system

Abstract

We provide the system. [Solution] A means of photographing the user's body, A display means for displaying the three-dimensional structure of an object selected by the user, An augmented reality system that overlays and displays selected objects onto the user's body, A machine learning processing means for transmitting information to a remote data processing device and generating styling suggestions, A presentation method for showing the generated styling suggestions to the user, A system that includes online trading methods for processing the buying and selling of products that users are interested in.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional shopping experience, there is a problem that it is difficult for a user to confirm the fit and style of a product without actually trying it on before purchase. In addition, due to the impact of the novel coronavirus infection, the demand for a contactless shopping experience is increasing, but there is a lack of alternative means for trying on in a real store. Moreover, even with various sizes and designs in online shopping, it is difficult for a user to instantly select a product and styling suitable for the user, and an improvement in satisfaction after purchase is required.

Means for Solving the Problems

[0005] This invention provides a system comprising: a shooting means for photographing the user's body; a display means for displaying a three-dimensional model of a product selected by the user; an augmented reality means for overlaying the selected product onto the user's body; and an artificial intelligence processing means for transmitting data to a server and generating styling suggestions, and presenting the generated styling suggestions to the user. With this system, the user can check the fit and style of products in real time from the comfort of their home, and furthermore, receive styling suggestions from artificial intelligence to make the optimal product selection. This improves the contactless shopping experience.

[0006] A "user" is an individual or consumer who uses the system to try on or purchase products.

[0007] "Means of photography" refers to cameras and photographic devices used to photograph the user's body.

[0008] "Display means" refers to a monitor or display device used to display a three-dimensional model of a product selected by the user on a screen.

[0009] "Augmented reality means" refers to technology that overlays a three-dimensional model of a selected product onto the user's body.

[0010] A "three-dimensional model" refers to the three-dimensional shape data of a product represented on a computer.

[0011] A "server" refers to a computer system used to collect and process data, generate styling suggestions, and send and receive information.

[0012] "Sending data" refers to the act of transferring information from a terminal to a server.

[0013] "Artificial intelligence processing means" refers to methods for performing machine learning and data analysis to generate styling suggestions.

[0014] "Styling proposal" refers to information that proposes an optimal fashion coordination based on user preferences and trends.

[0015] "Presentation means" refers to means for visually or audibly notifying a user of a styling proposal.

[0016] "E-commerce means" refers to a system for processing online selection, purchase, and payment of goods.

Brief Description of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Modes for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), etc.

[0021] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

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

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0034] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This invention is a system that allows users to virtually try on clothes and accessories using a smartphone or tablet. The user takes a full-body photo using the device's camera and selects products. The device generates a three-dimensional model of the selected product and displays it overlaid on the user's image using augmented reality means.

[0039] In this process, the device adjusts the 3D model appropriately, taking into account the user's body shape and position. Next, the device sends this data to a server, which analyzes the received data using artificial intelligence processing. The server then takes into account the user's past purchase history and current fashion trends to generate optimal styling suggestions.

[0040] The generated styling suggestions are sent from the server to the terminal, which then presents the suggestions to the user. The user can continue virtual try-on based on this information. If the user is interested in purchasing, the terminal initiates the purchase process using e-commerce tools.

[0041] For example, if a user wants to choose and try on a new dress from the comfort of their home, the device will display a 3D model of the dress and suggest the best outfit based on AI styling recommendations. The user can then decide to purchase the dress based on this feedback and complete the purchase process on the device. This format allows for a satisfying shopping experience without the need for physical try-on.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user launches a dedicated application on their device, stands in a position where their entire body can be photographed, and activates the camera. The user then selects the clothes or accessories they want to try on within the app.

[0045] Step 2:

[0046] The device detects the user's body from real-time video footage captured by the camera and obtains 3D model data of the selected product. The device also uses augmented reality to overlay the product data onto the user's video.

[0047] Step 3:

[0048] The device adjusts the position and size of the 3D model in real time, taking into account the user's body shape and the fit of the selected product. It checks the degree of matching of each part to ensure a natural overlay.

[0049] Step 4:

[0050] The terminal transmits current video data and product selection information to the server. The data also includes user-specific body type information and product attribute information.

[0051] Step 5:

[0052] The server uses an AI agent to analyze the transmitted data. The server references the user's past purchase history and current fashion trends to generate optimal styling suggestions.

[0053] Step 6:

[0054] The server sends the generated styling suggestions to the terminal. The suggestions include specific information about accessories and other clothing combinations that would suit the product.

[0055] Step 7:

[0056] The device displays the received styling suggestions to the user on the screen. The user continues trying on clothes based on the displayed suggestions, selecting other items or adjusting the fit as needed.

[0057] Step 8:

[0058] If the user decides to make a purchase, the device initiates the purchase process through e-commerce. The device sends the necessary information to the server and processes the payment.

[0059] Step 9:

[0060] The server processes the purchase information and arranges for product shipment. The user receives a purchase completion notification via their device.

[0061] (Example 1)

[0062] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0063] Traditional online shopping systems have faced challenges such as users being unable to actually try on products, leading to errors in product selection. Furthermore, it has been difficult to provide styling suggestions that take into account individual user body types and preferences, making it challenging to offer a truly satisfying shopping experience.

[0064] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0065] In this invention, the server includes means for photographing the user's body and acquiring images, means for generating a three-dimensional model using product information selected by the user, and means for transmitting the data to the server and generating styling suggestions using the generated AI model. This makes it possible for the user to virtually try on products that are appropriately adjusted to their body type and to receive styling suggestions based on their individual preferences.

[0066] "Means of photography" refers to a device or function for photographing the user's body and acquiring image data.

[0067] "Generation means" refers to the technology and equipment used to create a three-dimensional model of a product based on product information selected by the user.

[0068] "Augmented reality means" refers to technologies and systems that overlay virtual three-dimensional models onto images of the real world.

[0069] "Adjustment means" refers to a system that analyzes the user's body shape and has the function to automatically adjust the position and size of the displayed three-dimensional model appropriately.

[0070] "Analysis means" refers to a device or function that transmits data to a server and processes it to create styling suggestions for the user using a generated AI model.

[0071] "Notification means" refers to functions or devices for communicating generated styling suggestions to the user.

[0072] "Electronic commerce methods" refer to systems and technologies that enable users to complete the purchase process of selected goods online.

[0073] This invention provides a system that allows users to virtually try on clothes and accessories using their own devices, such as smartphones and tablets. The user takes a full-body photograph using the device's camera, and the system operates based on that image. The device is equipped with a high-resolution camera, a touchscreen, and a processor for utilizing augmented reality (AR) technology. Specifically, the device's camera system and AR framework (e.g., ARKit for iOS or ARCore for Android®) are used to overlay product models onto images of the real world.

[0074] When a user selects a product, the terminal receives the product's digital information and generates a 3D model. This can be done using 3D modeling software (e.g., Blender or Unity). The generated model is then adjusted according to the user's body shape and displayed realistically. Image processing libraries (e.g., OpenCV) are used for this adjustment process.

[0075] The adjusted data is then sent from the terminal to the server. The server analyzes the received data using a generative AI model (e.g., TENSORFLOW® or PyTorch). Based on the user's past purchase history and current trend information, the server provides optimal styling suggestions. These suggestions are important as part of a unique sales strategy.

[0076] For example, if a user wants to virtually try on a new dress and find the best styling for them, the system uses AR technology to display a 3D model of the dress on the user's screen and provides AI-powered styling suggestions. These suggestions include specific advice such as, "Gold accessories would go well with this red dress." Furthermore, if the user wishes to purchase the dress, they can securely complete the payment process on their device. This entire process allows users to enjoy an effective shopping experience from the comfort of their homes.

[0077] Examples of prompts include, "Generate the latest styling suggestions for women in their 30s that are suitable for autumn fashion."

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The user takes a full-body photo using the device's camera. The input is a full-body image of the user. The device extracts the user's body shape data from this image. Using an image processing library, it measures basic dimensions such as shoulder width and height, and generates body shape information as output.

[0081] Step 2:

[0082] The terminal receives information about the product selected by the user and generates a corresponding 3D model. The input is the identification information of the selected product. Based on this information, a model is generated using 3D modeling software, and 3D model data is created as output.

[0083] Step 3:

[0084] The terminal adjusts the generated 3D model based on the user's body shape information. The inputs are the body shape information obtained in step 1 and the 3D model generated in step 2. Image processing technology is used to appropriately adjust the size and angle of the model, generating a model that fits the user as output.

[0085] Step 4:

[0086] The adjusted 3D model is displayed on the device by overlaying it onto the user's video using augmented reality. The input is the adjusted 3D model data. Using the device's AR framework, the model is overlaid on the video in real time, generating an output video to be displayed to the user.

[0087] Step 5:

[0088] The terminal sends the adjusted data to the server. The input consists of the adjusted 3D model and the user's body shape information. A data transmission communication protocol is used to generate the data that the server receives as output.

[0089] Step 6:

[0090] The server generates styling suggestions using an AI model based on the received data. The input is data sent from the terminal. The AI ​​model refers to purchase history and trend information in the database to generate appropriate styling suggestions and outputs styling suggestion data.

[0091] Step 7:

[0092] The server sends the generated styling suggestions to the terminal. The input is the generated styling suggestion data. Depending on the presentation method, communication means are used to appropriately deliver the suggestions to the user, and data is generated that is received by the terminal as output.

[0093] Step 8:

[0094] The terminal presents the received styling suggestions to the user. The input is the received styling suggestion data. The terminal's display is used to show the information, providing the user with visual feedback as output.

[0095] Step 9:

[0096] If the user decides to make a purchase, the terminal initiates the purchase process using e-commerce methods. The input is the user's purchase decision information. The payment app on the terminal is launched to execute the purchase process, and a purchase completion notification is generated as output.

[0097] (Application Example 1)

[0098] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0099] In modern virtual stores, it is difficult for users to make satisfactory purchase decisions without physically trying on items. Furthermore, online shopping often lacks appropriate styling suggestions and recommendations for related products, resulting in a limited user experience.

[0100] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0101] In this invention, the server includes a means for capturing images of the user's body, an augmented reality means for overlaying and displaying selected objects, and a machine learning processing means for generating styling suggestions. This allows the user to try out appropriate outfits from the comfort of their home, receive recommendations for related products, and improve their shopping experience.

[0102] "Photography means" refers to a digital imaging device used to acquire an image of the user's body.

[0103] "Display means" refers to a device or software for visually showing the three-dimensional structure of an object selected by the user.

[0104] "Augmented reality" refers to a technology that overlays digital objects onto images of the real world, providing users with a virtual experience.

[0105] "Machine learning processing means" refers to components of artificial intelligence used to analyze data and automatically generate styling suggestions suitable for the user.

[0106] "Presentation means" refers to a method for visually or audibly showing the generated styling suggestions to the user.

[0107] "Online trading methods" refer to digital platforms and related technologies used to buy and sell goods via the internet.

[0108] A "recommendation system" is an artificial intelligence-based system used to suggest additional relevant items based on the user's preferences and history.

[0109] Regarding embodiments for carrying out the invention, the present invention is a system that allows a user to view selected objects superimposed onto their own image from a remote location such as their home, and provides an experience from receiving styling suggestions to making a purchase. This system is configured as follows.

[0110] First, the user takes a picture of themselves using a device equipped with a camera (e.g., a smartphone or tablet). The device uses its camera function to capture the user's entire body. Next, the device uses a display to show the three-dimensional structure of an object selected by the user. At this point, the device uses AR technology to overlay the digital object onto the real-world image. Specifically, software platforms such as ARKit and ARCore are used.

[0111] Furthermore, the device transmits the acquired data to a remote server. The server utilizes cloud-based AI processing services (e.g., Google Cloud AI or AWS AI) and employs machine learning models to generate styling suggestions based on the received user data. This generation process involves analysis based on the user's past purchase history and the latest fashion trends. The generated suggestions are then displayed on the device via a presentation system.

[0112] When a user becomes interested in a styling suggestion, they can purchase the product through online transactions on their device. An e-commerce platform is used in this process.

[0113] A concrete example is a scenario where a user uses the "Smart Closet" application to try on new clothes and check AI styling suggestions. These suggestions may include combinations with previously purchased items or coordinated outfits optimized for the user's individual preferences.

[0114] An example of a prompt to input into the AI ​​model would be, "Based on the user's past purchase history, please generate the best styling suggestions for this dress. Also, please consider current fashion trends." This would allow users to easily enjoy fashion coordination at home without having to physically try on clothes.

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The user activates the device's camera and takes a full-body picture. The input is real-time video data, and the output is an image of the user. This image forms the basis for subsequent augmented reality processing. Specifically, the user positions the device at an appropriate distance and positions their image within the screen.

[0118] Step 2:

[0119] The device displays a 3D model of the product selected by the user. The input is the digital data of the selected object, and the output is a display of that 3D model superimposed on the user's image. Augmented reality technologies using ARKit or ARCore are used for data processing. Specifically, the 3D model is adjusted to match the user's body shape and orientation and superimposed on the real-world image.

[0120] Step 3:

[0121] The system sends user image data and object selection data to the server. The input is the user's image and selection data, and the output is the result of the transmission to the server. Specifically, the terminal uses an internet connection to upload the data to the remote server.

[0122] Step 4:

[0123] The server generates styling suggestions based on the received data. Inputs include past purchase history, current fashion trends, and user image data, while output is styling suggestions. This process uses a generative AI model to perform data analysis and suggestion generation based on prompt messages.

[0124] Step 5:

[0125] The generated styling suggestions are sent from the server to the terminal. The input is the styling suggestions generated on the server, and the output is the suggestion data received by the terminal. Specifically, the data is transmitted to the terminal again via the internet connection.

[0126] Step 6:

[0127] The terminal receives suggestion data and presents it to the user. The input is suggestion data sent from the server, and the output is styling suggestions displayed on the terminal screen. The user views this information and decides whether to continue trying on clothes or consider purchasing.

[0128] Step 7:

[0129] If the user decides to purchase, the terminal will process the purchase through an online transaction method. The input is the user's intention to purchase and the selected product information, and the output is a confirmation that the transaction is complete. Specifically, the terminal enters payment information and completes the purchase through the online transaction platform.

[0130] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0131] This invention is a system that allows users to virtually try on clothes and accessories via a smartphone or tablet, and combines an emotion engine to provide styling suggestions based on the user's emotions. First, the user takes a full-body photo using the device's camera. The device generates three-dimensional models of the clothes and accessories, and uses augmented reality technology to overlay the models of the selected items onto the user's image.

[0132] In this system, the device incorporates an emotion engine that analyzes the user's facial expressions and voice to recognize emotions in real time. The emotion engine can determine emotional states such as joy, surprise, and sadness from facial features and voice tone.

[0133] The device then sends the fitting data, along with the acquired emotional information, to the server. The server uses artificial intelligence processing to analyze this data and generates optimal styling suggestions that take into account the user's past history, current fashion trends, and emotional state. For example, if the user expresses surprise, the server will suggest a new style or provide a bolder combination of fashion items.

[0134] The generated styling suggestions are sent to the device and presented to the user. The user can continue trying on clothes based on these suggestions. Furthermore, if the user wishes to purchase, the device can proceed with the purchase process via e-commerce. This format allows the user to have a personalized try-on experience that reflects their emotions, improving shopping satisfaction. For example, if the user has a cheerful expression, they may receive more casual and colorful suggestions, allowing them to shop in a way that suits their mood.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] The user launches a dedicated application on their device and uses the camera in a position where their entire body can be photographed. The user then selects the items they wish to try on from within the app.

[0138] Step 2:

[0139] The device analyzes camera footage in real time to detect the user's body. It also acquires a 3D model of the selected product and overlays it onto the user's body using augmented reality.

[0140] Step 3:

[0141] The device activates an emotion engine to analyze the user's facial expressions and voice. The emotion engine analyzes facial features and voice tone to identify the emotional state. For example, if a smile is detected, it determines that the user is "happy."

[0142] Step 4:

[0143] The device sends the user's body shape data, selected product information, and detected emotion data to the server. This allows the server to receive diverse information all at once.

[0144] Step 5:

[0145] The server uses an AI agent to analyze the received data. The server combines emotional information, past history, and trend information to generate optimal styling suggestions for the user. For example, if the user expresses surprise, the server will consider new styles or bolder suggestions.

[0146] Step 6:

[0147] The server sends the generated styling suggestions to the terminal. In addition to standard styling suggestions, the server's suggestions may include special elements tailored to the user's mood.

[0148] Step 7:

[0149] The device displays the received styling suggestions on its screen and presents them to the user. The user can then try on the clothes again or try a different style based on the information presented.

[0150] Step 8:

[0151] If the user is satisfied with the suggested style and wishes to purchase it, the device will display an e-commerce form and proceed with the purchase process.

[0152] Step 9:

[0153] The server processes the purchase information sent from the terminal and initiates the shipping process for the goods. This allows the user to receive a notification that the purchase is complete.

[0154] (Example 2)

[0155] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0156] Conventional virtual try-on systems have the problem of not being able to improve individual satisfaction because they simply suggest clothing and accessory styling without considering the user's emotions. Furthermore, styling suggestions are one-way and cannot be optimized according to the user's emotions, resulting in the problem of not being able to provide the truly optimal style for the user.

[0157] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0158] In this invention, the server includes emotion analysis means for analyzing the user's emotions, artificial intelligence processing means for transmitting data to the server and generating styling suggestions considering the emotional information, and presentation means for presenting the generated styling suggestions to the user. This enables personalized styling suggestions based on the user's emotions, thereby improving user satisfaction.

[0159] "Photography equipment" refers to a device equipped with the function of acquiring the user's body as image data.

[0160] A "generation means" is a device that has the function of constructing a three-dimensional model of clothing or accessories based on acquired image data.

[0161] "Augmented reality means" refers to devices that enable the real-time visual display of a three-dimensional model superimposed onto the user's body.

[0162] An "emotion analysis device" is a device that has the function of analyzing a user's facial expressions and voice to determine their emotional state.

[0163] "Artificial intelligence processing means" refers to a system that generates styling suggestions using a learning algorithm based on data received by the server.

[0164] A "presentation means" is a device for visually or audibly communicating the generated styling suggestions to the user.

[0165] An "electronic transaction method" is a system that has the functionality to allow users to complete the purchase process of selected goods online.

[0166] This invention is a system that allows users to virtually try on clothes and accessories using a mobile information terminal such as a smartphone or tablet. The terminal is equipped with advanced imaging, generation, augmented reality, and emotion analysis capabilities.

[0167] First, the user takes a picture of their body using the device's camera. The camera function is utilized to obtain high-resolution and accurate image data. Next, the acquired image data is sent to a generation system, where a three-dimensional model of clothing and accessories is automatically generated. 3D modeling software and libraries (e.g., Blender or Autodesk Maya) are used for this generation.

[0168] Next, augmented reality (AR) technology kicks in, overlaying the generated 3D model onto the user's image in real time. AR technology is used for this display, with ARKit and ARCore being representative examples.

[0169] Furthermore, the device incorporates emotion analysis capabilities. This device uses face recognition and voice analysis libraries (e.g., OpenCV and Microsoft® Azure® Face API) to analyze the user's facial expressions and voice in real time and determine emotions such as joy and surprise.

[0170] The fitting data and sentiment information collected together are sent from the terminal to the server. The server uses artificial intelligence processing tools to analyze this data. For this purpose, machine learning frameworks (e.g., TensorFlow and PyTorch) are used. The server considers the user's past history, current fashion information, and sentiment analysis results to generate optimal styling suggestions.

[0171] The generated styling suggestions are sent to the terminal and presented to the user through a display device. This allows the user to review the styles and continue trying them on. Furthermore, when the user purchases the selected items, the terminal's electronic transaction device is used to complete the online payment.

[0172] For example, if the user has a cheerful expression, the system will suggest a casual, brightly colored style. An example of such a prompt would be, "Please generate a recommended style, taking into account the emotions the user has expressed."

[0173] This system enables users to enjoy a personalized try-on experience tailored to their own feelings, thereby improving shopping satisfaction.

[0174] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0175] Step 1:

[0176] The user activates the device's camera and takes a picture of their body. The input data is the image acquired through the device's camera. This image data is high resolution and accurately captures the user's entire body. An image file is generated as output.

[0177] Step 2:

[0178] The device generates three-dimensional models of clothing and accessories using captured image data. The input is the user's image data, and the output is the data of the three-dimensional model. 3D modeling software is used to generate the three-dimensional model. Specifically, it analyzes the acquired images and adjusts the model to match the position and size of the human body.

[0179] Step 3:

[0180] The device uses augmented reality technology to overlay a generated 3D model onto the user's image. The input consists of the 3D model data and the user's image data, while the output is a virtual try-on image displayed in augmented reality. Specifically, the model is displayed in real-time, adapting to the user's movements, providing a natural try-on experience.

[0181] Step 4:

[0182] The device uses a camera and microphone to analyze the user's emotions. Input is the user's facial expressions and voice data. Output is the analyzed emotional state (joy, surprise, sadness, etc.). Specifically, a process is performed to analyze facial features and voice tone to determine emotions in real time.

[0183] Step 5:

[0184] The device sends fitting data and emotional data to the server. The input is this data, and the output is the information transferred to the server. Specifically, the HTTPS protocol is used for secure data transmission.

[0185] Step 6:

[0186] The server generates styling suggestions using an AI model based on the received data. Inputs include user try-on data, emotional state, past history, and trend information. The output is a styling suggestion optimized for the user. Specifically, it utilizes machine learning algorithms to analyze data from multiple perspectives.

[0187] Step 7:

[0188] The server sends the generated styling suggestions to the terminal. The input is the styling suggestion data. The output is the suggestion sent to the terminal. Specifically, the server converts the suggested content into a format suitable for external presentations and prepares it for clear presentation to the user.

[0189] Step 8:

[0190] The terminal presents the transmitted styling suggestions to the user. The input is the styling suggestion data. The output is suggestion information that the user can visually confirm. Specifically, it displays the suggestions on the screen, allowing the user to continue trying on clothes interactively.

[0191] Step 9:

[0192] When a user purchases a product, the terminal uses electronic transaction methods to complete the purchase process. Inputs include the user's purchase intention and payment information. Output is the completed purchase transaction. Specifically, a secure online payment is processed based on the user's expressed intention.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] Conventional virtual try-on systems were unable to offer styling suggestions that took into account the user's emotions, and could only provide uniform suggestions. Therefore, a challenge was that it was difficult to provide a personalized experience tailored to the individual circumstances of each user.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0197] In this invention, the server includes emotion analysis means for analyzing facial expressions and voice to recognize the user's emotional state, artificial intelligence processing means for generating styling suggestions based on the user's emotional state, and presentation means for presenting the generated styling suggestions to the user. This enables personalized styling suggestions that reflect the user's emotions.

[0198] "Means of photography" refers to a device or function for photographing the user's body, and includes devices such as cameras.

[0199] "Display means" refers to a device or function for visually presenting a three-dimensional model of an item selected by the user, and includes devices such as displays and monitors.

[0200] "Augmented reality means" refers to a technology or device for superimposing selected objects onto a user's body, and is a technology that uses augmented reality technology to superimpose the virtual and real worlds.

[0201] "Emotional analysis means" refers to a technology or device for recognizing a user's emotional state by analyzing their facial expressions and voice.

[0202] "Artificial intelligence processing means" refers to a technology for processing data and generating styling suggestions based on the user's emotional state, and involves processing using machine learning algorithms.

[0203] "Presentation means" refers to a device or function for providing the generated styling suggestions to the user visually or audibly, and includes devices such as displays and speakers.

[0204] This invention is implemented as a system using a terminal and a server. The terminal is equipped with a camera as a means of capturing images of the user's body, thereby acquiring a full-body image of the user. The terminal also has a display as a means of displaying, which displays a three-dimensional model of the item selected by the user. By using augmented reality means to overlay these three-dimensional models onto the user's body image, virtual try-on is realized.

[0205] The device is equipped with emotion analysis capabilities, using software such as OpenCV and DeepFace to analyze the user's facial expressions and voice, and determine their emotional state in real time. This allows it to recognize emotions such as joy, surprise, and sadness. This emotion data is then transmitted from the device to a server.

[0206] The server uses artificial intelligence processing to generate styling suggestions based on received sentiment data. The server also combines past history and trend information to provide the user with the most suitable styling suggestions. The generated styling suggestions are displayed on the terminal's screen via a presentation device.

[0207] For example, when a user smiles, the server might suggest a casual, brightly colored outfit. This is the most appropriate suggestion based on the user's emotional state, providing a personalized shopping experience for each individual user. The system is designed to facilitate a smooth fitting and purchase process that reflects emotions.

[0208] An example of a prompt in a generative AI model is: "I am designing a fashion app using an emotion engine. Please suggest what dataset and algorithms I should use to build an AI model that suggests casual, bright-toned styling when it detects a user's smile."

[0209] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0210] Step 1:

[0211] The user takes a full-body photograph using the device. The device's camera is used, and the user presses the capture button when their posture is straight to acquire a full-body image as input data. A high-resolution user image is generated as output.

[0212] Step 2:

[0213] Within the terminal, a three-dimensional model of an item selected by the user is displayed via a display device. This model is selected from a pre-stored database. The input is information about the item selected by the user, and the output is a visual display of the three-dimensional item model on the screen.

[0214] Step 3:

[0215] The device uses augmented reality (AR) technology to overlay a three-dimensional object model onto the acquired full-body image. The input consists of the output images from steps 1 and 2. AR technology is used to synthesize the images, and the output displays the object image in real-time as if it were being worn on the user's body.

[0216] Step 4:

[0217] The device collects user emotions using emotion analysis tools and analyzes facial expressions and voice. Input is real-time data captured through the camera and microphone. Using libraries such as OpenCV and DeepFace, the input data is analyzed and an emotional state (e.g., joy, sadness) is obtained as output.

[0218] Step 5:

[0219] The device sends emotional data to the server. The input is data containing the user's emotional state, and the output is the state sent to the server.

[0220] Step 6:

[0221] The server generates styling suggestions using artificial intelligence processing based on received sentiment data, past history, and trend information. The input consists of the user's sentiment, history, and trend information. The server analyzes this data and uses machine learning algorithms to output optimal styling suggestions.

[0222] Step 7:

[0223] The generated styling suggestions are sent from the server to the terminal's display and viewed by the user on the display. The input is the styling suggestions sent from the server, and the output is their visual presentation.

[0224] Step 8:

[0225] When a user selects an item they like, they proceed with the purchase through e-commerce using the terminal. The input is the user's purchase decision information, and the output is the status after the purchase process is completed.

[0226] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0227] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0228] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0229] [Second Embodiment]

[0230] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0231] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0232] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0233] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0234] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0235] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0236] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0237] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0238] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0239] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0240] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0241] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0242] This invention is a system that allows users to virtually try on clothes and accessories using a smartphone or tablet. The user takes a full-body photo using the device's camera and selects products. The device generates a three-dimensional model of the selected product and displays it overlaid on the user's image using augmented reality means.

[0243] In this process, the device adjusts the 3D model appropriately, taking into account the user's body shape and position. Next, the device sends this data to a server, which analyzes the received data using artificial intelligence processing. The server then takes into account the user's past purchase history and current fashion trends to generate optimal styling suggestions.

[0244] The generated styling suggestions are sent from the server to the terminal, which then presents the suggestions to the user. The user can continue virtual try-on based on this information. If the user is interested in purchasing, the terminal initiates the purchase process using e-commerce tools.

[0245] For example, if a user wants to choose and try on a new dress from the comfort of their home, the device will display a 3D model of the dress and suggest the best outfit based on AI styling recommendations. The user can then decide to purchase the dress based on this feedback and complete the purchase process on the device. This format allows for a satisfying shopping experience without the need for physical try-on.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user launches a dedicated application on their device, stands in a position where their entire body can be photographed, and activates the camera. The user then selects the clothes or accessories they want to try on within the app.

[0249] Step 2:

[0250] The device detects the user's body from real-time video footage captured by the camera and obtains 3D model data of the selected product. The device also uses augmented reality to overlay the product data onto the user's video.

[0251] Step 3:

[0252] The device adjusts the position and size of the 3D model in real time, taking into account the user's body shape and the fit of the selected product. It checks the degree of matching of each part to ensure a natural overlay.

[0253] Step 4:

[0254] The terminal transmits current video data and product selection information to the server. The data also includes user-specific body type information and product attribute information.

[0255] Step 5:

[0256] The server uses an AI agent to analyze the transmitted data. The server references the user's past purchase history and current fashion trends to generate optimal styling suggestions.

[0257] Step 6:

[0258] The server sends the generated styling suggestions to the terminal. The suggestions include specific information about accessories and other clothing combinations that would suit the product.

[0259] Step 7:

[0260] The device displays the received styling suggestions to the user on the screen. The user continues trying on clothes based on the displayed suggestions, selecting other items or adjusting the fit as needed.

[0261] Step 8:

[0262] If the user decides to make a purchase, the device initiates the purchase process through e-commerce. The device sends the necessary information to the server and processes the payment.

[0263] Step 9:

[0264] The server processes the purchase information and arranges for product shipment. The user receives a purchase completion notification via their device.

[0265] (Example 1)

[0266] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0267] Traditional online shopping systems have faced challenges such as users being unable to actually try on products, leading to errors in product selection. Furthermore, it has been difficult to provide styling suggestions that take into account individual user body types and preferences, making it challenging to offer a truly satisfying shopping experience.

[0268] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0269] In this invention, the server includes means for photographing the user's body and acquiring images, means for generating a three-dimensional model using product information selected by the user, and means for transmitting the data to the server and generating styling suggestions using the generated AI model. This makes it possible for the user to virtually try on products that are appropriately adjusted to their body type and to receive styling suggestions based on their individual preferences.

[0270] "Means of photography" refers to a device or function for photographing the user's body and acquiring image data.

[0271] "Generation means" refers to the technology and equipment used to create a three-dimensional model of a product based on product information selected by the user.

[0272] "Augmented reality means" refers to technologies and systems that overlay virtual three-dimensional models onto images of the real world.

[0273] "Adjustment means" refers to a system that analyzes the user's body shape and has the function to automatically adjust the position and size of the displayed three-dimensional model appropriately.

[0274] "Analysis means" refers to a device or function that transmits data to a server and processes it to create styling suggestions for the user using a generated AI model.

[0275] "Notification means" refers to functions or devices for communicating generated styling suggestions to the user.

[0276] "Electronic commerce methods" refer to systems and technologies that enable users to complete the purchase process of selected goods online.

[0277] This invention provides a system that allows users to virtually try on clothes and accessories using their own devices, such as smartphones and tablets. The user takes a full-body photograph using the device's camera, and the system operates based on that image. The device is equipped with a high-resolution camera, a touchscreen, and a processor for utilizing augmented reality (AR) technology. Specifically, the device's camera system and AR framework (e.g., ARKit for iOS or ARCore for Android) are used to overlay product models onto images of the real world.

[0278] When a user selects a product, the terminal receives the product's digital information and generates a 3D model. This can be done using 3D modeling software (e.g., Blender or Unity). The generated model is then adjusted according to the user's body shape and displayed realistically. Image processing libraries (e.g., OpenCV) are used for this adjustment process.

[0279] The adjusted data is then sent from the terminal to the server. The server analyzes the received data using a generative AI model (e.g., TensorFlow or PyTorch). Based on the user's past purchase history and current trend information, the server provides optimal styling suggestions. These suggestions are important as part of a unique sales strategy.

[0280] For example, if a user wants to virtually try on a new dress and check the most suitable styling for themselves, the system will display the three-dimensional model of the dress on the user's video using AR technology and provide styling suggestions by AI. The suggestions include specific advice such as "Golden accessories match this red dress". Furthermore, if the user wishes to purchase, they can safely complete the payment procedure on the terminal. Through this series of processes, the user can enjoy an effective shopping experience while staying at home.

[0281] Examples of prompt sentences include "Please generate the latest styling suggestions for women in their 30s suitable for autumn fashion".

[0282] The flow of the specific process in Example 1 will be described using FIG. 11.

[0283] Step 1:

[0284] The user uses the camera of the terminal to take a full-body photo. The input is a full-body image of the user. Based on this image, the terminal extracts the user's body shape data. Using an image processing library, basic dimensions such as shoulder width and height are measured, and body shape information is generated as the output.

[0285] Step 2:

[0286] The terminal receives the information of the product selected by the user and generates the corresponding three-dimensional model. The input is the identification information of the selected product. Based on this information, a model is generated using three-dimensional modeling software, and three-dimensional model data is created as the output.

[0287] Step 3:

[0288] The terminal adjusts the generated 3D model based on the user's body shape information. The inputs are the body shape information obtained in step 1 and the 3D model generated in step 2. Image processing technology is used to appropriately adjust the size and angle of the model, generating a model that fits the user as output.

[0289] Step 4:

[0290] The adjusted 3D model is displayed on the device by overlaying it onto the user's video using augmented reality. The input is the adjusted 3D model data. Using the device's AR framework, the model is overlaid on the video in real time, generating an output video to be displayed to the user.

[0291] Step 5:

[0292] The terminal sends the adjusted data to the server. The input consists of the adjusted 3D model and the user's body shape information. A data transmission communication protocol is used to generate the data that the server receives as output.

[0293] Step 6:

[0294] The server generates styling suggestions using an AI model based on the received data. The input is data sent from the terminal. The AI ​​model refers to purchase history and trend information in the database to generate appropriate styling suggestions and outputs styling suggestion data.

[0295] Step 7:

[0296] The server sends the generated styling suggestions to the terminal. The input is the generated styling suggestion data. Depending on the presentation method, communication means are used to appropriately deliver the suggestions to the user, and data is generated that is received by the terminal as output.

[0297] Step 8:

[0298] The terminal presents the received styling suggestions to the user. The input is the received styling suggestion data. The terminal's display is used to show the information, providing the user with visual feedback as output.

[0299] Step 9:

[0300] If the user decides to make a purchase, the terminal initiates the purchase process using e-commerce methods. The input is the user's purchase decision information. The payment app on the terminal is launched to execute the purchase process, and a purchase completion notification is generated as output.

[0301] (Application Example 1)

[0302] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0303] In modern virtual stores, it is difficult for users to make satisfactory purchase decisions without physically trying on items. Furthermore, online shopping often lacks appropriate styling suggestions and recommendations for related products, resulting in a limited user experience.

[0304] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0305] In this invention, the server includes a means for capturing images of the user's body, an augmented reality means for overlaying and displaying selected objects, and a machine learning processing means for generating styling suggestions. This allows the user to try out appropriate outfits from the comfort of their home, receive recommendations for related products, and improve their shopping experience.

[0306] "Photography means" refers to a digital imaging device used to acquire an image of the user's body.

[0307] The "display means" is a device or software for visually presenting the three-dimensional structure of an object selected by the user.

[0308] The "augmented reality means" is a technology that overlays digital objects on real-world images to provide users with a virtual experience.

[0309] The "machine learning processing means" is a component of artificial intelligence used to analyze data and automatically generate styling proposals suitable for the user.

[0310] The "presentation means" is a method for visually or auditorily presenting the generated styling proposals to the user.

[0311] The "online trading means" is a digital platform and related technologies used to execute the sale and purchase of goods through the Internet.

[0312] The "recommendation means" is an AI-based system used to propose relevant additional items based on the user's preferences and history.

[0313] Regarding the embodiments for implementing the invention, the present invention is a system that provides an experience from when the user overlays and displays an object selected for their own image from a remote location such as home until they obtain a styling proposal and proceed to purchase. This system is configured as follows.

[0314] First, the user uses a terminal equipped with a photographing device (e.g., a smartphone or tablet) to photograph themselves. At this time, the terminal utilizes the camera function to photograph the user's entire body. Next, the terminal uses a display device to display the three-dimensional structure of the object selected by the user. At this time, the terminal uses AR technology to overlay digital objects on the real-world image. Specifically, software platforms such as ARKit or ARCore are utilized.

[0315] Furthermore, the device transmits the acquired data to a remote server. The server utilizes cloud-based AI processing services (e.g., Google Cloud AI or AWS AI) and machine learning models to generate styling suggestions based on the received user data. This generation process involves analysis based on the user's past purchase history and the latest fashion trends. The generated suggestions are then displayed on the device via a presentation system.

[0316] When a user becomes interested in a styling suggestion, they can purchase the product through online transactions on their device. An e-commerce platform is used in this process.

[0317] A concrete example is a scenario where a user uses the "Smart Closet" application to try on new clothes and check AI styling suggestions. These suggestions may include combinations with previously purchased items or coordinated outfits optimized for the user's individual preferences.

[0318] An example of a prompt to input into the AI ​​model would be, "Based on the user's past purchase history, please generate the best styling suggestions for this dress. Also, please consider current fashion trends." This would allow users to easily enjoy fashion coordination at home without having to physically try on clothes.

[0319] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0320] Step 1:

[0321] The user activates the device's camera and takes a full-body picture. The input is real-time video data, and the output is an image of the user. This image forms the basis for subsequent augmented reality processing. Specifically, the user positions the device at an appropriate distance and positions their image within the screen.

[0322] Step 2:

[0323] The device displays a 3D model of the product selected by the user. The input is the digital data of the selected object, and the output is a display of that 3D model superimposed on the user's image. Augmented reality technologies using ARKit or ARCore are used for data processing. Specifically, the 3D model is adjusted to match the user's body shape and orientation and superimposed on the real-world image.

[0324] Step 3:

[0325] The system sends user image data and object selection data to the server. The input is the user's image and selection data, and the output is the result of the transmission to the server. Specifically, the terminal uses an internet connection to upload the data to the remote server.

[0326] Step 4:

[0327] The server generates styling suggestions based on the received data. Inputs include past purchase history, current fashion trends, and user image data, while output is styling suggestions. This process uses a generative AI model to perform data analysis and suggestion generation based on prompt messages.

[0328] Step 5:

[0329] The generated styling suggestions are sent from the server to the terminal. The input is the styling suggestions generated on the server, and the output is the suggestion data received by the terminal. Specifically, the data is transmitted to the terminal again via the internet connection.

[0330] Step 6:

[0331] The terminal receives suggestion data and presents it to the user. The input is suggestion data sent from the server, and the output is styling suggestions displayed on the terminal screen. The user views this information and decides whether to continue trying on clothes or consider purchasing.

[0332] Step 7:

[0333] If the user decides to purchase, the terminal will process the purchase through an online transaction method. The input is the user's intention to purchase and the selected product information, and the output is a confirmation that the transaction is complete. Specifically, the terminal enters payment information and completes the purchase through the online transaction platform.

[0334] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0335] This invention is a system that allows users to virtually try on clothes and accessories via a smartphone or tablet, and combines an emotion engine to provide styling suggestions based on the user's emotions. First, the user takes a full-body photo using the device's camera. The device generates three-dimensional models of the clothes and accessories, and uses augmented reality technology to overlay the models of the selected items onto the user's image.

[0336] In this system, the device incorporates an emotion engine that analyzes the user's facial expressions and voice to recognize emotions in real time. The emotion engine can determine emotional states such as joy, surprise, and sadness from facial features and voice tone.

[0337] The device then sends the fitting data, along with the acquired emotional information, to the server. The server uses artificial intelligence processing to analyze this data and generates optimal styling suggestions that take into account the user's past history, current fashion trends, and emotional state. For example, if the user expresses surprise, the server will suggest a new style or provide a bolder combination of fashion items.

[0338] The generated styling suggestions are sent to the device and presented to the user. The user can continue trying on clothes based on these suggestions. Furthermore, if the user wishes to purchase, the device can proceed with the purchase process via e-commerce. This format allows the user to have a personalized try-on experience that reflects their emotions, improving shopping satisfaction. For example, if the user has a cheerful expression, they may receive more casual and colorful suggestions, allowing them to shop in a way that suits their mood.

[0339] The following describes the processing flow.

[0340] Step 1:

[0341] The user launches a dedicated application on their device and uses the camera in a position where their entire body can be photographed. The user then selects the items they wish to try on from within the app.

[0342] Step 2:

[0343] The device analyzes camera footage in real time to detect the user's body. It also acquires a 3D model of the selected product and overlays it onto the user's body using augmented reality.

[0344] Step 3:

[0345] The device activates an emotion engine to analyze the user's facial expressions and voice. The emotion engine analyzes facial features and voice tone to identify the emotional state. For example, if a smile is detected, it determines that the user is "happy."

[0346] Step 4:

[0347] The device sends the user's body shape data, selected product information, and detected emotion data to the server. This allows the server to receive diverse information all at once.

[0348] Step 5:

[0349] The server uses an AI agent to analyze the received data. The server combines emotional information, past history, and trend information to generate optimal styling suggestions for the user. For example, if the user expresses surprise, the server will consider new styles or bolder suggestions.

[0350] Step 6:

[0351] The server sends the generated styling suggestions to the terminal. In addition to standard styling suggestions, the server's suggestions may include special elements tailored to the user's mood.

[0352] Step 7:

[0353] The device displays the received styling suggestions on its screen and presents them to the user. The user can then try on the clothes again or try a different style based on the information presented.

[0354] Step 8:

[0355] If the user is satisfied with the suggested style and wishes to purchase it, the device will display an e-commerce form and proceed with the purchase process.

[0356] Step 9:

[0357] The server processes the purchase information sent from the terminal and initiates the shipping process for the goods. This allows the user to receive a notification that the purchase is complete.

[0358] (Example 2)

[0359] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0360] Conventional virtual try-on systems have the problem of not being able to improve individual satisfaction because they simply suggest clothing and accessory styling without considering the user's emotions. Furthermore, styling suggestions are one-way and cannot be optimized according to the user's emotions, resulting in the problem of not being able to provide the truly optimal style for the user.

[0361] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0362] In this invention, the server includes emotion analysis means for analyzing the user's emotions, artificial intelligence processing means for transmitting data to the server and generating styling suggestions considering the emotional information, and presentation means for presenting the generated styling suggestions to the user. This enables personalized styling suggestions based on the user's emotions, thereby improving user satisfaction.

[0363] "Photography equipment" refers to a device equipped with the function of acquiring the user's body as image data.

[0364] A "generation means" is a device that has the function of constructing a three-dimensional model of clothing or accessories based on acquired image data.

[0365] "Augmented reality means" refers to devices that enable the real-time visual display of a three-dimensional model superimposed onto the user's body.

[0366] An "emotion analysis device" is a device that has the function of analyzing a user's facial expressions and voice to determine their emotional state.

[0367] "Artificial intelligence processing means" refers to a system that generates styling suggestions using a learning algorithm based on data received by the server.

[0368] A "presentation means" is a device for visually or audibly communicating the generated styling suggestions to the user.

[0369] An "electronic transaction method" is a system that has the functionality to allow users to complete the purchase process of selected goods online.

[0370] This invention is a system that allows users to virtually try on clothes and accessories using a mobile information terminal such as a smartphone or tablet. The terminal is equipped with advanced imaging, generation, augmented reality, and emotion analysis capabilities.

[0371] First, the user takes a picture of their body using the device's camera. The camera function is utilized to obtain high-resolution and accurate image data. Next, the acquired image data is sent to a generation system, where a three-dimensional model of clothing and accessories is automatically generated. 3D modeling software and libraries (e.g., Blender or Autodesk Maya) are used for this generation.

[0372] Next, augmented reality (AR) technology kicks in, overlaying the generated 3D model onto the user's image in real time. AR technology is used for this display, with ARKit and ARCore being representative examples.

[0373] Furthermore, the device incorporates emotion analysis capabilities. This device uses face recognition and voice analysis libraries (e.g., OpenCV and Microsoft Azure Face API) to analyze the user's facial expressions and voice in real time and determine emotions such as joy and surprise.

[0374] The fitting data and sentiment information collected together are sent from the terminal to the server. The server uses artificial intelligence processing tools to analyze this data. For this purpose, machine learning frameworks (e.g., TensorFlow and PyTorch) are used. The server considers the user's past history, current fashion information, and sentiment analysis results to generate optimal styling suggestions.

[0375] The generated styling suggestions are sent to the terminal and presented to the user through a display device. This allows the user to review the styles and continue trying them on. Furthermore, when the user purchases the selected items, the terminal's electronic transaction device is used to complete the online payment.

[0376] For example, if the user has a cheerful expression, the system will suggest a casual, brightly colored style. An example of such a prompt would be, "Please generate a recommended style, taking into account the emotions the user has expressed."

[0377] This system enables users to enjoy a personalized try-on experience tailored to their own feelings, thereby improving shopping satisfaction.

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] The user activates the device's camera and takes a picture of their body. The input data is the image acquired through the device's camera. This image data is high resolution and accurately captures the user's entire body. An image file is generated as output.

[0381] Step 2:

[0382] The device generates three-dimensional models of clothing and accessories using captured image data. The input is the user's image data, and the output is the data of the three-dimensional model. 3D modeling software is used to generate the three-dimensional model. Specifically, it analyzes the acquired images and adjusts the model to match the position and size of the human body.

[0383] Step 3:

[0384] The device uses augmented reality technology to overlay a generated 3D model onto the user's image. The input consists of the 3D model data and the user's image data, while the output is a virtual try-on image displayed in augmented reality. Specifically, the model is displayed in real-time, adapting to the user's movements, providing a natural try-on experience.

[0385] Step 4:

[0386] The device uses a camera and microphone to analyze the user's emotions. Input is the user's facial expressions and voice data. Output is the analyzed emotional state (joy, surprise, sadness, etc.). Specifically, a process is performed to analyze facial features and voice tone to determine emotions in real time.

[0387] Step 5:

[0388] The device sends fitting data and emotional data to the server. The input is this data, and the output is the information transferred to the server. Specifically, the HTTPS protocol is used for secure data transmission.

[0389] Step 6:

[0390] The server generates styling suggestions using an AI model based on the received data. Inputs include user try-on data, emotional state, past history, and trend information. The output is a styling suggestion optimized for the user. Specifically, it utilizes machine learning algorithms to analyze data from multiple perspectives.

[0391] Step 7:

[0392] The server sends the generated styling suggestions to the terminal. The input is the styling suggestion data. The output is the suggestion sent to the terminal. Specifically, the server converts the suggested content into a format suitable for external presentations and prepares it for clear presentation to the user.

[0393] Step 8:

[0394] The terminal presents the transmitted styling suggestions to the user. The input is the styling suggestion data. The output is suggestion information that the user can visually confirm. Specifically, it displays the suggestions on the screen, allowing the user to continue trying on clothes interactively.

[0395] Step 9:

[0396] When a user purchases a product, the terminal uses electronic transaction methods to complete the purchase process. Inputs include the user's purchase intention and payment information. Output is the completed purchase transaction. Specifically, a secure online payment is processed based on the user's expressed intention.

[0397] (Application Example 2)

[0398] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0399] Conventional virtual try-on systems were unable to offer styling suggestions that took into account the user's emotions, and could only provide uniform suggestions. Therefore, a challenge was that it was difficult to provide a personalized experience tailored to the individual circumstances of each user.

[0400] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0401] In this invention, the server includes emotion analysis means for analyzing facial expressions and voice to recognize the user's emotional state, artificial intelligence processing means for generating styling suggestions based on the user's emotional state, and presentation means for presenting the generated styling suggestions to the user. This enables personalized styling suggestions that reflect the user's emotions.

[0402] "Means of photography" refers to a device or function for photographing the user's body, and includes devices such as cameras.

[0403] "Display means" refers to a device or function for visually presenting a three-dimensional model of an item selected by the user, and includes devices such as displays and monitors.

[0404] "Augmented reality means" refers to a technology or device for superimposing selected objects onto a user's body, and is a technology that uses augmented reality technology to superimpose the virtual and real worlds.

[0405] "Emotional analysis means" refers to a technology or device for recognizing a user's emotional state by analyzing their facial expressions and voice.

[0406] "Artificial intelligence processing means" refers to a technology for processing data and generating styling suggestions based on the user's emotional state, and involves processing using machine learning algorithms.

[0407] "Presentation means" refers to a device or function for providing the generated styling suggestions to the user visually or audibly, and includes devices such as displays and speakers.

[0408] This invention is implemented as a system using a terminal and a server. The terminal is equipped with a camera as a means of capturing images of the user's body, thereby acquiring a full-body image of the user. The terminal also has a display as a means of displaying, which displays a three-dimensional model of the item selected by the user. By using augmented reality means to overlay these three-dimensional models onto the user's body image, virtual try-on is realized.

[0409] The device is equipped with emotion analysis capabilities, using software such as OpenCV and DeepFace to analyze the user's facial expressions and voice, and determine their emotional state in real time. This allows it to recognize emotions such as joy, surprise, and sadness. This emotion data is then transmitted from the device to a server.

[0410] The server uses artificial intelligence processing to generate styling suggestions based on received sentiment data. The server also combines past history and trend information to provide the user with the most suitable styling suggestions. The generated styling suggestions are displayed on the terminal's screen via a presentation device.

[0411] For example, when a user smiles, the server might suggest a casual, brightly colored outfit. This is the most appropriate suggestion based on the user's emotional state, providing a personalized shopping experience for each individual user. The system is designed to facilitate a smooth fitting and purchase process that reflects emotions.

[0412] An example of a prompt in a generative AI model is: "I am designing a fashion app using an emotion engine. Please suggest what dataset and algorithms I should use to build an AI model that suggests casual, bright-toned styling when it detects a user's smile."

[0413] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0414] Step 1:

[0415] The user takes a full-body photograph using the device. The device's camera is used, and the user presses the capture button when their posture is straight to acquire a full-body image as input data. A high-resolution user image is generated as output.

[0416] Step 2:

[0417] Within the terminal, a three-dimensional model of an item selected by the user is displayed via a display device. This model is selected from a pre-stored database. The input is information about the item selected by the user, and the output is a visual display of the three-dimensional item model on the screen.

[0418] Step 3:

[0419] The device uses augmented reality (AR) technology to overlay a three-dimensional object model onto the acquired full-body image. The input consists of the output images from steps 1 and 2. AR technology is used to synthesize the images, and the output displays the object image in real-time as if it were being worn on the user's body.

[0420] Step 4:

[0421] The device collects user emotions using emotion analysis tools and analyzes facial expressions and voice. Input is real-time data captured through the camera and microphone. Using libraries such as OpenCV and DeepFace, the input data is analyzed and an emotional state (e.g., joy, sadness) is obtained as output.

[0422] Step 5:

[0423] The device sends emotional data to the server. The input is data containing the user's emotional state, and the output is the state sent to the server.

[0424] Step 6:

[0425] The server generates styling suggestions using artificial intelligence processing based on received sentiment data, past history, and trend information. The input consists of the user's sentiment, history, and trend information. The server analyzes this data and uses machine learning algorithms to output optimal styling suggestions.

[0426] Step 7:

[0427] The generated styling suggestions are sent from the server to the terminal's display and viewed by the user on the display. The input is the styling suggestions sent from the server, and the output is their visual presentation.

[0428] Step 8:

[0429] When a user selects an item they like, they proceed with the purchase through e-commerce using the terminal. The input is the user's purchase decision information, and the output is the status after the purchase process is completed.

[0430] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0431] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0432] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0433] [Third Embodiment]

[0434] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0435] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0436] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0437] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0438] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0439] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0440] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0441] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0442] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0443] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0444] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0445] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0446] This invention is a system that allows users to virtually try on clothes and accessories using a smartphone or tablet. The user takes a full-body photo using the device's camera and selects products. The device generates a three-dimensional model of the selected product and displays it overlaid on the user's image using augmented reality means.

[0447] In this process, the device adjusts the 3D model appropriately, taking into account the user's body shape and position. Next, the device sends this data to a server, which analyzes the received data using artificial intelligence processing. The server then takes into account the user's past purchase history and current fashion trends to generate optimal styling suggestions.

[0448] The generated styling suggestions are sent from the server to the terminal, which then presents the suggestions to the user. The user can continue virtual try-on based on this information. If the user is interested in purchasing, the terminal initiates the purchase process using e-commerce tools.

[0449] For example, if a user wants to choose and try on a new dress from the comfort of their home, the device will display a 3D model of the dress and suggest the best outfit based on AI styling recommendations. The user can then decide to purchase the dress based on this feedback and complete the purchase process on the device. This format allows for a satisfying shopping experience without the need for physical try-on.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] The user launches a dedicated application on their device, stands in a position where their entire body can be photographed, and activates the camera. The user then selects the clothes or accessories they want to try on within the app.

[0453] Step 2:

[0454] The device detects the user's body from real-time video footage captured by the camera and obtains 3D model data of the selected product. The device also uses augmented reality to overlay the product data onto the user's video.

[0455] Step 3:

[0456] The device adjusts the position and size of the 3D model in real time, taking into account the user's body shape and the fit of the selected product. It checks the degree of matching of each part to ensure a natural overlay.

[0457] Step 4:

[0458] The terminal transmits current video data and product selection information to the server. The data also includes user-specific body type information and product attribute information.

[0459] Step 5:

[0460] The server uses an AI agent to analyze the transmitted data. The server refers to the user's past purchase history and current fashion trends to generate optimal styling suggestions.

[0461] Step 6:

[0462] The server sends the generated styling suggestions to the terminal. The suggestions include specific information about accessories and other clothing combinations that would suit the product.

[0463] Step 7:

[0464] The device displays the received styling suggestions to the user on the screen. The user continues trying on clothes based on the displayed suggestions, selecting other items or adjusting the fit as needed.

[0465] Step 8:

[0466] If the user decides to make a purchase, the device initiates the purchase process through e-commerce. The device sends the necessary information to the server and processes the payment.

[0467] Step 9:

[0468] The server processes the purchase information and arranges for product shipment. The user receives a purchase completion notification via their device.

[0469] (Example 1)

[0470] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0471] Traditional online shopping systems have faced challenges such as users being unable to actually try on products, leading to errors in product selection. Furthermore, it has been difficult to provide styling suggestions that take into account individual user body types and preferences, making it challenging to offer a truly satisfying shopping experience.

[0472] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0473] In this invention, the server includes means for photographing the user's body and acquiring images, means for generating a three-dimensional model using product information selected by the user, and means for transmitting the data to the server and generating styling suggestions using the generated AI model. This makes it possible for the user to virtually try on products that are appropriately adjusted to their body type and to receive styling suggestions based on their individual preferences.

[0474] "Means of photography" refers to a device or function for photographing the user's body and acquiring image data.

[0475] "Generation means" refers to the technology and equipment used to create a three-dimensional model of a product based on product information selected by the user.

[0476] "Augmented reality means" refers to technologies and systems that overlay virtual three-dimensional models onto images of the real world.

[0477] "Adjustment means" refers to a system that analyzes the user's body shape and automatically adjusts the position and size of the displayed three-dimensional model appropriately.

[0478] "Analysis means" refers to a device or function that transmits data to a server and processes it to create styling suggestions for the user using a generated AI model.

[0479] "Notification means" refers to functions or devices for communicating generated styling suggestions to the user.

[0480] "Electronic commerce methods" refer to systems and technologies that enable users to complete the purchase process of selected goods online.

[0481] This invention provides a system that allows users to virtually try on clothes and accessories using their own devices, such as smartphones and tablets. The user takes a full-body photograph using the device's camera, and the system operates based on that image. The device is equipped with a high-resolution camera, a touchscreen, and a processor for utilizing augmented reality (AR) technology. Specifically, the device's camera system and AR framework (e.g., ARKit for iOS or ARCore for Android) are used to overlay product models onto images of the real world.

[0482] When a user selects a product, the terminal receives the product's digital information and generates a 3D model. This can be done using 3D modeling software (e.g., Blender or Unity). The generated model is then adjusted according to the user's body shape and displayed realistically. Image processing libraries (e.g., OpenCV) are used for this adjustment process.

[0483] The adjusted data is then sent from the terminal to the server. The server analyzes the received data using a generative AI model (e.g., TensorFlow or PyTorch). Based on the user's past purchase history and current trend information, the server provides optimal styling suggestions. These suggestions are important as part of a unique sales strategy.

[0484] For example, if a user wants to virtually try on a new dress and find the best styling for them, the system uses AR technology to display a 3D model of the dress on the user's screen and provides AI-powered styling suggestions. These suggestions include specific advice such as, "Gold accessories would go well with this red dress." Furthermore, if the user wishes to purchase the dress, they can securely complete the payment process on their device. This entire process allows users to enjoy an effective shopping experience from the comfort of their homes.

[0485] Examples of prompts include, "Generate the latest styling suggestions for women in their 30s that are suitable for autumn fashion."

[0486] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0487] Step 1:

[0488] The user takes a full-body photo using the device's camera. The input is a full-body image of the user. The device extracts the user's body shape data from this image. Using an image processing library, it measures basic dimensions such as shoulder width and height, and generates body shape information as output.

[0489] Step 2:

[0490] The terminal receives information about the product selected by the user and generates a corresponding 3D model. The input is the identification information of the selected product. Based on this information, a model is generated using 3D modeling software, and 3D model data is created as output.

[0491] Step 3:

[0492] The terminal adjusts the generated 3D model based on the user's body shape information. The inputs are the body shape information obtained in step 1 and the 3D model generated in step 2. Image processing technology is used to appropriately adjust the size and angle of the model, generating a model that fits the user as output.

[0493] Step 4:

[0494] The adjusted 3D model is displayed on the device by overlaying it onto the user's video using augmented reality. The input is the adjusted 3D model data. Using the device's AR framework, the model is overlaid on the video in real time, generating an output video to be displayed to the user.

[0495] Step 5:

[0496] The terminal sends the adjusted data to the server. The input consists of the adjusted 3D model and the user's body shape information. A data transmission communication protocol is used to generate the data that the server receives as output.

[0497] Step 6:

[0498] The server generates styling suggestions using an AI model based on the received data. The input is data sent from the terminal. The AI ​​model refers to purchase history and trend information in the database to generate appropriate styling suggestions and outputs styling suggestion data.

[0499] Step 7:

[0500] The server sends the generated styling suggestions to the terminal. The input is the generated styling suggestion data. Depending on the presentation method, communication means are used to appropriately deliver the suggestions to the user, and data is generated that is received by the terminal as output.

[0501] Step 8:

[0502] The terminal presents the received styling suggestions to the user. The input is the received styling suggestion data. The terminal's display is used to show the information, providing the user with visual feedback as output.

[0503] Step 9:

[0504] If the user decides to make a purchase, the terminal initiates the purchase process using e-commerce methods. The input is the user's purchase decision information. The payment app on the terminal is launched to execute the purchase process, and a purchase completion notification is generated as output.

[0505] (Application Example 1)

[0506] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0507] In modern virtual stores, it is difficult for users to make satisfactory purchase decisions without physically trying on items. Furthermore, online shopping often lacks appropriate styling suggestions and recommendations for related products, resulting in a limited user experience.

[0508] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0509] In this invention, the server includes a means for capturing images of the user's body, an augmented reality means for overlaying and displaying selected objects, and a machine learning processing means for generating styling suggestions. This allows the user to try out appropriate outfits from the comfort of their home, receive recommendations for related products, and improve their shopping experience.

[0510] "Photography means" refers to a digital imaging device used to acquire an image of the user's body.

[0511] "Display means" refers to a device or software for visually showing the three-dimensional structure of an object selected by the user.

[0512] "Augmented reality" refers to a technology that overlays digital objects onto images of the real world, providing users with a virtual experience.

[0513] "Machine learning processing means" refers to components of artificial intelligence used to analyze data and automatically generate styling suggestions suitable for the user.

[0514] "Presentation means" refers to a method for visually or audibly showing the generated styling suggestions to the user.

[0515] "Online trading methods" refer to digital platforms and related technologies used to buy and sell goods via the internet.

[0516] A "recommendation system" is an artificial intelligence-based system used to suggest additional relevant items based on the user's preferences and history.

[0517] Regarding embodiments for carrying out the invention, the present invention is a system that allows a user to view selected objects superimposed onto their own image from a remote location such as their home, and provides an experience from receiving styling suggestions to making a purchase. This system is configured as follows.

[0518] First, the user takes a picture of themselves using a device equipped with a camera (e.g., a smartphone or tablet). The device uses its camera function to capture the user's entire body. Next, the device uses a display to show the three-dimensional structure of an object selected by the user. At this point, the device uses AR technology to overlay the digital object onto the real-world image. Specifically, software platforms such as ARKit and ARCore are used.

[0519] Furthermore, the device transmits the acquired data to a remote server. The server utilizes cloud-based AI processing services (e.g., Google Cloud AI or AWS AI) and machine learning models to generate styling suggestions based on the received user data. This generation process involves analysis based on the user's past purchase history and the latest fashion trends. The generated suggestions are then displayed on the device via a presentation system.

[0520] When a user becomes interested in a styling suggestion, they can purchase the product through online transactions on their device. An e-commerce platform is used in this process.

[0521] A concrete example is a scenario where a user uses the "Smart Closet" application to try on new clothes and check AI styling suggestions. These suggestions may include combinations with previously purchased items or coordinated outfits optimized for the user's individual preferences.

[0522] An example of a prompt to input into the AI ​​model would be, "Based on the user's past purchase history, please generate the best styling suggestions for this dress. Also, please consider current fashion trends." This would allow users to easily enjoy fashion coordination at home without having to physically try on clothes.

[0523] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0524] Step 1:

[0525] The user activates the device's camera and takes a full-body picture. The input is real-time video data, and the output is an image of the user. This image forms the basis for subsequent augmented reality processing. Specifically, the user positions the device at an appropriate distance and positions their image within the screen.

[0526] Step 2:

[0527] The device displays a 3D model of the product selected by the user. The input is the digital data of the selected object, and the output is a display of that 3D model superimposed on the user's image. Augmented reality technologies using ARKit or ARCore are used for data processing. Specifically, the 3D model is adjusted to match the user's body shape and orientation and superimposed on the real-world image.

[0528] Step 3:

[0529] The system sends user image data and object selection data to the server. The input is the user's image and selection data, and the output is the result of the transmission to the server. Specifically, the terminal uses an internet connection to upload the data to the remote server.

[0530] Step 4:

[0531] The server generates styling suggestions based on the received data. Inputs include past purchase history, current fashion trends, and user image data, while output is styling suggestions. This process uses a generative AI model to perform data analysis and suggestion generation based on prompt messages.

[0532] Step 5:

[0533] The generated styling suggestions are sent from the server to the terminal. The input is the styling suggestions generated on the server, and the output is the suggestion data received by the terminal. Specifically, the data is transmitted to the terminal again via the internet connection.

[0534] Step 6:

[0535] The terminal receives suggestion data and presents it to the user. The input is suggestion data sent from the server, and the output is styling suggestions displayed on the terminal screen. The user views this information and decides whether to continue trying on clothes or consider purchasing.

[0536] Step 7:

[0537] If the user decides to purchase, the terminal will process the purchase through an online transaction method. The input is the user's intention to purchase and the selected product information, and the output is a confirmation that the transaction is complete. Specifically, the terminal enters payment information and completes the purchase through the online transaction platform.

[0538] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0539] This invention is a system that allows users to virtually try on clothes and accessories via a smartphone or tablet, and combines an emotion engine to provide styling suggestions based on the user's emotions. First, the user takes a full-body photo using the device's camera. The device generates three-dimensional models of the clothes and accessories, and uses augmented reality technology to overlay the models of the selected items onto the user's image.

[0540] In this system, the device incorporates an emotion engine that analyzes the user's facial expressions and voice to recognize emotions in real time. The emotion engine can determine emotional states such as joy, surprise, and sadness from facial features and voice tone.

[0541] The device then sends the fitting data, along with the acquired emotional information, to the server. The server uses artificial intelligence processing to analyze this data and generates optimal styling suggestions that take into account the user's past history, current fashion trends, and emotional state. For example, if the user expresses surprise, the server will suggest a new style or provide a bolder combination of fashion items.

[0542] The generated styling suggestions are sent to the device and presented to the user. The user can continue trying on clothes based on these suggestions. Furthermore, if the user wishes to purchase, the device can proceed with the purchase process via e-commerce. This format allows the user to have a personalized try-on experience that reflects their emotions, improving shopping satisfaction. For example, if the user has a cheerful expression, they may receive more casual and colorful suggestions, allowing them to shop in a way that suits their mood.

[0543] The following describes the processing flow.

[0544] Step 1:

[0545] The user launches a dedicated application on their device and uses the camera in a position where their entire body can be photographed. The user then selects the items they wish to try on from within the app.

[0546] Step 2:

[0547] The device analyzes camera footage in real time to detect the user's body. It also acquires a 3D model of the selected product and overlays it onto the user's body using augmented reality.

[0548] Step 3:

[0549] The device activates an emotion engine to analyze the user's facial expressions and voice. The emotion engine analyzes facial features and voice tone to identify the emotional state. For example, if a smile is detected, it determines that the user is "happy."

[0550] Step 4:

[0551] The device sends the user's body shape data, selected product information, and detected emotion data to the server. This allows the server to receive diverse information all at once.

[0552] Step 5:

[0553] The server uses an AI agent to analyze the received data. The server combines emotional information, past history, and trend information to generate optimal styling suggestions for the user. For example, if the user expresses surprise, the server will consider new styles or bold suggestions.

[0554] Step 6:

[0555] The server sends the generated styling suggestions to the terminal. In addition to standard styling suggestions, the server's suggestions may include special elements tailored to the user's mood.

[0556] Step 7:

[0557] The device displays the received styling suggestions on the screen and presents them to the user. The user can then try on the clothes again or try a different style based on the information presented.

[0558] Step 8:

[0559] If the user is satisfied with the suggested style and wishes to purchase it, the device will display an e-commerce form and proceed with the purchase process.

[0560] Step 9:

[0561] The server processes the purchase information sent from the terminal and initiates the shipping process for the goods. This allows the user to receive a notification that the purchase is complete.

[0562] (Example 2)

[0563] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0564] Conventional virtual try-on systems have the problem of not being able to improve individual satisfaction because they simply suggest clothing and accessory styling without considering the user's emotions. Furthermore, styling suggestions are one-way and cannot be optimized according to the user's emotions, resulting in the problem of not being able to provide the truly optimal style for the user.

[0565] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0566] In this invention, the server includes emotion analysis means for analyzing the user's emotions, artificial intelligence processing means for transmitting data to the server and generating styling suggestions considering the emotional information, and presentation means for presenting the generated styling suggestions to the user. This enables personalized styling suggestions based on the user's emotions, thereby improving user satisfaction.

[0567] "Photography equipment" refers to a device equipped with the function of acquiring the user's body as image data.

[0568] A "generation means" is a device that has the function of constructing a three-dimensional model of clothing or accessories based on acquired image data.

[0569] "Augmented reality means" refers to devices that enable the real-time visual display of a three-dimensional model superimposed onto the user's body.

[0570] An "emotion analysis device" is a device that has the function of analyzing a user's facial expressions and voice to determine their emotional state.

[0571] "Artificial intelligence processing means" refers to a system that generates styling suggestions using a learning algorithm based on data received by the server.

[0572] A "presentation means" is a device for visually or audibly communicating the generated styling suggestions to the user.

[0573] An "electronic transaction method" is a system that has the functionality to allow users to complete the purchase process of selected goods online.

[0574] This invention is a system that allows users to virtually try on clothes and accessories using a mobile information terminal such as a smartphone or tablet. The terminal is equipped with advanced imaging, generation, augmented reality, and emotion analysis capabilities.

[0575] First, the user takes a picture of their body using the device's camera. The camera function is utilized to obtain high-resolution and accurate image data. Next, the acquired image data is sent to a generation system, where a three-dimensional model of clothing and accessories is automatically generated. 3D modeling software and libraries (e.g., Blender or Autodesk Maya) are used for this generation.

[0576] Next, augmented reality (AR) technology kicks in, overlaying the generated 3D model onto the user's image in real time. AR technology is used for this display, with ARKit and ARCore being representative examples.

[0577] Furthermore, the device incorporates emotion analysis capabilities. This device uses face recognition and voice analysis libraries (e.g., OpenCV and Microsoft Azure Face API) to analyze the user's facial expressions and voice in real time and determine emotions such as joy and surprise.

[0578] The fitting data and sentiment information collected together are sent from the terminal to the server. The server uses artificial intelligence processing tools to analyze this data. For this purpose, machine learning frameworks (e.g., TensorFlow and PyTorch) are used. The server considers the user's past history, current fashion information, and sentiment analysis results to generate optimal styling suggestions.

[0579] The generated styling suggestions are sent to the terminal and presented to the user through a display device. This allows the user to review the styles and continue trying on clothes. Furthermore, when the user purchases selected items, the terminal's electronic transaction device is used to complete the online payment.

[0580] For example, if the user has a cheerful expression, the system will suggest a casual, brightly colored style. An example of such a prompt would be, "Please generate a recommended style, taking into account the emotions the user has expressed."

[0581] This system enables users to enjoy a personalized try-on experience tailored to their own feelings, thereby improving shopping satisfaction.

[0582] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0583] Step 1:

[0584] The user activates the device's camera and takes a picture of their body. The input data is the image acquired through the device's camera. This image data is high resolution and accurately captures the user's entire body. An image file is generated as output.

[0585] Step 2:

[0586] The device generates three-dimensional models of clothing and accessories using captured image data. The input is the user's image data, and the output is the data of the three-dimensional model. 3D modeling software is used to generate the three-dimensional model. Specifically, it analyzes the acquired images and adjusts the model to match the position and size of the human body.

[0587] Step 3:

[0588] The device uses augmented reality technology to overlay a generated 3D model onto the user's image. The input consists of the 3D model data and the user's image data, while the output is a virtual try-on image displayed in augmented reality. Specifically, the model is displayed in real-time, adapting to the user's movements, providing a natural try-on experience.

[0589] Step 4:

[0590] The device uses a camera and microphone to analyze the user's emotions. Input is the user's facial expressions and voice data. Output is the analyzed emotional state (joy, surprise, sadness, etc.). Specifically, a process is performed to analyze facial features and voice tone to determine emotions in real time.

[0591] Step 5:

[0592] The device sends fitting data and emotional data to the server. The input is this data, and the output is the information transferred to the server. Specifically, the HTTPS protocol is used for secure data transmission.

[0593] Step 6:

[0594] The server generates styling suggestions using an AI model based on the received data. Inputs include user try-on data, emotional state, past history, and trend information. The output is a styling suggestion optimized for the user. Specifically, it utilizes machine learning algorithms to analyze data from multiple perspectives.

[0595] Step 7:

[0596] The server sends the generated styling suggestions to the terminal. The input is the styling suggestion data. The output is the suggestion sent to the terminal. Specifically, the server converts the suggested content into a format suitable for external presentations and prepares it for clear presentation to the user.

[0597] Step 8:

[0598] The terminal presents the transmitted styling suggestions to the user. The input is the styling suggestion data. The output is suggestion information that the user can visually confirm. Specifically, it displays the suggestions on the screen, allowing the user to continue trying on clothes interactively.

[0599] Step 9:

[0600] When a user purchases a product, the terminal uses electronic transaction methods to complete the purchase process. Inputs include the user's purchase intention and payment information. Output is the completed purchase transaction. Specifically, a secure online payment is processed based on the user's expressed intention.

[0601] (Application Example 2)

[0602] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0603] Conventional virtual try-on systems were unable to offer styling suggestions that took into account the user's emotions, and could only provide uniform suggestions. Therefore, a challenge was that it was difficult to provide a personalized experience tailored to the individual circumstances of each user.

[0604] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0605] In this invention, the server includes emotion analysis means for analyzing facial expressions and voice to recognize the user's emotional state, artificial intelligence processing means for generating styling suggestions based on the user's emotional state, and presentation means for presenting the generated styling suggestions to the user. This enables personalized styling suggestions that reflect the user's emotions.

[0606] "Means of photography" refers to a device or function for photographing the user's body, and includes devices such as cameras.

[0607] "Display means" refers to a device or function for visually presenting a three-dimensional model of an item selected by the user, and includes devices such as displays and monitors.

[0608] "Augmented reality means" refers to a technology or device for superimposing selected objects onto a user's body, and is a technology that uses augmented reality technology to superimpose the virtual and real worlds.

[0609] "Emotional analysis means" refers to a technology or device for recognizing a user's emotional state by analyzing their facial expressions and voice.

[0610] "Artificial intelligence processing means" refers to a technology for processing data and generating styling suggestions based on the user's emotional state, and involves processing using machine learning algorithms.

[0611] "Presentation means" refers to a device or function for providing the generated styling suggestions to the user visually or audibly, and includes devices such as displays and speakers.

[0612] This invention is implemented as a system using a terminal and a server. The terminal is equipped with a camera as a means of capturing images of the user's body, thereby acquiring a full-body image of the user. The terminal also has a display as a means of displaying, which displays a three-dimensional model of the item selected by the user. By using augmented reality means to overlay these three-dimensional models onto the user's body image, virtual try-on is realized.

[0613] The device is equipped with emotion analysis capabilities, using software such as OpenCV and DeepFace to analyze the user's facial expressions and voice, and determine their emotional state in real time. This allows it to recognize emotions such as joy, surprise, and sadness. This emotion data is then transmitted from the device to a server.

[0614] The server uses artificial intelligence processing to generate styling suggestions based on received sentiment data. The server also combines past history and trend information to provide the user with the most suitable styling suggestions. The generated styling suggestions are displayed on the terminal's screen via a presentation device.

[0615] For example, when a user smiles, the server might suggest a casual, brightly colored outfit. This is the most appropriate suggestion based on the user's emotional state, providing a personalized shopping experience for each individual user. The system is designed to facilitate a smooth fitting and purchase process that reflects emotions.

[0616] An example of a prompt in a generative AI model is: "I am designing a fashion app using an emotion engine. Please suggest what dataset and algorithms I should use to build an AI model that suggests casual, bright-toned styling when it detects a user's smile."

[0617] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0618] Step 1:

[0619] The user takes a full-body photograph using the device. The device's camera is used, and the user presses the capture button when their posture is straight to acquire a full-body image as input data. A high-resolution user image is generated as output.

[0620] Step 2:

[0621] Within the terminal, a three-dimensional model of an item selected by the user is displayed via a display device. This model is selected from a pre-stored database. The input is information about the item selected by the user, and the output is a visual display of the three-dimensional item model on the screen.

[0622] Step 3:

[0623] The device uses augmented reality (AR) technology to overlay a three-dimensional object model onto the acquired full-body image. The input consists of the output images from steps 1 and 2. AR technology is used to synthesize the images, and the output displays the object image in real-time as if it were being worn on the user's body.

[0624] Step 4:

[0625] The device collects user emotions using emotion analysis tools and analyzes facial expressions and voice. Input is real-time data captured through the camera and microphone. Using libraries such as OpenCV and DeepFace, the input data is analyzed and an emotional state (e.g., joy, sadness) is obtained as output.

[0626] Step 5:

[0627] The device sends emotional data to the server. The input is data containing the user's emotional state, and the output is the state sent to the server.

[0628] Step 6:

[0629] The server generates styling suggestions using artificial intelligence processing based on received sentiment data, past history, and trend information. The input consists of the user's sentiment, history, and trend information. The server analyzes this data and uses machine learning algorithms to output optimal styling suggestions.

[0630] Step 7:

[0631] The generated styling suggestions are sent from the server to the terminal's display and viewed by the user on the display. The input is the styling suggestions sent from the server, and the output is their visual presentation.

[0632] Step 8:

[0633] When a user selects an item they like, they proceed with the purchase through e-commerce using the terminal. The input is the user's purchase decision information, and the output is the status after the purchase process is completed.

[0634] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0635] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0636] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0637] [Fourth Embodiment]

[0638] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0639] As shown in Figure 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.

[0640] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0641] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0642] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0643] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0644] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0645] The controlled 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0646] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0647] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0648] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0649] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0650] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0651] This invention is a system that allows users to virtually try on clothes and accessories using a smartphone or tablet. The user takes a full-body photo using the device's camera and selects products. The device generates a three-dimensional model of the selected product and displays it overlaid on the user's image using augmented reality means.

[0652] In this process, the device adjusts the 3D model appropriately, taking into account the user's body shape and position. Next, the device sends this data to a server, which analyzes the received data using artificial intelligence processing. The server then takes into account the user's past purchase history and current fashion trends to generate optimal styling suggestions.

[0653] The generated styling suggestions are sent from the server to the terminal, which then presents the suggestions to the user. The user can continue virtual try-on based on this information. If the user is interested in purchasing, the terminal initiates the purchase process using e-commerce tools.

[0654] For example, if a user wants to choose and try on a new dress from the comfort of their home, the device will display a 3D model of the dress and suggest the best outfit based on AI styling recommendations. The user can then decide to purchase the dress based on this feedback and complete the purchase process on the device. This format allows for a satisfying shopping experience without the need for physical try-on.

[0655] The following describes the processing flow.

[0656] Step 1:

[0657] The user launches a dedicated application on their device, stands in a position where their entire body can be photographed, and activates the camera. The user then selects the clothes or accessories they want to try on within the app.

[0658] Step 2:

[0659] The device detects the user's body from real-time video footage captured by the camera and obtains 3D model data of the selected product. The device also uses augmented reality to overlay the product data onto the user's video.

[0660] Step 3:

[0661] The device adjusts the position and size of the 3D model in real time, taking into account the user's body shape and the fit of the selected product. It checks the degree of matching of each part to ensure a natural overlay.

[0662] Step 4:

[0663] The terminal transmits current video data and product selection information to the server. The data also includes user-specific body type information and product attribute information.

[0664] Step 5:

[0665] The server uses an AI agent to analyze the transmitted data. The server refers to the user's past purchase history and current fashion trends to generate optimal styling suggestions.

[0666] Step 6:

[0667] The server sends the generated styling suggestions to the terminal. The suggestions include specific information about accessories and other clothing combinations that would suit the product.

[0668] Step 7:

[0669] The device displays the received styling suggestions to the user on the screen. The user continues trying on clothes based on the displayed suggestions, selecting other items or adjusting the fit as needed.

[0670] Step 8:

[0671] If the user decides to make a purchase, the device initiates the purchase process through e-commerce. The device sends the necessary information to the server and processes the payment.

[0672] Step 9:

[0673] The server processes the purchase information and arranges for product shipment. The user receives a purchase completion notification via their device.

[0674] (Example 1)

[0675] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0676] Traditional online shopping systems have faced challenges such as users being unable to actually try on products, leading to errors in product selection. Furthermore, it has been difficult to provide styling suggestions that take into account individual user body types and preferences, making it challenging to offer a truly satisfying shopping experience.

[0677] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0678] In this invention, the server includes means for photographing the user's body and acquiring images, means for generating a three-dimensional model using product information selected by the user, and means for transmitting the data to the server and generating styling suggestions using the generated AI model. This makes it possible for the user to virtually try on products that are appropriately adjusted to their body type and to receive styling suggestions based on their individual preferences.

[0679] "Means of photography" refers to a device or function for photographing the user's body and acquiring image data.

[0680] "Generation means" refers to the technology and equipment used to create a three-dimensional model of a product based on product information selected by the user.

[0681] "Augmented reality means" refers to technologies and systems that overlay virtual three-dimensional models onto images of the real world.

[0682] "Adjustment means" refers to a system that analyzes the user's body shape and automatically adjusts the position and size of the displayed three-dimensional model appropriately.

[0683] "Analysis means" refers to a device or function that transmits data to a server and processes it to create styling suggestions for the user using a generated AI model.

[0684] "Notification means" refers to functions or devices for communicating generated styling suggestions to the user.

[0685] "Electronic commerce methods" refer to systems and technologies that enable users to complete the purchase process of selected goods online.

[0686] This invention provides a system that allows users to virtually try on clothes and accessories using their own devices, such as smartphones and tablets. The user takes a full-body photograph using the device's camera, and the system operates based on that image. The device is equipped with a high-resolution camera, a touchscreen, and a processor for utilizing augmented reality (AR) technology. Specifically, the device's camera system and AR framework (e.g., ARKit for iOS or ARCore for Android) are used to overlay product models onto images of the real world.

[0687] When a user selects a product, the terminal receives the product's digital information and generates a 3D model. This can be done using 3D modeling software (e.g., Blender or Unity). The generated model is then adjusted according to the user's body shape and displayed realistically. Image processing libraries (e.g., OpenCV) are used for this adjustment process.

[0688] The adjusted data is then sent from the terminal to the server. The server analyzes the received data using a generative AI model (e.g., TensorFlow or PyTorch). Based on the user's past purchase history and current trend information, the server provides optimal styling suggestions. These suggestions are important as part of a unique sales strategy.

[0689] For example, if a user wants to virtually try on a new dress and find the best styling for them, the system uses AR technology to display a 3D model of the dress on the user's screen and provides AI-powered styling suggestions. These suggestions include specific advice such as, "Gold accessories would go well with this red dress." Furthermore, if the user wishes to purchase the dress, they can securely complete the payment process on their device. This entire process allows users to enjoy an effective shopping experience from the comfort of their homes.

[0690] Examples of prompts include, "Generate the latest styling suggestions for women in their 30s that are suitable for autumn fashion."

[0691] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0692] Step 1:

[0693] The user takes a full-body photo using the device's camera. The input is a full-body image of the user. The device extracts the user's body shape data from this image. Using an image processing library, it measures basic dimensions such as shoulder width and height, and generates body shape information as output.

[0694] Step 2:

[0695] The terminal receives information about the product selected by the user and generates a corresponding 3D model. The input is the identification information of the selected product. Based on this information, a model is generated using 3D modeling software, and 3D model data is created as output.

[0696] Step 3:

[0697] The terminal adjusts the generated 3D model based on the user's body shape information. The inputs are the body shape information obtained in step 1 and the 3D model generated in step 2. Image processing technology is used to appropriately adjust the size and angle of the model, generating a model that fits the user as output.

[0698] Step 4:

[0699] The adjusted 3D model is displayed on the device by overlaying it onto the user's video using augmented reality. The input is the adjusted 3D model data. Using the device's AR framework, the model is overlaid on the video in real time, generating an output video to be displayed to the user.

[0700] Step 5:

[0701] The terminal sends the adjusted data to the server. The input consists of the adjusted 3D model and the user's body shape information. A data transmission communication protocol is used to generate the data that the server receives as output.

[0702] Step 6:

[0703] The server generates styling suggestions using an AI model based on the received data. The input is data sent from the terminal. The AI ​​model refers to purchase history and trend information in the database to generate appropriate styling suggestions and outputs styling suggestion data.

[0704] Step 7:

[0705] The server sends the generated styling suggestions to the terminal. The input is the generated styling suggestion data. Depending on the presentation method, communication means are used to appropriately deliver the suggestions to the user, and data is generated that is received by the terminal as output.

[0706] Step 8:

[0707] The terminal presents the received styling suggestions to the user. The input is the received styling suggestion data. The terminal's display is used to show the information, providing the user with visual feedback as output.

[0708] Step 9:

[0709] If the user decides to make a purchase, the terminal initiates the purchase process using e-commerce methods. The input is the user's purchase decision information. The payment app on the terminal is launched to execute the purchase process, and a purchase completion notification is generated as output.

[0710] (Application Example 1)

[0711] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0712] In modern virtual stores, it is difficult for users to make satisfactory purchase decisions without physically trying on items. Furthermore, online shopping often lacks appropriate styling suggestions and recommendations for related products, resulting in a limited user experience.

[0713] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0714] In this invention, the server includes a means for capturing images of the user's body, an augmented reality means for overlaying and displaying selected objects, and a machine learning processing means for generating styling suggestions. This allows the user to try out appropriate outfits from the comfort of their home, receive recommendations for related products, and improve their shopping experience.

[0715] "Photography means" refers to a digital imaging device used to acquire an image of the user's body.

[0716] "Display means" refers to a device or software for visually showing the three-dimensional structure of an object selected by the user.

[0717] "Augmented reality" refers to a technology that overlays digital objects onto images of the real world, providing users with a virtual experience.

[0718] "Machine learning processing means" refers to components of artificial intelligence used to analyze data and automatically generate styling suggestions suitable for the user.

[0719] "Presentation means" refers to a method for visually or audibly showing the generated styling suggestions to the user.

[0720] "Online trading methods" refer to digital platforms and related technologies used to buy and sell goods via the internet.

[0721] A "recommendation system" is an artificial intelligence-based system used to suggest additional relevant items based on the user's preferences and history.

[0722] Regarding embodiments for carrying out the invention, the present invention is a system that allows a user to view selected objects superimposed onto their own image from a remote location such as their home, and provides an experience from receiving styling suggestions to making a purchase. This system is configured as follows.

[0723] First, the user takes a picture of themselves using a device equipped with a camera (e.g., a smartphone or tablet). The device uses its camera function to capture the user's entire body. Next, the device uses a display to show the three-dimensional structure of an object selected by the user. At this point, the device uses AR technology to overlay the digital object onto the real-world image. Specifically, software platforms such as ARKit and ARCore are used.

[0724] Furthermore, the device transmits the acquired data to a remote server. The server utilizes cloud-based AI processing services (e.g., Google Cloud AI or AWS AI) and machine learning models to generate styling suggestions based on the received user data. This generation process involves analysis based on the user's past purchase history and the latest fashion trends. The generated suggestions are then displayed on the device via a presentation system.

[0725] When a user becomes interested in a styling suggestion, they can purchase the product through online transactions on their device. An e-commerce platform is used in this process.

[0726] A concrete example is a scenario where a user uses the "Smart Closet" application to try on new clothes and check AI styling suggestions. These suggestions may include combinations with previously purchased items or coordinated outfits optimized for the user's individual preferences.

[0727] An example of a prompt to input into the AI ​​model would be, "Based on the user's past purchase history, please generate the best styling suggestions for this dress. Also, please consider current fashion trends." This would allow users to easily enjoy fashion coordination at home without having to physically try on clothes.

[0728] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0729] Step 1:

[0730] The user activates the device's camera and takes a full-body picture. The input is real-time video data, and the output is an image of the user. This image forms the basis for subsequent augmented reality processing. Specifically, the user positions the device at an appropriate distance and positions their image within the screen.

[0731] Step 2:

[0732] The device displays a 3D model of the product selected by the user. The input is the digital data of the selected object, and the output is a display of that 3D model superimposed on the user's image. Augmented reality technologies using ARKit or ARCore are used for data processing. Specifically, the 3D model is adjusted to match the user's body shape and orientation and superimposed on the real-world image.

[0733] Step 3:

[0734] The system sends user image data and object selection data to the server. The input is the user's image and selection data, and the output is the result of the transmission to the server. Specifically, the terminal uses an internet connection to upload the data to the remote server.

[0735] Step 4:

[0736] The server generates styling suggestions based on the received data. Inputs include past purchase history, current fashion trends, and user image data, while output is styling suggestions. This process uses a generative AI model to perform data analysis and suggestion generation based on prompt messages.

[0737] Step 5:

[0738] The generated styling suggestions are sent from the server to the terminal. The input is the styling suggestions generated on the server, and the output is the suggestion data received by the terminal. Specifically, the data is transmitted to the terminal again via the internet connection.

[0739] Step 6:

[0740] The terminal receives suggestion data and presents it to the user. The input is suggestion data sent from the server, and the output is styling suggestions displayed on the terminal screen. The user views this information and decides whether to continue trying on clothes or consider purchasing.

[0741] Step 7:

[0742] If the user decides to purchase, the terminal will process the purchase through an online transaction method. The input is the user's intention to purchase and the selected product information, and the output is a confirmation that the transaction is complete. Specifically, the terminal enters payment information and completes the purchase through the online transaction platform.

[0743] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0744] This invention is a system that allows users to virtually try on clothes and accessories via a smartphone or tablet, and combines an emotion engine to provide styling suggestions based on the user's emotions. First, the user takes a full-body photo using the device's camera. The device generates three-dimensional models of the clothes and accessories, and uses augmented reality technology to overlay the models of the selected items onto the user's image.

[0745] In this system, the device incorporates an emotion engine that analyzes the user's facial expressions and voice to recognize emotions in real time. The emotion engine can determine emotional states such as joy, surprise, and sadness from facial features and voice tone.

[0746] The device then sends the fitting data, along with the acquired emotional information, to the server. The server uses artificial intelligence processing to analyze this data and generates optimal styling suggestions that take into account the user's past history, current fashion trends, and emotional state. For example, if the user expresses surprise, the server will suggest a new style or provide a bolder combination of fashion items.

[0747] The generated styling suggestions are sent to the device and presented to the user. The user can continue trying on clothes based on these suggestions. Furthermore, if the user wishes to purchase, the device can proceed with the purchase process via e-commerce. This format allows the user to have a personalized try-on experience that reflects their emotions, improving shopping satisfaction. For example, if the user has a cheerful expression, they may receive more casual and colorful suggestions, allowing them to shop in a way that suits their mood.

[0748] The following describes the processing flow.

[0749] Step 1:

[0750] The user launches a dedicated application on their device and uses the camera in a position where their entire body can be photographed. The user then selects the items they wish to try on from within the app.

[0751] Step 2:

[0752] The device analyzes camera footage in real time to detect the user's body. It also acquires a 3D model of the selected product and overlays it onto the user's body using augmented reality.

[0753] Step 3:

[0754] The device activates an emotion engine to analyze the user's facial expressions and voice. The emotion engine analyzes facial features and voice tone to identify the emotional state. For example, if a smile is detected, it determines that the user is "happy."

[0755] Step 4:

[0756] The device sends the user's body shape data, selected product information, and detected emotion data to the server. This allows the server to receive diverse information all at once.

[0757] Step 5:

[0758] The server uses an AI agent to analyze the received data. The server combines emotional information, past history, and trend information to generate optimal styling suggestions for the user. For example, if the user expresses surprise, the server will consider new styles or bold suggestions.

[0759] Step 6:

[0760] The server sends the generated styling suggestions to the terminal. In addition to standard styling suggestions, the server's suggestions may include special elements tailored to the user's mood.

[0761] Step 7:

[0762] The device displays the received styling suggestions on the screen and presents them to the user. The user can then try on the clothes again or try a different style based on the information presented.

[0763] Step 8:

[0764] If the user is satisfied with the suggested style and wishes to purchase it, the device will display an e-commerce form and proceed with the purchase process.

[0765] Step 9:

[0766] The server processes the purchase information sent from the terminal and initiates the shipping process for the goods. This allows the user to receive a notification that the purchase is complete.

[0767] (Example 2)

[0768] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0769] Conventional virtual try-on systems have the problem of not being able to improve individual satisfaction because they simply suggest clothing and accessory styling without considering the user's emotions. Furthermore, styling suggestions are one-way and cannot be optimized according to the user's emotions, resulting in the problem of not being able to provide the truly optimal style for the user.

[0770] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0771] In this invention, the server includes emotion analysis means for analyzing the user's emotions, artificial intelligence processing means for transmitting data to the server and generating styling suggestions considering the emotional information, and presentation means for presenting the generated styling suggestions to the user. This enables personalized styling suggestions based on the user's emotions, thereby improving user satisfaction.

[0772] "Photography equipment" refers to a device equipped with the function of acquiring the user's body as image data.

[0773] A "generation means" is a device that has the function of constructing a three-dimensional model of clothing or accessories based on acquired image data.

[0774] "Augmented reality means" refers to devices that enable the real-time visual display of a three-dimensional model superimposed onto the user's body.

[0775] An "emotion analysis device" is a device that has the function of analyzing a user's facial expressions and voice to determine their emotional state.

[0776] "Artificial intelligence processing means" refers to a system that generates styling suggestions using a learning algorithm based on data received by the server.

[0777] A "presentation means" is a device for visually or audibly communicating the generated styling suggestions to the user.

[0778] An "electronic transaction method" is a system that has the functionality to allow users to complete the purchase process of selected goods online.

[0779] This invention is a system that allows users to virtually try on clothes and accessories using a mobile information terminal such as a smartphone or tablet. The terminal is equipped with advanced imaging, generation, augmented reality, and emotion analysis capabilities.

[0780] First, the user takes a picture of their body using the device's camera. The camera function is utilized to obtain high-resolution and accurate image data. Next, the acquired image data is sent to a generation system, where a three-dimensional model of clothing and accessories is automatically generated. 3D modeling software and libraries (e.g., Blender or Autodesk Maya) are used for this generation.

[0781] Next, augmented reality (AR) technology kicks in, overlaying the generated 3D model onto the user's image in real time. AR technology is used for this display, with ARKit and ARCore being representative examples.

[0782] Furthermore, the device incorporates emotion analysis capabilities. This device uses face recognition and voice analysis libraries (e.g., OpenCV and Microsoft Azure Face API) to analyze the user's facial expressions and voice in real time and determine emotions such as joy and surprise.

[0783] The fitting data and sentiment information collected together are sent from the terminal to the server. The server uses artificial intelligence processing tools to analyze this data. For this purpose, machine learning frameworks (e.g., TensorFlow and PyTorch) are used. The server considers the user's past history, current fashion information, and sentiment analysis results to generate optimal styling suggestions.

[0784] The generated styling suggestions are sent to the terminal and presented to the user through a display device. This allows the user to review the styles and continue trying on clothes. Furthermore, when the user purchases selected items, the terminal's electronic transaction device is used to complete the online payment.

[0785] For example, if the user has a cheerful expression, the system will suggest a casual, brightly colored style. An example of such a prompt would be, "Please generate a recommended style, taking into account the emotions the user has expressed."

[0786] This system enables users to enjoy a personalized try-on experience tailored to their own feelings, thereby improving shopping satisfaction.

[0787] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0788] Step 1:

[0789] The user activates the device's camera and takes a picture of their body. The input data is the image acquired through the device's camera. This image data is high resolution and accurately captures the user's entire body. An image file is generated as output.

[0790] Step 2:

[0791] The device generates three-dimensional models of clothing and accessories using captured image data. The input is the user's image data, and the output is the data of the three-dimensional model. 3D modeling software is used to generate the three-dimensional model. Specifically, it analyzes the acquired images and adjusts the model to match the position and size of the human body.

[0792] Step 3:

[0793] The device uses augmented reality technology to overlay a generated 3D model onto the user's image. The input consists of the 3D model data and the user's image data, while the output is a virtual try-on image displayed in augmented reality. Specifically, the model is displayed in real-time, adapting to the user's movements, providing a natural try-on experience.

[0794] Step 4:

[0795] The device uses a camera and microphone to analyze the user's emotions. Input is the user's facial expressions and voice data. Output is the analyzed emotional state (joy, surprise, sadness, etc.). Specifically, a process is performed to analyze facial features and voice tone to determine emotions in real time.

[0796] Step 5:

[0797] The device sends fitting data and emotional data to the server. The input is this data, and the output is the information transferred to the server. Specifically, the HTTPS protocol is used for secure data transmission.

[0798] Step 6:

[0799] The server generates styling suggestions using an AI model based on the received data. Inputs include user try-on data, emotional state, past history, and trend information. The output is a styling suggestion optimized for the user. Specifically, it utilizes machine learning algorithms to analyze data from multiple perspectives.

[0800] Step 7:

[0801] The server sends the generated styling suggestions to the terminal. The input is the styling suggestion data. The output is the suggestion sent to the terminal. Specifically, the server converts the suggested content into a format suitable for external presentations and prepares it for clear presentation to the user.

[0802] Step 8:

[0803] The terminal presents the transmitted styling suggestions to the user. The input is the styling suggestion data. The output is suggestion information that the user can visually confirm. Specifically, it displays the suggestions on the screen, allowing the user to continue trying on clothes interactively.

[0804] Step 9:

[0805] When a user purchases a product, the terminal uses electronic transaction methods to complete the purchase process. Inputs include the user's purchase intention and payment information. Output is the completed purchase transaction. Specifically, a secure online payment is processed based on the user's expressed intention.

[0806] (Application Example 2)

[0807] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0808] Conventional virtual try-on systems were unable to offer styling suggestions that took into account the user's emotions, and could only provide uniform suggestions. Therefore, a challenge was that it was difficult to provide a personalized experience tailored to the individual circumstances of each user.

[0809] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0810] In this invention, the server includes emotion analysis means for analyzing facial expressions and voice to recognize the user's emotional state, artificial intelligence processing means for generating styling suggestions based on the user's emotional state, and presentation means for presenting the generated styling suggestions to the user. This enables personalized styling suggestions that reflect the user's emotions.

[0811] "Means of photography" refers to a device or function for photographing the user's body, and includes devices such as cameras.

[0812] "Display means" refers to a device or function for visually presenting a three-dimensional model of an item selected by the user, and includes devices such as displays and monitors.

[0813] "Augmented reality means" refers to a technology or device for superimposing selected objects onto a user's body, and is a technology that uses augmented reality technology to superimpose the virtual and real worlds.

[0814] "Emotional analysis means" refers to a technology or device for recognizing a user's emotional state by analyzing their facial expressions and voice.

[0815] "Artificial intelligence processing means" refers to a technology for processing data and generating styling suggestions based on the user's emotional state, and involves processing using machine learning algorithms.

[0816] "Presentation means" refers to a device or function for providing the generated styling suggestions to the user visually or audibly, and includes devices such as displays and speakers.

[0817] This invention is implemented as a system using a terminal and a server. The terminal is equipped with a camera as a means of capturing images of the user's body, thereby acquiring a full-body image of the user. The terminal also has a display as a means of displaying, which displays a three-dimensional model of the item selected by the user. By using augmented reality means to overlay these three-dimensional models onto the user's body image, virtual try-on is realized.

[0818] The device is equipped with emotion analysis capabilities, using software such as OpenCV and DeepFace to analyze the user's facial expressions and voice, and determine their emotional state in real time. This allows it to recognize emotions such as joy, surprise, and sadness. This emotion data is then transmitted from the device to a server.

[0819] The server uses artificial intelligence processing to generate styling suggestions based on received sentiment data. The server also combines past history and trend information to provide the user with the most suitable styling suggestions. The generated styling suggestions are displayed on the terminal's screen via a presentation device.

[0820] For example, when a user smiles, the server might suggest a casual, brightly colored outfit. This is the most appropriate suggestion based on the user's emotional state, providing a personalized shopping experience for each individual user. The system is designed to facilitate a smooth fitting and purchase process that reflects emotions.

[0821] An example of a prompt in a generative AI model is: "I am designing a fashion app using an emotion engine. Please suggest what dataset and algorithms I should use to build an AI model that suggests casual, bright-toned styling when it detects a user's smile."

[0822] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0823] Step 1:

[0824] The user takes a full-body photograph using the device. The device's camera is used, and the user presses the capture button when their posture is straight to acquire a full-body image as input data. A high-resolution user image is generated as output.

[0825] Step 2:

[0826] Within the terminal, a three-dimensional model of an item selected by the user is displayed via a display device. This model is selected from a pre-stored database. The input is information about the item selected by the user, and the output is a visual display of the three-dimensional item model on the screen.

[0827] Step 3:

[0828] The device uses augmented reality (AR) technology to overlay a three-dimensional object model onto the acquired full-body image. The input consists of the output images from steps 1 and 2. AR technology is used to synthesize the images, and the output displays the object image in real-time as if it were being worn on the user's body.

[0829] Step 4:

[0830] The device collects user emotions using emotion analysis tools and analyzes facial expressions and voice. Input is real-time data captured through the camera and microphone. Using libraries such as OpenCV and DeepFace, the input data is analyzed and an emotional state (e.g., joy, sadness) is obtained as output.

[0831] Step 5:

[0832] The device sends emotional data to the server. The input is data containing the user's emotional state, and the output is the state sent to the server.

[0833] Step 6:

[0834] The server generates styling suggestions using artificial intelligence processing based on received sentiment data, past history, and trend information. The input consists of the user's sentiment, history, and trend information. The server analyzes this data and uses machine learning algorithms to output optimal styling suggestions.

[0835] Step 7:

[0836] The generated styling suggestions are sent from the server to the terminal's display and viewed by the user on the display. The input is the styling suggestions sent from the server, and the output is their visual presentation.

[0837] Step 8:

[0838] When a user selects an item they like, they proceed with the purchase through e-commerce using the terminal. The input is the user's purchase decision information, and the output is the status after the purchase process is completed.

[0839] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0840] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0841] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0842] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0843] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0844] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0845] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0846] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0847] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0848] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0849] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0850] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0851] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0852] 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.

[0853] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0854] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0855] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0856] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0857] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0858] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0859] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0860] The following is further disclosed regarding the embodiments described above.

[0861] (Claim 1)

[0862] A means of photographing the user's body,

[0863] A display means for displaying a three-dimensional model of the product selected by the user,

[0864] An augmented reality system that overlays and displays the selected product onto the user's body,

[0865] An artificial intelligence processing means for sending data to a server and generating styling suggestions,

[0866] A presentation method for showing the generated styling suggestions to the user,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] The system according to claim 1, which optimizes styling suggestions using the user's past history and current trend information.

[0870] (Claim 3)

[0871] The system according to claim 1, further comprising electronic commerce means for processing the purchase of a product selected by the user.

[0872] "Example 1"

[0873] (Claim 1)

[0874] A means of capturing images of the user's body,

[0875] A generation means that generates a three-dimensional model of a product using product information selected by the user,

[0876] Augmented reality means that realistically overlays a three-dimensional model onto the user's video,

[0877] An adjustment means that automatically analyzes the user's body shape and adjusts the display position and size,

[0878] An analysis method that sends data to a server and generates styling suggestions using a generated AI model,

[0879] A notification method for presenting the generated styling suggestions to the user,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, which optimizes styling suggestions based on the user's past purchase history and trend information.

[0883] (Claim 3)

[0884] The system according to claim 1, further comprising electronic commerce means for processing the purchase of a product selected by the user.

[0885] "Application Example 1"

[0886] (Claim 1)

[0887] A means of photographing the user's body,

[0888] A display means for displaying the three-dimensional structure of an object selected by the user,

[0889] An augmented reality system that overlays and displays selected objects onto the user's body,

[0890] A machine learning processing means for transmitting information to a remote data processing device and generating styling suggestions,

[0891] A presentation method for showing the generated styling suggestions to the user,

[0892] A system that includes online trading methods for processing the buying and selling of products that users are interested in.

[0893] (Claim 2)

[0894] The system according to claim 1, which optimizes styling suggestions using the user's past activity history and the latest trend information.

[0895] (Claim 3)

[0896] The system according to claim 1, further comprising an artificial intelligence-driven recommendation means for suggesting additional items for an object selected by the user and improving the user experience.

[0897] "Example 2 of combining an emotion engine"

[0898] (Claim 1)

[0899] A means of photographing the user's body,

[0900] A generation means for generating a three-dimensional model of a product selected by the user,

[0901] An augmented reality system that overlays and displays the selected product onto the user's body,

[0902] A means of analyzing user emotions,

[0903] An artificial intelligence processing means for sending data to a server and generating styling suggestions while considering emotional information,

[0904] A presentation method for showing the generated styling suggestions to the user,

[0905] A system that includes this.

[0906] (Claim 2)

[0907] The system according to claim 1, which optimizes styling suggestions using the user's past history, current trend information, and the user's emotions.

[0908] (Claim 3)

[0909] The system according to claim 1, further comprising electronic transaction means for processing the purchase of a product selected by the user.

[0910] "Application example 2 when combining with an emotional engine"

[0911] (Claim 1)

[0912] A means of photographing the user's body,

[0913] A display means for displaying a three-dimensional model of an item selected by the user,

[0914] An augmented reality means that overlays and displays selected items onto the user's body,

[0915] An emotion analysis method that analyzes facial expressions and voice to recognize the user's emotional state,

[0916] An artificial intelligence processing means for generating styling suggestions based on the user's emotional state,

[0917] A presentation method for showing the generated styling suggestions to the user,

[0918] A system that includes this.

[0919] (Claim 2)

[0920] The system according to claim 1, which optimizes styling suggestions using the user's past history and current trend information, and taking into account the user's emotional state.

[0921] (Claim 3)

[0922] The system according to claim 1, further comprising an e-commerce function for processing the purchase of items selected by the user. [Explanation of symbols]

[0923] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of photographing the user's body, A display means for displaying the three-dimensional structure of an object selected by the user, An augmented reality system that overlays and displays selected objects onto the user's body, A machine learning processing means for transmitting information to a remote data processing device and generating styling suggestions, A presentation method for showing the generated styling suggestions to the user, A system that includes online trading methods for processing the buying and selling of products that users are interested in.

2. The system according to claim 1, which optimizes styling suggestions using the user's past activity history and the latest trend information.

3. The system according to claim 1, further comprising an artificial intelligence-driven recommendation means for suggesting additional items for an object selected by the user and improving the user experience.

Images