. After selection, the information is also sent to the server.

[0767] AI-based cutting method and finished image generation

[0768] Server: Based on the analysis of the facial photo, data on the user's emotions, and the hairstyle information selected by the user, the AI ​​model generates the optimal cutting method and finished image. By using the emotion engine, it can make adjustments based on the user's emotions.

[0769] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[0770] View the final image and get feedback

[0771] Device: The received finished image and cutting method data are displayed within the application, while the user's facial expression is recognized again and analyzed using the emotion engine.

[0772] User: Check the displayed image of the finished hairstyle and press the "OK" button if satisfied. If a negative emotion is detected from a change in facial expression, the system can automatically suggest an alternative hairstyle.

[0773] Sharing information with hairdressers

[0774] User: Save the final image of the finished look and cutting method that they are satisfied with, and then go to the salon and present this. Specifically, they can show the screen of their smartphone to the hairdresser, or if necessary, bring a printed copy of the data with them.

[0775] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method.

[0776] Specific examples

[0777] For example, a specific example will be given where the user desires a "bob cut."

[0778] 1. User: Take a photo of their face with their smartphone camera and upload it to the application. The emotion engine analyzes the user's facial expressions and identifies emotions such as joy, excitement, or anxiety.

[0779] 2. Device: Sends a photo of the face and basic information to the server.

[0780] 3. Server: Analyzes the facial photo to identify facial contours, hair type, and hair length, and then adds emotional information using an emotion engine.

[0781] 4. User: Selects a bob cut style. The emotion engine detects the user's emotion and sends emotional feedback for the selected style to the server.

[0782] 5. Server: The AI ​​model combines the analysis results, emotional information, and bob cut data to generate the optimal finished image.

[0783] 6. Server: Sends the generated finished image to the device.

[0784] 7. Device: The finished image is displayed in the app, and the emotion engine checks the user's facial expressions again.

[0785] 8. User: If satisfied with the image, press the "OK" button to save the data. Based on the emotional feedback, the system can suggest other styles.

[0786] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[0787] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[0788] This system reduces the gap between the user and the hairdresser, allowing them to achieve their ideal hairstyle. By using an emotion engine, it is possible to suggest styles based on the user's emotions, providing even higher satisfaction.

[0789] The processing flow will be explained below.

[0790] Step 1:

[0791] User: Use the camera on your smartphone to take a photo of yourself, preferably a high-resolution image.

[0792] Step 2:

[0793] Device: Check the captured facial photo and press the upload button in the application to send the facial photo and user ID to the server.

[0794] Step 3:

[0795] Server: Stores the received facial photos and user IDs and prepares to send the facial photos to the AI ​​analysis unit.

[0796] Step 4:

[0797] Server: The AI ​​analysis unit analyzes the facial photo and, in addition to facial contours, hair type, and hair length, the emotion engine recognizes emotions from the user's facial expressions.

[0798] Step 5:

[0799] Server: Stores the facial feature data including the recognized emotion data and proceeds to the next step.

[0800] Step 6:

[0801] Server: The system generates thumbnails of multiple standard hairstyles and sends the data to the device.

[0802] Step 7:

[0803] Device: Displays thumbnail images of multiple hairstyles so the user can choose the hairstyle they want.

[0804] Step 8:

[0805] User: Selects the hairstyle they want. After selection, this information is also sent to the server.

[0806] Step 9:

[0807] Server: The AI ​​model combines the analysis results, emotional data, and information about the hairstyle selected by the user to generate the optimal cutting method and finished image.

[0808] Step 10:

[0809] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[0810] Step 11:

[0811] Device: The received finished image and cutting method data are displayed within the application, while the emotion engine analyzes the user's facial expression again.

[0812] Step 12:

[0813] User: Check the displayed image of the finished product. If it is acceptable, press the "OK" button. If it is not, provide feedback and proceed to the next step.

[0814] Step 13:

[0815] Device: Sends user feedback and emotion engine analysis results to the server.

[0816] Step 14:

[0817] Server: Based on the feedback and sentiment data obtained, the AI ​​model suggests other hairstyles that would suit the user.

[0818] Step 15:

[0819] Server: Sends data on new suggested hairstyles to the device.

[0820] Step 16:

[0821] Terminal: Shows the proposed new hairstyle image.

[0822] Step 17:

[0823] User: Review the new final image and if satisfied, press the "OK" button. If not, provide further feedback and repeat the process from step 13.

[0824] Step 18:

[0825] Device: When the user presses the "OK" button, the final finished image and cutting method data are saved on the device.

[0826] Step 19:

[0827] User: Go to the hair salon and show the hairdresser the finished image and cutting method data saved on the smartphone screen. If necessary, you can also print it out and bring it with you.

[0828] Step 20:

[0829] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method data.

[0830] This detailed processing step allows users to receive hairstyle suggestions based on their emotions using the emotion engine, and also provides feedback on the final result, resulting in a highly satisfying haircut.

[0831] Example 2

[0832] 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."

[0833] When a user tells a hair salon what hairstyle they want, the actual result often differs from their expectations. This leads to lower user satisfaction and a lack of smooth communication with the hairdresser. Furthermore, conventional systems have difficulty proposing hairstyles that take the user's emotions into account, making it difficult to provide optimal suggestions for each individual user.

[0834] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to take a facial image of themselves and transmit the image, a means for transmitting the taken facial image to the server using a terminal, a means for the server to store the received facial image in a database and perform preprocessing, a means for analyzing the uploaded facial image and identifying the facial contour, hair type, and hair length, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, a means for transferring the generated finished image to the terminal and displaying it, a means for the user to check the displayed finished image and obtain feedback, and a means for the user to save the final finished image and data on the haircut method and present it to the service provider. This allows the user to check the desired hairstyle in advance and enables hairstyle suggestions based on their emotions, thereby improving user satisfaction and facilitating smoother communication with the hairdresser.

[0835] A "user" is an individual who uses the system to take a picture of their face and select a hairstyle.

[0836] A "face image" is a digital image of a user's face that is uploaded to the system.

[0837] The "server" is a computer system that analyzes the facial image received from the user and generates an image of the optimal hairstyle.

[0838] A "terminal" is a device used by a user to take a facial image and send it to a server, such as a smartphone or tablet.

[0839] A "database" is a system that manages data such as facial images, analysis results, and user information stored on a server.

[0840] "Preprocessing" refers to the process by which the server converts the facial images it receives into an appropriate format and prepares them for analysis.

[0841] The "AI Analysis Unit" is a system that uses artificial intelligence to analyze facial images and identify facial contours, hair type, hair length, etc.

[0842] The "emotion engine" is a technology that analyzes emotions from a user's facial image and reflects them in hairstyle suggestions.

[0843] The "cutting method" is a specific haircutting method to achieve the ideal result based on the hairstyle selected by the user.

[0844] The "finished image" is an image of the hairstyle applied to the user's face, generated based on the analysis results and the hairstyle selected by the user.

[0845] "Feedback" refers to the user's evaluation and opinions on the displayed finished video, and is information that the system uses to reflect in its next suggestions and corrections.

[0846] A "service provider" is a professional, such as a hairdresser or barber, who actually provides haircutting services to users.

[0847] The present invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that image. Furthermore, by combining it with an emotion engine that recognizes and reflects the user's emotions, it is possible to achieve more sophisticated and personalized hairstyle suggestions. The specific configuration and procedures for implementing this system are as follows.

[0848] System Configuration

[0849] 1. User Device

[0850] Users take a photo of their face using a device such as a smartphone or tablet. A dedicated application is installed on the device, and they have the means to upload the image to the server through this application. At this time, the emotion engine analyzes the user's facial expressions and identifies the user's emotions.

[0851] 2. Server

[0852] The server has several functions:

[0853] Image reception and preprocessing: Receives the face image and user ID sent from the user's device and performs preprocessing such as image resizing and format conversion.

[0854] AI Analysis Unit: The pre-processed facial image is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length. The emotion engine then analyzes the user's facial expressions to obtain emotional information.

[0855] Hairstyle generation: Based on the analysis results, the user's emotional data, and the hairstyle information selected by the user, the generative AI model generates the optimal cutting method and finished image.

[0856] Data transfer: The generated finished image and cutting method data are sent to the user's device.

[0857] 3. Database

[0858] The database runs on a server and stores and manages the user's facial image, analysis results, emotional data, generated finished footage, and cutting method data.

[0859] Specific examples

[0860] Step-by-step process example

[0861] Below is a specific example of when a user wants a bob cut.

[0862] 1. User: Takes a picture of their face with their smartphone camera and uploads it to the application. The emotion engine analyzes the user's facial expressions and identifies emotions such as joy, excitement, or anxiety.

[0863] 2. Device: Sends face image and basic information to the server.

[0864] 3. Server: Analyzes the facial image to identify facial contours, hair type, and hair length, and then adds emotional information using an emotion engine.

[0865] 4. User: Selects a bob cut style. The emotion engine detects the user's emotion and sends emotional feedback for the selected style to the server.

[0866] 5. Server: The analysis results, emotional information, and bob cut data are combined, and the generative AI model generates the optimal finished video.

[0867] 6. Server: Sends the generated finished video to the terminal.

[0868] 7. Device: The finished video is displayed in the app, and the emotion engine checks the user's facial expressions again.

[0869] 8. User: If satisfied with the image, press the "OK" button to save the data. Based on the emotional feedback, the system can suggest other styles.

[0870] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[0871] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[0872] Prompt Sentence Examples

[0873] For example, if the user wants a bob cut, the prompt text is:

[0874] "I would like a bob cut. My current hair length is shoulder-length and wavy. I'm excited."

[0875] This system reduces the gap between the user and the hairdresser, allowing them to see their ideal hairstyle in advance. By using an emotion engine, it is possible to suggest styles based on the user's emotions, improving user satisfaction.

[0876] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0877] Step 1:

[0878] User: Take a picture of their face using their smartphone camera.

[0879] Specific actions: Open the camera app and adjust it so that your entire face is clearly visible under good lighting conditions.

[0880] Input: A face image.

[0881] Output: The captured face image.

[0882] Step 2:

[0883] Device: Uses a dedicated application to send the captured facial image to the server.

[0884] Specific operation: Press the upload button in the application to send data including the face image and user ID to the server via HTTPS protocol.

[0885] Input: A captured face image and user ID.

[0886] Output: Spatial transfer successful message to server.

[0887] Step 3:

[0888] Server: Stores the received face images and user IDs in a database and performs preprocessing.

[0889] Specific operation: Convert the facial image to a standard resolution and format (e.g., resize to 256x256 pixels).

[0890] Input: Face image and user ID.

[0891] Output: Preprocessed face image.

[0892] Step 4:

[0893] Server: The pre-processed facial image is input into the AI ​​analysis unit to identify features such as facial contours, hair type, and hair length.

[0894] Specific operation: Uses a deep learning model to extract facial features and output analysis results.

[0895] Input: Preprocessed face image.

[0896] Output: Facial feature data (shape, hair type, hair length, etc.).

[0897] Step 5:

[0898] Server: The emotion engine analyzes facial expressions in the facial images to identify the user's emotional state.

[0899] Specific behavior: Use a facial expression recognition algorithm to generate emotion labels such as happiness, excitement, and anxiety.

[0900] Input: Preprocessed face image.

[0901] Output: Emotion data (happiness, excitement, anxiety, etc.).

[0902] Step 6:

[0903] User: Selects the desired hairstyle through the user interface (e.g., bob cut).

[0904] Specific operations: Select the desired hairstyle on the hairstyle selection screen of the application and press the decision button.

[0905] Input: Your desired hairstyle selection information.

[0906] Output: Selected hairstyle information.

[0907] Step 7:

[0908] Server: The generative AI model combines the analysis results, the user's emotional data, and the selected hairstyle information to generate the optimal cutting method and a video of the finished product.

[0909] Specific operation: All data (facial feature data, emotional data, hairstyle information) is input and the AI ​​model generates the optimal finished image.

[0910] Input: Facial feature data, emotion data, hairstyle information.

[0911] Output: Optimal cutting method and finished image.

[0912] Step 8:

[0913] Server: Transfers the generated finished video and cutting method data to the terminal.

[0914] Specific operation: The generated data is sent to the terminal using the HTTPS protocol.

[0915] Input: Optimal cutting method and finished footage.

[0916] Output: A transmission completion message.

[0917] Step 9:

[0918] Terminal: The received finished image and cutting method data are displayed within the application.

[0919] Specific operation: The finished video is displayed on the mobile application screen and an interface is provided for collecting feedback.

[0920] Input: Received finished footage and cutting method.

[0921] Output: The application display screen.

[0922] Step 10:

[0923] User: Check the displayed finished image, and if satisfied, press the "OK" button to send feedback to the system.

[0924] Specific actions: Check the finished video in detail, and if you are satisfied, press the "OK" button. If necessary, enter feedback comments.

[0925] Input: Feedback on how the hairstyle turned out.

[0926] Output: Feedback information.

[0927] Step 11:

[0928] User: Save the final image and cutting method data and present it when going to the hair salon.

[0929] Specific actions: View the saved data on your smartphone screen and show it to your hairdresser, or print it out and bring it with you if necessary.

[0930] Input: Final footage and cutting data.

[0931] Output: Presentation to hairdresser.

[0932] Step 12:

[0933] Hairdresser: Cuts the user's hair according to their wishes, based on the information provided.

[0934] Specific actions: Based on the presented data, confirm the cutting method and then perform the actual cutting based on that.

[0935] Input: User-provided cutting method and finished footage.

[0936] Output: The finished hairstyle.

[0937] (Application example 2)

[0938] 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."

[0939] Conventional hairstyle simulation systems were unable to suggest hairstyles that reflected the user's emotions, and were unable to sufficiently increase user satisfaction. Furthermore, the lack of a system that effectively utilized user feedback to make new suggestions made the process of finding the optimal hairstyle cumbersome. Therefore, there was a need for a system that could suggest optimal hairstyles based on the user's emotions and efficiently utilize feedback to make further suggestions.

[0940] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0941] In this invention, the server includes a means for recognizing the user's emotions and adding that information to the analysis results, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, and a means for displaying the generated finished image and reanalyzing the user's facial expression to obtain feedback. This makes it possible to propose an optimal hairstyle based on the user's emotions. Furthermore, by automatically proposing new hairstyles based on the feedback, the user can efficiently find their ideal hairstyle.

[0942] A "user" is an individual who uses the system to simulate their own hairstyle.

[0943] A "face photo" is an image of a face taken by a user using an information processing device such as a smartphone.

[0944] The "means for uploading" is a function that allows a user to send a photograph of their face taken to a server via the Internet.

[0945] "Means for analysis" refers to software or algorithms that analyze uploaded facial photos and identify facial features such as facial contours, hair type, and hair length.

[0946] "Emotion recognition means" refers to technology that analyzes facial expressions in facial photos and feedback to identify the user's emotional state (happiness, anxiety, excitement, etc.).

[0947] The "means of fusion" is a function that combines analyzed facial feature information with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[0948] The "means of generation" is an algorithm that uses an AI model to create the optimal hairstyle cutting method and finished image based on the fused data.

[0949] The "display means" is a method for displaying the generated finished image on the display of the user's information processing device.

[0950] The "means for reanalyzing and obtaining feedback" is a technique for reanalyzing the facial expressions shown by the user in response to the displayed finished image and obtaining emotional feedback.

[0951] "Automatic suggestion method" is a function in which AI suggests alternative optimal hairstyles based on user feedback.

[0952] The "means for saving" is a method for saving the finished image and cutting method data that the user is satisfied with in a digital format in a recording device.

[0953] The "presenting means" is a means for displaying the saved cut information on the screen of an information processing device or on a recording medium to show it to the hairdresser.

[0954] An "information processing device" is a device that processes digital data, such as a smartphone, tablet, or personal computer.

[0955] A "recording medium" is a physical medium used to store or record data, such as paper, a USB memory stick, or a CD.

[0956] "Server" means a remote computing device that receives, analyzes, and stores uploaded user facial photographs and associated data.

[0957] To build a system that realizes this application example, the following hardware and software are used.

[0958] Hardware

[0959] User device: Information processing device such as smartphone, tablet, PC, etc.

[0960] Server: A remote computing device that analyzes facial photos, recognizes emotions, and generates hairstyles.

[0961] software

[0962] Facial recognition software: Libraries for extracting facial features, such as OpenCV or dlib.

[0963] Emotion Recognition Engine: A library for analyzing facial expressions and recognizing user emotions. It uses machine learning models with TensorFlow and Keras.

[0964] Hairstyle Generation Model: Uses an AI model to generate optimal hairstyles based on facial features and emotional information. Utilizes TensorFlow and PyTorch.

[0965] Specific methods for data processing and calculation

[0966] Taking and uploading a photo of your face

[0967] Users take a photo of themselves using their smartphone camera and upload it to the server through the application interface, along with their user ID.

[0968] Facial photo analysis and emotion recognition

[0969] The server uses facial recognition software to analyze the uploaded facial photo and extract features such as facial contours, hair type, and hair length, while simultaneously using an emotion recognition engine to identify emotions from the user's facial expressions.

[0970] Hairstyle generation

[0971] The system combines the user's selected hairstyle with facial features and emotional information, and uses a hairstyle generation model to generate the optimal cutting method and finished image. This image is generated using an AI model and is also adjusted according to the user's emotions.

[0972] Display and feedback of the finished image

[0973] The server then sends the resulting image to the user's device, where it is displayed within the application. The user's facial expressions are analyzed again to obtain feedback. If a negative emotion is detected, the system automatically suggests an alternative hairstyle.

[0974] Saving and presenting the final image

[0975] Once the user is satisfied with the final look and cutting method, the data is saved and when they go to the salon, they can show the smartphone screen or bring a printed copy of the data to communicate their wishes to the hairdresser.

[0976] Specific examples

[0977] For example, if the user enters the following prompt sentence, the system will suggest suitable hairstyles:

[0978] Example prompt sentence:

[0979] Users take a photo of themselves with their smartphone and upload it to the application. The application analyzes the user's photo and provides the ability to try out various hairstyles. It also has an assistant function that recognizes the user's emotions and recommends the best hairstyle based on that emotion.

[0980] This allows users to check the optimal hairstyle based on their facial photo and emotions, and efficiently request a haircut at a salon. This system not only increases user satisfaction, but also facilitates smooth communication with hairdressers.

[0981] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0982] Step 1:

[0983] The user takes a photo of their face using the smartphone camera. Once the photo is taken, they press the upload button in the application. This causes the device to send the photo and user ID to the server. The input includes the photo and user ID, and the output includes the photo and user ID sent to the server.

[0984] Step 2:

[0985] The server analyzes the received facial photo using facial recognition software (e.g., OpenCV). Specifically, it extracts features such as facial contours, hair type, and hair length. At the same time, it uses an emotion recognition engine (e.g., using TensorFlow or Keras) to identify emotions from the user's facial expressions. The facial photo is given as input, and facial feature data and emotion data are generated as output.

[0986] Step 3:

[0987] The user selects the desired hairstyle on the hairstyle selection screen. The selected hairstyle information is sent from the terminal to the server. The user's hairstyle selection is the input, and the selected hairstyle information is sent to the server as the output.

[0988] Step 4:

[0989] The server combines the analyzed facial feature data, emotion data, and the user-selected hairstyle information. This allows a hairstyle generation model (using, for example, TensorFlow or PyTorch) to generate the optimal haircutting method and finished image. Given the facial feature data, emotion data, and selected hairstyle information as input, the generated finished image and haircutting method data are obtained as output.

[0990] Step 5:

[0991] The server transmits the generated finished image and cutting method data to the terminal. The generated finished image and cutting method data are included as input, and these data are transmitted to the terminal as output.

[0992] Step 6:

[0993] The device displays the received finished image in the application for the user to confirm. It then analyzes the user's facial expression again to obtain emotional feedback. If the server detects a negative emotion based on this feedback, it automatically suggests a different hairstyle. The user's facial expression is given as input, and emotional feedback and a new hairstyle suggestion are obtained as output.

[0994] Step 7:

[0995] When the user is satisfied with the final image and cutting method, the data is saved. By presenting the saved data when visiting the salon, the user can accurately convey their wishes to the hairdresser. The finalized image of the final image and cutting method data are given as input, and these data are saved as output.

[0996] 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.

[0997] 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.

[0998] 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.

[0999] [Third embodiment]

[1000] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1001] 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.

[1002] 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).

[1003] 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.

[1004] 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.

[1005] 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).

[1006] 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.

[1007] 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.

[1008] 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.

[1009] 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.

[1010] 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.

[1011] 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."

[1012] This invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that photo. The following elements are required to implement this system: a device such as a smartphone or tablet, a server, and a dedicated application.

[1013] System configuration

[1014] Take and upload a photo of your face

[1015] User: Take a photo of their face using the camera function on their smartphone. After taking the photo, the user presses the upload button in the application to send the photo to the server.

[1016] Device: The application sends the captured face photo and user ID to the server.

[1017] Server: Receives facial photos and user information and prepares the facial photos to be input into the AI ​​model.

[1018] Face photo analysis and hairstyle selection

[1019] Server: The received facial photo is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length, which allows customization according to the user's hair condition.

[1020] User: Select the hairstyle they want on the hairstyle selection screen. After selection, the information is also sent to the server.

[1021] AI-based cutting method and finished image generation

[1022] Server: Based on the analysis of the facial photo and the hairstyle selected by the user, the AI ​​model generates the optimal cutting method and finished image, allowing users to simulate the actual image after the haircut.

[1023] Server: Sends the generated finished image and cutting method data to the terminal.

[1024] View the final image and get feedback

[1025] Device: The received image of the finished hairstyle is displayed to the user within the application. The user checks the displayed image and presses the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again.

[1026] Sharing information with hairdressers

[1027] User: Save the final image of the finished look and cutting method that they are satisfied with, and then go to the salon and present this. Specifically, they can show the screen of their smartphone to the hairdresser, or if necessary, bring a printed copy of the data with them.

[1028] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method.

[1029] Specific examples

[1030] For example, a specific example will be given where the user desires a "bob cut."

[1031] 1. User: Take a photo of their face with their smartphone camera and upload it to the application.

[1032] 2. Device: Sends a photo of the face and basic information to the server.

[1033] 3. Server: Analyzes the facial photo and identifies facial contours, hair type, and hair length.

[1034] 4. User: Choose a bob cut style.

[1035] 5. Server: The analysis results are combined with the bob cut data, and the AI ​​model generates the optimal finished image.

[1036] 6. Server: Sends the generated finished image to the device.

[1037] 7. Device: The finished image is displayed in the app and the user is asked to confirm.

[1038] 8. User: Once satisfied with the image, presses the "OK" button to save the data.

[1039] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[1040] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[1041] This system reduces the gap in results between the user and the hairdresser, allowing them to achieve their ideal hairstyle.

[1042] The processing flow will be explained below.

[1043] Step 1:

[1044] User: Use the camera on your smartphone to take a photo of yourself, preferably a high-resolution image.

[1045] Step 2:

[1046] Device: Check the captured facial photo and press the upload button in the application to send the facial photo and user ID to the server.

[1047] Step 3:

[1048] Server: Stores the received facial photos and user IDs and prepares to send the facial photos to the AI ​​analysis unit.

[1049] Step 4:

[1050] Server: The AI ​​analysis unit analyzes the facial photo to identify facial contours, hair type, and hair length, sometimes using external systems or cloud services.

[1051] Step 5:

[1052] User: Within the application, select the desired hairstyle from the thumbnails of multiple hairstyles displayed.

[1053] Step 6:

[1054] Device: Sends the selected hairstyle information to the server.

[1055] Step 7:

[1056] Server: The AI ​​model combines the analysis results with the hairstyle information selected by the user to generate the optimal cutting method and finished image.

[1057] Step 8:

[1058] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[1059] Step 9:

[1060] Terminal: The received finished image and cutting method data are displayed within the application.

[1061] Step 10:

[1062] User: Check the displayed image of the finished look, and if you are satisfied, press the "OK" button. If you are not satisfied, select another hairstyle and repeat the steps from step 5.

[1063] Step 11:

[1064] Device: When the user presses the "OK" button, the final finished image and cutting method data are saved on the device.

[1065] Step 12:

[1066] User: Go to the hair salon and show the hairdresser the finished image and cutting method data saved on the smartphone screen. If necessary, you can also print it out and bring it with you.

[1067] Step 13:

[1068] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method data.

[1069] Example 1

[1070] 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."

[1071] Conventional hairstyle selection systems have had the problem that it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, leading to dissatisfaction with the finished product. Also, few systems allow users to simulate the finished hairstyle in advance based on a photo of their own face. As a result, a communication gap occurs between the user and the hairdresser, making it difficult to achieve the ideal hairstyle.

[1072] 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.

[1073] In this invention, the server includes a means for a user to take a photo of their face and upload the photo, a means for analyzing the uploaded photo of their face to identify the facial contours, hair type, and hair length, and a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image. This allows the user to check in advance the finished image of the hairstyle based on their face photo, and makes it possible to present specific haircut information to the hairdresser.

[1074] "User" refers to an individual who uses the system to take a photo of themselves and select the hairstyle they desire.

[1075] "Terminal" refers to a device used by a user, such as a smartphone or tablet.

[1076] "Server" means the computer system that has the central function of receiving and processing uploaded photos and selected hairstyles.

[1077] "Taking and uploading a photo of your face" refers to the process in which a user takes a photo of their face using the device's camera and sends the photo to the server.

[1078] "Facial photo analysis" refers to the process of identifying facial contours, hair type, and hair length based on a facial photo uploaded to a server.

[1079] The "analysis results" are data obtained from facial photos processed by AI, and include information such as facial contours, hair type, and hair length.

[1080] "Hairstyle selection" refers to the act of a user selecting the hairstyle they want within a dedicated application.

[1081] "Hairstyle information" is data relating to the hairstyle selected by the user, and the cutting method and finished image are generated based on this information.

[1082] "Cutting method" refers to the haircutting method and treatment procedure suggested according to the hairstyle selected by the user.

[1083] "Finished Image" refers to an image generated by the AI ​​model that shows how the selected hairstyle will look on the user's face.

[1084] "Getting feedback" refers to the process of users checking their satisfaction with the displayed finished image and obtaining the results.

[1085] "Generative AI model" refers to artificial intelligence technology that generates the optimal cutting method and finished image based on a facial photo and hairstyle information.

[1086] "Means of presenting to the hairdresser on a smartphone or in printed form" refers to the means by which the user can show the hairdresser the haircut information saved by the user, including using the screen of a digital device or a paper printout.

[1087] "Artificial intelligence" refers to the technology that analyzes facial photos and performs computational processing to generate cutting methods and finished images.

[1088] This invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that photo. The following elements are required to implement this system: a device such as a smartphone or tablet, a server, and a dedicated application.

[1089] System configuration

[1090] Take and upload a photo of your face

[1091] User: Uses the camera function of the smartphone to take a photo of his / her face. After taking the photo, he / she presses the "upload" button in the dedicated application to send the photo to the server.

[1092] Device: The application sends the user's face photo data and user ID to the server. The photo is sent in JPEG or PNG format.

[1093] Preparation for facial photo analysis

[1094] Server: Stores the received face photo and user ID in a database. Then, it performs pre-processing to input the photo data into the AI ​​analysis unit. This pre-processing includes image resizing and noise removal.

[1095] Facial photo analysis

[1096] Server: The AI ​​analysis unit is used to analyze the facial features of the photo, specifically identifying facial contours, hair type, hair length, etc. The analysis results are saved in JSON format for subsequent processing.

[1097] Hairstyle selection

[1098] User: Select the desired hairstyle on the hairstyle selection screen of the dedicated application. For example, select "Bob Cut." After selecting, press the "Send" button to send the information to the server.

[1099] Terminal: Sends hairstyle information to the server. The selected hairstyle information is sent as text data.

[1100] AI-based cutting method and finished image generation

[1101] Server: Based on the analysis results of the facial photo and the hairstyle selected by the user, the generative AI model generates the optimal haircut method and finished image. Specifically, the prompt "Based on the facial photo and the selected hairstyle, please generate the optimal haircut method and finished image" is input to the AI.

[1102] Server: The generated finished image and cutting method data are encoded in JPEG or PNG format and sent to the user's device.

[1103] View the final image and get feedback

[1104] Device: The received finished image is displayed in the dedicated application. After checking the displayed image, the user can save the image by pressing the "OK" button, or return to the hairstyle selection screen by pressing the "Reselect" button.

[1105] User: If you are satisfied with the final image, press the "OK" button to save the data, but if you are not satisfied, select the hairstyle again.

[1106] Sharing information with hairdressers

[1107] User: Saves the final image of the finished look and cutting method data in a dedicated application, and shows the screen on their smartphone to the hairdresser when they visit the salon.

[1108] Hairdresser: Cuts the customer's hair according to their wishes, based on the presented image of the finished look and cutting method.

[1109] Specific examples

[1110] For example, a specific example will be given where the user desires a "bob cut."

[1111] User: Take a photo of their face with their smartphone camera and upload it to the application.

[1112] Device: Sends a photo of your face and basic information to the server.

[1113] Server: Analyzes facial photos to identify facial contours, hair type, and hair length.

[1114] User: Select "BobCut" on the application selection screen.

[1115] Server: The analysis results are combined with the "bob cut" style data, and the generative AI model generates the optimal finished image. Example prompt: "Generate the best bob cut style for this user based on their face photo."

[1116] Server: Sends the finished image generated by the AI ​​model to the user's device.

[1117] On device: The finished image is displayed in the app and the user is asked to confirm.

[1118] User: Once satisfied with the image, presses the "OK" button to save the data.

[1119] User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[1120] Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[1121] This reduces the gap in the results between the user and the hairdresser, allowing them to achieve their ideal hairstyle.

[1122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1123] Step 1:

[1124] User: Activates the camera function of the smartphone and takes a photo of his / her face. After taking the photo, he / she presses the "upload" button in the dedicated application to send the photo to the server.

[1125] Input: A photo of the user's face (JPEG or PNG format).

[1126] Output: A request to upload a face photo to the server.

[1127] Specific operation: Take a photo with your smartphone camera and use the app's upload function to send the photo to the server.

[1128] Step 2:

[1129] On the device, the application sends the user's face photo data and user ID to the server. The photo is sent using the HTTPS protocol.

[1130] Input: User's face photo data, user ID.

[1131] Output: Send face photo data to the server.

[1132] What it does: The application converts the face photo data and user ID into a binary format and sends it securely to the server using the HTTPS protocol.

[1133] Step 3:

[1134] Server: Stores the received face photo and user ID in a database, then performs preprocessing to input the photo data into the AI ​​analysis unit.

[1135] Input: Face photo data, user ID.

[1136] Output: Preprocessed facial photo data.

[1137] Specific operation: The server resizes the facial photo data, removes noise, and stores it in the database.

[1138] Step 4:

[1139] Server: Uses an AI analysis unit to analyze the facial features of the photo, specifically identifying facial contours, hair type, hair length, etc.

[1140] Input: Preprocessed facial photo data.

[1141] Output: Feature data such as facial contours, hair type, and hair length (JSON format).

[1142] Specific operation: The AI ​​analysis unit uses deep learning technology to analyze facial photos and extract feature data.

[1143] Step 5:

[1144] User: Select the desired hairstyle on the hairstyle selection screen of the dedicated application. For example, select "Bob Cut." After selecting, press the "Send" button to send the information to the server.

[1145] Enter: hairstyle selection.

[1146] Output: Request to send hairstyle information.

[1147] Specific actions: Scroll through the hairstyle thumbnails in the application, select "Bob Cut," and press the "Submit" button to submit the hairstyle information.

[1148] Step 6:

[1149] Terminal: Sends hairstyle information to the server. The selected hairstyle information is sent as text data.

[1150] Input: Hairstyle information.

[1151] Output: Sending hairstyle information to the server.

[1152] What it does: The application converts the selected hairstyle information into text format and sends it to the server using the HTTPS protocol.

[1153] Step 7:

[1154] Server: Based on the analysis results of the facial photo and the hairstyle selected by the user, the generative AI model generates the optimal haircut method and finished image. Specifically, the prompt "Based on the facial photo and the selected hairstyle, please generate the optimal haircut method and finished image" is input to the AI.

[1155] Input: Analysis result feature data, selected hairstyle information.

[1156] Output: The generated cutting method and finished image.

[1157] Specific operation: The server inputs the analysis results and selected hairstyle information into the generative AI model, and generates a finished image based on the prompt text.

[1158] Step 8:

[1159] Server: The generated finished image and cutting method data are encoded in JPEG or PNG format and sent to the user's device.

[1160] Input: Generated cutting method and finished image.

[1161] Output: Sends the finished image and cutting method data to the user's device.

[1162] What happens: The server encodes the generated data and sends it to the user's device using the HTTPS protocol.

[1163] Step 9:

[1164] Device: The received finished image is displayed in the dedicated application. After checking the displayed image, the user can save the image by pressing the "OK" button, or return to the hairstyle selection screen by pressing the "Reselect" button.

[1165] Input: Finished image and cutting method data.

[1166] Output: Saved image or hairstyle reselection request.

[1167] Specific behavior: The application displays the received data and performs the save or reselection process depending on the user's selection.

[1168] Step 10:

[1169] User: Saves the final image of the finished look and cutting method data in a dedicated application, and shows the screen on their smartphone to the hairdresser when they visit the salon.

[1170] Input: Saved finished image and cutting method data.

[1171] Output: Presentation to hairdresser.

[1172] Specific operation: Display the data stored in the dedicated application and show it to the hairdresser, or print out the data and bring it with you if necessary.

[1173] Step 11:

[1174] Hairdresser: Cuts the customer's hair according to their wishes, based on the presented image of the finished look and cutting method.

[1175] Input: The proposed finished image and cutting method data.

[1176] Output: The actual haircut.

[1177] Specific operation: Cuts hair based on the provided data to achieve the hairstyle desired by the user.

[1178] (Application example 1)

[1179] 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."

[1180] The present invention aims to provide a system that allows users to check the finished hairstyle in advance, and to provide a means for smoothly and effectively sharing information with actual beauty salons and facilitating communication with hairdressers. Another objective is to improve the reliability of the user's desired hairstyle and to increase the accuracy of guidelines for hairdressers when performing the cut.

[1181] 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.

[1182] In this invention, the server includes a means for a user to take a photo of their face and upload the photo, a means for analyzing the uploaded photo of their face to identify the facial contours, hair type, and hair length, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, and a means for displaying and sharing this information with the hairdresser via a smartphone at the hair salon. This allows the user to check the optimal hairstyle in advance and to smoothly share information with the hairdresser when the hairstyle is performed at the hair salon.

[1183] "User" refers to ordinary consumers who use the system, and in particular to those who take a photo of their own face to check the final hairstyle.

[1184] "Facial photo" refers to image data of a face that is taken by a user using a device such as a smartphone and uploaded to the system.

[1185] "Means for uploading" refers to the part of the application that includes the function to send a photograph of a user's face to a server via the Internet.

[1186] "Means of analysis" refers to the function of using an artificial intelligence model to identify facial contours, hair type, hair length, etc. from the facial photo received by the server.

[1187] "Means for generating the optimal cutting method and finished image" refers to the function in which the AI ​​model combines the hairstyle selected by the user with the analysis results of the facial photo, simulates the optimal hairstyle finish, and generates the results as data.

[1188] "Means for displaying" refers to the function of displaying the generated finished image on the user's smartphone or tablet, allowing the user to visually check it.

[1189] "Means for obtaining feedback" refers to the function that allows the user to input opinions and comments, including the level of satisfaction with the displayed finished image, through the application and transmit them to the server.

[1190] "A means of saving the final image of the finished look and data on the cutting method, and presenting it to the hairdresser" refers to the function of saving the image of the hairstyle that the user is satisfied with as digital data, and showing it to the hairdresser at the salon on the screen of a device such as a smartphone, or presenting it in printed form if necessary.

[1191] "A means of displaying and sharing this information with hairdressers via smartphones at beauty salons" refers to the function of displaying and sharing the finished image and cutting method saved by the user on a smartphone so that the hairdresser can visually confirm it at the beauty salon.

[1192] "Artificial intelligence model" refers to a machine learning algorithm used to simulate the outcome of a hairstyle, and in this invention is used in particular to analyze the features of a facial photograph and generate an optimal hairstyle.

[1193] "Server" refers to the central computer system that receives and analyzes the User's facial photograph and feedback, and stores and transmits the generated finished images.

[1194] This invention is a system that allows users to take a photo of themselves using a device such as a smartphone or tablet and check in advance how their desired hairstyle will look based on that photo. The following elements are required to implement this system: a device, a server, and a dedicated application.

[1195] System configuration

[1196] 1. Take and upload a photo of your face

[1197] Users take a photo of their face using the camera on their smartphone, and then press the upload button in the application to send the photo to the server.

[1198] The device sends the captured facial photo and user ID to the server via the application.

[1199] The server receives the facial photo and user information, converts the facial photo into a format suitable for analysis, and prepares it for input into the artificial intelligence model.

[1200] 2. Face photo analysis and hairstyle selection

[1201] The server inputs the received facial photo into an AI analysis unit to identify features such as facial contours, hair type, and hair length, which allows customization according to the user's hair condition.

[1202] The user selects the hairstyle they want on the hairstyle selection screen, and after selection, the information is also sent to the server.

[1203] 3. AI-based cutting method and finished image generation

[1204] The server uses an AI model to generate the optimal haircut method and finished image based on the analysis of the facial photo and the hairstyle selected by the user, allowing users to simulate the actual image after the haircut.

[1205] The server again transmits the generated finished image and cutting method data to the terminal.

[1206] 4. View the final image and get feedback

[1207] The device will then display the received image of the finished look to the user within the application. The user can check the image and press the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again.

[1208] 5. Sharing information with hairdressers

[1209] Users can save the final image of the finished look and cutting method they are satisfied with, and then go to the salon and present this information to the hairdresser. Specifically, they can show the screen on their smartphone to the hairdresser, or if necessary, bring a printout of the data with them.

[1210] The hairdresser will cut the customer's hair based on the presented image of the finished look and cutting method.

[1211] Hardware and software used

[1212] Hardware: Smartphone (Android / iOS), server with high-performance CPU / GPU

[1213] Software: Smartphone app (iOS: Swift, Android: Kotlin), server side (Flask, Keras, OpenCV)

[1214] Specific examples

[1215] For example, consider the case where a user desires a shortcut.

[1216] The user is prompted to "Simulate the style of the shortcut."

[1217] The server receives the prompt, analyzes the facial photo, and generates the optimal shortcut image.

[1218] The server sends the generated finished image and cutting instructions to the user's terminal.

[1219] The user shows the image to the hairdresser at the salon and a specific cut plan is drawn up.

[1220] Prompt Sentence Examples

[1221] 1. Prompt: "Simulate a shortcut style based on a photo of the user's face."

[1222] 2. Prompt: "Generate the best possible finished image based on the user's desired hairstyle."

[1223] This allows users and hairdressers to smoothly share information to achieve their ideal hairstyle.

[1224] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1225] Step 1:

[1226] The user takes a photo of their face using the camera function of their smartphone and then presses the upload button in the application to send the photo to the server. The input data is the face photo and user ID, and the output is the image data sent to the server.

[1227] Step 2:

[1228] The server receives the uploaded facial photo and user information and converts the facial photo into a format suitable for analysis. This process mainly involves resizing and standardizing the image. The input data is the user's facial photo, and the output is image data in a format suitable for analysis.

[1229] Step 3:

[1230] The server analyzes facial photos. It inputs the image data into an artificial intelligence model (using Keras) to identify features such as facial contours, hair type, and hair length. The input data is resized and standardized image data, and the output is facial feature data.

[1231] Step 4:

[1232] The user selects the desired hairstyle on the application's hairstyle selection screen and sends the information to the server. The input data is the hairstyle ID selected by the user, and the output is the hairstyle data sent to the server.

[1233] Step 5:

[1234] The server uses an artificial intelligence model to generate the optimal haircut method and finished image based on the analysis of the facial photo and the hairstyle ID selected by the user. This process uses data analysis and a generative AI model to combine facial feature data and selected hairstyle data. The input data is facial feature data and hairstyle ID, and the output is the generated finished image and haircut method data.

[1235] Step 6:

[1236] The server then sends the generated finished image and cutting instructions to the user's device. The input data is the finished image and cutting instructions, and the output is the visual data sent to the user's smartphone.

[1237] Step 7:

[1238] The terminal displays the received finished image to the user in the application. The user checks the displayed image and presses the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again. The input data is the finished image received from the server, and the output is the user's feedback.

[1239] Step 8:

[1240] The user saves the final image of the finished look and data on the cutting method that they are satisfied with, and then goes to the salon and presents this. Specifically, they show the screen of their smartphone to the hairdresser, or if necessary, they bring a printed copy of the data. The input data is the saved image and cutting method data, and the output is what is presented at the salon.

[1241] Step 9:

[1242] The hairdresser cuts the user's hair based on the presented image of the finished look and cutting method. The input data is the image of the finished look and cutting method presented by the user, and the output is the actual hairstyle.

[1243] 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.

[1244] This invention is a system that allows users to take a photo of their face and check in advance how their desired hairstyle will look based on that photo, and it also combines an emotion engine that recognizes and reflects the user's emotions. To implement this system, the following elements are required: a device such as a smartphone or tablet, a server, a dedicated application, and an emotion engine.

[1245] System configuration

[1246] Take and upload a photo of your face

[1247] User: Take a photo of their face using the camera function on their smartphone. After taking the photo, the user presses the upload button in the application to send the photo to the server.

[1248] Device: The application sends the captured face photo and user ID to the server.

[1249] Server: Receives facial photos and user information and prepares the facial photos to be input into the AI ​​analysis unit.

[1250] Face photo analysis and hairstyle selection

[1251] Server: The received facial photo is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length. The facial photo is also analyzed to analyze the user's facial expressions, and the emotion engine recognizes the user's emotions.

[1252] User: Select the hairstyle they want on the hairstyle selection screen. After selection, the information is also sent to the server.

[1253] AI-based cutting method and finished image generation

[1254] Server: Based on the analysis of the facial photo, data on the user's emotions, and the hairstyle information selected by the user, the AI ​​model generates the optimal cutting method and finished image. By using the emotion engine, it can make adjustments based on the user's emotions.

[1255] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[1256] View the final image and get feedback

[1257] Device: The received finished image and cutting method data are displayed within the application, while the user's facial expression is recognized again and analyzed using the emotion engine.

[1258] User: Check the displayed image of the finished hairstyle and press the "OK" button if satisfied. If a negative emotion is detected from a change in facial expression, the system can automatically suggest an alternative hairstyle.

[1259] Sharing information with hairdressers

[1260] User: Save the final image of the finished look and cutting method that they are satisfied with, and then go to the salon and present this. Specifically, they can show the screen of their smartphone to the hairdresser, or if necessary, bring a printed copy of the data with them.

[1261] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method.

[1262] Specific examples

[1263] For example, a specific example will be given where the user desires a "bob cut."

[1264] 1. User: Take a photo of their face with their smartphone camera and upload it to the application. The emotion engine analyzes the user's facial expressions and identifies emotions such as joy, excitement, or anxiety.

[1265] 2. Device: Sends a photo of the face and basic information to the server.

[1266] 3. Server: Analyzes the facial photo to identify facial contours, hair type, and hair length, and then adds emotional information using an emotion engine.

[1267] 4. User: Selects a bob cut style. The emotion engine detects the user's emotion and sends emotional feedback for the selected style to the server.

[1268] 5. Server: The AI ​​model combines the analysis results, emotional information, and bob cut data to generate the optimal finished image.

[1269] 6. Server: Sends the generated finished image to the device.

[1270] 7. Device: The finished image is displayed in the app, and the emotion engine checks the user's facial expressions again.

[1271] 8. User: If satisfied with the image, press the "OK" button to save the data. Based on the emotional feedback, the system can suggest other styles.

[1272] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[1273] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[1274] This system reduces the gap between the user and the hairdresser, allowing them to achieve their ideal hairstyle. By using an emotion engine, it is possible to suggest styles based on the user's emotions, providing even higher satisfaction.

[1275] The processing flow will be explained below.

[1276] Step 1:

[1277] User: Use the camera on your smartphone to take a photo of yourself, preferably a high-resolution image.

[1278] Step 2:

[1279] Device: Check the captured facial photo and press the upload button in the application to send the facial photo and user ID to the server.

[1280] Step 3:

[1281] Server: Stores the received facial photos and user IDs and prepares to send the facial photos to the AI ​​analysis unit.

[1282] Step 4:

[1283] Server: The AI ​​analysis unit analyzes the facial photo and, in addition to facial contours, hair type, and hair length, the emotion engine recognizes emotions from the user's facial expressions.

[1284] Step 5:

[1285] Server: Stores the facial feature data including the recognized emotion data and proceeds to the next step.

[1286] Step 6:

[1287] Server: The system generates thumbnails of multiple standard hairstyles and sends the data to the device.

[1288] Step 7:

[1289] Device: Displays thumbnail images of multiple hairstyles so the user can choose the hairstyle they want.

[1290] Step 8:

[1291] User: Selects the hairstyle they want. After selection, this information is also sent to the server.

[1292] Step 9:

[1293] Server: The AI ​​model combines the analysis results, emotional data, and information about the hairstyle selected by the user to generate the optimal cutting method and finished image.

[1294] Step 10:

[1295] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[1296] Step 11:

[1297] Device: The received finished image and cutting method data are displayed within the application, while the emotion engine analyzes the user's facial expression again.

[1298] Step 12:

[1299] User: Check the displayed image of the finished product. If it is acceptable, press the "OK" button. If it is not, provide feedback and proceed to the next step.

[1300] Step 13:

[1301] Device: Sends user feedback and emotion engine analysis results to the server.

[1302] Step 14:

[1303] Server: Based on the feedback and sentiment data obtained, the AI ​​model suggests other hairstyles that would suit the user.

[1304] Step 15:

[1305] Server: Sends data on new suggested hairstyles to the device.

[1306] Step 16:

[1307] Terminal: Shows the proposed new hairstyle image.

[1308] Step 17:

[1309] User: Review the new final image and if satisfied, press the "OK" button. If not, provide further feedback and repeat the process from step 13.

[1310] Step 18:

[1311] Device: When the user presses the "OK" button, the final finished image and cutting method data are saved on the device.

[1312] Step 19:

[1313] User: Go to the hair salon and show the hairdresser the finished image and cutting method data saved on the smartphone screen. If necessary, you can also print it out and bring it with you.

[1314] Step 20:

[1315] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method data.

[1316] This detailed processing step allows users to receive hairstyle suggestions based on their emotions using the emotion engine, and also provides feedback on the final result, resulting in a highly satisfying haircut.

[1317] Example 2

[1318] 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."

[1319] When a user tells a hair salon what hairstyle they want, the actual result often differs from their expectations. This leads to lower user satisfaction and a lack of smooth communication with the hairdresser. Furthermore, conventional systems have difficulty proposing hairstyles that take the user's emotions into account, making it difficult to provide optimal suggestions for each individual user.

[1320] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to take a facial image of themselves and transmit the image, a means for transmitting the taken facial image to the server using a terminal, a means for the server to store the received facial image in a database and perform preprocessing, a means for analyzing the uploaded facial image and identifying the facial contour, hair type, and hair length, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, a means for transferring the generated finished image to the terminal and displaying it, a means for the user to check the displayed finished image and obtain feedback, and a means for the user to save the final finished image and data on the haircut method and present it to the service provider. This allows the user to check the desired hairstyle in advance and enables hairstyle suggestions based on their emotions, thereby improving user satisfaction and facilitating smoother communication with the hairdresser.

[1321] A "user" is an individual who uses the system to take a picture of their face and select a hairstyle.

[1322] A "face image" is a digital image of a user's face that is uploaded to the system.

[1323] The "server" is a computer system that analyzes the facial image received from the user and generates an image of the optimal hairstyle.

[1324] A "terminal" is a device used by a user to take a facial image and send it to a server, such as a smartphone or tablet.

[1325] A "database" is a system that manages data such as facial images, analysis results, and user information stored on a server.

[1326] "Preprocessing" refers to the process by which the server converts the facial images it receives into an appropriate format and prepares them for analysis.

[1327] The "AI Analysis Unit" is a system that uses artificial intelligence to analyze facial images and identify facial contours, hair type, hair length, etc.

[1328] The "emotion engine" is a technology that analyzes emotions from a user's facial image and reflects them in hairstyle suggestions.

[1329] The "cutting method" is a specific haircutting method to achieve the ideal result based on the hairstyle selected by the user.

[1330] The "finished image" is an image of the hairstyle applied to the user's face, generated based on the analysis results and the hairstyle selected by the user.

[1331] "Feedback" refers to the user's evaluation and opinions on the displayed finished video, and is information that the system uses to reflect in its next suggestions and corrections.

[1332] A "service provider" is a professional, such as a hairdresser or barber, who actually provides haircutting services to users.

[1333] The present invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that image. Furthermore, by combining it with an emotion engine that recognizes and reflects the user's emotions, it is possible to achieve more sophisticated and personalized hairstyle suggestions. The specific configuration and procedures for implementing this system are as follows.

[1334] System Configuration

[1335] 1. User Device

[1336] Users take a photo of their face using a device such as a smartphone or tablet. A dedicated application is installed on the device, and they have the means to upload the image to the server through this application. At this time, the emotion engine analyzes the user's facial expressions and identifies the user's emotions.

[1337] 2. Server

[1338] The server has several functions:

[1339] Image reception and preprocessing: Receives the face image and user ID sent from the user's device and performs preprocessing such as image resizing and format conversion.

[1340] AI Analysis Unit: The pre-processed facial image is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length. The emotion engine then analyzes the user's facial expressions to obtain emotional information.

[1341] Hairstyle generation: Based on the analysis results, the user's emotional data, and the hairstyle information selected by the user, the generative AI model generates the optimal cutting method and finished image.

[1342] Data transfer: The generated finished image and cutting method data are sent to the user's device.

[1343] 3. Database

[1344] The database runs on a server and stores and manages the user's facial image, analysis results, emotional data, generated finished footage, and cutting method data.

[1345] Specific examples

[1346] Step-by-step process example

[1347] Below is a specific example of when a user wants a bob cut.

[1348] 1. User: Takes a picture of their face with their smartphone camera and uploads it to the application. The emotion engine analyzes the user's facial expressions and identifies emotions such as joy, excitement, or anxiety.

[1349] 2. Device: Sends face image and basic information to the server.

[1350] 3. Server: Analyzes the facial image to identify facial contours, hair type, and hair length, and then adds emotional information using an emotion engine.

[1351] 4. User: Selects a bob cut style. The emotion engine detects the user's emotion and sends emotional feedback for the selected style to the server.

[1352] 5. Server: The analysis results, emotional information, and bob cut data are combined, and the generative AI model generates the optimal finished video.

[1353] 6. Server: Sends the generated finished video to the terminal.

[1354] 7. Device: The finished video is displayed in the app, and the emotion engine checks the user's facial expressions again.

[1355] 8. User: If satisfied with the image, press the "OK" button to save the data. Based on the emotional feedback, the system can suggest other styles.

[1356] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[1357] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[1358] Prompt Sentence Examples

[1359] For example, if the user wants a bob cut, the prompt text is:

[1360] "I would like a bob cut. My current hair length is shoulder-length and wavy. I'm excited."

[1361] This system reduces the gap between the user and the hairdresser, allowing them to see their ideal hairstyle in advance. By using an emotion engine, it is possible to suggest styles based on the user's emotions, improving user satisfaction.

[1362] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1363] Step 1:

[1364] User: Take a picture of their face using their smartphone camera.

[1365] Specific actions: Open the camera app and adjust it so that your entire face is clearly visible under good lighting conditions.

[1366] Input: A face image.

[1367] Output: The captured face image.

[1368] Step 2:

[1369] Device: Uses a dedicated application to send the captured facial image to the server.

[1370] Specific operation: Press the upload button in the application to send data including the face image and user ID to the server via HTTPS protocol.

[1371] Input: A captured face image and user ID.

[1372] Output: Spatial transfer successful message to server.

[1373] Step 3:

[1374] Server: Stores the received face images and user IDs in a database and performs preprocessing.

[1375] Specific operation: Convert the facial image to a standard resolution and format (e.g., resize to 256x256 pixels).

[1376] Input: Face image and user ID.

[1377] Output: Preprocessed face image.

[1378] Step 4:

[1379] Server: The pre-processed facial image is input into the AI ​​analysis unit to identify features such as facial contours, hair type, and hair length.

[1380] Specific operation: Uses a deep learning model to extract facial features and output analysis results.

[1381] Input: Preprocessed face image.

[1382] Output: Facial feature data (shape, hair type, hair length, etc.).

[1383] Step 5:

[1384] Server: The emotion engine analyzes facial expressions in the facial images to identify the user's emotional state.

[1385] Specific behavior: Use a facial expression recognition algorithm to generate emotion labels such as happiness, excitement, and anxiety.

[1386] Input: Preprocessed face image.

[1387] Output: Emotion data (happiness, excitement, anxiety, etc.).

[1388] Step 6:

[1389] User: Selects the desired hairstyle through the user interface (e.g., bob cut).

[1390] Specific operations: Select the desired hairstyle on the hairstyle selection screen of the application and press the decision button.

[1391] Input: Your desired hairstyle selection information.

[1392] Output: Selected hairstyle information.

[1393] Step 7:

[1394] Server: The generative AI model combines the analysis results, the user's emotional data, and the selected hairstyle information to generate the optimal cutting method and a video of the finished product.

[1395] Specific operation: All data (facial feature data, emotional data, hairstyle information) is input and the AI ​​model generates the optimal finished image.

[1396] Input: Facial feature data, emotion data, hairstyle information.

[1397] Output: Optimal cutting method and finished image.

[1398] Step 8:

[1399] Server: Transfers the generated finished video and cutting method data to the terminal.

[1400] Specific operation: The generated data is sent to the terminal using the HTTPS protocol.

[1401] Input: Optimal cutting method and finished footage.

[1402] Output: A transmission completion message.

[1403] Step 9:

[1404] Terminal: The received finished image and cutting method data are displayed within the application.

[1405] Specific operation: The finished video is displayed on the mobile application screen and an interface is provided for collecting feedback.

[1406] Input: Received finished footage and cutting method.

[1407] Output: The application display screen.

[1408] Step 10:

[1409] User: Check the displayed finished image, and if satisfied, press the "OK" button to send feedback to the system.

[1410] Specific actions: Check the finished video in detail, and if you are satisfied, press the "OK" button. If necessary, enter feedback comments.

[1411] Input: Feedback on how the hairstyle turned out.

[1412] Output: Feedback information.

[1413] Step 11:

[1414] User: Save the final image and cutting method data and present it when going to the hair salon.

[1415] Specific actions: View the saved data on your smartphone screen and show it to your hairdresser, or print it out and bring it with you if necessary.

[1416] Input: Final footage and cutting data.

[1417] Output: Presentation to hairdresser.

[1418] Step 12:

[1419] Hairdresser: Cuts the user's hair according to their wishes, based on the information provided.

[1420] Specific actions: Based on the presented data, confirm the cutting method and then perform the actual cutting based on that.

[1421] Input: User-provided cutting method and finished footage.

[1422] Output: The finished hairstyle.

[1423] (Application example 2)

[1424] 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."

[1425] Conventional hairstyle simulation systems were unable to suggest hairstyles that reflected the user's emotions, and were unable to sufficiently increase user satisfaction. Furthermore, the lack of a system that effectively utilized user feedback to make new suggestions made the process of finding the optimal hairstyle cumbersome. Therefore, there was a need for a system that could suggest optimal hairstyles based on the user's emotions and efficiently utilize feedback to make further suggestions.

[1426] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1427] In this invention, the server includes a means for recognizing the user's emotions and adding that information to the analysis results, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, and a means for displaying the generated finished image and reanalyzing the user's facial expression to obtain feedback. This makes it possible to propose an optimal hairstyle based on the user's emotions. Furthermore, by automatically proposing new hairstyles based on the feedback, the user can efficiently find their ideal hairstyle.

[1428] A "user" is an individual who uses the system to simulate their own hairstyle.

[1429] A "face photo" is an image of a face taken by a user using an information processing device such as a smartphone.

[1430] The "means for uploading" is a function that allows a user to send a photograph of their face taken to a server via the Internet.

[1431] "Means for analysis" refers to software or algorithms that analyze uploaded facial photos and identify facial features such as facial contours, hair type, and hair length.

[1432] "Emotion recognition means" refers to technology that analyzes facial expressions in facial photos and feedback to identify the user's emotional state (happiness, anxiety, excitement, etc.).

[1433] The "means of fusion" is a function that combines analyzed facial feature information with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[1434] The "means of generation" is an algorithm that uses an AI model to create the optimal hairstyle cutting method and finished image based on the fused data.

[1435] The "display means" is a method for displaying the generated finished image on the display of the user's information processing device.

[1436] The "means for reanalyzing and obtaining feedback" is a technique for reanalyzing the facial expressions shown by the user in response to the displayed finished image and obtaining emotional feedback.

[1437] "Automatic suggestion method" is a function in which AI suggests alternative optimal hairstyles based on user feedback.

[1438] The "means for saving" is a method for saving the finished image and cutting method data that the user is satisfied with in a digital format in a recording device.

[1439] The "presenting means" is a means for displaying the saved cut information on the screen of an information processing device or on a recording medium to show it to the hairdresser.

[1440] An "information processing device" is a device that processes digital data, such as a smartphone, tablet, or personal computer.

[1441] A "recording medium" is a physical medium used to store or record data, such as paper, a USB memory stick, or a CD.

[1442] "Server" means a remote computing device that receives, analyzes, and stores uploaded user facial photographs and associated data.

[1443] To build a system that realizes this application example, the following hardware and software are used.

[1444] Hardware

[1445] User device: Information processing device such as smartphone, tablet, PC, etc.

[1446] Server: A remote computing device that analyzes facial photos, recognizes emotions, and generates hairstyles.

[1447] software

[1448] Facial recognition software: Libraries for extracting facial features, such as OpenCV or dlib.

[1449] Emotion Recognition Engine: A library for analyzing facial expressions and recognizing user emotions. It uses machine learning models with TensorFlow and Keras.

[1450] Hairstyle Generation Model: Uses an AI model to generate optimal hairstyles based on facial features and emotional information. Utilizes TensorFlow and PyTorch.

[1451] Specific methods for data processing and calculation

[1452] Taking and uploading a photo of your face

[1453] Users take a photo of themselves using their smartphone camera and upload it to the server through the application interface, along with their user ID.

[1454] Facial photo analysis and emotion recognition

[1455] The server uses facial recognition software to analyze the uploaded facial photo and extract features such as facial contours, hair type, and hair length, while simultaneously using an emotion recognition engine to identify emotions from the user's facial expressions.

[1456] Hairstyle generation

[1457] The system combines the user's selected hairstyle with facial features and emotional information, and uses a hairstyle generation model to generate the optimal cutting method and finished image. This image is generated using an AI model and is also adjusted according to the user's emotions.

[1458] Display and feedback of the finished image

[1459] The server then sends the resulting image to the user's device, where it is displayed within the application. The user's facial expressions are analyzed again to obtain feedback. If a negative emotion is detected, the system automatically suggests an alternative hairstyle.

[1460] Saving and presenting the final image

[1461] Once the user is satisfied with the final look and cutting method, the data is saved and when they go to the salon, they can show the smartphone screen or bring a printed copy of the data to communicate their wishes to the hairdresser.

[1462] Specific examples

[1463] For example, if the user enters the following prompt sentence, the system will suggest suitable hairstyles:

[1464] Example prompt sentence:

[1465] Users take a photo of themselves with their smartphone and upload it to the application. The application analyzes the user's photo and provides the ability to try out various hairstyles. It also has an assistant function that recognizes the user's emotions and recommends the best hairstyle based on that emotion.

[1466] This allows users to check the optimal hairstyle based on their facial photo and emotions, and efficiently request a haircut at a salon. This system not only increases user satisfaction, but also facilitates smooth communication with hairdressers.

[1467] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1468] Step 1:

[1469] The user takes a photo of their face using the smartphone camera. Once the photo is taken, they press the upload button in the application. This causes the device to send the photo and user ID to the server. The input includes the photo and user ID, and the output includes the photo and user ID sent to the server.

[1470] Step 2:

[1471] The server analyzes the received facial photo using facial recognition software (e.g., OpenCV). Specifically, it extracts features such as facial contours, hair type, and hair length. At the same time, it uses an emotion recognition engine (e.g., using TensorFlow or Keras) to identify emotions from the user's facial expressions. The facial photo is given as input, and facial feature data and emotion data are generated as output.

[1472] Step 3:

[1473] The user selects the desired hairstyle on the hairstyle selection screen. The selected hairstyle information is sent from the terminal to the server. The user's hairstyle selection is the input, and the selected hairstyle information is sent to the server as the output.

[1474] Step 4:

[1475] The server combines the analyzed facial feature data, emotion data, and the user-selected hairstyle information. This allows a hairstyle generation model (using, for example, TensorFlow or PyTorch) to generate the optimal haircutting method and finished image. Given the facial feature data, emotion data, and selected hairstyle information as input, the generated finished image and haircutting method data are obtained as output.

[1476] Step 5:

[1477] The server transmits the generated finished image and cutting method data to the terminal. The generated finished image and cutting method data are included as input, and these data are transmitted to the terminal as output.

[1478] Step 6:

[1479] The device displays the received finished image in the application for the user to confirm. It then analyzes the user's facial expression again to obtain emotional feedback. If the server detects a negative emotion based on this feedback, it automatically suggests a different hairstyle. The user's facial expression is given as input, and emotional feedback and a new hairstyle suggestion are obtained as output.

[1480] Step 7:

[1481] When the user is satisfied with the final image and cutting method, the data is saved. By presenting the saved data when visiting the salon, the user can accurately convey their wishes to the hairdresser. The finalized image of the final image and cutting method data are given as input, and these data are saved as output.

[1482] 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.

[1483] 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.

[1484] 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.

[1485] [Fourth embodiment]

[1486] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1487] 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.

[1488] 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).

[1489] 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.

[1490] 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.

[1491] 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).

[1492] 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.

[1493] 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.

[1494] 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.

[1495] 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.

[1496] 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.

[1497] 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.

[1498] 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."

[1499] This invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that photo. The following elements are required to implement this system: a device such as a smartphone or tablet, a server, and a dedicated application.

[1500] System configuration

[1501] Take and upload a photo of your face

[1502] User: Take a photo of their face using the camera function on their smartphone. After taking the photo, the user presses the upload button in the application to send the photo to the server.

[1503] Device: The application sends the captured face photo and user ID to the server.

[1504] Server: Receives facial photos and user information and prepares the facial photos to be input into the AI ​​model.

[1505] Face photo analysis and hairstyle selection

[1506] Server: The received facial photo is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length, which allows customization according to the user's hair condition.

[1507] User: Select the hairstyle they want on the hairstyle selection screen. After selection, the information is also sent to the server.

[1508] AI-based cutting method and finished image generation

[1509] Server: Based on the analysis of the facial photo and the hairstyle selected by the user, the AI ​​model generates the optimal cutting method and finished image, allowing users to simulate the actual image after the haircut.

[1510] Server: Sends the generated finished image and cutting method data to the terminal.

[1511] View the final image and get feedback

[1512] Device: The received image of the finished hairstyle is displayed to the user within the application. The user checks the displayed image and presses the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again.

[1513] Sharing information with hairdressers

[1514] User: Save the final image of the finished look and cutting method that they are satisfied with, and then go to the salon and present this. Specifically, they can show the screen of their smartphone to the hairdresser, or if necessary, bring a printed copy of the data with them.

[1515] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method.

[1516] Specific examples

[1517] For example, a specific example will be given where the user desires a "bob cut."

[1518] 1. User: Take a photo of their face with their smartphone camera and upload it to the application.

[1519] 2. Device: Sends a photo of the face and basic information to the server.

[1520] 3. Server: Analyzes the facial photo and identifies facial contours, hair type, and hair length.

[1521] 4. User: Choose a bob cut style.

[1522] 5. Server: The analysis results are combined with the bob cut data, and the AI ​​model generates the optimal finished image.

[1523] 6. Server: Sends the generated finished image to the device.

[1524] 7. Device: The finished image is displayed in the app and the user is asked to confirm.

[1525] 8. User: Once satisfied with the image, presses the "OK" button to save the data.

[1526] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[1527] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[1528] This system reduces the gap in results between the user and the hairdresser, allowing them to achieve their ideal hairstyle.

[1529] The processing flow will be explained below.

[1530] Step 1:

[1531] User: Use the camera on your smartphone to take a photo of yourself, preferably a high-resolution image.

[1532] Step 2:

[1533] Device: Check the captured facial photo and press the upload button in the application to send the facial photo and user ID to the server.

[1534] Step 3:

[1535] Server: Stores the received facial photos and user IDs and prepares to send the facial photos to the AI ​​analysis unit.

[1536] Step 4:

[1537] Server: The AI ​​analysis unit analyzes the facial photo to identify facial contours, hair type, and hair length, sometimes using external systems or cloud services.

[1538] Step 5:

[1539] User: Within the application, select the desired hairstyle from the thumbnails of multiple hairstyles displayed.

[1540] Step 6:

[1541] Device: Sends the selected hairstyle information to the server.

[1542] Step 7:

[1543] Server: The AI ​​model combines the analysis results with the hairstyle information selected by the user to generate the optimal cutting method and finished image.

[1544] Step 8:

[1545] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[1546] Step 9:

[1547] Terminal: The received finished image and cutting method data are displayed within the application.

[1548] Step 10:

[1549] User: Check the displayed image of the finished look, and if you are satisfied, press the "OK" button. If you are not satisfied, select another hairstyle and repeat the steps from step 5.

[1550] Step 11:

[1551] Device: When the user presses the "OK" button, the final finished image and cutting method data are saved on the device.

[1552] Step 12:

[1553] User: Go to the hair salon and show the hairdresser the finished image and cutting method data saved on the smartphone screen. If necessary, you can also print it out and bring it with you.

[1554] Step 13:

[1555] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method data.

[1556] Example 1

[1557] 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."

[1558] Conventional hairstyle selection systems have had the problem that it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, leading to dissatisfaction with the finished product. Also, few systems allow users to simulate the finished hairstyle in advance based on a photo of their own face. As a result, a communication gap occurs between the user and the hairdresser, making it difficult to achieve the ideal hairstyle.

[1559] 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.

[1560] In this invention, the server includes a means for a user to take a photo of their face and upload the photo, a means for analyzing the uploaded photo of their face to identify the facial contours, hair type, and hair length, and a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image. This allows the user to check in advance the finished image of the hairstyle based on their face photo, and makes it possible to present specific haircut information to the hairdresser.

[1561] "User" refers to an individual who uses the system to take a photo of themselves and select the hairstyle they desire.

[1562] "Terminal" refers to a device used by a user, such as a smartphone or tablet.

[1563] "Server" means the computer system that has the central function of receiving and processing uploaded photos and selected hairstyles.

[1564] "Taking and uploading a photo of your face" refers to the process in which a user takes a photo of their face using the device's camera and sends the photo to the server.

[1565] "Facial photo analysis" refers to the process of identifying facial contours, hair type, and hair length based on a facial photo uploaded to a server.

[1566] The "analysis results" are data obtained from facial photos processed by AI, and include information such as facial contours, hair type, and hair length.

[1567] "Hairstyle selection" refers to the act of a user selecting the hairstyle they want within a dedicated application.

[1568] "Hairstyle information" is data relating to the hairstyle selected by the user, and the cutting method and finished image are generated based on this information.

[1569] "Cutting method" refers to the haircutting method and treatment procedure suggested according to the hairstyle selected by the user.

[1570] "Finished Image" refers to an image generated by the AI ​​model that shows how the selected hairstyle will look on the user's face.

[1571] "Getting feedback" refers to the process of users checking their satisfaction with the displayed finished image and obtaining the results.

[1572] "Generative AI model" refers to artificial intelligence technology that generates the optimal cutting method and finished image based on a facial photo and hairstyle information.

[1573] "Means of presenting to the hairdresser on a smartphone or in printed form" refers to the means by which the user can show the hairdresser the haircut information saved by the user, including using the screen of a digital device or a paper printout.

[1574] "Artificial intelligence" refers to the technology that analyzes facial photos and performs computational processing to generate cutting methods and finished images.

[1575] This invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that photo. The following elements are required to implement this system: a device such as a smartphone or tablet, a server, and a dedicated application.

[1576] System configuration

[1577] Take and upload a photo of your face

[1578] User: Uses the camera function of the smartphone to take a photo of his / her face. After taking the photo, he / she presses the "upload" button in the dedicated application to send the photo to the server.

[1579] Device: The application sends the user's face photo data and user ID to the server. The photo is sent in JPEG or PNG format.

[1580] Preparation for facial photo analysis

[1581] Server: Stores the received face photo and user ID in a database. Then, it performs pre-processing to input the photo data into the AI ​​analysis unit. This pre-processing includes image resizing and noise removal.

[1582] Facial photo analysis

[1583] Server: The AI ​​analysis unit is used to analyze the facial features of the photo, specifically identifying facial contours, hair type, hair length, etc. The analysis results are saved in JSON format for subsequent processing.

[1584] Hairstyle selection

[1585] User: Select the desired hairstyle on the hairstyle selection screen of the dedicated application. For example, select "Bob Cut." After selecting, press the "Send" button to send the information to the server.

[1586] Terminal: Sends hairstyle information to the server. The selected hairstyle information is sent as text data.

[1587] AI-based cutting method and finished image generation

[1588] Server: Based on the analysis results of the facial photo and the hairstyle selected by the user, the generative AI model generates the optimal haircut method and finished image. Specifically, the prompt "Based on the facial photo and the selected hairstyle, please generate the optimal haircut method and finished image" is input to the AI.

[1589] Server: The generated finished image and cutting method data are encoded in JPEG or PNG format and sent to the user's device.

[1590] View the final image and get feedback

[1591] Device: The received finished image is displayed in the dedicated application. After checking the displayed image, the user can save the image by pressing the "OK" button, or return to the hairstyle selection screen by pressing the "Reselect" button.

[1592] User: If you are satisfied with the final image, press the "OK" button to save the data, but if you are not satisfied, select the hairstyle again.

[1593] Sharing information with hairdressers

[1594] User: Saves the final image of the finished look and cutting method data in a dedicated application, and shows the screen on their smartphone to the hairdresser when they visit the salon.

[1595] Hairdresser: Cuts the customer's hair according to their wishes, based on the presented image of the finished look and cutting method.

[1596] Specific examples

[1597] For example, a specific example will be given where the user desires a "bob cut."

[1598] User: Take a photo of their face with their smartphone camera and upload it to the application.

[1599] Device: Sends a photo of your face and basic information to the server.

[1600] Server: Analyzes facial photos to identify facial contours, hair type, and hair length.

[1601] User: Select "BobCut" on the application selection screen.

[1602] Server: The analysis results are combined with the "bob cut" style data, and the generative AI model generates the optimal finished image. Example prompt: "Generate the best bob cut style for this user based on their face photo."

[1603] Server: Sends the finished image generated by the AI ​​model to the user's device.

[1604] On device: The finished image is displayed in the app and the user is asked to confirm.

[1605] User: Once satisfied with the image, presses the "OK" button to save the data.

[1606] User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[1607] Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[1608] This reduces the gap in the results between the user and the hairdresser, allowing them to achieve their ideal hairstyle.

[1609] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1610] Step 1:

[1611] User: Activates the camera function of the smartphone and takes a photo of his / her face. After taking the photo, he / she presses the "upload" button in the dedicated application to send the photo to the server.

[1612] Input: A photo of the user's face (JPEG or PNG format).

[1613] Output: A request to upload a face photo to the server.

[1614] Specific operation: Take a photo with your smartphone camera and use the app's upload function to send the photo to the server.

[1615] Step 2:

[1616] On the device, the application sends the user's face photo data and user ID to the server. The photo is sent using the HTTPS protocol.

[1617] Input: User's face photo data, user ID.

[1618] Output: Send face photo data to the server.

[1619] What it does: The application converts the face photo data and user ID into a binary format and sends it securely to the server using the HTTPS protocol.

[1620] Step 3:

[1621] Server: Stores the received face photo and user ID in a database, then performs preprocessing to input the photo data into the AI ​​analysis unit.

[1622] Input: Face photo data, user ID.

[1623] Output: Preprocessed facial photo data.

[1624] Specific operation: The server resizes the facial photo data, removes noise, and stores it in the database.

[1625] Step 4:

[1626] Server: Uses an AI analysis unit to analyze the facial features of the photo, specifically identifying facial contours, hair type, hair length, etc.

[1627] Input: Preprocessed facial photo data.

[1628] Output: Feature data such as facial contours, hair type, and hair length (JSON format).

[1629] Specific operation: The AI ​​analysis unit uses deep learning technology to analyze facial photos and extract feature data.

[1630] Step 5:

[1631] User: Select the desired hairstyle on the hairstyle selection screen of the dedicated application. For example, select "Bob Cut." After selecting, press the "Send" button to send the information to the server.

[1632] Enter: hairstyle selection.

[1633] Output: Request to send hairstyle information.

[1634] Specific actions: Scroll through the hairstyle thumbnails in the application, select "Bob Cut," and press the "Submit" button to submit the hairstyle information.

[1635] Step 6:

[1636] Terminal: Sends hairstyle information to the server. The selected hairstyle information is sent as text data.

[1637] Input: Hairstyle information.

[1638] Output: Sending hairstyle information to the server.

[1639] What it does: The application converts the selected hairstyle information into text format and sends it to the server using the HTTPS protocol.

[1640] Step 7:

[1641] Server: Based on the analysis results of the facial photo and the hairstyle selected by the user, the generative AI model generates the optimal haircut method and finished image. Specifically, the prompt "Based on the facial photo and the selected hairstyle, please generate the optimal haircut method and finished image" is input to the AI.

[1642] Input: Analysis result feature data, selected hairstyle information.

[1643] Output: The generated cutting method and finished image.

[1644] Specific operation: The server inputs the analysis results and selected hairstyle information into the generative AI model, and generates a finished image based on the prompt text.

[1645] Step 8:

[1646] Server: The generated finished image and cutting method data are encoded in JPEG or PNG format and sent to the user's device.

[1647] Input: Generated cutting method and finished image.

[1648] Output: Sends the finished image and cutting method data to the user's device.

[1649] What happens: The server encodes the generated data and sends it to the user's device using the HTTPS protocol.

[1650] Step 9:

[1651] Device: The received finished image is displayed in the dedicated application. After checking the displayed image, the user can save the image by pressing the "OK" button, or return to the hairstyle selection screen by pressing the "Reselect" button.

[1652] Input: Finished image and cutting method data.

[1653] Output: Saved image or hairstyle reselection request.

[1654] Specific behavior: The application displays the received data and performs the save or reselection process depending on the user's selection.

[1655] Step 10:

[1656] User: Saves the final image of the finished look and cutting method data in a dedicated application, and shows the screen on their smartphone to the hairdresser when they visit the salon.

[1657] Input: Saved finished image and cutting method data.

[1658] Output: Presentation to hairdresser.

[1659] Specific operation: Display the data stored in the dedicated application and show it to the hairdresser, or print out the data and bring it with you if necessary.

[1660] Step 11:

[1661] Hairdresser: Cuts the customer's hair according to their wishes, based on the presented image of the finished look and cutting method.

[1662] Input: The proposed finished image and cutting method data.

[1663] Output: The actual haircut.

[1664] Specific operation: Cuts hair based on the provided data to achieve the hairstyle desired by the user.

[1665] (Application example 1)

[1666] 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."

[1667] The present invention aims to provide a system that allows users to check the finished hairstyle in advance, and to provide a means for smoothly and effectively sharing information with actual beauty salons and facilitating communication with hairdressers. Another objective is to improve the reliability of the user's desired hairstyle and to increase the accuracy of guidelines for hairdressers when performing the cut.

[1668] 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.

[1669] In this invention, the server includes a means for a user to take a photo of their face and upload the photo, a means for analyzing the uploaded photo of their face to identify the facial contours, hair type, and hair length, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, and a means for displaying and sharing this information with the hairdresser via a smartphone at the hair salon. This allows the user to check the optimal hairstyle in advance and to smoothly share information with the hairdresser when the hairstyle is performed at the hair salon.

[1670] "User" refers to ordinary consumers who use the system, and in particular to those who take a photo of their own face to check the final hairstyle.

[1671] "Facial photo" refers to image data of a face that is taken by a user using a device such as a smartphone and uploaded to the system.

[1672] "Means for uploading" refers to the part of the application that includes the function to send a photograph of a user's face to a server via the Internet.

[1673] "Means of analysis" refers to the function of using an artificial intelligence model to identify facial contours, hair type, hair length, etc. from the facial photo received by the server.

[1674] "Means for generating the optimal cutting method and finished image" refers to the function in which the AI ​​model combines the hairstyle selected by the user with the analysis results of the facial photo, simulates the optimal hairstyle finish, and generates the results as data.

[1675] "Means for displaying" refers to the function of displaying the generated finished image on the user's smartphone or tablet, allowing the user to visually check it.

[1676] "Means for obtaining feedback" refers to the function that allows the user to input opinions and comments, including the level of satisfaction with the displayed finished image, through the application and transmit them to the server.

[1677] "A means of saving the final image of the finished look and data on the cutting method, and presenting it to the hairdresser" refers to the function of saving the image of the hairstyle that the user is satisfied with as digital data, and showing it to the hairdresser at the salon on the screen of a device such as a smartphone, or presenting it in printed form if necessary.

[1678] "A means of displaying and sharing this information with hairdressers via smartphones at beauty salons" refers to the function of displaying and sharing the finished image and cutting method saved by the user on a smartphone so that the hairdresser can visually confirm it at the beauty salon.

[1679] "Artificial intelligence model" refers to a machine learning algorithm used to simulate the outcome of a hairstyle, and in this invention is used in particular to analyze the features of a facial photograph and generate an optimal hairstyle.

[1680] "Server" refers to the central computer system that receives and analyzes the User's facial photograph and feedback, and stores and transmits the generated finished images.

[1681] This invention is a system that allows users to take a photo of themselves using a device such as a smartphone or tablet and check in advance how their desired hairstyle will look based on that photo. The following elements are required to implement this system: a device, a server, and a dedicated application.

[1682] System configuration

[1683] 1. Take and upload a photo of your face

[1684] Users take a photo of their face using the camera on their smartphone, and then press the upload button in the application to send the photo to the server.

[1685] The device sends the captured facial photo and user ID to the server via the application.

[1686] The server receives the facial photo and user information, converts the facial photo into a format suitable for analysis, and prepares it for input into the artificial intelligence model.

[1687] 2. Face photo analysis and hairstyle selection

[1688] The server inputs the received facial photo into an AI analysis unit to identify features such as facial contours, hair type, and hair length, which allows customization according to the user's hair condition.

[1689] The user selects the hairstyle they want on the hairstyle selection screen, and after selection, the information is also sent to the server.

[1690] 3. AI-based cutting method and finished image generation

[1691] The server uses an AI model to generate the optimal haircut method and finished image based on the analysis of the facial photo and the hairstyle selected by the user, allowing users to simulate the actual image after the haircut.

[1692] The server again transmits the generated finished image and cutting method data to the terminal.

[1693] 4. View the final image and get feedback

[1694] The device will then display the received image of the finished look to the user within the application. The user can check the image and press the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again.

[1695] 5. Sharing information with hairdressers

[1696] Users can save the final image of the finished look and cutting method they are satisfied with, and then go to the salon and present this information to the hairdresser. Specifically, they can show the screen on their smartphone to the hairdresser, or if necessary, bring a printout of the data with them.

[1697] The hairdresser will cut the customer's hair based on the presented image of the finished look and cutting method.

[1698] Hardware and software used

[1699] Hardware: Smartphone (Android / iOS), server with high-performance CPU / GPU

[1700] Software: Smartphone app (iOS: Swift, Android: Kotlin), server side (Flask, Keras, OpenCV)

[1701] Specific examples

[1702] For example, consider the case where a user desires a shortcut.

[1703] The user is prompted to "Simulate the style of the shortcut."

[1704] The server receives the prompt, analyzes the facial photo, and generates the optimal shortcut image.

[1705] The server sends the generated finished image and cutting instructions to the user's terminal.

[1706] The user shows the image to the hairdresser at the salon and a specific cut plan is drawn up.

[1707] Prompt Sentence Examples

[1708] 1. Prompt: "Simulate a shortcut style based on a photo of the user's face."

[1709] 2. Prompt: "Generate the best possible finished image based on the user's desired hairstyle."

[1710] This allows users and hairdressers to smoothly share information to achieve their ideal hairstyle.

[1711] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1712] Step 1:

[1713] The user takes a photo of their face using the camera function of their smartphone and then presses the upload button in the application to send the photo to the server. The input data is the face photo and user ID, and the output is the image data sent to the server.

[1714] Step 2:

[1715] The server receives the uploaded facial photo and user information and converts the facial photo into a format suitable for analysis. This process mainly involves resizing and standardizing the image. The input data is the user's facial photo, and the output is image data in a format suitable for analysis.

[1716] Step 3:

[1717] The server analyzes facial photos. It inputs the image data into an artificial intelligence model (using Keras) to identify features such as facial contours, hair type, and hair length. The input data is resized and standardized image data, and the output is facial feature data.

[1718] Step 4:

[1719] The user selects the desired hairstyle on the application's hairstyle selection screen and sends the information to the server. The input data is the hairstyle ID selected by the user, and the output is the hairstyle data sent to the server.

[1720] Step 5:

[1721] The server uses an artificial intelligence model to generate the optimal haircut method and finished image based on the analysis of the facial photo and the hairstyle ID selected by the user. This process uses data analysis and a generative AI model to combine facial feature data and selected hairstyle data. The input data is facial feature data and hairstyle ID, and the output is the generated finished image and haircut method data.

[1722] Step 6:

[1723] The server then sends the generated finished image and cutting instructions to the user's device. The input data is the finished image and cutting instructions, and the output is the visual data sent to the user's smartphone.

[1724] Step 7:

[1725] The terminal displays the received finished image to the user in the application. The user checks the displayed image and presses the "OK" button if they are satisfied. If they are not satisfied, they can select the hairstyle again. The input data is the finished image received from the server, and the output is the user's feedback.

[1726] Step 8:

[1727] The user saves the final image of the finished look and data on the cutting method that they are satisfied with, and then goes to the salon and presents this. Specifically, they show the screen of their smartphone to the hairdresser, or if necessary, they bring a printed copy of the data. The input data is the saved image and cutting method data, and the output is what is presented at the salon.

[1728] Step 9:

[1729] The hairdresser cuts the user's hair based on the presented image of the finished look and cutting method. The input data is the image of the finished look and cutting method presented by the user, and the output is the actual hairstyle.

[1730] 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.

[1731] This invention is a system that allows users to take a photo of their face and check in advance how their desired hairstyle will look based on that photo, and it also combines an emotion engine that recognizes and reflects the user's emotions. To implement this system, the following elements are required: a device such as a smartphone or tablet, a server, a dedicated application, and an emotion engine.

[1732] System configuration

[1733] Take and upload a photo of your face

[1734] User: Take a photo of their face using the camera function on their smartphone. After taking the photo, the user presses the upload button in the application to send the photo to the server.

[1735] Device: The application sends the captured face photo and user ID to the server.

[1736] Server: Receives facial photos and user information and prepares the facial photos to be input into the AI ​​analysis unit.

[1737] Face photo analysis and hairstyle selection

[1738] Server: The received facial photo is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length. The facial photo is also analyzed to analyze the user's facial expressions, and the emotion engine recognizes the user's emotions.

[1739] User: Select the hairstyle they want on the hairstyle selection screen. After selection, the information is also sent to the server.

[1740] AI-based cutting method and finished image generation

[1741] Server: Based on the analysis of the facial photo, data on the user's emotions, and the hairstyle information selected by the user, the AI ​​model generates the optimal cutting method and finished image. By using the emotion engine, it can make adjustments based on the user's emotions.

[1742] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[1743] View the final image and get feedback

[1744] Device: The received finished image and cutting method data are displayed within the application, while the user's facial expression is recognized again and analyzed using the emotion engine.

[1745] User: Check the displayed image of the finished hairstyle and press the "OK" button if satisfied. If a negative emotion is detected from a change in facial expression, the system can automatically suggest an alternative hairstyle.

[1746] Sharing information with hairdressers

[1747] User: Save the final image of the finished look and cutting method that they are satisfied with, and then go to the salon and present this. Specifically, they can show the screen of their smartphone to the hairdresser, or if necessary, bring a printed copy of the data with them.

[1748] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method.

[1749] Specific examples

[1750] For example, a specific example will be given where the user desires a "bob cut."

[1751] 1. User: Take a photo of their face with their smartphone camera and upload it to the application. The emotion engine analyzes the user's facial expressions and identifies emotions such as joy, excitement, or anxiety.

[1752] 2. Device: Sends a photo of the face and basic information to the server.

[1753] 3. Server: Analyzes the facial photo to identify facial contours, hair type, and hair length, and then adds emotional information using an emotion engine.

[1754] 4. User: Selects a bob cut style. The emotion engine detects the user's emotion and sends emotional feedback for the selected style to the server.

[1755] 5. Server: The AI ​​model combines the analysis results, emotional information, and bob cut data to generate the optimal finished image.

[1756] 6. Server: Sends the generated finished image to the device.

[1757] 7. Device: The finished image is displayed in the app, and the emotion engine checks the user's facial expressions again.

[1758] 8. User: If satisfied with the image, press the "OK" button to save the data. Based on the emotional feedback, the system can suggest other styles.

[1759] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[1760] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[1761] This system reduces the gap between the user and the hairdresser, allowing them to achieve their ideal hairstyle. By using an emotion engine, it is possible to suggest styles based on the user's emotions, providing even higher satisfaction.

[1762] The processing flow will be explained below.

[1763] Step 1:

[1764] User: Use the camera on your smartphone to take a photo of yourself, preferably a high-resolution image.

[1765] Step 2:

[1766] Device: Check the captured facial photo and press the upload button in the application to send the facial photo and user ID to the server.

[1767] Step 3:

[1768] Server: Stores the received facial photos and user IDs and prepares to send the facial photos to the AI ​​analysis unit.

[1769] Step 4:

[1770] Server: The AI ​​analysis unit analyzes the facial photo and, in addition to facial contours, hair type, and hair length, the emotion engine recognizes emotions from the user's facial expressions.

[1771] Step 5:

[1772] Server: Stores the facial feature data including the recognized emotion data and proceeds to the next step.

[1773] Step 6:

[1774] Server: The system generates thumbnails of multiple standard hairstyles and sends the data to the device.

[1775] Step 7:

[1776] Device: Displays thumbnail images of multiple hairstyles so the user can choose the hairstyle they want.

[1777] Step 8:

[1778] User: Selects the hairstyle they want. After selection, this information is also sent to the server.

[1779] Step 9:

[1780] Server: The AI ​​model combines the analysis results, emotional data, and information about the hairstyle selected by the user to generate the optimal cutting method and finished image.

[1781] Step 10:

[1782] Server: Sends the generated finished image (an image of the user's face with the hairstyle applied) and cutting method data to the device.

[1783] Step 11:

[1784] Device: The received finished image and cutting method data are displayed within the application, while the emotion engine analyzes the user's facial expression again.

[1785] Step 12:

[1786] User: Check the displayed image of the finished product. If it is acceptable, press the "OK" button. If it is not, provide feedback and proceed to the next step.

[1787] Step 13:

[1788] Device: Sends user feedback and emotion engine analysis results to the server.

[1789] Step 14:

[1790] Server: Based on the feedback and sentiment data obtained, the AI ​​model suggests other hairstyles that would suit the user.

[1791] Step 15:

[1792] Server: Sends data on new suggested hairstyles to the device.

[1793] Step 16:

[1794] Terminal: Shows the proposed new hairstyle image.

[1795] Step 17:

[1796] User: Review the new final image and if satisfied, press the "OK" button. If not, provide further feedback and repeat the process from step 13.

[1797] Step 18:

[1798] Device: When the user presses the "OK" button, the final finished image and cutting method data are saved on the device.

[1799] Step 19:

[1800] User: Go to the hair salon and show the hairdresser the finished image and cutting method data saved on the smartphone screen. If necessary, you can also print it out and bring it with you.

[1801] Step 20:

[1802] Hairdresser: Cuts the user's hair based on the presented image of the finished look and cutting method data.

[1803] This detailed processing step allows users to receive hairstyle suggestions based on their emotions using the emotion engine, and also provides feedback on the final result, resulting in a highly satisfying haircut.

[1804] Example 2

[1805] 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."

[1806] When a user tells a hair salon what hairstyle they want, the actual result often differs from their expectations. This leads to lower user satisfaction and a lack of smooth communication with the hairdresser. Furthermore, conventional systems have difficulty proposing hairstyles that take the user's emotions into account, making it difficult to provide optimal suggestions for each individual user.

[1807] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for a user to take a facial image of themselves and transmit the image, a means for transmitting the taken facial image to the server using a terminal, a means for the server to store the received facial image in a database and perform preprocessing, a means for analyzing the uploaded facial image and identifying the facial contour, hair type, and hair length, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, a means for transferring the generated finished image to the terminal and displaying it, a means for the user to check the displayed finished image and obtain feedback, and a means for the user to save the final finished image and data on the haircut method and present it to the service provider. This allows the user to check the desired hairstyle in advance and enables hairstyle suggestions based on their emotions, thereby improving user satisfaction and facilitating smoother communication with the hairdresser.

[1808] A "user" is an individual who uses the system to take a picture of their face and select a hairstyle.

[1809] A "face image" is a digital image of a user's face that is uploaded to the system.

[1810] The "server" is a computer system that analyzes the facial image received from the user and generates an image of the optimal hairstyle.

[1811] A "terminal" is a device used by a user to take a facial image and send it to a server, such as a smartphone or tablet.

[1812] A "database" is a system that manages data such as facial images, analysis results, and user information stored on a server.

[1813] "Preprocessing" refers to the process by which the server converts the facial images it receives into an appropriate format and prepares them for analysis.

[1814] The "AI Analysis Unit" is a system that uses artificial intelligence to analyze facial images and identify facial contours, hair type, hair length, etc.

[1815] The "emotion engine" is a technology that analyzes emotions from a user's facial image and reflects them in hairstyle suggestions.

[1816] The "cutting method" is a specific haircutting method to achieve the ideal result based on the hairstyle selected by the user.

[1817] The "finished image" is an image of the hairstyle applied to the user's face, generated based on the analysis results and the hairstyle selected by the user.

[1818] "Feedback" refers to the user's evaluation and opinions on the displayed finished video, and is information that the system uses to reflect in its next suggestions and corrections.

[1819] A "service provider" is a professional, such as a hairdresser or barber, who actually provides haircutting services to users.

[1820] The present invention is a system that allows users to take a photo of their face and check the desired hairstyle in advance based on that image. Furthermore, by combining it with an emotion engine that recognizes and reflects the user's emotions, it is possible to achieve more sophisticated and personalized hairstyle suggestions. The specific configuration and procedures for implementing this system are as follows.

[1821] System Configuration

[1822] 1. User Device

[1823] Users take a photo of their face using a device such as a smartphone or tablet. A dedicated application is installed on the device, and they have the means to upload the image to the server through this application. At this time, the emotion engine analyzes the user's facial expressions and identifies the user's emotions.

[1824] 2. Server

[1825] The server has several functions:

[1826] Image reception and preprocessing: Receives the face image and user ID sent from the user's device and performs preprocessing such as image resizing and format conversion.

[1827] AI Analysis Unit: The pre-processed facial image is input into the AI ​​analysis unit to identify facial features such as facial contours, hair type, and hair length. The emotion engine then analyzes the user's facial expressions to obtain emotional information.

[1828] Hairstyle generation: Based on the analysis results, the user's emotional data, and the hairstyle information selected by the user, the generative AI model generates the optimal cutting method and finished image.

[1829] Data transfer: The generated finished image and cutting method data are sent to the user's device.

[1830] 3. Database

[1831] The database runs on a server and stores and manages the user's facial image, analysis results, emotional data, generated finished footage, and cutting method data.

[1832] Specific examples

[1833] Step-by-step process example

[1834] Below is a specific example of when a user wants a bob cut.

[1835] 1. User: Takes a picture of their face with their smartphone camera and uploads it to the application. The emotion engine analyzes the user's facial expressions and identifies emotions such as joy, excitement, or anxiety.

[1836] 2. Device: Sends face image and basic information to the server.

[1837] 3. Server: Analyzes the facial image to identify facial contours, hair type, and hair length, and then adds emotional information using an emotion engine.

[1838] 4. User: Selects a bob cut style. The emotion engine detects the user's emotion and sends emotional feedback for the selected style to the server.

[1839] 5. Server: The analysis results, emotional information, and bob cut data are combined, and the generative AI model generates the optimal finished video.

[1840] 6. Server: Sends the generated finished video to the terminal.

[1841] 7. Device: The finished video is displayed in the app, and the emotion engine checks the user's facial expressions again.

[1842] 8. User: If satisfied with the image, press the "OK" button to save the data. Based on the emotional feedback, the system can suggest other styles.

[1843] 9. User: Go to the salon and show the hairdresser the haircut information on your smartphone screen.

[1844] 10. Hairdresser: Based on the information provided, the hairdresser will provide the haircut according to the user's wishes.

[1845] Prompt Sentence Examples

[1846] For example, if the user wants a bob cut, the prompt text is:

[1847] "I would like a bob cut. My current hair length is shoulder-length and wavy. I'm excited."

[1848] This system reduces the gap between the user and the hairdresser, allowing them to see their ideal hairstyle in advance. By using an emotion engine, it is possible to suggest styles based on the user's emotions, improving user satisfaction.

[1849] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1850] Step 1:

[1851] User: Take a picture of their face using their smartphone camera.

[1852] Specific actions: Open the camera app and adjust it so that your entire face is clearly visible under good lighting conditions.

[1853] Input: A face image.

[1854] Output: The captured face image.

[1855] Step 2:

[1856] Device: Uses a dedicated application to send the captured facial image to the server.

[1857] Specific operation: Press the upload button in the application to send data including the face image and user ID to the server via HTTPS protocol.

[1858] Input: A captured face image and user ID.

[1859] Output: Spatial transfer successful message to server.

[1860] Step 3:

[1861] Server: Stores the received face images and user IDs in a database and performs preprocessing.

[1862] Specific operation: Convert the facial image to a standard resolution and format (e.g., resize to 256x256 pixels).

[1863] Input: Face image and user ID.

[1864] Output: Preprocessed face image.

[1865] Step 4:

[1866] Server: The pre-processed facial image is input into the AI ​​analysis unit to identify features such as facial contours, hair type, and hair length.

[1867] Specific operation: Uses a deep learning model to extract facial features and output analysis results.

[1868] Input: Preprocessed face image.

[1869] Output: Facial feature data (shape, hair type, hair length, etc.).

[1870] Step 5:

[1871] Server: The emotion engine analyzes facial expressions in the facial images to identify the user's emotional state.

[1872] Specific behavior: Use a facial expression recognition algorithm to generate emotion labels such as happiness, excitement, and anxiety.

[1873] Input: Preprocessed face image.

[1874] Output: Emotion data (happiness, excitement, anxiety, etc.).

[1875] Step 6:

[1876] User: Selects the desired hairstyle through the user interface (e.g., bob cut).

[1877] Specific operations: Select the desired hairstyle on the hairstyle selection screen of the application and press the decision button.

[1878] Input: Your desired hairstyle selection information.

[1879] Output: Selected hairstyle information.

[1880] Step 7:

[1881] Server: The generative AI model combines the analysis results, the user's emotional data, and the selected hairstyle information to generate the optimal cutting method and a video of the finished product.

[1882] Specific operation: All data (facial feature data, emotional data, hairstyle information) is input and the AI ​​model generates the optimal finished image.

[1883] Input: Facial feature data, emotion data, hairstyle information.

[1884] Output: Optimal cutting method and finished image.

[1885] Step 8:

[1886] Server: Transfers the generated finished video and cutting method data to the terminal.

[1887] Specific operation: The generated data is sent to the terminal using the HTTPS protocol.

[1888] Input: Optimal cutting method and finished footage.

[1889] Output: A transmission completion message.

[1890] Step 9:

[1891] Terminal: The received finished image and cutting method data are displayed within the application.

[1892] Specific operation: The finished video is displayed on the mobile application screen and an interface is provided for collecting feedback.

[1893] Input: Received finished footage and cutting method.

[1894] Output: The application display screen.

[1895] Step 10:

[1896] User: Check the displayed finished image, and if satisfied, press the "OK" button to send feedback to the system.

[1897] Specific actions: Check the finished video in detail, and if you are satisfied, press the "OK" button. If necessary, enter feedback comments.

[1898] Input: Feedback on how the hairstyle turned out.

[1899] Output: Feedback information.

[1900] Step 11:

[1901] User: Save the final image and cutting method data and present it when going to the hair salon.

[1902] Specific actions: View the saved data on your smartphone screen and show it to your hairdresser, or print it out and bring it with you if necessary.

[1903] Input: Final footage and cutting data.

[1904] Output: Presentation to hairdresser.

[1905] Step 12:

[1906] Hairdresser: Cuts the user's hair according to their wishes, based on the information provided.

[1907] Specific actions: Based on the presented data, confirm the cutting method and then perform the actual cutting based on that.

[1908] Input: User-provided cutting method and finished footage.

[1909] Output: The finished hairstyle.

[1910] (Application example 2)

[1911] 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."

[1912] Conventional hairstyle simulation systems were unable to suggest hairstyles that reflected the user's emotions, and were unable to sufficiently increase user satisfaction. Furthermore, the lack of a system that effectively utilized user feedback to make new suggestions made the process of finding the optimal hairstyle cumbersome. Therefore, there was a need for a system that could suggest optimal hairstyles based on the user's emotions and efficiently utilize feedback to make further suggestions.

[1913] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1914] In this invention, the server includes a means for recognizing the user's emotions and adding that information to the analysis results, a means for combining the analysis results with the hairstyle selected by the user to generate an optimal haircut method and finished image, and a means for displaying the generated finished image and reanalyzing the user's facial expression to obtain feedback. This makes it possible to propose an optimal hairstyle based on the user's emotions. Furthermore, by automatically proposing new hairstyles based on the feedback, the user can efficiently find their ideal hairstyle.

[1915] A "user" is an individual who uses the system to simulate their own hairstyle.

[1916] A "face photo" is an image of a face taken by a user using an information processing device such as a smartphone.

[1917] The "means for uploading" is a function that allows a user to send a photograph of their face taken to a server via the Internet.

[1918] "Means for analysis" refers to software or algorithms that analyze uploaded facial photos and identify facial features such as facial contours, hair type, and hair length.

[1919] "Emotion recognition means" refers to technology that analyzes facial expressions in facial photos and feedback to identify the user's emotional state (happiness, anxiety, excitement, etc.).

[1920] The "means of fusion" is a function that combines analyzed facial feature information with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[1921] The "means of generation" is an algorithm that uses an AI model to create the optimal hairstyle cutting method and finished image based on the fused data.

[1922] The "display means" is a method for displaying the generated finished image on the display of the user's information processing device.

[1923] The "means for reanalyzing and obtaining feedback" is a technique for reanalyzing the facial expressions shown by the user in response to the displayed finished image and obtaining emotional feedback.

[1924] "Automatic suggestion method" is a function in which AI suggests alternative optimal hairstyles based on user feedback.

[1925] The "means for saving" is a method for saving the finished image and cutting method data that the user is satisfied with in a digital format in a recording device.

[1926] The "presenting means" is a means for displaying the saved cut information on the screen of an information processing device or on a recording medium to show it to the hairdresser.

[1927] An "information processing device" is a device that processes digital data, such as a smartphone, tablet, or personal computer.

[1928] A "recording medium" is a physical medium used to store or record data, such as paper, a USB memory stick, or a CD.

[1929] "Server" means a remote computing device that receives, analyzes, and stores uploaded user facial photographs and associated data.

[1930] To build a system that realizes this application example, the following hardware and software are used.

[1931] Hardware

[1932] User device: Information processing device such as smartphone, tablet, PC, etc.

[1933] Server: A remote computing device that analyzes facial photos, recognizes emotions, and generates hairstyles.

[1934] software

[1935] Facial recognition software: Libraries for extracting facial features, such as OpenCV or dlib.

[1936] Emotion Recognition Engine: A library for analyzing facial expressions and recognizing user emotions. It uses machine learning models with TensorFlow and Keras.

[1937] Hairstyle Generation Model: Uses an AI model to generate optimal hairstyles based on facial features and emotional information. Utilizes TensorFlow and PyTorch.

[1938] Specific methods for data processing and calculation

[1939] Taking and uploading a photo of your face

[1940] Users take a photo of themselves using their smartphone camera and upload it to the server through the application interface, along with their user ID.

[1941] Facial photo analysis and emotion recognition

[1942] The server uses facial recognition software to analyze the uploaded facial photo and extract features such as facial contours, hair type, and hair length, while simultaneously using an emotion recognition engine to identify emotions from the user's facial expressions.

[1943] Hairstyle generation

[1944] The system combines the user's selected hairstyle with facial features and emotional information, and uses a hairstyle generation model to generate the optimal cutting method and finished image. This image is generated using an AI model and is also adjusted according to the user's emotions.

[1945] Display and feedback of the finished image

[1946] The server then sends the resulting image to the user's device, where it is displayed within the application. The user's facial expressions are analyzed again to obtain feedback. If a negative emotion is detected, the system automatically suggests an alternative hairstyle.

[1947] Saving and presenting the final image

[1948] Once the user is satisfied with the final look and cutting method, the data is saved and when they go to the salon, they can show the smartphone screen or bring a printed copy of the data to communicate their wishes to the hairdresser.

[1949] Specific examples

[1950] For example, if the user enters the following prompt sentence, the system will suggest suitable hairstyles:

[1951] Example prompt sentence:

[1952] Users take a photo of themselves with their smartphone and upload it to the application. The application analyzes the user's photo and provides the ability to try out various hairstyles. It also has an assistant function that recognizes the user's emotions and recommends the best hairstyle based on that emotion.

[1953] This allows users to check the optimal hairstyle based on their facial photo and emotions, and efficiently request a haircut at a salon. This system not only increases user satisfaction, but also facilitates smooth communication with hairdressers.

[1954] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1955] Step 1:

[1956] The user takes a photo of their face using the smartphone camera. Once the photo is taken, they press the upload button in the application. This causes the device to send the photo and user ID to the server. The input includes the photo and user ID, and the output includes the photo and user ID sent to the server.

[1957] Step 2:

[1958] The server analyzes the received facial photo using facial recognition software (e.g., OpenCV). Specifically, it extracts features such as facial contours, hair type, and hair length. At the same time, it uses an emotion recognition engine (e.g., using TensorFlow or Keras) to identify emotions from the user's facial expressions. The facial photo is given as input, and facial feature data and emotion data are generated as output.

[1959] Step 3:

[1960] The user selects the desired hairstyle on the hairstyle selection screen. The selected hairstyle information is sent from the terminal to the server. The user's hairstyle selection is the input, and the selected hairstyle information is sent to the server as the output.

[1961] Step 4:

[1962] The server combines the analyzed facial feature data, emotion data, and the user-selected hairstyle information. This allows a hairstyle generation model (using, for example, TensorFlow or PyTorch) to generate the optimal haircutting method and finished image. Given the facial feature data, emotion data, and selected hairstyle information as input, the generated finished image and haircutting method data are obtained as output.

[1963] Step 5:

[1964] The server transmits the generated finished image and cutting method data to the terminal. The generated finished image and cutting method data are included as input, and these data are transmitted to the terminal as output.

[1965] Step 6:

[1966] The device displays the received finished image in the application for the user to confirm. It then analyzes the user's facial expression again to obtain emotional feedback. If the server detects a negative emotion based on this feedback, it automatically suggests a different hairstyle. The user's facial expression is given as input, and emotional feedback and a new hairstyle suggestion are obtained as output.

[1967] Step 7:

[1968] When the user is satisfied with the final image and cutting method, the data is saved. By presenting the saved data when visiting the salon, the user can accurately convey their wishes to the hairdresser. The finalized image of the final image and cutting method data are given as input, and these data are saved as output.

[1969] 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.

[1970] 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.

[1971] 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.

[1972] 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.

[1973] 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.

[1974] 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.

[1975] 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).

[1976] 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.

[1977] 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."

[1978] 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.

[1979] 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).

[1980] 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.

[1981] 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.

[1982] 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.

[1983] 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.

[1984] 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.

[1985] 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.

[1986] 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.

[1987] 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.

[1988] 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.

[1989] 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.

[1990] The following is further disclosed regarding the above embodiment.

[1991] (Claim 1)

[1992] A means for users to take and upload a photo of their face;

[1993] A method for analyzing uploaded facial photos to identify facial contours, hair type, and hair length;

[1994] A method to combine the analysis results with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[1995] a means for displaying the generated finished image;

[1996] A means for users to view the displayed finished image and receive feedback;

[1997] A way for users to save the final image of the finished product and data on the cutting method and present it to the hairdresser.

[1998] A system including:

[1999] (Claim 2)

[2000] The system of claim 1 uses an artificial intelligence model to generate the optimal cutting method and finished image based on the analysis results and the hairstyle selected by the user.

[2001] (Claim 3)

[2002] 10. The system of claim 1, further comprising means for presenting the user-saved cutting information to the hairdresser via a smartphone or in printed form.

[2003] "Example 1"

[2004] (Claim 1)

[2005] A means for users to take and upload a photo of their face;

[2006] A method for analyzing uploaded facial photos to identify facial contours, hair type, and hair length;

[2007] A method to combine the analysis results with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[2008] a means for displaying the generated finished image;

[2009] A means for users to view the displayed finished image and receive feedback;

[2010] A way for users to save the final image of the finished product and data on the cutting method and present it to the hairdresser.

[2011] A system including:

[2012] (Claim 2)

[2013] The system of claim 1 uses a generative AI model that generates the optimal cutting method and finished image based on the analysis results and the hairstyle selected by the user.

[2014] (Claim 3)

[2015] 10. The system of claim 1, including artificial intelligence that analyzes a facial photograph to identify facial contours, hair type, and hair length.

[2016] "Application Example 1"

[2017] (Claim 1)

[2018] A means for users to take and upload a photo of their face;

[2019] A method for analyzing uploaded facial photos to identify facial contours, hair type, and hair length;

[2020] A method to combine the analysis results with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[2021] a means for displaying the generated finished image;

[2022] A means for users to view the displayed finished image and receive feedback;

[2023] A way for users to save the final image of the finished product and data on the cutting method and present it to the hairdresser.

[2024] In the beauty salon, this information can be displayed and shared with the hairdresser via smartphone,

[2025] A system including:

[2026] (Claim 2)

[2027] The system of claim 1 uses an artificial intelligence model that generates the optimal cutting method and finished image based on the analysis results and the hairstyle selected by the user, and the generated image can be viewed and shared at the beauty salon via a smartphone.

[2028] (Claim 3)

[2029] The system of claim 1 further includes a means for presenting the haircut information saved by the user to the hairdresser on a smartphone or in printed form, and for displaying hairstyle simulation data generated by the AI ​​model in cooperation with a server.

[2030] "Example 2: Combining Emotion Engines"

[2031] (Claim 1)

[2032] A means for a user to take a picture of their face and transmit the picture;

[2033] means for transmitting the captured face image to a server using a terminal;

[2034] A means for storing the received facial images in a database and performing preprocessing by the server;

[2035] A method for analyzing uploaded facial images to identify facial contours, hair type, and hair length;

[2036] A method to combine the analysis results with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[2037] a means for transferring the generated finished image to a terminal and displaying it;

[2038] A means for users to view the displayed finished image and receive feedback;

[2039] A means for the user to save the final finished image and cutting method data and present it to the service provider;

[2040] A system including:

[2041] (Claim 2)

[2042] The system of claim 1 uses an artificial intelligence model that generates the optimal cutting method and finished image based on the analysis results and the hairstyle selected by the user.

[2043] (Claim 3)

[2044] 10. The system of claim 1, further comprising means for presenting the cut information saved by the user to the service provider on a mobile device or in printed form.

[2045] "Application example 2 when combining emotion engines"

[2046] (Claim 1)

[2047] A means for users to take and upload a photo of their face;

[2048] A method for analyzing uploaded facial photos to identify facial contours, hair type, and hair length;

[2049] A means of recognizing user emotions and adding that information to the analysis results;

[2050] A method to combine the analysis results with the hairstyle selected by the user to generate the optimal cutting method and finished image.

[2051] A means for displaying the generated finished image and reanalyzing the user's facial expression to obtain feedback;

[2052] A means of automatically suggesting alternative hairstyles to the user based on their feedback; and

[2053] A way for users to save the final image of the finished product and data on the cutting method and present it to the hairdresser.

[2054] A system including:

[2055] (Claim 2)

[2056] The system of claim 1 uses an artificial intelligence model to generate the optimal cutting method and finished image based on the analysis results and the hairstyle selected by the user.

[2057] (Claim 3)

[2058] 2. The system according to claim 1, further comprising means for presenting the haircut information saved by the user to the hairdresser via an information processing device or a recording medium. [Explanation of symbols]

[2059] 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 take and upload a photo of their face; A method for analyzing uploaded facial photos to identify facial contours, hair type, and hair length; A method to combine the analysis results with the hairstyle selected by the user to generate the optimal cutting method and finished image. a means for displaying the generated finished image; A means for users to view the displayed finished image and receive feedback; A way for users to save the final image of the finished product and data on the cutting method and present it to the hairdresser. A system including:

2. The system according to claim 1, which uses an artificial intelligence model to generate the optimal cutting method and finished image based on the analysis results and the hairstyle selected by the user.

3. 10. The system of claim 1, further comprising means for presenting the user-saved cutting information to the hairdresser via a smartphone or in printed form.

Images