system

Abstract

Provide a system. A means for uploading a user's photo; A means of performing facial recognition and extracting feature points from uploaded photos; A means for the user to input an image of the person they want to be; means for generating a prompt based on the feature points and an image input by the user and editing the photo; A method to suggest makeup tools and techniques based on edited photos, means for generating and displaying a purchase link for the suggested makeup tool; 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 the past, when users wanted to improve their appearance, seeking professional help required a lot of money and time, making it difficult to achieve at home. It was also difficult to find specific makeup techniques and tools on one's own, requiring trial and error before arriving at the optimal technique. There is a need for a system that solves these problems and allows users to easily and effectively achieve the look they want. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means: a system including means for uploading a user's photo, means for performing facial recognition on the uploaded photo to extract feature points, means for the user to input an image of themselves that they would like to achieve, means for generating prompts and editing the photo based on the feature points and the image input by the user, means for suggesting makeup tools and makeup techniques based on the edited photo, and means for generating and displaying links to purchase the suggested makeup tools, allowing users to easily receive expert-level advice from the comfort of their own homes. This system allows users to efficiently improve their appearance and achieve their desired style.

[0006] A "user" is an individual who uses the system to upload a photo and input the image of themselves they want to portray.

[0007] "Means for uploading photos" refers to an interface or function that allows a user to use a terminal to send their own photos to the system.

[0008] "Means for performing facial recognition and extracting features" refers to algorithms and processing procedures that identify the position and shape of the face, as well as features such as the eyes and nose, from uploaded photos and extract this information as data.

[0009] The "means for inputting the image of the person you want to be" is an interface that allows the user to provide the system with the style and characteristics they are aiming for by means of text input or other methods.

[0010] The "means for generating prompts and editing photos" refers to an algorithm or processing procedure that creates editing instructions (prompts) based on the extracted feature points and image information entered by the user, and processes the photo in accordance with those instructions.

[0011] The "means for suggesting makeup tools and makeup techniques" refers to functions and algorithms that, based on edited photos, suggest the makeup tools that users should use and the specific makeup steps using those tools.

[0012] The "means for generating and displaying purchase links" is a function for creating links to online shopping sites corresponding to the suggested makeup tools and displaying them so that the user can easily purchase them through those links.

[0013] A "terminal" is an electronic device used by a user, such as a computer, smartphone, or tablet.

[0014] A "system" is a collection of software and hardware that executes a series of operations realized by combining the above means. [Brief explanation of the drawings]

[0015] [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 illustrating 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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention is a system that helps users realize the person they want to be, and suggests makeup tools and makeup techniques based on the user's photograph, leading to purchases. The program of this system is configured as follows.

[0037] Photo upload

[0038] A user uploads his / her own photo to the system using a terminal. This photo is then sent to the server as data necessary for subsequent processing after the user's facial features are recognized. The terminal has the function of sending the uploaded photo file to the server.

[0039] Face Recognition and Feature Extraction

[0040] The server performs facial recognition on the received photo and extracts features such as eyes, nose, mouth, and eyebrows. These features are used to determine the size and position of each part of the user's face. The server stores the extracted features in a database and uses them to generate subsequent prompts.

[0041] Input the target image

[0042] The user inputs the desired image of themselves using a terminal. This input is in text format and includes specific styles such as "natural makeup" or "glamorous." The terminal then sends the input target image to the server.

[0043] Prompt generation and photo editing

[0044] The server generates an editing prompt based on the extracted facial feature points and the user's target image. This prompt is passed to the photo editing engine and contains instructions for editing the photo to match the user's desired style. The edited photo shows the user's new look.

[0045] Makeup tools and techniques

[0046] Based on the edited photo, the server suggests makeup products and specific makeup techniques to the user. The suggested makeup products include foundation, eye shadow, lipstick, etc. Specific instructions for using each makeup product are also provided.

[0047] Generate and view purchasing links

[0048] The server generates a purchase link corresponding to the suggested makeup products. This link is from an online shop and is arranged so that the user can easily purchase the products. The terminal displays the generated purchase link to the user in a clickable format.

[0049] Specific examples

[0050] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." The server performs facial recognition on the photo and extracts features such as large eyes and a high nose. Based on this, the server generates prompts and edits the photo to create a "natural makeup" style. Based on the editing results, the server suggests the use of foundation, eye shadow, and lipstick, and provides detailed instructions on how to use each product. Furthermore, the server generates a purchase link for the suggested makeup products and displays it to the user via their device.

[0051] This system allows users to receive professional makeup advice from the comfort of their own home, and then easily purchase the necessary makeup tools. This system provides an effective means for users to achieve the style they desire.

[0052] The processing flow will be explained below.

[0053] Step 1:

[0054] A user opens the system interface using a terminal, selects his / her own photo, and clicks the upload button. The terminal then sends the selected photo file to the server.

[0055] Step 2:

[0056] The server stores the received photo file and uses a facial recognition algorithm to identify the position and contours of the face. The identified feature points (eyes, nose, mouth, eyebrows, etc.) are extracted as data and stored in a database.

[0057] Step 3:

[0058] The user enters the desired image of themselves (e.g., "natural makeup," "glamorous," etc.) into the input form on the device and clicks the send button. The device then sends the entered target image to the server.

[0059] Step 4:

[0060] The server generates prompts based on the extracted feature points and the target image entered by the user, and passes the prompts to a photo editing engine to create an edited photo that matches the user's desired style.

[0061] Step 5:

[0062] Based on the edited photo, the server generates a list of makeup products (e.g., foundation, eye shadow, lipstick, etc.) that the user should use, along with specific makeup steps using those products.

[0063] Step 6:

[0064] The terminal displays the list of makeup tools and makeup procedures received from the server to the user. The procedures for using each makeup tool are explained in detail so that the user can easily understand.

[0065] Step 7:

[0066] The server generates a purchase link corresponding to the suggested makeup products. For each makeup item, it creates an appropriate online shop link and sends it to the terminal.

[0067] Step 8:

[0068] The terminal displays the generated purchase link to the user, who can easily purchase the suggested makeup tool by clicking the displayed link.

[0069] Example 1

[0070] 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."

[0071] Nowadays, many users seek makeup advice to improve their style, but getting advice from a professional makeup artist requires time and money. Users also have difficulty choosing the right makeup tools and finding the right products. Even when purchasing makeup online, it can be difficult to know which products actually suit you.

[0072] 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.

[0073] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating prompts based on the feature points and the image input by the user and editing the photo using a generative AI model, means for suggesting makeup tools and makeup techniques based on the edited photo, and means for generating and displaying a purchase link for the suggested makeup tools. This allows users to easily receive professional makeup advice and easily select and purchase appropriate makeup tools.

[0074] "User" refers to an individual who uses the system, uploads their own photograph, and inputs a target image.

[0075] A "photo uploader" is a piece of hardware or software that allows users to submit their own photos to the system.

[0076] "Facial recognition means" refers to an algorithm or program that performs the process of detecting facial features from uploaded photographs and extracting features such as eyes, nose, mouth, and eyebrows.

[0077] "Feature points" refer to parts such as the eyes, nose, mouth, and eyebrows that occupy important positions in a facial image, and are data that indicate the position information and features of these parts.

[0078] The "target image input means" is a part of software or an interface that has the function of allowing the user to input information such as the desired makeup style in text format and send it to the system.

[0079] A "prompt" refers to text data containing instructions or commands that the system inputs to the generated AI model.

[0080] A "generative AI model" is an artificial intelligence algorithm trained using large datasets to perform tasks such as natural language processing and image processing.

[0081] A "photo editing tool" is software or algorithm that processes a user's photo to match a target image based on instructions output from a generative AI model.

[0082] The "makeup tool suggestion means" is a process or function that suggests cosmetics that the user should use and how to use them based on the edited photo.

[0083] The "purchase link generating means" is a part of software that has the function of generating an online purchase link corresponding to the suggested makeup tool, allowing the user to easily access it.

[0084] The present invention is a system that enables users to realize the self they want to be. This system suggests makeup tools and makeup techniques based on a user's photograph and encourages purchases based on these suggestions. Specific embodiments for implementing this system are described below.

[0085] First, a user uploads a photo of their face using a terminal, which can be a smartphone, tablet, or computer. The uploaded photo is sent to a server, which uses it as the basis for subsequent facial recognition and feature extraction.

[0086] The server then processes the received photos. Specifically, the server performs facial recognition using image processing libraries such as OpenCV and Dlib. The facial recognition algorithm extracts the main facial features (eyes, nose, mouth, eyebrows, etc.) and obtains the position and size data of each feature. This feature data is stored in a database for later use in prompt generation and photo editing.

[0087] Users use their devices to input the image of their desired look in text format, including specific styles such as "natural makeup" or "glamorous makeup." The device converts this text information into JSON format and sends it to the server.

[0088] The server generates a prompt based on the feature point data and the target image entered by the user. This prompt is then input to a generative AI model (e.g., GPT-4 (registered trademark)), which generates a text-format instruction such as the following:

[0089] "The user in this photo is aiming for a natural look. Use a light brown eyeshadow and a thin eyeliner to make the eyes appear slightly larger. Choose a natural pink lipstick and aim for a smooth overall look."

[0090] Based on the generated instructions, the server calls a photo editing engine (e.g., Adobe Photoshop API) to automatically edit the photo, so that the edited photo matches the user's desired style.

[0091] The server then suggests makeup products and how to use them based on the edited photo. Suggested makeup products include foundation, eyeshadow, lipstick, etc. Specific instructions for using each product are also provided, including how to apply foundation and eyeshadow.

[0092] Finally, the server generates a purchase link for each of the suggested makeup products. This link is located in an online shop, allowing users to easily access and complete the purchase process. The generated purchase link is formatted in HTML and displayed on the user's device. This allows the user to directly purchase the suggested makeup products by clicking the link on the screen.

[0093] For example, if a user uploads a photo of themselves and indicates that they want to achieve "natural makeup," the server first performs facial recognition and extracts features such as "big eyes" and "high nose." Next, a generative AI model is used to generate prompts, and a photo editing engine is used to edit the photo into a "natural makeup" style based on the prompts. The server then suggests the use of foundation, brown eyeshadow, and pink lipstick, and generates and displays purchase links for each product to the user.

[0094] Thus, the present invention provides an effective means for users to receive professional makeup advice from the comfort of their own home and purchase appropriate makeup tools based on the advice.

[0095] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0096] Step 1:

[0097] The user uploads a photo of their face. The user uses the device to select a photo from the camera app or photo gallery, and then uses the system's upload function to send the photo to the server. At this time, the user inputs the file data of the face photo, and the device sends this data to the server as an HTTP request. The server saves the uploaded image file and uses it for subsequent processing.

[0098] Step 2:

[0099] The server performs facial recognition and extracts feature points. The server processes the received photo files using the OpenCV and Dlib libraries in a Python script. Specifically, the face detection algorithm recognizes faces in the photos and extracts feature points such as eyes, nose, mouth, and eyebrows. The input for this process is the saved image file, and the output is the coordinate data of the feature points. The server stores the extracted feature point data in a MySQL (registered trademark) database.

[0100] Step 3:

[0101] The user inputs the desired image. Using the device interface, the user inputs a style such as "natural makeup" or "glamorous makeup" into the text field. After completing the input, the user clicks the "Send" button, and the device sends the input string to the server in JSON format. The input of this process is the text data entered by the user, and the output is JSON format data.

[0102] Step 4:

[0103] The server generates prompts and edits photos. The server obtains feature point data extracted from a database and the target image submitted by the user. It generates prompt text based on this. For example, it generates a prompt text for a "natural makeup" style based on the feature point data. The generated prompt text is input into a generative AI model (e.g., GPT-4), and the AI ​​outputs text containing specific instructions for editing the photo. Based on this text, the server edits the photo using the Adobe Photoshop API. The inputs to this process are the feature point data and the target image, and the output is a prompt text containing editing instructions and an edited photo file.

[0104] Step 5:

[0105] The server suggests makeup tools and techniques. Based on the edited photo, the server queries the generative AI model to obtain the makeup tools the user should use and the specific makeup techniques that accompany them. For example, it analyzes the photo and suggests using "foundation, eye shadow, and lipstick," providing detailed instructions on how to use each tool. The input for this process is the edited photo file, and the output is text information about the suggested makeup tools and their application techniques.

[0106] Step 6:

[0107] The server generates and displays a purchase link. The server generates an online purchase link corresponding to the suggested makeup products. This link is formatted in HTML and sent to the user's device. The user can access the corresponding online shop's purchase page by clicking the link displayed on the device. The input to this process is the text information of the makeup products, and the output is an HTML document containing the purchase link.

[0108] (Application example 1)

[0109] 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."

[0110] The present invention relates to a system that suggests makeup that matches the image a user desires and encourages the purchase of makeup tools that match this. Conventional systems only offer suggestions online, making it difficult for users to find the suggested products in physical stores. Another issue is that these systems do not provide detailed advice to help users accurately understand and execute the suggested makeup techniques. This makes it difficult for users to efficiently select makeup products and apply appropriate makeup.

[0111] 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.

[0112] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating a prompt based on the feature points and the image input by the user and editing the photo, means for suggesting makeup tools and makeup techniques based on the edited photo, means for generating and displaying a purchase link for the suggested makeup tools, and means for displaying location information of the suggested makeup tools. This allows the user to easily find suggested products in a physical store and receive detailed makeup technique suggestions.

[0113] "Means for uploading user photos" refers to a method by which a user can provide their own image data to the system.

[0114] "Means for performing facial recognition and extracting feature points from uploaded photographs" refers to a method for detecting faces in the provided image data and identifying the positional information of each part of the face (eyes, nose, mouth, etc.).

[0115] "Means for users to input the image of themselves they want to achieve" refers to a method by which users can communicate to the system the image of the style and makeup they are aiming for in text or selection format.

[0116] The "means for generating prompts based on the feature points and the image input by the user and editing the photo" is a method for generating image editing instructions based on the extracted facial information and the user's desired style, and processing the image in accordance with those instructions.

[0117] The "means of suggesting makeup tools and makeup techniques based on edited photos" refers to a method of suggesting specific makeup tools and how to use them to users by referring to edited images.

[0118] The "means for generating and displaying a purchase link for the suggested makeup tools" is a method for generating an online shopping link for purchasing the suggested makeup products and displaying it to the user.

[0119] The "means for displaying location information of the suggested makeup tools" is a method for providing the user with map information showing where the suggested makeup tools are actually located in the store.

[0120] The present invention is a system that helps users realize the image they want to achieve by suggesting makeup tools and makeup techniques based on a user's photo, leading to purchases. This system is implemented in the following manner.

[0121] First, a user uploads a photo of themselves to the application using their smartphone. This application has a function for sending the photo to a server. The server then performs facial recognition on the uploaded photo and extracts feature points such as the eyes, nose, mouth, and eyebrows. This process uses an image processing library called OpenCV and a pre-trained facial recognition model.

[0122] Next, the user enters the image of their desired look in text form within the application. For example, they could use a specific style such as "natural makeup" or "glamorous." The input image information, along with extracted feature points, is sent to the server. The server uses this information to generate a prompt using a generative AI model. This prompt is then passed to the photo editing engine, which provides instructions for editing the photo to match the user's desired style.

[0123] Based on the edited photo, the server suggests makeup products and techniques suitable for the user. Suggested makeup products include foundation, eye shadow, lipstick, etc. Specific steps and methods for using each makeup product are also provided. Furthermore, an online purchase link for the suggested makeup products is generated and displayed to the user via a smartphone application.

[0124] To support the in-store shopping experience, the application also provides location information for the suggested makeup products, allowing users to easily find the suggested products in the store. Using the in-store map displayed on the smartphone, users can efficiently search for products.

[0125] For example, if a user uploads a photo of themselves and specifies that they are aiming for a "glamorous" look, the server will perform facial recognition on the photo and extract features such as large eyes and a high nose. Based on this, the server will generate prompts and edit the photo to create a "glamorous" style. Based on the editing results, the server will suggest the use of bright eyeshadow, thick lipstick, etc., and provide detailed instructions on how to use each product. The server will then generate a purchase link and in-store location information for the suggested makeup products, which will be displayed to the user via a smartphone application.

[0126] An example of a prompt sentence to input to the generative AI model is as follows:

[0127] User's facial features: [0.3, 0.4, 0.5, ...], Desired makeup style: 'glamorous'

[0128] As described above, users can receive professional makeup advice at home or in a brick-and-mortar store, easily purchase the necessary makeup tools based on that advice, and apply makeup appropriately. It is expected that the present invention will significantly improve users' makeup experience.

[0129] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0130] Step 1:

[0131] A user uploads their own photo to the application using a smartphone. The device receives the photo file selected by the user and sends it to the server. The input is the user's photo, and the output is that the photo data is sent to the server.

[0132] Step 2:

[0133] The server receives the uploaded photo and performs facial recognition processing. It uses OpenCV to detect the facial area from the image and extracts feature points such as eyes, nose, and mouth. The input is the user's photo data, and the output is facial feature point data. This feature point data is stored in a database on the server for further processing.

[0134] Step 3:

[0135] The user inputs the desired makeup style in text format within the application. The terminal sends the input image information to the server. The input is the user's text data, and the output is the image information sent to the server.

[0136] Step 4:

[0137] The server uses a generative AI model to generate prompts based on the received image information of the user's facial feature points and makeup style. These prompts are editing instructions that are passed to the photo editing engine. The input is facial feature point data and image information, and the output is an editing prompt.

[0138] Step 5:

[0139] The photo editing engine edits the photo based on the generated prompt to match the user's desired style. The input is the prompt and the original photo data, and the output is the edited photo data. This edited photo is saved on the server and used for future suggestions.

[0140] Step 6:

[0141] The server then uses the edited photo to suggest makeup products and techniques that are suitable for the user. Using the generated AI model, it recommends specific makeup products, such as foundation and eyeshadow, and how to use them. The input is the edited photo data, and the output is a list of makeup products and how to use them.

[0142] Step 7:

[0143] The server generates and provides online purchase links for the suggested makeup products to the user. It also displays the location information of the suggested makeup products to support in-store purchases. The input is a list of makeup products, and the output is a purchase link and location information.

[0144] Step 8:

[0145] Users can purchase makeup products online through the provided purchasing link, and can also check their location in a physical store to find suggested products in-store. This stage involves user-initiated selection and purchasing behavior.

[0146] 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.

[0147] The present invention is a system that recognizes a user's emotions and suggests makeup tools and makeup techniques based on the emotions. The program of this system is configured as follows.

[0148] Photo upload

[0149] The user uses the device to upload their own photo through the system interface, and the device sends the selected photo file to the server, which stores the photo and uses it for facial and emotion recognition.

[0150] Face Recognition and Feature Extraction

[0151] The server performs facial recognition processing on the received photos to identify facial contours and feature points, such as the positions and shapes of the eyes, nose, mouth, eyebrows, etc. This information is then stored in a database for subsequent processing.

[0152] emotion recognition

[0153] The server analyzes the user's facial expressions from the uploaded photo and recognizes emotions using an emotion engine, such as happiness, sadness, surprise, etc. This emotion information is also used to generate subsequent prompts and make-up suggestions.

[0154] Input the target image

[0155] The user uses the terminal to input the image of the person they want to be. This information is input in text format and includes specific styles such as "natural makeup" or "glamorous." The terminal then sends the input image information to the server.

[0156] Prompt generation and photo editing

[0157] The server generates prompts based on the extracted facial features, the target image entered by the user, and the recognized emotions. The prompts are passed to the photo editing engine, which then creates an edited photo that matches the user's desired style. The emotional data is reflected in the edits, and the style is set to match the user's mood.

[0158] Makeup tools and techniques

[0159] Based on the edited photo, the server suggests makeup products and techniques that best suit the user's emotions and desired image. The suggestions include a list of specific products, such as foundation, eye shadow, and lipstick, along with detailed instructions on how to use each product.

[0160] Generate and view purchasing links

[0161] The server generates a purchase link for the recommended makeup products. This link is from an online shop and is set up so that the user can easily purchase. The terminal displays the generated purchase link to the user in a clickable format.

[0162] Specific examples

[0163] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." At the same time, the "happy" emotion is recognized from the user's facial expression. The server performs facial recognition to extract each feature point and identifies the "happy" emotion using an emotion engine. Based on this information, a prompt is generated and the photo is edited to a style that matches "natural makeup" and a "happy" emotion. Specific makeup techniques for foundation, eye shadow, and lipstick are then suggested, along with detailed instructions for using each tool. Furthermore, a purchase link for the suggested makeup tools is generated and displayed to the user via their device. In this way, users can easily find makeup tools and techniques that match their emotions and the style they are aiming for.

[0164] This invention allows users to receive professional makeup advice tailored to their emotions at that moment from the comfort of their own homes, and to easily purchase the makeup tools they need based on that advice. The system takes the user's emotions into consideration and provides more personalized makeup suggestions, thereby improving user satisfaction.

[0165] The processing flow will be explained below.

[0166] Step 1:

[0167] A user opens the system interface using a terminal, selects his / her own photo, and clicks the upload button. The terminal then sends the selected photo file to the server.

[0168] Step 2:

[0169] The server stores the received photo file and performs facial recognition processing on the photo. Specifically, it identifies the position and outline of the face and extracts feature points such as the eyes, nose, mouth, and eyebrows. The extracted feature points are stored in a database.

[0170] Step 3:

[0171] The server uses an emotion engine to analyze the user's facial expressions from the uploaded photo and recognize emotions. For example, it identifies emotions such as happiness, sadness, and surprise, and generates emotion data. The emotion data is also stored in a database.

[0172] Step 4:

[0173] The user enters the desired image of themselves (e.g., "natural makeup" or "glamorous") in text format into the input form on the device and clicks the send button. The device then sends the entered target image to the server.

[0174] Step 5:

[0175] The server generates prompts based on the extracted facial feature points, the user-input target image, and the recognized emotion data, which are then passed to the photo editing engine and used as editing instructions.

[0176] Step 6:

[0177] The server then uses prompts to edit the photo and create an edited version that matches the user's desired style, such as adjusting eye shape or skin tone to create a natural look. The edited photo is then stored in a database.

[0178] Step 7:

[0179] The server then uses the edited photos to suggest the best makeup tools and techniques for the user. Specifically, it generates a list of foundation, eyeshadow, lipstick, etc., along with a makeup procedure using those items.

[0180] Step 8:

[0181] The terminal displays the list of makeup tools and makeup procedures received from the server to the user. The procedures and methods for using each makeup tool are explained in detail so that the user can easily understand.

[0182] Step 9:

[0183] The server generates a purchase link corresponding to the suggested makeup products and sends it to the terminal. An appropriate online shop link is created for each makeup item.

[0184] Step 10:

[0185] The terminal displays the generated purchase link to the user, who can easily purchase the suggested makeup tool by clicking the displayed link.

[0186] Through the above process, users are presented with makeup tools and techniques based on their own emotions and goals, and can easily purchase them. This system takes into account the user's current emotions and provides more personalized makeup suggestions, thereby improving satisfaction.

[0187] Example 2

[0188] 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."

[0189] Conventional makeup suggestion systems have difficulty providing personalized makeup advice because they do not take the user's emotions into consideration. Furthermore, there is a lack of easy ways for users to purchase the makeup tools they need, resulting in low user satisfaction. The present invention aims to solve these problems by providing a system that can suggest professional makeup that suits the user and encourages them to purchase the makeup.

[0190] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for uploading a user's own photo using the user's terminal, a means for transmitting the uploaded photo to the server and extracting feature points using a face recognition library, and a means for the user to input a target image in text format using the terminal. This allows the user to receive personalized makeup suggestions based on their own emotions and the target image. In addition, by including a means for generating a purchase link for the suggested makeup tools and displaying it on the terminal, the user can easily purchase the necessary makeup tools. As a result, user satisfaction is improved and purchases can be encouraged.

[0191] "User" refers to a person who uses the system to upload their own photos and receive makeup suggestions.

[0192] "Terminal" refers to a computing device used by a user, such as a smartphone or personal computer.

[0193] "Server" refers to a computer system that receives data sent from a terminal and performs processing such as facial recognition, emotion recognition, and makeup suggestions.

[0194] "Photo upload" refers to the act of a user sending their own photo to the system via their terminal.

[0195] A "face recognition library" refers to a software module for extracting facial feature points from a photograph. Examples include OpenCV and Dlib.

[0196] "Feature points" are data points that indicate the position and shape of facial features, such as the position and shape of the eyes, nose, mouth, and eyebrows.

[0197] "Goal image" refers to text information that indicates the specific makeup style the user wants to achieve. Examples include "natural makeup" and "glamorous."

[0198] "Emotion information" refers to data indicating emotions recognized from a user's photo, such as happiness, sadness, surprise, etc.

[0199] A "prompt" refers to a sentence that gives specific editing instructions to a photo editing engine.

[0200] "Photo Editing Engine" means software that edits photos based on prompts. Examples include the Adobe Photoshop API.

[0201] "Makeup tools" refers to the specific products used to apply makeup. Examples include foundation, eye shadow, and lipstick.

[0202] "Makeup technique" refers to the specific steps for applying makeup using makeup tools.

[0203] "Purchase Link" refers to a link to an online shop for purchasing the suggested makeup products.

[0204] "Personalized makeup suggestions" refer to suggestions for customized makeup techniques based on the user's individual emotions and target image.

[0205] The present invention is a system that analyzes a user's emotions and suggests optimal makeup tools and makeup techniques based on those emotions. This system is implemented in the following manner.

[0206] Users use their devices (smartphones or PCs) to upload their own photos through the system interface. The devices then send the selected photo files to the server, which stores the received photos and prepares them for further processing.

[0207] Next, the server uses the stored photo to extract facial feature points using a facial recognition library (e.g., OpenCV or Dlib). These feature points include the position and shape of the eyes, nose, mouth, eyebrows, etc. This extracted feature point information is stored in a database.

[0208] The server then uses the extracted feature point data to utilize an emotion recognition engine (e.g., a general emotion recognition API) to identify the user's emotion. Emotional information recognized includes happiness, sadness, surprise, etc. This emotional information is also stored in a database.

[0209] Next, the user uses the device to enter the makeup style they are aiming for in text format. For example, they can enter a specific style such as "natural makeup" or "glamorous." The device then sends this text data to the server, which then stores the received data in a database.

[0210] The server combines the facial feature point data, the target image, and the emotion information to generate a prompt. This prompt is passed to a photo editing engine (e.g., Adobe Photoshop API), which edits the photo based on the user's desired style. An example of a generated prompt sentence is as follows:

[0211] Example prompt:

[0212] Apply natural makeup to your user's photo and edit it in a style that matches her happy expression. Use light eyeshadow and a light lip color.

[0213] After the edited photo is generated, the server uses the photo to suggest the best makeup products and techniques to match the user's emotions and desired image. The list of specific products includes foundation, eye shadow, lipstick, etc., and provides detailed instructions on how to use each product.

[0214] For example, advice is given such as "Spread liquid foundation thinly and evenly," "Apply light eyeshadow lightly to the outer corners of your eyes," and "Apply light lip color carefully using a lip brush."

[0215] Furthermore, the server generates a purchase link for the recommended makeup tools and sends it to the terminal. The purchase link is from an online shop, and the user can easily complete the purchase procedure by clicking the link.

[0216] In this way, users can receive personalized makeup suggestions based on their own emotions and the style they are aiming for, and can easily purchase the necessary makeup tools.

[0217] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0218] Step 1:

[0219] A user uses a terminal to upload his / her own photo through the system interface. Specifically, the user selects a photo through the file selection dialog and clicks the upload button. The input is the user's photo file, which is sent by the terminal to the server. The output is the photo file received by the server.

[0220] Step 2:

[0221] The server stores the received photos and starts the facial recognition process. Specifically, it uses a facial recognition library (e.g., OpenCV or Dlib) on the stored photos. The input is the photo file received from the user, and the output is the facial contour and feature point data extracted from the photo. This data is stored in a database.

[0222] Step 3:

[0223] The server uses an emotion recognition engine (for example, a general emotion recognition API) based on the extracted facial feature point data to identify the user's emotion. Specifically, it makes an API request and receives emotion data as a response. The input is facial feature point data, and the output is recognized emotion information. This information is also stored in a database.

[0224] Step 4:

[0225] The user uses the terminal to input the target image in text format. Specifically, they enter keywords such as "natural makeup" or "glamorous" in the text box and click the send button. The input is the text data entered by the user and is sent from the terminal to the server. The output is the text data received by the server.

[0226] Step 5:

[0227] The server generates a prompt by combining the received target image, facial feature data, and emotion information. Specifically, it uses these data to create a prompt sentence to instruct the photo editing engine. The input is the target image, facial feature data, and emotion information, and the output is the generated prompt sentence.

[0228] Step 6:

[0229] The server passes the generated prompt text to a photo editing engine (e.g., Adobe Photoshop API) to edit the photo. Specifically, the photo is edited based on the prompt, and an edited photo is generated. The input is the prompt text and the original photo data, and the output is the edited photo. The edited photo is saved on the server.

[0230] Step 7:

[0231] Based on the edited photo, the server suggests the best makeup tools and techniques to match the user's emotions and desired image. Specifically, it generates a list of each tool and instructions for using them based on the information in the database. The input is the edited photo and related data, and the output is a list of makeup tools and specific makeup technique advice.

[0232] Step 8:

[0233] The server generates a purchase link for the suggested makeup products and sends it to the terminal. Specifically, it generates a link to an online shop and displays it in a clickable format for the user. The input is a list of makeup products, and the output is a purchase link. The terminal displays this link to the user, allowing them to easily complete the purchase procedure.

[0234] The above are the specific processing steps of this system's program. At each step, appropriate data processing and calculations are performed based on the input data, and the output required for the next step is generated.

[0235] (Application example 2)

[0236] 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."

[0237] Today's consumers want makeup suggestions and purchasing support that reflect their emotions and moods. However, conventional makeup suggestion systems have the problem of being unable to provide personalized advice because they do not take into account the emotional state of each individual user. In particular, when providing online makeup advice, it has been difficult to suggest makeup tools and methods that reflect the user's emotions. Thus, providing makeup support that incorporates the user's emotions is a challenge.

[0238] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0239] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating a prompt based on the feature points and the image input by the user and editing the photo, means for suggesting makeup tools and makeup techniques based on the edited photo, means for generating and displaying a purchase link for the suggested makeup tools, and means for recognizing the user's emotions and suggesting makeup tools and makeup techniques based on the emotions. This allows the user to receive personalized makeup suggestions that reflect their own emotions.

[0240] "User photo uploading means" is a method by which a user can send their photo from their device to the server.

[0241] "Means for performing facial recognition and extracting feature points" refers to a method for detecting faces from uploaded photos and analyzing specific points such as eyes, nose, and mouth.

[0242] "Means for users to input the image of themselves they want to have" refers to a method by which users input their desired makeup style and image of their appearance into the system.

[0243] The "means for generating prompts and editing photos" refers to a method by which the system generates appropriate instructions and edits photos based on facial recognition feature points and the input image.

[0244] The "means for suggesting makeup tools and makeup techniques" is a method for suggesting makeup tools suitable for a user and how to use them based on an edited photo.

[0245] The "means for generating and displaying a purchase link for the suggested makeup tool" is a method for generating an online purchase link for the makeup tool suggested by the system and displaying it to the user.

[0246] "Means for recognizing a user's emotions and suggesting makeup tools and techniques based on those emotions" refers to a method for analyzing emotions from a user's photo and suggesting optimal makeup tools and techniques based on the results.

[0247] The present invention is a system that recognizes a user's emotions and suggests makeup tools and makeup techniques based on the emotions. This system is configured through the following steps.

[0248] First, the user uploads a photo. This operation is performed using a device such as a smartphone. The photo data uploaded from the device is sent to a server and stored on the server. The server then performs facial recognition processing on the received photo. This processing uses a facial recognition software library such as OpenCV. As a result of facial recognition, feature points such as the eyes, nose, mouth, and eyebrows are extracted. This feature point information is stored in a database and used for subsequent processing.

[0249] The server then analyzes the user's facial expressions from the uploaded photo using an emotion recognition library or model such as EmotionDetector. For example, emotions such as happiness, sadness, and surprise are identified. This emotional information is used to generate subsequent prompts and make-up suggestions.

[0250] Next, the user inputs the image of the person they want to be. This information is entered into the terminal in text format, and includes specific styles such as "natural makeup" or "glamorous makeup." This input information is then sent from the terminal to the server.

[0251] The server generates prompts based on this information, namely the extracted facial features, the target image entered by the user, and the recognized emotions. The generated prompts are passed to the photo editing engine using an AI model. The photo editing engine follows the prompts to create an edited photo that matches the user's desired style. Emotional data is reflected in the edits, setting a style that matches the user's mood.

[0252] Based on the edited photo, the server suggests the makeup products and techniques that best suit the user's emotions and desired image. These suggestions include a list of specific products, such as foundation, eye shadow, and lipstick. It also provides detailed instructions on how to use each product and how to apply the makeup. It also generates a link to purchase the suggested makeup products. This link is from an online shop, and is set up so that users can easily purchase them via their device.

[0253] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." At the same time, the "happy" emotion is recognized from the user's facial expression. The server performs facial recognition, extracts each feature point, and identifies the "happy" emotion using an emotion engine. Based on this information, a prompt is generated and the photo is edited to a style that matches "natural makeup" and a "happy" emotion. Specific makeup techniques for foundation, eye shadow, and lipstick are then suggested, along with detailed instructions for using each tool. Furthermore, a purchase link for the suggested makeup tools is generated and displayed to the user via their device. In this way, users can easily find the makeup tools and techniques that match their emotions and the style they are aiming for.

[0254] An example of a prompt sentence is, "Based on the user's photo, edit the makeup to create a natural look. The user's emotion is recognized as happiness, and a makeup style that matches that emotion will be suggested."

[0255] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0256] Step 1:

[0257] The terminal provides an interface for the user to upload photos. The user selects a photo and performs upload. The terminal then sends the selected photo file to the server and temporarily stores the photo data as preprocessing.

[0258] Input: Photos uploaded by the user via the device

[0259] Output: Image data sent to the server

[0260] Step 2:

[0261] The server performs facial recognition on the received photo data using a facial recognition library such as OpenCV. Specifically, it detects the facial area and extracts feature points such as eyes, nose, mouth, and eyebrows. The extracted feature point information is stored in a database.

[0262] Input: Image data sent to the server

[0263] Output: Extracted facial feature points data

[0264] Step 3:

[0265] The server recognizes the user's emotions from the received photo data. It uses an emotion recognition library such as EmotionDetector to analyze facial expressions in the photo and identify the user's emotional state. This emotion data is also stored in a database.

[0266] Input: Image data sent to the server

[0267] Output: User emotion data

[0268] Step 4:

[0269] The user uses the device to input text describing the style or image they want to achieve, such as "natural makeup" or "glamorous makeup." This input data is then sent to the server.

[0270] Input: Text data of styles and images that users input from the terminal

[0271] Output: Text data sent to the server

[0272] Step 5:

[0273] The server generates prompts based on the extracted feature data, the user's input image, and the recognized emotions. These prompts are passed to the photo editing engine, which uses AI models to edit the photo to match the user's desired style.

[0274] Input: feature point data, user input data, emotion data

[0275] Output: Generated prompt and edited photo data

[0276] Step 6:

[0277] The server then suggests the best makeup products and techniques based on the edited photo, including a list of specific makeup products (e.g., foundation, eyeshadow, lipstick, etc.) and instructions for using them.

[0278] Input: Edited photo data

[0279] Output: A list of suggested makeup products and detailed instructions for use

[0280] Step 7:

[0281] The server generates a purchase link for the suggested makeup tool. This link is from an online shop and is displayed to the user. The terminal displays the generated purchase link to the user to encourage purchase.

[0282] Input: A list of suggested makeup products

[0283] Output: Generated purchasing links

[0284] 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.

[0285] 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.

[0286] 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.

[0287] [Second embodiment]

[0288] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0289] 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.

[0290] 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).

[0291] 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.

[0292] 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.

[0293] 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).

[0294] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0295] 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.

[0296] 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.

[0297] 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.

[0298] 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.

[0299] 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."

[0300] The present invention is a system that helps users realize the person they want to be, and suggests makeup tools and makeup techniques based on the user's photograph, leading to purchases. The program of this system is configured as follows.

[0301] Photo upload

[0302] A user uploads his / her own photo to the system using a terminal. This photo is then sent to the server as data necessary for subsequent processing after the user's facial features are recognized. The terminal has the function of sending the uploaded photo file to the server.

[0303] Face Recognition and Feature Extraction

[0304] The server performs facial recognition on the received photo and extracts features such as eyes, nose, mouth, and eyebrows. These features are used to determine the size and position of each part of the user's face. The server stores the extracted features in a database and uses them to generate subsequent prompts.

[0305] Input the target image

[0306] The user inputs the desired image of themselves using a terminal. This input is in text format and includes specific styles such as "natural makeup" or "glamorous." The terminal then sends the input target image to the server.

[0307] Prompt generation and photo editing

[0308] The server generates an editing prompt based on the extracted facial feature points and the user's target image. This prompt is passed to the photo editing engine and contains instructions for editing the photo to match the user's desired style. The edited photo shows the user's new look.

[0309] Makeup tools and techniques

[0310] Based on the edited photo, the server suggests makeup products and specific makeup techniques to the user. The suggested makeup products include foundation, eye shadow, lipstick, etc. Specific instructions for using each makeup product are also provided.

[0311] Generate and view purchasing links

[0312] The server generates a purchase link corresponding to the suggested makeup products. This link is from an online shop and is arranged so that the user can easily purchase the products. The terminal displays the generated purchase link to the user in a clickable format.

[0313] Specific examples

[0314] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." The server performs facial recognition on the photo and extracts features such as large eyes and a high nose. Based on this, the server generates prompts and edits the photo to create a "natural makeup" style. Based on the editing results, the server suggests the use of foundation, eye shadow, and lipstick, and provides detailed instructions on how to use each product. Furthermore, the server generates a purchase link for the suggested makeup products and displays it to the user via their device.

[0315] This system allows users to receive professional makeup advice from the comfort of their own home, and then easily purchase the necessary makeup tools. This system provides an effective means for users to achieve the style they desire.

[0316] The processing flow will be explained below.

[0317] Step 1:

[0318] A user opens the system interface using a terminal, selects his / her own photo, and clicks the upload button. The terminal then sends the selected photo file to the server.

[0319] Step 2:

[0320] The server stores the received photo file and uses a facial recognition algorithm to identify the position and contours of the face. The identified feature points (eyes, nose, mouth, eyebrows, etc.) are extracted as data and stored in a database.

[0321] Step 3:

[0322] The user enters the desired image of themselves (e.g., "natural makeup," "glamorous," etc.) into the input form on the device and clicks the send button. The device then sends the entered target image to the server.

[0323] Step 4:

[0324] The server generates prompts based on the extracted feature points and the target image entered by the user, and passes the prompts to a photo editing engine to create an edited photo that matches the user's desired style.

[0325] Step 5:

[0326] Based on the edited photo, the server generates a list of makeup products (e.g., foundation, eye shadow, lipstick, etc.) that the user should use, along with specific makeup steps using those products.

[0327] Step 6:

[0328] The terminal displays the list of makeup tools and makeup procedures received from the server to the user. The procedures for using each makeup tool are explained in detail so that the user can easily understand.

[0329] Step 7:

[0330] The server generates a purchase link corresponding to the suggested makeup products. For each makeup item, it creates an appropriate online shop link and sends it to the terminal.

[0331] Step 8:

[0332] The terminal displays the generated purchase link to the user, who can easily purchase the suggested makeup tool by clicking the displayed link.

[0333] Example 1

[0334] 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."

[0335] Nowadays, many users seek makeup advice to improve their style, but getting advice from a professional makeup artist requires time and money. Users also have difficulty choosing the right makeup tools and finding the right products. Even when purchasing makeup online, it can be difficult to know which products actually suit you.

[0336] 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.

[0337] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating prompts based on the feature points and the image input by the user and editing the photo using a generative AI model, means for suggesting makeup tools and makeup techniques based on the edited photo, and means for generating and displaying a purchase link for the suggested makeup tools. This allows users to easily receive professional makeup advice and easily select and purchase appropriate makeup tools.

[0338] "User" refers to an individual who uses the system, uploads their own photograph, and inputs a target image.

[0339] A "photo uploader" is a piece of hardware or software that allows users to submit their own photos to the system.

[0340] "Facial recognition means" refers to an algorithm or program that performs the process of detecting facial features from uploaded photographs and extracting features such as eyes, nose, mouth, and eyebrows.

[0341] "Feature points" refer to parts such as the eyes, nose, mouth, and eyebrows that occupy important positions in a facial image, and are data that indicate the position information and features of these parts.

[0342] The "target image input means" is a part of software or an interface that has the function of allowing the user to input information such as the desired makeup style in text format and send it to the system.

[0343] A "prompt" refers to text data containing instructions or commands that the system inputs to the generated AI model.

[0344] A "generative AI model" is an artificial intelligence algorithm trained using large datasets to perform tasks such as natural language processing and image processing.

[0345] A "photo editing tool" is software or algorithm that processes a user's photo to match a target image based on instructions output from a generative AI model.

[0346] The "makeup tool suggestion means" is a process or function that suggests cosmetics that the user should use and how to use them based on the edited photo.

[0347] The "purchase link generating means" is a part of software that has the function of generating an online purchase link corresponding to the suggested makeup tool, allowing the user to easily access it.

[0348] The present invention is a system that enables users to realize the self they want to be. This system suggests makeup tools and makeup techniques based on a user's photograph and encourages purchases based on these suggestions. Specific embodiments for implementing this system are described below.

[0349] First, a user uploads a photo of their face using a terminal, which can be a smartphone, tablet, or computer. The uploaded photo is sent to a server, which uses it as the basis for subsequent facial recognition and feature extraction.

[0350] The server then processes the received photos. Specifically, the server performs facial recognition using image processing libraries such as OpenCV and Dlib. The facial recognition algorithm extracts the main facial features (eyes, nose, mouth, eyebrows, etc.) and obtains the position and size data of each feature. This feature data is stored in a database for later use in prompt generation and photo editing.

[0351] Users use their devices to input the image of their desired look in text format, including specific styles such as "natural makeup" or "glamorous makeup." The device converts this text information into JSON format and sends it to the server.

[0352] The server generates a prompt based on the feature point data and the target image entered by the user. This prompt is then fed into a generative AI model (e.g., GPT-4), which generates a text-based instruction like the following:

[0353] "The user in this photo is aiming for a natural look. Use a light brown eyeshadow and a thin eyeliner to make the eyes appear slightly larger. Choose a natural pink lipstick and aim for a smooth overall look."

[0354] Based on the generated instructions, the server calls a photo editing engine (e.g., Adobe Photoshop API) to automatically edit the photo, so that the edited photo matches the user's desired style.

[0355] The server then suggests makeup products and how to use them based on the edited photo. Suggested makeup products include foundation, eyeshadow, lipstick, etc. Specific instructions for using each product are also provided, including how to apply foundation and eyeshadow.

[0356] Finally, the server generates a purchase link for each of the suggested makeup products. This link is located in an online shop, allowing users to easily access and complete the purchase process. The generated purchase link is formatted in HTML and displayed on the user's device. This allows the user to directly purchase the suggested makeup products by clicking the link on the screen.

[0357] For example, if a user uploads a photo of themselves and indicates that they want to achieve "natural makeup," the server first performs facial recognition and extracts features such as "big eyes" and "high nose." Next, a generative AI model is used to generate prompts, and a photo editing engine is used to edit the photo into a "natural makeup" style based on the prompts. The server then suggests the use of foundation, brown eyeshadow, and pink lipstick, and generates and displays purchase links for each product to the user.

[0358] Thus, the present invention provides an effective means for users to receive professional makeup advice from the comfort of their own home and purchase appropriate makeup tools based on the advice.

[0359] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0360] Step 1:

[0361] The user uploads a photo of their face. The user uses the device to select a photo from the camera app or photo gallery, and then uses the system's upload function to send the photo to the server. At this time, the user inputs the file data of the face photo, and the device sends this data to the server as an HTTP request. The server saves the uploaded image file and uses it for subsequent processing.

[0362] Step 2:

[0363] The server performs facial recognition and extracts feature points. The server processes the received photo files using the OpenCV and Dlib libraries in a Python script. Specifically, the face detection algorithm recognizes faces in the photo and extracts feature points such as eyes, nose, mouth, and eyebrows. The input for this process is the saved image file, and the output is the coordinate data of the feature points. The server stores the extracted feature point data in a MySQL database.

[0364] Step 3:

[0365] The user inputs the desired image. Using the device interface, the user inputs a style such as "natural makeup" or "glamorous makeup" into the text field. After completing the input, the user clicks the "Send" button, and the device sends the input string to the server in JSON format. The input of this process is the text data entered by the user, and the output is JSON format data.

[0366] Step 4:

[0367] The server generates prompts and edits photos. The server obtains feature point data extracted from a database and the target image submitted by the user. It generates prompt text based on this. For example, it generates a prompt text for a "natural makeup" style based on the feature point data. The generated prompt text is input into a generative AI model (e.g., GPT-4), and the AI ​​outputs text containing specific instructions for editing the photo. Based on this text, the server edits the photo using the Adobe Photoshop API. The inputs to this process are the feature point data and the target image, and the output is a prompt text containing editing instructions and an edited photo file.

[0368] Step 5:

[0369] The server suggests makeup tools and techniques. Based on the edited photo, the server queries the generative AI model to obtain the makeup tools the user should use and the specific makeup techniques that accompany them. For example, it analyzes the photo and suggests using "foundation, eye shadow, and lipstick," providing detailed instructions on how to use each tool. The input for this process is the edited photo file, and the output is text information about the suggested makeup tools and their application techniques.

[0370] Step 6:

[0371] The server generates and displays a purchase link. The server generates an online purchase link corresponding to the suggested makeup products. This link is formatted in HTML and sent to the user's device. The user can access the corresponding online shop's purchase page by clicking the link displayed on the device. The input to this process is the text information of the makeup products, and the output is an HTML document containing the purchase link.

[0372] (Application example 1)

[0373] 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."

[0374] The present invention relates to a system that suggests makeup that matches the image a user desires and encourages the purchase of makeup tools that match this. Conventional systems only offer suggestions online, making it difficult for users to find the suggested products in physical stores. Another issue is that these systems do not provide detailed advice to help users accurately understand and execute the suggested makeup techniques. This makes it difficult for users to efficiently select makeup products and apply appropriate makeup.

[0375] 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.

[0376] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating a prompt based on the feature points and the image input by the user and editing the photo, means for suggesting makeup tools and makeup techniques based on the edited photo, means for generating and displaying a purchase link for the suggested makeup tools, and means for displaying location information of the suggested makeup tools. This allows the user to easily find suggested products in a physical store and receive detailed makeup technique suggestions.

[0377] "Means for uploading user photos" refers to a method by which a user can provide their own image data to the system.

[0378] "Means for performing facial recognition and extracting feature points from uploaded photographs" refers to a method for detecting faces in the provided image data and identifying the positional information of each part of the face (eyes, nose, mouth, etc.).

[0379] "Means for users to input the image of themselves they want to achieve" refers to a method by which users can communicate to the system the image of the style and makeup they are aiming for in text or selection format.

[0380] The "means for generating prompts based on the feature points and the image input by the user and editing the photo" is a method for generating image editing instructions based on the extracted facial information and the user's desired style, and processing the image in accordance with those instructions.

[0381] The "means of suggesting makeup tools and makeup techniques based on edited photos" refers to a method of suggesting specific makeup tools and how to use them to users by referring to edited images.

[0382] The "means for generating and displaying a purchase link for the suggested makeup tools" is a method for generating an online shopping link for purchasing the suggested makeup products and displaying it to the user.

[0383] The "means for displaying location information of the suggested makeup tools" is a method for providing the user with map information showing where the suggested makeup tools are actually located in the store.

[0384] The present invention is a system that helps users realize the image they want to achieve by suggesting makeup tools and makeup techniques based on a user's photo, leading to purchases. This system is implemented in the following manner.

[0385] First, a user uploads a photo of themselves to the application using their smartphone. This application has a function for sending the photo to a server. The server then performs facial recognition on the uploaded photo and extracts feature points such as the eyes, nose, mouth, and eyebrows. This process uses an image processing library called OpenCV and a pre-trained facial recognition model.

[0386] Next, the user enters the image of their desired look in text form within the application. For example, they could use a specific style such as "natural makeup" or "glamorous." The input image information, along with extracted feature points, is sent to the server. The server uses this information to generate a prompt using a generative AI model. This prompt is then passed to the photo editing engine, which provides instructions for editing the photo to match the user's desired style.

[0387] Based on the edited photo, the server suggests makeup products and techniques suitable for the user. Suggested makeup products include foundation, eye shadow, lipstick, etc. Specific steps and methods for using each makeup product are also provided. Furthermore, an online purchase link for the suggested makeup products is generated and displayed to the user via a smartphone application.

[0388] To support the in-store shopping experience, the application also provides location information for the suggested makeup products, allowing users to easily find the suggested products in the store. Using the in-store map displayed on the smartphone, users can efficiently search for products.

[0389] For example, if a user uploads a photo of themselves and specifies that they are aiming for a "glamorous" look, the server will perform facial recognition on the photo and extract features such as large eyes and a high nose. Based on this, the server will generate prompts and edit the photo to create a "glamorous" style. Based on the editing results, the server will suggest the use of bright eyeshadow, thick lipstick, etc., and provide detailed instructions on how to use each product. The server will then generate a purchase link and in-store location information for the suggested makeup products, which will be displayed to the user via a smartphone application.

[0390] An example of a prompt sentence to input to the generative AI model is as follows:

[0391] User's facial features: [0.3, 0.4, 0.5, ...], Desired makeup style: 'glamorous'

[0392] As described above, users can receive professional makeup advice at home or in a brick-and-mortar store, easily purchase the necessary makeup tools based on that advice, and apply makeup appropriately. It is expected that the present invention will significantly improve users' makeup experience.

[0393] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0394] Step 1:

[0395] A user uploads their own photo to the application using a smartphone. The device receives the photo file selected by the user and sends it to the server. The input is the user's photo, and the output is that the photo data is sent to the server.

[0396] Step 2:

[0397] The server receives the uploaded photo and performs facial recognition processing. It uses OpenCV to detect the facial area from the image and extracts feature points such as eyes, nose, and mouth. The input is the user's photo data, and the output is facial feature point data. This feature point data is stored in a database on the server for further processing.

[0398] Step 3:

[0399] The user inputs the desired makeup style in text format within the application. The terminal sends the input image information to the server. The input is the user's text data, and the output is the image information sent to the server.

[0400] Step 4:

[0401] The server uses a generative AI model to generate prompts based on the received image information of the user's facial feature points and makeup style. These prompts are editing instructions that are passed to the photo editing engine. The input is facial feature point data and image information, and the output is an editing prompt.

[0402] Step 5:

[0403] The photo editing engine edits the photo based on the generated prompt to match the user's desired style. The input is the prompt and the original photo data, and the output is the edited photo data. This edited photo is saved on the server and used for future suggestions.

[0404] Step 6:

[0405] The server then uses the edited photo to suggest makeup products and techniques that are suitable for the user. Using the generated AI model, it recommends specific makeup products, such as foundation and eyeshadow, and how to use them. The input is the edited photo data, and the output is a list of makeup products and how to use them.

[0406] Step 7:

[0407] The server generates and provides online purchase links for the suggested makeup products to the user. It also displays the location information of the suggested makeup products to support in-store purchases. The input is a list of makeup products, and the output is a purchase link and location information.

[0408] Step 8:

[0409] Users can purchase makeup products online through the provided purchasing link, and can also check their location in a physical store to find suggested products in-store. This stage involves user-initiated selection and purchasing behavior.

[0410] 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.

[0411] The present invention is a system that recognizes a user's emotions and suggests makeup tools and makeup techniques based on the emotions. The program of this system is configured as follows.

[0412] Photo upload

[0413] The user uses the device to upload their own photo through the system interface, and the device sends the selected photo file to the server, which stores the photo and uses it for facial and emotion recognition.

[0414] Face Recognition and Feature Extraction

[0415] The server performs facial recognition processing on the received photos to identify facial contours and feature points, such as the positions and shapes of the eyes, nose, mouth, eyebrows, etc. This information is then stored in a database for subsequent processing.

[0416] emotion recognition

[0417] The server analyzes the user's facial expressions from the uploaded photo and recognizes emotions using an emotion engine, such as happiness, sadness, surprise, etc. This emotion information is also used to generate subsequent prompts and make-up suggestions.

[0418] Input the target image

[0419] The user uses the terminal to input the image of the person they want to be. This information is input in text format and includes specific styles such as "natural makeup" or "glamorous." The terminal then sends the input image information to the server.

[0420] Prompt generation and photo editing

[0421] The server generates prompts based on the extracted facial features, the target image entered by the user, and the recognized emotions. The prompts are passed to the photo editing engine, which then creates an edited photo that matches the user's desired style. The emotional data is reflected in the edits, and the style is set to match the user's mood.

[0422] Makeup tools and techniques

[0423] Based on the edited photo, the server suggests makeup products and techniques that best suit the user's emotions and desired image. The suggestions include a list of specific products, such as foundation, eye shadow, and lipstick, along with detailed instructions on how to use each product.

[0424] Generate and view purchasing links

[0425] The server generates a purchase link for the recommended makeup products. This link is from an online shop and is set up so that the user can easily purchase. The terminal displays the generated purchase link to the user in a clickable format.

[0426] Specific examples

[0427] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." At the same time, the "happy" emotion is recognized from the user's facial expression. The server performs facial recognition to extract each feature point and identifies the "happy" emotion using an emotion engine. Based on this information, a prompt is generated and the photo is edited to a style that matches "natural makeup" and a "happy" emotion. Specific makeup techniques for foundation, eye shadow, and lipstick are then suggested, along with detailed instructions for using each tool. Furthermore, a purchase link for the suggested makeup tools is generated and displayed to the user via their device. In this way, users can easily find makeup tools and techniques that match their emotions and the style they are aiming for.

[0428] This invention allows users to receive professional makeup advice tailored to their emotions at that moment from the comfort of their own homes, and to easily purchase the makeup tools they need based on that advice. The system takes the user's emotions into consideration and provides more personalized makeup suggestions, thereby improving user satisfaction.

[0429] The processing flow will be explained below.

[0430] Step 1:

[0431] A user opens the system interface using a terminal, selects his / her own photo, and clicks the upload button. The terminal then sends the selected photo file to the server.

[0432] Step 2:

[0433] The server stores the received photo file and performs facial recognition processing on the photo. Specifically, it identifies the position and outline of the face and extracts feature points such as the eyes, nose, mouth, and eyebrows. The extracted feature points are stored in a database.

[0434] Step 3:

[0435] The server uses an emotion engine to analyze the user's facial expressions from the uploaded photo and recognize emotions. For example, it identifies emotions such as happiness, sadness, and surprise, and generates emotion data. The emotion data is also stored in a database.

[0436] Step 4:

[0437] The user enters the desired image of themselves (e.g., "natural makeup" or "glamorous") in text format into the input form on the device and clicks the send button. The device then sends the entered target image to the server.

[0438] Step 5:

[0439] The server generates prompts based on the extracted facial feature points, the user-input target image, and the recognized emotion data, which are then passed to the photo editing engine and used as editing instructions.

[0440] Step 6:

[0441] The server then uses prompts to edit the photo and create an edited version that matches the user's desired style, such as adjusting eye shape or skin tone to create a natural look. The edited photo is then stored in a database.

[0442] Step 7:

[0443] The server then uses the edited photos to suggest the best makeup tools and techniques for the user. Specifically, it generates a list of foundation, eyeshadow, lipstick, etc., along with a makeup procedure using those items.

[0444] Step 8:

[0445] The terminal displays the list of makeup tools and makeup procedures received from the server to the user. The procedures and methods for using each makeup tool are explained in detail so that the user can easily understand.

[0446] Step 9:

[0447] The server generates a purchase link corresponding to the suggested makeup products and sends it to the terminal. An appropriate online shop link is created for each makeup item.

[0448] Step 10:

[0449] The terminal displays the generated purchase link to the user, who can easily purchase the suggested makeup tool by clicking the displayed link.

[0450] Through the above process, users are presented with makeup tools and techniques based on their own emotions and goals, and can easily purchase them. This system takes into account the user's current emotions and provides more personalized makeup suggestions, thereby improving satisfaction.

[0451] Example 2

[0452] 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."

[0453] Conventional makeup suggestion systems have difficulty providing personalized makeup advice because they do not take the user's emotions into consideration. Furthermore, there is a lack of easy ways for users to purchase the makeup tools they need, resulting in low user satisfaction. The present invention aims to solve these problems by providing a system that can suggest professional makeup that suits the user and encourages them to purchase the makeup.

[0454] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for uploading a user's own photo using the user's terminal, a means for transmitting the uploaded photo to the server and extracting feature points using a face recognition library, and a means for the user to input a target image in text format using the terminal. This allows the user to receive personalized makeup suggestions based on their own emotions and the target image. In addition, by including a means for generating a purchase link for the suggested makeup tools and displaying it on the terminal, the user can easily purchase the necessary makeup tools. As a result, user satisfaction is improved and purchases can be encouraged.

[0455] "User" refers to a person who uses the system to upload their own photos and receive makeup suggestions.

[0456] "Terminal" refers to a computing device used by a user, such as a smartphone or personal computer.

[0457] "Server" refers to a computer system that receives data sent from a terminal and performs processing such as facial recognition, emotion recognition, and makeup suggestions.

[0458] "Photo upload" refers to the act of a user sending their own photo to the system via their terminal.

[0459] A "face recognition library" refers to a software module for extracting facial feature points from a photograph. Examples include OpenCV and Dlib.

[0460] "Feature points" are data points that indicate the position and shape of facial features, such as the position and shape of the eyes, nose, mouth, and eyebrows.

[0461] "Goal image" refers to text information that indicates the specific makeup style the user wants to achieve. Examples include "natural makeup" and "glamorous."

[0462] "Emotion information" refers to data indicating emotions recognized from a user's photo, such as happiness, sadness, surprise, etc.

[0463] A "prompt" refers to a sentence that gives specific editing instructions to a photo editing engine.

[0464] "Photo Editing Engine" means software that edits photos based on prompts. Examples include the Adobe Photoshop API.

[0465] "Makeup tools" refers to the specific products used to apply makeup. Examples include foundation, eye shadow, and lipstick.

[0466] "Makeup technique" refers to the specific steps for applying makeup using makeup tools.

[0467] "Purchase Link" refers to a link to an online shop for purchasing the suggested makeup products.

[0468] "Personalized makeup suggestions" refer to suggestions for customized makeup techniques based on the user's individual emotions and target image.

[0469] The present invention is a system that analyzes a user's emotions and suggests optimal makeup tools and makeup techniques based on those emotions. This system is implemented in the following manner.

[0470] Users use their devices (smartphones or PCs) to upload their own photos through the system interface. The devices then send the selected photo files to the server, which stores the received photos and prepares them for further processing.

[0471] Next, the server uses the stored photo to extract facial feature points using a facial recognition library (e.g., OpenCV or Dlib). These feature points include the position and shape of the eyes, nose, mouth, eyebrows, etc. This extracted feature point information is stored in a database.

[0472] The server then uses the extracted feature point data to utilize an emotion recognition engine (e.g., a general emotion recognition API) to identify the user's emotion. Emotional information recognized includes happiness, sadness, surprise, etc. This emotional information is also stored in a database.

[0473] Next, the user uses the device to enter the makeup style they are aiming for in text format. For example, they can enter a specific style such as "natural makeup" or "glamorous." The device then sends this text data to the server, which then stores the received data in a database.

[0474] The server combines the facial feature point data, the target image, and the emotion information to generate a prompt. This prompt is passed to a photo editing engine (e.g., Adobe Photoshop API), which edits the photo based on the user's desired style. An example of a generated prompt sentence is as follows:

[0475] Example prompt:

[0476] Apply natural makeup to your user's photo and edit it in a style that matches her happy expression. Use light eyeshadow and a light lip color.

[0477] After the edited photo is generated, the server uses the photo to suggest the best makeup products and techniques to match the user's emotions and desired image. The list of specific products includes foundation, eye shadow, lipstick, etc., and provides detailed instructions on how to use each product.

[0478] For example, advice is given such as "Spread liquid foundation thinly and evenly," "Apply light eyeshadow lightly to the outer corners of your eyes," and "Apply light lip color carefully using a lip brush."

[0479] Furthermore, the server generates a purchase link for the recommended makeup tools and sends it to the terminal. The purchase link is from an online shop, and the user can easily complete the purchase procedure by clicking the link.

[0480] In this way, users can receive personalized makeup suggestions based on their own emotions and the style they are aiming for, and can easily purchase the necessary makeup tools.

[0481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0482] Step 1:

[0483] A user uses a terminal to upload his / her own photo through the system interface. Specifically, the user selects a photo through the file selection dialog and clicks the upload button. The input is the user's photo file, which is sent by the terminal to the server. The output is the photo file received by the server.

[0484] Step 2:

[0485] The server stores the received photos and starts the facial recognition process. Specifically, it uses a facial recognition library (e.g., OpenCV or Dlib) on the stored photos. The input is the photo file received from the user, and the output is the facial contour and feature point data extracted from the photo. This data is stored in a database.

[0486] Step 3:

[0487] The server uses an emotion recognition engine (for example, a general emotion recognition API) based on the extracted facial feature point data to identify the user's emotion. Specifically, it makes an API request and receives emotion data as a response. The input is facial feature point data, and the output is recognized emotion information. This information is also stored in a database.

[0488] Step 4:

[0489] The user uses the terminal to input the target image in text format. Specifically, they enter keywords such as "natural makeup" or "glamorous" in the text box and click the send button. The input is the text data entered by the user and is sent from the terminal to the server. The output is the text data received by the server.

[0490] Step 5:

[0491] The server generates a prompt by combining the received target image, facial feature data, and emotion information. Specifically, it uses these data to create a prompt sentence to instruct the photo editing engine. The input is the target image, facial feature data, and emotion information, and the output is the generated prompt sentence.

[0492] Step 6:

[0493] The server passes the generated prompt text to a photo editing engine (e.g., Adobe Photoshop API) to edit the photo. Specifically, the photo is edited based on the prompt, and an edited photo is generated. The input is the prompt text and the original photo data, and the output is the edited photo. The edited photo is saved on the server.

[0494] Step 7:

[0495] Based on the edited photo, the server suggests the best makeup tools and techniques to match the user's emotions and desired image. Specifically, it generates a list of each tool and instructions for using them based on the information in the database. The input is the edited photo and related data, and the output is a list of makeup tools and specific makeup technique advice.

[0496] Step 8:

[0497] The server generates a purchase link for the suggested makeup products and sends it to the terminal. Specifically, it generates a link to an online shop and displays it in a clickable format for the user. The input is a list of makeup products, and the output is a purchase link. The terminal displays this link to the user, allowing them to easily complete the purchase procedure.

[0498] The above are the specific processing steps of this system's program. At each step, appropriate data processing and calculations are performed based on the input data, and the output required for the next step is generated.

[0499] (Application example 2)

[0500] 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."

[0501] Today's consumers want makeup suggestions and purchasing support that reflect their emotions and moods. However, conventional makeup suggestion systems have the problem of being unable to provide personalized advice because they do not take into account the emotional state of each individual user. In particular, when providing online makeup advice, it has been difficult to suggest makeup tools and methods that reflect the user's emotions. Thus, providing makeup support that incorporates the user's emotions is a challenge.

[0502] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0503] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating a prompt based on the feature points and the image input by the user and editing the photo, means for suggesting makeup tools and makeup techniques based on the edited photo, means for generating and displaying a purchase link for the suggested makeup tools, and means for recognizing the user's emotions and suggesting makeup tools and makeup techniques based on the emotions. This allows the user to receive personalized makeup suggestions that reflect their own emotions.

[0504] "User photo uploading means" is a method by which a user can send their photo from their device to the server.

[0505] "Means for performing facial recognition and extracting feature points" refers to a method for detecting faces from uploaded photos and analyzing specific points such as eyes, nose, and mouth.

[0506] "Means for users to input the image of themselves they want to have" refers to a method by which users input their desired makeup style and image of their appearance into the system.

[0507] The "means for generating prompts and editing photos" refers to a method by which the system generates appropriate instructions and edits photos based on facial recognition feature points and the input image.

[0508] The "means for suggesting makeup tools and makeup techniques" is a method for suggesting makeup tools suitable for a user and how to use them based on an edited photo.

[0509] The "means for generating and displaying a purchase link for the suggested makeup tool" is a method for generating an online purchase link for the makeup tool suggested by the system and displaying it to the user.

[0510] "Means for recognizing a user's emotions and suggesting makeup tools and techniques based on those emotions" refers to a method for analyzing emotions from a user's photo and suggesting optimal makeup tools and techniques based on the results.

[0511] The present invention is a system that recognizes a user's emotions and suggests makeup tools and makeup techniques based on the emotions. This system is configured through the following steps.

[0512] First, the user uploads a photo. This operation is performed using a device such as a smartphone. The photo data uploaded from the device is sent to a server and stored on the server. The server then performs facial recognition processing on the received photo. This processing uses a facial recognition software library such as OpenCV. As a result of facial recognition, feature points such as the eyes, nose, mouth, and eyebrows are extracted. This feature point information is stored in a database and used for subsequent processing.

[0513] The server then analyzes the user's facial expressions from the uploaded photo using an emotion recognition library or model such as EmotionDetector. For example, emotions such as happiness, sadness, and surprise are identified. This emotional information is used to generate subsequent prompts and make-up suggestions.

[0514] Next, the user inputs the image of the person they want to be. This information is entered into the terminal in text format, and includes specific styles such as "natural makeup" or "glamorous makeup." This input information is then sent from the terminal to the server.

[0515] The server generates prompts based on this information, namely the extracted facial features, the target image entered by the user, and the recognized emotions. The generated prompts are passed to the photo editing engine using an AI model. The photo editing engine follows the prompts to create an edited photo that matches the user's desired style. Emotional data is reflected in the edits, setting a style that matches the user's mood.

[0516] Based on the edited photo, the server suggests the makeup products and techniques that best suit the user's emotions and desired image. These suggestions include a list of specific products, such as foundation, eye shadow, and lipstick. It also provides detailed instructions on how to use each product and how to apply the makeup. It also generates a link to purchase the suggested makeup products. This link is from an online shop, and is set up so that users can easily purchase them via their device.

[0517] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." At the same time, the "happy" emotion is recognized from the user's facial expression. The server performs facial recognition, extracts each feature point, and identifies the "happy" emotion using an emotion engine. Based on this information, a prompt is generated and the photo is edited to a style that matches "natural makeup" and a "happy" emotion. Specific makeup techniques for foundation, eye shadow, and lipstick are then suggested, along with detailed instructions for using each tool. Furthermore, a purchase link for the suggested makeup tools is generated and displayed to the user via their device. In this way, users can easily find the makeup tools and techniques that match their emotions and the style they are aiming for.

[0518] An example of a prompt sentence is, "Based on the user's photo, edit the makeup to create a natural look. The user's emotion is recognized as happiness, and a makeup style that matches that emotion will be suggested."

[0519] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0520] Step 1:

[0521] The terminal provides an interface for the user to upload photos. The user selects a photo and performs upload. The terminal then sends the selected photo file to the server and temporarily stores the photo data as preprocessing.

[0522] Input: Photos uploaded by the user via the device

[0523] Output: Image data sent to the server

[0524] Step 2:

[0525] The server performs facial recognition on the received photo data using a facial recognition library such as OpenCV. Specifically, it detects the facial area and extracts feature points such as eyes, nose, mouth, and eyebrows. The extracted feature point information is stored in a database.

[0526] Input: Image data sent to the server

[0527] Output: Extracted facial feature points data

[0528] Step 3:

[0529] The server recognizes the user's emotions from the received photo data. It uses an emotion recognition library such as EmotionDetector to analyze facial expressions in the photo and identify the user's emotional state. This emotion data is also stored in a database.

[0530] Input: Image data sent to the server

[0531] Output: User emotion data

[0532] Step 4:

[0533] The user uses the device to input text describing the style or image they want to achieve, such as "natural makeup" or "glamorous makeup." This input data is then sent to the server.

[0534] Input: Text data of styles and images that users input from the terminal

[0535] Output: Text data sent to the server

[0536] Step 5:

[0537] The server generates prompts based on the extracted feature data, the user's input image, and the recognized emotions. These prompts are passed to the photo editing engine, which uses AI models to edit the photo to match the user's desired style.

[0538] Input: feature point data, user input data, emotion data

[0539] Output: Generated prompt and edited photo data

[0540] Step 6:

[0541] The server then suggests the best makeup products and techniques based on the edited photo, including a list of specific makeup products (e.g., foundation, eyeshadow, lipstick, etc.) and instructions for using them.

[0542] Input: Edited photo data

[0543] Output: A list of suggested makeup products and detailed instructions for use

[0544] Step 7:

[0545] The server generates a purchase link for the suggested makeup tool. This link is from an online shop and is displayed to the user. The terminal displays the generated purchase link to the user to encourage purchase.

[0546] Input: A list of suggested makeup products

[0547] Output: Generated purchasing links

[0548] 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.

[0549] 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.

[0550] 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.

[0551] [Third embodiment]

[0552] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0553] 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.

[0554] 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).

[0555] 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.

[0556] 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.

[0557] 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).

[0558] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0559] 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.

[0560] 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.

[0561] 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.

[0562] 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.

[0563] 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."

[0564] The present invention is a system that helps users realize the person they want to be, and suggests makeup tools and makeup techniques based on the user's photograph, leading to purchases. The program of this system is configured as follows.

[0565] Photo upload

[0566] A user uploads his / her own photo to the system using a terminal. This photo is then sent to the server as data necessary for subsequent processing after the user's facial features are recognized. The terminal has the function of sending the uploaded photo file to the server.

[0567] Face Recognition and Feature Extraction

[0568] The server performs facial recognition on the received photo and extracts features such as eyes, nose, mouth, and eyebrows. These features are used to determine the size and position of each part of the user's face. The server stores the extracted features in a database and uses them to generate subsequent prompts.

[0569] Input the target image

[0570] The user inputs the desired image of themselves using a terminal. This input is in text format and includes specific styles such as "natural makeup" or "glamorous." The terminal then sends the input target image to the server.

[0571] Prompt generation and photo editing

[0572] The server generates an editing prompt based on the extracted facial feature points and the user's target image. This prompt is passed to the photo editing engine and contains instructions for editing the photo to match the user's desired style. The edited photo shows the user's new look.

[0573] Makeup tools and techniques

[0574] Based on the edited photo, the server suggests makeup products and specific makeup techniques to the user. The suggested makeup products include foundation, eye shadow, lipstick, etc. Specific instructions for using each makeup product are also provided.

[0575] Generate and view purchasing links

[0576] The server generates a purchase link corresponding to the suggested makeup products. This link is from an online shop and is arranged so that the user can easily purchase the products. The terminal displays the generated purchase link to the user in a clickable format.

[0577] Specific examples

[0578] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." The server performs facial recognition on the photo and extracts features such as large eyes and a high nose. Based on this, the server generates prompts and edits the photo to create a "natural makeup" style. Based on the editing results, the server suggests the use of foundation, eye shadow, and lipstick, and provides detailed instructions on how to use each product. Furthermore, the server generates a purchase link for the suggested makeup products and displays it to the user via their device.

[0579] This system allows users to receive professional makeup advice from the comfort of their own home, and then easily purchase the necessary makeup tools. This system provides an effective means for users to achieve the style they desire.

[0580] The processing flow will be explained below.

[0581] Step 1:

[0582] A user opens the system interface using a terminal, selects his / her own photo, and clicks the upload button. The terminal then sends the selected photo file to the server.

[0583] Step 2:

[0584] The server stores the received photo file and uses a facial recognition algorithm to identify the position and contours of the face. The identified feature points (eyes, nose, mouth, eyebrows, etc.) are extracted as data and stored in a database.

[0585] Step 3:

[0586] The user enters the desired image of themselves (e.g., "natural makeup," "glamorous," etc.) into the input form on the device and clicks the send button. The device then sends the entered target image to the server.

[0587] Step 4:

[0588] The server generates prompts based on the extracted feature points and the target image entered by the user, and passes the prompts to a photo editing engine to create an edited photo that matches the user's desired style.

[0589] Step 5:

[0590] Based on the edited photo, the server generates a list of makeup products (e.g., foundation, eye shadow, lipstick, etc.) that the user should use, along with specific makeup steps using those products.

[0591] Step 6:

[0592] The terminal displays the list of makeup tools and makeup procedures received from the server to the user. The procedures for using each makeup tool are explained in detail so that the user can easily understand.

[0593] Step 7:

[0594] The server generates a purchase link corresponding to the suggested makeup products. For each makeup item, it creates an appropriate online shop link and sends it to the terminal.

[0595] Step 8:

[0596] The terminal displays the generated purchase link to the user, who can easily purchase the suggested makeup tool by clicking the displayed link.

[0597] Example 1

[0598] 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."

[0599] Nowadays, many users seek makeup advice to improve their style, but getting advice from a professional makeup artist requires time and money. Users also have difficulty choosing the right makeup tools and finding the right products. Even when purchasing makeup online, it can be difficult to know which products actually suit you.

[0600] 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.

[0601] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating prompts based on the feature points and the image input by the user and editing the photo using a generative AI model, means for suggesting makeup tools and makeup techniques based on the edited photo, and means for generating and displaying a purchase link for the suggested makeup tools. This allows users to easily receive professional makeup advice and easily select and purchase appropriate makeup tools.

[0602] "User" refers to an individual who uses the system, uploads their own photograph, and inputs a target image.

[0603] A "photo uploader" is a piece of hardware or software that allows users to submit their own photos to the system.

[0604] "Facial recognition means" refers to an algorithm or program that performs the process of detecting facial features from uploaded photographs and extracting features such as eyes, nose, mouth, and eyebrows.

[0605] "Feature points" refer to parts such as the eyes, nose, mouth, and eyebrows that occupy important positions in a facial image, and are data that indicate the position information and features of these parts.

[0606] The "target image input means" is a part of software or an interface that has the function of allowing the user to input information such as the desired makeup style in text format and send it to the system.

[0607] A "prompt" refers to text data containing instructions or commands that the system inputs to the generated AI model.

[0608] A "generative AI model" is an artificial intelligence algorithm trained using large datasets to perform tasks such as natural language processing and image processing.

[0609] A "photo editing tool" is software or algorithm that processes a user's photo to match a target image based on instructions output from a generative AI model.

[0610] The "makeup tool suggestion means" is a process or function that suggests cosmetics that the user should use and how to use them based on the edited photo.

[0611] The "purchase link generating means" is a part of software that has the function of generating an online purchase link corresponding to the suggested makeup tool, allowing the user to easily access it.

[0612] The present invention is a system that enables users to realize the self they want to be. This system suggests makeup tools and makeup techniques based on a user's photograph and encourages purchases based on these suggestions. Specific embodiments for implementing this system are described below.

[0613] First, a user uploads a photo of their face using a terminal, which can be a smartphone, tablet, or computer. The uploaded photo is sent to a server, which uses it as the basis for subsequent facial recognition and feature extraction.

[0614] The server then processes the received photos. Specifically, the server performs facial recognition using image processing libraries such as OpenCV and Dlib. The facial recognition algorithm extracts the main facial features (eyes, nose, mouth, eyebrows, etc.) and obtains the position and size data of each feature. This feature data is stored in a database for later use in prompt generation and photo editing.

[0615] Users use their devices to input the image of their desired look in text format, including specific styles such as "natural makeup" or "glamorous makeup." The device converts this text information into JSON format and sends it to the server.

[0616] The server generates a prompt based on the feature point data and the target image entered by the user. This prompt is then fed into a generative AI model (e.g., GPT-4), which generates a text-based instruction like the following:

[0617] "The user in this photo is aiming for a natural look. Use a light brown eyeshadow and a thin eyeliner to make the eyes appear slightly larger. Choose a natural pink lipstick and aim for a smooth overall look."

[0618] Based on the generated instructions, the server calls a photo editing engine (e.g., Adobe Photoshop API) to automatically edit the photo, so that the edited photo matches the user's desired style.

[0619] The server then suggests makeup products and how to use them based on the edited photo. Suggested makeup products include foundation, eyeshadow, lipstick, etc. Specific instructions for using each product are also provided, including how to apply foundation and eyeshadow.

[0620] Finally, the server generates a purchase link for each of the suggested makeup products. This link is located in an online shop, allowing users to easily access and complete the purchase process. The generated purchase link is formatted in HTML and displayed on the user's device. This allows the user to directly purchase the suggested makeup products by clicking the link on the screen.

[0621] For example, if a user uploads a photo of themselves and indicates that they want to achieve "natural makeup," the server first performs facial recognition and extracts features such as "big eyes" and "high nose." Next, a generative AI model is used to generate prompts, and a photo editing engine is used to edit the photo into a "natural makeup" style based on the prompts. The server then suggests the use of foundation, brown eyeshadow, and pink lipstick, and generates and displays purchase links for each product to the user.

[0622] Thus, the present invention provides an effective means for users to receive professional makeup advice from the comfort of their own home and purchase appropriate makeup tools based on the advice.

[0623] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0624] Step 1:

[0625] The user uploads a photo of their face. The user uses the device to select a photo from the camera app or photo gallery, and then uses the system's upload function to send the photo to the server. At this time, the user inputs the file data of the face photo, and the device sends this data to the server as an HTTP request. The server saves the uploaded image file and uses it for subsequent processing.

[0626] Step 2:

[0627] The server performs facial recognition and extracts feature points. The server processes the received photo files using the OpenCV and Dlib libraries in a Python script. Specifically, the face detection algorithm recognizes faces in the photo and extracts feature points such as eyes, nose, mouth, and eyebrows. The input for this process is the saved image file, and the output is the coordinate data of the feature points. The server stores the extracted feature point data in a MySQL database.

[0628] Step 3:

[0629] The user inputs the desired image. Using the device interface, the user inputs a style such as "natural makeup" or "glamorous makeup" into the text field. After completing the input, the user clicks the "Send" button, and the device sends the input string to the server in JSON format. The input of this process is the text data entered by the user, and the output is JSON format data.

[0630] Step 4:

[0631] The server generates prompts and edits photos. The server obtains feature point data extracted from a database and the target image submitted by the user. It generates prompt text based on this. For example, it generates a prompt text for a "natural makeup" style based on the feature point data. The generated prompt text is input into a generative AI model (e.g., GPT-4), and the AI ​​outputs text containing specific instructions for editing the photo. Based on this text, the server edits the photo using the Adobe Photoshop API. The inputs to this process are the feature point data and the target image, and the output is a prompt text containing editing instructions and an edited photo file.

[0632] Step 5:

[0633] The server suggests makeup tools and techniques. Based on the edited photo, the server queries the generative AI model to obtain the makeup tools the user should use and the specific makeup techniques that accompany them. For example, it analyzes the photo and suggests using "foundation, eye shadow, and lipstick," providing detailed instructions on how to use each tool. The input for this process is the edited photo file, and the output is text information about the suggested makeup tools and their application techniques.

[0634] Step 6:

[0635] The server generates and displays a purchase link. The server generates an online purchase link corresponding to the suggested makeup products. This link is formatted in HTML and sent to the user's device. The user can access the corresponding online shop's purchase page by clicking the link displayed on the device. The input to this process is the text information of the makeup products, and the output is an HTML document containing the purchase link.

[0636] (Application example 1)

[0637] 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."

[0638] The present invention relates to a system that suggests makeup that matches the image a user desires and encourages the purchase of makeup tools that match this. Conventional systems only offer suggestions online, making it difficult for users to find the suggested products in physical stores. Another issue is that these systems do not provide detailed advice to help users accurately understand and execute the suggested makeup techniques. This makes it difficult for users to efficiently select makeup products and apply appropriate makeup.

[0639] 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.

[0640] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating a prompt based on the feature points and the image input by the user and editing the photo, means for suggesting makeup tools and makeup techniques based on the edited photo, means for generating and displaying a purchase link for the suggested makeup tools, and means for displaying location information of the suggested makeup tools. This allows the user to easily find suggested products in a physical store and receive detailed makeup technique suggestions.

[0641] "Means for uploading user photos" refers to a method by which a user can provide their own image data to the system.

[0642] "Means for performing facial recognition and extracting feature points from uploaded photographs" refers to a method for detecting faces in the provided image data and identifying the positional information of each part of the face (eyes, nose, mouth, etc.).

[0643] "Means for users to input the image of themselves they want to achieve" refers to a method by which users can communicate to the system the image of the style and makeup they are aiming for in text or selection format.

[0644] The "means for generating prompts based on the feature points and the image input by the user and editing the photo" is a method for generating image editing instructions based on the extracted facial information and the user's desired style, and processing the image in accordance with those instructions.

[0645] The "means of suggesting makeup tools and makeup techniques based on edited photos" refers to a method of suggesting specific makeup tools and how to use them to users by referring to edited images.

[0646] The "means for generating and displaying a purchase link for the suggested makeup tools" is a method for generating an online shopping link for purchasing the suggested makeup products and displaying it to the user.

[0647] The "means for displaying location information of the suggested makeup tools" is a method for providing the user with map information showing where the suggested makeup tools are actually located in the store.

[0648] The present invention is a system that helps users realize the image they want to achieve by suggesting makeup tools and makeup techniques based on a user's photo, leading to purchases. This system is implemented in the following manner.

[0649] First, a user uploads a photo of themselves to the application using their smartphone. This application has a function for sending the photo to a server. The server then performs facial recognition on the uploaded photo and extracts feature points such as the eyes, nose, mouth, and eyebrows. This process uses an image processing library called OpenCV and a pre-trained facial recognition model.

[0650] Next, the user enters the image of their desired look in text form within the application. For example, they could use a specific style such as "natural makeup" or "glamorous." The input image information, along with extracted feature points, is sent to the server. The server uses this information to generate a prompt using a generative AI model. This prompt is then passed to the photo editing engine, which provides instructions for editing the photo to match the user's desired style.

[0651] Based on the edited photo, the server suggests makeup products and techniques suitable for the user. Suggested makeup products include foundation, eye shadow, lipstick, etc. Specific steps and methods for using each makeup product are also provided. Furthermore, an online purchase link for the suggested makeup products is generated and displayed to the user via a smartphone application.

[0652] To support the in-store shopping experience, the application also provides location information for the suggested makeup products, allowing users to easily find the suggested products in the store. Using the in-store map displayed on the smartphone, users can efficiently search for products.

[0653] For example, if a user uploads a photo of themselves and specifies that they are aiming for a "glamorous" look, the server will perform facial recognition on the photo and extract features such as large eyes and a high nose. Based on this, the server will generate prompts and edit the photo to create a "glamorous" style. Based on the editing results, the server will suggest the use of bright eyeshadow, thick lipstick, etc., and provide detailed instructions on how to use each product. The server will then generate a purchase link and in-store location information for the suggested makeup products, which will be displayed to the user via a smartphone application.

[0654] An example of a prompt sentence to input to the generative AI model is as follows:

[0655] User's facial features: [0.3, 0.4, 0.5, ...], Desired makeup style: 'glamorous'

[0656] As described above, users can receive professional makeup advice at home or in a brick-and-mortar store, easily purchase the necessary makeup tools based on that advice, and apply makeup appropriately. It is expected that the present invention will significantly improve users' makeup experience.

[0657] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0658] Step 1:

[0659] A user uploads their own photo to the application using a smartphone. The device receives the photo file selected by the user and sends it to the server. The input is the user's photo, and the output is that the photo data is sent to the server.

[0660] Step 2:

[0661] The server receives the uploaded photo and performs facial recognition processing. It uses OpenCV to detect the facial area from the image and extracts feature points such as eyes, nose, and mouth. The input is the user's photo data, and the output is facial feature point data. This feature point data is stored in a database on the server for further processing.

[0662] Step 3:

[0663] The user inputs the desired makeup style in text format within the application. The terminal sends the input image information to the server. The input is the user's text data, and the output is the image information sent to the server.

[0664] Step 4:

[0665] The server uses a generative AI model to generate prompts based on the received image information of the user's facial feature points and makeup style. These prompts are editing instructions that are passed to the photo editing engine. The input is facial feature point data and image information, and the output is an editing prompt.

[0666] Step 5:

[0667] The photo editing engine edits the photo based on the generated prompt to match the user's desired style. The input is the prompt and the original photo data, and the output is the edited photo data. This edited photo is saved on the server and used for future suggestions.

[0668] Step 6:

[0669] The server then uses the edited photo to suggest makeup products and techniques that are suitable for the user. Using the generated AI model, it recommends specific makeup products, such as foundation and eyeshadow, and how to use them. The input is the edited photo data, and the output is a list of makeup products and how to use them.

[0670] Step 7:

[0671] The server generates and provides online purchase links for the suggested makeup products to the user. It also displays the location information of the suggested makeup products to support in-store purchases. The input is a list of makeup products, and the output is a purchase link and location information.

[0672] Step 8:

[0673] Users can purchase makeup products online through the provided purchasing link, and can also check their location in a physical store to find suggested products in-store. This stage involves user-initiated selection and purchasing behavior.

[0674] 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.

[0675] The present invention is a system that recognizes a user's emotions and suggests makeup tools and makeup techniques based on the emotions. The program of this system is configured as follows.

[0676] Photo upload

[0677] The user uses the device to upload their own photo through the system interface, and the device sends the selected photo file to the server, which stores the photo and uses it for facial and emotion recognition.

[0678] Face Recognition and Feature Extraction

[0679] The server performs facial recognition processing on the received photos to identify facial contours and feature points, such as the positions and shapes of the eyes, nose, mouth, eyebrows, etc. This information is then stored in a database for subsequent processing.

[0680] emotion recognition

[0681] The server analyzes the user's facial expressions from the uploaded photo and recognizes emotions using an emotion engine, such as happiness, sadness, surprise, etc. This emotion information is also used to generate subsequent prompts and make-up suggestions.

[0682] Input the target image

[0683] The user uses the terminal to input the image of the person they want to be. This information is input in text format and includes specific styles such as "natural makeup" or "glamorous." The terminal then sends the input image information to the server.

[0684] Prompt generation and photo editing

[0685] The server generates prompts based on the extracted facial features, the target image entered by the user, and the recognized emotions. The prompts are passed to the photo editing engine, which then creates an edited photo that matches the user's desired style. The emotional data is reflected in the edits, and the style is set to match the user's mood.

[0686] Makeup tools and techniques

[0687] Based on the edited photo, the server suggests makeup products and techniques that best suit the user's emotions and desired image. The suggestions include a list of specific products, such as foundation, eye shadow, and lipstick, along with detailed instructions on how to use each product.

[0688] Generate and view purchasing links

[0689] The server generates a purchase link for the recommended makeup products. This link is from an online shop and is set up so that the user can easily purchase. The terminal displays the generated purchase link to the user in a clickable format.

[0690] Specific examples

[0691] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." At the same time, the "happy" emotion is recognized from the user's facial expression. The server performs facial recognition to extract each feature point and identifies the "happy" emotion using an emotion engine. Based on this information, a prompt is generated and the photo is edited to a style that matches "natural makeup" and a "happy" emotion. Specific makeup techniques for foundation, eye shadow, and lipstick are then suggested, along with detailed instructions for using each tool. Furthermore, a purchase link for the suggested makeup tools is generated and displayed to the user via their device. In this way, users can easily find makeup tools and techniques that match their emotions and the style they are aiming for.

[0692] This invention allows users to receive professional makeup advice tailored to their emotions at that moment from the comfort of their own homes, and to easily purchase the makeup tools they need based on that advice. The system takes the user's emotions into consideration and provides more personalized makeup suggestions, thereby improving user satisfaction.

[0693] The processing flow will be explained below.

[0694] Step 1:

[0695] A user opens the system interface using a terminal, selects his / her own photo, and clicks the upload button. The terminal then sends the selected photo file to the server.

[0696] Step 2:

[0697] The server stores the received photo file and performs facial recognition processing on the photo. Specifically, it identifies the position and outline of the face and extracts feature points such as the eyes, nose, mouth, and eyebrows. The extracted feature points are stored in a database.

[0698] Step 3:

[0699] The server uses an emotion engine to analyze the user's facial expressions from the uploaded photo and recognize emotions. For example, it identifies emotions such as happiness, sadness, and surprise, and generates emotion data. The emotion data is also stored in a database.

[0700] Step 4:

[0701] The user enters the desired image of themselves (e.g., "natural makeup" or "glamorous") in text format into the input form on the device and clicks the send button. The device then sends the entered target image to the server.

[0702] Step 5:

[0703] The server generates prompts based on the extracted facial feature points, the user-input target image, and the recognized emotion data, which are then passed to the photo editing engine and used as editing instructions.

[0704] Step 6:

[0705] The server then uses prompts to edit the photo and create an edited version that matches the user's desired style, such as adjusting eye shape or skin tone to create a natural look. The edited photo is then stored in a database.

[0706] Step 7:

[0707] The server then uses the edited photos to suggest the best makeup tools and techniques for the user. Specifically, it generates a list of foundation, eyeshadow, lipstick, etc., along with a makeup procedure using those items.

[0708] Step 8:

[0709] The terminal displays the list of makeup tools and makeup procedures received from the server to the user. The procedures and methods for using each makeup tool are explained in detail so that the user can easily understand.

[0710] Step 9:

[0711] The server generates a purchase link corresponding to the suggested makeup products and sends it to the terminal. An appropriate online shop link is created for each makeup item.

[0712] Step 10:

[0713] The terminal displays the generated purchase link to the user, who can easily purchase the suggested makeup tool by clicking the displayed link.

[0714] Through the above process, users are presented with makeup tools and techniques based on their own emotions and goals, and can easily purchase them. This system takes into account the user's current emotions and provides more personalized makeup suggestions, thereby improving satisfaction.

[0715] Example 2

[0716] 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."

[0717] Conventional makeup suggestion systems have difficulty providing personalized makeup advice because they do not take the user's emotions into consideration. Furthermore, there is a lack of easy ways for users to purchase the makeup tools they need, resulting in low user satisfaction. The present invention aims to solve these problems by providing a system that can suggest professional makeup that suits the user and encourages them to purchase the makeup.

[0718] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for uploading a user's own photo using the user's terminal, a means for transmitting the uploaded photo to the server and extracting feature points using a face recognition library, and a means for the user to input a target image in text format using the terminal. This allows the user to receive personalized makeup suggestions based on their own emotions and the target image. In addition, by including a means for generating a purchase link for the suggested makeup tools and displaying it on the terminal, the user can easily purchase the necessary makeup tools. As a result, user satisfaction is improved and purchases can be encouraged.

[0719] "User" refers to a person who uses the system to upload their own photos and receive makeup suggestions.

[0720] "Terminal" refers to a computing device used by a user, such as a smartphone or personal computer.

[0721] "Server" refers to a computer system that receives data sent from a terminal and performs processing such as facial recognition, emotion recognition, and makeup suggestions.

[0722] "Photo upload" refers to the act of a user sending their own photo to the system via their terminal.

[0723] A "face recognition library" refers to a software module for extracting facial feature points from a photograph. Examples include OpenCV and Dlib.

[0724] "Feature points" are data points that indicate the position and shape of facial features, such as the position and shape of the eyes, nose, mouth, and eyebrows.

[0725] "Goal image" refers to text information that indicates the specific makeup style the user wants to achieve. Examples include "natural makeup" and "glamorous."

[0726] "Emotion information" refers to data indicating emotions recognized from a user's photo, such as happiness, sadness, surprise, etc.

[0727] A "prompt" refers to a sentence that gives specific editing instructions to a photo editing engine.

[0728] "Photo Editing Engine" means software that edits photos based on prompts. Examples include the Adobe Photoshop API.

[0729] "Makeup tools" refers to the specific products used to apply makeup. Examples include foundation, eye shadow, and lipstick.

[0730] "Makeup technique" refers to the specific steps for applying makeup using makeup tools.

[0731] "Purchase Link" refers to a link to an online shop for purchasing the suggested makeup products.

[0732] "Personalized makeup suggestions" refer to suggestions for customized makeup techniques based on the user's individual emotions and target image.

[0733] The present invention is a system that analyzes a user's emotions and suggests optimal makeup tools and makeup techniques based on those emotions. This system is implemented in the following manner.

[0734] Users use their devices (smartphones or PCs) to upload their own photos through the system interface. The devices then send the selected photo files to the server, which stores the received photos and prepares them for further processing.

[0735] Next, the server uses the stored photo to extract facial feature points using a facial recognition library (e.g., OpenCV or Dlib). These feature points include the position and shape of the eyes, nose, mouth, eyebrows, etc. This extracted feature point information is stored in a database.

[0736] The server then uses the extracted feature point data to utilize an emotion recognition engine (e.g., a general emotion recognition API) to identify the user's emotion. Emotional information recognized includes happiness, sadness, surprise, etc. This emotional information is also stored in a database.

[0737] Next, the user uses the device to enter the makeup style they are aiming for in text format. For example, they can enter a specific style such as "natural makeup" or "glamorous." The device then sends this text data to the server, which then stores the received data in a database.

[0738] The server combines the facial feature point data, the target image, and the emotion information to generate a prompt. This prompt is passed to a photo editing engine (e.g., Adobe Photoshop API), which edits the photo based on the user's desired style. An example of a generated prompt sentence is as follows:

[0739] Example prompt:

[0740] Apply natural makeup to your user's photo and edit it in a style that matches her happy expression. Use light eyeshadow and a light lip color.

[0741] After the edited photo is generated, the server uses the photo to suggest the best makeup products and techniques to match the user's emotions and desired image. The list of specific products includes foundation, eye shadow, lipstick, etc., and provides detailed instructions on how to use each product.

[0742] For example, advice is given such as "Spread liquid foundation thinly and evenly," "Apply light eyeshadow lightly to the outer corners of your eyes," and "Apply light lip color carefully using a lip brush."

[0743] Furthermore, the server generates a purchase link for the recommended makeup tools and sends it to the terminal. The purchase link is from an online shop, and the user can easily complete the purchase procedure by clicking the link.

[0744] In this way, users can receive personalized makeup suggestions based on their own emotions and the style they are aiming for, and can easily purchase the necessary makeup tools.

[0745] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0746] Step 1:

[0747] A user uses a terminal to upload his / her own photo through the system interface. Specifically, the user selects a photo through the file selection dialog and clicks the upload button. The input is the user's photo file, which is sent by the terminal to the server. The output is the photo file received by the server.

[0748] Step 2:

[0749] The server stores the received photos and starts the facial recognition process. Specifically, it uses a facial recognition library (e.g., OpenCV or Dlib) on the stored photos. The input is the photo file received from the user, and the output is the facial contour and feature point data extracted from the photo. This data is stored in a database.

[0750] Step 3:

[0751] The server uses an emotion recognition engine (for example, a general emotion recognition API) based on the extracted facial feature point data to identify the user's emotion. Specifically, it makes an API request and receives emotion data as a response. The input is facial feature point data, and the output is recognized emotion information. This information is also stored in a database.

[0752] Step 4:

[0753] The user uses the terminal to input the target image in text format. Specifically, they enter keywords such as "natural makeup" or "glamorous" in the text box and click the send button. The input is the text data entered by the user and is sent from the terminal to the server. The output is the text data received by the server.

[0754] Step 5:

[0755] The server generates a prompt by combining the received target image, facial feature data, and emotion information. Specifically, it uses these data to create a prompt sentence to instruct the photo editing engine. The input is the target image, facial feature data, and emotion information, and the output is the generated prompt sentence.

[0756] Step 6:

[0757] The server passes the generated prompt text to a photo editing engine (e.g., Adobe Photoshop API) to edit the photo. Specifically, the photo is edited based on the prompt, and an edited photo is generated. The input is the prompt text and the original photo data, and the output is the edited photo. The edited photo is saved on the server.

[0758] Step 7:

[0759] Based on the edited photo, the server suggests the best makeup tools and techniques to match the user's emotions and desired image. Specifically, it generates a list of each tool and instructions for using them based on the information in the database. The input is the edited photo and related data, and the output is a list of makeup tools and specific makeup technique advice.

[0760] Step 8:

[0761] The server generates a purchase link for the suggested makeup products and sends it to the terminal. Specifically, it generates a link to an online shop and displays it in a clickable format for the user. The input is a list of makeup products, and the output is a purchase link. The terminal displays this link to the user, allowing them to easily complete the purchase procedure.

[0762] The above are the specific processing steps of this system's program. At each step, appropriate data processing and calculations are performed based on the input data, and the output required for the next step is generated.

[0763] (Application example 2)

[0764] 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."

[0765] Today's consumers want makeup suggestions and purchasing support that reflect their emotions and moods. However, conventional makeup suggestion systems have the problem of being unable to provide personalized advice because they do not take into account the emotional state of each individual user. In particular, when providing online makeup advice, it has been difficult to suggest makeup tools and methods that reflect the user's emotions. Thus, providing makeup support that incorporates the user's emotions is a challenge.

[0766] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0767] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating a prompt based on the feature points and the image input by the user and editing the photo, means for suggesting makeup tools and makeup techniques based on the edited photo, means for generating and displaying a purchase link for the suggested makeup tools, and means for recognizing the user's emotions and suggesting makeup tools and makeup techniques based on the emotions. This allows the user to receive personalized makeup suggestions that reflect their own emotions.

[0768] "User photo uploading means" is a method by which a user can send their photo from their device to the server.

[0769] "Means for performing facial recognition and extracting feature points" refers to a method for detecting faces from uploaded photos and analyzing specific points such as eyes, nose, and mouth.

[0770] "Means for users to input the image of themselves they want to have" refers to a method by which users input their desired makeup style and image of their appearance into the system.

[0771] The "means for generating prompts and editing photos" refers to a method by which the system generates appropriate instructions and edits photos based on facial recognition feature points and the input image.

[0772] The "means for suggesting makeup tools and makeup techniques" is a method for suggesting makeup tools suitable for a user and how to use them based on an edited photo.

[0773] The "means for generating and displaying a purchase link for the suggested makeup tool" is a method for generating an online purchase link for the makeup tool suggested by the system and displaying it to the user.

[0774] "Means for recognizing a user's emotions and suggesting makeup tools and techniques based on those emotions" refers to a method for analyzing emotions from a user's photo and suggesting optimal makeup tools and techniques based on the results.

[0775] The present invention is a system that recognizes a user's emotions and suggests makeup tools and makeup techniques based on the emotions. This system is configured through the following steps.

[0776] First, the user uploads a photo. This operation is performed using a device such as a smartphone. The photo data uploaded from the device is sent to a server and stored on the server. The server then performs facial recognition processing on the received photo. This processing uses a facial recognition software library such as OpenCV. As a result of facial recognition, feature points such as the eyes, nose, mouth, and eyebrows are extracted. This feature point information is stored in a database and used for subsequent processing.

[0777] The server then analyzes the user's facial expressions from the uploaded photo using an emotion recognition library or model such as EmotionDetector. For example, emotions such as happiness, sadness, and surprise are identified. This emotional information is used to generate subsequent prompts and make-up suggestions.

[0778] Next, the user inputs the image of the person they want to be. This information is entered into the terminal in text format, and includes specific styles such as "natural makeup" or "glamorous makeup." This input information is then sent from the terminal to the server.

[0779] The server generates prompts based on this information, namely the extracted facial features, the target image entered by the user, and the recognized emotions. The generated prompts are passed to the photo editing engine using an AI model. The photo editing engine follows the prompts to create an edited photo that matches the user's desired style. Emotional data is reflected in the edits, setting a style that matches the user's mood.

[0780] Based on the edited photo, the server suggests the makeup products and techniques that best suit the user's emotions and desired image. These suggestions include a list of specific products, such as foundation, eye shadow, and lipstick. It also provides detailed instructions on how to use each product and how to apply the makeup. It also generates a link to purchase the suggested makeup products. This link is from an online shop, and is set up so that users can easily purchase them via their device.

[0781] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." At the same time, the "happy" emotion is recognized from the user's facial expression. The server performs facial recognition, extracts each feature point, and identifies the "happy" emotion using an emotion engine. Based on this information, a prompt is generated and the photo is edited to a style that matches "natural makeup" and a "happy" emotion. Specific makeup techniques for foundation, eye shadow, and lipstick are then suggested, along with detailed instructions for using each tool. Furthermore, a purchase link for the suggested makeup tools is generated and displayed to the user via their device. In this way, users can easily find the makeup tools and techniques that match their emotions and the style they are aiming for.

[0782] An example of a prompt sentence is, "Based on the user's photo, edit the makeup to create a natural look. The user's emotion is recognized as happiness, and a makeup style that matches that emotion will be suggested."

[0783] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0784] Step 1:

[0785] The terminal provides an interface for the user to upload photos. The user selects a photo and performs upload. The terminal then sends the selected photo file to the server and temporarily stores the photo data as preprocessing.

[0786] Input: Photos uploaded by the user via the device

[0787] Output: Image data sent to the server

[0788] Step 2:

[0789] The server performs facial recognition on the received photo data using a facial recognition library such as OpenCV. Specifically, it detects the facial area and extracts feature points such as eyes, nose, mouth, and eyebrows. The extracted feature point information is stored in a database.

[0790] Input: Image data sent to the server

[0791] Output: Extracted facial feature points data

[0792] Step 3:

[0793] The server recognizes the user's emotions from the received photo data. It uses an emotion recognition library such as EmotionDetector to analyze facial expressions in the photo and identify the user's emotional state. This emotion data is also stored in a database.

[0794] Input: Image data sent to the server

[0795] Output: User emotion data

[0796] Step 4:

[0797] The user uses the device to input text describing the style or image they want to achieve, such as "natural makeup" or "glamorous makeup." This input data is then sent to the server.

[0798] Input: Text data of styles and images that users input from the terminal

[0799] Output: Text data sent to the server

[0800] Step 5:

[0801] The server generates prompts based on the extracted feature data, the user's input image, and the recognized emotions. These prompts are passed to the photo editing engine, which uses AI models to edit the photo to match the user's desired style.

[0802] Input: feature point data, user input data, emotion data

[0803] Output: Generated prompt and edited photo data

[0804] Step 6:

[0805] The server then suggests the best makeup products and techniques based on the edited photo, including a list of specific makeup products (e.g., foundation, eyeshadow, lipstick, etc.) and instructions for using them.

[0806] Input: Edited photo data

[0807] Output: A list of suggested makeup products and detailed instructions for use

[0808] Step 7:

[0809] The server generates a purchase link for the suggested makeup tool. This link is from an online shop and is displayed to the user. The terminal displays the generated purchase link to the user to encourage purchase.

[0810] Input: A list of suggested makeup products

[0811] Output: Generated purchasing links

[0812] 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.

[0813] 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.

[0814] 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.

[0815] [Fourth embodiment]

[0816] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0817] 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.

[0818] 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).

[0819] 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.

[0820] 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.

[0821] 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).

[0822] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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."

[0829] The present invention is a system that helps users realize the person they want to be, and suggests makeup tools and makeup techniques based on the user's photograph, leading to purchases. The program of this system is configured as follows.

[0830] Photo upload

[0831] A user uploads his / her own photo to the system using a terminal. This photo is then sent to the server as data necessary for subsequent processing after the user's facial features are recognized. The terminal has the function of sending the uploaded photo file to the server.

[0832] Face Recognition and Feature Extraction

[0833] The server performs facial recognition on the received photo and extracts features such as eyes, nose, mouth, and eyebrows. These features are used to determine the size and position of each part of the user's face. The server stores the extracted features in a database and uses them to generate subsequent prompts.

[0834] Input the target image

[0835] The user inputs the desired image of themselves using a terminal. This input is in text format and includes specific styles such as "natural makeup" or "glamorous." The terminal then sends the input target image to the server.

[0836] Prompt generation and photo editing

[0837] The server generates an editing prompt based on the extracted facial feature points and the user's target image. This prompt is passed to the photo editing engine and contains instructions for editing the photo to match the user's desired style. The edited photo shows the user's new look.

[0838] Makeup tools and techniques

[0839] Based on the edited photo, the server suggests makeup products and specific makeup techniques to the user. The suggested makeup products include foundation, eye shadow, lipstick, etc. Specific instructions for using each makeup product are also provided.

[0840] Generate and view purchasing links

[0841] The server generates a purchase link corresponding to the suggested makeup products. This link is from an online shop and is arranged so that the user can easily purchase the products. The terminal displays the generated purchase link to the user in a clickable format.

[0842] Specific examples

[0843] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." The server performs facial recognition on the photo and extracts features such as large eyes and a high nose. Based on this, the server generates prompts and edits the photo to create a "natural makeup" style. Based on the editing results, the server suggests the use of foundation, eye shadow, and lipstick, and provides detailed instructions on how to use each product. Furthermore, the server generates a purchase link for the suggested makeup products and displays it to the user via their device.

[0844] This system allows users to receive professional makeup advice from the comfort of their own home, and then easily purchase the necessary makeup tools. This system provides an effective means for users to achieve the style they desire.

[0845] The processing flow will be explained below.

[0846] Step 1:

[0847] A user opens the system interface using a terminal, selects his / her own photo, and clicks the upload button. The terminal then sends the selected photo file to the server.

[0848] Step 2:

[0849] The server stores the received photo file and uses a facial recognition algorithm to identify the position and contours of the face. The identified feature points (eyes, nose, mouth, eyebrows, etc.) are extracted as data and stored in a database.

[0850] Step 3:

[0851] The user enters the desired image of themselves (e.g., "natural makeup," "glamorous," etc.) into the input form on the device and clicks the send button. The device then sends the entered target image to the server.

[0852] Step 4:

[0853] The server generates prompts based on the extracted feature points and the target image entered by the user, and passes the prompts to a photo editing engine to create an edited photo that matches the user's desired style.

[0854] Step 5:

[0855] Based on the edited photo, the server generates a list of makeup products (e.g., foundation, eye shadow, lipstick, etc.) that the user should use, along with specific makeup steps using those products.

[0856] Step 6:

[0857] The terminal displays the list of makeup tools and makeup procedures received from the server to the user. The procedures for using each makeup tool are explained in detail so that the user can easily understand.

[0858] Step 7:

[0859] The server generates a purchase link corresponding to the suggested makeup products. For each makeup item, it creates an appropriate online shop link and sends it to the terminal.

[0860] Step 8:

[0861] The terminal displays the generated purchase link to the user, who can easily purchase the suggested makeup tool by clicking the displayed link.

[0862] Example 1

[0863] 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."

[0864] Nowadays, many users seek makeup advice to improve their style, but getting advice from a professional makeup artist requires time and money. Users also have difficulty choosing the right makeup tools and finding the right products. Even when purchasing makeup online, it can be difficult to know which products actually suit you.

[0865] 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.

[0866] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating prompts based on the feature points and the image input by the user and editing the photo using a generative AI model, means for suggesting makeup tools and makeup techniques based on the edited photo, and means for generating and displaying a purchase link for the suggested makeup tools. This allows users to easily receive professional makeup advice and easily select and purchase appropriate makeup tools.

[0867] "User" refers to an individual who uses the system, uploads their own photograph, and inputs a target image.

[0868] A "photo uploader" is a piece of hardware or software that allows users to submit their own photos to the system.

[0869] "Facial recognition means" refers to an algorithm or program that performs the process of detecting facial features from uploaded photographs and extracting features such as eyes, nose, mouth, and eyebrows.

[0870] "Feature points" refer to parts such as the eyes, nose, mouth, and eyebrows that occupy important positions in a facial image, and are data that indicate the position information and features of these parts.

[0871] The "target image input means" is a part of software or an interface that has the function of allowing the user to input information such as the desired makeup style in text format and send it to the system.

[0872] A "prompt" refers to text data containing instructions or commands that the system inputs to the generated AI model.

[0873] A "generative AI model" is an artificial intelligence algorithm trained using large datasets to perform tasks such as natural language processing and image processing.

[0874] A "photo editing tool" is software or algorithm that processes a user's photo to match a target image based on instructions output from a generative AI model.

[0875] The "makeup tool suggestion means" is a process or function that suggests cosmetics that the user should use and how to use them based on the edited photo.

[0876] The "purchase link generating means" is a part of software that has the function of generating an online purchase link corresponding to the suggested makeup tool, allowing the user to easily access it.

[0877] The present invention is a system that enables users to realize the self they want to be. This system suggests makeup tools and makeup techniques based on a user's photograph and encourages purchases based on these suggestions. Specific embodiments for implementing this system are described below.

[0878] First, a user uploads a photo of their face using a terminal, which can be a smartphone, tablet, or computer. The uploaded photo is sent to a server, which uses it as the basis for subsequent facial recognition and feature extraction.

[0879] The server then processes the received photos. Specifically, the server performs facial recognition using image processing libraries such as OpenCV and Dlib. The facial recognition algorithm extracts the main facial features (eyes, nose, mouth, eyebrows, etc.) and obtains the position and size data of each feature. This feature data is stored in a database for later use in prompt generation and photo editing.

[0880] Users use their devices to input the image of their desired look in text format, including specific styles such as "natural makeup" or "glamorous makeup." The device converts this text information into JSON format and sends it to the server.

[0881] The server generates a prompt based on the feature point data and the target image entered by the user. This prompt is then fed into a generative AI model (e.g., GPT-4), which generates a text-based instruction like the following:

[0882] "The user in this photo is aiming for a natural look. Use a light brown eyeshadow and a thin eyeliner to make the eyes appear slightly larger. Choose a natural pink lipstick and aim for a smooth overall look."

[0883] Based on the generated instructions, the server calls a photo editing engine (e.g., Adobe Photoshop API) to automatically edit the photo, so that the edited photo matches the user's desired style.

[0884] The server then suggests makeup products and how to use them based on the edited photo. Suggested makeup products include foundation, eyeshadow, lipstick, etc. Specific instructions for using each product are also provided, including how to apply foundation and eyeshadow.

[0885] Finally, the server generates a purchase link for each of the suggested makeup products. This link is located in an online shop, allowing users to easily access and complete the purchase process. The generated purchase link is formatted in HTML and displayed on the user's device. This allows the user to directly purchase the suggested makeup products by clicking the link on the screen.

[0886] For example, if a user uploads a photo of themselves and indicates that they want to achieve "natural makeup," the server first performs facial recognition and extracts features such as "big eyes" and "high nose." Next, a generative AI model is used to generate prompts, and a photo editing engine is used to edit the photo into a "natural makeup" style based on the prompts. The server then suggests the use of foundation, brown eyeshadow, and pink lipstick, and generates and displays purchase links for each product to the user.

[0887] Thus, the present invention provides an effective means for users to receive professional makeup advice from the comfort of their own home and purchase appropriate makeup tools based on the advice.

[0888] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0889] Step 1:

[0890] The user uploads a photo of their face. The user uses the device to select a photo from the camera app or photo gallery, and then uses the system's upload function to send the photo to the server. At this time, the user inputs the file data of the face photo, and the device sends this data to the server as an HTTP request. The server saves the uploaded image file and uses it for subsequent processing.

[0891] Step 2:

[0892] The server performs facial recognition and extracts feature points. The server processes the received photo files using the OpenCV and Dlib libraries in a Python script. Specifically, the face detection algorithm recognizes faces in the photo and extracts feature points such as eyes, nose, mouth, and eyebrows. The input for this process is the saved image file, and the output is the coordinate data of the feature points. The server stores the extracted feature point data in a MySQL database.

[0893] Step 3:

[0894] The user inputs the desired image. Using the device interface, the user inputs a style such as "natural makeup" or "glamorous makeup" into the text field. After completing the input, the user clicks the "Send" button, and the device sends the input string to the server in JSON format. The input of this process is the text data entered by the user, and the output is JSON format data.

[0895] Step 4:

[0896] The server generates prompts and edits photos. The server obtains feature point data extracted from a database and the target image submitted by the user. It generates prompt text based on this. For example, it generates a prompt text for a "natural makeup" style based on the feature point data. The generated prompt text is input into a generative AI model (e.g., GPT-4), and the AI ​​outputs text containing specific instructions for editing the photo. Based on this text, the server edits the photo using the Adobe Photoshop API. The inputs to this process are the feature point data and the target image, and the output is a prompt text containing editing instructions and an edited photo file.

[0897] Step 5:

[0898] The server suggests makeup tools and techniques. Based on the edited photo, the server queries the generative AI model to obtain the makeup tools the user should use and the specific makeup techniques that accompany them. For example, it analyzes the photo and suggests using "foundation, eye shadow, and lipstick," providing detailed instructions on how to use each tool. The input for this process is the edited photo file, and the output is text information about the suggested makeup tools and their application techniques.

[0899] Step 6:

[0900] The server generates and displays a purchase link. The server generates an online purchase link corresponding to the suggested makeup products. This link is formatted in HTML and sent to the user's device. The user can access the corresponding online shop's purchase page by clicking the link displayed on the device. The input to this process is the text information of the makeup products, and the output is an HTML document containing the purchase link.

[0901] (Application example 1)

[0902] 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."

[0903] The present invention relates to a system that suggests makeup that matches the image a user desires and encourages the purchase of makeup tools that match this. Conventional systems only offer suggestions online, making it difficult for users to find the suggested products in physical stores. Another issue is that these systems do not provide detailed advice to help users accurately understand and execute the suggested makeup techniques. This makes it difficult for users to efficiently select makeup products and apply appropriate makeup.

[0904] 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.

[0905] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating a prompt based on the feature points and the image input by the user and editing the photo, means for suggesting makeup tools and makeup techniques based on the edited photo, means for generating and displaying a purchase link for the suggested makeup tools, and means for displaying location information of the suggested makeup tools. This allows the user to easily find suggested products in a physical store and receive detailed makeup technique suggestions.

[0906] "Means for uploading user photos" refers to a method by which a user can provide their own image data to the system.

[0907] "Means for performing facial recognition and extracting feature points from uploaded photographs" refers to a method for detecting faces in the provided image data and identifying the positional information of each part of the face (eyes, nose, mouth, etc.).

[0908] "Means for users to input the image of themselves they want to achieve" refers to a method by which users can communicate to the system the image of the style and makeup they are aiming for in text or selection format.

[0909] The "means for generating prompts based on the feature points and the image input by the user and editing the photo" is a method for generating image editing instructions based on the extracted facial information and the user's desired style, and processing the image in accordance with those instructions.

[0910] The "means of suggesting makeup tools and makeup techniques based on edited photos" refers to a method of suggesting specific makeup tools and how to use them to users by referring to edited images.

[0911] The "means for generating and displaying a purchase link for the suggested makeup tools" is a method for generating an online shopping link for purchasing the suggested makeup products and displaying it to the user.

[0912] The "means for displaying location information of the suggested makeup tools" is a method for providing the user with map information showing where the suggested makeup tools are actually located in the store.

[0913] The present invention is a system that helps users realize the image they want to achieve by suggesting makeup tools and makeup techniques based on a user's photo, leading to purchases. This system is implemented in the following manner.

[0914] First, a user uploads a photo of themselves to the application using their smartphone. This application has a function for sending the photo to a server. The server then performs facial recognition on the uploaded photo and extracts feature points such as the eyes, nose, mouth, and eyebrows. This process uses an image processing library called OpenCV and a pre-trained facial recognition model.

[0915] Next, the user enters the image of their desired look in text form within the application. For example, they could use a specific style such as "natural makeup" or "glamorous." The input image information, along with extracted feature points, is sent to the server. The server uses this information to generate a prompt using a generative AI model. This prompt is then passed to the photo editing engine, which provides instructions for editing the photo to match the user's desired style.

[0916] Based on the edited photo, the server suggests makeup products and techniques suitable for the user. Suggested makeup products include foundation, eye shadow, lipstick, etc. Specific steps and methods for using each makeup product are also provided. Furthermore, an online purchase link for the suggested makeup products is generated and displayed to the user via a smartphone application.

[0917] To support the in-store shopping experience, the application also provides location information for the suggested makeup products, allowing users to easily find the suggested products in the store. Using the in-store map displayed on the smartphone, users can efficiently search for products.

[0918] For example, if a user uploads a photo of themselves and specifies that they are aiming for a "glamorous" look, the server will perform facial recognition on the photo and extract features such as large eyes and a high nose. Based on this, the server will generate prompts and edit the photo to create a "glamorous" style. Based on the editing results, the server will suggest the use of bright eyeshadow, thick lipstick, etc., and provide detailed instructions on how to use each product. The server will then generate a purchase link and in-store location information for the suggested makeup products, which will be displayed to the user via a smartphone application.

[0919] An example of a prompt sentence to input to the generative AI model is as follows:

[0920] User's facial features: [0.3, 0.4, 0.5, ...], Desired makeup style: 'glamorous'

[0921] As described above, users can receive professional makeup advice at home or in a brick-and-mortar store, easily purchase the necessary makeup tools based on that advice, and apply makeup appropriately. It is expected that the present invention will significantly improve users' makeup experience.

[0922] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0923] Step 1:

[0924] A user uploads their own photo to the application using a smartphone. The device receives the photo file selected by the user and sends it to the server. The input is the user's photo, and the output is that the photo data is sent to the server.

[0925] Step 2:

[0926] The server receives the uploaded photo and performs facial recognition processing. It uses OpenCV to detect the facial area from the image and extracts feature points such as eyes, nose, and mouth. The input is the user's photo data, and the output is facial feature point data. This feature point data is stored in a database on the server for further processing.

[0927] Step 3:

[0928] The user inputs the desired makeup style in text format within the application. The terminal sends the input image information to the server. The input is the user's text data, and the output is the image information sent to the server.

[0929] Step 4:

[0930] The server uses a generative AI model to generate prompts based on the received image information of the user's facial feature points and makeup style. These prompts are editing instructions that are passed to the photo editing engine. The input is facial feature point data and image information, and the output is an editing prompt.

[0931] Step 5:

[0932] The photo editing engine edits the photo based on the generated prompt to match the user's desired style. The input is the prompt and the original photo data, and the output is the edited photo data. This edited photo is saved on the server and used for future suggestions.

[0933] Step 6:

[0934] The server then uses the edited photo to suggest makeup products and techniques that are suitable for the user. Using the generated AI model, it recommends specific makeup products, such as foundation and eyeshadow, and how to use them. The input is the edited photo data, and the output is a list of makeup products and how to use them.

[0935] Step 7:

[0936] The server generates and provides online purchase links for the suggested makeup products to the user. It also displays the location information of the suggested makeup products to support in-store purchases. The input is a list of makeup products, and the output is a purchase link and location information.

[0937] Step 8:

[0938] Users can purchase makeup products online through the provided purchasing link, and can also check their location in a physical store to find suggested products in-store. This stage involves user-initiated selection and purchasing behavior.

[0939] 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.

[0940] The present invention is a system that recognizes a user's emotions and suggests makeup tools and makeup techniques based on the emotions. The program of this system is configured as follows.

[0941] Photo upload

[0942] The user uses the device to upload their own photo through the system interface, and the device sends the selected photo file to the server, which stores the photo and uses it for facial and emotion recognition.

[0943] Face Recognition and Feature Extraction

[0944] The server performs facial recognition processing on the received photos to identify facial contours and feature points, such as the positions and shapes of the eyes, nose, mouth, eyebrows, etc. This information is then stored in a database for subsequent processing.

[0945] emotion recognition

[0946] The server analyzes the user's facial expressions from the uploaded photo and recognizes emotions using an emotion engine, such as happiness, sadness, surprise, etc. This emotion information is also used to generate subsequent prompts and make-up suggestions.

[0947] Input the target image

[0948] The user uses the terminal to input the image of the person they want to be. This information is input in text format and includes specific styles such as "natural makeup" or "glamorous." The terminal then sends the input image information to the server.

[0949] Prompt generation and photo editing

[0950] The server generates prompts based on the extracted facial features, the target image entered by the user, and the recognized emotions. The prompts are passed to the photo editing engine, which then creates an edited photo that matches the user's desired style. The emotional data is reflected in the edits, and the style is set to match the user's mood.

[0951] Makeup tools and techniques

[0952] Based on the edited photo, the server suggests makeup products and techniques that best suit the user's emotions and desired image. The suggestions include a list of specific products, such as foundation, eye shadow, and lipstick, along with detailed instructions on how to use each product.

[0953] Generate and view purchasing links

[0954] The server generates a purchase link for the recommended makeup products. This link is from an online shop and is set up so that the user can easily purchase. The terminal displays the generated purchase link to the user in a clickable format.

[0955] Specific examples

[0956] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." At the same time, the "happy" emotion is recognized from the user's facial expression. The server performs facial recognition to extract each feature point and identifies the "happy" emotion using an emotion engine. Based on this information, a prompt is generated and the photo is edited to a style that matches "natural makeup" and a "happy" emotion. Specific makeup techniques for foundation, eye shadow, and lipstick are then suggested, along with detailed instructions for using each tool. Furthermore, a purchase link for the suggested makeup tools is generated and displayed to the user via their device. In this way, users can easily find makeup tools and techniques that match their emotions and the style they are aiming for.

[0957] This invention allows users to receive professional makeup advice tailored to their emotions at that moment from the comfort of their own homes, and to easily purchase the makeup tools they need based on that advice. The system takes the user's emotions into consideration and provides more personalized makeup suggestions, thereby improving user satisfaction.

[0958] The processing flow will be explained below.

[0959] Step 1:

[0960] A user opens the system interface using a terminal, selects his / her own photo, and clicks the upload button. The terminal then sends the selected photo file to the server.

[0961] Step 2:

[0962] The server stores the received photo file and performs facial recognition processing on the photo. Specifically, it identifies the position and outline of the face and extracts feature points such as the eyes, nose, mouth, and eyebrows. The extracted feature points are stored in a database.

[0963] Step 3:

[0964] The server uses an emotion engine to analyze the user's facial expressions from the uploaded photo and recognize emotions. For example, it identifies emotions such as happiness, sadness, and surprise, and generates emotion data. The emotion data is also stored in a database.

[0965] Step 4:

[0966] The user enters the desired image of themselves (e.g., "natural makeup" or "glamorous") in text format into the input form on the device and clicks the send button. The device then sends the entered target image to the server.

[0967] Step 5:

[0968] The server generates prompts based on the extracted facial feature points, the user-input target image, and the recognized emotion data, which are then passed to the photo editing engine and used as editing instructions.

[0969] Step 6:

[0970] The server then uses prompts to edit the photo and create an edited version that matches the user's desired style, such as adjusting eye shape or skin tone to create a natural look. The edited photo is then stored in a database.

[0971] Step 7:

[0972] The server then uses the edited photos to suggest the best makeup tools and techniques for the user. Specifically, it generates a list of foundation, eyeshadow, lipstick, etc., along with a makeup procedure using those items.

[0973] Step 8:

[0974] The terminal displays the list of makeup tools and makeup procedures received from the server to the user. The procedures and methods for using each makeup tool are explained in detail so that the user can easily understand.

[0975] Step 9:

[0976] The server generates a purchase link corresponding to the suggested makeup products and sends it to the terminal. An appropriate online shop link is created for each makeup item.

[0977] Step 10:

[0978] The terminal displays the generated purchase link to the user, who can easily purchase the suggested makeup tool by clicking the displayed link.

[0979] Through the above process, users are presented with makeup tools and techniques based on their own emotions and goals, and can easily purchase them. This system takes into account the user's current emotions and provides more personalized makeup suggestions, thereby improving satisfaction.

[0980] Example 2

[0981] 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."

[0982] Conventional makeup suggestion systems have difficulty providing personalized makeup advice because they do not take the user's emotions into consideration. Furthermore, there is a lack of easy ways for users to purchase the makeup tools they need, resulting in low user satisfaction. The present invention aims to solve these problems by providing a system that can suggest professional makeup that suits the user and encourages them to purchase the makeup.

[0983] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for uploading a user's own photo using the user's terminal, a means for transmitting the uploaded photo to the server and extracting feature points using a face recognition library, and a means for the user to input a target image in text format using the terminal. This allows the user to receive personalized makeup suggestions based on their own emotions and the target image. In addition, by including a means for generating a purchase link for the suggested makeup tools and displaying it on the terminal, the user can easily purchase the necessary makeup tools. As a result, user satisfaction is improved and purchases can be encouraged.

[0984] "User" refers to a person who uses the system to upload their own photos and receive makeup suggestions.

[0985] "Terminal" refers to a computing device used by a user, such as a smartphone or personal computer.

[0986] "Server" refers to a computer system that receives data sent from a terminal and performs processing such as facial recognition, emotion recognition, and makeup suggestions.

[0987] "Photo upload" refers to the act of a user sending their own photo to the system via their terminal.

[0988] A "face recognition library" refers to a software module for extracting facial feature points from a photograph. Examples include OpenCV and Dlib.

[0989] "Feature points" are data points that indicate the position and shape of facial features, such as the position and shape of the eyes, nose, mouth, and eyebrows.

[0990] "Goal image" refers to text information that indicates the specific makeup style the user wants to achieve. Examples include "natural makeup" and "glamorous."

[0991] "Emotion information" refers to data indicating emotions recognized from a user's photo, such as happiness, sadness, surprise, etc.

[0992] A "prompt" refers to a sentence that gives specific editing instructions to a photo editing engine.

[0993] "Photo Editing Engine" means software that edits photos based on prompts. Examples include the Adobe Photoshop API.

[0994] "Makeup tools" refers to the specific products used to apply makeup. Examples include foundation, eye shadow, and lipstick.

[0995] "Makeup technique" refers to the specific steps for applying makeup using makeup tools.

[0996] "Purchase Link" refers to a link to an online shop for purchasing the suggested makeup products.

[0997] "Personalized makeup suggestions" refer to suggestions for customized makeup techniques based on the user's individual emotions and target image.

[0998] The present invention is a system that analyzes a user's emotions and suggests optimal makeup tools and makeup techniques based on those emotions. This system is implemented in the following manner.

[0999] Users use their devices (smartphones or PCs) to upload their own photos through the system interface. The devices then send the selected photo files to the server, which stores the received photos and prepares them for further processing.

[1000] Next, the server uses the stored photo to extract facial feature points using a facial recognition library (e.g., OpenCV or Dlib). These feature points include the position and shape of the eyes, nose, mouth, eyebrows, etc. This extracted feature point information is stored in a database.

[1001] The server then uses the extracted feature point data to utilize an emotion recognition engine (e.g., a general emotion recognition API) to identify the user's emotion. Emotional information recognized includes happiness, sadness, surprise, etc. This emotional information is also stored in a database.

[1002] Next, the user uses the device to enter the makeup style they are aiming for in text format. For example, they can enter a specific style such as "natural makeup" or "glamorous." The device then sends this text data to the server, which then stores the received data in a database.

[1003] The server combines the facial feature point data, the target image, and the emotion information to generate a prompt. This prompt is passed to a photo editing engine (e.g., Adobe Photoshop API), which edits the photo based on the user's desired style. An example of a generated prompt sentence is as follows:

[1004] Example prompt:

[1005] Apply natural makeup to your user's photo and edit it in a style that matches her happy expression. Use light eyeshadow and a light lip color.

[1006] After the edited photo is generated, the server uses the photo to suggest the best makeup products and techniques to match the user's emotions and desired image. The list of specific products includes foundation, eye shadow, lipstick, etc., and provides detailed instructions on how to use each product.

[1007] For example, advice is given such as "Spread liquid foundation thinly and evenly," "Apply light eyeshadow lightly to the outer corners of your eyes," and "Apply light lip color carefully using a lip brush."

[1008] Furthermore, the server generates a purchase link for the recommended makeup tools and sends it to the terminal. The purchase link is from an online shop, and the user can easily complete the purchase procedure by clicking the link.

[1009] In this way, users can receive personalized makeup suggestions based on their own emotions and the style they are aiming for, and can easily purchase the necessary makeup tools.

[1010] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1011] Step 1:

[1012] A user uses a terminal to upload his / her own photo through the system interface. Specifically, the user selects a photo through the file selection dialog and clicks the upload button. The input is the user's photo file, which is sent by the terminal to the server. The output is the photo file received by the server.

[1013] Step 2:

[1014] The server stores the received photos and starts the facial recognition process. Specifically, it uses a facial recognition library (e.g., OpenCV or Dlib) on the stored photos. The input is the photo file received from the user, and the output is the facial contour and feature point data extracted from the photo. This data is stored in a database.

[1015] Step 3:

[1016] The server uses an emotion recognition engine (for example, a general emotion recognition API) based on the extracted facial feature point data to identify the user's emotion. Specifically, it makes an API request and receives emotion data as a response. The input is facial feature point data, and the output is recognized emotion information. This information is also stored in a database.

[1017] Step 4:

[1018] The user uses the terminal to input the target image in text format. Specifically, they enter keywords such as "natural makeup" or "glamorous" in the text box and click the send button. The input is the text data entered by the user and is sent from the terminal to the server. The output is the text data received by the server.

[1019] Step 5:

[1020] The server generates a prompt by combining the received target image, facial feature data, and emotion information. Specifically, it uses these data to create a prompt sentence to instruct the photo editing engine. The input is the target image, facial feature data, and emotion information, and the output is the generated prompt sentence.

[1021] Step 6:

[1022] The server passes the generated prompt text to a photo editing engine (e.g., Adobe Photoshop API) to edit the photo. Specifically, the photo is edited based on the prompt, and an edited photo is generated. The input is the prompt text and the original photo data, and the output is the edited photo. The edited photo is saved on the server.

[1023] Step 7:

[1024] Based on the edited photo, the server suggests the best makeup tools and techniques to match the user's emotions and desired image. Specifically, it generates a list of each tool and instructions for using them based on the information in the database. The input is the edited photo and related data, and the output is a list of makeup tools and specific makeup technique advice.

[1025] Step 8:

[1026] The server generates a purchase link for the suggested makeup products and sends it to the terminal. Specifically, it generates a link to an online shop and displays it in a clickable format for the user. The input is a list of makeup products, and the output is a purchase link. The terminal displays this link to the user, allowing them to easily complete the purchase procedure.

[1027] The above are the specific processing steps of this system's program. At each step, appropriate data processing and calculations are performed based on the input data, and the output required for the next step is generated.

[1028] (Application example 2)

[1029] 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."

[1030] Today's consumers want makeup suggestions and purchasing support that reflect their emotions and moods. However, conventional makeup suggestion systems have the problem of being unable to provide personalized advice because they do not take into account the emotional state of each individual user. In particular, when providing online makeup advice, it has been difficult to suggest makeup tools and methods that reflect the user's emotions. Thus, providing makeup support that incorporates the user's emotions is a challenge.

[1031] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1032] In this invention, the server includes means for uploading a user's photo, means for performing facial recognition on the uploaded photo and extracting feature points, means for the user to input an image of themselves that they would like to have, means for generating a prompt based on the feature points and the image input by the user and editing the photo, means for suggesting makeup tools and makeup techniques based on the edited photo, means for generating and displaying a purchase link for the suggested makeup tools, and means for recognizing the user's emotions and suggesting makeup tools and makeup techniques based on the emotions. This allows the user to receive personalized makeup suggestions that reflect their own emotions.

[1033] "User photo uploading means" is a method by which a user can send their photo from their device to the server.

[1034] "Means for performing facial recognition and extracting feature points" refers to a method for detecting faces from uploaded photos and analyzing specific points such as eyes, nose, and mouth.

[1035] "Means for users to input the image of themselves they want to have" refers to a method by which users input their desired makeup style and image of their appearance into the system.

[1036] The "means for generating prompts and editing photos" refers to a method by which the system generates appropriate instructions and edits photos based on facial recognition feature points and the input image.

[1037] The "means for suggesting makeup tools and makeup techniques" is a method for suggesting makeup tools suitable for a user and how to use them based on an edited photo.

[1038] The "means for generating and displaying a purchase link for the suggested makeup tool" is a method for generating an online purchase link for the makeup tool suggested by the system and displaying it to the user.

[1039] "Means for recognizing a user's emotions and suggesting makeup tools and techniques based on those emotions" refers to a method for analyzing emotions from a user's photo and suggesting optimal makeup tools and techniques based on the results.

[1040] The present invention is a system that recognizes a user's emotions and suggests makeup tools and makeup techniques based on the emotions. This system is configured through the following steps.

[1041] First, the user uploads a photo. This operation is performed using a device such as a smartphone. The photo data uploaded from the device is sent to a server and stored on the server. The server then performs facial recognition processing on the received photo. This processing uses a facial recognition software library such as OpenCV. As a result of facial recognition, feature points such as the eyes, nose, mouth, and eyebrows are extracted. This feature point information is stored in a database and used for subsequent processing.

[1042] The server then analyzes the user's facial expressions from the uploaded photo using an emotion recognition library or model such as EmotionDetector. For example, emotions such as happiness, sadness, and surprise are identified. This emotional information is used to generate subsequent prompts and make-up suggestions.

[1043] Next, the user inputs the image of the person they want to be. This information is entered into the terminal in text format, and includes specific styles such as "natural makeup" or "glamorous makeup." This input information is then sent from the terminal to the server.

[1044] The server generates prompts based on this information, namely the extracted facial features, the target image entered by the user, and the recognized emotions. The generated prompts are passed to the photo editing engine using an AI model. The photo editing engine follows the prompts to create an edited photo that matches the user's desired style. Emotional data is reflected in the edits, setting a style that matches the user's mood.

[1045] Based on the edited photo, the server suggests the makeup products and techniques that best suit the user's emotions and desired image. These suggestions include a list of specific products, such as foundation, eye shadow, and lipstick. It also provides detailed instructions on how to use each product and how to apply the makeup. It also generates a link to purchase the suggested makeup products. This link is from an online shop, and is set up so that users can easily purchase them via their device.

[1046] As a concrete example, consider the case where a user uploads a photo of themselves and indicates that they are aiming for "natural makeup." At the same time, the "happy" emotion is recognized from the user's facial expression. The server performs facial recognition, extracts each feature point, and identifies the "happy" emotion using an emotion engine. Based on this information, a prompt is generated and the photo is edited to a style that matches "natural makeup" and a "happy" emotion. Specific makeup techniques for foundation, eye shadow, and lipstick are then suggested, along with detailed instructions for using each tool. Furthermore, a purchase link for the suggested makeup tools is generated and displayed to the user via their device. In this way, users can easily find the makeup tools and techniques that match their emotions and the style they are aiming for.

[1047] An example of a prompt sentence is, "Based on the user's photo, edit the makeup to create a natural look. The user's emotion is recognized as happiness, and a makeup style that matches that emotion will be suggested."

[1048] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1049] Step 1:

[1050] The terminal provides an interface for the user to upload photos. The user selects a photo and performs upload. The terminal then sends the selected photo file to the server and temporarily stores the photo data as preprocessing.

[1051] Input: Photos uploaded by the user via the device

[1052] Output: Image data sent to the server

[1053] Step 2:

[1054] The server performs facial recognition on the received photo data using a facial recognition library such as OpenCV. Specifically, it detects the facial area and extracts feature points such as eyes, nose, mouth, and eyebrows. The extracted feature point information is stored in a database.

[1055] Input: Image data sent to the server

[1056] Output: Extracted facial feature points data

[1057] Step 3:

[1058] The server recognizes the user's emotions from the received photo data. It uses an emotion recognition library such as EmotionDetector to analyze facial expressions in the photo and identify the user's emotional state. This emotion data is also stored in a database.

[1059] Input: Image data sent to the server

[1060] Output: User emotion data

[1061] Step 4:

[1062] The user uses the device to input text describing the style or image they want to achieve, such as "natural makeup" or "glamorous makeup." This input data is then sent to the server.

[1063] Input: Text data of styles and images that users input from the terminal

[1064] Output: Text data sent to the server

[1065] Step 5:

[1066] The server generates prompts based on the extracted feature data, the user's input image, and the recognized emotions. These prompts are passed to the photo editing engine, which uses AI models to edit the photo to match the user's desired style.

[1067] Input: feature point data, user input data, emotion data

[1068] Output: Generated prompt and edited photo data

[1069] Step 6:

[1070] The server then suggests the best makeup products and techniques based on the edited photo, including a list of specific makeup products (e.g., foundation, eyeshadow, lipstick, etc.) and instructions for using them.

[1071] Input: Edited photo data

[1072] Output: A list of suggested makeup products and detailed instructions for use

[1073] Step 7:

[1074] The server generates a purchase link for the suggested makeup tool. This link is from an online shop and is displayed to the user. The terminal displays the generated purchase link to the user to encourage purchase.

[1075] Input: A list of suggested makeup products

[1076] Output: Generated purchasing links

[1077] 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.

[1078] 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.

[1079] 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.

[1080] 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.

[1081] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1082] 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.

[1083] 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).

[1084] 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.

[1085] 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."

[1086] 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.

[1087] 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).

[1088] 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.

[1089] 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.

[1090] 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.

[1091] 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.

[1092] 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.

[1093] 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.

[1094] 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.

[1095] 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.

[1096] 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.

[1097] 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.

[1098] The following is further disclosed regarding the above embodiment.

[1099] (Claim 1)

[1100] a means for uploading a user photo;

[1101] A means of performing facial recognition and extracting feature points from uploaded photos;

[1102] A means for the user to input an image of the person they want to be;

[1103] means for generating a prompt based on the feature points and an image input by the user and editing the photo;

[1104] A method to suggest makeup tools and techniques based on edited photos,

[1105] means for generating and displaying a purchase link for the suggested makeup tool;

[1106] A system including:

[1107] (Claim 2)

[1108] 10. The system according to claim 1, further comprising means for providing a user with a purchasing link for the suggested makeup tool to encourage the user to purchase the recommended makeup tool.

[1109] (Claim 3)

[1110] 2. The system according to claim 1, further comprising means for generating specific advice on makeup tools and makeup techniques based on the extracted feature points and an image input by the user.

[1111] "Example 1"

[1112] (Claim 1)

[1113] a means for uploading a user photo;

[1114] A means of performing facial recognition and extracting feature points from uploaded photos;

[1115] A means for the user to input an image of the person they want to be;

[1116] A means for generating a prompt based on the feature points and an image input by the user, and editing the photo using a generative AI model;

[1117] A method to suggest makeup tools and techniques based on edited photos,

[1118] means for generating and displaying a purchase link for the suggested makeup tool;

[1119] A system including:

[1120] (Claim 2)

[1121] 10. The system according to claim 1, further comprising means for providing a user with a purchasing link for the suggested makeup tool to encourage the user to purchase the recommended makeup tool.

[1122] (Claim 3)

[1123] The system of claim 1, further comprising means for generating specific advice on makeup tools and makeup techniques using a generative AI model based on the extracted feature points and an image input by the user.

[1124] "Application Example 1"

[1125] (Claim 1)

[1126] a means for uploading a user photo;

[1127] A means of performing facial recognition and extracting feature points from uploaded photos;

[1128] A means for the user to input an image of the person they want to be;

[1129] means for generating a prompt based on the feature points and an image input by the user and editing the photo;

[1130] A method to suggest makeup tools and techniques based on edited photos,

[1131] means for generating and displaying a purchase link for the suggested makeup tool;

[1132] a means for displaying location information of the suggested makeup tools;

[1133] A system including:

[1134] (Claim 2)

[1135] 2. The system according to claim 1, further comprising means for providing a user with a purchase link for the suggested makeup tool to encourage the user to make a purchase.

[1136] (Claim 3)

[1137] 2. The system according to claim 1, further comprising means for generating specific advice on makeup tools and makeup techniques based on the extracted feature points and an image input by the user.

[1138] "Example 2: Combining Emotion Engines"

[1139] (Claim 1)

[1140] a means for uploading a photograph of the user using the user's device;

[1141] A means for transmitting the uploaded photo to a server and extracting feature points using a face recognition library;

[1142] A means for a user to input a target image in text format using a terminal;

[1143] a means for generating a prompt based on the extracted feature points, a target image input by the user, and the recognized emotion information, and editing the photo using a photo editing engine;

[1144] A means for suggesting the best makeup tools and techniques to match the user's emotions and desired image based on the edited photo;

[1145] A means for generating a purchase link for the suggested makeup tool and displaying it on the terminal;

[1146] A system including:

[1147] (Claim 2)

[1148] 10. The system according to claim 1, further comprising means for providing a user with a purchasing link for the suggested makeup tool to encourage the user to purchase the recommended makeup tool.

[1149] (Claim 3)

[1150] 2. The system according to claim 1, further comprising means for generating specific advice on makeup tools and makeup techniques based on the extracted feature points, an image input by the user, and the recognized emotion information.

[1151] "Application example 2 when combining emotion engines"

[1152] (Claim 1)

[1153] a means for uploading a user photo;

[1154] A means of performing facial recognition and extracting feature points from uploaded photos;

[1155] A means for the user to input an image of the person they want to be;

[1156] means for generating a prompt based on the feature points and an image input by the user and editing the photo;

[1157] A method to suggest makeup tools and techniques based on edited photos,

[1158] means for generating and displaying a purchase link for the suggested makeup tool;

[1159] means for recognizing a user's emotion and suggesting makeup tools and makeup techniques based on the emotion;

[1160] A system including:

[1161] (Claim 2)

[1162] 10. The system according to claim 1, further comprising means for providing a user with a purchasing link for the suggested makeup tool to encourage the user to purchase the recommended makeup tool.

[1163] (Claim 3)

[1164] 2. The system according to claim 1, further comprising means for generating specific advice on makeup tools and makeup techniques based on the extracted feature points, an image input by the user, and the recognized emotion. [Explanation of symbols]

[1165] 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 uploading a user photo; A means of performing facial recognition and extracting feature points from uploaded photos; A means for the user to input an image of the person they want to be; means for generating a prompt based on the feature points and an image input by the user and editing the photo; A method to suggest makeup tools and techniques based on edited photos, means for generating and displaying a purchase link for the suggested makeup tool; A system including:

2. The system according to claim 1 , further comprising means for providing a user with a purchasing link for the suggested makeup tool to encourage the user to purchase it.

3. 2. The system according to claim 1, further comprising means for generating specific advice on makeup tools and makeup techniques based on the extracted feature points and an image input by the user.

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