system

Abstract

An object of a system according to an embodiment is to enable a user to easily find a fashion item or a hairstyle suitable for the user and to smoothly try on or purchase the fashion item or the hairstyle.SOLUTION: A system includes a 3D image capturing unit, an analysis unit, a suggestion unit, a try-on unit, a guide unit, and a transmission unit. The 3D image capturing unit captures a 3D image of a user. The analysis unit analyzes the 3D image captured by the 3D image capturing unit. The proposal unit proposes a fashion item or a hairstyle to the user on the basis of a result analyzed by the analysis unit. The try-on unit tries on the fashion item or the hairstyle proposed by the proposing unit on the 3D image. The guide unit guides the user to an EC site for purchasing the fashion item tried on by the try-on unit. The transmission unit transmits the image of the hairstyle proposed by the proposal unit to the beauty parlor.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] Conventional technology has made it difficult for users to find fashion items and hairstyles that suit them, and the process of trying on and purchasing items can be cumbersome.

[0005] The system according to the embodiment aims to enable users to easily find fashion items and hairstyles that suit them, and smoothly try them on and purchase them. [Means for solving the problem]

[0006] The system according to the embodiment includes a 3D image capture unit, an analysis unit, a suggestion unit, a try-on unit, a guidance unit, and a transmission unit. The 3D image capture unit captures a 3D image of the user. The analysis unit analyzes the 3D image captured by the 3D image capture unit. The suggestion unit suggests fashion items and hairstyles to the user based on the results of the analysis by the analysis unit. The try-on unit tries on the fashion items and hairstyles suggested by the suggestion unit on the 3D image. The guidance unit guides the user to an e-commerce site to purchase the fashion items tried on by the try-on unit. The transmission unit transmits an image of the hairstyle suggested by the suggestion unit to a beauty salon. [Effects of the Invention]

[0007] The system according to the embodiment allows users to easily find fashion items and hairstyles that suit them, and smoothly try them on and purchase them. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The coordination system according to an embodiment of the present invention automatically captures a user's 3D image, analyzes it using a generation AI, suggests fashion items and hairstyles in a conversational format, allows the user to try them on, guides the user to an e-commerce site, and sends an image of the hairstyle to a beauty salon. This allows the coordination system to freely coordinate fashion items and hairstyles using the user's 3D image, allowing the user to actually try them on and check the look. Furthermore, the system allows the user to easily purchase items they like and send an image of the hairstyle to a beauty salon.

[0029] A coordination system according to an embodiment includes a 3D image capture unit, an analysis unit, a suggestion unit, a fitting unit, a guidance unit, and a transmission unit. The 3D image capture unit captures a 3D image of the user. For example, a 3D image can be captured using a smartphone or a dedicated 3D scanner and imported into the system. The 3D image capture unit can also capture 3D images using a stereo camera or LiDAR. The analysis unit analyzes the captured 3D image. For example, a generation AI extracts features such as the user's body type, face shape, and hair length. The analysis unit can also analyze the 3D image using an image processing algorithm or a machine learning model. The suggestion unit suggests fashion items and hairstyles to the user based on the analysis results. For example, the generation AI suggests optimal items and hairstyles through dialogue with the user. The suggestion unit can also make suggestions based on user preferences and trend analysis. The fitting unit allows the user to try on the suggested fashion items and hairstyles on the 3D image. For example, the generation AI applies the suggested items and hairstyles to the 3D image, allowing the user to visually confirm how they will actually look. The fitting unit can also use 3D rendering technology or a virtual fitting system to try on the fashion items. The guidance unit guides the user to an e-commerce site to purchase the fashion items they have tried on. For example, the generation AI may ask the user, "Do you want to purchase this dress?" If the user selects purchase, the corresponding e-commerce site page is displayed. The guidance unit can also guide the user to the e-commerce site by providing a link or using a navigation system. The transmission unit sends an image of the suggested hairstyle to a beauty salon. For example, the generation AI may ask the user, "Do you want to send this hairstyle to a beauty salon?" If the user selects send, the image of the hairstyle is sent to the beauty salon. The transmission unit can also send the image using a communication protocol or data format. As a result, the coordination system according to the embodiment allows the user to freely coordinate fashion items and hairstyles using a 3D image of the user, and actually try them on to confirm the look. Furthermore, the user can easily purchase items they like and send an image of the hairstyle to a beauty salon.For example, if you want to choose a new dress and hairstyle for a special event, the system can help you find the perfect outfit.

[0030] The 3D image capture unit can track a user's movements in real time and automatically indicate the optimal shooting angle. For example, when a user takes a 3D image using a smartphone, the camera of the 3D image capture unit tracks the user's movements in real time and automatically indicates the optimal shooting angle. For example, the camera detects the position of the user's face and instructs the camera to adjust to the optimal angle. Furthermore, when a dedicated 3D scanner is used to scan a user's entire body, the scanner tracks the user's movements in real time and automatically indicates the optimal shooting angle. For example, the scanner detects the position of the user's body and instructs the camera to adjust to the optimal angle. Furthermore, when a drone is used to take a 3D image of a user, the 3D image capture unit tracks the user's movements in real time and automatically indicates the optimal shooting angle. For example, the drone detects the position of the user's face and body and instructs the camera to adjust to the optimal angle. This allows the drone to track the user's movements in real time and automatically indicate the optimal shooting angle, thereby capturing more accurate 3D images.

[0031] The analysis unit can also analyze the texture and color of the user's skin and suggest skin care products. For example, the generation AI analyzes the user's 3D image to detect skin texture and color. For example, it analyzes the level of dryness and uneven skin tone and suggests optimal skin care products based on that. The analysis unit also analyzes the user's 3D image to detect features such as skin tone, blemishes, and wrinkles. For example, it suggests foundation that matches the skin tone, or skin care products that cover blemishes and wrinkles. The generation AI also analyzes the user's skin condition and suggests skin care products according to the season and environment. For example, it suggests products with high moisturizing effects in the dry winter and products that protect against UV rays in the summer. In this way, the analysis unit improves the user's beauty experience by analyzing the user's skin texture and color and suggesting optimal skin care products.

[0032] The 3D image capture unit can capture the entire body from 360 degrees using a drone or a robot. The 3D image capture unit, for example, uses a drone to capture the entire body of the user from 360 degrees. For example, the drone flies around the user and captures 3D images from multiple angles. The 3D image capture unit also uses a robotic arm to capture the entire body of the user from 360 degrees. For example, the robotic arm rotates around the user and captures 3D images from multiple angles. The 3D image capture unit also uses multiple cameras to capture the entire body of the user from 360 degrees. For example, cameras are placed around the user and simultaneously capture 3D images from multiple angles. This allows for capturing more detailed 3D images by capturing the entire body from 360 degrees using a drone or a robot.

[0033] The 3D image capture unit can enable the captured 3D image to be used as an avatar in games or social networking sites. The 3D image capture unit, for example, uses the captured 3D image as an avatar in a game. For example, a user uses their own 3D image as a game character and controls it in the game. The 3D image capture unit also uses the captured 3D image as an avatar on social networking sites. For example, a user uses their own 3D image as a profile picture and displays it on the social networking site. The 3D image capture unit also uses the captured 3D image as an avatar in virtual events. For example, a user uses their own 3D image as a participant in a virtual event and interacts with other participants. This allows the captured 3D image to be used as an avatar in games or social networking sites, thereby enhancing the user's experience.

[0034] The suggestion unit can learn the user's past purchase history and preferences and make more personalized suggestions. For example, the generation AI of the suggestion unit analyzes the user's past purchase history and suggests fashion items based on the user's preferences. For example, it suggests new items in a style similar to items previously purchased. The suggestion unit also learns the user's preferences and makes personalized suggestions. For example, it suggests the most suitable fashion items based on the user's preferred colors and designs. The suggestion unit also learns the user's past purchase history and preferences and makes suggestions according to the season or event. For example, it suggests items made of cool materials in the summer and items made of warm materials in the winter. In this way, the suggestion unit learns the user's past purchase history and preferences and makes more personalized suggestions, thereby improving user satisfaction.

[0035] The suggestion unit can make conversational suggestions not only via text but also via voice or video call. In the suggestion unit, for example, the generation AI interacts with the user via voice call to suggest fashion items and hairstyles. For example, when the user expresses their preferences via voice, the generation AI makes suggestions via voice. The suggestion unit also interacts with the user via video call to suggest fashion items and hairstyles. For example, when the user expresses their preferences via video call, the generation AI makes suggestions via video call. The suggestion unit can also receive suggestions while interacting with the generation AI by selecting text, voice, or video call. For example, when the user expresses their preferences via text, the generation AI makes suggestions via voice or video call. This allows conversational suggestions to be made not only via text but also via voice or video call, improving user convenience.

[0036] The suggestion unit can consider the user's lifestyle and event schedule to suggest the best outfit for a specific scene. For example, the generation AI analyzes the user's lifestyle and suggests fashion items that are best suited to everyday life. For example, it suggests items that match work or hobbies. The suggestion unit also considers the user's event schedule to suggest the best outfit for a specific scene. For example, it suggests items that are best suited to a wedding or party. The suggestion unit also learns the user's lifestyle and event schedule through the generation AI to suggest outfits that suit the season and weather. For example, it suggests items that are best suited to a summer beach party. In this way, by considering the user's lifestyle and event schedule to suggest the best outfit for a specific scene, user satisfaction is improved.

[0037] The fitting unit can simulate different lighting conditions and backgrounds to recreate actual usage scenarios. For example, the generation AI in the fitting unit simulates different lighting conditions to recreate how an item tried on by a user would look in an actual usage scenario. For example, it simulates natural daylight and artificial nightlight. The fitting unit also simulates different backgrounds to recreate how an item tried on by a user would look in an actual usage scenario. For example, it simulates backgrounds such as an office or a party venue. The fitting unit also simulates a combination of lighting conditions and backgrounds to recreate how an item tried on by a user would look in various scenarios. For example, it simulates an office in the daytime or a party venue at night. By simulating different lighting conditions and backgrounds and recreating actual usage scenarios, the fitting unit can more accurately check how the item will look when tried on by a user.

[0038] The fitting unit can simulate the movement and texture of the item being tried on in real time, allowing the user to check how it looks when moving. For example, the fitting unit can simulate the movement of the item being tried on by a generation AI in real time, allowing the user to check how it looks when moving. For example, it can simulate the movement of clothes when walking or sitting. The fitting unit can also simulate the texture of the item being tried on in real time, allowing the user to visually check how it feels when touched. For example, it can simulate the texture of different materials such as silk and denim. The fitting unit can also simulate a combination of movement and texture, allowing the user to check how the item being tried on looks with various movements and environments. For example, it can simulate the movement and texture of clothes when running or jumping. This allows the movement and texture of the item being tried on to be simulated in real time, allowing the user to check how it looks when moving, allowing the user to more accurately understand how the item actually feels when being tried on.

[0039] The fitting unit allows users to share items they have tried on with friends and family via social media or messaging apps and receive feedback. The fitting unit, for example, provides a function that allows users to share items they have tried on via social media and receive feedback from friends and family. For example, users can post images of items they have tried on to social media and receive comments and likes. The fitting unit also provides a function that allows users to share items they have tried on with friends and family via messaging apps and receive feedback. For example, users can send images of items they have tried on via messages and exchange opinions in real time. The fitting unit also provides a dedicated platform for sharing items they have tried on and aggregates feedback from friends and family. For example, users can upload images of items they have tried on to a dedicated platform and centrally manage feedback. This allows users to share items they have tried on with friends and family via social media or messaging apps and receive feedback, helping them make better choices.

[0040] The fitting unit allows a user to share items that have been tried on with other users in a virtual fashion show and receive their ratings. The fitting unit, for example, provides a function that allows a user to share items that have been tried on with other users in a virtual fashion show and receive their ratings. For example, the user can show off the items that have been tried on on a virtual runway and receive ratings from other users. The fitting unit also provides a function that allows a user to share items that have been tried on in a virtual fashion show with other users and receive their ratings in real time. For example, the user can show off the items that have been tried on through live streaming and receive comments and ratings in real time. The fitting unit also provides a function that allows a user to share items that have been tried on with other users in a virtual fashion show contest and compete for ratings. For example, the user can enter the items that have been tried on in a contest and compete for ratings through votes from other users. This helps a user make better choices by sharing the items that have been tried on with other users in a virtual fashion show and receiving their ratings.

[0041] The guidance unit can analyze item reviews and ratings before purchase and suggest the best option to the user. In the guidance unit, for example, the generation AI analyzes item reviews and ratings and suggests the best option to the user. For example, it may prioritize suggesting highly rated items. The guidance unit also analyzes reviews and ratings based on the user's preferences and needs and suggests the best item. For example, it may suggest items with the functions and features the user desires. The guidance unit also analyzes item reviews and ratings and provides feedback to suggest the best option to the user. For example, it may suggest items that meet the conditions the user desires. In this way, the generation AI analyzes item reviews and ratings before purchase and suggests the best option to the user, helping the user make better choices.

[0042] The guidance unit can provide a more realistic experience by allowing the user to try on purchased items in a virtual reality (VR) environment. For example, the user tries on the purchased items using a VR headset. The guidance unit also tries on the purchased items in the VR environment to simulate actual usage scenarios. For example, the user can check how the items look when walking or sitting in the VR environment. The guidance unit also provides a function for trying on purchased items in the VR environment and sharing them with friends and family. For example, the user can check the items they have tried on in the VR environment together with their friends and family. This allows the user to try on purchased items in a virtual reality (VR) environment, providing a more realistic experience and improving user satisfaction.

[0043] The guidance unit can provide advice on how to care for and style an item after purchase. For example, the generation AI provides advice on how to care for an item after purchase. For example, it provides advice on how to wash and store the item. The guidance unit also provides styling advice for the item after purchase. For example, it suggests other items and accessories that go well with the purchased item. The guidance unit also provides a dedicated app that allows the generation AI to provide advice on how to care for and style an item after purchase. For example, the user receives care and styling advice through the app. This improves user satisfaction by providing advice on how to care for and style an item after purchase.

[0044] The transmission unit can analyze the user's hair type and scalp condition and recommend optimal hair care products. For example, the generation AI in the transmission unit analyzes the user's hair type and recommends optimal hair care products. For example, it analyzes the dryness and degree of damage of the hair and recommends shampoos and treatments with high moisturizing effects based on that. The transmission unit also analyzes the user's scalp condition and recommends optimal hair care products. For example, it analyzes the oil content and dandruff state of the scalp and recommends shampoos and lotions for scalp care based on that. The generation AI in the transmission unit also analyzes the user's hair type and scalp condition and recommends hair care products according to the season and environment. For example, it recommends products with high moisturizing effects in the dry winter and products with UV protection in the summer. In this way, by analyzing the user's hair type and scalp condition and recommending optimal hair care products, user satisfaction is improved.

[0045] The transmission unit supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed. For example, the generation AI in the transmission unit analyzes the user's wishes and provides specific instructions to the hairdresser. For example, it communicates details of the hairstyle the user desires to the hairdresser. In addition, the generation AI in the transmission unit supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed. For example, it communicates the characteristics of the hairstyle the user desires and styling methods to the hairdresser. In addition, the generation AI in the transmission unit analyzes the user's wishes and provides specific advice to the hairdresser. For example, it communicates suggestions for cuts and colors that suit the hairstyle the user desires to the hairdresser. This supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed, making consultations at the hair salon smoother.

[0046] The transmission unit can support counseling at a beauty salon by using an image of a hairstyle to try on the hairstyle in real time using AR (augmented reality) technology. The transmission unit, for example, uses AR technology to try on a hairstyle that the user desires in real time, thereby supporting counseling at a beauty salon. For example, the user uses a smartphone to check the desired hairstyle in real time. The transmission unit also uses AR technology to try on the hairstyle that the user desires in real time during counseling at a beauty salon. For example, a hairdresser uses a tablet to simulate the user's hairstyle in real time. The transmission unit also provides a dedicated app that uses AR technology to try on the hairstyle that the user desires in real time and support counseling at a beauty salon. For example, the user checks the desired hairstyle through the app in real time. This allows the user to try on the hairstyle image in real time using AR (augmented reality) technology to support counseling at a beauty salon, thereby improving user satisfaction.

[0047] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0048] The suggestion unit can suggest fashion items that are optimal for specific occasions based on the user's lifestyle. For example, it can suggest items that match work or hobbies. The suggestion unit can also consider the user's event schedule and suggest coordination that is optimal for specific occasions. For example, it can suggest items that are optimal for weddings or parties. The suggestion unit can also suggest coordination that is optimal for the season or weather. For example, it can suggest items that are optimal for a summer beach party. In this way, it is possible to improve user satisfaction by considering the user's lifestyle and event schedule and suggesting coordination that is optimal for specific occasions.

[0049] The fitting unit can simulate different lighting conditions and backgrounds to recreate actual usage scenes. For example, it can simulate natural daylight and artificial nightlight. The fitting unit can also simulate backgrounds such as an office or a party venue. For example, it can simulate an office in the daytime or a party venue at night. The fitting unit can also simulate a combination of lighting conditions and backgrounds to recreate how an item tried on by a user looks in various scenes. This allows the user to more accurately check how the item will look when tried on by simulating different lighting conditions and backgrounds to recreate actual usage scenes.

[0050] The fitting unit can simulate the movement and texture of the item being tried on in real time, allowing the user to check how it looks when moving. For example, it can simulate the movement of the clothes when walking or sitting. The fitting unit can also simulate the texture of different materials, such as silk or denim, in real time, allowing the user to visually check how it feels when touched. The fitting unit can also simulate a combination of movement and texture, allowing the user to check how the item being tried on looks with various movements and in various environments. In this way, by simulating the movement and texture of the item being tried on in real time and checking how it looks when moving, the user can more accurately understand how the item actually feels when being tried on.

[0051] The transmission unit can use AR (augmented reality) technology to try on hairstyle images in real time, supporting counseling at a beauty salon. For example, a user uses a smartphone to check their desired hairstyle in real time. The transmission unit can also use AR technology to try on the user's desired hairstyle in real time during counseling at a beauty salon. For example, a hairdresser uses a tablet to simulate the user's hairstyle in real time. The transmission unit can also use AR technology to provide a dedicated app to support counseling at a beauty salon by allowing the user to try on the user's desired hairstyle in real time. This allows the user to try on hairstyle images in real time using AR (augmented reality) technology to support counseling at a beauty salon, thereby improving user satisfaction.

[0052] The transmission unit supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed. For example, the generation AI analyzes the user's wishes and provides specific instructions to the hairdresser. The transmission unit also supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed. For example, the generation AI communicates the characteristics of the hairstyle the user wants to have and the styling method to the hairdresser. The transmission unit also analyzes the user's wishes and provides specific advice to the hairdresser. This allows the dialogue with the hairdresser when sending an image of the hairstyle to be supported, allowing the user's wishes to be accurately conveyed, making counseling at the hair salon smoother.

[0053] The processing flow of the first embodiment will be briefly explained below.

[0054] Step 1: The 3D image capture unit captures a 3D image of the user. For example, a 3D image can be taken using a smartphone or a dedicated 3D scanner and imported into the system. The 3D image capture unit can also capture 3D images using a stereo camera or LiDAR. Step 2: The analysis unit analyzes the captured 3D image. For example, the generative AI extracts features such as the user's body type, face shape, and hair length. The analysis unit can also analyze the 3D image using image processing algorithms and machine learning models. Step 3: The suggestion unit suggests fashion items and hairstyles to the user based on the analyzed results. For example, the generation AI suggests optimal items and hairstyles through dialogue with the user. The suggestion unit can also make suggestions based on the user's preferences and trend analysis. Step 4: The fitting section tries on the suggested fashion items and hairstyles on the 3D image. For example, the generative AI applies the suggested items and hairstyles to the 3D image, allowing the user to visually confirm how they will actually look. The fitting section can also use 3D rendering technology or a virtual fitting system to try on the items. Step 5: The navigation unit guides the user to an e-commerce site to purchase the fashion item they tried on. For example, the generation AI asks the user, "Do you want to buy this dress?" If the user selects purchase, the corresponding e-commerce site page is displayed. The navigation unit can also guide the user to the e-commerce site by providing a link or using a navigation system. Step 6: The transmission unit sends an image of the proposed hairstyle to the hair salon. For example, the generation AI asks the user, "Do you want to send this hairstyle to the hair salon?" If the user selects "send," the image of the hairstyle is sent to the hair salon. The transmission unit can also send the image using a communication protocol or data format.

[0055] (Example 2) The coordination system according to an embodiment of the present invention automatically captures a user's 3D image, analyzes it using a generation AI, suggests fashion items and hairstyles in a conversational format, allows the user to try them on, guides the user to an e-commerce site, and sends an image of the hairstyle to a beauty salon. This allows the coordination system to freely coordinate fashion items and hairstyles using the user's 3D image, allowing the user to actually try them on and check the look. Furthermore, the system allows the user to easily purchase items they like and send an image of the hairstyle to a beauty salon.

[0056] A coordination system according to an embodiment includes a 3D image capture unit, an analysis unit, a suggestion unit, a fitting unit, a guidance unit, and a transmission unit. The 3D image capture unit captures a 3D image of the user. For example, a 3D image can be captured using a smartphone or a dedicated 3D scanner and imported into the system. The 3D image capture unit can also capture 3D images using a stereo camera or LiDAR. The analysis unit analyzes the captured 3D image. For example, a generation AI extracts features such as the user's body type, face shape, and hair length. The analysis unit can also analyze the 3D image using an image processing algorithm or a machine learning model. The suggestion unit suggests fashion items and hairstyles to the user based on the analysis results. For example, the generation AI suggests optimal items and hairstyles through dialogue with the user. The suggestion unit can also make suggestions based on user preferences and trend analysis. The fitting unit allows the user to try on the suggested fashion items and hairstyles on the 3D image. For example, the generation AI applies the suggested items and hairstyles to the 3D image, allowing the user to visually confirm how they will actually look. The fitting unit can also use 3D rendering technology or a virtual fitting system to try on the fashion items. The guidance unit guides the user to an e-commerce site to purchase the fashion items they have tried on. For example, the generation AI may ask the user, "Do you want to purchase this dress?" If the user selects purchase, the corresponding e-commerce site page is displayed. The guidance unit can also guide the user to the e-commerce site by providing a link or using a navigation system. The transmission unit sends an image of the suggested hairstyle to a beauty salon. For example, the generation AI may ask the user, "Do you want to send this hairstyle to a beauty salon?" If the user selects send, the image of the hairstyle is sent to the beauty salon. The transmission unit can also send the image using a communication protocol or data format. As a result, the coordination system according to the embodiment allows the user to freely coordinate fashion items and hairstyles using a 3D image of the user, and actually try them on to confirm the look. Furthermore, the user can easily purchase items they like and send an image of the hairstyle to a beauty salon.For example, if you want to choose a new dress and hairstyle for a special event, the system can help you find the perfect outfit.

[0057] The 3D image capture unit can track a user's movements in real time and automatically indicate the optimal shooting angle. For example, when a user takes a 3D image using a smartphone, the camera of the 3D image capture unit tracks the user's movements in real time and automatically indicates the optimal shooting angle. For example, the camera detects the position of the user's face and instructs the camera to adjust to the optimal angle. Furthermore, when a dedicated 3D scanner is used to scan a user's entire body, the scanner tracks the user's movements in real time and automatically indicates the optimal shooting angle. For example, the scanner detects the position of the user's body and instructs the camera to adjust to the optimal angle. Furthermore, when a drone is used to take a 3D image of a user, the 3D image capture unit tracks the user's movements in real time and automatically indicates the optimal shooting angle. For example, the drone detects the position of the user's face and body and instructs the camera to adjust to the optimal angle. This allows the drone to track the user's movements in real time and automatically indicate the optimal shooting angle, thereby capturing more accurate 3D images.

[0058] The analysis unit can also analyze the texture and color of the user's skin and suggest skin care products. For example, the generation AI analyzes the user's 3D image to detect skin texture and color. For example, it analyzes the level of dryness and uneven skin tone and suggests optimal skin care products based on that. The analysis unit also analyzes the user's 3D image to detect features such as skin tone, blemishes, and wrinkles. For example, it suggests foundation that matches the skin tone, or skin care products that cover blemishes and wrinkles. The generation AI also analyzes the user's skin condition and suggests skin care products according to the season and environment. For example, it suggests products with high moisturizing effects in the dry winter and products that protect against UV rays in the summer. In this way, the analysis unit improves the user's beauty experience by analyzing the user's skin texture and color and suggesting optimal skin care products.

[0059] The analysis unit can estimate the user's emotions and adjust the music and lighting so that the photo can be taken in a relaxed state. For example, the analysis unit uses a generation AI to analyze the user's facial expressions and voice to estimate emotions. For example, if the user is nervous, it plays relaxing music. The analysis unit also analyzes the user's emotions in real time during shooting and adjusts the brightness and color of the lighting. For example, it uses warm lighting to help the user relax. The analysis unit also uses the emotion estimation function to provide a relaxing environment for the user. For example, it displays natural sounds and scenery to help the user relax. This allows the analysis unit to estimate the user's emotions and adjust the music and lighting so that the photo can be taken in a relaxed state, thereby capturing more natural 3D images.

[0060] The 3D image capture unit can capture the entire body from 360 degrees using a drone or a robot. The 3D image capture unit, for example, uses a drone to capture the entire body of the user from 360 degrees. For example, the drone flies around the user and captures 3D images from multiple angles. The 3D image capture unit also uses a robotic arm to capture the entire body of the user from 360 degrees. For example, the robotic arm rotates around the user and captures 3D images from multiple angles. The 3D image capture unit also uses multiple cameras to capture the entire body of the user from 360 degrees. For example, cameras are placed around the user and simultaneously capture 3D images from multiple angles. This allows for capturing more detailed 3D images by capturing the entire body from 360 degrees using a drone or a robot.

[0061] The 3D image capture unit can enable the captured 3D image to be used as an avatar in games or social networking sites. The 3D image capture unit, for example, uses the captured 3D image as an avatar in a game. For example, a user uses their own 3D image as a game character and controls it in the game. The 3D image capture unit also uses the captured 3D image as an avatar on social networking sites. For example, a user uses their own 3D image as a profile picture and displays it on the social networking site. The 3D image capture unit also uses the captured 3D image as an avatar in virtual events. For example, a user uses their own 3D image as a participant in a virtual event and interacts with other participants. This allows the captured 3D image to be used as an avatar in games or social networking sites, thereby enhancing the user's experience.

[0062] The analysis unit can automatically apply filters and effects according to the user's emotions. The analysis unit, for example, uses an emotion estimation function to automatically apply filters according to the user's emotions. For example, if the user is happy, a bright filter is applied. The analysis unit also automatically applies effects according to the user's emotions at the time of shooting. For example, if the user is relaxed, a soft effect is applied. The analysis unit also uses the emotion estimation function to automatically apply backgrounds according to the user's emotions. For example, if the user is having fun, a fun background is applied. In this way, by automatically applying filters and effects according to the user's emotions, it is possible to provide more attractive 3D images.

[0063] The suggestion unit can learn the user's past purchase history and preferences and make more personalized suggestions. For example, the generation AI of the suggestion unit analyzes the user's past purchase history and suggests fashion items based on the user's preferences. For example, it suggests new items in a style similar to items previously purchased. The suggestion unit also learns the user's preferences and makes personalized suggestions. For example, it suggests the most suitable fashion items based on the user's preferred colors and designs. The suggestion unit also learns the user's past purchase history and preferences and makes suggestions according to the season or event. For example, it suggests items made of cool materials in the summer and items made of warm materials in the winter. In this way, the suggestion unit learns the user's past purchase history and preferences and makes more personalized suggestions, thereby improving user satisfaction.

[0064] The suggestion unit can make suggestions according to the user's emotions and prioritize suggesting items that elicit positive emotions. The suggestion unit, for example, uses an emotion estimation function to suggest fashion items according to the user's emotions. For example, if the user is happy, it suggests brightly colored items. The suggestion unit also analyzes the user's emotions and prioritizes suggesting items that elicit positive emotions. For example, it suggests items made from materials that allow the user to relax. The suggestion unit also uses the emotion estimation function to suggest coordination according to the user's emotions. For example, if the user is having fun, it suggests casual style items. In this way, by making suggestions according to the user's emotions and prioritize suggesting items that elicit positive emotions, user satisfaction is improved.

[0065] The suggestion unit can make conversational suggestions not only via text but also via voice or video call. In the suggestion unit, for example, the generation AI interacts with the user via voice call to suggest fashion items and hairstyles. For example, when the user expresses their preferences via voice, the generation AI makes suggestions via voice. The suggestion unit also interacts with the user via video call to suggest fashion items and hairstyles. For example, when the user expresses their preferences via video call, the generation AI makes suggestions via video call. The suggestion unit can also receive suggestions while interacting with the generation AI by selecting text, voice, or video call. For example, when the user expresses their preferences via text, the generation AI makes suggestions via voice or video call. This allows conversational suggestions to be made not only via text but also via voice or video call, improving user convenience.

[0066] The suggestion unit can consider the user's lifestyle and event schedule to suggest the best outfit for a specific scene. For example, the generation AI analyzes the user's lifestyle and suggests fashion items that are best suited to everyday life. For example, it suggests items that match work or hobbies. The suggestion unit also considers the user's event schedule to suggest the best outfit for a specific scene. For example, it suggests items that are best suited to a wedding or party. The suggestion unit also learns the user's lifestyle and event schedule through the generation AI to suggest outfits that suit the season and weather. For example, it suggests items that are best suited to a summer beach party. In this way, by considering the user's lifestyle and event schedule to suggest the best outfit for a specific scene, user satisfaction is improved.

[0067] The suggestion unit can display background music and visual effects according to the user's emotions during the suggestion. The suggestion unit, for example, uses an emotion estimation function to play background music according to the user's emotions. For example, when the user is relaxed, relaxing music is played. The suggestion unit also displays visual effects according to the user's emotions. For example, when the user is having fun, fun visual effects are displayed. The suggestion unit also uses the emotion estimation function to display a combination of background music and visual effects according to the user's emotions. For example, when the user is relaxed, relaxing music and visual effects are displayed. In this way, by displaying background music and visual effects according to the user's emotions during the suggestion, the user's experience is improved.

[0068] The fitting unit can simulate different lighting conditions and backgrounds to recreate actual usage scenarios. For example, the generation AI in the fitting unit simulates different lighting conditions to recreate how an item tried on by a user would look in an actual usage scenario. For example, it simulates natural daylight and artificial nightlight. The fitting unit also simulates different backgrounds to recreate how an item tried on by a user would look in an actual usage scenario. For example, it simulates backgrounds such as an office or a party venue. The fitting unit also simulates a combination of lighting conditions and backgrounds to recreate how an item tried on by a user would look in various scenarios. For example, it simulates an office in the daytime or a party venue at night. By simulating different lighting conditions and backgrounds and recreating actual usage scenarios, the fitting unit can more accurately check how the item will look when tried on by a user.

[0069] The fitting unit can simulate the movement and texture of the item being tried on in real time, allowing the user to check how it looks when moving. For example, the fitting unit can simulate the movement of the item being tried on by a generation AI in real time, allowing the user to check how it looks when moving. For example, it can simulate the movement of clothes when walking or sitting. The fitting unit can also simulate the texture of the item being tried on in real time, allowing the user to visually check how it feels when touched. For example, it can simulate the texture of different materials such as silk and denim. The fitting unit can also simulate a combination of movement and texture, allowing the user to check how the item being tried on looks with various movements and environments. For example, it can simulate the movement and texture of clothes when running or jumping. This allows the movement and texture of the item being tried on to be simulated in real time, allowing the user to check how it looks when moving, allowing the user to more accurately understand how the item actually feels when being tried on.

[0070] The fitting unit can use the emotion estimation function to analyze the user's emotions when trying on clothes and highlight items that elicit positive emotions. The fitting unit, for example, uses the emotion estimation function to analyze the user's emotions regarding the items they have tried on and highlight items that elicit positive emotions. For example, items that the user is happy with are prominently displayed. The fitting unit also analyzes the user's emotions when trying on clothes in real time and preferentially suggests items that elicit positive emotions. For example, it suggests items made of materials that the user can use to relax. The fitting unit also uses the emotion estimation function to analyze the user's emotions regarding the items they have tried on and provides feedback to elicit positive emotions. For example, it displays compliments or encouraging messages for items that the user enjoys. In this way, the emotion estimation function is used to analyze the user's emotions when trying on clothes and highlight items that elicit positive emotions, thereby improving user satisfaction.

[0071] The fitting unit allows users to share items they have tried on with friends and family via social media or messaging apps and receive feedback. The fitting unit, for example, provides a function that allows users to share items they have tried on via social media and receive feedback from friends and family. For example, users can post images of items they have tried on to social media and receive comments and likes. The fitting unit also provides a function that allows users to share items they have tried on with friends and family via messaging apps and receive feedback. For example, users can send images of items they have tried on via messages and exchange opinions in real time. The fitting unit also provides a dedicated platform for sharing items they have tried on and aggregates feedback from friends and family. For example, users can upload images of items they have tried on to a dedicated platform and centrally manage feedback. This allows users to share items they have tried on with friends and family via social media or messaging apps and receive feedback, helping them make better choices.

[0072] The fitting unit allows a user to share items that have been tried on with other users in a virtual fashion show and receive their ratings. The fitting unit, for example, provides a function that allows a user to share items that have been tried on with other users in a virtual fashion show and receive their ratings. For example, the user can show off the items that have been tried on on a virtual runway and receive ratings from other users. The fitting unit also provides a function that allows a user to share items that have been tried on in a virtual fashion show with other users and receive their ratings in real time. For example, the user can show off the items that have been tried on through live streaming and receive comments and ratings in real time. The fitting unit also provides a function that allows a user to share items that have been tried on with other users in a virtual fashion show contest and compete for ratings. For example, the user can enter the items that have been tried on in a contest and compete for ratings through votes from other users. This helps a user make better choices by sharing the items that have been tried on with other users in a virtual fashion show and receiving their ratings.

[0073] The fitting unit can use the emotion estimation function to automatically apply backgrounds and effects according to the user's emotions when trying on clothes. The fitting unit, for example, uses the emotion estimation function to automatically apply a background according to the user's emotions. For example, if the user is relaxed, a relaxing background is applied. The fitting unit also automatically applies effects according to the user's emotions when trying on clothes. For example, if the user is having fun, a fun effect is applied. The fitting unit also uses the emotion estimation function to automatically apply a combination of backgrounds and effects according to the user's emotions. For example, if the user is relaxed, a relaxing background and effect are applied. In this way, the user's experience is improved by using the emotion estimation function to automatically apply backgrounds and effects according to the user's emotions when trying on clothes.

[0074] The guidance unit can analyze item reviews and ratings before purchase and suggest the best option to the user. In the guidance unit, for example, the generation AI analyzes item reviews and ratings and suggests the best option to the user. For example, it may prioritize suggesting highly rated items. The guidance unit also analyzes reviews and ratings based on the user's preferences and needs and suggests the best item. For example, it may suggest items with the functions and features the user desires. The guidance unit also analyzes item reviews and ratings and provides feedback to suggest the best option to the user. For example, it may suggest items that meet the conditions the user desires. In this way, the generation AI analyzes item reviews and ratings before purchase and suggests the best option to the user, helping the user make better choices.

[0075] The guiding unit can use the emotion estimation function to analyze the user's emotion at the time of purchase and suggest benefits and discounts to elicit positive emotions. The guiding unit, for example, uses the emotion estimation function to analyze the user's emotion and suggest benefits and discounts to elicit positive emotions. For example, if the user is happy, a special discount is provided. The guiding unit also analyzes the user's emotion at the time of purchase in real time and suggests benefits and discounts to elicit positive emotions. For example, if the user is relaxed, a special benefit is provided. The guiding unit also uses the emotion estimation function to suggest benefits and discounts according to the user's emotion. For example, if the user is enjoying themselves, a special campaign is provided. In this way, by using the emotion estimation function to analyze the user's emotion at the time of purchase and suggesting benefits and discounts to elicit positive emotions, user satisfaction is improved.

[0076] The guidance unit can provide a more realistic experience by allowing the user to try on purchased items in a virtual reality (VR) environment. For example, the user tries on the purchased items using a VR headset. The guidance unit also tries on the purchased items in the VR environment to simulate actual usage scenarios. For example, the user can check how the items look when walking or sitting in the VR environment. The guidance unit also provides a function for trying on purchased items in the VR environment and sharing them with friends and family. For example, the user can check the items they have tried on in the VR environment together with their friends and family. This allows the user to try on purchased items in a virtual reality (VR) environment, providing a more realistic experience and improving user satisfaction.

[0077] The guidance unit can provide advice on how to care for and style an item after purchase. For example, the generation AI provides advice on how to care for an item after purchase. For example, it provides advice on how to wash and store the item. The guidance unit also provides styling advice for the item after purchase. For example, it suggests other items and accessories that go well with the purchased item. The guidance unit also provides a dedicated app that allows the generation AI to provide advice on how to care for and style an item after purchase. For example, the user receives care and styling advice through the app. This improves user satisfaction by providing advice on how to care for and style an item after purchase.

[0078] The guiding unit can use the emotion estimation function to provide a personalized message or gift according to the user's emotion at the time of purchase. For example, the guiding unit uses the emotion estimation function to provide a personalized message according to the user's emotion at the time of purchase. For example, if the user is happy, it sends a message of thanks. The guiding unit also analyzes the user's emotion at the time of purchase in real time and provides a personalized gift according to the emotion. For example, if the user is relaxed, it sends a special gift. The guiding unit also uses the emotion estimation function to provide a personalized message or gift according to the user's emotion. For example, if the user is having fun, it provides a special campaign. In this way, by using the emotion estimation function to provide a personalized message or gift according to the user's emotion at the time of purchase, user satisfaction is improved.

[0079] The transmission unit can analyze the user's hair type and scalp condition and recommend optimal hair care products. For example, the generation AI in the transmission unit analyzes the user's hair type and recommends optimal hair care products. For example, it analyzes the dryness and degree of damage of the hair and recommends shampoos and treatments with high moisturizing effects based on that. The transmission unit also analyzes the user's scalp condition and recommends optimal hair care products. For example, it analyzes the oil content and dandruff state of the scalp and recommends shampoos and lotions for scalp care based on that. The generation AI in the transmission unit also analyzes the user's hair type and scalp condition and recommends hair care products according to the season and environment. For example, it recommends products with high moisturizing effects in the dry winter and products with UV protection in the summer. In this way, by analyzing the user's hair type and scalp condition and recommending optimal hair care products, user satisfaction is improved.

[0080] The transmission unit supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed. For example, the generation AI in the transmission unit analyzes the user's wishes and provides specific instructions to the hairdresser. For example, it communicates details of the hairstyle the user desires to the hairdresser. In addition, the generation AI in the transmission unit supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed. For example, it communicates the characteristics of the hairstyle the user desires and styling methods to the hairdresser. In addition, the generation AI in the transmission unit analyzes the user's wishes and provides specific advice to the hairdresser. For example, it communicates suggestions for cuts and colors that suit the hairstyle the user desires to the hairdresser. This supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed, making consultations at the hair salon smoother.

[0081] The transmission unit can use the emotion estimation function to suggest a hairstyle according to the user's emotion and preferentially transmit hairstyles that elicit positive emotions. The transmission unit, for example, uses the emotion estimation function to suggest a hairstyle according to the user's emotion. For example, when the user is relaxed, it suggests a relaxing hairstyle. The transmission unit also analyzes the user's emotion and preferentially suggests hairstyles that elicit positive emotions. For example, when the user is having fun, it suggests a fun hairstyle. The transmission unit also uses the emotion estimation function to suggest a hairstyle according to the user's emotion and preferentially transmit hairstyles that elicit positive emotions. For example, when the user is happy, it suggests a bright-colored hairstyle. In this way, by using the emotion estimation function to suggest a hairstyle according to the user's emotion and preferentially transmit hairstyles that elicit positive emotions, user satisfaction is improved.

[0082] The transmission unit can support counseling at a beauty salon by using an image of a hairstyle to try on the hairstyle in real time using AR (augmented reality) technology. The transmission unit, for example, uses AR technology to try on a hairstyle that the user desires in real time, thereby supporting counseling at a beauty salon. For example, the user uses a smartphone to check the desired hairstyle in real time. The transmission unit also uses AR technology to try on the hairstyle that the user desires in real time during counseling at a beauty salon. For example, a hairdresser uses a tablet to simulate the user's hairstyle in real time. The transmission unit also provides a dedicated app that uses AR technology to try on the hairstyle that the user desires in real time and support counseling at a beauty salon. For example, the user checks the desired hairstyle through the app in real time. This allows the user to try on the hairstyle image in real time using AR (augmented reality) technology to support counseling at a beauty salon, thereby improving user satisfaction.

[0083] The transmission unit uses the emotion estimation function to suggest a hairstyle that matches the user's emotions, thereby making the consultation at the beauty salon smoother. For example, the transmission unit uses the emotion estimation function to suggest a hairstyle that matches the user's emotions, thereby making the consultation at the beauty salon smoother. For example, if the user is relaxed, the transmission unit suggests a relaxing hairstyle. The transmission unit also analyzes the user's emotions and suggests a hairstyle that elicits positive emotions, thereby making the consultation at the beauty salon smoother. For example, if the user is having fun, the transmission unit suggests a fun hairstyle. The transmission unit also uses the emotion estimation function to suggest a hairstyle that matches the user's emotions, thereby providing a dedicated app for making the consultation at the beauty salon smoother. For example, the user checks the desired hairstyle through the app and communicates it to the hairdresser. In this way, the emotion estimation function is used to suggest a hairstyle that matches the user's emotions, making the consultation at the beauty salon smoother, thereby improving user satisfaction.

[0084] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0085] The suggestion unit can estimate the user's emotions and provide a relaxing environment based on the estimated user's emotions. For example, if the user is nervous, the suggestion unit can play relaxing music. The suggestion unit can also adjust lighting according to the user's emotions. For example, warm-colored lighting can be used to help the user relax. The suggestion unit can also display a background according to the user's emotions. For example, a natural landscape can be displayed to help the user relax. This makes it possible to provide a more comfortable experience by providing an environment according to the user's emotions.

[0086] The analysis unit can estimate the user's emotions and suggest optimal fashion items based on the estimated user emotions. For example, if the user is happy, bright colored items are suggested. The analysis unit can also suggest styles that correspond to the user's emotions. For example, if the user is relaxed, casual style items are suggested. The analysis unit can also suggest materials that correspond to the user's emotions. For example, items made of materials that make the user feel relaxed are suggested. In this way, by suggesting fashion items that correspond to the user's emotions, user satisfaction can be improved.

[0087] The suggestion unit can estimate the user's emotions and suggest an optimal hairstyle based on the estimated user's emotions. For example, if the user is relaxed, the suggestion unit can suggest a relaxing hairstyle. The suggestion unit can also suggest a styling that matches the user's emotions. For example, if the user is having fun, the suggestion unit can suggest a fun styling. The suggestion unit can also suggest a color that matches the user's emotions. For example, if the user is happy, the suggestion unit can suggest a bright-colored hairstyle. In this way, by suggesting a hairstyle that matches the user's emotions, it is possible to improve user satisfaction.

[0088] The fitting unit can estimate the user's emotions and provide an optimal fitting environment based on the estimated user's emotions. For example, if the user is nervous, the fitting unit can play relaxing music. The fitting unit can also adjust lighting according to the user's emotions. For example, warm lighting can be used to help the user relax. The fitting unit can also display a background according to the user's emotions. For example, a natural landscape can be displayed to help the user relax. This can provide a fitting environment according to the user's emotions, thereby providing a more comfortable fitting experience.

[0089] The transmission unit can estimate the user's emotions and transmit an image of an optimal hairstyle to the hair salon based on the estimated user's emotions. For example, if the user is relaxed, the transmission unit transmits an image of a relaxing hairstyle. The transmission unit can also suggest a styling that corresponds to the user's emotions. For example, if the user is having fun, the transmission unit can suggest a fun styling. The transmission unit can also suggest a color that corresponds to the user's emotions. For example, if the user is happy, the transmission unit transmits an image of a hairstyle with a bright color. In this way, by transmitting an image of a hairstyle that corresponds to the user's emotions to the hair salon, user satisfaction can be improved.

[0090] The suggestion unit can suggest fashion items that are optimal for specific occasions based on the user's lifestyle. For example, it can suggest items that match work or hobbies. The suggestion unit can also consider the user's event schedule and suggest coordination that is optimal for specific occasions. For example, it can suggest items that are optimal for weddings or parties. The suggestion unit can also suggest coordination that is optimal for the season or weather. For example, it can suggest items that are optimal for a summer beach party. In this way, it is possible to improve user satisfaction by considering the user's lifestyle and event schedule and suggesting coordination that is optimal for specific occasions.

[0091] The fitting unit can simulate different lighting conditions and backgrounds to recreate actual usage scenes. For example, it can simulate natural daylight and artificial nightlight. The fitting unit can also simulate backgrounds such as an office or a party venue. For example, it can simulate an office in the daytime or a party venue at night. The fitting unit can also simulate a combination of lighting conditions and backgrounds to recreate how an item tried on by a user looks in various scenes. This allows the user to more accurately check how the item will look when tried on by simulating different lighting conditions and backgrounds to recreate actual usage scenes.

[0092] The fitting unit can simulate the movement and texture of the item being tried on in real time, allowing the user to check how it looks when moving. For example, it can simulate the movement of the clothes when walking or sitting. The fitting unit can also simulate the texture of different materials, such as silk or denim, in real time, allowing the user to visually check how it feels when touched. The fitting unit can also simulate a combination of movement and texture, allowing the user to check how the item being tried on looks with various movements and in various environments. In this way, by simulating the movement and texture of the item being tried on in real time and checking how it looks when moving, the user can more accurately understand how the item actually feels when being tried on.

[0093] The transmission unit can use AR (augmented reality) technology to try on hairstyle images in real time, supporting counseling at a beauty salon. For example, a user uses a smartphone to check their desired hairstyle in real time. The transmission unit can also use AR technology to try on the user's desired hairstyle in real time during counseling at a beauty salon. For example, a hairdresser uses a tablet to simulate the user's hairstyle in real time. The transmission unit can also use AR technology to provide a dedicated app to support counseling at a beauty salon by allowing the user to try on the user's desired hairstyle in real time. This allows the user to try on hairstyle images in real time using AR (augmented reality) technology to support counseling at a beauty salon, thereby improving user satisfaction.

[0094] The transmission unit supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed. For example, the generation AI analyzes the user's wishes and provides specific instructions to the hairdresser. The transmission unit also supports the dialogue with the hairdresser when sending an image of the hairstyle, allowing the user's wishes to be accurately conveyed. For example, the generation AI communicates the characteristics of the hairstyle the user wants to have and the styling method to the hairdresser. The transmission unit also analyzes the user's wishes and provides specific advice to the hairdresser. This allows the dialogue with the hairdresser when sending an image of the hairstyle to be supported, allowing the user's wishes to be accurately conveyed, making counseling at the hair salon smoother.

[0095] The processing flow of the second embodiment will be briefly explained below.

[0096] Step 1: The 3D image capture unit captures a 3D image of the user. For example, a 3D image can be taken using a smartphone or a dedicated 3D scanner and imported into the system. The 3D image capture unit can also capture 3D images using a stereo camera or LiDAR. Step 2: The analysis unit analyzes the captured 3D image. For example, the generative AI extracts features such as the user's body type, face shape, and hair length. The analysis unit can also analyze the 3D image using image processing algorithms and machine learning models. Step 3: The suggestion unit suggests fashion items and hairstyles to the user based on the analyzed results. For example, the generation AI suggests optimal items and hairstyles through dialogue with the user. The suggestion unit can also make suggestions based on the user's preferences and trend analysis. Step 4: The fitting section tries on the suggested fashion items and hairstyles on the 3D image. For example, the generative AI applies the suggested items and hairstyles to the 3D image, allowing the user to visually confirm how they will actually look. The fitting section can also use 3D rendering technology or a virtual fitting system to try on the items. Step 5: The navigation unit guides the user to an e-commerce site to purchase the fashion item they tried on. For example, the generation AI asks the user, "Do you want to buy this dress?" If the user selects purchase, the corresponding e-commerce site page is displayed. The navigation unit can also guide the user to the e-commerce site by providing a link or using a navigation system. Step 6: The transmission unit sends an image of the proposed hairstyle to the hair salon. For example, the generation AI asks the user, "Do you want to send this hairstyle to the hair salon?" If the user selects "send," the image of the hairstyle is sent to the hair salon. The transmission unit can also send the image using a communication protocol or data format.

[0097] 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.

[0098] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0099] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0100] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0101] 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.

[0102] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0103] 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.

[0104] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0105] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0110] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0111] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0112] 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.

[0113] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0114] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0115] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0116] 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.

[0117] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0118] 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.

[0119] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0120] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0125] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0126] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0127] 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.

[0128] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0129] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0130] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0131] 7, the 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.

[0132] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0133] 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.

[0134] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0135] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0136] 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.

[0137] The control object 443 includes a display device, LEDs in the eyes, and motors that drive 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.

[0138] 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.

[0139] 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.

[0140] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0141] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0142] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0143] 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.

[0144] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0145] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0146] 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.

[0147] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions 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.

[0148] 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.

[0149] 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).

[0150] 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 expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, 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 expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0151] 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."

[0152] 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.

[0153] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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. A processor also includes 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.

[0158] The hardware resource that executes the specific process 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 process may be a single processor.

[0159] 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.

[0160] 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.

[0161] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0162] 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.

[0163] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0164] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a 3D image capture unit that captures a 3D image of a user; an analysis unit that analyzes the 3D image captured by the 3D image capture unit; a suggestion unit that suggests fashion items and hairstyles to the user based on the results of the analysis by the analysis unit; a fitting unit for trying on the fashion item and the hairstyle suggested by the suggestion unit on the 3D image; a guidance unit that guides the user to the EC site to purchase the fashion item that has been tried on by the fitting unit; a transmission unit that transmits an image of the hairstyle suggested by the suggestion unit to a beauty salon. A system characterized by:

2. The 3D image capture unit Tracks the user's movements in real time and automatically suggests the optimal shooting angle 2. The system of claim 1.

3. The analysis unit Analyzing the texture and color of the user's skin and suggesting skin care products 2. The system of claim 1.

4. The analysis unit The system estimates the user's emotions and adjusts the music and lighting to allow the user to take photos in a relaxed state.

2. The system of claim 1.

5. The 3D image capture unit Using drones or robots to capture the entire body from 360 degrees 2. The system of claim 1.

6. The 3D image capture unit The captured 3D image can be used as an avatar in games and on the SNS.

2. The system of claim 1.

7. The analysis unit Automatically apply filters and effects according to the user's emotions 2. The system of claim 1.

8. The proposal unit Learn about the user's purchase history and preferences to provide more personalized suggestions 2. The system of claim 1.

Images