System

Abstract

A system is provided.SOLUTION: A system, comprising: means for sending cosmetics information selected by a user to a server; means for sending facial image data uploaded by the user to the server; means for receiving the cosmetics information and the facial image data at the server and generating a facial image of the user after using the cosmetics by using an image generation algorithm; means for sending the generated facial image to a terminal; and means for displaying the generated facial image and related cosmetics information to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The men's cosmetics market is growing rapidly, and men's awareness of beauty is also increasing. However, many men lack confidence in choosing cosmetics that suit them and feel a psychological hurdle in actually trying them out. In particular, when shopping online, the risk of purchasing is perceived as high because the product cannot be tried in person. As a result, many men are unable to find cosmetics that suit them, and potential demand is not being met. This invention aims to solve this problem by providing an environment where men can easily try out cosmetics, lowering the hurdle to purchase and helping more men choose cosmetics that suit them. [Means for solving the problem]

[0005] The present invention relates to a system including: a means for transmitting information about cosmetics selected by a user to a server; a means for transmitting facial image data uploaded by the user to the server; a means for receiving the cosmetic information and facial image data in the server and generating an image of the user's face after using the cosmetics using an image generation algorithm; a means for transmitting the generated facial image to a terminal; and a means for displaying the generated facial image and related cosmetic information to the user. The system further includes a means for the server to customize the cosmetic information based on the user's basic information and pass the customized information to the image generation algorithm to make the generated facial image more suitable for the user. These means allow users to confirm the effects of the cosmetics before purchasing, allowing them to confidently select appropriate cosmetics. The system also includes a means for recommending related cosmetics selected by the user and a means for adding the recommended cosmetics to a cart and providing step-by-step guidance through the purchase process, making it easy for even users unfamiliar with online shopping to proceed with the purchase. This system can raise men's awareness of beauty and lower the barrier to purchase.

[0006] A "user" is a person who uses the system to select and try on cosmetics.

[0007] A "server" is a central processing unit that processes and stores data, receives user input and facial images, and executes image generation algorithms.

[0008] A "terminal" is a device (e.g., a PC or smartphone) that is directly operated by a user and exchanges data with a server.

[0009] "Cosmetics" is a general term for products that are intended to moisturize, beautify, or make up the skin.

[0010] "Facial image data" refers to a digital image file of a user's face that the user uploads.

[0011] An "image generation algorithm" is a computational process that generates an image of a face after applying cosmetics based on input facial image data and cosmetic information.

[0012] A "generated facial image" is a visual representation of a face after applying a user-selected cosmetic product, generated by an image generation algorithm.

[0013] "Recommendation" means suggesting relevant products or services to a user.

[0014] The "purchase procedure" refers to a series of operations for actually purchasing the product selected by the user. [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 showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[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 supports purchasing decisions by visualizing the effects of using cosmetics selected by the user in advance. This system is realized through cooperation between a server, a terminal, and the user. The program processing of this system is explained in detail below.

[0037] Basic processing flow

[0038] User authentication and basic information entry

[0039] A user accesses an e-commerce site and enters their email address and password on the login screen.

[0040] The terminal sends this authentication information to the server.

[0041] The server receives the authentication information and checks it against a database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts a session.

[0042] Selection of cosmetics

[0043] The user selects a cosmetic category, such as skin care or lip care.

[0044] The terminal transmits the selected category information to the server.

[0045] The server generates a list of applicable cosmetics and sends it to the terminal.

[0046] The user selects the cosmetic product of interest from the list.

[0047] The terminal transmits information about the selected cosmetics to the server.

[0048] Upload a face image and generate an image using AI

[0049] The server asks the user to upload a face image.

[0050] The user uploads an image of their face and sends it to the server via their terminal.

[0051] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0052] An image generation algorithm generates an image of the face and returns the result to the server.

[0053] Image display and recommendations

[0054] The server sends the generated facial image to the device.

[0055] The terminal displays the generated facial image to the user.

[0056] The server refers to the user's basic information, recommends related cosmetics, and sends that information to the terminal.

[0057] The device displays information about the recommended cosmetics to the user.

[0058] Purchase procedure

[0059] The user adds the selected or recommended cosmetic product to the cart.

[0060] The terminal guides the user through the purchase process, detailing each step.

[0061] The user follows the purchase procedure and enters and confirms the required information.

[0062] The server receives the final purchase information and processes the order.

[0063] Specific examples

[0064] For example, consider a case where a user is looking for skin care products to combat dryness in winter. The user accesses an e-commerce site and logs in. After successfully logging in, the user selects the skin care category. The server generates a list of skin care cosmetics and displays it to the user via their terminal. The user selects a moisturizing cream that interests them and sends that information to the server.

[0065] Next, the server requests the upload of a facial image, and the user uploads an image of their face. The server then feeds the received facial image and the selected moisturizing cream information into an image generation algorithm to generate an image of the face after using the moisturizing cream. This image is then displayed on the device, allowing the user to visually confirm the effect.

[0066] The server then recommends cosmetics related to the user, such as face wash and lotion from the same brand, and sends this information to the device. The user then refers to these recommendations and considers purchasing them along with the moisturizing cream. They proceed through the purchasing process by following step-by-step instructions, and finally confirm the purchase.

[0067] In this way, the present invention is a system that helps users to easily select cosmetics that are suitable for them and helps them make more reliable purchasing decisions.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] A user accesses an e-commerce site and enters their email address and password on the login screen.

[0071] Step 2:

[0072] The terminal sends the entered login information to the server.

[0073] Step 3:

[0074] The server checks the received login information against a database and authenticates the user.

[0075] Step 4:

[0076] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[0077] Step 5:

[0078] The server notifies the user of successful authentication and begins the session.

[0079] Step 6:

[0080] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[0081] Step 7:

[0082] The terminal transmits the selected category information to the server.

[0083] Step 8:

[0084] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[0085] Step 9:

[0086] The terminal displays the generated cosmetics list to the user.

[0087] Step 10:

[0088] The user selects the cosmetic product of interest from the list.

[0089] Step 11:

[0090] The terminal transmits information about the selected cosmetics to the server.

[0091] Step 12:

[0092] The server asks the user to upload an image of their face.

[0093] Step 13:

[0094] The terminal displays the upload form to the user.

[0095] Step 14:

[0096] The user uploads an image of their face and sends it to the server via their terminal.

[0097] Step 15:

[0098] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0099] Step 16:

[0100] An image generation algorithm generates an image of the face after applying the cosmetics based on the received data.

[0101] Step 17:

[0102] The server sends the generated facial image to the device.

[0103] Step 18:

[0104] The terminal displays the generated facial image to the user.

[0105] Step 19:

[0106] The server references the user's basic information and recommends related cosmetics.

[0107] Step 20:

[0108] The device displays information about the recommended cosmetics to the user.

[0109] Step 21:

[0110] The user adds the selected or recommended cosmetic product to the cart.

[0111] Step 22:

[0112] The terminal guides the user through the purchase process, detailing each step.

[0113] Step 23:

[0114] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[0115] Step 24:

[0116] The user makes a final confirmation and confirms the purchase.

[0117] Step 25:

[0118] The server receives the final purchase information and processes the order.

[0119] Step 26:

[0120] The server sends an order confirmation email to the user and proceeds with the delivery process.

[0121] Example 1

[0122] 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."

[0123] In conventional online shopping, it is difficult for users to visually confirm the effects of using the selected product beforehand, which often makes them feel uneasy about making a purchase decision.In addition, there is a problem that the product information and recommendations suitable for the user are not provided sufficiently, making it difficult to find the most suitable product.

[0124] 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.

[0125] In this invention, the server includes a means for transmitting product information selected by the user to the server, a means for transmitting facial image data uploaded by the user to the server, and a means for generating an image of the user's face after using the product using a generative model. This allows the user to visually confirm the effects of using the selected product in advance, enabling optimal purchasing decisions.

[0126] "User" refers to an individual or legal entity that uses the service or system.

[0127] "Product Information" refers to detailed descriptions of product characteristics, price, ingredients, usage, etc.

[0128] "Server" refers to a computer on a network that processes, stores, and transmits data.

[0129] "Facial image data" refers to an image file that digitally records and stores a user's face.

[0130] A "generative model" refers to an algorithm that generates new data based on input data.

[0131] "Terminal" refers to a device (such as a personal computer, smartphone, or tablet) that a user operates.

[0132] "Image" refers to the visual result produced by a generative model.

[0133] "Basic Information" refers to personal information used for personalization, such as the user's skin type, skin color, and age.

[0134] "Recommendation" refers to suggesting related products based on a user's preferences and attributes.

[0135] A "cart" is an online location where a user temporarily stores items they are considering purchasing.

[0136] The "purchase procedure" refers to a series of steps a user goes through to complete an order for a product.

[0137] This invention is a system that supports purchasing decisions by visualizing the effects of using a product selected by the user in advance. This system is realized by the cooperation of three parties: a server, a terminal, and the user.

[0138] First, a user accesses an e-commerce site and enters their email address and password on the login screen. This information is sent from the terminal to the server. The server compares the received authentication information with a database, and if authentication is successful, obtains the user's basic information. The basic information includes the user's skin type, skin color, age, etc., and the server starts a session based on this information. The session start information and the user's basic information are sent to the terminal, which displays it on the user's screen.

[0139] Next, the user selects a cosmetics category (e.g., skin care, lip care) on the device screen. The device sends the selected category information to the server. The server retrieves a list of cosmetics in that category from the database and sends it to the device. When the user selects a cosmetic product that interests them from the list, that information is sent from the device to the server.

[0140] The server then displays a screen on the device requesting the user to upload a facial image. The user uploads their facial image, which is then sent from the device to the server. The server then provides the received facial image data and the selected cosmetic information as a prompt to the image generation AI model (e.g., DALL-E). An example of a prompt is, "Use the facial image and the selected cosmetic information to generate an image of the face after using the cosmetics."

[0141] The image generation AI model generates an image of the user's face after use based on the input data and returns the result to the server, which then sends the generated image of the face to the device, which then displays it on the user's screen.

[0142] Furthermore, the server refers to the user's basic information and recommends related cosmetics (for example, facial cleanser or lotion from the same brand). This information is also sent to the device, which displays it to the user. The user can add the recommended cosmetics to their cart and proceed to the purchase process. The device guides the user through each step of the purchase process in detail and supports them in entering and confirming the necessary information.

[0143] Finally, the server processes the order based on the purchase information received from the user. This process includes generating an order number, checking inventory, and processing payment. The server then sends the final order information to the terminal, and the terminal displays a message to the user that the order has been confirmed.

[0144] This invention allows the user to visually confirm the effects of the selected product, enabling the user to make a more reliable purchasing decision.

[0145] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0146] Step 1: User authentication and basic information entry

[0147] 1. A user enters their email address and password on the login screen of an e-commerce site. The information is sent from the device to the server.

[0148] 2. The server checks the entered authentication information against the database. Input: Authentication information (email address, password). Output: Authentication result (success / failure), basic user information.

[0149] 3. If authentication is successful, the server obtains the user's basic information (e.g., skin type, skin color, age, etc.) and starts a session. The session start information and the user's basic information are sent to the terminal. The terminal receives this information and displays it on the user's screen.

[0150] Step 2: Choose your cosmetics

[0151] 1. The user selects a cosmetics category (e.g., skin care or lip care) from a list of categories provided. The selection information is sent from the terminal to the server.

[0152] 2. The server retrieves the relevant cosmetics list from the database based on the selected category information. Input: Category information. Output: Cosmetics list.

[0153] 3. The server sends the cosmetics list to the terminal, and the terminal displays the list to the user.

[0154] 4. The user selects the cosmetics they are interested in from the list, and the selection information is sent from the terminal to the server.

[0155] Step 3: Upload a face image and generate an image using AI

[0156] 1. The server instructs the device to display a screen requesting the user to upload a facial image. The device displays the screen according to the instructions.

[0157] 2. The user uploads a picture of their face via the device screen, and the image data is sent from the device to the server.

[0158] 3. The server receives the facial image data and the selected cosmetic information and provides it as a prompt to the image generation AI model (e.g., DALL-E). Input: Facial image data, selected cosmetic information. Output: Generated facial image.

[0159] An example prompt is, "Use the image of your face and the selected cosmetic product information to generate an image of your face after using the product."

[0160] 4. The image generation AI model generates an image of the user's face based on the provided data and returns the result to the server.

[0161] 5. The server sends the generated facial image data to the device, which displays the received image on the user's screen.

[0162] Step 4: View and recommend images

[0163] 1. The device displays the generated face image received from the server to the user.

[0164] 2. The user reviews the generated facial image.

[0165] 3. The server references the user's basic information, retrieves related cosmetics (such as face wash and lotion from the same brand) from the database, and generates a list. Input: User's basic information. Output: List of related products.

[0166] 4. The server sends the relevant cosmetic list to the terminal, which displays the list to the user.

[0167] Step 5: Checkout

[0168] 1. The user adds selected or recommended cosmetics to the cart. This information is sent from the device to the server.

[0169] 2. The device will display your cart and provide detailed steps to begin the checkout process.

[0170] 3. The user enters and confirms the information required for the purchase (shipping address, payment method, etc.). This information is sent from the terminal to the server. Input: Purchase information. Output: Order confirmation.

[0171] 4. The server processes the order based on the received purchase information. Order processing includes generating an order number, checking inventory, and processing payments. Output: Final order information.

[0172] 5. The server sends the final order information to the terminal, and the terminal displays a final confirmation screen to the user. The user confirms the order and the purchase process is complete.

[0173] (Application example 1)

[0174] 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."

[0175] With conventional e-commerce sites and virtual stores, it was difficult for users to visualize the effects of using the cosmetics they selected in advance, which led to the issue of taking a long time to make a purchasing decision. In addition, because users could not actually try the cosmetics, it was difficult to confirm whether the product was truly suitable for them. This led to a situation where users were not satisfied with their ideal cosmetics selection.

[0176] 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.

[0177] In this invention, the server includes means for transmitting information about cosmetics selected by the user to the server, means for transmitting facial image data uploaded by the user to the server, means for receiving the cosmetic information and facial image data in the server and generating an image of the user's face after using the cosmetics using an image generation algorithm, means for transmitting the generated facial image to the terminal, means for displaying the generated facial image and related cosmetic information to the user, means for displaying the generated facial image to the user in real time via a smart device, and means for the user to try on cosmetics in a virtual store using prompts generated using an artificial intelligence model. This allows the user to visually check the effects of the cosmetics after applying them directly to their face in real time, making it easy to select cosmetics that suit them.

[0178] "User authentication" is the process of verifying a user's identity and granting them access to a system.

[0179] "Basic information" refers to information about the user's personal attributes (skin type, skin color, age, etc.).

[0180] "Smart devices" refers to portable electronic devices with advanced computing capabilities such as smartphones, tablets, smart glasses, and head-mounted displays.

[0181] "Cosmetics" is a general term that refers to products used to protect, moisturize, and beautify the face and skin, such as skin care and lip care.

[0182] An "image generation algorithm" is a set of calculations and processing techniques that take image data of a user's face as input and generate a specific effect (in this case, the appearance after applying cosmetics).

[0183] A "prompt sentence" refers to an instruction or input sentence that uses an image generation AI model to generate the image the user wants to see.

[0184] A "virtual store" is a virtual store that operates on the Internet and is a platform where users can browse, try out, and purchase products online.

[0185] "Real-time" refers to a state in which data processing and display are carried out immediately, with almost no time delay.

[0186] "Recommendation" refers to suggesting products suitable for a user based on the user's past behavior and basic information.

[0187] "Facial image" refers to the visual output image that results from applying a cosmetic effect to an image of a user's face.

[0188] The "purchase procedure" refers to a series of steps or processes for actually purchasing the product selected by the user.

[0189] "Terminal" refers to an electronic device (e.g., smartphone, PC, etc.) that a user uses to access the system and send and receive data.

[0190] "Artificial intelligence model" refers to machine learning and deep learning techniques used to analyze and generate data and perform specific tasks.

[0191] A "user session" refers to the sequence of activities that occur between the time a user logs in to the time they log out of the system.

[0192] The present invention is a system that supports purchase decision-making by visualizing the effects of using cosmetics selected by a user in advance. This system is realized through cooperation between a server, a terminal, and a user. The following describes in detail the mode for carrying out the present invention.

[0193] User authentication and basic information entry

[0194] The process begins when a user accesses the virtual store application using a device such as a smartphone and logs in. The user enters their email address and password on the login screen, and the device sends this authentication information to the server. The server receives the authentication information and compares it with a database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts the session.

[0195] Selection of cosmetics

[0196] The user selects a cosmetics category (e.g., skin care or lip care). The device sends the selected category information to the server, which then generates a list of the corresponding cosmetics and sends it to the device. The user selects the cosmetics they are interested in from the list, and the device sends information about the selected cosmetics to the server.

[0197] Upload a face image and generate an image using AI

[0198] The server requests the user to upload a facial image. The user takes a photo of their face using a smartphone or other device and sends it to the server via their device. The server receives the facial image data and selected cosmetic information and passes it to an image generation algorithm. The generative AI model generates an image of the face and returns the result to the server.

[0199] Image display and recommendations

[0200] The server then sends the generated facial image to the device, which then displays the image to the user. The server then refers to the user's basic information and recommends related cosmetics, sending that information to the device. The device then displays information about the recommended cosmetics to the user.

[0201] Purchase procedure

[0202] The user adds the selected or recommended cosmetics to the cart. The terminal guides the user through the purchase procedure step by step, supporting the user. The user follows the purchase procedure, inputs and confirms the necessary information, and the server receives the final purchase information and processes the order.

[0203] Hardware and software used

[0204] Hardware: smartphones, servers, databases

[0205] Software: authentication systems, image generation algorithms (e.g., DALL-E, MidJourney), virtual store applications

[0206] Prompt Sentence Examples

[0207] Specific examples of prompts include:

[0208] User "john.doe@example.com" selected "Rose Red Lip Gloss" from the Lip Care category. Upload a face image and view the AI-generated image of the product after application.

[0209] In this way, the present invention is a system that helps users to easily select cosmetics that are suitable for them and helps them make more reliable purchasing decisions.

[0210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0211] Step 1:

[0212] A user accesses the virtual store application using a smartphone and enters their email address and password on the login screen. The device sends this authentication information to the server. The server receives this authentication information and compares it with the information stored in the database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts the session.

[0213] Input: Email address, password

[0214] Output: Authentication result, user basic information, session ID

[0215] Step 2:

[0216] The user selects a cosmetics category within the application (e.g., skin care, lip care, etc.). The device sends the selected category information to the server. The server retrieves a corresponding cosmetics list from the database based on the selected category and sends it to the device. The user selects cosmetics that interest them from this list, and the device sends that information to the server.

[0217] Input: Category selection information

[0218] Output: Cosmetics list, selected cosmetics information

[0219] Step 3:

[0220] The server requests the user to upload a facial image. The user takes a photo of their face with their smartphone and sends the image to the server via their device. The server receives this facial image data and selected cosmetic information and passes it to an image generation algorithm. The generative AI model generates an image of the face and returns the generated result to the server.

[0221] Input: Facial image, selected cosmetic information

[0222] Output: Generated face image

[0223] Step 4:

[0224] The server then sends the generated facial image to the device, which displays the image to the user in real time.The server then recommends related cosmetics based on the user's basic information and sends that information to the device.The device then displays information about the recommended cosmetics to the user.

[0225] Input: Generated face image, basic user information

[0226] Output: Facial image display, recommended cosmetics list

[0227] Step 5:

[0228] The user adds the selected or recommended cosmetics to the cart. The terminal guides the user through the purchase procedure step by step, supporting the user. Once the user follows the purchase procedure and enters and confirms the necessary information, the server receives the final purchase information and processes the order.

[0229] Input: Cosmetics added to cart, purchase information

[0230] Output: Order confirmation, purchase completion notification

[0231] Through the above processing steps, the user can visually check the cosmetics that suit him / her in real time and make a purchasing decision.

[0232] 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.

[0233] The present invention provides a system that visualizes the effects of using cosmetics selected by the user in advance and supports purchasing decisions, and by combining it with an emotion engine that recognizes the user's emotions, it provides a more suitable cosmetics selection and purchasing experience for the user. The specific processing of the program of this system is described in detail below.

[0234] Basic processing flow

[0235] User authentication and basic information entry

[0236] A user accesses an e-commerce site and enters their email address and password on the login screen.

[0237] The terminal sends this authentication information to the server.

[0238] The server checks the received login information against a database and authenticates the user.

[0239] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[0240] The server notifies the user of successful authentication and begins the session.

[0241] Selection of cosmetics

[0242] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[0243] The terminal transmits the selected category information to the server.

[0244] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[0245] The terminal displays the generated cosmetics list to the user.

[0246] The user selects the cosmetic product of interest from the list.

[0247] The terminal transmits information about the selected cosmetics to the server.

[0248] Upload a face image and generate an image using AI

[0249] The server asks the user to upload a face image.

[0250] The terminal displays the upload form to the user.

[0251] The user uploads an image of their face and sends it to the server via their terminal.

[0252] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0253] An image generation algorithm generates an image of the face and returns the result to the server.

[0254] Running and tuning the emotion engine

[0255] The device captures the user's facial expressions and voice and sends them to the emotion engine.

[0256] The emotion engine analyzes the user's emotion data and sends the results to the server.

[0257] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[0258] The server sends the adjusted facial image to the device.

[0259] Image display and recommendations

[0260] The device displays the adjusted image of the face to the user.

[0261] The server references the user's emotional data and basic information and recommends related cosmetics.

[0262] The device displays information about the recommended cosmetics to the user.

[0263] Purchase procedure

[0264] The user adds the selected or recommended cosmetic product to the cart.

[0265] The terminal guides the user through the purchase process, detailing each step.

[0266] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[0267] The user makes a final confirmation and confirms the purchase.

[0268] The server receives the final purchase information and processes the order.

[0269] Specific examples

[0270] For example, consider a case where a user is looking for a lip balm to combat dry lips. The user accesses an e-commerce site and logs in. After successfully logging in, the user selects the lip care category. The server generates a list of lip care cosmetics and displays it to the user via their terminal. The user selects the lip balm that interests them and sends the information to the server.

[0271] The server then requests a facial image upload, and the user uploads their own facial image. The server then feeds the received facial image and the selected lip balm information into an image generation algorithm to generate an image of the face after using the lip balm. This image is then displayed on the device.

[0272] The emotion engine captures the user's facial expressions and voice and analyzes how satisfied the user is with the image. Based on the emotion engine's analysis, the server adjusts the generated facial image to better match the user's emotions. It also recommends related cosmetics (e.g., other lip care products or moisturizing creams from the same brand) based on the user's satisfaction.

[0273] The user references the adjusted image and recommendations and adds the lip balm and related products to their cart. They then follow the instructions on the device to complete the purchase and finally confirm the purchase. In this way, the present invention is a system that takes user emotions into consideration to provide a more appropriate cosmetics selection and purchasing experience.

[0274] The processing flow will be explained below.

[0275] Step 1:

[0276] A user accesses an e-commerce site and enters their email address and password on the login screen.

[0277] Step 2:

[0278] The terminal sends the entered login information to the server.

[0279] Step 3:

[0280] The server checks the received login information against a database and authenticates the user.

[0281] Step 4:

[0282] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[0283] Step 5:

[0284] The server notifies the user of successful authentication and begins the session.

[0285] Step 6:

[0286] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[0287] Step 7:

[0288] The terminal transmits the selected category information to the server.

[0289] Step 8:

[0290] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[0291] Step 9:

[0292] The terminal displays the generated cosmetics list to the user.

[0293] Step 10:

[0294] The user selects the cosmetic product of interest from the list.

[0295] Step 11:

[0296] The terminal transmits information about the selected cosmetics to the server.

[0297] Step 12:

[0298] The server asks the user to upload an image of their face.

[0299] Step 13:

[0300] The terminal displays the upload form to the user.

[0301] Step 14:

[0302] The user uploads an image of their face and sends it to the server via their terminal.

[0303] Step 15:

[0304] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0305] Step 16:

[0306] An image generation algorithm generates an image of the face after applying the cosmetics based on the received data.

[0307] Step 17:

[0308] The server sends the generated facial image to the device.

[0309] Step 18:

[0310] The terminal displays the generated facial image to the user.

[0311] Step 19:

[0312] The device captures the user's facial expressions and voice and sends them to the emotion engine.

[0313] Step 20:

[0314] The emotion engine analyzes the user's emotion data and sends the results to the server.

[0315] Step 21:

[0316] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[0317] Step 22:

[0318] The server sends the adjusted facial image to the device.

[0319] Step 23:

[0320] The device displays the adjusted image of the face to the user.

[0321] Step 24:

[0322] The server references the user's emotional data and basic information and recommends related cosmetics.

[0323] Step 25:

[0324] The device displays information about the recommended cosmetics to the user.

[0325] Step 26:

[0326] The user adds the selected or recommended cosmetic product to the cart.

[0327] Step 27:

[0328] The terminal guides the user through the purchase process, detailing each step.

[0329] Step 28:

[0330] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[0331] Step 29:

[0332] The user makes a final confirmation and confirms the purchase.

[0333] Step 30:

[0334] The server receives the final purchase information and processes the order.

[0335] Step 31:

[0336] The server sends an order confirmation email to the user and proceeds with the delivery process.

[0337] Example 2

[0338] 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."

[0339] In the past, when selecting cosmetics, it was difficult for users to confirm the effects and appearance of the product in advance unless they actually tried it on. Furthermore, there was no system that selected cosmetics taking into account the user's emotions, making it impossible to provide an appropriate selection and purchasing experience. As a result, users were likely to make selections that were unsatisfactory and end up purchasing the wrong product.

[0340] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for transmitting product information selected by the user to the server, means for transmitting image data uploaded by the user to the server, means for receiving the product information and image data in the server and generating an image of the user after using the product using a generation algorithm, means for receiving captured data from the terminal and analyzing the user's emotional data using an emotion analysis engine, and means for displaying the generated image and related product information to the user. This allows the user to check in advance what the product will look like after use, and recommendations based on the emotional data enable a more appropriate product selection and purchasing experience.

[0341] A "user" is an individual who uses the system to select and purchase products.

[0342] A "server" is a central computer system that receives and processes information from users.

[0343] A "terminal" is a device used by a user to input information and display results.

[0344] A "product" is an object that a user selects and considers purchasing in this system.

[0345] "Information" refers collectively to data entered by users, data processed by the server, and data generated by the system.

[0346] A "generation algorithm" is a program that generates images based on the user's image data and product information.

[0347] "Image" is visual data created by a generative algorithm that shows the user's appearance after using the product.

[0348] An "emotion analysis engine" is a technology that analyzes data such as a user's facial expressions and voice to determine their emotional state.

[0349] "Recommendation" is the act of a system suggesting products that it deems appropriate based on the user's information and emotional data.

[0350] The present invention relates to a system that visualizes the image of a product selected by a user after use and supports appropriate product selection through user sentiment analysis. This system is implemented using the following hardware and software.

[0351] Hardware and software used

[0352] 1. Server:

[0353] Database (e.g. MySQL)

[0354] Image generation algorithms (e.g., StyleGAN)

[0355] Sentiment analysis engine (e.g. OpenFace)

[0356] Data protection through SSL / TLS communication

[0357] 2. Terminal:

[0358] User devices such as computers, smartphones, and tablets

[0359] Web browser or dedicated application

[0360] Camera and microphone (for capturing emotional data)

[0361] Details of data processing and calculation

[0362] The server authenticates the user by comparing the authentication information entered by the user with the database. If authentication is successful, the server retrieves the user's basic information (skin type, skin color, age, etc.) from the database.

[0363] When a user selects a product category, the server retrieves information about products in that category and generates a list of products. This list is sent to the terminal and displayed to the user.

[0364] Once a user selects a particular cosmetic product and uploads a facial image, the server passes the image data and product information to an image generation algorithm, which generates an image of the face after using the product.

[0365] The server sends the generated image to the device and displays it to the user. The device also uses a camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion analysis engine.

[0366] The emotion analysis engine analyzes the user's emotional data and sends the results to the server, which then adjusts the generated image based on the emotional data to make it more suitable for the user.

[0367] The server recommends related products based on the user's emotional data and basic information, which are then displayed to the user on the device, who can then add the selected products to their cart.

[0368] Specific examples

[0369] For example, consider a case where a user is looking for a lip balm to combat dry lips. The user accesses an e-commerce site and enters their email address and password on the login screen. After successfully logging in, the user selects the "lip care" category. The server generates a list of applicable products and displays it to the user via their terminal. The user selects a lip balm and sends the information to the server.

[0370] Next, the server requests the user to upload an image of their face, and the user uploads an image of their face. The server passes the image data and product information to an image generation algorithm, which generates an image of the face after using the lip balm. This image is displayed on the device. The device also uses a camera and microphone to capture the user's facial expressions and voice, which are analyzed by an emotion analysis engine. Based on the analysis results, the server adjusts the generated image and recommends related products.

[0371] Prompt Sentence Examples

[0372] An example of a prompt to be input to the generative AI model is as follows:

[0373] "Generate an image of a face after using lip balm based on the following face image and lip balm information."

[0374] Face image file: user_face.jpg

[0375] Lip Balm Info: { "Brand": "BeautyX", "Product": "Moisturizing Lip Balm"}

[0376] By using the specific examples and prompts described above, users can check the image of the product after use in advance and select the appropriate product based on the results of the emotion analysis. This will realize a system that provides higher satisfaction and a more appropriate purchasing experience.

[0377] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0378] Step 1:

[0379] A user accesses an e-commerce site and enters their email address and password.

[0380] Enter your email address and password

[0381] Output: Sending authentication information

[0382] Specific behavior: A user accesses the login screen, enters their email address and password, and clicks the "Login" button.

[0383] Step 2:

[0384] The terminal transmits the entered authentication information to the server.

[0385] Input: The email address and password entered by the user

[0386] Output: Sending authentication information to the server

[0387] Specific operation: The device encrypts the authentication information using SSL / TLS and sends it to the server.

[0388] Step 3:

[0389] The server checks the received authentication information against a database and authenticates the user.

[0390] Input: Authentication information received from the device

[0391] Output: Authentication result (success or failure)

[0392] Specific operation: The server accesses a database (e.g. MySQL) and verifies the authentication information. If authentication is successful, the user ID is obtained.

[0393] Step 4:

[0394] If the server is successful in authentication, it retrieves the user's basic information from the database.

[0395] Input: User ID that was successfully authenticated

[0396] Output: User basic information

[0397] Specific operation: The server retrieves basic information (e.g., skin type, skin color, age, etc.) from the database based on the user ID.

[0398] Step 5:

[0399] The server notifies the user of successful authentication and begins the session.

[0400] Input: Authentication success result and basic user information

[0401] Output: Successful authentication and session information

[0402] Specific operation: The server generates session information and sends it to the terminal along with a notification of successful authentication.

[0403] Step 6:

[0404] The user selects a cosmetic category.

[0405] Input: Cosmetic category (e.g. skin care, lip care)

[0406] Output: Selected category information

[0407] Specific behavior: The user clicks on the desired category from the displayed category list.

[0408] Step 7:

[0409] The terminal transmits the selected category information to the server.

[0410] Input: Category information selected by the user

[0411] Output: Send category information to the server

[0412] Specific operation: The device sends a category selection event to the server.

[0413] Step 8:

[0414] The server generates a list of cosmetics according to the category and transmits it to the terminal.

[0415] Input: Selected category information

[0416] Output: Cosmetics list

[0417] Specific operation: The server retrieves the cosmetics information for the relevant category from the database, and sends it to the terminal in list format.

[0418] Step 9:

[0419] The terminal displays the generated cosmetics list to the user.

[0420] Input: Cosmetics list received from the server

[0421] Output: A list of cosmetics displayed to the user

[0422] Specific operation: The device displays the list in HTML or on a dedicated application screen.

[0423] Step 10:

[0424] The user selects the cosmetic product of interest from the list.

[0425] Input: Cosmetic information selected from the cosmetics list

[0426] Output: Selected cosmetic product information

[0427] Specific Action: The user clicks on a specific cosmetic product from the list.

[0428] Step 11:

[0429] The terminal transmits information about the selected cosmetics to the server.

[0430] Input: Cosmetic information selected by the user

[0431] Output: Sending cosmetic information to the server

[0432] Specific operation: The device sends a cosmetics selection event to the server.

[0433] Step 12:

[0434] The server requests the user to upload a facial image.

[0435] Input: Selected cosmetic information

[0436] Output: Face image upload request

[0437] Specific operation: The server generates an upload form and displays it to the user via the terminal.

[0438] Step 13:

[0439] The terminal displays the upload form to the user.

[0440] Input: Upload request received from the server

[0441] Output: The upload form that is displayed to the user

[0442] Specific behavior: The device displays an upload form.

[0443] Step 14:

[0444] The user uploads an image of their face and sends it to the server via their terminal.

[0445] Input: User's face image data

[0446] Output: Sending face image data to the server

[0447] Specific operation: The user selects their own face image and clicks the upload button. The device sends the image data to the server.

[0448] Step 15:

[0449] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0450] Input: User's facial image data and selected cosmetics information

[0451] Output: Generated face image

[0452] Specific operation: The server provides image data and cosmetic information to a generative AI model (e.g., StyleGAN) and generates a prompt. The generative AI model processes the data and generates an image.

[0453] Step 16:

[0454] An image generation algorithm generates an image of the face and returns the result to the server.

[0455] Input: Facial image data and cosmetic information received from the server

[0456] Output: Generated face image

[0457] What it does: The image generation algorithm processes and generates an image of the face after applying the cosmetics, which is then sent back to the server.

[0458] Step 17:

[0459] The device captures the user's facial expressions and voice and sends them to an emotion analysis engine.

[0460] Input: User facial and voice data

[0461] Output: Sending data to a sentiment analysis engine

[0462] What it does: The device uses the camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion analysis engine.

[0463] Step 18:

[0464] The emotion analysis engine analyzes the user's emotion data and sends the results to the server.

[0465] Input: Facial expression and voice data received from the device

[0466] Output: Parsed emotion data

[0467] Specific operation: The emotion analysis engine analyzes the user's emotional state and sends the results to the server.

[0468] Step 19:

[0469] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[0470] Input: Emotion data received from the sentiment analysis engine

[0471] Output: Adjusted face image and recommendation information

[0472] How it works: The server adjusts the generated facial image based on the emotion data and recommends related products.

[0473] Step 20:

[0474] The server sends the adjusted facial image to the device.

[0475] Input: Aligned face image

[0476] Output: Send face image to device

[0477] Specific operation: The server sends the adjusted face image to the device and displays it to the user.

[0478] Step 21:

[0479] The device displays the adjusted image of the face to the user.

[0480] Input: Adjusted face image received from the server

[0481] Output: A face image shown to the user

[0482] Specific operation: The device displays the adjusted image of the face on the application screen.

[0483] Step 22:

[0484] The server refers to the user's emotional data and basic information and recommends related products.

[0485] Input: Emotion data and basic user information

[0486] Output: Recommended product information

[0487] Specific operation: The server selects related products based on emotional data and basic information and creates a recommendation list.

[0488] Step 23:

[0489] The terminal displays the recommended product information to the user.

[0490] Input: Recommended product information received from the server

[0491] Output: A list of recommended products displayed to the user

[0492] Specific behavior: The device displays a list of recommended products to the user.

[0493] Step 24:

[0494] The user adds the recommended product to their cart.

[0495] Input: Product selected from recommended product list

[0496] Output: Product information added to cart

[0497] Specific behavior: The user selects a product from the recommended product list and clicks the Add to Cart button.

[0498] Step 25:

[0499] The device will guide you through the purchase process step by step.

[0500] Input: Product information added to cart

[0501] Output: Checkout screen

[0502] What happens: The device generates a checkout screen and guides the user through each step.

[0503] Step 26:

[0504] The user enters the required information, such as shipping address and payment information.

[0505] Input: Shipping address, payment information

[0506] Output: The entered shipping address and payment information

[0507] Specific behavior: The user enters the required information on the checkout screen and clicks the Next button.

[0508] Step 27:

[0509] The user makes a final confirmation and confirms the purchase.

[0510] Input: Final confirmation of purchase details

[0511] Output: Purchase confirmed

[0512] Specific operation: The user confirms the purchase details and clicks the "Confirm Purchase" button.

[0513] Step 28:

[0514] The server receives the final purchase information and processes the order.

[0515] Input: User purchase confirmation information

[0516] Output: Order processing begins

[0517] Specific operation: The server receives the purchase information and processes the order (e.g., checks inventory, processes payment, prepares shipping).

[0518] (Application example 2)

[0519] 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."

[0520] The present invention aims to provide a system that allows users to visually check the effects of cosmetics before purchasing them, and that selects cosmetics and provides a purchasing experience that takes the user's emotions into consideration. Conventional systems have made it difficult for users to accurately imagine the effects of using cosmetics, and have not selected cosmetics that reflect the user's emotions, making it impossible to provide a highly satisfying purchasing experience.

[0521] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for transmitting information about cosmetics selected by the user to the data processing device, means for transmitting facial image data uploaded by the user to the data processing device, means for receiving the cosmetic information and facial image data in the data processing device and generating an image of the user's face after using the cosmetics using an image generation algorithm, means for transmitting the generated facial image to the terminal, means for displaying the generated facial image and information about related cosmetics to the user, means for capturing facial expressions and voice and transmitting them to an emotion engine, means for transmitting emotion data analyzed by the emotion engine to the data processing device, and means for adjusting the generated facial image and recommendation information using the emotion data. This allows the user to visually check the effects of cosmetics in advance, and enables a more accurate selection of cosmetics based on emotions and a more satisfying purchasing experience.

[0522] A "user" is a person who accesses the system, selects cosmetics, and decides to purchase them.

[0523] "Cosmetic information" refers to attribute information related to the cosmetic selected by the user, specifically information such as brand name, product name, ingredients, effects, and price.

[0524] "Data processing device" refers to a computer system that receives, analyzes, and processes cosmetic product information and image data.

[0525] "Facial image data" refers to photographic data of a user's own face uploaded by the user.

[0526] "Image generation algorithm" refers to a program that combines image data of a user's face with information about the cosmetic product to generate an image of the user's face after using the cosmetic product.

[0527] "Terminal" refers to the device used by a user to access the system, enter information, confirm information, and complete purchase procedures. This includes smartphones, tablets, and PCs.

[0528] An "emotion engine" refers to software or hardware that analyzes emotions from a user's facial expressions and voice and feeds that data back into the system.

[0529] "Emotion data" refers to the numerical values ​​and category information resulting from the analysis by the emotion engine, and indicates the user's level of satisfaction, favorability, etc.

[0530] "Recommendation information" refers to related product suggestions provided to users by the system based on the user's basic information, cosmetic information, and emotional data.

[0531] "Purchase procedure" refers to the series of processes in which a user adds the selected product to the cart, makes payment, enters the delivery address, and finally confirms the purchase.

[0532] This invention is a virtual store system that visualizes the effects of using cosmetics selected by a user in advance and further recognizes the user's emotions to improve the cosmetics selection and purchasing experience. Specific embodiments for implementing this system are described below.

[0533] First, a user accesses the virtual store's application using a device (smartphone, tablet, PC, etc.) and logs in. After logging in, the user enters basic information, such as skin type, skin color, and age, and sends it to a data processing device (server). The server receives this information and performs user authentication.

[0534] Next, the user selects a cosmetics category (e.g., skin care, lip care, etc.), and a list of cosmetics according to the selected category is displayed on the terminal. When the user selects a cosmetic product that interests them, information about that cosmetic product is sent to the server.

[0535] The server requests the user to upload facial image data, and the user uploads the facial image via the terminal. The server uses an image generation algorithm (e.g., an AI model) to combine the uploaded facial image data with the selected cosmetic product information to generate an image of the user's face after using the cosmetic product. This generated image is then sent back to the terminal and displayed to the user.

[0536] The emotion engine then captures the user's facial expressions and voice and analyzes the user's emotional data. The analyzed emotional data is sent to the server, which then adjusts the generated facial image and recommendation information. The adjusted facial image and related cosmetic information are then displayed again on the device and presented to the user.

[0537] The system also has the function of recommending related cosmetics selected by the user. Based on the cosmetics that the user showed interest in and the analyzed emotional data, the server suggests other related products. The user can add these suggested cosmetics to their cart and proceed with the purchase process step by step.

[0538] The system's program is implemented primarily using the following hardware and software: a server as a data processing device, a terminal for user input and display, an AI model that executes the image generation algorithm, and an emotion engine that analyzes user emotions. Specifically, this includes the programming language Python, image processing with OpenCV, execution of AI models with TensorFlow and PyTorch, and emotion analysis with EmotionRecognition.

[0539] As a specific example, if a user wants to try a lip balm, they can send their facial image and lip balm information to the server, and the AI ​​model will generate an image of their face after using the lip balm. If the user is satisfied with this image, the next related product (e.g., a face cream or moisturizing lotion from the same brand) will be suggested based on the emotional data.

[0540] An example of a prompt might be, "If a user tries a lip balm, list what other related products would be recommended based on their facial image and emotion data."

[0541] In this way, the present invention allows users to visually confirm the effects of cosmetics in advance, and also provides a more accurate selection of cosmetics based on the user's emotions and a more satisfying purchasing experience.

[0542] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0543] Step 1:

[0544] A user accesses the virtual store's application using a terminal and logs in. They enter their email address and password on the login screen and send them to the server. The server compares the entered login information with a database to authenticate the user. If authentication is successful, the server obtains the user's basic information (e.g., skin type, skin color, age, etc.) and starts the session.

[0545] Step 2:

[0546] The user uses the terminal to select a cosmetics category (e.g., skin care, lip care, etc.). The selected category information is sent to the server. The server generates a cosmetics list based on the selected category and sends the generated list to the terminal. The terminal displays the received cosmetics list to the user.

[0547] Step 3:

[0548] The user selects a cosmetic product of interest from the cosmetics list. Information about the selected cosmetic product is sent from the terminal to the server. The server receives the information about the selected cosmetic product and then requests the user to upload image data of their face.

[0549] Step 4:

[0550] The user uploads an image of their face to the server via their device. The server then passes the received facial image data and selected cosmetic information to an image generation algorithm. The image generation algorithm combines the uploaded facial image data and cosmetic information to generate a facial image of the user after applying the cosmetic. The generated facial image is then sent to the device by the server.

[0551] Step 5:

[0552] The device displays the generated facial image to the user. At this time, the device captures the user's facial expressions and voice and sends them to the emotion engine. The emotion engine analyzes the user's emotional data and sends the results to the server. The server receives the emotional data and adjusts the generated facial image and recommendation information.

[0553] Step 6:

[0554] The server sends the adjusted facial image to the device, which then displays the adjusted facial image to the user. At the same time, the server recommends related cosmetics based on the user's basic information, emotional data, and cosmetic information, and sends this information to the device. The device then displays information about the recommended cosmetics to the user.

[0555] Step 7:

[0556] The user uses the device to add the recommended cosmetics to their cart. The cosmetics selected by the user are added to the cart, and the user is guided through the purchase process step by step. The server processes the necessary information for the purchase process (e.g., shipping address, payment information, etc.), and the purchase is confirmed.

[0557] This allows users to visually check the effects of cosmetics in advance, and enables them to select cosmetics more accurately based on their emotions and have a more satisfying purchasing experience.

[0558] 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.

[0559] 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.

[0560] 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.

[0561] [Second embodiment]

[0562] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0563] 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.

[0564] 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).

[0565] 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.

[0566] 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.

[0567] 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).

[0568] 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.

[0569] 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.

[0570] 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.

[0571] 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.

[0572] 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.

[0573] 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."

[0574] The present invention is a system that supports purchasing decisions by visualizing the effects of using cosmetics selected by the user in advance. This system is realized through cooperation between a server, a terminal, and the user. The program processing of this system is explained in detail below.

[0575] Basic processing flow

[0576] User authentication and basic information entry

[0577] A user accesses an e-commerce site and enters their email address and password on the login screen.

[0578] The terminal sends this authentication information to the server.

[0579] The server receives the authentication information and checks it against a database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts a session.

[0580] Selection of cosmetics

[0581] The user selects a cosmetic category, such as skin care or lip care.

[0582] The terminal transmits the selected category information to the server.

[0583] The server generates a list of applicable cosmetics and sends it to the terminal.

[0584] The user selects the cosmetic product of interest from the list.

[0585] The terminal transmits information about the selected cosmetics to the server.

[0586] Upload a face image and generate an image using AI

[0587] The server asks the user to upload a face image.

[0588] The user uploads an image of their face and sends it to the server via their terminal.

[0589] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0590] An image generation algorithm generates an image of the face and returns the result to the server.

[0591] Image display and recommendations

[0592] The server sends the generated facial image to the device.

[0593] The terminal displays the generated facial image to the user.

[0594] The server refers to the user's basic information, recommends related cosmetics, and sends that information to the terminal.

[0595] The device displays information about the recommended cosmetics to the user.

[0596] Purchase procedure

[0597] The user adds the selected or recommended cosmetic product to the cart.

[0598] The terminal guides the user through the purchase process, detailing each step.

[0599] The user follows the purchase procedure and enters and confirms the required information.

[0600] The server receives the final purchase information and processes the order.

[0601] Specific examples

[0602] For example, consider a case where a user is looking for skin care products to combat dryness in winter. The user accesses an e-commerce site and logs in. After successfully logging in, the user selects the skin care category. The server generates a list of skin care cosmetics and displays it to the user via their terminal. The user selects a moisturizing cream that interests them and sends that information to the server.

[0603] Next, the server requests the upload of a facial image, and the user uploads an image of their face. The server then feeds the received facial image and the selected moisturizing cream information into an image generation algorithm to generate an image of the face after using the moisturizing cream. This image is then displayed on the device, allowing the user to visually confirm the effect.

[0604] The server then recommends cosmetics related to the user, such as face wash and lotion from the same brand, and sends this information to the device. The user then refers to these recommendations and considers purchasing them along with the moisturizing cream. They proceed through the purchasing process by following step-by-step instructions, and finally confirm the purchase.

[0605] In this way, the present invention is a system that helps users to easily select cosmetics that are suitable for them and helps them make more reliable purchasing decisions.

[0606] The processing flow will be explained below.

[0607] Step 1:

[0608] A user accesses an e-commerce site and enters their email address and password on the login screen.

[0609] Step 2:

[0610] The terminal sends the entered login information to the server.

[0611] Step 3:

[0612] The server checks the received login information against a database and authenticates the user.

[0613] Step 4:

[0614] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[0615] Step 5:

[0616] The server notifies the user of successful authentication and begins the session.

[0617] Step 6:

[0618] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[0619] Step 7:

[0620] The terminal transmits the selected category information to the server.

[0621] Step 8:

[0622] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[0623] Step 9:

[0624] The terminal displays the generated cosmetics list to the user.

[0625] Step 10:

[0626] The user selects the cosmetic product of interest from the list.

[0627] Step 11:

[0628] The terminal transmits information about the selected cosmetics to the server.

[0629] Step 12:

[0630] The server asks the user to upload an image of their face.

[0631] Step 13:

[0632] The terminal displays the upload form to the user.

[0633] Step 14:

[0634] The user uploads an image of their face and sends it to the server via their terminal.

[0635] Step 15:

[0636] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0637] Step 16:

[0638] An image generation algorithm generates an image of the face after applying the cosmetics based on the received data.

[0639] Step 17:

[0640] The server sends the generated facial image to the device.

[0641] Step 18:

[0642] The terminal displays the generated facial image to the user.

[0643] Step 19:

[0644] The server references the user's basic information and recommends related cosmetics.

[0645] Step 20:

[0646] The device displays information about the recommended cosmetics to the user.

[0647] Step 21:

[0648] The user adds the selected or recommended cosmetic product to the cart.

[0649] Step 22:

[0650] The terminal guides the user through the purchase process, detailing each step.

[0651] Step 23:

[0652] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[0653] Step 24:

[0654] The user makes a final confirmation and confirms the purchase.

[0655] Step 25:

[0656] The server receives the final purchase information and processes the order.

[0657] Step 26:

[0658] The server sends an order confirmation email to the user and proceeds with the delivery process.

[0659] Example 1

[0660] 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."

[0661] In conventional online shopping, it is difficult for users to visually confirm the effects of using the selected product beforehand, which often makes them feel uneasy about making a purchase decision.In addition, there is a problem that the product information and recommendations suitable for the user are not provided sufficiently, making it difficult to find the most suitable product.

[0662] 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.

[0663] In this invention, the server includes a means for transmitting product information selected by the user to the server, a means for transmitting facial image data uploaded by the user to the server, and a means for generating an image of the user's face after using the product using a generative model. This allows the user to visually confirm the effects of using the selected product in advance, enabling optimal purchasing decisions.

[0664] "User" refers to an individual or legal entity that uses the service or system.

[0665] "Product Information" refers to detailed descriptions of product characteristics, price, ingredients, usage, etc.

[0666] "Server" refers to a computer on a network that processes, stores, and transmits data.

[0667] "Facial image data" refers to an image file that digitally records and stores a user's face.

[0668] A "generative model" refers to an algorithm that generates new data based on input data.

[0669] "Terminal" refers to a device (such as a personal computer, smartphone, or tablet) that a user operates.

[0670] "Image" refers to the visual result produced by a generative model.

[0671] "Basic Information" refers to personal information used for personalization, such as the user's skin type, skin color, and age.

[0672] "Recommendation" refers to suggesting related products based on a user's preferences and attributes.

[0673] A "cart" is an online location where a user temporarily stores items they are considering purchasing.

[0674] The "purchase procedure" refers to a series of steps a user goes through to complete an order for a product.

[0675] This invention is a system that supports purchasing decisions by visualizing the effects of using a product selected by the user in advance. This system is realized by the cooperation of three parties: a server, a terminal, and the user.

[0676] First, a user accesses an e-commerce site and enters their email address and password on the login screen. This information is sent from the terminal to the server. The server compares the received authentication information with a database, and if authentication is successful, obtains the user's basic information. The basic information includes the user's skin type, skin color, age, etc., and the server starts a session based on this information. The session start information and the user's basic information are sent to the terminal, which displays it on the user's screen.

[0677] Next, the user selects a cosmetics category (e.g., skin care, lip care) on the device screen. The device sends the selected category information to the server. The server retrieves a list of cosmetics in that category from the database and sends it to the device. When the user selects a cosmetic product that interests them from the list, that information is sent from the device to the server.

[0678] The server then displays a screen on the device requesting the user to upload a facial image. The user uploads their facial image, which is then sent from the device to the server. The server then provides the received facial image data and the selected cosmetic information as a prompt to the image generation AI model (e.g., DALL-E). An example of a prompt is, "Use the facial image and the selected cosmetic information to generate an image of the face after using the cosmetics."

[0679] The image generation AI model generates an image of the user's face after use based on the input data and returns the result to the server, which then sends the generated image of the face to the device, which then displays it on the user's screen.

[0680] Furthermore, the server refers to the user's basic information and recommends related cosmetics (for example, facial cleanser or lotion from the same brand). This information is also sent to the device, which displays it to the user. The user can add the recommended cosmetics to their cart and proceed to the purchase process. The device guides the user through each step of the purchase process in detail and supports them in entering and confirming the necessary information.

[0681] Finally, the server processes the order based on the purchase information received from the user. This process includes generating an order number, checking inventory, and processing payment. The server then sends the final order information to the terminal, and the terminal displays a message to the user that the order has been confirmed.

[0682] This invention allows the user to visually confirm the effects of the selected product, enabling the user to make a more reliable purchasing decision.

[0683] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0684] Step 1: User authentication and basic information entry

[0685] 1. A user enters their email address and password on the login screen of an e-commerce site. The information is sent from the device to the server.

[0686] 2. The server checks the entered authentication information against the database. Input: Authentication information (email address, password). Output: Authentication result (success / failure), basic user information.

[0687] 3. If authentication is successful, the server obtains the user's basic information (e.g., skin type, skin color, age, etc.) and starts a session. The session start information and the user's basic information are sent to the terminal. The terminal receives this information and displays it on the user's screen.

[0688] Step 2: Choose your cosmetics

[0689] 1. The user selects a cosmetics category (e.g., skin care or lip care) from a list of categories provided. The selection information is sent from the terminal to the server.

[0690] 2. The server retrieves the relevant cosmetics list from the database based on the selected category information. Input: Category information. Output: Cosmetics list.

[0691] 3. The server sends the cosmetics list to the terminal, and the terminal displays the list to the user.

[0692] 4. The user selects the cosmetics they are interested in from the list, and the selection information is sent from the terminal to the server.

[0693] Step 3: Upload a face image and generate an image using AI

[0694] 1. The server instructs the device to display a screen requesting the user to upload a facial image. The device displays the screen according to the instructions.

[0695] 2. The user uploads a picture of their face via the device screen, and the image data is sent from the device to the server.

[0696] 3. The server receives the facial image data and the selected cosmetic information and provides it as a prompt to the image generation AI model (e.g., DALL-E). Input: Facial image data, selected cosmetic information. Output: Generated facial image.

[0697] An example prompt is, "Use the image of your face and the selected cosmetic product information to generate an image of your face after using the product."

[0698] 4. The image generation AI model generates an image of the user's face based on the provided data and returns the result to the server.

[0699] 5. The server sends the generated facial image data to the device, which displays the received image on the user's screen.

[0700] Step 4: View and recommend images

[0701] 1. The device displays the generated face image received from the server to the user.

[0702] 2. The user reviews the generated facial image.

[0703] 3. The server references the user's basic information, retrieves related cosmetics (such as face wash and lotion from the same brand) from the database, and generates a list. Input: User's basic information. Output: List of related products.

[0704] 4. The server sends the relevant cosmetic list to the terminal, which displays the list to the user.

[0705] Step 5: Checkout

[0706] 1. The user adds selected or recommended cosmetics to the cart. This information is sent from the device to the server.

[0707] 2. The device will display your cart and provide detailed steps to begin the checkout process.

[0708] 3. The user enters and confirms the information required for the purchase (shipping address, payment method, etc.). This information is sent from the terminal to the server. Input: Purchase information. Output: Order confirmation.

[0709] 4. The server processes the order based on the received purchase information. Order processing includes generating an order number, checking inventory, and processing payments. Output: Final order information.

[0710] 5. The server sends the final order information to the terminal, and the terminal displays a final confirmation screen to the user. The user confirms the order and the purchase process is complete.

[0711] (Application example 1)

[0712] 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."

[0713] With conventional e-commerce sites and virtual stores, it was difficult for users to visualize the effects of using the cosmetics they selected in advance, which led to the issue of taking a long time to make a purchasing decision. In addition, because users could not actually try the cosmetics, it was difficult to confirm whether the product was truly suitable for them. This led to a situation where users were not satisfied with their ideal cosmetics selection.

[0714] 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.

[0715] In this invention, the server includes means for transmitting information about cosmetics selected by the user to the server, means for transmitting facial image data uploaded by the user to the server, means for receiving the cosmetic information and facial image data in the server and generating an image of the user's face after using the cosmetics using an image generation algorithm, means for transmitting the generated facial image to the terminal, means for displaying the generated facial image and related cosmetic information to the user, means for displaying the generated facial image to the user in real time via a smart device, and means for the user to try on cosmetics in a virtual store using prompts generated using an artificial intelligence model. This allows the user to visually check the effects of the cosmetics after applying them directly to their face in real time, making it easy to select cosmetics that suit them.

[0716] "User authentication" is the process of verifying a user's identity and granting them access to a system.

[0717] "Basic information" refers to information about the user's personal attributes (skin type, skin color, age, etc.).

[0718] "Smart devices" refers to portable electronic devices with advanced computing capabilities such as smartphones, tablets, smart glasses, and head-mounted displays.

[0719] "Cosmetics" is a general term that refers to products used to protect, moisturize, and beautify the face and skin, such as skin care and lip care.

[0720] An "image generation algorithm" is a set of calculations and processing techniques that take image data of a user's face as input and generate a specific effect (in this case, the appearance after applying cosmetics).

[0721] A "prompt sentence" refers to an instruction or input sentence that uses an image generation AI model to generate the image the user wants to see.

[0722] A "virtual store" is a virtual store that operates on the Internet and is a platform where users can browse, try out, and purchase products online.

[0723] "Real-time" refers to a state in which data processing and display are carried out immediately, with almost no time delay.

[0724] "Recommendation" refers to suggesting products suitable for a user based on the user's past behavior and basic information.

[0725] "Facial image" refers to the visual output image that results from applying a cosmetic effect to an image of a user's face.

[0726] The "purchase procedure" refers to a series of steps or processes for actually purchasing the product selected by the user.

[0727] "Terminal" refers to an electronic device (e.g., smartphone, PC, etc.) that a user uses to access the system and send and receive data.

[0728] "Artificial intelligence model" refers to machine learning and deep learning techniques used to analyze and generate data and perform specific tasks.

[0729] A "user session" refers to the sequence of activities that occur between the time a user logs in to the time they log out of the system.

[0730] The present invention is a system that supports purchase decision-making by visualizing the effects of using cosmetics selected by a user in advance. This system is realized through cooperation between a server, a terminal, and a user. The following describes in detail the mode for carrying out the present invention.

[0731] User authentication and basic information entry

[0732] The process begins when a user accesses the virtual store application using a device such as a smartphone and logs in. The user enters their email address and password on the login screen, and the device sends this authentication information to the server. The server receives the authentication information and compares it with a database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts the session.

[0733] Selection of cosmetics

[0734] The user selects a cosmetics category (e.g., skin care or lip care). The device sends the selected category information to the server, which then generates a list of the corresponding cosmetics and sends it to the device. The user selects the cosmetics they are interested in from the list, and the device sends information about the selected cosmetics to the server.

[0735] Upload a face image and generate an image using AI

[0736] The server requests the user to upload a facial image. The user takes a photo of their face using a smartphone or other device and sends it to the server via their device. The server receives the facial image data and selected cosmetic information and passes it to an image generation algorithm. The generative AI model generates an image of the face and returns the result to the server.

[0737] Image display and recommendations

[0738] The server then sends the generated facial image to the device, which then displays the image to the user. The server then refers to the user's basic information and recommends related cosmetics, sending that information to the device. The device then displays information about the recommended cosmetics to the user.

[0739] Purchase procedure

[0740] The user adds the selected or recommended cosmetics to the cart. The terminal guides the user through the purchase procedure step by step, supporting the user. The user follows the purchase procedure, inputs and confirms the necessary information, and the server receives the final purchase information and processes the order.

[0741] Hardware and software used

[0742] Hardware: smartphones, servers, databases

[0743] Software: authentication systems, image generation algorithms (e.g., DALL-E, MidJourney), virtual store applications

[0744] Prompt Sentence Examples

[0745] Specific examples of prompts include:

[0746] User "john.doe@example.com" selected "Rose Red Lip Gloss" from the Lip Care category. Upload a face image and view the AI-generated image of the product after application.

[0747] In this way, the present invention is a system that helps users to easily select cosmetics that are suitable for them and helps them make more reliable purchasing decisions.

[0748] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0749] Step 1:

[0750] A user accesses the virtual store application using a smartphone and enters their email address and password on the login screen. The device sends this authentication information to the server. The server receives this authentication information and compares it with the information stored in the database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts the session.

[0751] Input: Email address, password

[0752] Output: Authentication result, user basic information, session ID

[0753] Step 2:

[0754] The user selects a cosmetics category within the application (e.g., skin care, lip care, etc.). The device sends the selected category information to the server. The server retrieves a corresponding cosmetics list from the database based on the selected category and sends it to the device. The user selects cosmetics that interest them from this list, and the device sends that information to the server.

[0755] Input: Category selection information

[0756] Output: Cosmetics list, selected cosmetics information

[0757] Step 3:

[0758] The server requests the user to upload a facial image. The user takes a photo of their face with their smartphone and sends the image to the server via their device. The server receives this facial image data and selected cosmetic information and passes it to an image generation algorithm. The generative AI model generates an image of the face and returns the generated result to the server.

[0759] Input: Facial image, selected cosmetic information

[0760] Output: Generated face image

[0761] Step 4:

[0762] The server then sends the generated facial image to the device, which displays the image to the user in real time.The server then recommends related cosmetics based on the user's basic information and sends that information to the device.The device then displays information about the recommended cosmetics to the user.

[0763] Input: Generated face image, basic user information

[0764] Output: Facial image display, recommended cosmetics list

[0765] Step 5:

[0766] The user adds the selected or recommended cosmetics to the cart. The terminal guides the user through the purchase procedure step by step, supporting the user. Once the user follows the purchase procedure and enters and confirms the necessary information, the server receives the final purchase information and processes the order.

[0767] Input: Cosmetics added to cart, purchase information

[0768] Output: Order confirmation, purchase completion notification

[0769] Through the above processing steps, the user can visually check the cosmetics that suit him / her in real time and make a purchasing decision.

[0770] 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.

[0771] The present invention provides a system that visualizes the effects of using cosmetics selected by the user in advance and supports purchasing decisions, and by combining it with an emotion engine that recognizes the user's emotions, it provides a more suitable cosmetics selection and purchasing experience for the user. The specific processing of the program of this system is described in detail below.

[0772] Basic processing flow

[0773] User authentication and basic information entry

[0774] A user accesses an e-commerce site and enters their email address and password on the login screen.

[0775] The terminal sends this authentication information to the server.

[0776] The server checks the received login information against a database and authenticates the user.

[0777] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[0778] The server notifies the user of successful authentication and begins the session.

[0779] Selection of cosmetics

[0780] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[0781] The terminal transmits the selected category information to the server.

[0782] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[0783] The terminal displays the generated cosmetics list to the user.

[0784] The user selects the cosmetic product of interest from the list.

[0785] The terminal transmits information about the selected cosmetics to the server.

[0786] Upload a face image and generate an image using AI

[0787] The server asks the user to upload a face image.

[0788] The terminal displays the upload form to the user.

[0789] The user uploads an image of their face and sends it to the server via their terminal.

[0790] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0791] An image generation algorithm generates an image of the face and returns the result to the server.

[0792] Running and tuning the emotion engine

[0793] The device captures the user's facial expressions and voice and sends them to the emotion engine.

[0794] The emotion engine analyzes the user's emotion data and sends the results to the server.

[0795] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[0796] The server sends the adjusted facial image to the device.

[0797] Image display and recommendations

[0798] The device displays the adjusted image of the face to the user.

[0799] The server references the user's emotional data and basic information and recommends related cosmetics.

[0800] The device displays information about the recommended cosmetics to the user.

[0801] Purchase procedure

[0802] The user adds the selected or recommended cosmetic product to the cart.

[0803] The terminal guides the user through the purchase process, detailing each step.

[0804] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[0805] The user makes a final confirmation and confirms the purchase.

[0806] The server receives the final purchase information and processes the order.

[0807] Specific examples

[0808] For example, consider a case where a user is looking for a lip balm to combat dry lips. The user accesses an e-commerce site and logs in. After successfully logging in, the user selects the lip care category. The server generates a list of lip care cosmetics and displays it to the user via their terminal. The user selects the lip balm that interests them and sends the information to the server.

[0809] The server then requests a facial image upload, and the user uploads their own facial image. The server then feeds the received facial image and the selected lip balm information into an image generation algorithm to generate an image of the face after using the lip balm. This image is then displayed on the device.

[0810] The emotion engine captures the user's facial expressions and voice and analyzes how satisfied the user is with the image. Based on the emotion engine's analysis, the server adjusts the generated facial image to better match the user's emotions. It also recommends related cosmetics (e.g., other lip care products or moisturizing creams from the same brand) based on the user's satisfaction.

[0811] The user references the adjusted image and recommendations and adds the lip balm and related products to their cart. They then follow the instructions on the device to complete the purchase and finally confirm the purchase. In this way, the present invention is a system that takes user emotions into consideration to provide a more appropriate cosmetics selection and purchasing experience.

[0812] The processing flow will be explained below.

[0813] Step 1:

[0814] A user accesses an e-commerce site and enters their email address and password on the login screen.

[0815] Step 2:

[0816] The terminal sends the entered login information to the server.

[0817] Step 3:

[0818] The server checks the received login information against a database and authenticates the user.

[0819] Step 4:

[0820] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[0821] Step 5:

[0822] The server notifies the user of successful authentication and begins the session.

[0823] Step 6:

[0824] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[0825] Step 7:

[0826] The terminal transmits the selected category information to the server.

[0827] Step 8:

[0828] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[0829] Step 9:

[0830] The terminal displays the generated cosmetics list to the user.

[0831] Step 10:

[0832] The user selects the cosmetic product of interest from the list.

[0833] Step 11:

[0834] The terminal transmits information about the selected cosmetics to the server.

[0835] Step 12:

[0836] The server asks the user to upload an image of their face.

[0837] Step 13:

[0838] The terminal displays the upload form to the user.

[0839] Step 14:

[0840] The user uploads an image of their face and sends it to the server via their terminal.

[0841] Step 15:

[0842] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0843] Step 16:

[0844] An image generation algorithm generates an image of the face after applying the cosmetics based on the received data.

[0845] Step 17:

[0846] The server sends the generated facial image to the device.

[0847] Step 18:

[0848] The terminal displays the generated facial image to the user.

[0849] Step 19:

[0850] The device captures the user's facial expressions and voice and sends them to the emotion engine.

[0851] Step 20:

[0852] The emotion engine analyzes the user's emotion data and sends the results to the server.

[0853] Step 21:

[0854] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[0855] Step 22:

[0856] The server sends the adjusted facial image to the device.

[0857] Step 23:

[0858] The device displays the adjusted image of the face to the user.

[0859] Step 24:

[0860] The server references the user's emotional data and basic information and recommends related cosmetics.

[0861] Step 25:

[0862] The device displays information about the recommended cosmetics to the user.

[0863] Step 26:

[0864] The user adds the selected or recommended cosmetic product to the cart.

[0865] Step 27:

[0866] The terminal guides the user through the purchase process, detailing each step.

[0867] Step 28:

[0868] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[0869] Step 29:

[0870] The user makes a final confirmation and confirms the purchase.

[0871] Step 30:

[0872] The server receives the final purchase information and processes the order.

[0873] Step 31:

[0874] The server sends an order confirmation email to the user and proceeds with the delivery process.

[0875] Example 2

[0876] 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."

[0877] In the past, when selecting cosmetics, it was difficult for users to confirm the effects and appearance of the product in advance unless they actually tried it on. Furthermore, there was no system that selected cosmetics taking into account the user's emotions, making it impossible to provide an appropriate selection and purchasing experience. As a result, users were likely to make selections that were unsatisfactory and end up purchasing the wrong product.

[0878] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for transmitting product information selected by the user to the server, means for transmitting image data uploaded by the user to the server, means for receiving the product information and image data in the server and generating an image of the user after using the product using a generation algorithm, means for receiving captured data from the terminal and analyzing the user's emotional data using an emotion analysis engine, and means for displaying the generated image and related product information to the user. This allows the user to check in advance what the product will look like after use, and recommendations based on the emotional data enable a more appropriate product selection and purchasing experience.

[0879] A "user" is an individual who uses the system to select and purchase products.

[0880] A "server" is a central computer system that receives and processes information from users.

[0881] A "terminal" is a device used by a user to input information and display results.

[0882] A "product" is an object that a user selects and considers purchasing in this system.

[0883] "Information" refers collectively to data entered by users, data processed by the server, and data generated by the system.

[0884] A "generation algorithm" is a program that generates images based on the user's image data and product information.

[0885] "Image" is visual data created by a generative algorithm that shows the user's appearance after using the product.

[0886] An "emotion analysis engine" is a technology that analyzes data such as a user's facial expressions and voice to determine their emotional state.

[0887] "Recommendation" is the act of a system suggesting products that it deems appropriate based on the user's information and emotional data.

[0888] The present invention relates to a system that visualizes the image of a product selected by a user after use and supports appropriate product selection through user sentiment analysis. This system is implemented using the following hardware and software.

[0889] Hardware and software used

[0890] 1. Server:

[0891] Database (e.g. MySQL)

[0892] Image generation algorithms (e.g., StyleGAN)

[0893] Sentiment analysis engine (e.g. OpenFace)

[0894] Data protection through SSL / TLS communication

[0895] 2. Terminal:

[0896] User devices such as computers, smartphones, and tablets

[0897] Web browser or dedicated application

[0898] Camera and microphone (for capturing emotional data)

[0899] Details of data processing and calculation

[0900] The server authenticates the user by comparing the authentication information entered by the user with the database. If authentication is successful, the server retrieves the user's basic information (skin type, skin color, age, etc.) from the database.

[0901] When a user selects a product category, the server retrieves information about products in that category and generates a list of products. This list is sent to the terminal and displayed to the user.

[0902] Once a user selects a particular cosmetic product and uploads a facial image, the server passes the image data and product information to an image generation algorithm, which generates an image of the face after using the product.

[0903] The server sends the generated image to the device and displays it to the user. The device also uses a camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion analysis engine.

[0904] The emotion analysis engine analyzes the user's emotional data and sends the results to the server, which then adjusts the generated image based on the emotional data to make it more suitable for the user.

[0905] The server recommends related products based on the user's emotional data and basic information, which are then displayed to the user on the device, who can then add the selected products to their cart.

[0906] Specific examples

[0907] For example, consider a case where a user is looking for a lip balm to combat dry lips. The user accesses an e-commerce site and enters their email address and password on the login screen. After successfully logging in, the user selects the "lip care" category. The server generates a list of applicable products and displays it to the user via their terminal. The user selects a lip balm and sends the information to the server.

[0908] Next, the server requests the user to upload an image of their face, and the user uploads an image of their face. The server passes the image data and product information to an image generation algorithm, which generates an image of the face after using the lip balm. This image is displayed on the device. The device also uses a camera and microphone to capture the user's facial expressions and voice, which are analyzed by an emotion analysis engine. Based on the analysis results, the server adjusts the generated image and recommends related products.

[0909] Prompt Sentence Examples

[0910] An example of a prompt to be input to the generative AI model is as follows:

[0911] "Generate an image of a face after using lip balm based on the following face image and lip balm information."

[0912] Face image file: user_face.jpg

[0913] Lip Balm Info: { "Brand": "BeautyX", "Product": "Moisturizing Lip Balm"}

[0914] By using the specific examples and prompts described above, users can check the image of the product after use in advance and select the appropriate product based on the results of the emotion analysis. This will realize a system that provides higher satisfaction and a more appropriate purchasing experience.

[0915] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0916] Step 1:

[0917] A user accesses an e-commerce site and enters their email address and password.

[0918] Enter your email address and password

[0919] Output: Sending authentication information

[0920] Specific behavior: A user accesses the login screen, enters their email address and password, and clicks the "Login" button.

[0921] Step 2:

[0922] The terminal transmits the entered authentication information to the server.

[0923] Input: The email address and password entered by the user

[0924] Output: Sending authentication information to the server

[0925] Specific operation: The device encrypts the authentication information using SSL / TLS and sends it to the server.

[0926] Step 3:

[0927] The server checks the received authentication information against a database and authenticates the user.

[0928] Input: Authentication information received from the device

[0929] Output: Authentication result (success or failure)

[0930] Specific operation: The server accesses a database (e.g. MySQL) and verifies the authentication information. If authentication is successful, the user ID is obtained.

[0931] Step 4:

[0932] If the server is successful in authentication, it retrieves the user's basic information from the database.

[0933] Input: User ID that was successfully authenticated

[0934] Output: User basic information

[0935] Specific operation: The server retrieves basic information (e.g., skin type, skin color, age, etc.) from the database based on the user ID.

[0936] Step 5:

[0937] The server notifies the user of successful authentication and begins the session.

[0938] Input: Authentication success result and basic user information

[0939] Output: Successful authentication and session information

[0940] Specific operation: The server generates session information and sends it to the terminal along with a notification of successful authentication.

[0941] Step 6:

[0942] The user selects a cosmetic category.

[0943] Input: Cosmetic category (e.g. skin care, lip care)

[0944] Output: Selected category information

[0945] Specific behavior: The user clicks on the desired category from the displayed category list.

[0946] Step 7:

[0947] The terminal transmits the selected category information to the server.

[0948] Input: Category information selected by the user

[0949] Output: Send category information to the server

[0950] Specific operation: The device sends a category selection event to the server.

[0951] Step 8:

[0952] The server generates a list of cosmetics according to the category and transmits it to the terminal.

[0953] Input: Selected category information

[0954] Output: Cosmetics list

[0955] Specific operation: The server retrieves the cosmetics information for the relevant category from the database, and sends it to the terminal in list format.

[0956] Step 9:

[0957] The terminal displays the generated cosmetics list to the user.

[0958] Input: Cosmetics list received from the server

[0959] Output: A list of cosmetics displayed to the user

[0960] Specific operation: The device displays the list in HTML or on a dedicated application screen.

[0961] Step 10:

[0962] The user selects the cosmetic product of interest from the list.

[0963] Input: Cosmetic information selected from the cosmetics list

[0964] Output: Selected cosmetic product information

[0965] Specific Action: The user clicks on a specific cosmetic product from the list.

[0966] Step 11:

[0967] The terminal transmits information about the selected cosmetics to the server.

[0968] Input: Cosmetic information selected by the user

[0969] Output: Sending cosmetic information to the server

[0970] Specific operation: The device sends a cosmetics selection event to the server.

[0971] Step 12:

[0972] The server requests the user to upload a facial image.

[0973] Input: Selected cosmetic information

[0974] Output: Face image upload request

[0975] Specific operation: The server generates an upload form and displays it to the user via the terminal.

[0976] Step 13:

[0977] The terminal displays the upload form to the user.

[0978] Input: Upload request received from the server

[0979] Output: The upload form that is displayed to the user

[0980] Specific behavior: The device displays an upload form.

[0981] Step 14:

[0982] The user uploads an image of their face and sends it to the server via their terminal.

[0983] Input: User's face image data

[0984] Output: Sending face image data to the server

[0985] Specific operation: The user selects their own face image and clicks the upload button. The device sends the image data to the server.

[0986] Step 15:

[0987] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[0988] Input: User's facial image data and selected cosmetics information

[0989] Output: Generated face image

[0990] Specific operation: The server provides image data and cosmetic information to a generative AI model (e.g., StyleGAN) and generates a prompt. The generative AI model processes the data and generates an image.

[0991] Step 16:

[0992] An image generation algorithm generates an image of the face and returns the result to the server.

[0993] Input: Facial image data and cosmetic information received from the server

[0994] Output: Generated face image

[0995] What it does: The image generation algorithm processes and generates an image of the face after applying the cosmetics, which is then sent back to the server.

[0996] Step 17:

[0997] The device captures the user's facial expressions and voice and sends them to an emotion analysis engine.

[0998] Input: User facial and voice data

[0999] Output: Sending data to a sentiment analysis engine

[1000] What it does: The device uses the camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion analysis engine.

[1001] Step 18:

[1002] The emotion analysis engine analyzes the user's emotion data and sends the results to the server.

[1003] Input: Facial expression and voice data received from the device

[1004] Output: Parsed emotion data

[1005] Specific operation: The emotion analysis engine analyzes the user's emotional state and sends the results to the server.

[1006] Step 19:

[1007] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[1008] Input: Emotion data received from the sentiment analysis engine

[1009] Output: Adjusted face image and recommendation information

[1010] How it works: The server adjusts the generated facial image based on the emotion data and recommends related products.

[1011] Step 20:

[1012] The server sends the adjusted facial image to the device.

[1013] Input: Aligned face image

[1014] Output: Send face image to device

[1015] Specific operation: The server sends the adjusted face image to the device and displays it to the user.

[1016] Step 21:

[1017] The device displays the adjusted image of the face to the user.

[1018] Input: Adjusted face image received from the server

[1019] Output: A face image shown to the user

[1020] Specific operation: The device displays the adjusted image of the face on the application screen.

[1021] Step 22:

[1022] The server refers to the user's emotional data and basic information and recommends related products.

[1023] Input: Emotion data and basic user information

[1024] Output: Recommended product information

[1025] Specific operation: The server selects related products based on emotional data and basic information and creates a recommendation list.

[1026] Step 23:

[1027] The terminal displays the recommended product information to the user.

[1028] Input: Recommended product information received from the server

[1029] Output: A list of recommended products displayed to the user

[1030] Specific behavior: The device displays a list of recommended products to the user.

[1031] Step 24:

[1032] The user adds the recommended product to their cart.

[1033] Input: Product selected from recommended product list

[1034] Output: Product information added to cart

[1035] Specific behavior: The user selects a product from the recommended product list and clicks the Add to Cart button.

[1036] Step 25:

[1037] The device will guide you through the purchase process step by step.

[1038] Input: Product information added to cart

[1039] Output: Checkout screen

[1040] What happens: The device generates a checkout screen and guides the user through each step.

[1041] Step 26:

[1042] The user enters the required information, such as shipping address and payment information.

[1043] Input: Shipping address, payment information

[1044] Output: The entered shipping address and payment information

[1045] Specific behavior: The user enters the required information on the checkout screen and clicks the Next button.

[1046] Step 27:

[1047] The user makes a final confirmation and confirms the purchase.

[1048] Input: Final confirmation of purchase details

[1049] Output: Purchase confirmed

[1050] Specific operation: The user confirms the purchase details and clicks the "Confirm Purchase" button.

[1051] Step 28:

[1052] The server receives the final purchase information and processes the order.

[1053] Input: User purchase confirmation information

[1054] Output: Order processing begins

[1055] Specific operation: The server receives the purchase information and processes the order (e.g., checks inventory, processes payment, prepares shipping).

[1056] (Application example 2)

[1057] 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."

[1058] The present invention aims to provide a system that allows users to visually check the effects of cosmetics before purchasing them, and that selects cosmetics and provides a purchasing experience that takes the user's emotions into consideration. Conventional systems have made it difficult for users to accurately imagine the effects of using cosmetics, and have not selected cosmetics that reflect the user's emotions, making it impossible to provide a highly satisfying purchasing experience.

[1059] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for transmitting information about cosmetics selected by the user to the data processing device, means for transmitting facial image data uploaded by the user to the data processing device, means for receiving the cosmetic information and facial image data in the data processing device and generating an image of the user's face after using the cosmetics using an image generation algorithm, means for transmitting the generated facial image to the terminal, means for displaying the generated facial image and information about related cosmetics to the user, means for capturing facial expressions and voice and transmitting them to an emotion engine, means for transmitting emotion data analyzed by the emotion engine to the data processing device, and means for adjusting the generated facial image and recommendation information using the emotion data. This allows the user to visually check the effects of cosmetics in advance, and enables a more accurate selection of cosmetics based on emotions and a more satisfying purchasing experience.

[1060] A "user" is a person who accesses the system, selects cosmetics, and decides to purchase them.

[1061] "Cosmetic information" refers to attribute information related to the cosmetic selected by the user, specifically information such as brand name, product name, ingredients, effects, and price.

[1062] "Data processing device" refers to a computer system that receives, analyzes, and processes cosmetic product information and image data.

[1063] "Facial image data" refers to photographic data of a user's own face uploaded by the user.

[1064] "Image generation algorithm" refers to a program that combines image data of a user's face with information about the cosmetic product to generate an image of the user's face after using the cosmetic product.

[1065] "Terminal" refers to the device used by a user to access the system, enter information, confirm information, and complete purchase procedures. This includes smartphones, tablets, and PCs.

[1066] An "emotion engine" refers to software or hardware that analyzes emotions from a user's facial expressions and voice and feeds that data back into the system.

[1067] "Emotion data" refers to the numerical values ​​and category information resulting from the analysis by the emotion engine, and indicates the user's level of satisfaction, favorability, etc.

[1068] "Recommendation information" refers to related product suggestions provided to users by the system based on the user's basic information, cosmetic information, and emotional data.

[1069] "Purchase procedure" refers to the series of processes in which a user adds the selected product to the cart, makes payment, enters the delivery address, and finally confirms the purchase.

[1070] This invention is a virtual store system that visualizes the effects of using cosmetics selected by a user in advance and further recognizes the user's emotions to improve the cosmetics selection and purchasing experience. Specific embodiments for implementing this system are described below.

[1071] First, a user accesses the virtual store's application using a device (smartphone, tablet, PC, etc.) and logs in. After logging in, the user enters basic information, such as skin type, skin color, and age, and sends it to a data processing device (server). The server receives this information and performs user authentication.

[1072] Next, the user selects a cosmetics category (e.g., skin care, lip care, etc.), and a list of cosmetics according to the selected category is displayed on the terminal. When the user selects a cosmetic product that interests them, information about that cosmetic product is sent to the server.

[1073] The server requests the user to upload facial image data, and the user uploads the facial image via the terminal. The server uses an image generation algorithm (e.g., an AI model) to combine the uploaded facial image data with the selected cosmetic product information to generate an image of the user's face after using the cosmetic product. This generated image is then sent back to the terminal and displayed to the user.

[1074] The emotion engine then captures the user's facial expressions and voice and analyzes the user's emotional data. The analyzed emotional data is sent to the server, which then adjusts the generated facial image and recommendation information. The adjusted facial image and related cosmetic information are then displayed again on the device and presented to the user.

[1075] The system also has the function of recommending related cosmetics selected by the user. Based on the cosmetics that the user showed interest in and the analyzed emotional data, the server suggests other related products. The user can add these suggested cosmetics to their cart and proceed with the purchase process step by step.

[1076] The system's program is implemented primarily using the following hardware and software: a server as a data processing device, a terminal for user input and display, an AI model that executes the image generation algorithm, and an emotion engine that analyzes user emotions. Specifically, this includes the programming language Python, image processing with OpenCV, execution of AI models with TensorFlow and PyTorch, and emotion analysis with EmotionRecognition.

[1077] As a specific example, if a user wants to try a lip balm, they can send their facial image and lip balm information to the server, and the AI ​​model will generate an image of their face after using the lip balm. If the user is satisfied with this image, the next related product (e.g., a face cream or moisturizing lotion from the same brand) will be suggested based on the emotional data.

[1078] An example of a prompt might be, "If a user tries a lip balm, list what other related products would be recommended based on their facial image and emotion data."

[1079] In this way, the present invention allows users to visually confirm the effects of cosmetics in advance, and also provides a more accurate selection of cosmetics based on the user's emotions and a more satisfying purchasing experience.

[1080] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1081] Step 1:

[1082] A user accesses the virtual store's application using a terminal and logs in. They enter their email address and password on the login screen and send them to the server. The server compares the entered login information with a database to authenticate the user. If authentication is successful, the server obtains the user's basic information (e.g., skin type, skin color, age, etc.) and starts the session.

[1083] Step 2:

[1084] The user uses the terminal to select a cosmetics category (e.g., skin care, lip care, etc.). The selected category information is sent to the server. The server generates a cosmetics list based on the selected category and sends the generated list to the terminal. The terminal displays the received cosmetics list to the user.

[1085] Step 3:

[1086] The user selects a cosmetic product of interest from the cosmetics list. Information about the selected cosmetic product is sent from the terminal to the server. The server receives the information about the selected cosmetic product and then requests the user to upload image data of their face.

[1087] Step 4:

[1088] The user uploads an image of their face to the server via their device. The server then passes the received facial image data and selected cosmetic information to an image generation algorithm. The image generation algorithm combines the uploaded facial image data and cosmetic information to generate a facial image of the user after applying the cosmetic. The generated facial image is then sent to the device by the server.

[1089] Step 5:

[1090] The device displays the generated facial image to the user. At this time, the device captures the user's facial expressions and voice and sends them to the emotion engine. The emotion engine analyzes the user's emotional data and sends the results to the server. The server receives the emotional data and adjusts the generated facial image and recommendation information.

[1091] Step 6:

[1092] The server sends the adjusted facial image to the device, which then displays the adjusted facial image to the user. At the same time, the server recommends related cosmetics based on the user's basic information, emotional data, and cosmetic information, and sends this information to the device. The device then displays information about the recommended cosmetics to the user.

[1093] Step 7:

[1094] The user uses the device to add the recommended cosmetics to their cart. The cosmetics selected by the user are added to the cart, and the user is guided through the purchase process step by step. The server processes the necessary information for the purchase process (e.g., shipping address, payment information, etc.), and the purchase is confirmed.

[1095] This allows users to visually check the effects of cosmetics in advance, and enables them to select cosmetics more accurately based on their emotions and have a more satisfying purchasing experience.

[1096] 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.

[1097] 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.

[1098] 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.

[1099] [Third embodiment]

[1100] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1101] 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.

[1102] 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).

[1103] 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.

[1104] 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.

[1105] 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).

[1106] 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.

[1107] 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.

[1108] 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.

[1109] 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.

[1110] 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.

[1111] 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."

[1112] The present invention is a system that supports purchasing decisions by visualizing the effects of using cosmetics selected by the user in advance. This system is realized through cooperation between a server, a terminal, and the user. The program processing of this system is explained in detail below.

[1113] Basic processing flow

[1114] User authentication and basic information entry

[1115] A user accesses an e-commerce site and enters their email address and password on the login screen.

[1116] The terminal sends this authentication information to the server.

[1117] The server receives the authentication information and checks it against a database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts a session.

[1118] Selection of cosmetics

[1119] The user selects a cosmetic category, such as skin care or lip care.

[1120] The terminal transmits the selected category information to the server.

[1121] The server generates a list of applicable cosmetics and sends it to the terminal.

[1122] The user selects the cosmetic product of interest from the list.

[1123] The terminal transmits information about the selected cosmetics to the server.

[1124] Upload a face image and generate an image using AI

[1125] The server asks the user to upload a face image.

[1126] The user uploads an image of their face and sends it to the server via their terminal.

[1127] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1128] An image generation algorithm generates an image of the face and returns the result to the server.

[1129] Image display and recommendations

[1130] The server sends the generated facial image to the device.

[1131] The terminal displays the generated facial image to the user.

[1132] The server refers to the user's basic information, recommends related cosmetics, and sends that information to the terminal.

[1133] The device displays information about the recommended cosmetics to the user.

[1134] Purchase procedure

[1135] The user adds the selected or recommended cosmetic product to the cart.

[1136] The terminal guides the user through the purchase process, detailing each step.

[1137] The user follows the purchase procedure and enters and confirms the required information.

[1138] The server receives the final purchase information and processes the order.

[1139] Specific examples

[1140] For example, consider a case where a user is looking for skin care products to combat dryness in winter. The user accesses an e-commerce site and logs in. After successfully logging in, the user selects the skin care category. The server generates a list of skin care cosmetics and displays it to the user via their terminal. The user selects a moisturizing cream that interests them and sends that information to the server.

[1141] Next, the server requests the upload of a facial image, and the user uploads an image of their face. The server then feeds the received facial image and the selected moisturizing cream information into an image generation algorithm to generate an image of the face after using the moisturizing cream. This image is then displayed on the device, allowing the user to visually confirm the effect.

[1142] The server then recommends cosmetics related to the user, such as face wash and lotion from the same brand, and sends this information to the device. The user then refers to these recommendations and considers purchasing them along with the moisturizing cream. They proceed through the purchasing process by following step-by-step instructions, and finally confirm the purchase.

[1143] In this way, the present invention is a system that helps users to easily select cosmetics that are suitable for them and helps them make more reliable purchasing decisions.

[1144] The processing flow will be explained below.

[1145] Step 1:

[1146] A user accesses an e-commerce site and enters their email address and password on the login screen.

[1147] Step 2:

[1148] The terminal sends the entered login information to the server.

[1149] Step 3:

[1150] The server checks the received login information against a database and authenticates the user.

[1151] Step 4:

[1152] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[1153] Step 5:

[1154] The server notifies the user of successful authentication and begins the session.

[1155] Step 6:

[1156] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[1157] Step 7:

[1158] The terminal transmits the selected category information to the server.

[1159] Step 8:

[1160] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[1161] Step 9:

[1162] The terminal displays the generated cosmetics list to the user.

[1163] Step 10:

[1164] The user selects the cosmetic product of interest from the list.

[1165] Step 11:

[1166] The terminal transmits information about the selected cosmetics to the server.

[1167] Step 12:

[1168] The server asks the user to upload an image of their face.

[1169] Step 13:

[1170] The terminal displays the upload form to the user.

[1171] Step 14:

[1172] The user uploads an image of their face and sends it to the server via their terminal.

[1173] Step 15:

[1174] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1175] Step 16:

[1176] An image generation algorithm generates an image of the face after applying the cosmetics based on the received data.

[1177] Step 17:

[1178] The server sends the generated facial image to the device.

[1179] Step 18:

[1180] The terminal displays the generated facial image to the user.

[1181] Step 19:

[1182] The server references the user's basic information and recommends related cosmetics.

[1183] Step 20:

[1184] The device displays information about the recommended cosmetics to the user.

[1185] Step 21:

[1186] The user adds the selected or recommended cosmetic product to the cart.

[1187] Step 22:

[1188] The terminal guides the user through the purchase process, detailing each step.

[1189] Step 23:

[1190] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[1191] Step 24:

[1192] The user makes a final confirmation and confirms the purchase.

[1193] Step 25:

[1194] The server receives the final purchase information and processes the order.

[1195] Step 26:

[1196] The server sends an order confirmation email to the user and proceeds with the delivery process.

[1197] Example 1

[1198] 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."

[1199] In conventional online shopping, it is difficult for users to visually confirm the effects of using the selected product beforehand, which often makes them feel uneasy about making a purchase decision.In addition, there is a problem that the product information and recommendations suitable for the user are not provided sufficiently, making it difficult to find the most suitable product.

[1200] 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.

[1201] In this invention, the server includes a means for transmitting product information selected by the user to the server, a means for transmitting facial image data uploaded by the user to the server, and a means for generating an image of the user's face after using the product using a generative model. This allows the user to visually confirm the effects of using the selected product in advance, enabling optimal purchasing decisions.

[1202] "User" refers to an individual or legal entity that uses the service or system.

[1203] "Product Information" refers to detailed descriptions of product characteristics, price, ingredients, usage, etc.

[1204] "Server" refers to a computer on a network that processes, stores, and transmits data.

[1205] "Facial image data" refers to an image file that digitally records and stores a user's face.

[1206] A "generative model" refers to an algorithm that generates new data based on input data.

[1207] "Terminal" refers to a device (such as a personal computer, smartphone, or tablet) that a user operates.

[1208] "Image" refers to the visual result produced by a generative model.

[1209] "Basic Information" refers to personal information used for personalization, such as the user's skin type, skin color, and age.

[1210] "Recommendation" refers to suggesting related products based on a user's preferences and attributes.

[1211] A "cart" is an online location where a user temporarily stores items they are considering purchasing.

[1212] The "purchase procedure" refers to a series of steps a user goes through to complete an order for a product.

[1213] This invention is a system that supports purchasing decisions by visualizing the effects of using a product selected by the user in advance. This system is realized by the cooperation of three parties: a server, a terminal, and the user.

[1214] First, a user accesses an e-commerce site and enters their email address and password on the login screen. This information is sent from the terminal to the server. The server compares the received authentication information with a database, and if authentication is successful, obtains the user's basic information. The basic information includes the user's skin type, skin color, age, etc., and the server starts a session based on this information. The session start information and the user's basic information are sent to the terminal, which displays it on the user's screen.

[1215] Next, the user selects a cosmetics category (e.g., skin care, lip care) on the device screen. The device sends the selected category information to the server. The server retrieves a list of cosmetics in that category from the database and sends it to the device. When the user selects a cosmetic product that interests them from the list, that information is sent from the device to the server.

[1216] The server then displays a screen on the device requesting the user to upload a facial image. The user uploads their facial image, which is then sent from the device to the server. The server then provides the received facial image data and the selected cosmetic information as a prompt to the image generation AI model (e.g., DALL-E). An example of a prompt is, "Use the facial image and the selected cosmetic information to generate an image of the face after using the cosmetics."

[1217] The image generation AI model generates an image of the user's face after use based on the input data and returns the result to the server, which then sends the generated image of the face to the device, which then displays it on the user's screen.

[1218] Furthermore, the server refers to the user's basic information and recommends related cosmetics (for example, facial cleanser or lotion from the same brand). This information is also sent to the device, which displays it to the user. The user can add the recommended cosmetics to their cart and proceed to the purchase process. The device guides the user through each step of the purchase process in detail and supports them in entering and confirming the necessary information.

[1219] Finally, the server processes the order based on the purchase information received from the user. This process includes generating an order number, checking inventory, and processing payment. The server then sends the final order information to the terminal, and the terminal displays a message to the user that the order has been confirmed.

[1220] This invention allows the user to visually confirm the effects of the selected product, enabling the user to make a more reliable purchasing decision.

[1221] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1222] Step 1: User authentication and basic information entry

[1223] 1. A user enters their email address and password on the login screen of an e-commerce site. The information is sent from the device to the server.

[1224] 2. The server checks the entered authentication information against the database. Input: Authentication information (email address, password). Output: Authentication result (success / failure), basic user information.

[1225] 3. If authentication is successful, the server obtains the user's basic information (e.g., skin type, skin color, age, etc.) and starts a session. The session start information and the user's basic information are sent to the terminal. The terminal receives this information and displays it on the user's screen.

[1226] Step 2: Choose your cosmetics

[1227] 1. The user selects a cosmetics category (e.g., skin care or lip care) from a list of categories provided. The selection information is sent from the terminal to the server.

[1228] 2. The server retrieves the relevant cosmetics list from the database based on the selected category information. Input: Category information. Output: Cosmetics list.

[1229] 3. The server sends the cosmetics list to the terminal, and the terminal displays the list to the user.

[1230] 4. The user selects the cosmetics they are interested in from the list, and the selection information is sent from the terminal to the server.

[1231] Step 3: Upload a face image and generate an image using AI

[1232] 1. The server instructs the device to display a screen requesting the user to upload a facial image. The device displays the screen according to the instructions.

[1233] 2. The user uploads a picture of their face via the device screen, and the image data is sent from the device to the server.

[1234] 3. The server receives the facial image data and the selected cosmetic information and provides it as a prompt to the image generation AI model (e.g., DALL-E). Input: Facial image data, selected cosmetic information. Output: Generated facial image.

[1235] An example prompt is, "Use the image of your face and the selected cosmetic product information to generate an image of your face after using the product."

[1236] 4. The image generation AI model generates an image of the user's face based on the provided data and returns the result to the server.

[1237] 5. The server sends the generated facial image data to the device, which displays the received image on the user's screen.

[1238] Step 4: View and recommend images

[1239] 1. The device displays the generated face image received from the server to the user.

[1240] 2. The user reviews the generated facial image.

[1241] 3. The server references the user's basic information, retrieves related cosmetics (such as face wash and lotion from the same brand) from the database, and generates a list. Input: User's basic information. Output: List of related products.

[1242] 4. The server sends the relevant cosmetic list to the terminal, which displays the list to the user.

[1243] Step 5: Checkout

[1244] 1. The user adds selected or recommended cosmetics to the cart. This information is sent from the device to the server.

[1245] 2. The device will display your cart and provide detailed steps to begin the checkout process.

[1246] 3. The user enters and confirms the information required for the purchase (shipping address, payment method, etc.). This information is sent from the terminal to the server. Input: Purchase information. Output: Order confirmation.

[1247] 4. The server processes the order based on the received purchase information. Order processing includes generating an order number, checking inventory, and processing payments. Output: Final order information.

[1248] 5. The server sends the final order information to the terminal, and the terminal displays a final confirmation screen to the user. The user confirms the order and the purchase process is complete.

[1249] (Application example 1)

[1250] 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."

[1251] With conventional e-commerce sites and virtual stores, it was difficult for users to visualize the effects of using the cosmetics they selected in advance, which led to the issue of taking a long time to make a purchasing decision. In addition, because users could not actually try the cosmetics, it was difficult to confirm whether the product was truly suitable for them. This led to a situation where users were not satisfied with their ideal cosmetics selection.

[1252] 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.

[1253] In this invention, the server includes means for transmitting information about cosmetics selected by the user to the server, means for transmitting facial image data uploaded by the user to the server, means for receiving the cosmetic information and facial image data in the server and generating an image of the user's face after using the cosmetics using an image generation algorithm, means for transmitting the generated facial image to the terminal, means for displaying the generated facial image and related cosmetic information to the user, means for displaying the generated facial image to the user in real time via a smart device, and means for the user to try on cosmetics in a virtual store using prompts generated using an artificial intelligence model. This allows the user to visually check the effects of the cosmetics after applying them directly to their face in real time, making it easy to select cosmetics that suit them.

[1254] "User authentication" is the process of verifying a user's identity and granting them access to a system.

[1255] "Basic information" refers to information about the user's personal attributes (skin type, skin color, age, etc.).

[1256] "Smart devices" refers to portable electronic devices with advanced computing capabilities such as smartphones, tablets, smart glasses, and head-mounted displays.

[1257] "Cosmetics" is a general term that refers to products used to protect, moisturize, and beautify the face and skin, such as skin care and lip care.

[1258] An "image generation algorithm" is a set of calculations and processing techniques that take image data of a user's face as input and generate a specific effect (in this case, the appearance after applying cosmetics).

[1259] A "prompt sentence" refers to an instruction or input sentence that uses an image generation AI model to generate the image the user wants to see.

[1260] A "virtual store" is a virtual store that operates on the Internet and is a platform where users can browse, try out, and purchase products online.

[1261] "Real-time" refers to a state in which data processing and display are carried out immediately, with almost no time delay.

[1262] "Recommendation" refers to suggesting products suitable for a user based on the user's past behavior and basic information.

[1263] "Facial image" refers to the visual output image that results from applying a cosmetic effect to an image of a user's face.

[1264] The "purchase procedure" refers to a series of steps or processes for actually purchasing the product selected by the user.

[1265] "Terminal" refers to an electronic device (e.g., smartphone, PC, etc.) that a user uses to access the system and send and receive data.

[1266] "Artificial intelligence model" refers to machine learning and deep learning techniques used to analyze and generate data and perform specific tasks.

[1267] A "user session" refers to the sequence of activities that occur between the time a user logs in to the time they log out of the system.

[1268] The present invention is a system that supports purchase decision-making by visualizing the effects of using cosmetics selected by a user in advance. This system is realized through cooperation between a server, a terminal, and a user. The following describes in detail the mode for carrying out the present invention.

[1269] User authentication and basic information entry

[1270] The process begins when a user accesses the virtual store application using a device such as a smartphone and logs in. The user enters their email address and password on the login screen, and the device sends this authentication information to the server. The server receives the authentication information and compares it with a database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts the session.

[1271] Selection of cosmetics

[1272] The user selects a cosmetics category (e.g., skin care or lip care). The device sends the selected category information to the server, which then generates a list of the corresponding cosmetics and sends it to the device. The user selects the cosmetics they are interested in from the list, and the device sends information about the selected cosmetics to the server.

[1273] Upload a face image and generate an image using AI

[1274] The server requests the user to upload a facial image. The user takes a photo of their face using a smartphone or other device and sends it to the server via their device. The server receives the facial image data and selected cosmetic information and passes it to an image generation algorithm. The generative AI model generates an image of the face and returns the result to the server.

[1275] Image display and recommendations

[1276] The server then sends the generated facial image to the device, which then displays the image to the user. The server then refers to the user's basic information and recommends related cosmetics, sending that information to the device. The device then displays information about the recommended cosmetics to the user.

[1277] Purchase procedure

[1278] The user adds the selected or recommended cosmetics to the cart. The terminal guides the user through the purchase procedure step by step, supporting the user. The user follows the purchase procedure, inputs and confirms the necessary information, and the server receives the final purchase information and processes the order.

[1279] Hardware and software used

[1280] Hardware: smartphones, servers, databases

[1281] Software: authentication systems, image generation algorithms (e.g., DALL-E, MidJourney), virtual store applications

[1282] Prompt Sentence Examples

[1283] Specific examples of prompts include:

[1284] User "john.doe@example.com" selected "Rose Red Lip Gloss" from the Lip Care category. Upload a face image and view the AI-generated image of the product after application.

[1285] In this way, the present invention is a system that helps users to easily select cosmetics that are suitable for them and helps them make more reliable purchasing decisions.

[1286] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1287] Step 1:

[1288] A user accesses the virtual store application using a smartphone and enters their email address and password on the login screen. The device sends this authentication information to the server. The server receives this authentication information and compares it with the information stored in the database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts the session.

[1289] Input: Email address, password

[1290] Output: Authentication result, user basic information, session ID

[1291] Step 2:

[1292] The user selects a cosmetics category within the application (e.g., skin care, lip care, etc.). The device sends the selected category information to the server. The server retrieves a corresponding cosmetics list from the database based on the selected category and sends it to the device. The user selects cosmetics that interest them from this list, and the device sends that information to the server.

[1293] Input: Category selection information

[1294] Output: Cosmetics list, selected cosmetics information

[1295] Step 3:

[1296] The server requests the user to upload a facial image. The user takes a photo of their face with their smartphone and sends the image to the server via their device. The server receives this facial image data and selected cosmetic information and passes it to an image generation algorithm. The generative AI model generates an image of the face and returns the generated result to the server.

[1297] Input: Facial image, selected cosmetic information

[1298] Output: Generated face image

[1299] Step 4:

[1300] The server then sends the generated facial image to the device, which displays the image to the user in real time.The server then recommends related cosmetics based on the user's basic information and sends that information to the device.The device then displays information about the recommended cosmetics to the user.

[1301] Input: Generated face image, basic user information

[1302] Output: Facial image display, recommended cosmetics list

[1303] Step 5:

[1304] The user adds the selected or recommended cosmetics to the cart. The terminal guides the user through the purchase procedure step by step, supporting the user. Once the user follows the purchase procedure and enters and confirms the necessary information, the server receives the final purchase information and processes the order.

[1305] Input: Cosmetics added to cart, purchase information

[1306] Output: Order confirmation, purchase completion notification

[1307] Through the above processing steps, the user can visually check the cosmetics that suit him / her in real time and make a purchasing decision.

[1308] 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.

[1309] The present invention provides a system that visualizes the effects of using cosmetics selected by the user in advance and supports purchasing decisions, and by combining it with an emotion engine that recognizes the user's emotions, it provides a more suitable cosmetics selection and purchasing experience for the user. The specific processing of the program of this system is described in detail below.

[1310] Basic processing flow

[1311] User authentication and basic information entry

[1312] A user accesses an e-commerce site and enters their email address and password on the login screen.

[1313] The terminal sends this authentication information to the server.

[1314] The server checks the received login information against a database and authenticates the user.

[1315] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[1316] The server notifies the user of successful authentication and begins the session.

[1317] Selection of cosmetics

[1318] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[1319] The terminal transmits the selected category information to the server.

[1320] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[1321] The terminal displays the generated cosmetics list to the user.

[1322] The user selects the cosmetic product of interest from the list.

[1323] The terminal transmits information about the selected cosmetics to the server.

[1324] Upload a face image and generate an image using AI

[1325] The server asks the user to upload a face image.

[1326] The terminal displays the upload form to the user.

[1327] The user uploads an image of their face and sends it to the server via their terminal.

[1328] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1329] An image generation algorithm generates an image of the face and returns the result to the server.

[1330] Running and tuning the emotion engine

[1331] The device captures the user's facial expressions and voice and sends them to the emotion engine.

[1332] The emotion engine analyzes the user's emotion data and sends the results to the server.

[1333] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[1334] The server sends the adjusted facial image to the device.

[1335] Image display and recommendations

[1336] The device displays the adjusted image of the face to the user.

[1337] The server references the user's emotional data and basic information and recommends related cosmetics.

[1338] The device displays information about the recommended cosmetics to the user.

[1339] Purchase procedure

[1340] The user adds the selected or recommended cosmetic product to the cart.

[1341] The terminal guides the user through the purchase process, detailing each step.

[1342] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[1343] The user makes a final confirmation and confirms the purchase.

[1344] The server receives the final purchase information and processes the order.

[1345] Specific examples

[1346] For example, consider a case where a user is looking for a lip balm to combat dry lips. The user accesses an e-commerce site and logs in. After successfully logging in, the user selects the lip care category. The server generates a list of lip care cosmetics and displays it to the user via their terminal. The user selects the lip balm that interests them and sends the information to the server.

[1347] The server then requests a facial image upload, and the user uploads their own facial image. The server then feeds the received facial image and the selected lip balm information into an image generation algorithm to generate an image of the face after using the lip balm. This image is then displayed on the device.

[1348] The emotion engine captures the user's facial expressions and voice and analyzes how satisfied the user is with the image. Based on the emotion engine's analysis, the server adjusts the generated facial image to better match the user's emotions. It also recommends related cosmetics (e.g., other lip care products or moisturizing creams from the same brand) based on the user's satisfaction.

[1349] The user references the adjusted image and recommendations and adds the lip balm and related products to their cart. They then follow the instructions on the device to complete the purchase and finally confirm the purchase. In this way, the present invention is a system that takes user emotions into consideration to provide a more appropriate cosmetics selection and purchasing experience.

[1350] The processing flow will be explained below.

[1351] Step 1:

[1352] A user accesses an e-commerce site and enters their email address and password on the login screen.

[1353] Step 2:

[1354] The terminal sends the entered login information to the server.

[1355] Step 3:

[1356] The server checks the received login information against a database and authenticates the user.

[1357] Step 4:

[1358] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[1359] Step 5:

[1360] The server notifies the user of successful authentication and begins the session.

[1361] Step 6:

[1362] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[1363] Step 7:

[1364] The terminal transmits the selected category information to the server.

[1365] Step 8:

[1366] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[1367] Step 9:

[1368] The terminal displays the generated cosmetics list to the user.

[1369] Step 10:

[1370] The user selects the cosmetic product of interest from the list.

[1371] Step 11:

[1372] The terminal transmits information about the selected cosmetics to the server.

[1373] Step 12:

[1374] The server asks the user to upload an image of their face.

[1375] Step 13:

[1376] The terminal displays the upload form to the user.

[1377] Step 14:

[1378] The user uploads an image of their face and sends it to the server via their terminal.

[1379] Step 15:

[1380] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1381] Step 16:

[1382] An image generation algorithm generates an image of the face after applying the cosmetics based on the received data.

[1383] Step 17:

[1384] The server sends the generated facial image to the device.

[1385] Step 18:

[1386] The terminal displays the generated facial image to the user.

[1387] Step 19:

[1388] The device captures the user's facial expressions and voice and sends them to the emotion engine.

[1389] Step 20:

[1390] The emotion engine analyzes the user's emotion data and sends the results to the server.

[1391] Step 21:

[1392] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[1393] Step 22:

[1394] The server sends the adjusted facial image to the device.

[1395] Step 23:

[1396] The device displays the adjusted image of the face to the user.

[1397] Step 24:

[1398] The server references the user's emotional data and basic information and recommends related cosmetics.

[1399] Step 25:

[1400] The device displays information about the recommended cosmetics to the user.

[1401] Step 26:

[1402] The user adds the selected or recommended cosmetic product to the cart.

[1403] Step 27:

[1404] The terminal guides the user through the purchase process, detailing each step.

[1405] Step 28:

[1406] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[1407] Step 29:

[1408] The user makes a final confirmation and confirms the purchase.

[1409] Step 30:

[1410] The server receives the final purchase information and processes the order.

[1411] Step 31:

[1412] The server sends an order confirmation email to the user and proceeds with the delivery process.

[1413] Example 2

[1414] 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."

[1415] In the past, when selecting cosmetics, it was difficult for users to confirm the effects and appearance of the product in advance unless they actually tried it on. Furthermore, there was no system that selected cosmetics taking into account the user's emotions, making it impossible to provide an appropriate selection and purchasing experience. As a result, users were likely to make selections that were unsatisfactory and end up purchasing the wrong product.

[1416] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for transmitting product information selected by the user to the server, means for transmitting image data uploaded by the user to the server, means for receiving the product information and image data in the server and generating an image of the user after using the product using a generation algorithm, means for receiving captured data from the terminal and analyzing the user's emotional data using an emotion analysis engine, and means for displaying the generated image and related product information to the user. This allows the user to check in advance what the product will look like after use, and recommendations based on the emotional data enable a more appropriate product selection and purchasing experience.

[1417] A "user" is an individual who uses the system to select and purchase products.

[1418] A "server" is a central computer system that receives and processes information from users.

[1419] A "terminal" is a device used by a user to input information and display results.

[1420] A "product" is an object that a user selects and considers purchasing in this system.

[1421] "Information" refers collectively to data entered by users, data processed by the server, and data generated by the system.

[1422] A "generation algorithm" is a program that generates images based on the user's image data and product information.

[1423] "Image" is visual data created by a generative algorithm that shows the user's appearance after using the product.

[1424] An "emotion analysis engine" is a technology that analyzes data such as a user's facial expressions and voice to determine their emotional state.

[1425] "Recommendation" is the act of a system suggesting products that it deems appropriate based on the user's information and emotional data.

[1426] The present invention relates to a system that visualizes the image of a product selected by a user after use and supports appropriate product selection through user sentiment analysis. This system is implemented using the following hardware and software.

[1427] Hardware and software used

[1428] 1. Server:

[1429] Database (e.g. MySQL)

[1430] Image generation algorithms (e.g., StyleGAN)

[1431] Sentiment analysis engine (e.g. OpenFace)

[1432] Data protection through SSL / TLS communication

[1433] 2. Terminal:

[1434] User devices such as computers, smartphones, and tablets

[1435] Web browser or dedicated application

[1436] Camera and microphone (for capturing emotional data)

[1437] Details of data processing and calculation

[1438] The server authenticates the user by comparing the authentication information entered by the user with the database. If authentication is successful, the server retrieves the user's basic information (skin type, skin color, age, etc.) from the database.

[1439] When a user selects a product category, the server retrieves information about products in that category and generates a list of products. This list is sent to the terminal and displayed to the user.

[1440] Once a user selects a particular cosmetic product and uploads a facial image, the server passes the image data and product information to an image generation algorithm, which generates an image of the face after using the product.

[1441] The server sends the generated image to the device and displays it to the user. The device also uses a camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion analysis engine.

[1442] The emotion analysis engine analyzes the user's emotional data and sends the results to the server, which then adjusts the generated image based on the emotional data to make it more suitable for the user.

[1443] The server recommends related products based on the user's emotional data and basic information, which are then displayed to the user on the device, who can then add the selected products to their cart.

[1444] Specific examples

[1445] For example, consider a case where a user is looking for a lip balm to combat dry lips. The user accesses an e-commerce site and enters their email address and password on the login screen. After successfully logging in, the user selects the "lip care" category. The server generates a list of applicable products and displays it to the user via their terminal. The user selects a lip balm and sends the information to the server.

[1446] Next, the server requests the user to upload an image of their face, and the user uploads an image of their face. The server passes the image data and product information to an image generation algorithm, which generates an image of the face after using the lip balm. This image is displayed on the device. The device also uses a camera and microphone to capture the user's facial expressions and voice, which are analyzed by an emotion analysis engine. Based on the analysis results, the server adjusts the generated image and recommends related products.

[1447] Prompt Sentence Examples

[1448] An example of a prompt to be input to the generative AI model is as follows:

[1449] "Generate an image of a face after using lip balm based on the following face image and lip balm information."

[1450] Face image file: user_face.jpg

[1451] Lip Balm Info: { "Brand": "BeautyX", "Product": "Moisturizing Lip Balm"}

[1452] By using the specific examples and prompts described above, users can check the image of the product after use in advance and select the appropriate product based on the results of the emotion analysis. This will realize a system that provides higher satisfaction and a more appropriate purchasing experience.

[1453] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1454] Step 1:

[1455] A user accesses an e-commerce site and enters their email address and password.

[1456] Enter your email address and password

[1457] Output: Sending authentication information

[1458] Specific behavior: A user accesses the login screen, enters their email address and password, and clicks the "Login" button.

[1459] Step 2:

[1460] The terminal transmits the entered authentication information to the server.

[1461] Input: The email address and password entered by the user

[1462] Output: Sending authentication information to the server

[1463] Specific operation: The device encrypts the authentication information using SSL / TLS and sends it to the server.

[1464] Step 3:

[1465] The server checks the received authentication information against a database and authenticates the user.

[1466] Input: Authentication information received from the device

[1467] Output: Authentication result (success or failure)

[1468] Specific operation: The server accesses a database (e.g. MySQL) and verifies the authentication information. If authentication is successful, the user ID is obtained.

[1469] Step 4:

[1470] If the server is successful in authentication, it retrieves the user's basic information from the database.

[1471] Input: User ID that was successfully authenticated

[1472] Output: User basic information

[1473] Specific operation: The server retrieves basic information (e.g., skin type, skin color, age, etc.) from the database based on the user ID.

[1474] Step 5:

[1475] The server notifies the user of successful authentication and begins the session.

[1476] Input: Authentication success result and basic user information

[1477] Output: Successful authentication and session information

[1478] Specific operation: The server generates session information and sends it to the terminal along with a notification of successful authentication.

[1479] Step 6:

[1480] The user selects a cosmetic category.

[1481] Input: Cosmetic category (e.g. skin care, lip care)

[1482] Output: Selected category information

[1483] Specific behavior: The user clicks on the desired category from the displayed category list.

[1484] Step 7:

[1485] The terminal transmits the selected category information to the server.

[1486] Input: Category information selected by the user

[1487] Output: Send category information to the server

[1488] Specific operation: The device sends a category selection event to the server.

[1489] Step 8:

[1490] The server generates a list of cosmetics according to the category and transmits it to the terminal.

[1491] Input: Selected category information

[1492] Output: Cosmetics list

[1493] Specific operation: The server retrieves the cosmetics information for the relevant category from the database, and sends it to the terminal in list format.

[1494] Step 9:

[1495] The terminal displays the generated cosmetics list to the user.

[1496] Input: Cosmetics list received from the server

[1497] Output: A list of cosmetics displayed to the user

[1498] Specific operation: The device displays the list in HTML or on a dedicated application screen.

[1499] Step 10:

[1500] The user selects the cosmetic product of interest from the list.

[1501] Input: Cosmetic information selected from the cosmetics list

[1502] Output: Selected cosmetic product information

[1503] Specific Action: The user clicks on a specific cosmetic product from the list.

[1504] Step 11:

[1505] The terminal transmits information about the selected cosmetics to the server.

[1506] Input: Cosmetic information selected by the user

[1507] Output: Sending cosmetic information to the server

[1508] Specific operation: The device sends a cosmetics selection event to the server.

[1509] Step 12:

[1510] The server requests the user to upload a facial image.

[1511] Input: Selected cosmetic information

[1512] Output: Face image upload request

[1513] Specific operation: The server generates an upload form and displays it to the user via the terminal.

[1514] Step 13:

[1515] The terminal displays the upload form to the user.

[1516] Input: Upload request received from the server

[1517] Output: The upload form that is displayed to the user

[1518] Specific behavior: The device displays an upload form.

[1519] Step 14:

[1520] The user uploads an image of their face and sends it to the server via their terminal.

[1521] Input: User's face image data

[1522] Output: Sending face image data to the server

[1523] Specific operation: The user selects their own face image and clicks the upload button. The device sends the image data to the server.

[1524] Step 15:

[1525] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1526] Input: User's facial image data and selected cosmetics information

[1527] Output: Generated face image

[1528] Specific operation: The server provides image data and cosmetic information to a generative AI model (e.g., StyleGAN) and generates a prompt. The generative AI model processes the data and generates an image.

[1529] Step 16:

[1530] An image generation algorithm generates an image of the face and returns the result to the server.

[1531] Input: Facial image data and cosmetic information received from the server

[1532] Output: Generated face image

[1533] What it does: The image generation algorithm processes and generates an image of the face after applying the cosmetics, which is then sent back to the server.

[1534] Step 17:

[1535] The device captures the user's facial expressions and voice and sends them to an emotion analysis engine.

[1536] Input: User facial and voice data

[1537] Output: Sending data to a sentiment analysis engine

[1538] What it does: The device uses the camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion analysis engine.

[1539] Step 18:

[1540] The emotion analysis engine analyzes the user's emotion data and sends the results to the server.

[1541] Input: Facial expression and voice data received from the device

[1542] Output: Parsed emotion data

[1543] Specific operation: The emotion analysis engine analyzes the user's emotional state and sends the results to the server.

[1544] Step 19:

[1545] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[1546] Input: Emotion data received from the sentiment analysis engine

[1547] Output: Adjusted face image and recommendation information

[1548] How it works: The server adjusts the generated facial image based on the emotion data and recommends related products.

[1549] Step 20:

[1550] The server sends the adjusted facial image to the device.

[1551] Input: Aligned face image

[1552] Output: Send face image to device

[1553] Specific operation: The server sends the adjusted face image to the device and displays it to the user.

[1554] Step 21:

[1555] The device displays the adjusted image of the face to the user.

[1556] Input: Adjusted face image received from the server

[1557] Output: A face image shown to the user

[1558] Specific operation: The device displays the adjusted image of the face on the application screen.

[1559] Step 22:

[1560] The server refers to the user's emotional data and basic information and recommends related products.

[1561] Input: Emotion data and basic user information

[1562] Output: Recommended product information

[1563] Specific operation: The server selects related products based on emotional data and basic information and creates a recommendation list.

[1564] Step 23:

[1565] The terminal displays the recommended product information to the user.

[1566] Input: Recommended product information received from the server

[1567] Output: A list of recommended products displayed to the user

[1568] Specific behavior: The device displays a list of recommended products to the user.

[1569] Step 24:

[1570] The user adds the recommended product to their cart.

[1571] Input: Product selected from recommended product list

[1572] Output: Product information added to cart

[1573] Specific behavior: The user selects a product from the recommended product list and clicks the Add to Cart button.

[1574] Step 25:

[1575] The device will guide you through the purchase process step by step.

[1576] Input: Product information added to cart

[1577] Output: Checkout screen

[1578] What happens: The device generates a checkout screen and guides the user through each step.

[1579] Step 26:

[1580] The user enters the required information, such as shipping address and payment information.

[1581] Input: Shipping address, payment information

[1582] Output: The entered shipping address and payment information

[1583] Specific behavior: The user enters the required information on the checkout screen and clicks the Next button.

[1584] Step 27:

[1585] The user makes a final confirmation and confirms the purchase.

[1586] Input: Final confirmation of purchase details

[1587] Output: Purchase confirmed

[1588] Specific operation: The user confirms the purchase details and clicks the "Confirm Purchase" button.

[1589] Step 28:

[1590] The server receives the final purchase information and processes the order.

[1591] Input: User purchase confirmation information

[1592] Output: Order processing begins

[1593] Specific operation: The server receives the purchase information and processes the order (e.g., checks inventory, processes payment, prepares shipping).

[1594] (Application example 2)

[1595] 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."

[1596] The present invention aims to provide a system that allows users to visually check the effects of cosmetics before purchasing them, and that selects cosmetics and provides a purchasing experience that takes the user's emotions into consideration. Conventional systems have made it difficult for users to accurately imagine the effects of using cosmetics, and have not selected cosmetics that reflect the user's emotions, making it impossible to provide a highly satisfying purchasing experience.

[1597] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for transmitting information about cosmetics selected by the user to the data processing device, means for transmitting facial image data uploaded by the user to the data processing device, means for receiving the cosmetic information and facial image data in the data processing device and generating an image of the user's face after using the cosmetics using an image generation algorithm, means for transmitting the generated facial image to the terminal, means for displaying the generated facial image and information about related cosmetics to the user, means for capturing facial expressions and voice and transmitting them to an emotion engine, means for transmitting emotion data analyzed by the emotion engine to the data processing device, and means for adjusting the generated facial image and recommendation information using the emotion data. This allows the user to visually check the effects of cosmetics in advance, and enables a more accurate selection of cosmetics based on emotions and a more satisfying purchasing experience.

[1598] A "user" is a person who accesses the system, selects cosmetics, and decides to purchase them.

[1599] "Cosmetic information" refers to attribute information related to the cosmetic selected by the user, specifically information such as brand name, product name, ingredients, effects, and price.

[1600] "Data processing device" refers to a computer system that receives, analyzes, and processes cosmetic product information and image data.

[1601] "Facial image data" refers to photographic data of a user's own face uploaded by the user.

[1602] "Image generation algorithm" refers to a program that combines image data of a user's face with information about the cosmetic product to generate an image of the user's face after using the cosmetic product.

[1603] "Terminal" refers to the device used by a user to access the system, enter information, confirm information, and complete purchase procedures. This includes smartphones, tablets, and PCs.

[1604] An "emotion engine" refers to software or hardware that analyzes emotions from a user's facial expressions and voice and feeds that data back into the system.

[1605] "Emotion data" refers to the numerical values ​​and category information resulting from the analysis by the emotion engine, and indicates the user's level of satisfaction, favorability, etc.

[1606] "Recommendation information" refers to related product suggestions provided to users by the system based on the user's basic information, cosmetic information, and emotional data.

[1607] "Purchase procedure" refers to the series of processes in which a user adds the selected product to the cart, makes payment, enters the delivery address, and finally confirms the purchase.

[1608] This invention is a virtual store system that visualizes the effects of using cosmetics selected by a user in advance and further recognizes the user's emotions to improve the cosmetics selection and purchasing experience. Specific embodiments for implementing this system are described below.

[1609] First, a user accesses the virtual store's application using a device (smartphone, tablet, PC, etc.) and logs in. After logging in, the user enters basic information, such as skin type, skin color, and age, and sends it to a data processing device (server). The server receives this information and performs user authentication.

[1610] Next, the user selects a cosmetics category (e.g., skin care, lip care, etc.), and a list of cosmetics according to the selected category is displayed on the terminal. When the user selects a cosmetic product that interests them, information about that cosmetic product is sent to the server.

[1611] The server requests the user to upload facial image data, and the user uploads the facial image via the terminal. The server uses an image generation algorithm (e.g., an AI model) to combine the uploaded facial image data with the selected cosmetic product information to generate an image of the user's face after using the cosmetic product. This generated image is then sent back to the terminal and displayed to the user.

[1612] The emotion engine then captures the user's facial expressions and voice and analyzes the user's emotional data. The analyzed emotional data is sent to the server, which then adjusts the generated facial image and recommendation information. The adjusted facial image and related cosmetic information are then displayed again on the device and presented to the user.

[1613] The system also has the function of recommending related cosmetics selected by the user. Based on the cosmetics that the user showed interest in and the analyzed emotional data, the server suggests other related products. The user can add these suggested cosmetics to their cart and proceed with the purchase process step by step.

[1614] The system's program is implemented primarily using the following hardware and software: a server as a data processing device, a terminal for user input and display, an AI model that executes the image generation algorithm, and an emotion engine that analyzes user emotions. Specifically, this includes the programming language Python, image processing with OpenCV, execution of AI models with TensorFlow and PyTorch, and emotion analysis with EmotionRecognition.

[1615] As a specific example, if a user wants to try a lip balm, they can send their facial image and lip balm information to the server, and the AI ​​model will generate an image of their face after using the lip balm. If the user is satisfied with this image, the next related product (e.g., a face cream or moisturizing lotion from the same brand) will be suggested based on the emotional data.

[1616] An example of a prompt might be, "If a user tries a lip balm, list what other related products would be recommended based on their facial image and emotion data."

[1617] In this way, the present invention allows users to visually confirm the effects of cosmetics in advance, and also provides a more accurate selection of cosmetics based on the user's emotions and a more satisfying purchasing experience.

[1618] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1619] Step 1:

[1620] A user accesses the virtual store's application using a terminal and logs in. They enter their email address and password on the login screen and send them to the server. The server compares the entered login information with a database to authenticate the user. If authentication is successful, the server obtains the user's basic information (e.g., skin type, skin color, age, etc.) and starts the session.

[1621] Step 2:

[1622] The user uses the terminal to select a cosmetics category (e.g., skin care, lip care, etc.). The selected category information is sent to the server. The server generates a cosmetics list based on the selected category and sends the generated list to the terminal. The terminal displays the received cosmetics list to the user.

[1623] Step 3:

[1624] The user selects a cosmetic product of interest from the cosmetics list. Information about the selected cosmetic product is sent from the terminal to the server. The server receives the information about the selected cosmetic product and then requests the user to upload image data of their face.

[1625] Step 4:

[1626] The user uploads an image of their face to the server via their device. The server then passes the received facial image data and selected cosmetic information to an image generation algorithm. The image generation algorithm combines the uploaded facial image data and cosmetic information to generate a facial image of the user after applying the cosmetic. The generated facial image is then sent to the device by the server.

[1627] Step 5:

[1628] The device displays the generated facial image to the user. At this time, the device captures the user's facial expressions and voice and sends them to the emotion engine. The emotion engine analyzes the user's emotional data and sends the results to the server. The server receives the emotional data and adjusts the generated facial image and recommendation information.

[1629] Step 6:

[1630] The server sends the adjusted facial image to the device, which then displays the adjusted facial image to the user. At the same time, the server recommends related cosmetics based on the user's basic information, emotional data, and cosmetic information, and sends this information to the device. The device then displays information about the recommended cosmetics to the user.

[1631] Step 7:

[1632] The user uses the device to add the recommended cosmetics to their cart. The cosmetics selected by the user are added to the cart, and the user is guided through the purchase process step by step. The server processes the necessary information for the purchase process (e.g., shipping address, payment information, etc.), and the purchase is confirmed.

[1633] This allows users to visually check the effects of cosmetics in advance, and enables them to select cosmetics more accurately based on their emotions and have a more satisfying purchasing experience.

[1634] 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.

[1635] 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.

[1636] 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.

[1637] [Fourth embodiment]

[1638] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1639] 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.

[1640] 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).

[1641] 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.

[1642] 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.

[1643] 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).

[1644] 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.

[1645] 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.

[1646] 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.

[1647] 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.

[1648] 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.

[1649] 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.

[1650] 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."

[1651] The present invention is a system that supports purchasing decisions by visualizing the effects of using cosmetics selected by the user in advance. This system is realized through cooperation between a server, a terminal, and the user. The program processing of this system is explained in detail below.

[1652] Basic processing flow

[1653] User authentication and basic information entry

[1654] A user accesses an e-commerce site and enters their email address and password on the login screen.

[1655] The terminal sends this authentication information to the server.

[1656] The server receives the authentication information and checks it against a database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts a session.

[1657] Selection of cosmetics

[1658] The user selects a cosmetic category, such as skin care or lip care.

[1659] The terminal transmits the selected category information to the server.

[1660] The server generates a list of applicable cosmetics and sends it to the terminal.

[1661] The user selects the cosmetic product of interest from the list.

[1662] The terminal transmits information about the selected cosmetics to the server.

[1663] Upload a face image and generate an image using AI

[1664] The server asks the user to upload a face image.

[1665] The user uploads an image of their face and sends it to the server via their terminal.

[1666] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1667] An image generation algorithm generates an image of the face and returns the result to the server.

[1668] Image display and recommendations

[1669] The server sends the generated facial image to the device.

[1670] The terminal displays the generated facial image to the user.

[1671] The server refers to the user's basic information, recommends related cosmetics, and sends that information to the terminal.

[1672] The device displays information about the recommended cosmetics to the user.

[1673] Purchase procedure

[1674] The user adds the selected or recommended cosmetic product to the cart.

[1675] The terminal guides the user through the purchase process, detailing each step.

[1676] The user follows the purchase procedure and enters and confirms the required information.

[1677] The server receives the final purchase information and processes the order.

[1678] Specific examples

[1679] For example, consider a case where a user is looking for skin care products to combat dryness in winter. The user accesses an e-commerce site and logs in. After successfully logging in, the user selects the skin care category. The server generates a list of skin care cosmetics and displays it to the user via their terminal. The user selects a moisturizing cream that interests them and sends that information to the server.

[1680] Next, the server requests the upload of a facial image, and the user uploads an image of their face. The server then feeds the received facial image and the selected moisturizing cream information into an image generation algorithm to generate an image of the face after using the moisturizing cream. This image is then displayed on the device, allowing the user to visually confirm the effect.

[1681] The server then recommends cosmetics related to the user, such as face wash and lotion from the same brand, and sends this information to the device. The user then refers to these recommendations and considers purchasing them along with the moisturizing cream. They proceed through the purchasing process by following step-by-step instructions, and finally confirm the purchase.

[1682] In this way, the present invention is a system that helps users to easily select cosmetics that are suitable for them and helps them make more reliable purchasing decisions.

[1683] The processing flow will be explained below.

[1684] Step 1:

[1685] A user accesses an e-commerce site and enters their email address and password on the login screen.

[1686] Step 2:

[1687] The terminal sends the entered login information to the server.

[1688] Step 3:

[1689] The server checks the received login information against a database and authenticates the user.

[1690] Step 4:

[1691] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[1692] Step 5:

[1693] The server notifies the user of successful authentication and begins the session.

[1694] Step 6:

[1695] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[1696] Step 7:

[1697] The terminal transmits the selected category information to the server.

[1698] Step 8:

[1699] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[1700] Step 9:

[1701] The terminal displays the generated cosmetics list to the user.

[1702] Step 10:

[1703] The user selects the cosmetic product of interest from the list.

[1704] Step 11:

[1705] The terminal transmits information about the selected cosmetics to the server.

[1706] Step 12:

[1707] The server asks the user to upload an image of their face.

[1708] Step 13:

[1709] The terminal displays the upload form to the user.

[1710] Step 14:

[1711] The user uploads an image of their face and sends it to the server via their terminal.

[1712] Step 15:

[1713] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1714] Step 16:

[1715] An image generation algorithm generates an image of the face after applying the cosmetics based on the received data.

[1716] Step 17:

[1717] The server sends the generated facial image to the device.

[1718] Step 18:

[1719] The terminal displays the generated facial image to the user.

[1720] Step 19:

[1721] The server references the user's basic information and recommends related cosmetics.

[1722] Step 20:

[1723] The device displays information about the recommended cosmetics to the user.

[1724] Step 21:

[1725] The user adds the selected or recommended cosmetic product to the cart.

[1726] Step 22:

[1727] The terminal guides the user through the purchase process, detailing each step.

[1728] Step 23:

[1729] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[1730] Step 24:

[1731] The user makes a final confirmation and confirms the purchase.

[1732] Step 25:

[1733] The server receives the final purchase information and processes the order.

[1734] Step 26:

[1735] The server sends an order confirmation email to the user and proceeds with the delivery process.

[1736] Example 1

[1737] 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."

[1738] In conventional online shopping, it is difficult for users to visually confirm the effects of using the selected product beforehand, which often makes them feel uneasy about making a purchase decision.In addition, there is a problem that the product information and recommendations suitable for the user are not provided sufficiently, making it difficult to find the most suitable product.

[1739] 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.

[1740] In this invention, the server includes a means for transmitting product information selected by the user to the server, a means for transmitting facial image data uploaded by the user to the server, and a means for generating an image of the user's face after using the product using a generative model. This allows the user to visually confirm the effects of using the selected product in advance, enabling optimal purchasing decisions.

[1741] "User" refers to an individual or legal entity that uses the service or system.

[1742] "Product Information" refers to detailed descriptions of product characteristics, price, ingredients, usage, etc.

[1743] "Server" refers to a computer on a network that processes, stores, and transmits data.

[1744] "Facial image data" refers to an image file that digitally records and stores a user's face.

[1745] A "generative model" refers to an algorithm that generates new data based on input data.

[1746] "Terminal" refers to a device (such as a personal computer, smartphone, or tablet) that a user operates.

[1747] "Image" refers to the visual result produced by a generative model.

[1748] "Basic Information" refers to personal information used for personalization, such as the user's skin type, skin color, and age.

[1749] "Recommendation" refers to suggesting related products based on a user's preferences and attributes.

[1750] A "cart" is an online location where a user temporarily stores items they are considering purchasing.

[1751] The "purchase procedure" refers to a series of steps a user goes through to complete an order for a product.

[1752] This invention is a system that supports purchasing decisions by visualizing the effects of using a product selected by the user in advance. This system is realized by the cooperation of three parties: a server, a terminal, and the user.

[1753] First, a user accesses an e-commerce site and enters their email address and password on the login screen. This information is sent from the terminal to the server. The server compares the received authentication information with a database, and if authentication is successful, obtains the user's basic information. The basic information includes the user's skin type, skin color, age, etc., and the server starts a session based on this information. The session start information and the user's basic information are sent to the terminal, which displays it on the user's screen.

[1754] Next, the user selects a cosmetics category (e.g., skin care, lip care) on the device screen. The device sends the selected category information to the server. The server retrieves a list of cosmetics in that category from the database and sends it to the device. When the user selects a cosmetic product that interests them from the list, that information is sent from the device to the server.

[1755] The server then displays a screen on the device requesting the user to upload a facial image. The user uploads their facial image, which is then sent from the device to the server. The server then provides the received facial image data and the selected cosmetic information as a prompt to the image generation AI model (e.g., DALL-E). An example of a prompt is, "Use the facial image and the selected cosmetic information to generate an image of the face after using the cosmetics."

[1756] The image generation AI model generates an image of the user's face after use based on the input data and returns the result to the server, which then sends the generated image of the face to the device, which then displays it on the user's screen.

[1757] Furthermore, the server refers to the user's basic information and recommends related cosmetics (for example, facial cleanser or lotion from the same brand). This information is also sent to the device, which displays it to the user. The user can add the recommended cosmetics to their cart and proceed to the purchase process. The device guides the user through each step of the purchase process in detail and supports them in entering and confirming the necessary information.

[1758] Finally, the server processes the order based on the purchase information received from the user. This process includes generating an order number, checking inventory, and processing payment. The server then sends the final order information to the terminal, and the terminal displays a message to the user that the order has been confirmed.

[1759] This invention allows the user to visually confirm the effects of the selected product, enabling the user to make a more reliable purchasing decision.

[1760] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1761] Step 1: User authentication and basic information entry

[1762] 1. A user enters their email address and password on the login screen of an e-commerce site. The information is sent from the device to the server.

[1763] 2. The server checks the entered authentication information against the database. Input: Authentication information (email address, password). Output: Authentication result (success / failure), basic user information.

[1764] 3. If authentication is successful, the server obtains the user's basic information (e.g., skin type, skin color, age, etc.) and starts a session. The session start information and the user's basic information are sent to the terminal. The terminal receives this information and displays it on the user's screen.

[1765] Step 2: Choose your cosmetics

[1766] 1. The user selects a cosmetics category (e.g., skin care or lip care) from a list of categories provided. The selection information is sent from the terminal to the server.

[1767] 2. The server retrieves the relevant cosmetics list from the database based on the selected category information. Input: Category information. Output: Cosmetics list.

[1768] 3. The server sends the cosmetics list to the terminal, and the terminal displays the list to the user.

[1769] 4. The user selects the cosmetics they are interested in from the list, and the selection information is sent from the terminal to the server.

[1770] Step 3: Upload a face image and generate an image using AI

[1771] 1. The server instructs the device to display a screen requesting the user to upload a facial image. The device displays the screen according to the instructions.

[1772] 2. The user uploads a picture of their face via the device screen, and the image data is sent from the device to the server.

[1773] 3. The server receives the facial image data and the selected cosmetic information and provides it as a prompt to the image generation AI model (e.g., DALL-E). Input: Facial image data, selected cosmetic information. Output: Generated facial image.

[1774] An example prompt is, "Use the image of your face and the selected cosmetic product information to generate an image of your face after using the product."

[1775] 4. The image generation AI model generates an image of the user's face based on the provided data and returns the result to the server.

[1776] 5. The server sends the generated facial image data to the device, which displays the received image on the user's screen.

[1777] Step 4: View and recommend images

[1778] 1. The device displays the generated face image received from the server to the user.

[1779] 2. The user reviews the generated facial image.

[1780] 3. The server references the user's basic information, retrieves related cosmetics (such as face wash and lotion from the same brand) from the database, and generates a list. Input: User's basic information. Output: List of related products.

[1781] 4. The server sends the relevant cosmetic list to the terminal, which displays the list to the user.

[1782] Step 5: Checkout

[1783] 1. The user adds selected or recommended cosmetics to the cart. This information is sent from the device to the server.

[1784] 2. The device will display your cart and provide detailed steps to begin the checkout process.

[1785] 3. The user enters and confirms the information required for the purchase (shipping address, payment method, etc.). This information is sent from the terminal to the server. Input: Purchase information. Output: Order confirmation.

[1786] 4. The server processes the order based on the received purchase information. Order processing includes generating an order number, checking inventory, and processing payments. Output: Final order information.

[1787] 5. The server sends the final order information to the terminal, and the terminal displays a final confirmation screen to the user. The user confirms the order and the purchase process is complete.

[1788] (Application example 1)

[1789] 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."

[1790] With conventional e-commerce sites and virtual stores, it was difficult for users to visualize the effects of using the cosmetics they selected in advance, which led to the issue of taking a long time to make a purchasing decision. In addition, because users could not actually try the cosmetics, it was difficult to confirm whether the product was truly suitable for them. This led to a situation where users were not satisfied with their ideal cosmetics selection.

[1791] 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.

[1792] In this invention, the server includes means for transmitting information about cosmetics selected by the user to the server, means for transmitting facial image data uploaded by the user to the server, means for receiving the cosmetic information and facial image data in the server and generating an image of the user's face after using the cosmetics using an image generation algorithm, means for transmitting the generated facial image to the terminal, means for displaying the generated facial image and related cosmetic information to the user, means for displaying the generated facial image to the user in real time via a smart device, and means for the user to try on cosmetics in a virtual store using prompts generated using an artificial intelligence model. This allows the user to visually check the effects of the cosmetics after applying them directly to their face in real time, making it easy to select cosmetics that suit them.

[1793] "User authentication" is the process of verifying a user's identity and granting them access to a system.

[1794] "Basic information" refers to information about the user's personal attributes (skin type, skin color, age, etc.).

[1795] "Smart devices" refers to portable electronic devices with advanced computing capabilities such as smartphones, tablets, smart glasses, and head-mounted displays.

[1796] "Cosmetics" is a general term that refers to products used to protect, moisturize, and beautify the face and skin, such as skin care and lip care.

[1797] An "image generation algorithm" is a set of calculations and processing techniques that take image data of a user's face as input and generate a specific effect (in this case, the appearance after applying cosmetics).

[1798] A "prompt sentence" refers to an instruction or input sentence that uses an image generation AI model to generate the image the user wants to see.

[1799] A "virtual store" is a virtual store that operates on the Internet and is a platform where users can browse, try out, and purchase products online.

[1800] "Real-time" refers to a state in which data processing and display are carried out immediately, with almost no time delay.

[1801] "Recommendation" refers to suggesting products suitable for a user based on the user's past behavior and basic information.

[1802] "Facial image" refers to the visual output image that results from applying a cosmetic effect to an image of a user's face.

[1803] The "purchase procedure" refers to a series of steps or processes for actually purchasing the product selected by the user.

[1804] "Terminal" refers to an electronic device (e.g., smartphone, PC, etc.) that a user uses to access the system and send and receive data.

[1805] "Artificial intelligence model" refers to machine learning and deep learning techniques used to analyze and generate data and perform specific tasks.

[1806] A "user session" refers to the sequence of activities that occur between the time a user logs in to the time they log out of the system.

[1807] The present invention is a system that supports purchase decision-making by visualizing the effects of using cosmetics selected by a user in advance. This system is realized through cooperation between a server, a terminal, and a user. The following describes in detail the mode for carrying out the present invention.

[1808] User authentication and basic information entry

[1809] The process begins when a user accesses the virtual store application using a device such as a smartphone and logs in. The user enters their email address and password on the login screen, and the device sends this authentication information to the server. The server receives the authentication information and compares it with a database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts the session.

[1810] Selection of cosmetics

[1811] The user selects a cosmetics category (e.g., skin care or lip care). The device sends the selected category information to the server, which then generates a list of the corresponding cosmetics and sends it to the device. The user selects the cosmetics they are interested in from the list, and the device sends information about the selected cosmetics to the server.

[1812] Upload a face image and generate an image using AI

[1813] The server requests the user to upload a facial image. The user takes a photo of their face using a smartphone or other device and sends it to the server via their device. The server receives the facial image data and selected cosmetic information and passes it to an image generation algorithm. The generative AI model generates an image of the face and returns the result to the server.

[1814] Image display and recommendations

[1815] The server then sends the generated facial image to the device, which then displays the image to the user. The server then refers to the user's basic information and recommends related cosmetics, sending that information to the device. The device then displays information about the recommended cosmetics to the user.

[1816] Purchase procedure

[1817] The user adds the selected or recommended cosmetics to the cart. The terminal guides the user through the purchase procedure step by step, supporting the user. The user follows the purchase procedure, inputs and confirms the necessary information, and the server receives the final purchase information and processes the order.

[1818] Hardware and software used

[1819] Hardware: smartphones, servers, databases

[1820] Software: authentication systems, image generation algorithms (e.g., DALL-E, MidJourney), virtual store applications

[1821] Prompt Sentence Examples

[1822] Specific examples of prompts include:

[1823] User "john.doe@example.com" selected "Rose Red Lip Gloss" from the Lip Care category. Upload a face image and view the AI-generated image of the product after application.

[1824] In this way, the present invention is a system that helps users to easily select cosmetics that are suitable for them and helps them make more reliable purchasing decisions.

[1825] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1826] Step 1:

[1827] A user accesses the virtual store application using a smartphone and enters their email address and password on the login screen. The device sends this authentication information to the server. The server receives this authentication information and compares it with the information stored in the database. If authentication is successful, the server obtains the user's basic information (skin type, skin color, age, etc.) and starts the session.

[1828] Input: Email address, password

[1829] Output: Authentication result, user basic information, session ID

[1830] Step 2:

[1831] The user selects a cosmetics category within the application (e.g., skin care, lip care, etc.). The device sends the selected category information to the server. The server retrieves a corresponding cosmetics list from the database based on the selected category and sends it to the device. The user selects cosmetics that interest them from this list, and the device sends that information to the server.

[1832] Input: Category selection information

[1833] Output: Cosmetics list, selected cosmetics information

[1834] Step 3:

[1835] The server requests the user to upload a facial image. The user takes a photo of their face with their smartphone and sends the image to the server via their device. The server receives this facial image data and selected cosmetic information and passes it to an image generation algorithm. The generative AI model generates an image of the face and returns the generated result to the server.

[1836] Input: Facial image, selected cosmetic information

[1837] Output: Generated face image

[1838] Step 4:

[1839] The server then sends the generated facial image to the device, which displays the image to the user in real time.The server then recommends related cosmetics based on the user's basic information and sends that information to the device.The device then displays information about the recommended cosmetics to the user.

[1840] Input: Generated face image, basic user information

[1841] Output: Facial image display, recommended cosmetics list

[1842] Step 5:

[1843] The user adds the selected or recommended cosmetics to the cart. The terminal guides the user through the purchase procedure step by step, supporting the user. Once the user follows the purchase procedure and enters and confirms the necessary information, the server receives the final purchase information and processes the order.

[1844] Input: Cosmetics added to cart, purchase information

[1845] Output: Order confirmation, purchase completion notification

[1846] Through the above processing steps, the user can visually check the cosmetics that suit him / her in real time and make a purchasing decision.

[1847] 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.

[1848] The present invention provides a system that visualizes the effects of using cosmetics selected by the user in advance and supports purchasing decisions, and by combining it with an emotion engine that recognizes the user's emotions, it provides a more suitable cosmetics selection and purchasing experience for the user. The specific processing of the program of this system is described in detail below.

[1849] Basic processing flow

[1850] User authentication and basic information entry

[1851] A user accesses an e-commerce site and enters their email address and password on the login screen.

[1852] The terminal sends this authentication information to the server.

[1853] The server checks the received login information against a database and authenticates the user.

[1854] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[1855] The server notifies the user of successful authentication and begins the session.

[1856] Selection of cosmetics

[1857] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[1858] The terminal transmits the selected category information to the server.

[1859] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[1860] The terminal displays the generated cosmetics list to the user.

[1861] The user selects the cosmetic product of interest from the list.

[1862] The terminal transmits information about the selected cosmetics to the server.

[1863] Upload a face image and generate an image using AI

[1864] The server asks the user to upload a face image.

[1865] The terminal displays the upload form to the user.

[1866] The user uploads an image of their face and sends it to the server via their terminal.

[1867] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1868] An image generation algorithm generates an image of the face and returns the result to the server.

[1869] Running and tuning the emotion engine

[1870] The device captures the user's facial expressions and voice and sends them to the emotion engine.

[1871] The emotion engine analyzes the user's emotion data and sends the results to the server.

[1872] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[1873] The server sends the adjusted facial image to the device.

[1874] Image display and recommendations

[1875] The device displays the adjusted image of the face to the user.

[1876] The server references the user's emotional data and basic information and recommends related cosmetics.

[1877] The device displays information about the recommended cosmetics to the user.

[1878] Purchase procedure

[1879] The user adds the selected or recommended cosmetic product to the cart.

[1880] The terminal guides the user through the purchase process, detailing each step.

[1881] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[1882] The user makes a final confirmation and confirms the purchase.

[1883] The server receives the final purchase information and processes the order.

[1884] Specific examples

[1885] For example, consider a case where a user is looking for a lip balm to combat dry lips. The user accesses an e-commerce site and logs in. After successfully logging in, the user selects the lip care category. The server generates a list of lip care cosmetics and displays it to the user via their terminal. The user selects the lip balm that interests them and sends the information to the server.

[1886] The server then requests a facial image upload, and the user uploads their own facial image. The server then feeds the received facial image and the selected lip balm information into an image generation algorithm to generate an image of the face after using the lip balm. This image is then displayed on the device.

[1887] The emotion engine captures the user's facial expressions and voice and analyzes how satisfied the user is with the image. Based on the emotion engine's analysis, the server adjusts the generated facial image to better match the user's emotions. It also recommends related cosmetics (e.g., other lip care products or moisturizing creams from the same brand) based on the user's satisfaction.

[1888] The user references the adjusted image and recommendations and adds the lip balm and related products to their cart. They then follow the instructions on the device to complete the purchase and finally confirm the purchase. In this way, the present invention is a system that takes user emotions into consideration to provide a more appropriate cosmetics selection and purchasing experience.

[1889] The processing flow will be explained below.

[1890] Step 1:

[1891] A user accesses an e-commerce site and enters their email address and password on the login screen.

[1892] Step 2:

[1893] The terminal sends the entered login information to the server.

[1894] Step 3:

[1895] The server checks the received login information against a database and authenticates the user.

[1896] Step 4:

[1897] If the server is successful in authentication, it obtains the user's basic information (skin type, skin color, age, etc.).

[1898] Step 5:

[1899] The server notifies the user of successful authentication and begins the session.

[1900] Step 6:

[1901] The user selects a cosmetic category (e.g., skin care, lip care, etc.).

[1902] Step 7:

[1903] The terminal transmits the selected category information to the server.

[1904] Step 8:

[1905] The server generates a list of cosmetics according to the selected category and transmits it to the terminal.

[1906] Step 9:

[1907] The terminal displays the generated cosmetics list to the user.

[1908] Step 10:

[1909] The user selects the cosmetic product of interest from the list.

[1910] Step 11:

[1911] The terminal transmits information about the selected cosmetics to the server.

[1912] Step 12:

[1913] The server asks the user to upload an image of their face.

[1914] Step 13:

[1915] The terminal displays the upload form to the user.

[1916] Step 14:

[1917] The user uploads an image of their face and sends it to the server via their terminal.

[1918] Step 15:

[1919] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[1920] Step 16:

[1921] An image generation algorithm generates an image of the face after applying the cosmetics based on the received data.

[1922] Step 17:

[1923] The server sends the generated facial image to the device.

[1924] Step 18:

[1925] The terminal displays the generated facial image to the user.

[1926] Step 19:

[1927] The device captures the user's facial expressions and voice and sends them to the emotion engine.

[1928] Step 20:

[1929] The emotion engine analyzes the user's emotion data and sends the results to the server.

[1930] Step 21:

[1931] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[1932] Step 22:

[1933] The server sends the adjusted facial image to the device.

[1934] Step 23:

[1935] The device displays the adjusted image of the face to the user.

[1936] Step 24:

[1937] The server references the user's emotional data and basic information and recommends related cosmetics.

[1938] Step 25:

[1939] The device displays information about the recommended cosmetics to the user.

[1940] Step 26:

[1941] The user adds the selected or recommended cosmetic product to the cart.

[1942] Step 27:

[1943] The terminal guides the user through the purchase process, detailing each step.

[1944] Step 28:

[1945] The user follows the purchase procedure and enters the required information (e.g., shipping address, payment information, etc.).

[1946] Step 29:

[1947] The user makes a final confirmation and confirms the purchase.

[1948] Step 30:

[1949] The server receives the final purchase information and processes the order.

[1950] Step 31:

[1951] The server sends an order confirmation email to the user and proceeds with the delivery process.

[1952] Example 2

[1953] 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."

[1954] In the past, when selecting cosmetics, it was difficult for users to confirm the effects and appearance of the product in advance unless they actually tried it on. Furthermore, there was no system that selected cosmetics taking into account the user's emotions, making it impossible to provide an appropriate selection and purchasing experience. As a result, users were likely to make selections that were unsatisfactory and end up purchasing the wrong product.

[1955] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for transmitting product information selected by the user to the server, means for transmitting image data uploaded by the user to the server, means for receiving the product information and image data in the server and generating an image of the user after using the product using a generation algorithm, means for receiving captured data from the terminal and analyzing the user's emotional data using an emotion analysis engine, and means for displaying the generated image and related product information to the user. This allows the user to check in advance what the product will look like after use, and recommendations based on the emotional data enable a more appropriate product selection and purchasing experience.

[1956] A "user" is an individual who uses the system to select and purchase products.

[1957] A "server" is a central computer system that receives and processes information from users.

[1958] A "terminal" is a device used by a user to input information and display results.

[1959] A "product" is an object that a user selects and considers purchasing in this system.

[1960] "Information" refers collectively to data entered by users, data processed by the server, and data generated by the system.

[1961] A "generation algorithm" is a program that generates images based on the user's image data and product information.

[1962] "Image" is visual data created by a generative algorithm that shows the user's appearance after using the product.

[1963] An "emotion analysis engine" is a technology that analyzes data such as a user's facial expressions and voice to determine their emotional state.

[1964] "Recommendation" is the act of a system suggesting products that it deems appropriate based on the user's information and emotional data.

[1965] The present invention relates to a system that visualizes the image of a product selected by a user after use and supports appropriate product selection through user sentiment analysis. This system is implemented using the following hardware and software.

[1966] Hardware and software used

[1967] 1. Server:

[1968] Database (e.g. MySQL)

[1969] Image generation algorithms (e.g., StyleGAN)

[1970] Sentiment analysis engine (e.g. OpenFace)

[1971] Data protection through SSL / TLS communication

[1972] 2. Terminal:

[1973] User devices such as computers, smartphones, and tablets

[1974] Web browser or dedicated application

[1975] Camera and microphone (for capturing emotional data)

[1976] Details of data processing and calculation

[1977] The server authenticates the user by comparing the authentication information entered by the user with the database. If authentication is successful, the server retrieves the user's basic information (skin type, skin color, age, etc.) from the database.

[1978] When a user selects a product category, the server retrieves information about products in that category and generates a list of products. This list is sent to the terminal and displayed to the user.

[1979] Once a user selects a particular cosmetic product and uploads a facial image, the server passes the image data and product information to an image generation algorithm, which generates an image of the face after using the product.

[1980] The server sends the generated image to the device and displays it to the user. The device also uses a camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion analysis engine.

[1981] The emotion analysis engine analyzes the user's emotional data and sends the results to the server, which then adjusts the generated image based on the emotional data to make it more suitable for the user.

[1982] The server recommends related products based on the user's emotional data and basic information, which are then displayed to the user on the device, who can then add the selected products to their cart.

[1983] Specific examples

[1984] For example, consider a case where a user is looking for a lip balm to combat dry lips. The user accesses an e-commerce site and enters their email address and password on the login screen. After successfully logging in, the user selects the "lip care" category. The server generates a list of applicable products and displays it to the user via their terminal. The user selects a lip balm and sends the information to the server.

[1985] Next, the server requests the user to upload an image of their face, and the user uploads an image of their face. The server passes the image data and product information to an image generation algorithm, which generates an image of the face after using the lip balm. This image is displayed on the device. The device also uses a camera and microphone to capture the user's facial expressions and voice, which are analyzed by an emotion analysis engine. Based on the analysis results, the server adjusts the generated image and recommends related products.

[1986] Prompt Sentence Examples

[1987] An example of a prompt to be input to the generative AI model is as follows:

[1988] "Generate an image of a face after using lip balm based on the following face image and lip balm information."

[1989] Face image file: user_face.jpg

[1990] Lip Balm Info: { "Brand": "BeautyX", "Product": "Moisturizing Lip Balm"}

[1991] By using the specific examples and prompts described above, users can check the image of the product after use in advance and select the appropriate product based on the results of the emotion analysis. This will realize a system that provides higher satisfaction and a more appropriate purchasing experience.

[1992] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1993] Step 1:

[1994] A user accesses an e-commerce site and enters their email address and password.

[1995] Enter your email address and password

[1996] Output: Sending authentication information

[1997] Specific behavior: A user accesses the login screen, enters their email address and password, and clicks the "Login" button.

[1998] Step 2:

[1999] The terminal transmits the entered authentication information to the server.

[2000] Input: The email address and password entered by the user

[2001] Output: Sending authentication information to the server

[2002] Specific operation: The device encrypts the authentication information using SSL / TLS and sends it to the server.

[2003] Step 3:

[2004] The server checks the received authentication information against a database and authenticates the user.

[2005] Input: Authentication information received from the device

[2006] Output: Authentication result (success or failure)

[2007] Specific operation: The server accesses a database (e.g. MySQL) and verifies the authentication information. If authentication is successful, the user ID is obtained.

[2008] Step 4:

[2009] If the server is successful in authentication, it retrieves the user's basic information from the database.

[2010] Input: User ID that was successfully authenticated

[2011] Output: User basic information

[2012] Specific operation: The server retrieves basic information (e.g., skin type, skin color, age, etc.) from the database based on the user ID.

[2013] Step 5:

[2014] The server notifies the user of successful authentication and begins the session.

[2015] Input: Authentication success result and basic user information

[2016] Output: Successful authentication and session information

[2017] Specific operation: The server generates session information and sends it to the terminal along with a notification of successful authentication.

[2018] Step 6:

[2019] The user selects a cosmetic category.

[2020] Input: Cosmetic category (e.g. skin care, lip care)

[2021] Output: Selected category information

[2022] Specific behavior: The user clicks on the desired category from the displayed category list.

[2023] Step 7:

[2024] The terminal transmits the selected category information to the server.

[2025] Input: Category information selected by the user

[2026] Output: Send category information to the server

[2027] Specific operation: The device sends a category selection event to the server.

[2028] Step 8:

[2029] The server generates a list of cosmetics according to the category and transmits it to the terminal.

[2030] Input: Selected category information

[2031] Output: Cosmetics list

[2032] Specific operation: The server retrieves the cosmetics information for the relevant category from the database, and sends it to the terminal in list format.

[2033] Step 9:

[2034] The terminal displays the generated cosmetics list to the user.

[2035] Input: Cosmetics list received from the server

[2036] Output: A list of cosmetics displayed to the user

[2037] Specific operation: The device displays the list in HTML or on a dedicated application screen.

[2038] Step 10:

[2039] The user selects the cosmetic product of interest from the list.

[2040] Input: Cosmetic information selected from the cosmetics list

[2041] Output: Selected cosmetic product information

[2042] Specific Action: The user clicks on a specific cosmetic product from the list.

[2043] Step 11:

[2044] The terminal transmits information about the selected cosmetics to the server.

[2045] Input: Cosmetic information selected by the user

[2046] Output: Sending cosmetic information to the server

[2047] Specific operation: The device sends a cosmetics selection event to the server.

[2048] Step 12:

[2049] The server requests the user to upload a facial image.

[2050] Input: Selected cosmetic information

[2051] Output: Face image upload request

[2052] Specific operation: The server generates an upload form and displays it to the user via the terminal.

[2053] Step 13:

[2054] The terminal displays the upload form to the user.

[2055] Input: Upload request received from the server

[2056] Output: The upload form that is displayed to the user

[2057] Specific behavior: The device displays an upload form.

[2058] Step 14:

[2059] The user uploads an image of their face and sends it to the server via their terminal.

[2060] Input: User's face image data

[2061] Output: Sending face image data to the server

[2062] Specific operation: The user selects their own face image and clicks the upload button. The device sends the image data to the server.

[2063] Step 15:

[2064] The server passes the facial image data and selected cosmetic information to an image generation algorithm.

[2065] Input: User's facial image data and selected cosmetics information

[2066] Output: Generated face image

[2067] Specific operation: The server provides image data and cosmetic information to a generative AI model (e.g., StyleGAN) and generates a prompt. The generative AI model processes the data and generates an image.

[2068] Step 16:

[2069] An image generation algorithm generates an image of the face and returns the result to the server.

[2070] Input: Facial image data and cosmetic information received from the server

[2071] Output: Generated face image

[2072] What it does: The image generation algorithm processes and generates an image of the face after applying the cosmetics, which is then sent back to the server.

[2073] Step 17:

[2074] The device captures the user's facial expressions and voice and sends them to an emotion analysis engine.

[2075] Input: User facial and voice data

[2076] Output: Sending data to a sentiment analysis engine

[2077] What it does: The device uses the camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion analysis engine.

[2078] Step 18:

[2079] The emotion analysis engine analyzes the user's emotion data and sends the results to the server.

[2080] Input: Facial expression and voice data received from the device

[2081] Output: Parsed emotion data

[2082] Specific operation: The emotion analysis engine analyzes the user's emotional state and sends the results to the server.

[2083] Step 19:

[2084] The server receives the emotion data and adjusts the generated facial image and recommendation information.

[2085] Input: Emotion data received from the sentiment analysis engine

[2086] Output: Adjusted face image and recommendation information

[2087] How it works: The server adjusts the generated facial image based on the emotion data and recommends related products.

[2088] Step 20:

[2089] The server sends the adjusted facial image to the device.

[2090] Input: Aligned face image

[2091] Output: Send face image to device

[2092] Specific operation: The server sends the adjusted face image to the device and displays it to the user.

[2093] Step 21:

[2094] The device displays the adjusted image of the face to the user.

[2095] Input: Adjusted face image received from the server

[2096] Output: A face image shown to the user

[2097] Specific operation: The device displays the adjusted image of the face on the application screen.

[2098] Step 22:

[2099] The server refers to the user's emotional data and basic information and recommends related products.

[2100] Input: Emotion data and basic user information

[2101] Output: Recommended product information

[2102] Specific operation: The server selects related products based on emotional data and basic information and creates a recommendation list.

[2103] Step 23:

[2104] The terminal displays the recommended product information to the user.

[2105] Input: Recommended product information received from the server

[2106] Output: A list of recommended products displayed to the user

[2107] Specific behavior: The device displays a list of recommended products to the user.

[2108] Step 24:

[2109] The user adds the recommended product to their cart.

[2110] Input: Product selected from recommended product list

[2111] Output: Product information added to cart

[2112] Specific behavior: The user selects a product from the recommended product list and clicks the Add to Cart button.

[2113] Step 25:

[2114] The device will guide you through the purchase process step by step.

[2115] Input: Product information added to cart

[2116] Output: Checkout screen

[2117] What happens: The device generates a checkout screen and guides the user through each step.

[2118] Step 26:

[2119] The user enters the required information, such as shipping address and payment information.

[2120] Input: Shipping address, payment information

[2121] Output: The entered shipping address and payment information

[2122] Specific behavior: The user enters the required information on the checkout screen and clicks the Next button.

[2123] Step 27:

[2124] The user makes a final confirmation and confirms the purchase.

[2125] Input: Final confirmation of purchase details

[2126] Output: Purchase confirmed

[2127] Specific operation: The user confirms the purchase details and clicks the "Confirm Purchase" button.

[2128] Step 28:

[2129] The server receives the final purchase information and processes the order.

[2130] Input: User purchase confirmation information

[2131] Output: Order processing begins

[2132] Specific operation: The server receives the purchase information and processes the order (e.g., checks inventory, processes payment, prepares shipping).

[2133] (Application example 2)

[2134] 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."

[2135] The present invention aims to provide a system that allows users to visually check the effects of cosmetics before purchasing them, and that selects cosmetics and provides a purchasing experience that takes the user's emotions into consideration. Conventional systems have made it difficult for users to accurately imagine the effects of using cosmetics, and have not selected cosmetics that reflect the user's emotions, making it impossible to provide a highly satisfying purchasing experience.

[2136] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for transmitting information about cosmetics selected by the user to the data processing device, means for transmitting facial image data uploaded by the user to the data processing device, means for receiving the cosmetic information and facial image data in the data processing device and generating an image of the user's face after using the cosmetics using an image generation algorithm, means for transmitting the generated facial image to the terminal, means for displaying the generated facial image and information about related cosmetics to the user, means for capturing facial expressions and voice and transmitting them to an emotion engine, means for transmitting emotion data analyzed by the emotion engine to the data processing device, and means for adjusting the generated facial image and recommendation information using the emotion data. This allows the user to visually check the effects of cosmetics in advance, and enables a more accurate selection of cosmetics based on emotions and a more satisfying purchasing experience.

[2137] A "user" is a person who accesses the system, selects cosmetics, and decides to purchase them.

[2138] "Cosmetic information" refers to attribute information related to the cosmetic selected by the user, specifically information such as brand name, product name, ingredients, effects, and price.

[2139] "Data processing device" refers to a computer system that receives, analyzes, and processes cosmetic product information and image data.

[2140] "Facial image data" refers to photographic data of a user's own face uploaded by the user.

[2141] "Image generation algorithm" refers to a program that combines image data of a user's face with information about the cosmetic product to generate an image of the user's face after using the cosmetic product.

[2142] "Terminal" refers to the device used by a user to access the system, enter information, confirm information, and complete purchase procedures. This includes smartphones, tablets, and PCs.

[2143] An "emotion engine" refers to software or hardware that analyzes emotions from a user's facial expressions and voice and feeds that data back into the system.

[2144] "Emotion data" refers to the numerical values ​​and category information resulting from the analysis by the emotion engine, and indicates the user's level of satisfaction, favorability, etc.

[2145] "Recommendation information" refers to related product suggestions provided to users by the system based on the user's basic information, cosmetic information, and emotional data.

[2146] "Purchase procedure" refers to the series of processes in which a user adds the selected product to the cart, makes payment, enters the delivery address, and finally confirms the purchase.

[2147] This invention is a virtual store system that visualizes the effects of using cosmetics selected by a user in advance and further recognizes the user's emotions to improve the cosmetics selection and purchasing experience. Specific embodiments for implementing this system are described below.

[2148] First, a user accesses the virtual store's application using a device (smartphone, tablet, PC, etc.) and logs in. After logging in, the user enters basic information, such as skin type, skin color, and age, and sends it to a data processing device (server). The server receives this information and performs user authentication.

[2149] Next, the user selects a cosmetics category (e.g., skin care, lip care, etc.), and a list of cosmetics according to the selected category is displayed on the terminal. When the user selects a cosmetic product that interests them, information about that cosmetic product is sent to the server.

[2150] The server requests the user to upload facial image data, and the user uploads the facial image via the terminal. The server uses an image generation algorithm (e.g., an AI model) to combine the uploaded facial image data with the selected cosmetic product information to generate an image of the user's face after using the cosmetic product. This generated image is then sent back to the terminal and displayed to the user.

[2151] The emotion engine then captures the user's facial expressions and voice and analyzes the user's emotional data. The analyzed emotional data is sent to the server, which then adjusts the generated facial image and recommendation information. The adjusted facial image and related cosmetic information are then displayed again on the device and presented to the user.

[2152] The system also has the function of recommending related cosmetics selected by the user. Based on the cosmetics that the user showed interest in and the analyzed emotional data, the server suggests other related products. The user can add these suggested cosmetics to their cart and proceed with the purchase process step by step.

[2153] The system's program is implemented primarily using the following hardware and software: a server as a data processing device, a terminal for user input and display, an AI model that executes the image generation algorithm, and an emotion engine that analyzes user emotions. Specifically, this includes the programming language Python, image processing with OpenCV, execution of AI models with TensorFlow and PyTorch, and emotion analysis with EmotionRecognition.

[2154] As a specific example, if a user wants to try a lip balm, they can send their facial image and lip balm information to the server, and the AI ​​model will generate an image of their face after using the lip balm. If the user is satisfied with this image, the next related product (e.g., a face cream or moisturizing lotion from the same brand) will be suggested based on the emotional data.

[2155] An example of a prompt might be, "If a user tries a lip balm, list what other related products would be recommended based on their facial image and emotion data."

[2156] In this way, the present invention allows users to visually confirm the effects of cosmetics in advance, and also provides a more accurate selection of cosmetics based on the user's emotions and a more satisfying purchasing experience.

[2157] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2158] Step 1:

[2159] A user accesses the virtual store's application using a terminal and logs in. They enter their email address and password on the login screen and send them to the server. The server compares the entered login information with a database to authenticate the user. If authentication is successful, the server obtains the user's basic information (e.g., skin type, skin color, age, etc.) and starts the session.

[2160] Step 2:

[2161] The user uses the terminal to select a cosmetics category (e.g., skin care, lip care, etc.). The selected category information is sent to the server. The server generates a cosmetics list based on the selected category and sends the generated list to the terminal. The terminal displays the received cosmetics list to the user.

[2162] Step 3:

[2163] The user selects a cosmetic product of interest from the cosmetics list. Information about the selected cosmetic product is sent from the terminal to the server. The server receives the information about the selected cosmetic product and then requests the user to upload image data of their face.

[2164] Step 4:

[2165] The user uploads an image of their face to the server via their device. The server then passes the received facial image data and selected cosmetic information to an image generation algorithm. The image generation algorithm combines the uploaded facial image data and cosmetic information to generate a facial image of the user after applying the cosmetic. The generated facial image is then sent to the device by the server.

[2166] Step 5:

[2167] The device displays the generated facial image to the user. At this time, the device captures the user's facial expressions and voice and sends them to the emotion engine. The emotion engine analyzes the user's emotional data and sends the results to the server. The server receives the emotional data and adjusts the generated facial image and recommendation information.

[2168] Step 6:

[2169] The server sends the adjusted facial image to the device, which then displays the adjusted facial image to the user. At the same time, the server recommends related cosmetics based on the user's basic information, emotional data, and cosmetic information, and sends this information to the device. The device then displays information about the recommended cosmetics to the user.

[2170] Step 7:

[2171] The user uses the device to add the recommended cosmetics to their cart. The cosmetics selected by the user are added to the cart, and the user is guided through the purchase process step by step. The server processes the necessary information for the purchase process (e.g., shipping address, payment information, etc.), and the purchase is confirmed.

[2172] This allows users to visually check the effects of cosmetics in advance, and enables them to select cosmetics more accurately based on their emotions and have a more satisfying purchasing experience.

[2173] 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.

[2174] 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.

[2175] 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.

[2176] 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.

[2177] 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.

[2178] 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.

[2179] 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).

[2180] 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.

[2181] 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."

[2182] 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.

[2183] 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).

[2184] 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.

[2185] 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.

[2186] 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.

[2187] 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.

[2188] 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.

[2189] 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.

[2190] 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.

[2191] 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.

[2192] 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.

[2193] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same ...

Claims

1. means for transmitting information about cosmetics selected by a user to a server; means for transmitting face image data uploaded by a user to a server; means for receiving, at a server, cosmetic product information and facial image data, and generating an image of the user's face after using the cosmetic product using an image generation algorithm; means for transmitting the generated facial image to a terminal; means for displaying the generated facial image and associated cosmetic information to a user; A system including:

2. The system of claim 1, further comprising means for the server to customize cosmetic information based on basic information of the user and pass the customized information to the image generation algorithm, thereby making the generated facial image more suitable for the user.

3. A means for recommending related cosmetics selected by the user; A way to add recommended cosmetics to your cart and guide you step by step through the purchasing process, The system of claim 1 , comprising:

Images