system

Abstract

Provide a system. The system includes a means for a user to upload facial images taken from multiple angles; A means for analyzing the face image received by the server and recognizing facial feature points and hairstyle information; A server uses a generative AI model to synthesize multiple hairstyle patterns and display them naturally on the user's face image; A means for displaying a plurality of hairstyle patterns to a user on the terminal; A means for selecting a hairstyle pattern desired by the user; A means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern; A means for displaying the generated haircut recipe and a future hairstyle simulation to the user on the terminal; A system including:

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 conventional beauty salons, it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, and the finished product often differs from expectations. It is also difficult to predict future hairstyles and make long-term hairstyle plans. In particular, selecting the optimal hairstyle based on the user's facial features and hair shape requires a high level of technical knowledge. Therefore, to improve user satisfaction, a system is needed that allows users to more intuitively and easily select the desired hairstyle and communicate specific instructions to the hairdresser. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. The system has a means for a user to upload facial images taken from multiple angles, and a server analyzes the received facial images and recognizes facial feature points and hairstyle information. Furthermore, the server provides a means for using a generative AI model to synthesize multiple hairstyle patterns and display them naturally on the user's facial image. Next, the terminal has a means for displaying multiple hairstyle patterns to the user and allowing the user to select the hairstyle pattern they desire. Based on the selected hairstyle pattern, the server generates a specific haircut recipe and a future hairstyle simulation. The terminal also has a means for displaying the generated haircut recipe and future hairstyle simulation to the user. This allows the user to easily select the hairstyle they desire and provide specific instructions to the hairdresser.

[0006] "User" refers to an individual who operates the system and uploads a facial image to receive a simulation of a desired hairstyle and cutting recipe.

[0007] "Terminal" refers to a computer, smartphone, tablet, or other device operated by a user and used to communicate with a server.

[0008] "Server" refers to a remote computer system that receives and analyzes facial images uploaded by users, and synthesizes and stores hairstyle patterns using a generative AI model.

[0009] "Facial images" refer to photographs of the user's face taken from multiple angles, and are image data uploaded to the system.

[0010] "Analysis" refers to a series of processes in which the server recognizes the features and hairstyle information of the facial image received and generates a hairstyle pattern based on this.

[0011] "Feature points" refer to important points in a face image, such as the eyes, nose, mouth, and contours, and are reference points used to generate hairstyle patterns.

[0012] "Hairstyle patterns" refer to different hairstyle variations that the generative AI model synthesizes for a user's facial image.

[0013] "Generative AI model" refers to an artificial intelligence algorithm trained to generate hairstyle patterns.

[0014] "Synthesis" refers to the processing that the generative AI model performs to naturally display different hairstyle patterns on facial images.

[0015] A "haircut recipe" refers to a document that includes specific instructions for a hairdresser to perform a haircut based on the hairstyle selected by the user.

[0016] "Future hairstyle simulation" refers to a synthetic image or information that predicts future changes in hairstyle and provides it to the user. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention is a system for allowing a user to accurately communicate a desired hairstyle to a hairdresser, and can be implemented as follows.

[0039] First, the user accesses the system using a terminal and uploads facial images taken from multiple angles, such as the front, side, and back of the head. The user then follows the instructions to select the image file and send it to the system.

[0040] Next, the device temporarily saves the image file selected by the user and then sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. Specifically, it identifies important points such as the eyes, nose, mouth, and face shape, and also analyzes the current hairstyle shape and color.

[0041] The server then uses a generative AI model based on the analyzed data to generate multiple hairstyle patterns. The generative AI model synthesizes a natural hairstyle that suits the user's face based on the trained data. For example, different variations such as short hair, long hair, bob, and perm are generated.

[0042] The server then combines the generated hairstyle patterns with the user's facial image, saves each pattern as an image, and transmits the combined image to the terminal.

[0043] The terminal displays the list of hairstyle patterns received from the server to the user, who can then check the displayed hairstyle patterns and select the hairstyle that he or she likes best.

[0044] When the user selects the desired hairstyle, the device sends that information to the server. The server then generates a specific haircut recipe based on the selected hairstyle. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The device also simulates future hairstyles, displaying a composite image of what a long bob will look like in three months.

[0045] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then bring this haircut recipe to the hair salon and provide specific instructions to the hairdresser.

[0046] As a specific example, User A uploads three images of his face - one from the front, one from the side, and one from the back of his head - and the server generates ten different hairstyle patterns. User A selects a bob style from the images, and the server generates a haircut recipe based on that selection, including the length of the bangs and the amount of hair on the sides. In addition, a simulated image of a long bob three months from now is also provided. User A can show this information to a hairdresser to achieve the desired hairstyle.

[0047] In this way, by using the present invention, the user can simulate the hairstyle they want in advance and, based on the results, give detailed instructions to the hairdresser.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] The user accesses the system using a terminal, takes three images of their face (front, side, and back of the head), and uploads each image to the system.

[0051] Step 2:

[0052] The device temporarily stores the facial image files uploaded by the user, displays a confirmation message indicating that the upload is complete, and then transmits the facial image files to the server.

[0053] Step 3:

[0054] The server analyzes the received facial image. Specifically, it detects facial features (eyes, nose, mouth, contours, etc.) and identifies their positions. It also analyzes the shape and color of the hairstyle.

[0055] Step 4:

[0056] The server uses a generative AI model based on the analysis results to generate multiple hairstyle patterns to be combined with the user's facial image. The generative AI model uses the learned data to create a natural hairstyle. Different variations such as short hair, long hair, bob, and perm are generated.

[0057] Step 5:

[0058] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way, saves each pattern as an image file, and transmits the synthesized images to the terminal.

[0059] Step 6:

[0060] The terminal displays the list of hairstyle patterns received from the server to the user, who then checks the displayed multiple hairstyle patterns and selects the hairstyle that he or she likes best.

[0061] Step 7:

[0062] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server.

[0063] Step 8:

[0064] The server generates a specific haircut recipe based on the selected hairstyle pattern, which includes details such as the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0065] Step 9:

[0066] The server also simulates future hairstyles, for example, predicting what a long bob will look like in three months' time and generating a synthetic image of it.

[0067] Step 10:

[0068] The server transmits the generated haircut recipe and a future hairstyle simulation image to the terminal.

[0069] Step 11:

[0070] The terminal displays the haircut recipe and the future hairstyle simulation received from the server to the user, who can then show the haircut recipe to the hairdresser and provide specific instructions.

[0071] Example 1

[0072] 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."

[0073] With conventional systems, it was difficult for users to communicate their desired hairstyle in detail to the hairdresser, resulting in the hairstyle often not being exactly what they wanted.In addition, the process of selecting the hairstyle that best suits the user's face shape and characteristics was complicated, time-consuming, and laborious.

[0074] 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.

[0075] In this invention, the server includes means for analyzing the received facial image and recognizing facial features and hairstyle information, means for generating multiple hairstyle patterns using a generative AI model based on the analyzed data, and means for combining the generated hairstyle patterns with the facial image and transmitting them to the terminal. This allows the user to visually simulate a desired hairstyle in advance and to provide specific instructions to the hairdresser based on a detailed haircut recipe.

[0076] "User" refers to an individual who utilizes the system to simulate their own hairstyle.

[0077] "Terminal" refers to the electronic device that a User uses to access the System, upload images, and view results.

[0078] "Facial images" refer to digital images of a user's face taken from multiple angles.

[0079] "Server" refers to a computer system that analyzes received image data and generates hairstyle patterns using a generative AI model.

[0080] "Feature points" refer to important points in a facial image, such as the eyes, nose, mouth, and contours.

[0081] "Hairstyle information" refers to data regarding the style and color of a user's current hairstyle.

[0082] A "generative AI model" refers to an algorithm that generates hairstyle patterns that naturally fit the user's face based on learned data.

[0083] "Hairstyle patterns" refer to multiple hairstyle variations generated by a generative AI model.

[0084] A "haircut recipe" refers to detailed instructions for a hairdresser to perform a specific cut and color based on the selected hairstyle.

[0085] "Future hairstyle simulation" refers to an image that predicts the future shape and state of the hairstyle selected by the user.

[0086] This invention is a system that allows users to accurately communicate their desired hairstyle to their hairdresser. The system allows users to upload facial images taken from multiple angles, and uses AI technology to generate and display various hairstyle patterns for those facial images, and provides a specific haircut recipe based on the hairstyle pattern that the user is satisfied with.

[0087] First, the user accesses the system using a terminal and uploads facial images taken from the front, side, and back of the head. Following the instructions displayed on the screen, the user clicks the file selection button to select the image file, and then presses the send button to send the image to the system.

[0088] The device temporarily stores the uploaded facial image and then sends it to the server using the HTTP POST method with the REST API. The server analyzes the received facial image and uses face detection algorithms such as OpenCV or Dlib to recognize facial features (eyes, nose, mouth, contours, etc.) and current hairstyle information (shape and color).

[0089] After the analysis is complete, the server uses a generative AI model (e.g., GAN or DCGAN) based on the analyzed data to generate multiple hairstyle patterns. These AI models are trained in advance with a large amount of hairstyle data and synthesize hairstyles that fit the user's face naturally. An example of a prompt is, "Please generate hairstyles such as short hair, bob, and perm that suit the user's face."

[0090] The generated hairstyle pattern is saved on the server and simultaneously composited onto the user's face image. The composite image is generated using an image processing library (e.g., PIL or OpenCV) and saved as multiple image files. These files are saved with names such as "shorthair.png" and "bob.png."

[0091] Once the composite image is complete, the server sends it to the device, which then displays a list of the received hairstyle patterns for the user to easily review. The user can then select the hairstyle they like best from the displayed patterns.

[0092] After the user selects the desired hairstyle, the device sends that information to the server. The server then generates a specific haircut recipe based on the selected hairstyle. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The server also performs future hairstyle simulations, generating a composite image of what the long bob will look like in three months, for example.

[0093] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then take this information to the hair salon and provide specific instructions to the hairdresser.

[0094] As a specific example, User A uploads three images of his face - one from the front, one from the side, and one from the back of his head - and the server generates ten different hairstyle patterns. User A selects a bob style from the images, and the server generates a haircut recipe based on that selection, including the length of the bangs and the amount of hair on the sides. In addition, a simulated image of a long bob three months from now is also provided. User A can show this information to a hairdresser to achieve the desired hairstyle.

[0095] An example of a prompt sentence could be, "Generate an appropriate hairstyle pattern based on multiple face images provided by the user. For example, generate variations such as short hair, long hair, bob, perm, etc., and combine them naturally with the user's face."

[0096] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0097] Step 1:

[0098] The user accesses the system using a terminal and uploads facial images taken from the front, side, and back of the head. The user follows the on-screen instructions, clicks the file selection button, and selects the image file. Then, clicks the send button to send the facial image to the system. The input is the image file uploaded by the user, and the output is the data of the image file sent to the server.

[0099] Step 2:

[0100] The device temporarily saves the image file selected by the user. Then, it issues an HTTP request to send the saved image file to the server. Specifically, the device uses the REST API to send the image data to the server using the POST method. The input is the temporarily saved image file, and the output is the HTTP request sent to the server.

[0101] Step 3:

[0102] The server begins processing the received image file. Specifically, it first identifies the face region from the image using a face detection algorithm (e.g., OpenCV or Dlib). Next, it detects facial feature points (eyes, nose, mouth, face contours, etc.) with high accuracy. It also analyzes the shape and color of the current hairstyle. The input is the received face image, and the output is the analyzed facial feature point data and hairstyle information.

[0103] Step 4:

[0104] The server generates multiple hairstyle patterns using a generative AI model (e.g., GAN or DCGAN) based on the analyzed data. The AI ​​model is trained in advance with a large amount of hairstyle data and synthesizes a hairstyle that fits the user's face naturally. An example of a prompt is "Please generate hairstyles such as short hair, bob, and perm that suit the user's face." The input is the analyzed facial feature point data and the prompt, and the output is the generated multiple hairstyle patterns.

[0105] Step 5:

[0106] The server composites the generated hairstyle pattern onto the user's face image. This composite process uses an image processing library (e.g., PIL, OpenCV). The composite results are generated as multiple image files and saved on the server. Each file is saved with a name such as "shorthair.png" or "bob.png." The input is the generated hairstyle pattern and the user's face image, and the output is an image file of the composite hairstyle pattern.

[0107] Step 6:

[0108] The server sends the image files of the synthesized hairstyle patterns to the device. The device displays the received images on the application's UI so that the user can check them. Specifically, it displays a list in thumbnail format from which the user can select each hairstyle pattern. The input is the image files of the hairstyle patterns received from the server, and the output is multiple hairstyle patterns displayed on the UI.

[0109] Step 7:

[0110] The user checks the displayed hairstyle patterns and selects the hairstyle they like best. After selection, the terminal sends information about the selected hairstyle pattern to the server. The input is the hairstyle pattern selected by the user, and the output is the selection information sent to the server.

[0111] Step 8:

[0112] The server generates a specific haircut recipe based on the selected hairstyle pattern. The haircut recipe includes details such as bang length, side volume, and coloring instructions. These instructions are created using a dedicated template. The input is the user-selected hairstyle pattern, and the output is the generated haircut recipe.

[0113] Step 9:

[0114] The server performs a future hairstyle simulation. For example, to generate a composite image of what a long bob will look like three months from now, the generative AI model is used again. The simulation results are generated as an image file and saved on the server. The input is the hairstyle pattern selected by the user and the future simulation period, and the output is a composite future hairstyle simulation image.

[0115] Step 10:

[0116] The server sends the generated haircut recipe and a future hairstyle simulation image to the terminal, which displays it to the user, who can then take it to the hair salon. The input is the haircut recipe and simulation image received from the server, and the output is the haircut recipe and simulation image displayed to the user.

[0117] (Application example 1)

[0118] 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."

[0119] Conventional hairstyle simulation systems make it difficult for users to actually see the hairstyle they want. It's also difficult for users to communicate their specific hairstyle image to the hairdresser, resulting in the hair often not turning out as desired. Furthermore, since it's not possible to try out multiple hairstyle patterns in real time, selecting the optimal hairstyle takes time. There is a need for a system that solves these problems, allowing users to see multiple hairstyle patterns in real time in a virtual reality space and present specific haircut recipes to the hairdresser.

[0120] 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.

[0121] In this invention, the server includes: means for uploading facial images taken from multiple angles by the user; means for analyzing the received facial images by the server and recognizing facial features and hairstyle information; means for the server to use a generated AI model to synthesize multiple hairstyle patterns and display them naturally on the user's facial image; means for the server to use a display device to allow the user to check hairstyle patterns in real time in a virtual reality space; means for the terminal to display multiple hairstyle patterns to the user; means for the user to select a hairstyle pattern desired by the user; means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern; and means for the terminal to display the generated haircut recipe and future hairstyle simulation to the user. This allows the user to check multiple hairstyles in real time in the virtual reality space, making it easier for the user to select the optimal hairstyle and also enabling the user to accurately give specific haircut instructions to the hairdresser.

[0122] A "user" is an individual who uses the system to perform a hairstyle simulation.

[0123] "Facial images taken from multiple angles" are photographs of the user's face taken from different angles, such as from the front, side, or back of the head.

[0124] A "server" is a computer system that analyzes data via the Internet and generates and provides hairstyle patterns.

[0125] "Facial feature points" refer to the main parts of the face, such as the eyes, nose, mouth, and contours, and are points used to analyze their position and shape.

[0126] "Hairstyle information" is data relating to the characteristics of the user's hair, such as the shape and color of the current hairstyle.

[0127] A "generative AI model" is an artificial intelligence model that generates new hairstyles based on learned data.

[0128] A "hairstyle pattern" is a variation of a different hairstyle that is composited onto the user's face.

[0129] A "virtual reality space" is a computer-generated 3D virtual environment that users experience using a VR head-mounted display or similar device.

[0130] A "display device" is a device for checking hairstyle patterns in real time within a virtual reality space, such as a VR head-mounted display.

[0131] A "terminal" is a device such as a computer or smartphone that a user uses to operate the system.

[0132] A "haircut recipe" is information detailing specific instructions for a hairdresser to perform a haircut based on a selected hairstyle pattern.

[0133] A "future hairstyle simulation" is a composite image that predicts the growth and changes in hairstyle over the next few months, for example, and allows the user to check it in advance.

[0134] The present invention is a system that allows a user to accurately communicate their desired hairstyle to a hairdresser, and in particular provides a real-time hairstyle simulation in a virtual reality space. A method for implementing this will be described in detail below.

[0135] First, the user uses facial images taken from multiple angles, including the front, side, and back of the head, and uploads these facial images to the system using a terminal. Specifically, the user follows the instructions to select an image file and send it to the system.

[0136] Next, the device temporarily saves the facial image file selected by the user and then sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. In particular, it identifies important points such as the eyes, nose, mouth, and face shape. It also analyzes the current hairstyle shape and color.

[0137] The server then uses a generative AI model based on the analyzed data to generate multiple hairstyle patterns. The generative AI model synthesizes a natural hairstyle that suits the user's face based on the trained data. For example, it generates different variations such as short hair, long hair, bob, and perm.

[0138] The server then synthesizes the generated hairstyle patterns onto the user's facial image, allowing the user to view these synthesized images in real time in a virtual reality space.The user can use a VR head-mounted display (e.g., Oculus Rift) to view the hairstyle patterns in the virtual reality space and select the hairstyle that best suits them by changing their movements and viewpoints.

[0139] The user sends the hairstyle pattern they have selected to the server via their terminal. Based on this selection, the server generates a specific haircut recipe. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also performs a simulation of the future hairstyle, displaying a composite image of what the long bob will look like in three months, for example.

[0140] The generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can bring this haircut recipe to the salon and provide specific instructions to the hairdresser. For example, User A uploads three images of his face - from the front, side, and back of the head - and the server generates 10 hairstyle patterns. User A selects a bob style from these, and based on this selection, the server generates a haircut recipe specifying the length of the bangs, the amount of hair on the sides, and other factors. In addition, a simulation image of a long bob three months from now is also provided. User A can show this information to the hairdresser to achieve the specific hairstyle.

[0141] An example prompt has the following format:

[0142] Use the detailed facial image data below to generate 10 hairstyle patterns that best suit the user.

[0143] Image data: [URL of user's face photo (front, side, back)]

[0144] Facial features: [Analysis results of eyes, nose, mouth, face, etc.]

[0145] Current hairstyle: [shape and color]

[0146] This system allows users to simulate their desired hairstyle in advance in a virtual reality space, and based on the results, they can provide detailed instructions to their hairdresser.

[0147] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0148] Step 1:

[0149] The user takes facial images from multiple angles and uploads them to the system using a terminal. Here, the user inputs facial images from multiple angles, such as the front, side, and back of the head. The terminal temporarily stores these image files and then sends them to the server. The input data in this case are facial image files, and the output is the transmission of image files to the server.

[0150] Step 2:

[0151] The server analyzes the received facial image and recognizes facial feature points and hairstyle information. Specifically, it identifies important points such as the eyes, nose, mouth, and face shape, and also analyzes the current hairstyle shape and color. The input for this process is the facial image sent from the device, and the output is data on facial feature points and hairstyle information.

[0152] Step 3:

[0153] The server uses a generative AI model to generate multiple hairstyle patterns based on the analyzed facial features and hairstyle information. The generative AI model uses the trained data to synthesize a natural hairstyle that suits the user's face. The input for this process is the analyzed data, and the output is multiple hairstyle patterns.

[0154] Step 4:

[0155] The server synthesizes the generated hairstyle pattern with the user's facial image to generate a composite image. These composite images are intended for the user to view in a virtual reality space. The inputs to this process are the hairstyle pattern and the user's facial image, and the output is the composite image.

[0156] Step 5:

[0157] The user wears a VR head-mounted display and checks multiple hairstyle patterns in real time within a virtual reality space. Specifically, the user can change their viewpoint within the virtual space and freely rotate the hairstyle to check it. The input for this process is a composite image sent from the server, and the output is the user's hairstyle selection information.

[0158] Step 6:

[0159] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server. The input of this process is the user's hairstyle selection information, and the output is the transmission of the selection information to the server.

[0160] Step 7:

[0161] The server generates a specific haircut recipe based on the selected hairstyle pattern. A haircut recipe typically includes information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The server also simulates the future hairstyle, displaying a composite image of what the hair will look like three months from now. The input for this process is the user's hairstyle selection information, and the output is a specific haircut recipe and a simulated image of the future hairstyle.

[0162] Step 8:

[0163] The server sends the generated haircut recipe and a simulation image of the future hairstyle to the terminal. The terminal displays this to the user, who can then take the haircut recipe to the salon and give specific instructions to the hairdresser. The input of this process is the haircut recipe and simulation image sent from the server, and the output is the display to the user.

[0164] 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.

[0165] The present invention is a system that allows a user to accurately communicate the hairstyle they desire to a hairdresser and further suggests an appropriate hairstyle taking the user's feelings into consideration, and an embodiment of this system will be described below.

[0166] First, the user accesses the system using a terminal. The user takes and uploads facial images of the front, side, and back of the head. The user follows the instructions to select the image file and send it to the server.

[0167] The device temporarily saves the facial image file selected by the user and sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. It then uses an emotion engine to analyze the user's emotions from the facial image. Specifically, it detects facial expressions and subtle changes and determines the emotion.

[0168] Based on the analysis results, the emotion engine quantifies the user's current emotional state and inputs that information into a generative AI model. The server then uses the generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. Depending on the emotion, different variations are generated, such as short hair, long hair, bob, and perm.

[0169] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way and saves each pattern as an image file. These synthesized images are sent from the server to the terminal, which then displays a list of hairstyle patterns to the user. The user can then review the displayed hairstyle patterns and select the hairstyle they like best.

[0170] When the user selects the hairstyle they want, the device sends the selection information to the server. The server then generates a specific haircut recipe based on the user's selection and the analysis results of the emotion engine. This haircut recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also simulates future hairstyles based on the user's emotion data, predicting what the hairstyle will look like three months from now, for example, and generating a composite image.

[0171] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then bring this haircut recipe to the hair salon and provide specific instructions to the hairdresser.

[0172] As a specific example, if User A uploads facial images of the front, side, and back of the head, and the emotion engine analyzes this as an "excited state," the server will use the generative AI model to prioritize suggestions for short hair and bright colors that give a lively impression. User A selects a bob style from the list, and the server generates a haircut recipe based on that selection and emotion data, including the length of the bangs and the amount of hair on the sides. Furthermore, a simulation of the hairstyle three months from now is provided, predicting changes in emotions.

[0173] In this way, by using the present invention, the user can easily select the optimal hairstyle based on their emotions and accurately convey specific instructions to the hairdresser.

[0174] The processing flow will be explained below.

[0175] Step 1:

[0176] Users access the system using a terminal, take front, side, and back images of their face, and upload them to the system.

[0177] Step 2:

[0178] The device temporarily stores the facial image files uploaded by the user, displays a confirmation message indicating that the upload is complete, and then transmits the facial image files to the server.

[0179] Step 3:

[0180] The server analyzes the received facial image. Specifically, it detects facial features (eyes, nose, mouth, contours, etc.) and identifies their positions. It also analyzes the shape and color of the hairstyle.

[0181] Step 4:

[0182] The server uses an emotion engine to recognize emotions from the user's facial image. The emotion engine detects facial expressions and subtle changes and quantifies the user's emotional state. For example, it identifies emotions such as joy, sadness, excitement, and calmness.

[0183] Step 5:

[0184] The server inputs the analyzed facial feature points and emotional data into a generative AI model, which then synthesizes a natural hairstyle that matches the user's face based on the learned data. Depending on the emotional data, different variations such as short hair, long hair, bob, and perm are generated.

[0185] Step 6:

[0186] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way, saves each pattern as an image file, and transmits the synthesized images to the terminal.

[0187] Step 7:

[0188] The terminal displays the list of hairstyle patterns received from the server to the user, who then checks the displayed multiple hairstyle patterns and selects the hairstyle that he or she likes best.

[0189] Step 8:

[0190] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server.

[0191] Step 9:

[0192] The server generates a specific haircut recipe based on the selected hairstyle pattern and emotion data, which includes details such as the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0193] Step 10:

[0194] The server also simulates future hairstyles, for example, predicting what a long bob will look like in three months' time and generating a synthetic image of it.

[0195] Step 11:

[0196] The server transmits the generated haircut recipe and a future hairstyle simulation image to the terminal.

[0197] Step 12:

[0198] The terminal displays the haircut recipe and the future hairstyle simulation received from the server to the user, who can then show the haircut recipe to the hairdresser and provide specific instructions.

[0199] As a specific example, if User A uploads facial images of the front, side, and back of the head, and the emotion engine analyzes this as an "excited state," the server will use the generative AI model to prioritize suggestions for short hair and bright colors that give a lively impression. User A selects a bob style from the list, and the server generates a haircut recipe based on that selection and emotion data, including the length of the bangs and the amount of hair on the sides. Furthermore, a simulation of the hairstyle three months from now is provided, predicting changes in emotions.

[0200] In this way, by using the present invention, the user can easily select the optimal hairstyle based on their emotions and accurately convey specific instructions to the hairdresser.

[0201] Example 2

[0202] 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."

[0203] In conventional hair style suggestion systems at beauty salons, it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, and the system does not consider the user's emotional state when proposing a hairstyle, resulting in a hairstyle that is unsatisfying. The present invention aims to improve user satisfaction by enabling users to accurately communicate their desired hairstyle and by proposing an optimal hairstyle that takes the user's emotions into consideration.

[0204] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0205] In this invention, the server includes means for uploading facial images taken from multiple angles by the user, means for the terminal to temporarily store the image files and send them to the server, means for the server to analyze the received facial images and recognize facial features and emotions, means for the server to use a generative AI model to generate and display multiple hairstyle patterns based on the emotion data and the user's facial image, means for the terminal to display the multiple hairstyle patterns to the user, means for the user to select a hairstyle pattern desired by the server, means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern, and means for the terminal to display the generated haircut recipe and future hairstyle simulation to the user. This makes it possible to suggest an optimal hairstyle based on the user's emotions and generate a specific haircut recipe.

[0206] "Facial image" refers to an image file that shows the user's face from the front, side, or back of the head.

[0207] "Device" refers to a computing device used by a user, such as a smartphone, PC, or tablet.

[0208] "Server" refers to the central processing unit that processes information received from users and generates and transmits necessary data.

[0209] "Feature points" refer to the positional information of specific parts of the face, such as the facial contours, eyes, nose, and mouth.

[0210] "Emotion" refers to the psychological state that can be analyzed from the user's facial expressions and subtle changes.

[0211] "Generative AI model" refers to an artificial intelligence model that generates hairstyle patterns using machine learning algorithms.

[0212] "Hairstyle patterns" refers to multiple different hairstyle designs created by a generative AI model.

[0213] A "haircut recipe" refers to a document that details specific treatment methods and instructions based on a hairstyle pattern.

[0214] "Future hairstyle simulation" refers to a technology that predicts what a user's hairstyle will look like after a certain period of time and displays it as a composite image.

[0215] The present invention is a system that allows a user to accurately communicate the hairstyle they want to a hairdresser and further suggests an appropriate hairstyle taking the user's feelings into consideration. An embodiment of the system will be described below.

[0216] First, the user accesses the system's webpage on their device (such as a smartphone or PC). This webpage provides an interface for users to upload facial images. The user takes a picture of their face from the front, side, or back of the head, and clicks the "Upload" button to send the selected image file to the system.

[0217] The device temporarily stores the facial image file selected by the user in local storage. The stored image file is sent to the server as an HTTP POST request using JavaScript (registered trademark). This communication is asynchronous, using an Ajax library (e.g., jQuery).

[0218] The server passes the received facial images to an analysis program written in Python. OpenCV and Dlib libraries are used for facial analysis, which detects facial features and recognizes emotions by analyzing facial expressions and subtle changes in the facial images. Emotion recognition uses a cloud service's emotion analysis API (for example, Azure (registered trademark) emotion analysis API). The results of the emotion analysis are extracted as numerical data.

[0219] The server inputs this quantified emotional data into a generative AI model (such as StyleGAN). The generative AI model is built using deep learning frameworks such as TENSORFLOW (registered trademark) and PyTorch, and generates multiple hairstyle patterns to be synthesized onto the user's face based on the emotional data and facial images. In this process, an appropriate prompt sentence is input into the AI ​​model. An example of a prompt sentence is, "The user's emotional state is excited. Generate a hairstyle pattern with a short hair style or a bright color that gives a lively impression."

[0220] The generated hairstyle patterns are naturally combined with the facial image and saved as an image file. These combined images are sent from the server to the device as an HTTP response. The device's browser displays a list of the received hairstyle pattern images, allowing the user to select the desired hairstyle from multiple options.

[0221] When a user selects a specific hairstyle pattern, that information is sent from the device to the server. The server generates a specific haircut recipe based on the selected hairstyle pattern and emotional data. The haircut recipe includes detailed instructions on the length of the bangs, the amount of hair on the sides, and coloring. Furthermore, a future hairstyle simulation is performed, and an image of the predicted hairstyle three months from now is generated.

[0222] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user, who can then print or download the haircut recipe and bring it to the hair salon to provide specific hairstyle instructions to the hairdresser.

[0223] In this way, by using the present invention, the user can select the hairstyle that best suits his / her emotions and face, while providing accurate beauty instructions to the hairdresser.

[0224] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0225] Step 1:

[0226] A user accesses the system and uploads a facial image.

[0227] Users access the system's web page using a device such as a smartphone or PC. They click the "Upload Face Image" button on the web page, select a face image from the front, side, or back of the head, and upload it. At this time, the input data is the user's face image file, and the output is a message indicating successful file upload. Specifically, an image file is selected using an HTML form, and the image upload process is carried out using JavaScript.

[0228] Step 2:

[0229] The device temporarily saves the image file and sends it to the server.

[0230] The facial image file is temporarily saved in the device's local storage. After saving, an HTTP POST request is created using the Ajax library, and the image file is sent to the server. At this time, the input data is the saved image file, and the output is the file sent to the server. Specifically, asynchronous communication is performed using JavaScript and Ajax.

[0231] Step 3:

[0232] The server analyzes the facial image and recognizes the features and emotions.

[0233] The server passes the received facial images to an analysis program written in Python. It uses Python's OpenCV and Dlib libraries to detect facial feature points (eyes, nose, mouth, etc.). Based on this feature point data, it uses Azure's emotion analysis API to analyze the user's emotions from their facial expressions. The input data is the user's facial image, and the output is feature point data and emotion data. Specific operations include image preprocessing (resizing, grayscale conversion), feature point extraction, and making requests to the cloud API.

[0234] Step 4:

[0235] The server inputs the emotion data into the AI ​​model to generate a hairstyle pattern.

[0236] The results of the sentiment analysis are quantified and input into a generative AI model built using Python's TensorFlow or PyTorch. The generative AI model (for example, StyleGAN) generates multiple hairstyle patterns based on the input data. In this process, an appropriate prompt sentence is input into the AI ​​model. The input data is feature point data and emotion data, and the output is multiple hairstyle pattern images. Specifically, the emotion data is quantified, input into the AI ​​model, and hairstyle patterns are generated.

[0237] Step 5:

[0238] The server synthesizes the generated hairstyle pattern and sends it to the device.

[0239] The generated hairstyle pattern is composited with the user's facial image and output in a natural way. The composite image is saved on the server and sent to the device as an HTTP response. The input data is the generated hairstyle pattern and the user's facial image, and the output is a composite image file. A Python image processing library is used for the composite.

[0240] Step 6:

[0241] The device displays hairstyle patterns to the user.

[0242] The device's browser displays a list of composite images received from the server. Using HTML, CSS, and JavaScript, the images are displayed in a format that is easy for the user to view. The input data is the composite image file sent from the server, and the output is a list of hairstyles that is displayed to the user. Specifically, the images are loaded and displayed.

[0243] Step 7:

[0244] The user selects the desired hairstyle.

[0245] The user selects the desired hairstyle pattern by clicking on it from the displayed patterns. Information on the selected hairstyle pattern is sent from the device to the server. The input data is the ID of the hairstyle pattern clicked by the user, and the output is the transmission of the selected information to the server. Specific operations include processing the click event using JavaScript and sending data.

[0246] Step 8:

[0247] The device sends the selection information to the server

[0248] The device sends data including the ID of the selected image to the server as an HTTP POST request. The input data is the ID of the selected image, and the output is a message to the server indicating that the request was sent successfully. Specifically, asynchronous communication is performed using Ajax.

[0249] Step 9:

[0250] The server generates a haircut recipe and a simulation of the future hairstyle.

[0251] The server generates a specific haircut recipe (bangs length, amount of hair on the sides, coloring instructions, etc.) based on the selected hairstyle pattern and emotional data. It also performs a future hairstyle simulation and generates a predicted hairstyle three months from now. The input data is the selected hairstyle pattern and emotional data, and the output is a haircut recipe and predicted hairstyle image. Specifically, data analysis and model inference processing are performed.

[0252] Step 10:

[0253] Send the results generated by the server to the device

[0254] The generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal as an HTTP response. The input data are the haircut recipe and simulation image, and the output is the response sent to the terminal. Specifically, data packaging and HTTP transmission processing are performed.

[0255] Step 11:

[0256] The device displays the results to the user

[0257] The terminal displays the received cutting recipe and simulation image to the user. It uses HTML and JavaScript to provide an interface that the user can easily check. The input data is the cutting recipe and simulation image received from the server, and the output is what is displayed to the user. Specifically, data loading and display processing are carried out.

[0258] (Application example 2)

[0259] 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."

[0260] In conventional hair styling suggestion systems at hair salons, the desired hairstyle image often does not match between the user and the hairdresser, resulting in a decrease in user satisfaction. Furthermore, there was no system that could analyze the user's emotions from a facial image and suggest the optimal hairstyle based on that. This made it difficult to suggest a hairstyle that matched the user's mood and preferences at the time, which further led to dissatisfaction.

[0261] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for taking and uploading a facial image of a customer using a tablet or smartphone, means for analyzing emotions from the facial image and generating a hairstyle pattern based on the emotion, and means for displaying the generated hairstyle pattern to the customer. This makes it possible to suggest a hairstyle that is suited to the user's current emotional state, thereby improving user satisfaction.

[0262] A "user" is an individual who uses the hairstyle suggestion system.

[0263] A "face image" is a photograph of the user's face taken from multiple angles, such as the front, side, and back of the head.

[0264] The "server" is a computer on the network that receives and analyzes data and generates hairstyle patterns using a generative AI model.

[0265] A "generative AI model" is an artificial intelligence technology that generates hairstyle patterns based on a user's facial image and emotional data.

[0266] "Hairstyle patterns" are digital images of different types of hairstyles that are composited onto the user's facial image.

[0267] A "terminal" is a hardware device such as a tablet or smartphone that is operated by a user.

[0268] "Emotion" refers to the psychological state of the user that is analyzed from a facial image, and the analysis results are used to suggest hairstyles.

[0269] A "cut recipe" is a set of specific instructions for a hairstyle, including the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0270] A "future hairstyle simulation" is a digital image that predicts how a user's hairstyle will change over time.

[0271] A specific embodiment for carrying out this invention will be described below. First, a user accesses the system using a tablet or smartphone installed in a beauty salon. The user takes facial images of the front, side, and back of the head and uploads them to the system.

[0272] The hardware used is a tablet or smartphone camera, and the software is an application for capturing and uploading facial images. The system temporarily stores the facial image file selected by the user and sends it to a server.

[0273] The server analyzes the received facial image and recognizes facial features and hairstyle information. It also uses an emotion engine to analyze the user's emotions from the facial image. Specifically, it detects facial expressions and subtle changes and determines the emotion. The software used includes OpenCV (facial image analysis) and Keras (emotion engine).

[0274] Next, the server uses the generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. Different variations such as short hair, long hair, bob, and perm are generated depending on the emotion. These hairstyle patterns are naturally combined with the user's facial image, and each pattern is saved as an image file. This is what the generative AI model is used for.

[0275] The server sends the generated hairstyle patterns to a tablet or smartphone, which then displays them to the user. The user can then review the displayed hairstyle patterns and select the one they like best. The device then sends the selection information to the server.

[0276] The server generates a specific haircut recipe based on the hairstyle pattern selected by the user and the results of emotion analysis. This haircut recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also performs a simulation of future hairstyles, predicting what the hairstyle will look like three months from now, for example, and generates a composite image. This allows the user to receive a haircut at the salon that takes future hairstyles into consideration.

[0277] As a specific example, if user A takes a picture of his face with a tablet and the facial image is analyzed by the emotion engine as being in a "relaxed state," the server will use the generative AI model to preferentially suggest hairstyle patterns that give a calm impression. An example of a prompt sentence in this case is as follows:

[0278] "Input the user's facial image into an emotion engine and generative AI model to suggest hairstyle patterns that suit their relaxed state."

[0279] This allows the user to be suggested a hairstyle that is best suited to their current psychological state, improving satisfaction at the beauty salon.

[0280] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0281] Step 1:

[0282] First, the user accesses the system using a tablet or smartphone installed in the beauty salon. The user takes facial images of the front, side, and back of the head and uploads them to the system. The input is the facial image taken by the user, and the output is the uploaded facial image data. Specifically, the user takes a facial image using the camera application on the tablet or smartphone and sends it to the server.

[0283] Step 2:

[0284] The device temporarily stores the facial image file selected by the user and sends it to the server. The input is the facial image taken and uploaded by the user, and the output is the facial image data sent to the server. Specifically, the device transfers the temporarily stored image file to the server via an HTTP request.

[0285] Step 3:

[0286] The server analyzes the received facial image and recognizes facial feature points and hairstyle information. The input is the facial image data sent to the server, and the output is the analyzed facial feature point data and hairstyle information.

[0287] Specifically, it uses OpenCV to analyze facial images, extract feature points for each part of the face, recognize the shape and contours of the face, and extract information about the current hairstyle.

[0288] Step 4:

[0289] The server uses an emotion engine to analyze emotions from the user's facial image. The input is analyzed facial feature point data, and the output is analyzed emotion data. Specifically, the emotion engine using Keras is used to analyze emotions from facial expressions, and the results are obtained as numerical data.

[0290] Step 5:

[0291] The server uses a generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. The input is the user's facial image and analyzed emotional data, and the output is multiple generated hairstyle patterns. Specifically, a prompt sentence is generated based on the emotional data, and this is input into the generative AI model to automatically generate a hairstyle pattern that matches the emotion.

[0292] Step 6:

[0293] The server synthesizes the generated hairstyle pattern onto the user's facial image in a natural way and saves each pattern as an image file. The input is the user's facial image and the generated hairstyle pattern, and the output is an image file of the synthesized hairstyle pattern. Specifically, the server uses a synthesis algorithm to superimpose the generated hairstyle pattern onto the user's facial image.

[0294] Step 7:

[0295] The server sends the generated hairstyle patterns to a tablet or smartphone, and the device displays them as a list. The input is an image file of the synthesized hairstyle pattern, and the output is a list of hairstyle patterns displayed on the device. Specifically, the image file of the hairstyle pattern is sent to the device as an HTTP response, and the display application renders it.

[0296] Step 8:

[0297] The user checks the displayed hairstyle patterns and selects the hairstyle they like best. The input is the displayed hairstyle patterns, and the output is the information on the hairstyle pattern selected by the user. Specifically, the user selects the desired hairstyle using touch operations or selection buttons.

[0298] Step 9:

[0299] The terminal sends the user's selection information to the server. The input is the hairstyle pattern information selected by the user, and the output is the selection information sent to the server. Specifically, the user's selection information is transmitted to the server as an HTTP request.

[0300] Step 10:

[0301] The server generates a specific haircut recipe based on the hairstyle pattern selected by the user and the emotion analysis results. The input is the information on the selected hairstyle pattern and emotion data, and the output is a specific haircut recipe. Specifically, the server automatically generates a haircut recipe that includes the length of the bangs, the amount of hair on the sides, coloring instructions, etc.

[0302] Step 11:

[0303] The server also simulates future hairstyles, predicting what the user's hairstyle will look like in three months, for example, and generates a synthetic image. The input is the user's hairstyle pattern and predicted growth data, and the output is a simulated image of the future hairstyle. Specifically, the server predicts the future hairstyle using an algorithm that simulates hair growth.

[0304] Step 12:

[0305] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which then displays them to the user. The input is the haircut recipe and future hairstyle simulation image, and the output is the information displayed on the terminal. Specifically, the haircut recipe and simulation image are sent as an HTTP response, and the terminal presents them to the user using an application that displays them.

[0306] Through the above processing steps, the user is suggested a hairstyle that suits their current psychological state, improving their satisfaction at the beauty salon.

[0307] 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.

[0308] 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.

[0309] 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.

[0310] [Second embodiment]

[0311] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0312] 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.

[0313] 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).

[0314] 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.

[0315] 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.

[0316] 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).

[0317] 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. 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.

[0318] 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.

[0319] 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.

[0320] 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.

[0321] 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.

[0322] 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."

[0323] The present invention is a system for allowing a user to accurately communicate a desired hairstyle to a hairdresser, and can be implemented as follows.

[0324] First, the user accesses the system using a terminal and uploads facial images taken from multiple angles, such as the front, side, and back of the head. The user then follows the instructions to select the image file and send it to the system.

[0325] Next, the device temporarily saves the image file selected by the user and then sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. Specifically, it identifies important points such as the eyes, nose, mouth, and face shape, and also analyzes the current hairstyle shape and color.

[0326] The server then uses a generative AI model based on the analyzed data to generate multiple hairstyle patterns. The generative AI model synthesizes a natural hairstyle that suits the user's face based on the trained data. For example, different variations such as short hair, long hair, bob, and perm are generated.

[0327] The server then combines the generated hairstyle patterns with the user's facial image, saves each pattern as an image, and transmits the combined image to the terminal.

[0328] The terminal displays the list of hairstyle patterns received from the server to the user, who can then check the displayed hairstyle patterns and select the hairstyle that he or she likes best.

[0329] When the user selects the desired hairstyle, the device sends that information to the server. The server then generates a specific haircut recipe based on the selected hairstyle. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The device also simulates future hairstyles, displaying a composite image of what a long bob will look like in three months.

[0330] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then bring this haircut recipe to the hair salon and provide specific instructions to the hairdresser.

[0331] As a specific example, User A uploads three images of his face - one from the front, one from the side, and one from the back of his head - and the server generates ten different hairstyle patterns. User A selects a bob style from the images, and the server generates a haircut recipe based on that selection, including the length of the bangs and the amount of hair on the sides. In addition, a simulated image of a long bob three months from now is also provided. User A can show this information to a hairdresser to achieve the desired hairstyle.

[0332] In this way, by using the present invention, the user can simulate the hairstyle they want in advance and, based on the results, give detailed instructions to the hairdresser.

[0333] The processing flow will be explained below.

[0334] Step 1:

[0335] The user accesses the system using a terminal, takes three images of their face (front, side, and back of the head), and uploads each image to the system.

[0336] Step 2:

[0337] The device temporarily stores the facial image files uploaded by the user, displays a confirmation message indicating that the upload is complete, and then transmits the facial image files to the server.

[0338] Step 3:

[0339] The server analyzes the received facial image. Specifically, it detects facial features (eyes, nose, mouth, contours, etc.) and identifies their positions. It also analyzes the shape and color of the hairstyle.

[0340] Step 4:

[0341] The server uses a generative AI model based on the analysis results to generate multiple hairstyle patterns to be combined with the user's facial image. The generative AI model uses the learned data to create a natural hairstyle. Different variations such as short hair, long hair, bob, and perm are generated.

[0342] Step 5:

[0343] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way, saves each pattern as an image file, and transmits the synthesized images to the terminal.

[0344] Step 6:

[0345] The terminal displays the list of hairstyle patterns received from the server to the user, who then checks the displayed multiple hairstyle patterns and selects the hairstyle that he or she likes best.

[0346] Step 7:

[0347] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server.

[0348] Step 8:

[0349] The server generates a specific haircut recipe based on the selected hairstyle pattern, which includes details such as the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0350] Step 9:

[0351] The server also simulates future hairstyles, for example, predicting what a long bob will look like in three months' time and generating a synthetic image of it.

[0352] Step 10:

[0353] The server transmits the generated haircut recipe and a future hairstyle simulation image to the terminal.

[0354] Step 11:

[0355] The terminal displays the haircut recipe and the future hairstyle simulation received from the server to the user, who can then show the haircut recipe to the hairdresser and provide specific instructions.

[0356] Example 1

[0357] 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."

[0358] With conventional systems, it was difficult for users to communicate their desired hairstyle in detail to the hairdresser, resulting in the hairstyle often not being exactly what they wanted.In addition, the process of selecting the hairstyle that best suits the user's face shape and characteristics was complicated, time-consuming, and laborious.

[0359] 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.

[0360] In this invention, the server includes means for analyzing the received facial image and recognizing facial features and hairstyle information, means for generating multiple hairstyle patterns using a generative AI model based on the analyzed data, and means for combining the generated hairstyle patterns with the facial image and transmitting them to the terminal. This allows the user to visually simulate a desired hairstyle in advance and to provide specific instructions to the hairdresser based on a detailed haircut recipe.

[0361] "User" refers to an individual who utilizes the system to simulate their own hairstyle.

[0362] "Terminal" refers to the electronic device that a User uses to access the System, upload images, and view results.

[0363] "Facial images" refer to digital images of a user's face taken from multiple angles.

[0364] "Server" refers to a computer system that analyzes received image data and generates hairstyle patterns using a generative AI model.

[0365] "Feature points" refer to important points in a facial image, such as the eyes, nose, mouth, and contours.

[0366] "Hairstyle information" refers to data regarding the style and color of a user's current hairstyle.

[0367] A "generative AI model" refers to an algorithm that generates hairstyle patterns that naturally fit the user's face based on learned data.

[0368] "Hairstyle patterns" refer to multiple hairstyle variations generated by a generative AI model.

[0369] A "haircut recipe" refers to detailed instructions for a hairdresser to perform a specific cut and color based on the selected hairstyle.

[0370] "Future hairstyle simulation" refers to an image that predicts the future shape and state of the hairstyle selected by the user.

[0371] This invention is a system that allows users to accurately communicate their desired hairstyle to their hairdresser. The system allows users to upload facial images taken from multiple angles, and uses AI technology to generate and display various hairstyle patterns for those facial images, and provides a specific haircut recipe based on the hairstyle pattern that the user is satisfied with.

[0372] First, the user accesses the system using a terminal and uploads facial images taken from the front, side, and back of the head. Following the instructions displayed on the screen, the user clicks the file selection button to select the image file, and then presses the send button to send the image to the system.

[0373] The device temporarily stores the uploaded facial image and then sends it to the server using the HTTP POST method with the REST API. The server analyzes the received facial image and uses face detection algorithms such as OpenCV or Dlib to recognize facial features (eyes, nose, mouth, contours, etc.) and current hairstyle information (shape and color).

[0374] After the analysis is complete, the server uses a generative AI model (e.g., GAN or DCGAN) based on the analyzed data to generate multiple hairstyle patterns. These AI models are trained in advance with a large amount of hairstyle data and synthesize hairstyles that fit the user's face naturally. An example of a prompt is, "Please generate hairstyles such as short hair, bob, and perm that suit the user's face."

[0375] The generated hairstyle pattern is saved on the server and simultaneously composited onto the user's face image. The composite image is generated using an image processing library (e.g., PIL or OpenCV) and saved as multiple image files. These files are saved with names such as "shorthair.png" and "bob.png."

[0376] Once the composite image is complete, the server sends it to the device, which then displays a list of the received hairstyle patterns for the user to easily review. The user can then select the hairstyle they like best from the displayed patterns.

[0377] After the user selects the desired hairstyle, the device sends that information to the server. The server then generates a specific haircut recipe based on the selected hairstyle. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The server also performs future hairstyle simulations, generating a composite image of what the long bob will look like in three months, for example.

[0378] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then take this information to the hair salon and provide specific instructions to the hairdresser.

[0379] As a specific example, User A uploads three images of his face - one from the front, one from the side, and one from the back of his head - and the server generates ten different hairstyle patterns. User A selects a bob style from the images, and the server generates a haircut recipe based on that selection, including the length of the bangs and the amount of hair on the sides. In addition, a simulated image of a long bob three months from now is also provided. User A can show this information to a hairdresser to achieve the desired hairstyle.

[0380] An example of a prompt sentence could be, "Generate an appropriate hairstyle pattern based on multiple face images provided by the user. For example, generate variations such as short hair, long hair, bob, perm, etc., and combine them naturally with the user's face."

[0381] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0382] Step 1:

[0383] The user accesses the system using a terminal and uploads facial images taken from the front, side, and back of the head. The user follows the on-screen instructions, clicks the file selection button, and selects the image file. Then, clicks the send button to send the facial image to the system. The input is the image file uploaded by the user, and the output is the data of the image file sent to the server.

[0384] Step 2:

[0385] The device temporarily saves the image file selected by the user. Then, it issues an HTTP request to send the saved image file to the server. Specifically, the device uses the REST API to send the image data to the server using the POST method. The input is the temporarily saved image file, and the output is the HTTP request sent to the server.

[0386] Step 3:

[0387] The server begins processing the received image file. Specifically, it first identifies the face region from the image using a face detection algorithm (e.g., OpenCV or Dlib). Next, it detects facial feature points (eyes, nose, mouth, face contours, etc.) with high accuracy. It also analyzes the shape and color of the current hairstyle. The input is the received face image, and the output is the analyzed facial feature point data and hairstyle information.

[0388] Step 4:

[0389] The server generates multiple hairstyle patterns using a generative AI model (e.g., GAN or DCGAN) based on the analyzed data. The AI ​​model is trained in advance with a large amount of hairstyle data and synthesizes a hairstyle that fits the user's face naturally. An example of a prompt is "Please generate hairstyles such as short hair, bob, and perm that suit the user's face." The input is the analyzed facial feature point data and the prompt, and the output is the generated multiple hairstyle patterns.

[0390] Step 5:

[0391] The server composites the generated hairstyle pattern onto the user's face image. This composite process uses an image processing library (e.g., PIL, OpenCV). The composite results are generated as multiple image files and saved on the server. Each file is saved with a name such as "shorthair.png" or "bob.png." The input is the generated hairstyle pattern and the user's face image, and the output is an image file of the composite hairstyle pattern.

[0392] Step 6:

[0393] The server sends the image files of the synthesized hairstyle patterns to the device. The device displays the received images on the application's UI so that the user can check them. Specifically, it displays a list in thumbnail format from which the user can select each hairstyle pattern. The input is the image files of the hairstyle patterns received from the server, and the output is multiple hairstyle patterns displayed on the UI.

[0394] Step 7:

[0395] The user checks the displayed hairstyle patterns and selects the hairstyle they like best. After selection, the terminal sends information about the selected hairstyle pattern to the server. The input is the hairstyle pattern selected by the user, and the output is the selection information sent to the server.

[0396] Step 8:

[0397] The server generates a specific haircut recipe based on the selected hairstyle pattern. The haircut recipe includes details such as bang length, side volume, and coloring instructions. These instructions are created using a dedicated template. The input is the user-selected hairstyle pattern, and the output is the generated haircut recipe.

[0398] Step 9:

[0399] The server performs a future hairstyle simulation. For example, to generate a composite image of what a long bob will look like three months from now, the generative AI model is used again. The simulation results are generated as an image file and saved on the server. The input is the hairstyle pattern selected by the user and the future simulation period, and the output is a composite future hairstyle simulation image.

[0400] Step 10:

[0401] The server sends the generated haircut recipe and a future hairstyle simulation image to the terminal, which displays it to the user, who can then take it to the hair salon. The input is the haircut recipe and simulation image received from the server, and the output is the haircut recipe and simulation image displayed to the user.

[0402] (Application example 1)

[0403] 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."

[0404] Conventional hairstyle simulation systems make it difficult for users to actually see the hairstyle they want. It's also difficult for users to communicate their specific hairstyle image to the hairdresser, resulting in the hair often not turning out as desired. Furthermore, since it's not possible to try out multiple hairstyle patterns in real time, selecting the optimal hairstyle takes time. There is a need for a system that solves these problems, allowing users to see multiple hairstyle patterns in real time in a virtual reality space and present specific haircut recipes to the hairdresser.

[0405] 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.

[0406] In this invention, the server includes: means for uploading facial images taken from multiple angles by the user; means for analyzing the received facial images by the server and recognizing facial features and hairstyle information; means for the server to use a generated AI model to synthesize multiple hairstyle patterns and display them naturally on the user's facial image; means for the server to use a display device to allow the user to check hairstyle patterns in real time in a virtual reality space; means for the terminal to display multiple hairstyle patterns to the user; means for the user to select a hairstyle pattern desired by the user; means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern; and means for the terminal to display the generated haircut recipe and future hairstyle simulation to the user. This allows the user to check multiple hairstyles in real time in the virtual reality space, making it easier for the user to select the optimal hairstyle and also enabling the user to accurately give specific haircut instructions to the hairdresser.

[0407] A "user" is an individual who uses the system to perform a hairstyle simulation.

[0408] "Facial images taken from multiple angles" are photographs of the user's face taken from different angles, such as from the front, side, or back of the head.

[0409] A "server" is a computer system that analyzes data via the Internet and generates and provides hairstyle patterns.

[0410] "Facial feature points" refer to the main parts of the face, such as the eyes, nose, mouth, and contours, and are points used to analyze their position and shape.

[0411] "Hairstyle information" is data relating to the characteristics of the user's hair, such as the shape and color of the current hairstyle.

[0412] A "generative AI model" is an artificial intelligence model that generates new hairstyles based on learned data.

[0413] A "hairstyle pattern" is a variation of a different hairstyle that is composited onto the user's face.

[0414] A "virtual reality space" is a computer-generated 3D virtual environment that users experience using a VR head-mounted display or similar device.

[0415] A "display device" is a device for checking hairstyle patterns in real time within a virtual reality space, such as a VR head-mounted display.

[0416] A "terminal" is a device such as a computer or smartphone that a user uses to operate the system.

[0417] A "haircut recipe" is information detailing specific instructions for a hairdresser to perform a haircut based on a selected hairstyle pattern.

[0418] A "future hairstyle simulation" is a composite image that predicts the growth and changes in hairstyle over the next few months, for example, and allows the user to check it in advance.

[0419] The present invention is a system that allows a user to accurately communicate their desired hairstyle to a hairdresser, and in particular provides a real-time hairstyle simulation in a virtual reality space. A method for implementing this will be described in detail below.

[0420] First, the user uses facial images taken from multiple angles, including the front, side, and back of the head, and uploads these facial images to the system using a terminal. Specifically, the user follows the instructions to select an image file and send it to the system.

[0421] Next, the device temporarily saves the facial image file selected by the user and then sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. In particular, it identifies important points such as the eyes, nose, mouth, and face shape. It also analyzes the current hairstyle shape and color.

[0422] The server then uses a generative AI model based on the analyzed data to generate multiple hairstyle patterns. The generative AI model synthesizes a natural hairstyle that suits the user's face based on the trained data. For example, it generates different variations such as short hair, long hair, bob, and perm.

[0423] The server then synthesizes the generated hairstyle patterns onto the user's facial image, allowing the user to view these synthesized images in real time in a virtual reality space.The user can use a VR head-mounted display (e.g., Oculus Rift) to view the hairstyle patterns in the virtual reality space and select the hairstyle that best suits them by changing their movements and viewpoints.

[0424] The user sends the hairstyle pattern they have selected to the server via their terminal. Based on this selection, the server generates a specific haircut recipe. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also performs a simulation of the future hairstyle, displaying a composite image of what the long bob will look like in three months, for example.

[0425] The generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can bring this haircut recipe to the salon and provide specific instructions to the hairdresser. For example, User A uploads three images of his face - from the front, side, and back of the head - and the server generates 10 hairstyle patterns. User A selects a bob style from these, and based on this selection, the server generates a haircut recipe specifying the length of the bangs, the amount of hair on the sides, and other factors. In addition, a simulation image of a long bob three months from now is also provided. User A can show this information to the hairdresser to achieve the specific hairstyle.

[0426] An example prompt has the following format:

[0427] Use the detailed facial image data below to generate 10 hairstyle patterns that best suit the user.

[0428] Image data: [URL of user's face photo (front, side, back)]

[0429] Facial features: [Analysis results of eyes, nose, mouth, face, etc.]

[0430] Current hairstyle: [shape and color]

[0431] This system allows users to simulate their desired hairstyle in advance in a virtual reality space, and based on the results, they can provide detailed instructions to their hairdresser.

[0432] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0433] Step 1:

[0434] The user takes facial images from multiple angles and uploads them to the system using a terminal. Here, the user inputs facial images from multiple angles, such as the front, side, and back of the head. The terminal temporarily stores these image files and then sends them to the server. The input data in this case are facial image files, and the output is the transmission of image files to the server.

[0435] Step 2:

[0436] The server analyzes the received facial image and recognizes facial feature points and hairstyle information. Specifically, it identifies important points such as the eyes, nose, mouth, and face shape, and also analyzes the current hairstyle shape and color. The input for this process is the facial image sent from the device, and the output is data on facial feature points and hairstyle information.

[0437] Step 3:

[0438] The server uses a generative AI model to generate multiple hairstyle patterns based on the analyzed facial features and hairstyle information. The generative AI model uses the trained data to synthesize a natural hairstyle that suits the user's face. The input for this process is the analyzed data, and the output is multiple hairstyle patterns.

[0439] Step 4:

[0440] The server synthesizes the generated hairstyle pattern with the user's facial image to generate a composite image. These composite images are intended for the user to view in a virtual reality space. The inputs to this process are the hairstyle pattern and the user's facial image, and the output is the composite image.

[0441] Step 5:

[0442] The user wears a VR head-mounted display and checks multiple hairstyle patterns in real time within a virtual reality space. Specifically, the user can change their viewpoint within the virtual space and freely rotate the hairstyle to check it. The input for this process is a composite image sent from the server, and the output is the user's hairstyle selection information.

[0443] Step 6:

[0444] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server. The input of this process is the user's hairstyle selection information, and the output is the transmission of the selection information to the server.

[0445] Step 7:

[0446] The server generates a specific haircut recipe based on the selected hairstyle pattern. A haircut recipe typically includes information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The server also simulates the future hairstyle, displaying a composite image of what the hair will look like three months from now. The input for this process is the user's hairstyle selection information, and the output is a specific haircut recipe and a simulated image of the future hairstyle.

[0447] Step 8:

[0448] The server sends the generated haircut recipe and a simulation image of the future hairstyle to the terminal. The terminal displays this to the user, who can then take the haircut recipe to the salon and give specific instructions to the hairdresser. The input of this process is the haircut recipe and simulation image sent from the server, and the output is the display to the user.

[0449] 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.

[0450] The present invention is a system that allows a user to accurately communicate the hairstyle they desire to a hairdresser and further suggests an appropriate hairstyle taking the user's feelings into consideration, and an embodiment of this system will be described below.

[0451] First, the user accesses the system using a terminal. The user takes and uploads facial images of the front, side, and back of the head. The user follows the instructions to select the image file and send it to the server.

[0452] The device temporarily saves the facial image file selected by the user and sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. It then uses an emotion engine to analyze the user's emotions from the facial image. Specifically, it detects facial expressions and subtle changes and determines the emotion.

[0453] Based on the analysis results, the emotion engine quantifies the user's current emotional state and inputs that information into a generative AI model. The server then uses the generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. Depending on the emotion, different variations are generated, such as short hair, long hair, bob, and perm.

[0454] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way and saves each pattern as an image file. These synthesized images are sent from the server to the terminal, which then displays a list of hairstyle patterns to the user. The user can then review the displayed hairstyle patterns and select the hairstyle they like best.

[0455] When the user selects the hairstyle they want, the device sends the selection information to the server. The server then generates a specific haircut recipe based on the user's selection and the analysis results of the emotion engine. This haircut recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also simulates future hairstyles based on the user's emotion data, predicting what the hairstyle will look like three months from now, for example, and generating a composite image.

[0456] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then bring this haircut recipe to the hair salon and provide specific instructions to the hairdresser.

[0457] As a specific example, if User A uploads facial images of the front, side, and back of the head, and the emotion engine analyzes this as an "excited state," the server will use the generative AI model to prioritize suggestions for short hair and bright colors that give a lively impression. User A selects a bob style from the list, and the server generates a haircut recipe based on that selection and emotion data, including the length of the bangs and the amount of hair on the sides. Furthermore, a simulation of the hairstyle three months from now is provided, predicting changes in emotions.

[0458] In this way, by using the present invention, the user can easily select the optimal hairstyle based on their emotions and accurately convey specific instructions to the hairdresser.

[0459] The processing flow will be explained below.

[0460] Step 1:

[0461] Users access the system using a terminal, take front, side, and back images of their face, and upload them to the system.

[0462] Step 2:

[0463] The device temporarily stores the facial image files uploaded by the user, displays a confirmation message indicating that the upload is complete, and then transmits the facial image files to the server.

[0464] Step 3:

[0465] The server analyzes the received facial image. Specifically, it detects facial features (eyes, nose, mouth, contours, etc.) and identifies their positions. It also analyzes the shape and color of the hairstyle.

[0466] Step 4:

[0467] The server uses an emotion engine to recognize emotions from the user's facial image. The emotion engine detects facial expressions and subtle changes and quantifies the user's emotional state. For example, it identifies emotions such as joy, sadness, excitement, and calmness.

[0468] Step 5:

[0469] The server inputs the analyzed facial feature points and emotional data into a generative AI model, which then synthesizes a natural hairstyle that matches the user's face based on the learned data. Depending on the emotional data, different variations such as short hair, long hair, bob, and perm are generated.

[0470] Step 6:

[0471] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way, saves each pattern as an image file, and transmits the synthesized images to the terminal.

[0472] Step 7:

[0473] The terminal displays the list of hairstyle patterns received from the server to the user, who then checks the displayed multiple hairstyle patterns and selects the hairstyle that he or she likes best.

[0474] Step 8:

[0475] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server.

[0476] Step 9:

[0477] The server generates a specific haircut recipe based on the selected hairstyle pattern and emotion data, which includes details such as the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0478] Step 10:

[0479] The server also simulates future hairstyles, for example, predicting what a long bob will look like in three months' time and generating a synthetic image of it.

[0480] Step 11:

[0481] The server transmits the generated haircut recipe and a future hairstyle simulation image to the terminal.

[0482] Step 12:

[0483] The terminal displays the haircut recipe and the future hairstyle simulation received from the server to the user, who can then show the haircut recipe to the hairdresser and provide specific instructions.

[0484] As a specific example, if User A uploads facial images of the front, side, and back of the head, and the emotion engine analyzes this as an "excited state," the server will use the generative AI model to prioritize suggestions for short hair and bright colors that give a lively impression. User A selects a bob style from the list, and the server generates a haircut recipe based on that selection and emotion data, including the length of the bangs and the amount of hair on the sides. Furthermore, a simulation of the hairstyle three months from now is provided, predicting changes in emotions.

[0485] In this way, by using the present invention, the user can easily select the optimal hairstyle based on their emotions and accurately convey specific instructions to the hairdresser.

[0486] Example 2

[0487] 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."

[0488] In conventional hair style suggestion systems at beauty salons, it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, and the system does not consider the user's emotional state when proposing a hairstyle, resulting in a hairstyle that is unsatisfying. The present invention aims to improve user satisfaction by enabling users to accurately communicate their desired hairstyle and by proposing an optimal hairstyle that takes the user's emotions into consideration.

[0489] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0490] In this invention, the server includes means for uploading facial images taken from multiple angles by the user, means for the terminal to temporarily store the image files and send them to the server, means for the server to analyze the received facial images and recognize facial features and emotions, means for the server to use a generative AI model to generate and display multiple hairstyle patterns based on the emotion data and the user's facial image, means for the terminal to display the multiple hairstyle patterns to the user, means for the user to select a hairstyle pattern desired by the server, means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern, and means for the terminal to display the generated haircut recipe and future hairstyle simulation to the user. This makes it possible to suggest an optimal hairstyle based on the user's emotions and generate a specific haircut recipe.

[0491] "Facial image" refers to an image file that shows the user's face from the front, side, or back of the head.

[0492] "Device" refers to a computing device used by a user, such as a smartphone, PC, or tablet.

[0493] "Server" refers to the central processing unit that processes information received from users and generates and transmits necessary data.

[0494] "Feature points" refer to the positional information of specific parts of the face, such as the facial contours, eyes, nose, and mouth.

[0495] "Emotion" refers to the psychological state that can be analyzed from the user's facial expressions and subtle changes.

[0496] "Generative AI model" refers to an artificial intelligence model that generates hairstyle patterns using machine learning algorithms.

[0497] "Hairstyle patterns" refers to multiple different hairstyle designs created by a generative AI model.

[0498] A "haircut recipe" refers to a document that details specific treatment methods and instructions based on a hairstyle pattern.

[0499] "Future hairstyle simulation" refers to a technology that predicts what a user's hairstyle will look like after a certain period of time and displays it as a composite image.

[0500] The present invention is a system that allows a user to accurately communicate the hairstyle they want to a hairdresser and further suggests an appropriate hairstyle taking the user's feelings into consideration. An embodiment of the system will be described below.

[0501] First, the user accesses the system's webpage on their device (such as a smartphone or PC). This webpage provides an interface for users to upload facial images. The user takes a picture of their face from the front, side, or back of the head, and clicks the "Upload" button to send the selected image file to the system.

[0502] The device temporarily stores the facial image file selected by the user in local storage. The stored image file is then sent to the server as an HTTP POST request using JavaScript. This communication is asynchronous, using an Ajax library (e.g., jQuery).

[0503] The server passes the received facial images to an analysis program written in Python. OpenCV and Dlib libraries are used for facial analysis, which detects facial features and recognizes emotions by analyzing facial expressions and subtle changes in the facial images. Emotion recognition uses a cloud service's emotion analysis API (for example, Azure's emotion analysis API). The results of the emotion analysis are extracted as numerical data.

[0504] The server inputs this quantified emotion data into a generative AI model (such as StyleGAN). The generative AI model is built using deep learning frameworks such as TensorFlow and PyTorch, and generates multiple hairstyle patterns to be synthesized onto the user's face based on the emotion data and facial images. In this process, an appropriate prompt sentence is input into the AI ​​model. An example of a prompt sentence is, "The user's emotional state is excited. Generate a hairstyle pattern with a short hair style or a bright color that gives a lively impression."

[0505] The generated hairstyle patterns are naturally combined with the facial image and saved as an image file. These combined images are sent from the server to the device as an HTTP response. The device's browser displays a list of the received hairstyle pattern images, allowing the user to select the desired hairstyle from multiple options.

[0506] When a user selects a specific hairstyle pattern, that information is sent from the device to the server. The server generates a specific haircut recipe based on the selected hairstyle pattern and emotional data. The haircut recipe includes detailed instructions on the length of the bangs, the amount of hair on the sides, and coloring. Furthermore, a future hairstyle simulation is performed, and an image of the predicted hairstyle three months from now is generated.

[0507] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user, who can then print or download the haircut recipe and bring it to the hair salon to provide specific hairstyle instructions to the hairdresser.

[0508] In this way, by using the present invention, the user can select the hairstyle that best suits his / her emotions and face, while providing accurate beauty instructions to the hairdresser.

[0509] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0510] Step 1:

[0511] A user accesses the system and uploads a facial image.

[0512] Users access the system's web page using a device such as a smartphone or PC. They click the "Upload Face Image" button on the web page, select a face image from the front, side, or back of the head, and upload it. At this time, the input data is the user's face image file, and the output is a message indicating successful file upload. Specifically, an image file is selected using an HTML form, and the image upload process is carried out using JavaScript.

[0513] Step 2:

[0514] The device temporarily saves the image file and sends it to the server.

[0515] The facial image file is temporarily saved in the device's local storage. After saving, an HTTP POST request is created using the Ajax library, and the image file is sent to the server. At this time, the input data is the saved image file, and the output is the file sent to the server. Specifically, asynchronous communication is performed using JavaScript and Ajax.

[0516] Step 3:

[0517] The server analyzes the facial image and recognizes the features and emotions.

[0518] The server passes the received facial images to an analysis program written in Python. It uses Python's OpenCV and Dlib libraries to detect facial feature points (eyes, nose, mouth, etc.). Based on this feature point data, it uses Azure's emotion analysis API to analyze the user's emotions from their facial expressions. The input data is the user's facial image, and the output is feature point data and emotion data. Specific operations include image preprocessing (resizing, grayscale conversion), feature point extraction, and making requests to the cloud API.

[0519] Step 4:

[0520] The server inputs the emotion data into the AI ​​model to generate a hairstyle pattern.

[0521] The results of the sentiment analysis are quantified and input into a generative AI model built using Python's TensorFlow or PyTorch. The generative AI model (for example, StyleGAN) generates multiple hairstyle patterns based on the input data. In this process, an appropriate prompt sentence is input into the AI ​​model. The input data is feature point data and emotion data, and the output is multiple hairstyle pattern images. Specifically, the emotion data is quantified, input into the AI ​​model, and hairstyle patterns are generated.

[0522] Step 5:

[0523] The server synthesizes the generated hairstyle pattern and sends it to the device.

[0524] The generated hairstyle pattern is composited with the user's facial image and output in a natural way. The composite image is saved on the server and sent to the device as an HTTP response. The input data is the generated hairstyle pattern and the user's facial image, and the output is a composite image file. A Python image processing library is used for the composite.

[0525] Step 6:

[0526] The device displays hairstyle patterns to the user.

[0527] The device's browser displays a list of composite images received from the server. Using HTML, CSS, and JavaScript, the images are displayed in a format that is easy for the user to view. The input data is the composite image file sent from the server, and the output is a list of hairstyles that is displayed to the user. Specifically, the images are loaded and displayed.

[0528] Step 7:

[0529] The user selects the desired hairstyle.

[0530] The user selects the desired hairstyle pattern by clicking on it from the displayed patterns. Information on the selected hairstyle pattern is sent from the device to the server. The input data is the ID of the hairstyle pattern clicked by the user, and the output is the transmission of the selected information to the server. Specific operations include processing the click event using JavaScript and sending data.

[0531] Step 8:

[0532] The device sends the selection information to the server

[0533] The device sends data including the ID of the selected image to the server as an HTTP POST request. The input data is the ID of the selected image, and the output is a message to the server indicating that the request was sent successfully. Specifically, asynchronous communication is performed using Ajax.

[0534] Step 9:

[0535] The server generates a haircut recipe and a simulation of the future hairstyle.

[0536] The server generates a specific haircut recipe (bangs length, amount of hair on the sides, coloring instructions, etc.) based on the selected hairstyle pattern and emotional data. It also performs a future hairstyle simulation and generates a predicted hairstyle three months from now. The input data is the selected hairstyle pattern and emotional data, and the output is a haircut recipe and predicted hairstyle image. Specifically, data analysis and model inference processing are performed.

[0537] Step 10:

[0538] Send the results generated by the server to the device

[0539] The generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal as an HTTP response. The input data are the haircut recipe and simulation image, and the output is the response sent to the terminal. Specifically, data packaging and HTTP transmission processing are performed.

[0540] Step 11:

[0541] The device displays the results to the user

[0542] The terminal displays the received cutting recipe and simulation image to the user. It uses HTML and JavaScript to provide an interface that the user can easily check. The input data is the cutting recipe and simulation image received from the server, and the output is what is displayed to the user. Specifically, data loading and display processing are carried out.

[0543] (Application example 2)

[0544] 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."

[0545] In conventional hair styling suggestion systems at hair salons, the desired hairstyle image often does not match between the user and the hairdresser, resulting in a decrease in user satisfaction. Furthermore, there was no system that could analyze the user's emotions from a facial image and suggest the optimal hairstyle based on that. This made it difficult to suggest a hairstyle that matched the user's mood and preferences at the time, which further led to dissatisfaction.

[0546] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for taking and uploading a facial image of a customer using a tablet or smartphone, means for analyzing emotions from the facial image and generating a hairstyle pattern based on the emotion, and means for displaying the generated hairstyle pattern to the customer. This makes it possible to suggest a hairstyle that is suited to the user's current emotional state, thereby improving user satisfaction.

[0547] A "user" is an individual who uses the hairstyle suggestion system.

[0548] A "face image" is a photograph of the user's face taken from multiple angles, such as the front, side, and back of the head.

[0549] The "server" is a computer on the network that receives and analyzes data and generates hairstyle patterns using a generative AI model.

[0550] A "generative AI model" is an artificial intelligence technology that generates hairstyle patterns based on a user's facial image and emotional data.

[0551] "Hairstyle patterns" are digital images of different types of hairstyles that are composited onto the user's facial image.

[0552] A "terminal" is a hardware device such as a tablet or smartphone that is operated by a user.

[0553] "Emotion" refers to the psychological state of the user that is analyzed from a facial image, and the analysis results are used to suggest hairstyles.

[0554] A "cut recipe" is a set of specific instructions for a hairstyle, including the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0555] A "future hairstyle simulation" is a digital image that predicts how a user's hairstyle will change over time.

[0556] A specific embodiment for carrying out this invention will be described below. First, a user accesses the system using a tablet or smartphone installed in a beauty salon. The user takes facial images of the front, side, and back of the head and uploads them to the system.

[0557] The hardware used is a tablet or smartphone camera, and the software is an application for capturing and uploading facial images. The system temporarily stores the facial image file selected by the user and sends it to a server.

[0558] The server analyzes the received facial image and recognizes facial features and hairstyle information. It also uses an emotion engine to analyze the user's emotions from the facial image. Specifically, it detects facial expressions and subtle changes and determines the emotion. The software used includes OpenCV (facial image analysis) and Keras (emotion engine).

[0559] Next, the server uses the generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. Different variations such as short hair, long hair, bob, and perm are generated depending on the emotion. These hairstyle patterns are naturally combined with the user's facial image, and each pattern is saved as an image file. This is what the generative AI model is used for.

[0560] The server sends the generated hairstyle patterns to a tablet or smartphone, which then displays them to the user. The user can then review the displayed hairstyle patterns and select the one they like best. The device then sends the selection information to the server.

[0561] The server generates a specific haircut recipe based on the hairstyle pattern selected by the user and the results of emotion analysis. This haircut recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also performs a simulation of future hairstyles, predicting what the hairstyle will look like three months from now, for example, and generates a composite image. This allows the user to receive a haircut at the salon that takes future hairstyles into consideration.

[0562] As a specific example, if user A takes a picture of his face with a tablet and the facial image is analyzed by the emotion engine as being in a "relaxed state," the server will use the generative AI model to preferentially suggest hairstyle patterns that give a calm impression. An example of a prompt sentence in this case is as follows:

[0563] "Input the user's facial image into an emotion engine and generative AI model to suggest hairstyle patterns that suit their relaxed state."

[0564] This allows the user to be suggested a hairstyle that is best suited to their current psychological state, improving satisfaction at the beauty salon.

[0565] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0566] Step 1:

[0567] First, the user accesses the system using a tablet or smartphone installed in the beauty salon. The user takes facial images of the front, side, and back of the head and uploads them to the system. The input is the facial image taken by the user, and the output is the uploaded facial image data. Specifically, the user takes a facial image using the camera application on the tablet or smartphone and sends it to the server.

[0568] Step 2:

[0569] The device temporarily stores the facial image file selected by the user and sends it to the server. The input is the facial image taken and uploaded by the user, and the output is the facial image data sent to the server. Specifically, the device transfers the temporarily stored image file to the server via an HTTP request.

[0570] Step 3:

[0571] The server analyzes the received facial image and recognizes facial feature points and hairstyle information. The input is the facial image data sent to the server, and the output is the analyzed facial feature point data and hairstyle information.

[0572] Specifically, it uses OpenCV to analyze facial images, extract feature points for each part of the face, recognize the shape and contours of the face, and extract information about the current hairstyle.

[0573] Step 4:

[0574] The server uses an emotion engine to analyze emotions from the user's facial image. The input is analyzed facial feature point data, and the output is analyzed emotion data. Specifically, the emotion engine using Keras is used to analyze emotions from facial expressions, and the results are obtained as numerical data.

[0575] Step 5:

[0576] The server uses a generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. The input is the user's facial image and analyzed emotional data, and the output is multiple generated hairstyle patterns. Specifically, a prompt sentence is generated based on the emotional data, and this is input into the generative AI model to automatically generate a hairstyle pattern that matches the emotion.

[0577] Step 6:

[0578] The server synthesizes the generated hairstyle pattern onto the user's facial image in a natural way and saves each pattern as an image file. The input is the user's facial image and the generated hairstyle pattern, and the output is an image file of the synthesized hairstyle pattern. Specifically, the server uses a synthesis algorithm to superimpose the generated hairstyle pattern onto the user's facial image.

[0579] Step 7:

[0580] The server sends the generated hairstyle patterns to a tablet or smartphone, and the device displays them as a list. The input is an image file of the synthesized hairstyle pattern, and the output is a list of hairstyle patterns displayed on the device. Specifically, the image file of the hairstyle pattern is sent to the device as an HTTP response, and the display application renders it.

[0581] Step 8:

[0582] The user checks the displayed hairstyle patterns and selects the hairstyle they like best. The input is the displayed hairstyle patterns, and the output is the information on the hairstyle pattern selected by the user. Specifically, the user selects the desired hairstyle using touch operations or selection buttons.

[0583] Step 9:

[0584] The terminal sends the user's selection information to the server. The input is the hairstyle pattern information selected by the user, and the output is the selection information sent to the server. Specifically, the user's selection information is transmitted to the server as an HTTP request.

[0585] Step 10:

[0586] The server generates a specific haircut recipe based on the hairstyle pattern selected by the user and the emotion analysis results. The input is the information on the selected hairstyle pattern and emotion data, and the output is a specific haircut recipe. Specifically, the server automatically generates a haircut recipe that includes the length of the bangs, the amount of hair on the sides, coloring instructions, etc.

[0587] Step 11:

[0588] The server also simulates future hairstyles, predicting what the user's hairstyle will look like in three months, for example, and generates a synthetic image. The input is the user's hairstyle pattern and predicted growth data, and the output is a simulated image of the future hairstyle. Specifically, the server predicts the future hairstyle using an algorithm that simulates hair growth.

[0589] Step 12:

[0590] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which then displays them to the user. The input is the haircut recipe and future hairstyle simulation image, and the output is the information displayed on the terminal. Specifically, the haircut recipe and simulation image are sent as an HTTP response, and the terminal presents them to the user using an application that displays them.

[0591] Through the above processing steps, the user is suggested a hairstyle that suits their current psychological state, improving their satisfaction at the beauty salon.

[0592] 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.

[0593] 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.

[0594] 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.

[0595] [Third embodiment]

[0596] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0597] 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.

[0598] 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).

[0599] 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.

[0600] 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.

[0601] 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).

[0602] 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. 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.

[0603] 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.

[0604] 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.

[0605] 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.

[0606] 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.

[0607] 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."

[0608] The present invention is a system for allowing a user to accurately communicate a desired hairstyle to a hairdresser, and can be implemented as follows.

[0609] First, the user accesses the system using a terminal and uploads facial images taken from multiple angles, such as the front, side, and back of the head. The user then follows the instructions to select the image file and send it to the system.

[0610] Next, the device temporarily saves the image file selected by the user and then sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. Specifically, it identifies important points such as the eyes, nose, mouth, and face shape, and also analyzes the current hairstyle shape and color.

[0611] The server then uses a generative AI model based on the analyzed data to generate multiple hairstyle patterns. The generative AI model synthesizes a natural hairstyle that suits the user's face based on the trained data. For example, different variations such as short hair, long hair, bob, and perm are generated.

[0612] The server then combines the generated hairstyle patterns with the user's facial image, saves each pattern as an image, and transmits the combined image to the terminal.

[0613] The terminal displays the list of hairstyle patterns received from the server to the user, who can then check the displayed hairstyle patterns and select the hairstyle that he or she likes best.

[0614] When the user selects the desired hairstyle, the device sends that information to the server. The server then generates a specific haircut recipe based on the selected hairstyle. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The device also simulates future hairstyles, displaying a composite image of what a long bob will look like in three months.

[0615] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then bring this haircut recipe to the hair salon and provide specific instructions to the hairdresser.

[0616] As a specific example, User A uploads three images of his face - one from the front, one from the side, and one from the back of his head - and the server generates ten different hairstyle patterns. User A selects a bob style from the images, and the server generates a haircut recipe based on that selection, including the length of the bangs and the amount of hair on the sides. In addition, a simulated image of a long bob three months from now is also provided. User A can show this information to a hairdresser to achieve the desired hairstyle.

[0617] In this way, by using the present invention, the user can simulate the hairstyle they want in advance and, based on the results, give detailed instructions to the hairdresser.

[0618] The processing flow will be explained below.

[0619] Step 1:

[0620] The user accesses the system using a terminal, takes three images of their face (front, side, and back of the head), and uploads each image to the system.

[0621] Step 2:

[0622] The device temporarily stores the facial image files uploaded by the user, displays a confirmation message indicating that the upload is complete, and then transmits the facial image files to the server.

[0623] Step 3:

[0624] The server analyzes the received facial image. Specifically, it detects facial features (eyes, nose, mouth, contours, etc.) and identifies their positions. It also analyzes the shape and color of the hairstyle.

[0625] Step 4:

[0626] The server uses a generative AI model based on the analysis results to generate multiple hairstyle patterns to be combined with the user's facial image. The generative AI model uses the learned data to create a natural hairstyle. Different variations such as short hair, long hair, bob, and perm are generated.

[0627] Step 5:

[0628] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way, saves each pattern as an image file, and transmits the synthesized images to the terminal.

[0629] Step 6:

[0630] The terminal displays the list of hairstyle patterns received from the server to the user, who then checks the displayed multiple hairstyle patterns and selects the hairstyle that he or she likes best.

[0631] Step 7:

[0632] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server.

[0633] Step 8:

[0634] The server generates a specific haircut recipe based on the selected hairstyle pattern, which includes details such as the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0635] Step 9:

[0636] The server also simulates future hairstyles, for example, predicting what a long bob will look like in three months' time and generating a synthetic image of it.

[0637] Step 10:

[0638] The server transmits the generated haircut recipe and a future hairstyle simulation image to the terminal.

[0639] Step 11:

[0640] The terminal displays the haircut recipe and the future hairstyle simulation received from the server to the user, who can then show the haircut recipe to the hairdresser and provide specific instructions.

[0641] Example 1

[0642] 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."

[0643] With conventional systems, it was difficult for users to communicate their desired hairstyle in detail to the hairdresser, resulting in the hairstyle often not being exactly what they wanted.In addition, the process of selecting the hairstyle that best suits the user's face shape and characteristics was complicated, time-consuming, and laborious.

[0644] 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.

[0645] In this invention, the server includes means for analyzing the received facial image and recognizing facial features and hairstyle information, means for generating multiple hairstyle patterns using a generative AI model based on the analyzed data, and means for combining the generated hairstyle patterns with the facial image and transmitting them to the terminal. This allows the user to visually simulate a desired hairstyle in advance and to provide specific instructions to the hairdresser based on a detailed haircut recipe.

[0646] "User" refers to an individual who utilizes the system to simulate their own hairstyle.

[0647] "Terminal" refers to the electronic device that a User uses to access the System, upload images, and view results.

[0648] "Facial images" refer to digital images of a user's face taken from multiple angles.

[0649] "Server" refers to a computer system that analyzes received image data and generates hairstyle patterns using a generative AI model.

[0650] "Feature points" refer to important points in a facial image, such as the eyes, nose, mouth, and contours.

[0651] "Hairstyle information" refers to data regarding the style and color of a user's current hairstyle.

[0652] A "generative AI model" refers to an algorithm that generates hairstyle patterns that naturally fit the user's face based on learned data.

[0653] "Hairstyle patterns" refer to multiple hairstyle variations generated by a generative AI model.

[0654] A "haircut recipe" refers to detailed instructions for a hairdresser to perform a specific cut and color based on the selected hairstyle.

[0655] "Future hairstyle simulation" refers to an image that predicts the future shape and state of the hairstyle selected by the user.

[0656] This invention is a system that allows users to accurately communicate their desired hairstyle to their hairdresser. The system allows users to upload facial images taken from multiple angles, and uses AI technology to generate and display various hairstyle patterns for those facial images, and provides a specific haircut recipe based on the hairstyle pattern that the user is satisfied with.

[0657] First, the user accesses the system using a terminal and uploads facial images taken from the front, side, and back of the head. Following the instructions displayed on the screen, the user clicks the file selection button to select the image file, and then presses the send button to send the image to the system.

[0658] The device temporarily stores the uploaded facial image and then sends it to the server using the HTTP POST method with the REST API. The server analyzes the received facial image and uses face detection algorithms such as OpenCV or Dlib to recognize facial features (eyes, nose, mouth, contours, etc.) and current hairstyle information (shape and color).

[0659] After the analysis is complete, the server uses a generative AI model (e.g., GAN or DCGAN) based on the analyzed data to generate multiple hairstyle patterns. These AI models are trained in advance with a large amount of hairstyle data and synthesize hairstyles that fit the user's face naturally. An example of a prompt is, "Please generate hairstyles such as short hair, bob, and perm that suit the user's face."

[0660] The generated hairstyle pattern is saved on the server and simultaneously composited onto the user's face image. The composite image is generated using an image processing library (e.g., PIL or OpenCV) and saved as multiple image files. These files are saved with names such as "shorthair.png" and "bob.png."

[0661] Once the composite image is complete, the server sends it to the device, which then displays a list of the received hairstyle patterns for the user to easily review. The user can then select the hairstyle they like best from the displayed patterns.

[0662] After the user selects the desired hairstyle, the device sends that information to the server. The server then generates a specific haircut recipe based on the selected hairstyle. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The server also performs future hairstyle simulations, generating a composite image of what the long bob will look like in three months, for example.

[0663] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then take this information to the hair salon and provide specific instructions to the hairdresser.

[0664] As a specific example, User A uploads three images of his face - one from the front, one from the side, and one from the back of his head - and the server generates ten different hairstyle patterns. User A selects a bob style from the images, and the server generates a haircut recipe based on that selection, including the length of the bangs and the amount of hair on the sides. In addition, a simulated image of a long bob three months from now is also provided. User A can show this information to a hairdresser to achieve the desired hairstyle.

[0665] An example of a prompt sentence could be, "Generate an appropriate hairstyle pattern based on multiple face images provided by the user. For example, generate variations such as short hair, long hair, bob, perm, etc., and combine them naturally with the user's face."

[0666] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0667] Step 1:

[0668] The user accesses the system using a terminal and uploads facial images taken from the front, side, and back of the head. The user follows the on-screen instructions, clicks the file selection button, and selects the image file. Then, clicks the send button to send the facial image to the system. The input is the image file uploaded by the user, and the output is the data of the image file sent to the server.

[0669] Step 2:

[0670] The device temporarily saves the image file selected by the user. Then, it issues an HTTP request to send the saved image file to the server. Specifically, the device uses the REST API to send the image data to the server using the POST method. The input is the temporarily saved image file, and the output is the HTTP request sent to the server.

[0671] Step 3:

[0672] The server begins processing the received image file. Specifically, it first identifies the face region from the image using a face detection algorithm (e.g., OpenCV or Dlib). Next, it detects facial feature points (eyes, nose, mouth, face contours, etc.) with high accuracy. It also analyzes the shape and color of the current hairstyle. The input is the received face image, and the output is the analyzed facial feature point data and hairstyle information.

[0673] Step 4:

[0674] The server generates multiple hairstyle patterns using a generative AI model (e.g., GAN or DCGAN) based on the analyzed data. The AI ​​model is trained in advance with a large amount of hairstyle data and synthesizes a hairstyle that fits the user's face naturally. An example of a prompt is "Please generate hairstyles such as short hair, bob, and perm that suit the user's face." The input is the analyzed facial feature point data and the prompt, and the output is the generated multiple hairstyle patterns.

[0675] Step 5:

[0676] The server composites the generated hairstyle pattern onto the user's face image. This composite process uses an image processing library (e.g., PIL, OpenCV). The composite results are generated as multiple image files and saved on the server. Each file is saved with a name such as "shorthair.png" or "bob.png." The input is the generated hairstyle pattern and the user's face image, and the output is an image file of the composite hairstyle pattern.

[0677] Step 6:

[0678] The server sends the image files of the synthesized hairstyle patterns to the device. The device displays the received images on the application's UI so that the user can check them. Specifically, it displays a list in thumbnail format from which the user can select each hairstyle pattern. The input is the image files of the hairstyle patterns received from the server, and the output is multiple hairstyle patterns displayed on the UI.

[0679] Step 7:

[0680] The user checks the displayed hairstyle patterns and selects the hairstyle they like best. After selection, the terminal sends information about the selected hairstyle pattern to the server. The input is the hairstyle pattern selected by the user, and the output is the selection information sent to the server.

[0681] Step 8:

[0682] The server generates a specific haircut recipe based on the selected hairstyle pattern. The haircut recipe includes details such as bang length, side volume, and coloring instructions. These instructions are created using a dedicated template. The input is the user-selected hairstyle pattern, and the output is the generated haircut recipe.

[0683] Step 9:

[0684] The server performs a future hairstyle simulation. For example, to generate a composite image of what a long bob will look like three months from now, the generative AI model is used again. The simulation results are generated as an image file and saved on the server. The input is the hairstyle pattern selected by the user and the future simulation period, and the output is a composite future hairstyle simulation image.

[0685] Step 10:

[0686] The server sends the generated haircut recipe and a future hairstyle simulation image to the terminal, which displays it to the user, who can then take it to the hair salon. The input is the haircut recipe and simulation image received from the server, and the output is the haircut recipe and simulation image displayed to the user.

[0687] (Application example 1)

[0688] 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."

[0689] Conventional hairstyle simulation systems make it difficult for users to actually see the hairstyle they want. It's also difficult for users to communicate their specific hairstyle image to the hairdresser, resulting in the hair often not turning out as desired. Furthermore, since it's not possible to try out multiple hairstyle patterns in real time, selecting the optimal hairstyle takes time. There is a need for a system that solves these problems, allowing users to see multiple hairstyle patterns in real time in a virtual reality space and present specific haircut recipes to the hairdresser.

[0690] 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.

[0691] In this invention, the server includes: means for uploading facial images taken from multiple angles by the user; means for analyzing the received facial images by the server and recognizing facial features and hairstyle information; means for the server to use a generated AI model to synthesize multiple hairstyle patterns and display them naturally on the user's facial image; means for the server to use a display device to allow the user to check hairstyle patterns in real time in a virtual reality space; means for the terminal to display multiple hairstyle patterns to the user; means for the user to select a hairstyle pattern desired by the user; means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern; and means for the terminal to display the generated haircut recipe and future hairstyle simulation to the user. This allows the user to check multiple hairstyles in real time in the virtual reality space, making it easier for the user to select the optimal hairstyle and also enabling the user to accurately give specific haircut instructions to the hairdresser.

[0692] A "user" is an individual who uses the system to perform a hairstyle simulation.

[0693] "Facial images taken from multiple angles" are photographs of the user's face taken from different angles, such as from the front, side, or back of the head.

[0694] A "server" is a computer system that analyzes data via the Internet and generates and provides hairstyle patterns.

[0695] "Facial feature points" refer to the main parts of the face, such as the eyes, nose, mouth, and contours, and are points used to analyze their position and shape.

[0696] "Hairstyle information" is data relating to the characteristics of the user's hair, such as the shape and color of the current hairstyle.

[0697] A "generative AI model" is an artificial intelligence model that generates new hairstyles based on learned data.

[0698] A "hairstyle pattern" is a variation of a different hairstyle that is composited onto the user's face.

[0699] A "virtual reality space" is a computer-generated 3D virtual environment that users experience using a VR head-mounted display or similar device.

[0700] A "display device" is a device for checking hairstyle patterns in real time within a virtual reality space, such as a VR head-mounted display.

[0701] A "terminal" is a device such as a computer or smartphone that a user uses to operate the system.

[0702] A "haircut recipe" is information detailing specific instructions for a hairdresser to perform a haircut based on a selected hairstyle pattern.

[0703] A "future hairstyle simulation" is a composite image that predicts the growth and changes in hairstyle over the next few months, for example, and allows the user to check it in advance.

[0704] The present invention is a system that allows a user to accurately communicate their desired hairstyle to a hairdresser, and in particular provides a real-time hairstyle simulation in a virtual reality space. A method for implementing this will be described in detail below.

[0705] First, the user uses facial images taken from multiple angles, including the front, side, and back of the head, and uploads these facial images to the system using a terminal. Specifically, the user follows the instructions to select an image file and send it to the system.

[0706] Next, the device temporarily saves the facial image file selected by the user and then sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. In particular, it identifies important points such as the eyes, nose, mouth, and face shape. It also analyzes the current hairstyle shape and color.

[0707] The server then uses a generative AI model based on the analyzed data to generate multiple hairstyle patterns. The generative AI model synthesizes a natural hairstyle that suits the user's face based on the trained data. For example, it generates different variations such as short hair, long hair, bob, and perm.

[0708] The server then synthesizes the generated hairstyle patterns onto the user's facial image, allowing the user to view these synthesized images in real time in a virtual reality space.The user can use a VR head-mounted display (e.g., Oculus Rift) to view the hairstyle patterns in the virtual reality space and select the hairstyle that best suits them by changing their movements and viewpoints.

[0709] The user sends the hairstyle pattern they have selected to the server via their terminal. Based on this selection, the server generates a specific haircut recipe. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also performs a simulation of the future hairstyle, displaying a composite image of what the long bob will look like in three months, for example.

[0710] The generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can bring this haircut recipe to the salon and provide specific instructions to the hairdresser. For example, User A uploads three images of his face - from the front, side, and back of the head - and the server generates 10 hairstyle patterns. User A selects a bob style from these, and based on this selection, the server generates a haircut recipe specifying the length of the bangs, the amount of hair on the sides, and other factors. In addition, a simulation image of a long bob three months from now is also provided. User A can show this information to the hairdresser to achieve the specific hairstyle.

[0711] An example prompt has the following format:

[0712] Use the detailed facial image data below to generate 10 hairstyle patterns that best suit the user.

[0713] Image data: [URL of user's face photo (front, side, back)]

[0714] Facial features: [Analysis results of eyes, nose, mouth, face, etc.]

[0715] Current hairstyle: [shape and color]

[0716] This system allows users to simulate their desired hairstyle in advance in a virtual reality space, and based on the results, they can provide detailed instructions to their hairdresser.

[0717] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0718] Step 1:

[0719] The user takes facial images from multiple angles and uploads them to the system using a terminal. Here, the user inputs facial images from multiple angles, such as the front, side, and back of the head. The terminal temporarily stores these image files and then sends them to the server. The input data in this case are facial image files, and the output is the transmission of image files to the server.

[0720] Step 2:

[0721] The server analyzes the received facial image and recognizes facial feature points and hairstyle information. Specifically, it identifies important points such as the eyes, nose, mouth, and face shape, and also analyzes the current hairstyle shape and color. The input for this process is the facial image sent from the device, and the output is data on facial feature points and hairstyle information.

[0722] Step 3:

[0723] The server uses a generative AI model to generate multiple hairstyle patterns based on the analyzed facial features and hairstyle information. The generative AI model uses the trained data to synthesize a natural hairstyle that suits the user's face. The input for this process is the analyzed data, and the output is multiple hairstyle patterns.

[0724] Step 4:

[0725] The server synthesizes the generated hairstyle pattern with the user's facial image to generate a composite image. These composite images are intended for the user to view in a virtual reality space. The inputs to this process are the hairstyle pattern and the user's facial image, and the output is the composite image.

[0726] Step 5:

[0727] The user wears a VR head-mounted display and checks multiple hairstyle patterns in real time within a virtual reality space. Specifically, the user can change their viewpoint within the virtual space and freely rotate the hairstyle to check it. The input for this process is a composite image sent from the server, and the output is the user's hairstyle selection information.

[0728] Step 6:

[0729] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server. The input of this process is the user's hairstyle selection information, and the output is the transmission of the selection information to the server.

[0730] Step 7:

[0731] The server generates a specific haircut recipe based on the selected hairstyle pattern. A haircut recipe typically includes information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The server also simulates the future hairstyle, displaying a composite image of what the hair will look like three months from now. The input for this process is the user's hairstyle selection information, and the output is a specific haircut recipe and a simulated image of the future hairstyle.

[0732] Step 8:

[0733] The server sends the generated haircut recipe and a simulation image of the future hairstyle to the terminal. The terminal displays this to the user, who can then take the haircut recipe to the salon and give specific instructions to the hairdresser. The input of this process is the haircut recipe and simulation image sent from the server, and the output is the display to the user.

[0734] 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.

[0735] The present invention is a system that allows a user to accurately communicate the hairstyle they desire to a hairdresser and further suggests an appropriate hairstyle taking the user's feelings into consideration, and an embodiment of this system will be described below.

[0736] First, the user accesses the system using a terminal. The user takes and uploads facial images of the front, side, and back of the head. The user follows the instructions to select the image file and send it to the server.

[0737] The device temporarily saves the facial image file selected by the user and sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. It then uses an emotion engine to analyze the user's emotions from the facial image. Specifically, it detects facial expressions and subtle changes and determines the emotion.

[0738] Based on the analysis results, the emotion engine quantifies the user's current emotional state and inputs that information into a generative AI model. The server then uses the generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. Depending on the emotion, different variations are generated, such as short hair, long hair, bob, and perm.

[0739] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way and saves each pattern as an image file. These synthesized images are sent from the server to the terminal, which then displays a list of hairstyle patterns to the user. The user can then review the displayed hairstyle patterns and select the hairstyle they like best.

[0740] When the user selects the hairstyle they want, the device sends the selection information to the server. The server then generates a specific haircut recipe based on the user's selection and the analysis results of the emotion engine. This haircut recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also simulates future hairstyles based on the user's emotion data, predicting what the hairstyle will look like three months from now, for example, and generating a composite image.

[0741] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then bring this haircut recipe to the hair salon and provide specific instructions to the hairdresser.

[0742] As a specific example, if User A uploads facial images of the front, side, and back of the head, and the emotion engine analyzes this as an "excited state," the server will use the generative AI model to prioritize suggestions for short hair and bright colors that give a lively impression. User A selects a bob style from the list, and the server generates a haircut recipe based on that selection and emotion data, including the length of the bangs and the amount of hair on the sides. Furthermore, a simulation of the hairstyle three months from now is provided, predicting changes in emotions.

[0743] In this way, by using the present invention, the user can easily select the optimal hairstyle based on their emotions and accurately convey specific instructions to the hairdresser.

[0744] The processing flow will be explained below.

[0745] Step 1:

[0746] Users access the system using a terminal, take front, side, and back images of their face, and upload them to the system.

[0747] Step 2:

[0748] The device temporarily stores the facial image files uploaded by the user, displays a confirmation message indicating that the upload is complete, and then transmits the facial image files to the server.

[0749] Step 3:

[0750] The server analyzes the received facial image. Specifically, it detects facial features (eyes, nose, mouth, contours, etc.) and identifies their positions. It also analyzes the shape and color of the hairstyle.

[0751] Step 4:

[0752] The server uses an emotion engine to recognize emotions from the user's facial image. The emotion engine detects facial expressions and subtle changes and quantifies the user's emotional state. For example, it identifies emotions such as joy, sadness, excitement, and calmness.

[0753] Step 5:

[0754] The server inputs the analyzed facial feature points and emotional data into a generative AI model, which then synthesizes a natural hairstyle that matches the user's face based on the learned data. Depending on the emotional data, different variations such as short hair, long hair, bob, and perm are generated.

[0755] Step 6:

[0756] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way, saves each pattern as an image file, and transmits the synthesized images to the terminal.

[0757] Step 7:

[0758] The terminal displays the list of hairstyle patterns received from the server to the user, who then checks the displayed multiple hairstyle patterns and selects the hairstyle that he or she likes best.

[0759] Step 8:

[0760] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server.

[0761] Step 9:

[0762] The server generates a specific haircut recipe based on the selected hairstyle pattern and emotion data, which includes details such as the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0763] Step 10:

[0764] The server also simulates future hairstyles, for example, predicting what a long bob will look like in three months' time and generating a synthetic image of it.

[0765] Step 11:

[0766] The server transmits the generated haircut recipe and a future hairstyle simulation image to the terminal.

[0767] Step 12:

[0768] The terminal displays the haircut recipe and the future hairstyle simulation received from the server to the user, who can then show the haircut recipe to the hairdresser and provide specific instructions.

[0769] As a specific example, if User A uploads facial images of the front, side, and back of the head, and the emotion engine analyzes this as an "excited state," the server will use the generative AI model to prioritize suggestions for short hair and bright colors that give a lively impression. User A selects a bob style from the list, and the server generates a haircut recipe based on that selection and emotion data, including the length of the bangs and the amount of hair on the sides. Furthermore, a simulation of the hairstyle three months from now is provided, predicting changes in emotions.

[0770] In this way, by using the present invention, the user can easily select the optimal hairstyle based on their emotions and accurately convey specific instructions to the hairdresser.

[0771] Example 2

[0772] 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."

[0773] In conventional hair style suggestion systems at beauty salons, it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, and the system does not consider the user's emotional state when proposing a hairstyle, resulting in a hairstyle that is unsatisfying. The present invention aims to improve user satisfaction by enabling users to accurately communicate their desired hairstyle and by proposing an optimal hairstyle that takes the user's emotions into consideration.

[0774] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0775] In this invention, the server includes means for uploading facial images taken from multiple angles by the user, means for the terminal to temporarily store the image files and send them to the server, means for the server to analyze the received facial images and recognize facial features and emotions, means for the server to use a generative AI model to generate and display multiple hairstyle patterns based on the emotion data and the user's facial image, means for the terminal to display the multiple hairstyle patterns to the user, means for the user to select a hairstyle pattern desired by the server, means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern, and means for the terminal to display the generated haircut recipe and future hairstyle simulation to the user. This makes it possible to suggest an optimal hairstyle based on the user's emotions and generate a specific haircut recipe.

[0776] "Facial image" refers to an image file that shows the user's face from the front, side, or back of the head.

[0777] "Device" refers to a computing device used by a user, such as a smartphone, PC, or tablet.

[0778] "Server" refers to the central processing unit that processes information received from users and generates and transmits necessary data.

[0779] "Feature points" refer to the positional information of specific parts of the face, such as the facial contours, eyes, nose, and mouth.

[0780] "Emotion" refers to the psychological state that can be analyzed from the user's facial expressions and subtle changes.

[0781] "Generative AI model" refers to an artificial intelligence model that generates hairstyle patterns using machine learning algorithms.

[0782] "Hairstyle patterns" refers to multiple different hairstyle designs created by a generative AI model.

[0783] A "haircut recipe" refers to a document that details specific treatment methods and instructions based on a hairstyle pattern.

[0784] "Future hairstyle simulation" refers to a technology that predicts what a user's hairstyle will look like after a certain period of time and displays it as a composite image.

[0785] The present invention is a system that allows a user to accurately communicate the hairstyle they want to a hairdresser and further suggests an appropriate hairstyle taking the user's feelings into consideration. An embodiment of the system will be described below.

[0786] First, the user accesses the system's webpage on their device (such as a smartphone or PC). This webpage provides an interface for users to upload facial images. The user takes a picture of their face from the front, side, or back of the head, and clicks the "Upload" button to send the selected image file to the system.

[0787] The device temporarily stores the facial image file selected by the user in local storage. The stored image file is then sent to the server as an HTTP POST request using JavaScript. This communication is asynchronous, using an Ajax library (e.g., jQuery).

[0788] The server passes the received facial images to an analysis program written in Python. OpenCV and Dlib libraries are used for facial analysis, which detects facial features and recognizes emotions by analyzing facial expressions and subtle changes in the facial images. Emotion recognition uses a cloud service's emotion analysis API (for example, Azure's emotion analysis API). The results of the emotion analysis are extracted as numerical data.

[0789] The server inputs this quantified emotion data into a generative AI model (such as StyleGAN). The generative AI model is built using deep learning frameworks such as TensorFlow and PyTorch, and generates multiple hairstyle patterns to be synthesized onto the user's face based on the emotion data and facial images. In this process, an appropriate prompt sentence is input into the AI ​​model. An example of a prompt sentence is, "The user's emotional state is excited. Generate a hairstyle pattern with a short hair style or a bright color that gives a lively impression."

[0790] The generated hairstyle patterns are naturally combined with the facial image and saved as an image file. These combined images are sent from the server to the device as an HTTP response. The device's browser displays a list of the received hairstyle pattern images, allowing the user to select the desired hairstyle from multiple options.

[0791] When a user selects a specific hairstyle pattern, that information is sent from the device to the server. The server generates a specific haircut recipe based on the selected hairstyle pattern and emotional data. The haircut recipe includes detailed instructions on the length of the bangs, the amount of hair on the sides, and coloring. Furthermore, a future hairstyle simulation is performed, and an image of the predicted hairstyle three months from now is generated.

[0792] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user, who can then print or download the haircut recipe and bring it to the hair salon to provide specific hairstyle instructions to the hairdresser.

[0793] In this way, by using the present invention, the user can select the hairstyle that best suits his / her emotions and face, while providing accurate beauty instructions to the hairdresser.

[0794] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0795] Step 1:

[0796] A user accesses the system and uploads a facial image.

[0797] Users access the system's web page using a device such as a smartphone or PC. They click the "Upload Face Image" button on the web page, select a face image from the front, side, or back of the head, and upload it. At this time, the input data is the user's face image file, and the output is a message indicating successful file upload. Specifically, an image file is selected using an HTML form, and the image upload process is carried out using JavaScript.

[0798] Step 2:

[0799] The device temporarily saves the image file and sends it to the server.

[0800] The facial image file is temporarily saved in the device's local storage. After saving, an HTTP POST request is created using the Ajax library, and the image file is sent to the server. At this time, the input data is the saved image file, and the output is the file sent to the server. Specifically, asynchronous communication is performed using JavaScript and Ajax.

[0801] Step 3:

[0802] The server analyzes the facial image and recognizes the features and emotions.

[0803] The server passes the received facial images to an analysis program written in Python. It uses Python's OpenCV and Dlib libraries to detect facial feature points (eyes, nose, mouth, etc.). Based on this feature point data, it uses Azure's emotion analysis API to analyze the user's emotions from their facial expressions. The input data is the user's facial image, and the output is feature point data and emotion data. Specific operations include image preprocessing (resizing, grayscale conversion), feature point extraction, and making requests to the cloud API.

[0804] Step 4:

[0805] The server inputs the emotion data into the AI ​​model to generate a hairstyle pattern.

[0806] The results of the sentiment analysis are quantified and input into a generative AI model built using Python's TensorFlow or PyTorch. The generative AI model (for example, StyleGAN) generates multiple hairstyle patterns based on the input data. In this process, an appropriate prompt sentence is input into the AI ​​model. The input data is feature point data and emotion data, and the output is multiple hairstyle pattern images. Specifically, the emotion data is quantified, input into the AI ​​model, and hairstyle patterns are generated.

[0807] Step 5:

[0808] The server synthesizes the generated hairstyle pattern and sends it to the device.

[0809] The generated hairstyle pattern is composited with the user's facial image and output in a natural way. The composite image is saved on the server and sent to the device as an HTTP response. The input data is the generated hairstyle pattern and the user's facial image, and the output is a composite image file. A Python image processing library is used for the composite.

[0810] Step 6:

[0811] The device displays hairstyle patterns to the user.

[0812] The device's browser displays a list of composite images received from the server. Using HTML, CSS, and JavaScript, the images are displayed in a format that is easy for the user to view. The input data is the composite image file sent from the server, and the output is a list of hairstyles that is displayed to the user. Specifically, the images are loaded and displayed.

[0813] Step 7:

[0814] The user selects the desired hairstyle.

[0815] The user selects the desired hairstyle pattern by clicking on it from the displayed patterns. Information on the selected hairstyle pattern is sent from the device to the server. The input data is the ID of the hairstyle pattern clicked by the user, and the output is the transmission of the selected information to the server. Specific operations include processing the click event using JavaScript and sending data.

[0816] Step 8:

[0817] The device sends the selection information to the server

[0818] The device sends data including the ID of the selected image to the server as an HTTP POST request. The input data is the ID of the selected image, and the output is a message to the server indicating that the request was sent successfully. Specifically, asynchronous communication is performed using Ajax.

[0819] Step 9:

[0820] The server generates a haircut recipe and a simulation of the future hairstyle.

[0821] The server generates a specific haircut recipe (bangs length, amount of hair on the sides, coloring instructions, etc.) based on the selected hairstyle pattern and emotional data. It also performs a future hairstyle simulation and generates a predicted hairstyle three months from now. The input data is the selected hairstyle pattern and emotional data, and the output is a haircut recipe and predicted hairstyle image. Specifically, data analysis and model inference processing are performed.

[0822] Step 10:

[0823] Send the results generated by the server to the device

[0824] The generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal as an HTTP response. The input data are the haircut recipe and simulation image, and the output is the response sent to the terminal. Specifically, data packaging and HTTP transmission processing are performed.

[0825] Step 11:

[0826] The device displays the results to the user

[0827] The terminal displays the received cutting recipe and simulation image to the user. It uses HTML and JavaScript to provide an interface that the user can easily check. The input data is the cutting recipe and simulation image received from the server, and the output is what is displayed to the user. Specifically, data loading and display processing are carried out.

[0828] (Application example 2)

[0829] 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."

[0830] In conventional hair styling suggestion systems at hair salons, the desired hairstyle image often does not match between the user and the hairdresser, resulting in a decrease in user satisfaction. Furthermore, there was no system that could analyze the user's emotions from a facial image and suggest the optimal hairstyle based on that. This made it difficult to suggest a hairstyle that matched the user's mood and preferences at the time, which further led to dissatisfaction.

[0831] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for taking and uploading a facial image of a customer using a tablet or smartphone, means for analyzing emotions from the facial image and generating a hairstyle pattern based on the emotion, and means for displaying the generated hairstyle pattern to the customer. This makes it possible to suggest a hairstyle that is suited to the user's current emotional state, thereby improving user satisfaction.

[0832] A "user" is an individual who uses the hairstyle suggestion system.

[0833] A "face image" is a photograph of the user's face taken from multiple angles, such as the front, side, and back of the head.

[0834] The "server" is a computer on the network that receives and analyzes data and generates hairstyle patterns using a generative AI model.

[0835] A "generative AI model" is an artificial intelligence technology that generates hairstyle patterns based on a user's facial image and emotional data.

[0836] "Hairstyle patterns" are digital images of different types of hairstyles that are composited onto the user's facial image.

[0837] A "terminal" is a hardware device such as a tablet or smartphone that is operated by a user.

[0838] "Emotion" refers to the psychological state of the user that is analyzed from a facial image, and the analysis results are used to suggest hairstyles.

[0839] A "cut recipe" is a set of specific instructions for a hairstyle, including the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0840] A "future hairstyle simulation" is a digital image that predicts how a user's hairstyle will change over time.

[0841] A specific embodiment for carrying out this invention will be described below. First, a user accesses the system using a tablet or smartphone installed in a beauty salon. The user takes facial images of the front, side, and back of the head and uploads them to the system.

[0842] The hardware used is a tablet or smartphone camera, and the software is an application for capturing and uploading facial images. The system temporarily stores the facial image file selected by the user and sends it to a server.

[0843] The server analyzes the received facial image and recognizes facial features and hairstyle information. It also uses an emotion engine to analyze the user's emotions from the facial image. Specifically, it detects facial expressions and subtle changes and determines the emotion. The software used includes OpenCV (facial image analysis) and Keras (emotion engine).

[0844] Next, the server uses the generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. Different variations such as short hair, long hair, bob, and perm are generated depending on the emotion. These hairstyle patterns are naturally combined with the user's facial image, and each pattern is saved as an image file. This is what the generative AI model is used for.

[0845] The server sends the generated hairstyle patterns to a tablet or smartphone, which then displays them to the user. The user can then review the displayed hairstyle patterns and select the one they like best. The device then sends the selection information to the server.

[0846] The server generates a specific haircut recipe based on the hairstyle pattern selected by the user and the results of emotion analysis. This haircut recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also performs a simulation of future hairstyles, predicting what the hairstyle will look like three months from now, for example, and generates a composite image. This allows the user to receive a haircut at the salon that takes future hairstyles into consideration.

[0847] As a specific example, if user A takes a picture of his face with a tablet and the facial image is analyzed by the emotion engine as being in a "relaxed state," the server will use the generative AI model to preferentially suggest hairstyle patterns that give a calm impression. An example of a prompt sentence in this case is as follows:

[0848] "Input the user's facial image into an emotion engine and generative AI model to suggest hairstyle patterns that suit their relaxed state."

[0849] This allows the user to be suggested a hairstyle that is best suited to their current psychological state, improving satisfaction at the beauty salon.

[0850] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0851] Step 1:

[0852] First, the user accesses the system using a tablet or smartphone installed in the beauty salon. The user takes facial images of the front, side, and back of the head and uploads them to the system. The input is the facial image taken by the user, and the output is the uploaded facial image data. Specifically, the user takes a facial image using the camera application on the tablet or smartphone and sends it to the server.

[0853] Step 2:

[0854] The device temporarily stores the facial image file selected by the user and sends it to the server. The input is the facial image taken and uploaded by the user, and the output is the facial image data sent to the server. Specifically, the device transfers the temporarily stored image file to the server via an HTTP request.

[0855] Step 3:

[0856] The server analyzes the received facial image and recognizes facial feature points and hairstyle information. The input is the facial image data sent to the server, and the output is the analyzed facial feature point data and hairstyle information.

[0857] Specifically, it uses OpenCV to analyze facial images, extract feature points for each part of the face, recognize the shape and contours of the face, and extract information about the current hairstyle.

[0858] Step 4:

[0859] The server uses an emotion engine to analyze emotions from the user's facial image. The input is analyzed facial feature point data, and the output is analyzed emotion data. Specifically, the emotion engine using Keras is used to analyze emotions from facial expressions, and the results are obtained as numerical data.

[0860] Step 5:

[0861] The server uses a generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. The input is the user's facial image and analyzed emotional data, and the output is multiple generated hairstyle patterns. Specifically, a prompt sentence is generated based on the emotional data, and this is input into the generative AI model to automatically generate a hairstyle pattern that matches the emotion.

[0862] Step 6:

[0863] The server synthesizes the generated hairstyle pattern onto the user's facial image in a natural way and saves each pattern as an image file. The input is the user's facial image and the generated hairstyle pattern, and the output is an image file of the synthesized hairstyle pattern. Specifically, the server uses a synthesis algorithm to superimpose the generated hairstyle pattern onto the user's facial image.

[0864] Step 7:

[0865] The server sends the generated hairstyle patterns to a tablet or smartphone, and the device displays them as a list. The input is an image file of the synthesized hairstyle pattern, and the output is a list of hairstyle patterns displayed on the device. Specifically, the image file of the hairstyle pattern is sent to the device as an HTTP response, and the display application renders it.

[0866] Step 8:

[0867] The user checks the displayed hairstyle patterns and selects the hairstyle they like best. The input is the displayed hairstyle patterns, and the output is the information on the hairstyle pattern selected by the user. Specifically, the user selects the desired hairstyle using touch operations or selection buttons.

[0868] Step 9:

[0869] The terminal sends the user's selection information to the server. The input is the hairstyle pattern information selected by the user, and the output is the selection information sent to the server. Specifically, the user's selection information is transmitted to the server as an HTTP request.

[0870] Step 10:

[0871] The server generates a specific haircut recipe based on the hairstyle pattern selected by the user and the emotion analysis results. The input is the information on the selected hairstyle pattern and emotion data, and the output is a specific haircut recipe. Specifically, the server automatically generates a haircut recipe that includes the length of the bangs, the amount of hair on the sides, coloring instructions, etc.

[0872] Step 11:

[0873] The server also simulates future hairstyles, predicting what the user's hairstyle will look like in three months, for example, and generates a synthetic image. The input is the user's hairstyle pattern and predicted growth data, and the output is a simulated image of the future hairstyle. Specifically, the server predicts the future hairstyle using an algorithm that simulates hair growth.

[0874] Step 12:

[0875] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which then displays them to the user. The input is the haircut recipe and future hairstyle simulation image, and the output is the information displayed on the terminal. Specifically, the haircut recipe and simulation image are sent as an HTTP response, and the terminal presents them to the user using an application that displays them.

[0876] Through the above processing steps, the user is suggested a hairstyle that suits their current psychological state, improving their satisfaction at the beauty salon.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] [Fourth embodiment]

[0881] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0882] 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.

[0883] 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).

[0884] 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.

[0885] 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.

[0886] 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).

[0887] 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. 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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."

[0894] The present invention is a system for allowing a user to accurately communicate a desired hairstyle to a hairdresser, and can be implemented as follows.

[0895] First, the user accesses the system using a terminal and uploads facial images taken from multiple angles, such as the front, side, and back of the head. The user then follows the instructions to select the image file and send it to the system.

[0896] Next, the device temporarily saves the image file selected by the user and then sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. Specifically, it identifies important points such as the eyes, nose, mouth, and face shape, and also analyzes the current hairstyle shape and color.

[0897] The server then uses a generative AI model based on the analyzed data to generate multiple hairstyle patterns. The generative AI model synthesizes a natural hairstyle that suits the user's face based on the trained data. For example, different variations such as short hair, long hair, bob, and perm are generated.

[0898] The server then combines the generated hairstyle patterns with the user's facial image, saves each pattern as an image, and transmits the combined image to the terminal.

[0899] The terminal displays the list of hairstyle patterns received from the server to the user, who can then check the displayed hairstyle patterns and select the hairstyle that he or she likes best.

[0900] When the user selects the desired hairstyle, the device sends that information to the server. The server then generates a specific haircut recipe based on the selected hairstyle. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The device also simulates future hairstyles, displaying a composite image of what a long bob will look like in three months.

[0901] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then bring this haircut recipe to the hair salon and provide specific instructions to the hairdresser.

[0902] As a specific example, User A uploads three images of his face - one from the front, one from the side, and one from the back of his head - and the server generates ten different hairstyle patterns. User A selects a bob style from the images, and the server generates a haircut recipe based on that selection, including the length of the bangs and the amount of hair on the sides. In addition, a simulated image of a long bob three months from now is also provided. User A can show this information to a hairdresser to achieve the desired hairstyle.

[0903] In this way, by using the present invention, the user can simulate the hairstyle they want in advance and, based on the results, give detailed instructions to the hairdresser.

[0904] The processing flow will be explained below.

[0905] Step 1:

[0906] The user accesses the system using a terminal, takes three images of their face (front, side, and back of the head), and uploads each image to the system.

[0907] Step 2:

[0908] The device temporarily stores the facial image files uploaded by the user, displays a confirmation message indicating that the upload is complete, and then transmits the facial image files to the server.

[0909] Step 3:

[0910] The server analyzes the received facial image. Specifically, it detects facial features (eyes, nose, mouth, contours, etc.) and identifies their positions. It also analyzes the shape and color of the hairstyle.

[0911] Step 4:

[0912] The server uses a generative AI model based on the analysis results to generate multiple hairstyle patterns to be combined with the user's facial image. The generative AI model uses the learned data to create a natural hairstyle. Different variations such as short hair, long hair, bob, and perm are generated.

[0913] Step 5:

[0914] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way, saves each pattern as an image file, and transmits the synthesized images to the terminal.

[0915] Step 6:

[0916] The terminal displays the list of hairstyle patterns received from the server to the user, who then checks the displayed multiple hairstyle patterns and selects the hairstyle that he or she likes best.

[0917] Step 7:

[0918] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server.

[0919] Step 8:

[0920] The server generates a specific haircut recipe based on the selected hairstyle pattern, which includes details such as the length of the bangs, the amount of hair on the sides, and coloring instructions.

[0921] Step 9:

[0922] The server also simulates future hairstyles, for example, predicting what a long bob will look like in three months' time and generating a synthetic image of it.

[0923] Step 10:

[0924] The server transmits the generated haircut recipe and a future hairstyle simulation image to the terminal.

[0925] Step 11:

[0926] The terminal displays the haircut recipe and the future hairstyle simulation received from the server to the user, who can then show the haircut recipe to the hairdresser and provide specific instructions.

[0927] Example 1

[0928] 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."

[0929] With conventional systems, it was difficult for users to communicate their desired hairstyle in detail to the hairdresser, resulting in the hairstyle often not being exactly what they wanted.In addition, the process of selecting the hairstyle that best suits the user's face shape and characteristics was complicated, time-consuming, and laborious.

[0930] 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.

[0931] In this invention, the server includes means for analyzing the received facial image and recognizing facial features and hairstyle information, means for generating multiple hairstyle patterns using a generative AI model based on the analyzed data, and means for combining the generated hairstyle patterns with the facial image and transmitting them to the terminal. This allows the user to visually simulate a desired hairstyle in advance and to provide specific instructions to the hairdresser based on a detailed haircut recipe.

[0932] "User" refers to an individual who utilizes the system to simulate their own hairstyle.

[0933] "Terminal" refers to the electronic device that a User uses to access the System, upload images, and view results.

[0934] "Facial images" refer to digital images of a user's face taken from multiple angles.

[0935] "Server" refers to a computer system that analyzes received image data and generates hairstyle patterns using a generative AI model.

[0936] "Feature points" refer to important points in a facial image, such as the eyes, nose, mouth, and contours.

[0937] "Hairstyle information" refers to data regarding the style and color of a user's current hairstyle.

[0938] A "generative AI model" refers to an algorithm that generates hairstyle patterns that naturally fit the user's face based on learned data.

[0939] "Hairstyle patterns" refer to multiple hairstyle variations generated by a generative AI model.

[0940] A "haircut recipe" refers to detailed instructions for a hairdresser to perform a specific cut and color based on the selected hairstyle.

[0941] "Future hairstyle simulation" refers to an image that predicts the future shape and state of the hairstyle selected by the user.

[0942] This invention is a system that allows users to accurately communicate their desired hairstyle to their hairdresser. The system allows users to upload facial images taken from multiple angles, and uses AI technology to generate and display various hairstyle patterns for those facial images, and provides a specific haircut recipe based on the hairstyle pattern that the user is satisfied with.

[0943] First, the user accesses the system using a terminal and uploads facial images taken from the front, side, and back of the head. Following the instructions displayed on the screen, the user clicks the file selection button to select the image file, and then presses the send button to send the image to the system.

[0944] The device temporarily stores the uploaded facial image and then sends it to the server using the HTTP POST method with the REST API. The server analyzes the received facial image and uses face detection algorithms such as OpenCV or Dlib to recognize facial features (eyes, nose, mouth, contours, etc.) and current hairstyle information (shape and color).

[0945] After the analysis is complete, the server uses a generative AI model (e.g., GAN or DCGAN) based on the analyzed data to generate multiple hairstyle patterns. These AI models are trained in advance with a large amount of hairstyle data and synthesize hairstyles that fit the user's face naturally. An example of a prompt is, "Please generate hairstyles such as short hair, bob, and perm that suit the user's face."

[0946] The generated hairstyle pattern is saved on the server and simultaneously composited onto the user's face image. The composite image is generated using an image processing library (e.g., PIL or OpenCV) and saved as multiple image files. These files are saved with names such as "shorthair.png" and "bob.png."

[0947] Once the composite image is complete, the server sends it to the device, which then displays a list of the received hairstyle patterns for the user to easily review. The user can then select the hairstyle they like best from the displayed patterns.

[0948] After the user selects the desired hairstyle, the device sends that information to the server. The server then generates a specific haircut recipe based on the selected hairstyle. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The server also performs future hairstyle simulations, generating a composite image of what the long bob will look like in three months, for example.

[0949] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then take this information to the hair salon and provide specific instructions to the hairdresser.

[0950] As a specific example, User A uploads three images of his face - one from the front, one from the side, and one from the back of his head - and the server generates ten different hairstyle patterns. User A selects a bob style from the images, and the server generates a haircut recipe based on that selection, including the length of the bangs and the amount of hair on the sides. In addition, a simulated image of a long bob three months from now is also provided. User A can show this information to a hairdresser to achieve the desired hairstyle.

[0951] An example of a prompt sentence could be, "Generate an appropriate hairstyle pattern based on multiple face images provided by the user. For example, generate variations such as short hair, long hair, bob, perm, etc., and combine them naturally with the user's face."

[0952] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0953] Step 1:

[0954] The user accesses the system using a terminal and uploads facial images taken from the front, side, and back of the head. The user follows the on-screen instructions, clicks the file selection button, and selects the image file. Then, clicks the send button to send the facial image to the system. The input is the image file uploaded by the user, and the output is the data of the image file sent to the server.

[0955] Step 2:

[0956] The device temporarily saves the image file selected by the user. Then, it issues an HTTP request to send the saved image file to the server. Specifically, the device uses the REST API to send the image data to the server using the POST method. The input is the temporarily saved image file, and the output is the HTTP request sent to the server.

[0957] Step 3:

[0958] The server begins processing the received image file. Specifically, it first identifies the face region from the image using a face detection algorithm (e.g., OpenCV or Dlib). Next, it detects facial feature points (eyes, nose, mouth, face contours, etc.) with high accuracy. It also analyzes the shape and color of the current hairstyle. The input is the received face image, and the output is the analyzed facial feature point data and hairstyle information.

[0959] Step 4:

[0960] The server generates multiple hairstyle patterns using a generative AI model (e.g., GAN or DCGAN) based on the analyzed data. The AI ​​model is trained in advance with a large amount of hairstyle data and synthesizes a hairstyle that fits the user's face naturally. An example of a prompt is "Please generate hairstyles such as short hair, bob, and perm that suit the user's face." The input is the analyzed facial feature point data and the prompt, and the output is the generated multiple hairstyle patterns.

[0961] Step 5:

[0962] The server composites the generated hairstyle pattern onto the user's face image. This composite process uses an image processing library (e.g., PIL, OpenCV). The composite results are generated as multiple image files and saved on the server. Each file is saved with a name such as "shorthair.png" or "bob.png." The input is the generated hairstyle pattern and the user's face image, and the output is an image file of the composite hairstyle pattern.

[0963] Step 6:

[0964] The server sends the image files of the synthesized hairstyle patterns to the device. The device displays the received images on the application's UI so that the user can check them. Specifically, it displays a list in thumbnail format from which the user can select each hairstyle pattern. The input is the image files of the hairstyle patterns received from the server, and the output is multiple hairstyle patterns displayed on the UI.

[0965] Step 7:

[0966] The user checks the displayed hairstyle patterns and selects the hairstyle they like best. After selection, the terminal sends information about the selected hairstyle pattern to the server. The input is the hairstyle pattern selected by the user, and the output is the selection information sent to the server.

[0967] Step 8:

[0968] The server generates a specific haircut recipe based on the selected hairstyle pattern. The haircut recipe includes details such as bang length, side volume, and coloring instructions. These instructions are created using a dedicated template. The input is the user-selected hairstyle pattern, and the output is the generated haircut recipe.

[0969] Step 9:

[0970] The server performs a future hairstyle simulation. For example, to generate a composite image of what a long bob will look like three months from now, the generative AI model is used again. The simulation results are generated as an image file and saved on the server. The input is the hairstyle pattern selected by the user and the future simulation period, and the output is a composite future hairstyle simulation image.

[0971] Step 10:

[0972] The server sends the generated haircut recipe and a future hairstyle simulation image to the terminal, which displays it to the user, who can then take it to the hair salon. The input is the haircut recipe and simulation image received from the server, and the output is the haircut recipe and simulation image displayed to the user.

[0973] (Application example 1)

[0974] 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."

[0975] Conventional hairstyle simulation systems make it difficult for users to actually see the hairstyle they want. It's also difficult for users to communicate their specific hairstyle image to the hairdresser, resulting in the hair often not turning out as desired. Furthermore, since it's not possible to try out multiple hairstyle patterns in real time, selecting the optimal hairstyle takes time. There is a need for a system that solves these problems, allowing users to see multiple hairstyle patterns in real time in a virtual reality space and present specific haircut recipes to the hairdresser.

[0976] 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.

[0977] In this invention, the server includes: means for uploading facial images taken from multiple angles by the user; means for analyzing the received facial images by the server and recognizing facial features and hairstyle information; means for the server to use a generated AI model to synthesize multiple hairstyle patterns and display them naturally on the user's facial image; means for the server to use a display device to allow the user to check hairstyle patterns in real time in a virtual reality space; means for the terminal to display multiple hairstyle patterns to the user; means for the user to select a hairstyle pattern desired by the user; means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern; and means for the terminal to display the generated haircut recipe and future hairstyle simulation to the user. This allows the user to check multiple hairstyles in real time in the virtual reality space, making it easier for the user to select the optimal hairstyle and also enabling the user to accurately give specific haircut instructions to the hairdresser.

[0978] A "user" is an individual who uses the system to perform a hairstyle simulation.

[0979] "Facial images taken from multiple angles" are photographs of the user's face taken from different angles, such as from the front, side, or back of the head.

[0980] A "server" is a computer system that analyzes data via the Internet and generates and provides hairstyle patterns.

[0981] "Facial feature points" refer to the main parts of the face, such as the eyes, nose, mouth, and contours, and are points used to analyze their position and shape.

[0982] "Hairstyle information" is data relating to the characteristics of the user's hair, such as the shape and color of the current hairstyle.

[0983] A "generative AI model" is an artificial intelligence model that generates new hairstyles based on learned data.

[0984] A "hairstyle pattern" is a variation of a different hairstyle that is composited onto the user's face.

[0985] A "virtual reality space" is a computer-generated 3D virtual environment that users experience using a VR head-mounted display or similar device.

[0986] A "display device" is a device for checking hairstyle patterns in real time within a virtual reality space, such as a VR head-mounted display.

[0987] A "terminal" is a device such as a computer or smartphone that a user uses to operate the system.

[0988] A "haircut recipe" is information detailing specific instructions for a hairdresser to perform a haircut based on a selected hairstyle pattern.

[0989] A "future hairstyle simulation" is a composite image that predicts the growth and changes in hairstyle over the next few months, for example, and allows the user to check it in advance.

[0990] The present invention is a system that allows a user to accurately communicate their desired hairstyle to a hairdresser, and in particular provides a real-time hairstyle simulation in a virtual reality space. A method for implementing this will be described in detail below.

[0991] First, the user uses facial images taken from multiple angles, including the front, side, and back of the head, and uploads these facial images to the system using a terminal. Specifically, the user follows the instructions to select an image file and send it to the system.

[0992] Next, the device temporarily saves the facial image file selected by the user and then sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. In particular, it identifies important points such as the eyes, nose, mouth, and face shape. It also analyzes the current hairstyle shape and color.

[0993] The server then uses a generative AI model based on the analyzed data to generate multiple hairstyle patterns. The generative AI model synthesizes a natural hairstyle that suits the user's face based on the trained data. For example, it generates different variations such as short hair, long hair, bob, and perm.

[0994] The server then synthesizes the generated hairstyle patterns onto the user's facial image, allowing the user to view these synthesized images in real time in a virtual reality space.The user can use a VR head-mounted display (e.g., Oculus Rift) to view the hairstyle patterns in the virtual reality space and select the hairstyle that best suits them by changing their movements and viewpoints.

[0995] The user sends the hairstyle pattern they have selected to the server via their terminal. Based on this selection, the server generates a specific haircut recipe. This recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also performs a simulation of the future hairstyle, displaying a composite image of what the long bob will look like in three months, for example.

[0996] The generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can bring this haircut recipe to the salon and provide specific instructions to the hairdresser. For example, User A uploads three images of his face - from the front, side, and back of the head - and the server generates 10 hairstyle patterns. User A selects a bob style from these, and based on this selection, the server generates a haircut recipe specifying the length of the bangs, the amount of hair on the sides, and other factors. In addition, a simulation image of a long bob three months from now is also provided. User A can show this information to the hairdresser to achieve the specific hairstyle.

[0997] An example prompt has the following format:

[0998] Use the detailed facial image data below to generate 10 hairstyle patterns that best suit the user.

[0999] Image data: [URL of user's face photo (front, side, back)]

[1000] Facial features: [Analysis results of eyes, nose, mouth, face, etc.]

[1001] Current hairstyle: [shape and color]

[1002] This system allows users to simulate their desired hairstyle in advance in a virtual reality space, and based on the results, they can provide detailed instructions to their hairdresser.

[1003] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1004] Step 1:

[1005] The user takes facial images from multiple angles and uploads them to the system using a terminal. Here, the user inputs facial images from multiple angles, such as the front, side, and back of the head. The terminal temporarily stores these image files and then sends them to the server. The input data in this case are facial image files, and the output is the transmission of image files to the server.

[1006] Step 2:

[1007] The server analyzes the received facial image and recognizes facial feature points and hairstyle information. Specifically, it identifies important points such as the eyes, nose, mouth, and face shape, and also analyzes the current hairstyle shape and color. The input for this process is the facial image sent from the device, and the output is data on facial feature points and hairstyle information.

[1008] Step 3:

[1009] The server uses a generative AI model to generate multiple hairstyle patterns based on the analyzed facial features and hairstyle information. The generative AI model uses the trained data to synthesize a natural hairstyle that suits the user's face. The input for this process is the analyzed data, and the output is multiple hairstyle patterns.

[1010] Step 4:

[1011] The server synthesizes the generated hairstyle pattern with the user's facial image to generate a composite image. These composite images are intended for the user to view in a virtual reality space. The inputs to this process are the hairstyle pattern and the user's facial image, and the output is the composite image.

[1012] Step 5:

[1013] The user wears a VR head-mounted display and checks multiple hairstyle patterns in real time within a virtual reality space. Specifically, the user can change their viewpoint within the virtual space and freely rotate the hairstyle to check it. The input for this process is a composite image sent from the server, and the output is the user's hairstyle selection information.

[1014] Step 6:

[1015] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server. The input of this process is the user's hairstyle selection information, and the output is the transmission of the selection information to the server.

[1016] Step 7:

[1017] The server generates a specific haircut recipe based on the selected hairstyle pattern. A haircut recipe typically includes information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. The server also simulates the future hairstyle, displaying a composite image of what the hair will look like three months from now. The input for this process is the user's hairstyle selection information, and the output is a specific haircut recipe and a simulated image of the future hairstyle.

[1018] Step 8:

[1019] The server sends the generated haircut recipe and a simulation image of the future hairstyle to the terminal. The terminal displays this to the user, who can then take the haircut recipe to the salon and give specific instructions to the hairdresser. The input of this process is the haircut recipe and simulation image sent from the server, and the output is the display to the user.

[1020] 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.

[1021] The present invention is a system that allows a user to accurately communicate the hairstyle they desire to a hairdresser and further suggests an appropriate hairstyle taking the user's feelings into consideration, and an embodiment of this system will be described below.

[1022] First, the user accesses the system using a terminal. The user takes and uploads facial images of the front, side, and back of the head. The user follows the instructions to select the image file and send it to the server.

[1023] The device temporarily saves the facial image file selected by the user and sends it to the server. The server analyzes the received facial image and recognizes facial features and hairstyle information. It then uses an emotion engine to analyze the user's emotions from the facial image. Specifically, it detects facial expressions and subtle changes and determines the emotion.

[1024] Based on the analysis results, the emotion engine quantifies the user's current emotional state and inputs that information into a generative AI model. The server then uses the generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. Depending on the emotion, different variations are generated, such as short hair, long hair, bob, and perm.

[1025] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way and saves each pattern as an image file. These synthesized images are sent from the server to the terminal, which then displays a list of hairstyle patterns to the user. The user can then review the displayed hairstyle patterns and select the hairstyle they like best.

[1026] When the user selects the hairstyle they want, the device sends the selection information to the server. The server then generates a specific haircut recipe based on the user's selection and the analysis results of the emotion engine. This haircut recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also simulates future hairstyles based on the user's emotion data, predicting what the hairstyle will look like three months from now, for example, and generating a composite image.

[1027] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user. The user can then bring this haircut recipe to the hair salon and provide specific instructions to the hairdresser.

[1028] As a specific example, if User A uploads facial images of the front, side, and back of the head, and the emotion engine analyzes this as an "excited state," the server will use the generative AI model to prioritize suggestions for short hair and bright colors that give a lively impression. User A selects a bob style from the list, and the server generates a haircut recipe based on that selection and emotion data, including the length of the bangs and the amount of hair on the sides. Furthermore, a simulation of the hairstyle three months from now is provided, predicting changes in emotions.

[1029] In this way, by using the present invention, the user can easily select the optimal hairstyle based on their emotions and accurately convey specific instructions to the hairdresser.

[1030] The processing flow will be explained below.

[1031] Step 1:

[1032] Users access the system using a terminal, take front, side, and back images of their face, and upload them to the system.

[1033] Step 2:

[1034] The device temporarily stores the facial image files uploaded by the user, displays a confirmation message indicating that the upload is complete, and then transmits the facial image files to the server.

[1035] Step 3:

[1036] The server analyzes the received facial image. Specifically, it detects facial features (eyes, nose, mouth, contours, etc.) and identifies their positions. It also analyzes the shape and color of the hairstyle.

[1037] Step 4:

[1038] The server uses an emotion engine to recognize emotions from the user's facial image. The emotion engine detects facial expressions and subtle changes and quantifies the user's emotional state. For example, it identifies emotions such as joy, sadness, excitement, and calmness.

[1039] Step 5:

[1040] The server inputs the analyzed facial feature points and emotional data into a generative AI model, which then synthesizes a natural hairstyle that matches the user's face based on the learned data. Depending on the emotional data, different variations such as short hair, long hair, bob, and perm are generated.

[1041] Step 6:

[1042] The server then synthesizes the generated hairstyle patterns onto the user's facial image in a natural way, saves each pattern as an image file, and transmits the synthesized images to the terminal.

[1043] Step 7:

[1044] The terminal displays the list of hairstyle patterns received from the server to the user, who then checks the displayed multiple hairstyle patterns and selects the hairstyle that he or she likes best.

[1045] Step 8:

[1046] When the user selects a desired hairstyle pattern, the terminal transmits the selection information to the server.

[1047] Step 9:

[1048] The server generates a specific haircut recipe based on the selected hairstyle pattern and emotion data, which includes details such as the length of the bangs, the amount of hair on the sides, and coloring instructions.

[1049] Step 10:

[1050] The server also simulates future hairstyles, for example, predicting what a long bob will look like in three months' time and generating a synthetic image of it.

[1051] Step 11:

[1052] The server transmits the generated haircut recipe and a future hairstyle simulation image to the terminal.

[1053] Step 12:

[1054] The terminal displays the haircut recipe and the future hairstyle simulation received from the server to the user, who can then show the haircut recipe to the hairdresser and provide specific instructions.

[1055] As a specific example, if User A uploads facial images of the front, side, and back of the head, and the emotion engine analyzes this as an "excited state," the server will use the generative AI model to prioritize suggestions for short hair and bright colors that give a lively impression. User A selects a bob style from the list, and the server generates a haircut recipe based on that selection and emotion data, including the length of the bangs and the amount of hair on the sides. Furthermore, a simulation of the hairstyle three months from now is provided, predicting changes in emotions.

[1056] In this way, by using the present invention, the user can easily select the optimal hairstyle based on their emotions and accurately convey specific instructions to the hairdresser.

[1057] Example 2

[1058] 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."

[1059] In conventional hair style suggestion systems at beauty salons, it is difficult for users to accurately communicate their desired hairstyle to the hairdresser, and the system does not consider the user's emotional state when proposing a hairstyle, resulting in a hairstyle that is unsatisfying. The present invention aims to improve user satisfaction by enabling users to accurately communicate their desired hairstyle and by proposing an optimal hairstyle that takes the user's emotions into consideration.

[1060] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1061] In this invention, the server includes means for uploading facial images taken from multiple angles by the user, means for the terminal to temporarily store the image files and send them to the server, means for the server to analyze the received facial images and recognize facial features and emotions, means for the server to use a generative AI model to generate and display multiple hairstyle patterns based on the emotion data and the user's facial image, means for the terminal to display the multiple hairstyle patterns to the user, means for the user to select a hairstyle pattern desired by the server, means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern, and means for the terminal to display the generated haircut recipe and future hairstyle simulation to the user. This makes it possible to suggest an optimal hairstyle based on the user's emotions and generate a specific haircut recipe.

[1062] "Facial image" refers to an image file that shows the user's face from the front, side, or back of the head.

[1063] "Device" refers to a computing device used by a user, such as a smartphone, PC, or tablet.

[1064] "Server" refers to the central processing unit that processes information received from users and generates and transmits necessary data.

[1065] "Feature points" refer to the positional information of specific parts of the face, such as the facial contours, eyes, nose, and mouth.

[1066] "Emotion" refers to the psychological state that can be analyzed from the user's facial expressions and subtle changes.

[1067] "Generative AI model" refers to an artificial intelligence model that generates hairstyle patterns using machine learning algorithms.

[1068] "Hairstyle patterns" refers to multiple different hairstyle designs created by a generative AI model.

[1069] A "haircut recipe" refers to a document that details specific treatment methods and instructions based on a hairstyle pattern.

[1070] "Future hairstyle simulation" refers to a technology that predicts what a user's hairstyle will look like after a certain period of time and displays it as a composite image.

[1071] The present invention is a system that allows a user to accurately communicate the hairstyle they want to a hairdresser and further suggests an appropriate hairstyle taking the user's feelings into consideration. An embodiment of the system will be described below.

[1072] First, the user accesses the system's webpage on their device (such as a smartphone or PC). This webpage provides an interface for users to upload facial images. The user takes a picture of their face from the front, side, or back of the head, and clicks the "Upload" button to send the selected image file to the system.

[1073] The device temporarily stores the facial image file selected by the user in local storage. The stored image file is then sent to the server as an HTTP POST request using JavaScript. This communication is asynchronous, using an Ajax library (e.g., jQuery).

[1074] The server passes the received facial images to an analysis program written in Python. OpenCV and Dlib libraries are used for facial analysis, which detects facial features and recognizes emotions by analyzing facial expressions and subtle changes in the facial images. Emotion recognition uses a cloud service's emotion analysis API (for example, Azure's emotion analysis API). The results of the emotion analysis are extracted as numerical data.

[1075] The server inputs this quantified emotion data into a generative AI model (such as StyleGAN). The generative AI model is built using deep learning frameworks such as TensorFlow and PyTorch, and generates multiple hairstyle patterns to be synthesized onto the user's face based on the emotion data and facial images. In this process, an appropriate prompt sentence is input into the AI ​​model. An example of a prompt sentence is, "The user's emotional state is excited. Generate a hairstyle pattern with a short hair style or a bright color that gives a lively impression."

[1076] The generated hairstyle patterns are naturally combined with the facial image and saved as an image file. These combined images are sent from the server to the device as an HTTP response. The device's browser displays a list of the received hairstyle pattern images, allowing the user to select the desired hairstyle from multiple options.

[1077] When a user selects a specific hairstyle pattern, that information is sent from the device to the server. The server generates a specific haircut recipe based on the selected hairstyle pattern and emotional data. The haircut recipe includes detailed instructions on the length of the bangs, the amount of hair on the sides, and coloring. Furthermore, a future hairstyle simulation is performed, and an image of the predicted hairstyle three months from now is generated.

[1078] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which displays them to the user, who can then print or download the haircut recipe and bring it to the hair salon to provide specific hairstyle instructions to the hairdresser.

[1079] In this way, by using the present invention, the user can select the hairstyle that best suits his / her emotions and face, while providing accurate beauty instructions to the hairdresser.

[1080] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1081] Step 1:

[1082] A user accesses the system and uploads a facial image.

[1083] Users access the system's web page using a device such as a smartphone or PC. They click the "Upload Face Image" button on the web page, select a face image from the front, side, or back of the head, and upload it. At this time, the input data is the user's face image file, and the output is a message indicating successful file upload. Specifically, an image file is selected using an HTML form, and the image upload process is carried out using JavaScript.

[1084] Step 2:

[1085] The device temporarily saves the image file and sends it to the server.

[1086] The facial image file is temporarily saved in the device's local storage. After saving, an HTTP POST request is created using the Ajax library, and the image file is sent to the server. At this time, the input data is the saved image file, and the output is the file sent to the server. Specifically, asynchronous communication is performed using JavaScript and Ajax.

[1087] Step 3:

[1088] The server analyzes the facial image and recognizes the features and emotions.

[1089] The server passes the received facial images to an analysis program written in Python. It uses Python's OpenCV and Dlib libraries to detect facial feature points (eyes, nose, mouth, etc.). Based on this feature point data, it uses Azure's emotion analysis API to analyze the user's emotions from their facial expressions. The input data is the user's facial image, and the output is feature point data and emotion data. Specific operations include image preprocessing (resizing, grayscale conversion), feature point extraction, and making requests to the cloud API.

[1090] Step 4:

[1091] The server inputs the emotion data into the AI ​​model to generate a hairstyle pattern.

[1092] The results of the sentiment analysis are quantified and input into a generative AI model built using Python's TensorFlow or PyTorch. The generative AI model (for example, StyleGAN) generates multiple hairstyle patterns based on the input data. In this process, an appropriate prompt sentence is input into the AI ​​model. The input data is feature point data and emotion data, and the output is multiple hairstyle pattern images. Specifically, the emotion data is quantified, input into the AI ​​model, and hairstyle patterns are generated.

[1093] Step 5:

[1094] The server synthesizes the generated hairstyle pattern and sends it to the device.

[1095] The generated hairstyle pattern is composited with the user's facial image and output in a natural way. The composite image is saved on the server and sent to the device as an HTTP response. The input data is the generated hairstyle pattern and the user's facial image, and the output is a composite image file. A Python image processing library is used for the composite.

[1096] Step 6:

[1097] The device displays hairstyle patterns to the user.

[1098] The device's browser displays a list of composite images received from the server. Using HTML, CSS, and JavaScript, the images are displayed in a format that is easy for the user to view. The input data is the composite image file sent from the server, and the output is a list of hairstyles that is displayed to the user. Specifically, the images are loaded and displayed.

[1099] Step 7:

[1100] The user selects the desired hairstyle.

[1101] The user selects the desired hairstyle pattern by clicking on it from the displayed patterns. Information on the selected hairstyle pattern is sent from the device to the server. The input data is the ID of the hairstyle pattern clicked by the user, and the output is the transmission of the selected information to the server. Specific operations include processing the click event using JavaScript and sending data.

[1102] Step 8:

[1103] The device sends the selection information to the server

[1104] The device sends data including the ID of the selected image to the server as an HTTP POST request. The input data is the ID of the selected image, and the output is a message to the server indicating that the request was sent successfully. Specifically, asynchronous communication is performed using Ajax.

[1105] Step 9:

[1106] The server generates a haircut recipe and a simulation of the future hairstyle.

[1107] The server generates a specific haircut recipe (bangs length, amount of hair on the sides, coloring instructions, etc.) based on the selected hairstyle pattern and emotional data. It also performs a future hairstyle simulation and generates a predicted hairstyle three months from now. The input data is the selected hairstyle pattern and emotional data, and the output is a haircut recipe and predicted hairstyle image. Specifically, data analysis and model inference processing are performed.

[1108] Step 10:

[1109] Send the results generated by the server to the device

[1110] The generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal as an HTTP response. The input data are the haircut recipe and simulation image, and the output is the response sent to the terminal. Specifically, data packaging and HTTP transmission processing are performed.

[1111] Step 11:

[1112] The device displays the results to the user

[1113] The terminal displays the received cutting recipe and simulation image to the user. It uses HTML and JavaScript to provide an interface that the user can easily check. The input data is the cutting recipe and simulation image received from the server, and the output is what is displayed to the user. Specifically, data loading and display processing are carried out.

[1114] (Application example 2)

[1115] 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."

[1116] In conventional hair styling suggestion systems at hair salons, the desired hairstyle image often does not match between the user and the hairdresser, resulting in a decrease in user satisfaction. Furthermore, there was no system that could analyze the user's emotions from a facial image and suggest the optimal hairstyle based on that. This made it difficult to suggest a hairstyle that matched the user's mood and preferences at the time, which further led to dissatisfaction.

[1117] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for taking and uploading a facial image of a customer using a tablet or smartphone, means for analyzing emotions from the facial image and generating a hairstyle pattern based on the emotion, and means for displaying the generated hairstyle pattern to the customer. This makes it possible to suggest a hairstyle that is suited to the user's current emotional state, thereby improving user satisfaction.

[1118] A "user" is an individual who uses the hairstyle suggestion system.

[1119] A "face image" is a photograph of the user's face taken from multiple angles, such as the front, side, and back of the head.

[1120] The "server" is a computer on the network that receives and analyzes data and generates hairstyle patterns using a generative AI model.

[1121] A "generative AI model" is an artificial intelligence technology that generates hairstyle patterns based on a user's facial image and emotional data.

[1122] "Hairstyle patterns" are digital images of different types of hairstyles that are composited onto the user's facial image.

[1123] A "terminal" is a hardware device such as a tablet or smartphone that is operated by a user.

[1124] "Emotion" refers to the psychological state of the user that is analyzed from a facial image, and the analysis results are used to suggest hairstyles.

[1125] A "cut recipe" is a set of specific instructions for a hairstyle, including the length of the bangs, the amount of hair on the sides, and coloring instructions.

[1126] A "future hairstyle simulation" is a digital image that predicts how a user's hairstyle will change over time.

[1127] A specific embodiment for carrying out this invention will be described below. First, a user accesses the system using a tablet or smartphone installed in a beauty salon. The user takes facial images of the front, side, and back of the head and uploads them to the system.

[1128] The hardware used is a tablet or smartphone camera, and the software is an application for capturing and uploading facial images. The system temporarily stores the facial image file selected by the user and sends it to a server.

[1129] The server analyzes the received facial image and recognizes facial features and hairstyle information. It also uses an emotion engine to analyze the user's emotions from the facial image. Specifically, it detects facial expressions and subtle changes and determines the emotion. The software used includes OpenCV (facial image analysis) and Keras (emotion engine).

[1130] Next, the server uses the generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. Different variations such as short hair, long hair, bob, and perm are generated depending on the emotion. These hairstyle patterns are naturally combined with the user's facial image, and each pattern is saved as an image file. This is what the generative AI model is used for.

[1131] The server sends the generated hairstyle patterns to a tablet or smartphone, which then displays them to the user. The user can then review the displayed hairstyle patterns and select the one they like best. The device then sends the selection information to the server.

[1132] The server generates a specific haircut recipe based on the hairstyle pattern selected by the user and the results of emotion analysis. This haircut recipe includes detailed information such as the length of the bangs, the amount of hair on the sides, and coloring instructions. It also performs a simulation of future hairstyles, predicting what the hairstyle will look like three months from now, for example, and generates a composite image. This allows the user to receive a haircut at the salon that takes future hairstyles into consideration.

[1133] As a specific example, if user A takes a picture of his face with a tablet and the facial image is analyzed by the emotion engine as being in a "relaxed state," the server will use the generative AI model to preferentially suggest hairstyle patterns that give a calm impression. An example of a prompt sentence in this case is as follows:

[1134] "Input the user's facial image into an emotion engine and generative AI model to suggest hairstyle patterns that suit their relaxed state."

[1135] This allows the user to be suggested a hairstyle that is best suited to their current psychological state, improving satisfaction at the beauty salon.

[1136] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1137] Step 1:

[1138] First, the user accesses the system using a tablet or smartphone installed in the beauty salon. The user takes facial images of the front, side, and back of the head and uploads them to the system. The input is the facial image taken by the user, and the output is the uploaded facial image data. Specifically, the user takes a facial image using the camera application on the tablet or smartphone and sends it to the server.

[1139] Step 2:

[1140] The device temporarily stores the facial image file selected by the user and sends it to the server. The input is the facial image taken and uploaded by the user, and the output is the facial image data sent to the server. Specifically, the device transfers the temporarily stored image file to the server via an HTTP request.

[1141] Step 3:

[1142] The server analyzes the received facial image and recognizes facial feature points and hairstyle information. The input is the facial image data sent to the server, and the output is the analyzed facial feature point data and hairstyle information.

[1143] Specifically, it uses OpenCV to analyze facial images, extract feature points for each part of the face, recognize the shape and contours of the face, and extract information about the current hairstyle.

[1144] Step 4:

[1145] The server uses an emotion engine to analyze emotions from the user's facial image. The input is analyzed facial feature point data, and the output is analyzed emotion data. Specifically, the emotion engine using Keras is used to analyze emotions from facial expressions, and the results are obtained as numerical data.

[1146] Step 5:

[1147] The server uses a generative AI model to generate multiple hairstyle patterns to be combined with the user's facial image. The input is the user's facial image and analyzed emotional data, and the output is multiple generated hairstyle patterns. Specifically, a prompt sentence is generated based on the emotional data, and this is input into the generative AI model to automatically generate a hairstyle pattern that matches the emotion.

[1148] Step 6:

[1149] The server synthesizes the generated hairstyle pattern onto the user's facial image in a natural way and saves each pattern as an image file. The input is the user's facial image and the generated hairstyle pattern, and the output is an image file of the synthesized hairstyle pattern. Specifically, the server uses a synthesis algorithm to superimpose the generated hairstyle pattern onto the user's facial image.

[1150] Step 7:

[1151] The server sends the generated hairstyle patterns to a tablet or smartphone, and the device displays them as a list. The input is an image file of the synthesized hairstyle pattern, and the output is a list of hairstyle patterns displayed on the device. Specifically, the image file of the hairstyle pattern is sent to the device as an HTTP response, and the display application renders it.

[1152] Step 8:

[1153] The user checks the displayed hairstyle patterns and selects the hairstyle they like best. The input is the displayed hairstyle patterns, and the output is the information on the hairstyle pattern selected by the user. Specifically, the user selects the desired hairstyle using touch operations or selection buttons.

[1154] Step 9:

[1155] The terminal sends the user's selection information to the server. The input is the hairstyle pattern information selected by the user, and the output is the selection information sent to the server. Specifically, the user's selection information is transmitted to the server as an HTTP request.

[1156] Step 10:

[1157] The server generates a specific haircut recipe based on the hairstyle pattern selected by the user and the emotion analysis results. The input is the information on the selected hairstyle pattern and emotion data, and the output is a specific haircut recipe. Specifically, the server automatically generates a haircut recipe that includes the length of the bangs, the amount of hair on the sides, coloring instructions, etc.

[1158] Step 11:

[1159] The server also simulates future hairstyles, predicting what the user's hairstyle will look like in three months, for example, and generates a synthetic image. The input is the user's hairstyle pattern and predicted growth data, and the output is a simulated image of the future hairstyle. Specifically, the server predicts the future hairstyle using an algorithm that simulates hair growth.

[1160] Step 12:

[1161] Finally, the generated haircut recipe and future hairstyle simulation image are sent from the server to the terminal, which then displays them to the user. The input is the haircut recipe and future hairstyle simulation image, and the output is the information displayed on the terminal. Specifically, the haircut recipe and simulation image are sent as an HTTP response, and the terminal presents them to the user using an application that displays them.

[1162] Through the above processing steps, the user is suggested a hairstyle that suits their current psychological state, improving their satisfaction at the beauty salon.

[1163] 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.

[1164] 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.

[1165] 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.

[1166] 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.

[1167] FIG. 9 illustrates 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 behaviors 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.

[1168] 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.

[1169] 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).

[1170] 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.

[1171] 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."

[1172] 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.

[1173] 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).

[1174] 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.

[1175] 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.

[1176] 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.

[1177] 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.

[1178] 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.

[1179] 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.

[1180] 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.

[1181] 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.

[1182] 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.

[1183] 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.

[1184] The following is further disclosed regarding the above embodiment.

[1185] (Claim 1)

[1186] A means for a user to upload facial images taken from multiple directions;

[1187] A means for analyzing the face image received by the server and recognizing facial feature points and hairstyle information;

[1188] A server uses a generative AI model to synthesize multiple hairstyle patterns and display them naturally on the user's face image;

[1189] A means for displaying a plurality of hairstyle patterns to a user on the terminal;

[1190] A means for selecting a hairstyle pattern desired by the user;

[1191] A means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern;

[1192] A means for displaying the generated haircut recipe and a future hairstyle simulation to the user on the terminal;

[1193] A system including:

[1194] (Claim 2)

[1195] 10. The system of claim 1, further comprising means for identifying facial expressions, facial contours, and hair color when the server analyzes the received facial image.

[1196] (Claim 3)

[1197] 2. The system according to claim 1, further comprising means for including specifications of the length of the bangs, the amount of hair on the sides, and coloring in the cut recipe generated by the server after the user selects the desired hairstyle pattern.

[1198] "Example 1"

[1199] (Claim 1)

[1200] A means for a user to upload facial images taken from multiple directions;

[1201] A means for the terminal to temporarily store the uploaded facial image and transmit it to a server;

[1202] A means for analyzing the face image received by the server and recognizing facial feature points and hairstyle information;

[1203] A means for the server to generate a plurality of hairstyle patterns using a generative AI model based on the analysis data;

[1204] a means for the server to combine the generated hairstyle pattern with a facial image and transmit the combined image to a terminal;

[1205] A means for displaying a plurality of hairstyle patterns to a user on the terminal;

[1206] A means for selecting a hairstyle pattern desired by the user;

[1207] A means for transmitting information on the selected hairstyle pattern from the terminal to a server;

[1208] A means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern;

[1209] A means for displaying the generated haircut recipe and a future hairstyle simulation to the user on the terminal;

[1210] A system including:

[1211] (Claim 2)

[1212] The system according to claim 1, further comprising means for identifying the eyes, nose, mouth and contours as facial feature points when the server analyzes the received facial image, and further analyzing the shape and color of the current hairstyle.

[1213] (Claim 3)

[1214] The system according to claim 1, further comprising means for including instructions on the length of the bangs, the amount of hair on the sides, and coloring in the cutting recipe generated by the server.

[1215] "Application Example 1"

[1216] (Claim 1)

[1217] A means for a user to upload facial images taken from multiple directions;

[1218] A means for analyzing the face image received by the server and recognizing facial feature points and hairstyle information;

[1219] A server uses a generative AI model to synthesize multiple hairstyle patterns and display them naturally on the user's face image;

[1220] A means for utilizing a display device for a user to check hairstyle patterns in real time in a virtual reality space;

[1221] A means for displaying a plurality of hairstyle patterns to a user on the terminal;

[1222] A means for selecting a hairstyle pattern desired by the user;

[1223] A means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern;

[1224] A means for displaying the generated haircut recipe and a future hairstyle simulation to the user on the terminal;

[1225] A system including:

[1226] (Claim 2)

[1227] 10. The system of claim 1, further comprising means for identifying facial expressions, facial contours, and hair color when the server analyzes the received facial image.

[1228] (Claim 3)

[1229] 2. The system according to claim 1, further comprising means for including specifications of the length of the bangs, the amount of hair on the sides, and coloring in the cut recipe generated by the server after the user selects the desired hairstyle pattern.

[1230] "Example 2: Combining Emotion Engines"

[1231] (Claim 1)

[1232] A means for a user to upload facial images taken from multiple directions;

[1233] A means for the terminal to temporarily store the image file and transmit it to the server;

[1234] A means for analyzing the facial image received by the server and recognizing facial features and emotions;

[1235] A means for the server to use the generation AI model to generate and display a plurality of hairstyle patterns based on emotion data and a facial image of the user;

[1236] A means for displaying a plurality of hairstyle patterns to a user on the terminal;

[1237] A means for selecting a hairstyle pattern desired by the user;

[1238] A means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern;

[1239] A means for displaying the generated haircut recipe and a future hairstyle simulation to the user on the terminal;

[1240] A system including:

[1241] (Claim 2)

[1242] 10. The system of claim 1, further comprising means for identifying facial expressions, facial contours, and hair color when the server analyzes the received facial image.

[1243] (Claim 3)

[1244] 2. The system according to claim 1, further comprising means for including specifications of the length of the bangs, the amount of hair on the sides, and coloring in the cut recipe generated by the server after the user selects the desired hairstyle pattern.

[1245] "Application example 2 when combining emotion engines"

[1246] (Claim 1)

[1247] A means for a user to upload facial images taken from multiple directions;

[1248] A means for analyzing the face image received by the server and recognizing facial feature points and hairstyle information;

[1249] A server uses a generative AI model to synthesize multiple hairstyle patterns and display them naturally on the user's face image;

[1250] A means for displaying a plurality of hairstyle patterns to a user on the terminal;

[1251] A means for selecting a hairstyle pattern desired by the user;

[1252] A means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern;

[1253] A means for displaying the generated haircut recipe and a future hairstyle simulation to the user on the terminal;

[1254] A means for taking and uploading a facial image of a customer using a tablet or smartphone installed in a beauty salon;

[1255] A means for the server to analyze emotions from a face image and generate a hairstyle pattern based on the emotions;

[1256] A means for displaying the generated hairstyle pattern to the customer via a tablet or smartphone;

[1257] A system including:

[1258] (Claim 2)

[1259] 10. The system of claim 1, further comprising means for identifying facial expressions, facial contours, and hair color when the server analyzes the received facial image.

[1260] (Claim 3)

[1261] 2. The system according to claim 1, further comprising means for including specifications of the length of the bangs, the amount of hair on the sides, and coloring in the cut recipe generated by the server after the user selects the desired hairstyle pattern. [Explanation of symbols]

[1262] 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 a user to upload facial images taken from multiple directions; A means for analyzing the face image received by the server and recognizing facial feature points and hairstyle information; A server uses a generative AI model to synthesize multiple hairstyle patterns and display them naturally on the user's face image; A means for displaying a plurality of hairstyle patterns to a user on the terminal; A means for selecting a hairstyle pattern desired by the user; A means for the server to generate a specific haircut recipe and a future hairstyle simulation based on the selected hairstyle pattern; A means for displaying the generated haircut recipe and a future hairstyle simulation to the user on the terminal; A system including:

2. The system of claim 1 , further comprising means for identifying facial expressions, facial contours, and hair color when the server analyzes the received facial image.

3. 2. The system according to claim 1, further comprising means for including specifications of the length of the bangs, the amount of hair on the sides, and coloring in the cut recipe generated by the server after the user selects the desired hairstyle pattern.

Images