system

Abstract

We provide the system. [Solution] A means for acquiring personal image data and analyzing the personal head features from said image data, A means of inputting data on desired appearance changes based on individual choices, A means for generating images corresponding to the head features and the desired changes, for proposing multiple appearance modification option data, A means of presenting the results of the generated appearance changes using a machine equipped with a display device, Based on the generated appearance modification results, a means to support the selection of daily necessities while taking health status information into consideration, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When making appearance changes desired by an individual, it is required to eliminate the discrepancy between the ideal finish and the actual result, and to prevent possible health problems and misunderstandings that may occur during this process. However, currently, there are problems that it is difficult to generate an appropriate image that can be visually confirmed and to safely manage health-related information when making appearance changes.

Means for Solving the Problems

[0005] This invention provides a system that analyzes an individual's image data to generate and display an optimal finished image for a desired appearance change. This system takes into account the individual's health status data and includes means for sharing it with external professional experts. Specifically, it solves the problem by analyzing the individual's head characteristics, providing multiple appearance change options based on the acquired data, managing risk information according to the individual's health status, and securely sharing necessary information with external parties.

[0006] "Image data" is a collection of digital visual information used to capture the facial and head features of an individual.

[0007] "Head features" refer to data that describes the physical characteristics of an individual's face and head, such as shape, contour, and hair texture.

[0008] "Desired appearance change data" refers to data that shows selective information regarding the beauty style and haircut that an individual desires.

[0009] "Image generation means" refers to a technical process or apparatus for visualizing the expected appearance after a change in appearance, based on the analyzed head features of an individual.

[0010] A "display device" is a device such as a monitor or screen used to visually present the results of the generated changes to the appearance.

[0011] A "professional expert" is a third party who possesses specialized skills and knowledge in the field of beauty and hairstyling.

[0012] "Health status data" refers to information about an individual's allergies and other health conditions, particularly data that may influence the process of changes in appearance.

[0013] "Data transmission means" refers to technical means for transmitting generated appearance change results and related information to external devices or parties.

[0014] "Risk information" refers to information that indicates potential health risks associated with the process of altering appearance, based on an individual's health condition. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] 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.

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

[0018] In the following embodiments, a 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), and the like.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

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

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

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

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is a system that allows users to visually confirm changes in their appearance based on their personal preferences while minimizing risks during the process. Specifically, it photographs the user's face and head, and then inputs their preferences for beauty treatments and haircuts as digital data. The system aims to improve user satisfaction through this series of processes.

[0037] The first step for the user is to take an image of their face or head using the camera on their smartphone. The device temporarily stores this image data and prepares to send it to the server. At the same time, the user selects their desired style from several provided appearance modification options and enters this information on the device. This information is also sent to the server.

[0038] The server analyzes the received image data to identify the user's head features and generates an image of the desired hairstyle based on that information. The generative model used here has learned from past data and the latest trends, enabling it to generate more accurate images. The generated image is sent to the user's terminal, where it can be viewed.

[0039] Furthermore, users can register health data, such as allergies, through their devices. This information is stored on a server and used, as needed, to verify whether the appearance modification options selected by the user pose any health risks. The system can also provide risk information tailored to the user's health status to external experts, thus contributing to improved safety.

[0040] For example, if a user selects a short bob style, the server generates an image of the most suitable hairstyle for that style based on the user's head characteristics and calculates risk avoidance information for each step. For instance, if an allergy to a specific chemical is registered, the server uses that information to check whether the modified style can be safely implemented.

[0041] This system provides users with predictive images of their desired appearance and helps them manage health risks in advance, thereby supporting the realization of ideal services.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user takes an image of their face or head using the camera on their smartphone. The device temporarily stores this image data in its internal memory.

[0045] Step 2:

[0046] The user enters their desired appearance change options through the application on their device. The device records the selected appearance change information and prepares to send it to the server.

[0047] Step 3:

[0048] The image data captured by the device and the user's selected appearance modification data are compressed and encrypted, and then securely transmitted to the server.

[0049] Step 4:

[0050] The server analyzes the received image data and uses facial recognition technology to identify the user's head features. Based on this information and the user's selected appearance changes, the server inputs the data into a generating AI model.

[0051] Step 5:

[0052] The server uses a generated AI model to create a predictive appearance image that best suits the user's head features. Furthermore, it analyzes potential risks to the user's health data.

[0053] Step 6:

[0054] The server sends back the predicted appearance image and risk analysis information it generates to the terminal. This data is also encrypted again and transferred securely.

[0055] Step 7:

[0056] The terminal decodes the received data and presents the generated appearance image to the user via the user interface. The user reviews the result and makes a decision on whether to change the appearance.

[0057] Step 8:

[0058] If necessary, the device transmits the user's health data and risk information to external professional experts. Based on this information, the user can receive advice on how to perform safe procedures.

[0059] (Example 1)

[0060] 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."

[0061] When individuals attempt to modify their appearance as they wish, a challenge exists in that it is difficult to confirm the visual image beforehand. Furthermore, there is a lack of means to assess the health risks associated with appearance changes in advance, making it difficult to ensure safety. Additionally, there are challenges in incorporating expert opinions into evaluations due to insufficient methods for smoothly sharing information with external experts.

[0062] 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.

[0063] In this invention, the server includes means for acquiring an individual's characteristics and analyzing the individual's head from those characteristics, means for inputting the individual's desired appearance changes based on their choices, and means for generating images corresponding to the head information and the desired changes for proposing multiple appearance change options. This allows the user to visually confirm the result before changing their appearance, evaluate health risks in advance, and safely change their appearance. Furthermore, by sharing the obtained information with external experts, they can receive more accurate advice.

[0064] "Personal characteristics" refer to specific attributes and data related to an individual's appearance, including facial and head shape, hairline, and skin tone.

[0065] "Methods for analyzing the head" refer to methods that use image processing and artificial intelligence technology to identify individual head features from captured images and extract specific information.

[0066] "Requests for changes to appearance" refer to the user's preferences and requests regarding changes to their appearance, such as hairstyle or makeup.

[0067] The "image generation method" is a technology that creates a virtual finished image using a generation AI model based on the user's head characteristics and desired style information.

[0068] "Health status information" refers to medical information related to maintaining health, such as an individual's allergies and medical history.

[0069] "Risk information" refers to an assessment of the safety of products and methods used for cosmetic modifications, and includes explanations and warnings about events that may affect the user's health.

[0070] "External experts" refer to professionals with advanced knowledge and skills in related fields such as beauty and medicine.

[0071] This invention is a system aimed at visually confirming desired appearance changes and pre-assessing health risks. Specifically, it is implemented in the following way.

[0072] The user takes an image of their face or head using the camera on a device such as a smartphone or tablet. The captured image data is temporarily stored by the device and then prepared to be sent to the server. At the same time, the user selects a desired style from several appearance modification options provided on the device and sends that information to the server as well.

[0073] Upon receiving a series of pieces of information, the server analyzes the user's head features using an image processing algorithm. This analysis employs a generative AI model, incorporating the results of learning from past data and trends. Based on the received head features and the user's desired appearance changes, the server generates an optimal finished image for the user. This generated image is sent to the user's device, where the user can review it.

[0074] Furthermore, users can input allergy information and health status data through their devices. This data is stored on a server and used to determine whether appearance modification options pose health risks. If necessary, this risk information is also provided to external experts to enhance safety.

[0075] For example, if a user requests a short bob hairstyle, the server will generate an image suitable for this style based on the user's head features. If allergy information to specific medications is registered, the server will also take that information into consideration to determine if the new style can be safely implemented.

[0076] An example of a prompt to input into the generating AI model is, "Based on the user's current facial image and their desired short bob hairstyle, generate the optimal finished image and calculate risk information." This prompt allows the system to provide highly accurate predictive images.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The user takes an image of their face or head using the camera on a device such as a smartphone. The captured image data is temporarily stored on the device. Specifically, the user launches the camera app and captures the image. The input at this stage is the user's face image, and the output is the saved image file.

[0080] Step 2:

[0081] The user reviews the appearance customization options provided on the device and selects their desired style. This information is then entered into the application on the device. Specifically, the user scrolls through different style options on the app screen and taps the style they like. The input at this stage is the appearance customization option, and the output is the style data selected by the user.

[0082] Step 3:

[0083] The terminal performs preprocessing to send the captured image data and selected style information to the server. Specifically, it converts this data into an appropriate format and then encrypts it for security. The input at this stage is the image data and style data, and the output is the encrypted data ready for transmission.

[0084] Step 4:

[0085] The server analyzes the received image data and style information. It extracts the user's head features from the image data and generates an image based on the style information. Specifically, it uses an image processing algorithm and a generative AI model to analyze head feature data and generate a visual image that best suits the desired style. The input at this stage is encrypted image data and style information, and the output is the generated finished image.

[0086] Step 5:

[0087] The server sends the generated image to the user's terminal, and the user views the image on the terminal. Specifically, the server receives response data from the server and displays the image through the application. At this stage, the input is the generated image data, and the output is the displayed visual image.

[0088] Step 6:

[0089] Users input allergy information and health status data through their devices and send this data to the server. Specifically, this involves filling in the required data in a health information input form and tapping the submit button. The input at this stage is health information, and the output is health data recorded on the server.

[0090] Step 7:

[0091] The server evaluates the potential risks associated with the selected appearance modification option based on the received health information. If risk information is identified, the user is notified. Specifically, the server performs a database search and makes an automatic determination based on registered health concerns. The inputs at this stage are the user's health data and appearance modification options, and the output is the risk assessment result.

[0092] (Application Example 1)

[0093] 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."

[0094] When individuals change their appearance, it is difficult to accurately predict how their desired style will look beforehand, and there is a need for appropriate means to manage the health risks involved in the process. Furthermore, there is a lack of systems that can facilitate individual style selection within the home and provide appropriate advice.

[0095] 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.

[0096] In this invention, the server includes means for acquiring an individual's image data and analyzing the individual's head features from the image data; means for inputting data on desired appearance changes based on the individual's choices; and means for generating images corresponding to the head features and the desired changes, for proposing a plurality of appearance change option data. This allows users to visually confirm the desired appearance changes in advance, and also enables the suggestion of lifestyle products that take health information into consideration.

[0097] "Image data" refers to visual information obtained in digital format from an individual's appearance and used for analysis.

[0098] "Head features" refer to characteristics related to the shape and pattern of an individual's face and head, and are elements used to predict changes in appearance.

[0099] "Requested change data" refers to information describing the appearance changes that an individual desires, and is based on style selection.

[0100] "Image generation means" refers to a technical means for visually presenting multiple appearance modification options based on analyzed data.

[0101] A "display device" is hardware used to visually present the generated appearance change results to the user.

[0102] "Health status information" refers to data about an individual's physical health, and is information that is considered in order to implement safe appearance alterations.

[0103] "Daily necessities" are items related to an individual's daily life, and are intended to support appropriate choices based on health information.

[0104] The system implementing this invention supports personal appearance modification, allowing users to send their appearance data to a server using a smartphone or home appliance. The server analyzes the individual's head features from the received image data and generates multiple appearance modification options using a generative AI model based on the user's selected desired appearance modification data. This allows users to visually confirm the changes beforehand.

[0105] Furthermore, the server considers the user's health data, analyzes the health risks associated with appearance changes, and provides this information to the user. This makes it possible to address health concerns related to appearance changes in advance. As a display device, a smartphone or robot display is used to visually show the user images of the generated style and information on health risks.

[0106] As a concrete example, there is a process where the user selects their desired hairstyle, and the server generates a style image based on that. The user can then choose an appearance that suits them based on this generated image, and at the same time, appropriate lifestyle products are suggested based on allergy test results.

[0107] By using a generative AI model, it becomes possible to provide users with the latest fashion trends and personalized style suggestions. An example of a prompt to input into the generative AI model is, "Generate a hairstyle as an image that reflects the user's desired appearance change, and display a suggestion that also takes health risks into consideration." This system makes it easy to implement personalized appearance changes tailored to individual needs.

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The user takes an image of their face or head using a mobile device. The input data is image data, which the device temporarily stores and prepares for transmission to the server.

[0111] Step 2:

[0112] The terminal sends the desired appearance change data selected by the user to the server. At this point, the server receives both the image data and the desired change data. The input is the image data and the desired change data, and the output is this data stored on the server.

[0113] Step 3:

[0114] The server uses a generative AI model to begin analyzing the received image data. Head features are extracted at this stage. The input is image data, and the output is the analyzed head feature data. Data processing involves the extraction of specific features using image analysis algorithms.

[0115] Step 4:

[0116] The server generates multiple appearance modification options based on the analyzed head feature data and the user's selected style preference data. A generation AI model is used to generate style images. The input for this step is head feature data and appearance modification preference data, and the output is multiple appearance images.

[0117] Step 5:

[0118] The results are sent to the terminal, and the user confirms the generated style image through the display device. The input is the set of generated appearance images, and the output is the user's visual confirmation result.

[0119] Step 6:

[0120] Considering the user's health status data, the server analyzes health risks associated with the generation style. This includes allergy data. The input is health status data, and the output is the risk analysis results. Data calculations are performed to verify the safety of available products and modifications based on the generated image.

[0121] Step 7:

[0122] Finally, based on the information from the server, the user can select the optimal lifestyle products that minimize health risks. The input is the risk analysis results, and the output is a list of recommended products. The user then takes specific actions to make the best choice based on the information.

[0123] 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.

[0124] This invention relates to a system that recognizes a user's emotions and takes them into consideration when suggesting appearance changes to better suit the user's preferences. This system combines emotion data with information about the user's desired appearance changes to provide more personalized suggestions.

[0125] First, the user takes a picture of the requested image data using the camera function of their smartphone and temporarily saves it on the device. Next, the user enters information about the desired appearance changes into the application, and this data is also saved on the device. After this, the emotion engine infers and records the user's current emotional state from information such as their face, voice, and selected appearance.

[0126] The device sends image data, desired appearance change data, and emotion data to the server. The server receives this data, analyzes the image data to identify head features, and uses emotion data obtained from the emotion engine to adjust appearance change suggestions to suit the user's current emotional state. This process allows the generative AI model to optimize the predicted images of appearance change options.

[0127] The appearance change images generated from the server, along with the adjusted suggestions, are sent to the terminal and presented to the user. The user reviews these results and makes a decision on whether to adopt them. Furthermore, emotional data is shared with external professional experts, allowing for the provision of emotionally-driven professional advice.

[0128] As a concrete example, consider a user who is thinking about cutting their hair short but feels anxious. In this case, the emotion engine detects the user's anxiety and accordingly suggests a gradual style change that is not too drastic, presenting a style that provides reassurance. In this way, by utilizing emotion recognition, it is possible to implement appearance changes that are more personalized and result in higher user satisfaction.

[0129] The following describes the processing flow.

[0130] Step 1:

[0131] The user takes an image of their face or head using the camera on their smartphone. The device temporarily stores this image data in its memory.

[0132] Step 2:

[0133] The user enters their desired appearance changes on their device. For example, they can select a hairstyle or enter specific styling preferences and save them on their device.

[0134] Step 3:

[0135] The device analyzes the user's emotional state using an emotion engine based on their facial expressions and voice. The resulting emotional data is then stored on the device.

[0136] Step 4:

[0137] The device encrypts image data, appearance change request data, and emotion data and sends them to the server.

[0138] Step 5:

[0139] The server analyzes the received image data to identify the user's head features. Based on the analysis results, and taking into account emotional data and desired appearance changes, a generative AI model creates an image of the altered appearance.

[0140] Step 6:

[0141] The server generates a predicted appearance image and sends sentiment-based, optimized suggestions to the device. The data is encrypted and transmitted securely.

[0142] Step 7:

[0143] The device displays the received images and suggestions in the user interface. The user reviews the displayed information and decides whether it matches their preferences and feelings.

[0144] Step 8:

[0145] If there are changes based on the user's emotional state or preferences, feedback is sent from the device to the server. Furthermore, emotional data can be shared with external professional experts for advice as needed.

[0146] (Example 2)

[0147] 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".

[0148] In modern times, personal appearance customization is a significant concern for many people. However, conventional systems have struggled to provide flexible suggestions tailored to individual emotional states and specific needs. As a result, the accuracy and satisfaction of appearance customization often suffer from a decline in user expectations.

[0149] 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.

[0150] In this invention, the server includes means for acquiring personal image data and analyzing the personal head features from the image data; means for acquiring emotional data and adjusting appearance change suggestions based on the emotional data; and means for optimizing appearance change options using a generative AI model. This enables more personalized appearance change suggestions that are tailored to the user's emotional state and preferences.

[0151] "Personal image data" refers to digital data that represents visual information, including the user's physical characteristics.

[0152] "Means for analyzing head features" refers to a device or program that has the function of identifying and evaluating the shape of an individual's head and specific features from acquired personal image data.

[0153] "Desired appearance change data" refers to data that records information about the desired appearance state or changes that the user wants to achieve.

[0154] "Means for acquiring emotional data" refers to a device or software that analyzes the user's facial expressions and voice characteristics to generate data indicating their current emotional state.

[0155] "Means for optimizing appearance modification options" refers to a device or program that utilizes a generative AI model to calculate and present the most appropriate appearance modification options based on the user's preferences and emotional state.

[0156] "Data transmission means" refers to communication means for securely transmitting acquired and generated data to another device or user.

[0157] The following describes embodiments for carrying out the present invention.

[0158] This invention is a system for suggesting appearance changes that takes into account the user's emotional state. The user acquires image data of themselves using the camera function of their smartphone and inputs data on desired appearance changes into a dedicated application. This data is temporarily stored on the device.

[0159] The device uses a built-in emotion engine to acquire emotional data from the user's face and voice. The emotion engine utilizes image processing and voice analysis technologies to infer emotions from the user's facial expressions and tone of voice.

[0160] The device securely transmits acquired image data, desired appearance changes, and sentiment data to the server. The server uses a dedicated image analysis algorithm to identify the user's head features from the image data and uses a generative AI model based on the sentiment data to refine the appearance change suggestions. This model generates the optimal appearance change option by comparing it with existing data.

[0161] For example, when a user requests a change in hairstyle, if the emotion engine detects anxiety, the server can suggest a style that provides reassurance by proposing gradual changes. This suggestion is sent to the user's device, where the user reviews the results and decides whether to accept them.

[0162] An example of a prompt message is: "Generate a predictive image that suggests appearance modification options tailored to the user's preferences, based on their current emotions."

[0163] This system aims to increase user satisfaction by generating personalized suggestions that take emotional data into consideration.

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] The user takes a picture of themselves using the camera function of their smartphone to obtain data on the parts of their appearance they wish to change. Subsequently, they input data on their desired appearance changes (e.g., wanting to shorten their hair) through a dedicated application. This data is temporarily stored on the device. Image data and desired data in text format are obtained as input data and used in the next processing step.

[0167] Step 2:

[0168] The device uses a built-in emotion engine to analyze the user's facial expressions and voice, and acquire emotional data. The emotion engine uses image analysis technology to extract facial features from image data and voice analysis technology to analyze voice tone, thereby inferring the emotional state. The input data consists of captured images and audio data, and the output data represents the user's emotional state.

[0169] Step 3:

[0170] The device sends image data acquired in Step 1, desired appearance change data, and emotion data acquired in Step 2 to the server. This transmission is performed using a secure communication protocol. The input data includes encrypted data to protect user privacy.

[0171] Step 4:

[0172] The server identifies the user's head features from image data using an image analysis algorithm. Next, it uses a generative AI model based on emotion data to refine suggestions for appearance changes appropriate to the user's emotional state. This creates a predicted image of the appearance change. The input data consists of user data and emotion data requiring image analysis, and the output consists of the generated predicted image and suggested data of the appearance change.

[0173] Step 5:

[0174] The server generates a predicted image of the appearance change and sends the adjusted suggestion to the terminal for the user to view. The user reviews this and determines whether the suggestion matches their preferences. A feedback function allows the user to send their thoughts on the suggestion back to the server. The output data is the appearance change suggestion that the user views on the screen.

[0175] Step 6:

[0176] If necessary, the server shares sentiment data and appearance change results with external experts. This sharing allows users to receive expert advice based on their emotions. Input data includes the shared sentiment data and appearance change results, while output includes feedback and additional suggestions from experts.

[0177] (Application Example 2)

[0178] 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".

[0179] When individuals request changes to their device's appearance, they typically only receive fixed style suggestions, lacking personalized options that take into account the user's emotional state. Furthermore, there is a need for a system that easily incorporates professional opinions. This presents a challenge in reducing user anxiety and dissatisfaction, and enabling appearance changes that better suit their needs.

[0180] 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.

[0181] In this invention, the server includes means for acquiring personal image data and analyzing features from said data; means for analyzing the personal emotional state and adjusting appearance modification options based on that emotion; and means for sharing the adjusted appearance modification suggestions with an external organization and obtaining expert advice. This enables personalized appearance modifications that respond to the user's emotional state, thereby improving user satisfaction.

[0182] "Personal image data" refers to visual data used to obtain information about a user's appearance.

[0183] "Means of feature analysis" refers to methods for analyzing the visual elements obtained from image data and numerically evaluating their structure and characteristics.

[0184] "Desired appearance change data" refers to information about the appearance changes that the user wishes to make.

[0185] "Data generation means" refers to a processing method that generates newly proposed appearance information based on analyzed features and desired changes.

[0186] "Means of presentation on a display device" refers to a method relating to an apparatus or system for visually showing the results of the generated changes in appearance.

[0187] "Methods for analyzing emotional state" refer to methods for processing information obtained from a user's facial expressions and voice to infer their current emotional state.

[0188] "Means of sharing data with external organizations" refers to methods of sharing generated data with other professional organizations or individuals to obtain further feedback and advice.

[0189] The system for implementing this invention mainly consists of a user's device (such as a smartphone) and a server connected via a network. First, the user uses the smartphone's camera function to acquire image data and temporarily stores that data. Next, the user enters their desired appearance changes into the application, and this data is also stored on the device.

[0190] The server analyzes image data transmitted from the user's terminal to identify individual characteristics. Image processing libraries such as OpenCV are used for the analysis. Furthermore, an emotion engine utilizing TENSORFLOW® is used to perform emotion analysis from the user's voice and facial expressions. The results of the emotion analysis are useful in inferring the user's current emotional state.

[0191] Based on this emotional state, the server adjusts the appearance change options and creates an optimized predictive image using a generative AI model. The adjusted appearance suggestions are sent to the user's terminal via a user interface such as Flask. The user reviews the presented options and decides whether to adopt the appearance change.

[0192] For example, if a user wants to relax on Sunday, the system will detect the user's calm mood and suggest a casual loungewear style in soft colors. To support this process, the generating AI model is input with the following prompt: "If the user wants to have a relaxing Sunday, please suggest the most appropriate casual clothing style."

[0193] This allows for the provision of appearance modification suggestions that better match the user's emotions and desires, resulting in increased user satisfaction.

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The user uses their smartphone's camera to acquire image data of themselves and temporarily saves it to the device. In this process, the input is the user's face image, and the output is the image data saved to the device's local storage.

[0197] Step 2:

[0198] The user enters data requesting changes to the application's appearance. This data includes specific style and color preferences. The input represents the user's desired appearance information, while the output is the requested change data stored on the device.

[0199] Step 3:

[0200] The terminal sends image data and data requesting changes to the server. The input is the terminal's image data and change request data, and the output is user data securely transferred to the server.

[0201] Step 4:

[0202] The server analyzes the received image data using OpenCV to identify the user's features. The input for this step is image data, and the output generates numerical data about the structure and features of the face.

[0203] Step 5:

[0204] The server uses TensorFlow to analyze the user's emotional state. Facial expressions and audio data are input, and inferred data indicating the emotional state is output.

[0205] Step 6:

[0206] The server uses a generative AI model to adjust appearance change suggestions based on emotional states and user preferences. The input is analyzed emotional and preference data, and the server outputs adjusted appearance change options.

[0207] Step 7:

[0208] The server sends the adjusted appearance change suggestions to the user's terminal via Flask. The input here is the server-side appearance change options, and the output is the style suggestions displayed on the user's terminal.

[0209] Step 8:

[0210] The user reviews the received suggestions and decides whether to adopt the appearance changes. The input in this step is the appearance suggestions, and the user's selection is saved as the output.

[0211] Step 9:

[0212] If necessary, the server requests the generated AI model using specific prompt statements and shares data with external organizations. In this step, prompt statements are used as input, and external feedback and advice are output.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] 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.

[0219] 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).

[0220] 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.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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".

[0229] This invention is a system that allows users to visually confirm changes in their appearance based on their personal preferences while minimizing risks during the process. Specifically, it photographs the user's face and head, and then inputs their preferences for beauty treatments and haircuts as digital data. The system aims to improve user satisfaction through this series of processes.

[0230] The first step for the user is to take an image of their face or head using the camera on their smartphone. The device temporarily stores this image data and prepares to send it to the server. At the same time, the user selects their desired style from several provided appearance modification options and enters this information on the device. This information is also sent to the server.

[0231] The server analyzes the received image data to identify the user's head features and generates an image of the desired hairstyle based on that information. The generative model used here has learned from past data and the latest trends, enabling it to generate more accurate images. The generated image is sent to the user's terminal, where it can be viewed.

[0232] Furthermore, users can register health data, such as allergies, through their devices. This information is stored on a server and used, as needed, to verify whether the appearance modification options selected by the user pose any health risks. The system can also provide risk information tailored to the user's health status to external experts, thus contributing to improved safety.

[0233] For example, if a user selects a short bob style, the server generates an image of the most suitable hairstyle for that style based on the user's head characteristics and calculates risk avoidance information for each step. For instance, if an allergy to a specific chemical is registered, the server uses that information to check whether the modified style can be safely implemented.

[0234] This system provides users with predictive images of their desired appearance and helps them manage health risks in advance, thereby supporting the realization of ideal services.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The user takes an image of their face or head using the camera on their smartphone. The device temporarily stores this image data in its internal memory.

[0238] Step 2:

[0239] The user enters their desired appearance change options through the application on their device. The device records the selected appearance change information and prepares to send it to the server.

[0240] Step 3:

[0241] The image data captured by the device and the user's selected appearance modification data are compressed and encrypted, and then securely transmitted to the server.

[0242] Step 4:

[0243] The server analyzes the received image data and uses facial recognition technology to identify the user's head features. Based on this information and the user's selected appearance changes, the server inputs the data into a generating AI model.

[0244] Step 5:

[0245] The server uses a generated AI model to create a predictive appearance image that best suits the user's head features. Furthermore, it analyzes potential risks to the user's health data.

[0246] Step 6:

[0247] The server sends back the predicted appearance image and risk analysis information it generates to the terminal. This data is also encrypted again and transferred securely.

[0248] Step 7:

[0249] The terminal decodes the received data and presents the generated appearance image to the user via the user interface. The user reviews the result and makes a decision on whether to change the appearance.

[0250] Step 8:

[0251] If necessary, the device transmits the user's health data and risk information to external professional experts. Based on this information, the user can receive advice on how to perform safe procedures.

[0252] (Example 1)

[0253] 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."

[0254] When individuals attempt to modify their appearance as they wish, a challenge exists in that it is difficult to confirm the visual image beforehand. Furthermore, there is a lack of means to assess the health risks associated with appearance changes in advance, making it difficult to ensure safety. Additionally, there are challenges in incorporating expert opinions into evaluations due to insufficient methods for smoothly sharing information with external experts.

[0255] 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.

[0256] In this invention, the server includes means for acquiring an individual's characteristics and analyzing the individual's head from those characteristics, means for inputting the individual's desired appearance changes based on their choices, and means for generating images corresponding to the head information and the desired changes for proposing multiple appearance change options. This allows the user to visually confirm the result before changing their appearance, evaluate health risks in advance, and safely change their appearance. Furthermore, by sharing the obtained information with external experts, they can receive more accurate advice.

[0257] "Personal characteristics" refer to specific attributes and data related to an individual's appearance, including facial and head shape, hairline, and skin tone.

[0258] "Methods for analyzing the head" refer to methods that use image processing and artificial intelligence technology to identify individual head features from captured images and extract specific information.

[0259] "Requests for changes to appearance" refer to the user's preferences and requests regarding changes to their appearance, such as hairstyle or makeup.

[0260] The "image generation method" is a technology that creates a virtual finished image using a generation AI model based on the user's head characteristics and desired style information.

[0261] "Health status information" refers to medical information related to maintaining health, such as an individual's allergies and medical history.

[0262] "Risk information" refers to an assessment of the safety of products and methods used for cosmetic modifications, and includes explanations and warnings about events that may affect the user's health.

[0263] "External experts" refer to professionals with advanced knowledge and skills in related fields such as beauty and medicine.

[0264] This invention is a system aimed at visually confirming desired appearance changes and pre-assessing health risks. Specifically, it is implemented in the following way.

[0265] The user takes an image of their face or head using the camera on a device such as a smartphone or tablet. The captured image data is temporarily stored by the device and then prepared to be sent to the server. At the same time, the user selects a desired style from several appearance modification options provided on the device and sends that information to the server as well.

[0266] Upon receiving a series of pieces of information, the server analyzes the user's head features using an image processing algorithm. This analysis employs a generative AI model, incorporating the results of learning from past data and trends. Based on the received head features and the user's desired appearance changes, the server generates an optimal finished image for the user. This generated image is sent to the user's device, where the user can review it.

[0267] Furthermore, users can input allergy information and health status data through their devices. This data is stored on a server and used to determine whether appearance modification options pose health risks. If necessary, this risk information is also provided to external experts to enhance safety.

[0268] For example, if a user requests a short bob hairstyle, the server will generate an image suitable for this style based on the user's head features. If allergy information to specific medications is registered, the server will also take that information into consideration to determine if the new style can be safely implemented.

[0269] An example of a prompt to input into the generating AI model is, "Based on the user's current facial image and their desired short bob hairstyle, generate the optimal finished image and calculate risk information." This prompt allows the system to provide highly accurate predictive images.

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] The user takes an image of their face or head using the camera on a device such as a smartphone. The captured image data is temporarily stored on the device. Specifically, the user launches the camera app and captures the image. The input at this stage is the user's face image, and the output is the saved image file.

[0273] Step 2:

[0274] The user reviews the appearance customization options provided on the device and selects their desired style. This information is then entered into the application on the device. Specifically, the user scrolls through different style options on the app screen and taps the style they like. The input at this stage is the appearance customization option, and the output is the style data selected by the user.

[0275] Step 3:

[0276] The terminal performs preprocessing to send the captured image data and selected style information to the server. Specifically, it converts this data into an appropriate format and then encrypts it for security. The input at this stage is the image data and style data, and the output is the encrypted data ready for transmission.

[0277] Step 4:

[0278] The server analyzes the received image data and style information. It extracts the user's head features from the image data and generates an image based on the style information. Specifically, it uses an image processing algorithm and a generative AI model to analyze head feature data and generate a visual image that best suits the desired style. The input at this stage is encrypted image data and style information, and the output is the generated finished image.

[0279] Step 5:

[0280] The server sends the generated image to the user's terminal, and the user views the image on the terminal. Specifically, the server receives response data from the server and displays the image through the application. At this stage, the input is the generated image data, and the output is the displayed visual image.

[0281] Step 6:

[0282] The user inputs allergy information and health status data through the terminal and sends it to the server. As a specific operation, it is to fill in the data required in the health information input form and tap the send button. The input at this stage is health information, and the output is the health data recorded on the server.

[0283] Step 7:

[0284] Based on the received health information, the server evaluates the risks potential in the selected appearance change options. If risk information is identified, it notifies the user. As a specific operation, it performs a database search and makes an automatic determination based on the registered health concerns. The input at this stage is the user's health data and the appearance change options, and the output is the risk assessment result.

[0285] (Application Example 1)

[0286] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0287] When changing an individual's appearance, it is difficult to accurately predict what the desired style will look like in advance, and furthermore, means for appropriately managing the health risks in the process are required. Also, there is a lack of a system that can smoothly handle individual style selections within the home and provide appropriate advice.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0289] In this invention, the server includes means for acquiring an individual's image data and analyzing the individual's head features from the image data; means for inputting data on desired appearance changes based on the individual's choices; and means for generating images corresponding to the head features and the desired changes, for proposing a plurality of appearance change option data. This allows users to visually confirm the desired appearance changes in advance, and also enables the suggestion of lifestyle products that take health information into consideration.

[0290] "Image data" refers to visual information obtained in digital format from an individual's appearance and used for analysis.

[0291] "Head features" refer to characteristics related to the shape and pattern of an individual's face and head, and are elements used to predict changes in appearance.

[0292] "Requested change data" refers to information describing the appearance changes that an individual desires, and is based on style selection.

[0293] "Image generation means" refers to a technical means for visually presenting multiple appearance modification options based on analyzed data.

[0294] A "display device" is hardware used to visually present the generated appearance change results to the user.

[0295] "Health status information" refers to data about an individual's physical health, and is information that is considered in order to implement safe appearance alterations.

[0296] "Daily necessities" are items related to an individual's daily life, and are intended to support appropriate choices based on health information.

[0297] The system implementing this invention supports personal appearance modification, allowing users to send their appearance data to a server using a smartphone or home appliance. The server analyzes the individual's head features from the received image data and generates multiple appearance modification options using a generative AI model based on the user's selected desired appearance modification data. This allows users to visually confirm the changes beforehand.

[0298] Furthermore, the server considers the user's health data, analyzes the health risks associated with appearance changes, and provides this information to the user. This makes it possible to address health concerns related to appearance changes in advance. As a display device, a smartphone or robot display is used to visually show the user images of the generated style and information on health risks.

[0299] As a concrete example, there is a process where the user selects their desired hairstyle, and the server generates a style image based on that. The user can then choose an appearance that suits them based on this generated image, and at the same time, appropriate lifestyle products are suggested based on allergy test results.

[0300] By using a generative AI model, it becomes possible to provide users with the latest fashion trends and personalized style suggestions. An example of a prompt to input into the generative AI model is, "Generate a hairstyle as an image that reflects the user's desired appearance change, and display a suggestion that also takes health risks into consideration." This system makes it easy to implement personalized appearance changes tailored to individual needs.

[0301] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0302] Step 1:

[0303] The user uses a mobile terminal to take pictures of their face and head. The data input is image data, and the terminal temporarily stores this image and prepares it for transmission to the server.

[0304] Step 2:

[0305] The terminal sends the desired data for appearance changes selected by the user to the server. At this point, the server receives both the image data and the desired data. The input is the image data and the desired change data, and the output is these data stored in the server.

[0306] Step 3:

[0307] The server uses a generative AI model to start analyzing the received image data. Here, head features are extracted. The input is the image data, and the output is the analyzed head feature data. As data processing, specific feature extraction using an image analysis algorithm is performed.

[0308] Step 4:

[0309] The server generates multiple appearance change options based on the analyzed head feature data and the style desired data selected by the user. A style image is generated using a generative AI model. The input for this step is the head feature data and the desired appearance change data, and the output is multiple appearance images.

[0310] Step 5:

[0311] The results are sent to the terminal, and the user checks the generated style images through the display device. The input is the generated group of appearance images, and the output is the user's visual confirmation result.

[0312] Step 6:

[0313] Considering the user's health status data, the server analyzes health risks associated with the generation style. This includes allergy data. The input is health status data, and the output is the risk analysis results. Data calculations are performed to verify the safety of available products and modifications based on the generated image.

[0314] Step 7:

[0315] Finally, based on the information from the server, the user can select the optimal lifestyle products that minimize health risks. The input is the risk analysis results, and the output is a list of recommended products. The user then takes specific actions to make the best choice based on the information.

[0316] 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.

[0317] This invention relates to a system that recognizes a user's emotions and takes them into consideration when suggesting appearance changes to better suit the user's preferences. This system combines emotion data with information about the user's desired appearance changes to provide more personalized suggestions.

[0318] First, the user takes a picture of the requested image data using the camera function of their smartphone and temporarily saves it on the device. Next, the user enters information about the desired appearance changes into the application, and this data is also saved on the device. After this, the emotion engine infers and records the user's current emotional state from information such as their face, voice, and selected appearance.

[0319] The device sends image data, desired appearance change data, and emotion data to the server. The server receives this data, analyzes the image data to identify head features, and uses emotion data obtained from the emotion engine to adjust appearance change suggestions to suit the user's current emotional state. This process allows the generative AI model to optimize the predicted images of appearance change options.

[0320] The appearance change images generated from the server, along with the adjusted suggestions, are sent to the terminal and presented to the user. The user reviews these results and makes a decision on whether to adopt them. Furthermore, emotional data is shared with external professional experts, allowing for the provision of emotionally-driven professional advice.

[0321] As a concrete example, consider a user who is thinking about cutting their hair short but feels anxious. In this case, the emotion engine detects the user's anxiety and accordingly suggests a gradual style change that is not too drastic, presenting a style that provides reassurance. In this way, by utilizing emotion recognition, it is possible to implement appearance changes that are more personalized and result in higher user satisfaction.

[0322] The following describes the processing flow.

[0323] Step 1:

[0324] The user takes an image of their face or head using the camera on their smartphone. The device temporarily stores this image data in its memory.

[0325] Step 2:

[0326] The user enters their desired appearance changes on their device. For example, they can select a hairstyle or enter specific styling preferences and save them on their device.

[0327] Step 3:

[0328] The device analyzes the user's emotional state using an emotion engine based on their facial expressions and voice. The resulting emotional data is then stored on the device.

[0329] Step 4:

[0330] The device encrypts image data, appearance change request data, and emotion data and sends them to the server.

[0331] Step 5:

[0332] The server analyzes the received image data to identify the user's head features. Based on the analysis results, and taking into account emotional data and desired appearance changes, a generative AI model creates an image of the altered appearance.

[0333] Step 6:

[0334] The server generates a predicted appearance image and sends sentiment-based, optimized suggestions to the device. The data is encrypted and transmitted securely.

[0335] Step 7:

[0336] The device displays the received images and suggestions in the user interface. The user reviews the displayed information and decides whether it matches their preferences and feelings.

[0337] Step 8:

[0338] If there are changes based on the user's emotional state or preferences, feedback is sent from the device to the server. Furthermore, emotional data can be shared with external professional experts for advice as needed.

[0339] (Example 2)

[0340] 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".

[0341] In modern times, personal appearance customization is a significant concern for many people. However, conventional systems have struggled to provide flexible suggestions tailored to individual emotional states and specific needs. As a result, the accuracy and satisfaction of appearance customization often suffer from a decline in user expectations.

[0342] 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.

[0343] In this invention, the server includes means for acquiring personal image data and analyzing the personal head features from the image data; means for acquiring emotional data and adjusting appearance change suggestions based on the emotional data; and means for optimizing appearance change options using a generative AI model. This enables more personalized appearance change suggestions that are tailored to the user's emotional state and preferences.

[0344] "Personal image data" refers to digital data that represents visual information, including the user's physical characteristics.

[0345] "Means for analyzing head features" refers to a device or program that has the function of identifying and evaluating the shape of an individual's head and specific features from acquired personal image data.

[0346] "Desired appearance change data" refers to data that records information about the desired appearance state or changes that the user wants to achieve.

[0347] "Means for acquiring emotional data" refers to a device or software that analyzes the user's facial expressions and voice characteristics to generate data indicating their current emotional state.

[0348] "Means for optimizing appearance modification options" refers to a device or program that utilizes a generative AI model to calculate and present the most appropriate appearance modification options based on the user's preferences and emotional state.

[0349] "Data transmission means" refers to communication means for securely transmitting acquired and generated data to another device or user.

[0350] The following describes embodiments for carrying out the present invention.

[0351] This invention is a system for suggesting appearance changes that takes into account the user's emotional state. The user acquires image data of themselves using the camera function of their smartphone and inputs data on desired appearance changes into a dedicated application. This data is temporarily stored on the device.

[0352] The device uses a built-in emotion engine to acquire emotional data from the user's face and voice. The emotion engine utilizes image processing and voice analysis technologies to infer emotions from the user's facial expressions and tone of voice.

[0353] The device securely transmits acquired image data, desired appearance changes, and sentiment data to the server. The server uses a dedicated image analysis algorithm to identify the user's head features from the image data and uses a generative AI model based on the sentiment data to refine the appearance change suggestions. This model generates the optimal appearance change option by comparing it with existing data.

[0354] For example, when a user requests a change in hairstyle, if the emotion engine detects anxiety, the server can suggest a style that provides reassurance by proposing gradual changes. This suggestion is sent to the user's device, where the user reviews the results and decides whether to accept them.

[0355] An example of a prompt message is: "Generate a predictive image that suggests appearance modification options tailored to the user's preferences, based on their current emotions."

[0356] This system aims to increase user satisfaction by generating personalized suggestions that take emotional data into consideration.

[0357] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0358] Step 1:

[0359] The user takes a picture of themselves using the camera function of their smartphone to obtain data on the parts of their appearance they wish to change. Subsequently, they input data on their desired appearance changes (e.g., wanting to shorten their hair) through a dedicated application. This data is temporarily stored on the device. Image data and desired data in text format are obtained as input data and used in the next processing step.

[0360] Step 2:

[0361] The device uses a built-in emotion engine to analyze the user's facial expressions and voice, and acquire emotional data. The emotion engine uses image analysis technology to extract facial features from image data and voice analysis technology to analyze voice tone, thereby inferring the emotional state. The input data consists of captured images and audio data, and the output data represents the user's emotional state.

[0362] Step 3:

[0363] The device sends image data acquired in Step 1, desired appearance change data, and emotion data acquired in Step 2 to the server. This transmission is performed using a secure communication protocol. The input data includes encrypted data to protect user privacy.

[0364] Step 4:

[0365] The server identifies the user's head features from image data using an image analysis algorithm. Next, it uses a generative AI model based on emotion data to refine suggestions for appearance changes appropriate to the user's emotional state. This creates a predicted image of the appearance change. The input data consists of user data and emotion data requiring image analysis, and the output consists of the generated predicted image and suggested data of the appearance change.

[0366] Step 5:

[0367] The server generates a predicted image of the appearance change and sends the adjusted suggestion to the terminal for the user to view. The user reviews this and determines whether the suggestion matches their preferences. A feedback function allows the user to send their thoughts on the suggestion back to the server. The output data is the appearance change suggestion that the user views on the screen.

[0368] Step 6:

[0369] If necessary, the server shares sentiment data and appearance change results with external experts. This sharing allows users to receive expert advice based on their emotions. Input data includes the shared sentiment data and appearance change results, while output includes feedback and additional suggestions from experts.

[0370] (Application Example 2)

[0371] 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 as the "terminal".

[0372] When individuals request changes to their device's appearance, they typically only receive fixed style suggestions, lacking personalized options that take into account the user's emotional state. Furthermore, there is a need for a system that easily incorporates professional opinions. This presents a challenge in reducing user anxiety and dissatisfaction, and enabling appearance changes that better suit their needs.

[0373] 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.

[0374] In this invention, the server includes means for acquiring personal image data and analyzing features from said data; means for analyzing the personal emotional state and adjusting appearance modification options based on that emotion; and means for sharing the adjusted appearance modification suggestions with an external organization and obtaining expert advice. This enables personalized appearance modifications that respond to the user's emotional state, thereby improving user satisfaction.

[0375] "Personal image data" refers to visual data used to obtain information about a user's appearance.

[0376] "Means of feature analysis" refers to methods for analyzing the visual elements obtained from image data and numerically evaluating their structure and characteristics.

[0377] "Desired appearance change data" refers to information about the appearance changes that the user wishes to make.

[0378] "Data generation means" refers to a processing method that generates newly proposed appearance information based on analyzed features and desired changes.

[0379] "Means of presentation on a display device" refers to a method relating to an apparatus or system for visually showing the results of the generated changes in appearance.

[0380] "Methods for analyzing emotional state" refer to methods for processing information obtained from a user's facial expressions and voice to infer their current emotional state.

[0381] "Means of sharing data with external organizations" refers to methods of sharing generated data with other professional organizations or individuals to obtain further feedback and advice.

[0382] The system for implementing this invention mainly consists of a user's device (such as a smartphone) and a server connected via a network. First, the user uses the smartphone's camera function to acquire image data and temporarily stores that data. Next, the user enters their desired appearance changes into the application, and this data is also stored on the device.

[0383] The server analyzes image data transmitted from the user's terminal to identify individual characteristics. Image processing libraries such as OpenCV are used for the analysis. Additionally, a TensorFlow-based emotion engine is employed to perform emotion analysis based on the user's voice and facial expressions. The results of the emotion analysis are useful in inferring the user's current emotional state.

[0384] Based on this emotional state, the server adjusts the appearance change options and creates an optimized predictive image using a generative AI model. The adjusted appearance suggestions are sent to the user's terminal via a user interface such as Flask. The user reviews the presented options and decides whether to adopt the appearance change.

[0385] For example, if a user wants to relax on Sunday, the system will detect the user's calm mood and suggest a casual loungewear style in soft colors. To support this process, the generating AI model is input with the following prompt: "If the user wants to have a relaxing Sunday, please suggest the most appropriate casual clothing style."

[0386] This allows for the provision of appearance modification suggestions that better match the user's emotions and desires, resulting in increased user satisfaction.

[0387] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0388] Step 1:

[0389] The user uses their smartphone's camera to acquire image data of themselves and temporarily saves it to the device. In this process, the input is the user's face image, and the output is the image data saved to the device's local storage.

[0390] Step 2:

[0391] The user enters data requesting changes to the application's appearance. This data includes specific style and color preferences. The input represents the user's desired appearance information, while the output is the requested change data stored on the device.

[0392] Step 3:

[0393] The terminal sends image data and data requesting changes to the server. The input is the terminal's image data and change request data, and the output is user data securely transferred to the server.

[0394] Step 4:

[0395] The server analyzes the received image data using OpenCV to identify the user's features. The input for this step is image data, and the output generates numerical data about the structure and features of the face.

[0396] Step 5:

[0397] The server uses TensorFlow to analyze the user's emotional state. Facial expressions and audio data are input, and inferred data indicating the emotional state is output.

[0398] Step 6:

[0399] The server uses a generative AI model to adjust appearance change suggestions based on emotional states and user preferences. The input is analyzed emotional and preference data, and the server outputs adjusted appearance change options.

[0400] Step 7:

[0401] The server sends the adjusted appearance change suggestions to the user's terminal via Flask. The input here is the server-side appearance change options, and the output is the style suggestions displayed on the user's terminal.

[0402] Step 8:

[0403] The user reviews the received suggestions and decides whether to adopt the appearance changes. The input in this step is the appearance suggestions, and the user's selection is saved as the output.

[0404] Step 9:

[0405] If necessary, the server requests the generated AI model using specific prompt statements and shares data with external organizations. In this step, prompt statements are used as input, and external feedback and advice are output.

[0406] 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.

[0407] 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.

[0408] 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.

[0409] [Third Embodiment]

[0410] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0411] 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.

[0412] 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).

[0413] 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.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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".

[0422] This invention is a system that allows users to visually confirm changes in their appearance based on their personal preferences while minimizing risks during the process. Specifically, it photographs the user's face and head, and then inputs their preferences for beauty treatments and haircuts as digital data. The system aims to improve user satisfaction through this series of processes.

[0423] The first step for the user is to take an image of their face or head using the camera on their smartphone. The device temporarily stores this image data and prepares to send it to the server. At the same time, the user selects their desired style from several provided appearance modification options and enters this information on the device. This information is also sent to the server.

[0424] The server analyzes the received image data to identify the user's head features and generates an image of the desired hairstyle based on that information. The generative model used here has learned from past data and the latest trends, enabling it to generate more accurate images. The generated image is sent to the user's terminal, where it can be viewed.

[0425] Furthermore, users can register health data, such as allergies, through their devices. This information is stored on a server and used, as needed, to verify whether the appearance modification options selected by the user pose any health risks. The system can also provide risk information tailored to the user's health status to external experts, thus contributing to improved safety.

[0426] For example, if a user selects a short bob style, the server generates an image of the most suitable hairstyle for that style based on the user's head characteristics and calculates risk avoidance information for each step. For instance, if an allergy to a specific chemical is registered, the server uses that information to check whether the modified style can be safely implemented.

[0427] This system provides users with predictive images of their desired appearance and helps them manage health risks in advance, thereby supporting the realization of ideal services.

[0428] The following describes the processing flow.

[0429] Step 1:

[0430] The user takes an image of their face or head using the camera on their smartphone. The device temporarily stores this image data in its internal memory.

[0431] Step 2:

[0432] The user enters their desired appearance change options through the application on their device. The device records the selected appearance change information and prepares to send it to the server.

[0433] Step 3:

[0434] The image data captured by the device and the user's selected appearance modification data are compressed and encrypted, and then securely transmitted to the server.

[0435] Step 4:

[0436] The server analyzes the received image data and uses facial recognition technology to identify the user's head features. Based on this information and the user's selected appearance changes, the server inputs the data into a generating AI model.

[0437] Step 5:

[0438] The server uses a generated AI model to create a predictive appearance image that best suits the user's head features. Furthermore, it analyzes potential risks to the user's health data.

[0439] Step 6:

[0440] The server sends back the predicted appearance image and risk analysis information it generates to the terminal. This data is also encrypted again and transferred securely.

[0441] Step 7:

[0442] The terminal decodes the received data and presents the generated appearance image to the user via the user interface. The user reviews the result and makes a decision on whether to change the appearance.

[0443] Step 8:

[0444] If necessary, the device transmits the user's health data and risk information to external professional experts. Based on this information, the user can receive advice on how to perform safe procedures.

[0445] (Example 1)

[0446] 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."

[0447] When individuals attempt to modify their appearance as they wish, a challenge exists in that it is difficult to confirm the visual image beforehand. Furthermore, there is a lack of means to assess the health risks associated with appearance changes in advance, making it difficult to ensure safety. Additionally, there are challenges in incorporating expert opinions into evaluations due to insufficient methods for smoothly sharing information with external experts.

[0448] 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.

[0449] In this invention, the server includes means for acquiring an individual's characteristics and analyzing the individual's head from those characteristics, means for inputting the individual's desired appearance changes based on their choices, and means for generating images corresponding to the head information and the desired changes for proposing multiple appearance change options. This allows the user to visually confirm the result before changing their appearance, evaluate health risks in advance, and safely change their appearance. Furthermore, by sharing the obtained information with external experts, they can receive more accurate advice.

[0450] "Personal characteristics" refer to specific attributes and data related to an individual's appearance, including facial and head shape, hairline, and skin tone.

[0451] "Methods for analyzing the head" refer to methods that use image processing and artificial intelligence technology to identify individual head features from captured images and extract specific information.

[0452] "Requests for changes to appearance" refer to the user's preferences and requests regarding changes to their appearance, such as hairstyle or makeup.

[0453] The "image generation method" is a technology that creates a virtual finished image using a generation AI model based on the user's head characteristics and desired style information.

[0454] "Health status information" refers to medical information related to maintaining health, such as an individual's allergies and medical history.

[0455] "Risk information" refers to an assessment of the safety of products and methods used for cosmetic modifications, and includes explanations and warnings about events that may affect the user's health.

[0456] "External experts" refer to professionals with advanced knowledge and skills in related fields such as beauty and medicine.

[0457] This invention is a system aimed at visually confirming desired appearance changes and pre-assessing health risks. Specifically, it is implemented in the following way.

[0458] The user takes an image of their face or head using the camera on a device such as a smartphone or tablet. The captured image data is temporarily stored by the device and then prepared to be sent to the server. At the same time, the user selects a desired style from several appearance modification options provided on the device and sends that information to the server as well.

[0459] Upon receiving a series of pieces of information, the server analyzes the user's head features using an image processing algorithm. This analysis employs a generative AI model, incorporating the results of learning from past data and trends. Based on the received head features and the user's desired appearance changes, the server generates an optimal finished image for the user. This generated image is sent to the user's device, where the user can review it.

[0460] Furthermore, users can input allergy information and health status data through their devices. This data is stored on a server and used to determine whether appearance modification options pose health risks. If necessary, this risk information is also provided to external experts to enhance safety.

[0461] For example, if a user requests a short bob hairstyle, the server will generate an image suitable for this style based on the user's head features. If allergy information to specific medications is registered, the server will also take that information into consideration to determine if the new style can be safely implemented.

[0462] An example of a prompt to input into the generating AI model is, "Based on the user's current facial image and their desired short bob hairstyle, generate the optimal finished image and calculate risk information." This prompt allows the system to provide highly accurate predictive images.

[0463] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0464] Step 1:

[0465] The user takes an image of their face or head using the camera on a device such as a smartphone. The captured image data is temporarily stored on the device. Specifically, the user launches the camera app and captures the image. The input at this stage is the user's face image, and the output is the saved image file.

[0466] Step 2:

[0467] The user reviews the appearance customization options provided on the device and selects their desired style. This information is then entered into the application on the device. Specifically, the user scrolls through different style options on the app screen and taps the style they like. The input at this stage is the appearance customization option, and the output is the style data selected by the user.

[0468] Step 3:

[0469] The terminal performs preprocessing to send the captured image data and selected style information to the server. Specifically, it converts this data into an appropriate format and then encrypts it for security. The input at this stage is the image data and style data, and the output is the encrypted data ready for transmission.

[0470] Step 4:

[0471] The server analyzes the received image data and style information. It extracts the user's head features from the image data and generates an image based on the style information. Specifically, it uses an image processing algorithm and a generative AI model to analyze head feature data and generate a visual image that best suits the desired style. The input at this stage is encrypted image data and style information, and the output is the generated finished image.

[0472] Step 5:

[0473] The server sends the generated image to the user's terminal, and the user views the image on the terminal. Specifically, the server receives response data from the server and displays the image through the application. At this stage, the input is the generated image data, and the output is the displayed visual image.

[0474] Step 6:

[0475] Users input allergy information and health status data through their devices and send this data to the server. Specifically, this involves filling in the required data in a health information input form and tapping the submit button. The input at this stage is health information, and the output is health data recorded on the server.

[0476] Step 7:

[0477] The server evaluates the potential risks associated with the selected appearance modification option based on the received health information. If risk information is identified, the user is notified. Specifically, the server performs a database search and makes an automatic determination based on registered health concerns. The inputs at this stage are the user's health data and appearance modification options, and the output is the risk assessment result.

[0478] (Application Example 1)

[0479] 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."

[0480] When individuals change their appearance, it is difficult to accurately predict how their desired style will look beforehand, and there is a need for appropriate means to manage the health risks involved in the process. Furthermore, there is a lack of systems that can facilitate individual style selection within the home and provide appropriate advice.

[0481] 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.

[0482] In this invention, the server includes means for acquiring an individual's image data and analyzing the individual's head features from the image data; means for inputting data on desired appearance changes based on the individual's choices; and means for generating images corresponding to the head features and the desired changes, for proposing a plurality of appearance change option data. This allows users to visually confirm the desired appearance changes in advance, and also enables the suggestion of lifestyle products that take health information into consideration.

[0483] "Image data" refers to visual information obtained in digital format from an individual's appearance and used for analysis.

[0484] "Head features" refer to characteristics related to the shape and pattern of an individual's face and head, and are elements used to predict changes in appearance.

[0485] "Requested change data" refers to information describing the appearance changes that an individual desires, and is based on style selection.

[0486] "Image generation means" refers to a technical means for visually presenting multiple appearance modification options based on analyzed data.

[0487] A "display device" is hardware used to visually present the generated appearance change results to the user.

[0488] "Health status information" refers to data about an individual's physical health, and is information that is considered in order to implement safe appearance alterations.

[0489] "Daily necessities" are items related to an individual's daily life, and are intended to support appropriate choices based on health information.

[0490] The system implementing this invention supports personal appearance modification, allowing users to send their appearance data to a server using a smartphone or home appliance. The server analyzes the individual's head features from the received image data and generates multiple appearance modification options using a generative AI model based on the user's selected desired appearance modification data. This allows users to visually confirm the changes beforehand.

[0491] Furthermore, the server considers the user's health data, analyzes the health risks associated with appearance changes, and provides this information to the user. This makes it possible to address health concerns related to appearance changes in advance. As a display device, a smartphone or robot display is used to visually show the user images of the generated style and information on health risks.

[0492] As a concrete example, there is a process where the user selects their desired hairstyle, and the server generates a style image based on that. The user can then choose an appearance that suits them based on this generated image, and at the same time, appropriate lifestyle products are suggested based on allergy test results.

[0493] By using a generative AI model, it becomes possible to provide users with the latest fashion trends and personalized style suggestions. An example of a prompt to input into the generative AI model is, "Generate a hairstyle as an image that reflects the user's desired appearance change, and display a suggestion that also takes health risks into consideration." This system makes it easy to implement personalized appearance changes tailored to individual needs.

[0494] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0495] Step 1:

[0496] The user takes an image of their face or head using a mobile device. The input data is image data, which the device temporarily stores and prepares for transmission to the server.

[0497] Step 2:

[0498] The terminal sends the desired appearance change data selected by the user to the server. At this point, the server receives both the image data and the desired change data. The input is the image data and the desired change data, and the output is this data stored on the server.

[0499] Step 3:

[0500] The server uses a generative AI model to begin analyzing the received image data. Head features are extracted at this stage. The input is image data, and the output is the analyzed head feature data. Data processing involves the extraction of specific features using image analysis algorithms.

[0501] Step 4:

[0502] The server generates multiple appearance modification options based on the analyzed head feature data and the user's selected style preference data. A generation AI model is used to generate style images. The input for this step is head feature data and appearance modification preference data, and the output is multiple appearance images.

[0503] Step 5:

[0504] The results are sent to the terminal, and the user confirms the generated style image through the display device. The input is the set of generated appearance images, and the output is the user's visual confirmation result.

[0505] Step 6:

[0506] Considering the user's health status data, the server analyzes health risks associated with the generation style. This includes allergy data. The input is health status data, and the output is the risk analysis results. Data calculations are performed to verify the safety of available products and modifications based on the generated image.

[0507] Step 7:

[0508] Finally, based on the information from the server, the user can select the optimal lifestyle products that minimize health risks. The input is the risk analysis results, and the output is a list of recommended products. The user then takes specific actions to make the best choice based on the information.

[0509] 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.

[0510] This invention relates to a system that recognizes a user's emotions and takes them into consideration when suggesting appearance changes to better suit the user's preferences. This system combines emotion data with information about the user's desired appearance changes to provide more personalized suggestions.

[0511] First, the user takes a picture of the requested image data using the camera function of their smartphone and temporarily saves it on the device. Next, the user enters information about the desired appearance changes into the application, and this data is also saved on the device. After this, the emotion engine infers and records the user's current emotional state from information such as their face, voice, and selected appearance.

[0512] The device sends image data, desired appearance change data, and emotion data to the server. The server receives this data, analyzes the image data to identify head features, and uses emotion data obtained from the emotion engine to adjust appearance change suggestions to suit the user's current emotional state. This process allows the generative AI model to optimize the predicted images of appearance change options.

[0513] The appearance change images generated from the server, along with the adjusted suggestions, are sent to the terminal and presented to the user. The user reviews these results and makes a decision on whether to adopt them. Furthermore, emotional data is shared with external professional experts, allowing for the provision of emotionally-driven professional advice.

[0514] As a concrete example, consider a user who is thinking about cutting their hair short but feels anxious. In this case, the emotion engine detects the user's anxiety and accordingly suggests a gradual style change that is not too drastic, presenting a style that provides reassurance. In this way, by utilizing emotion recognition, it is possible to implement appearance changes that are more personalized and result in higher user satisfaction.

[0515] The following describes the processing flow.

[0516] Step 1:

[0517] The user takes an image of their face or head using the camera on their smartphone. The device temporarily stores this image data in its memory.

[0518] Step 2:

[0519] The user enters their desired appearance changes on their device. For example, they can select a hairstyle or enter specific styling preferences and save them on their device.

[0520] Step 3:

[0521] The device analyzes the user's emotional state using an emotion engine based on their facial expressions and voice. The resulting emotional data is then stored on the device.

[0522] Step 4:

[0523] The device encrypts image data, appearance change request data, and emotion data and sends them to the server.

[0524] Step 5:

[0525] The server analyzes the received image data to identify the user's head features. Based on the analysis results, and taking into account emotional data and desired appearance changes, a generative AI model creates an image of the altered appearance.

[0526] Step 6:

[0527] The server generates a predicted appearance image and sends sentiment-based, optimized suggestions to the device. The data is encrypted and transmitted securely.

[0528] Step 7:

[0529] The device displays the received images and suggestions in the user interface. The user reviews the displayed information and decides whether it matches their preferences and feelings.

[0530] Step 8:

[0531] If there are changes based on the user's emotional state or preferences, feedback is sent from the device to the server. Furthermore, emotional data can be shared with external professional experts for advice as needed.

[0532] (Example 2)

[0533] 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."

[0534] In modern times, personal appearance customization is a significant concern for many people. However, conventional systems have struggled to provide flexible suggestions tailored to individual emotional states and specific needs. As a result, the accuracy and satisfaction of appearance customization often suffer from a decline in user expectations.

[0535] 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.

[0536] In this invention, the server includes means for acquiring personal image data and analyzing the personal head features from the image data; means for acquiring emotional data and adjusting appearance change suggestions based on the emotional data; and means for optimizing appearance change options using a generative AI model. This enables more personalized appearance change suggestions that are tailored to the user's emotional state and preferences.

[0537] "Personal image data" refers to digital data that represents visual information, including the user's physical characteristics.

[0538] "Means for analyzing head features" refers to a device or program that has the function of identifying and evaluating the shape of an individual's head and specific features from acquired personal image data.

[0539] "Desired appearance change data" refers to data that records information about the desired appearance state or changes that the user wants to achieve.

[0540] "Means for acquiring emotional data" refers to a device or software that analyzes the user's facial expressions and voice characteristics to generate data indicating their current emotional state.

[0541] "Means for optimizing appearance modification options" refers to a device or program that utilizes a generative AI model to calculate and present the most appropriate appearance modification options based on the user's preferences and emotional state.

[0542] "Data transmission means" refers to communication means for securely transmitting acquired and generated data to another device or user.

[0543] The following describes embodiments for carrying out the present invention.

[0544] This invention is a system for suggesting appearance changes that takes into account the user's emotional state. The user acquires image data of themselves using the camera function of their smartphone and inputs data on desired appearance changes into a dedicated application. This data is temporarily stored on the device.

[0545] The device uses a built-in emotion engine to acquire emotional data from the user's face and voice. The emotion engine utilizes image processing and voice analysis technologies to infer emotions from the user's facial expressions and tone of voice.

[0546] The device securely transmits acquired image data, desired appearance changes, and sentiment data to the server. The server uses a dedicated image analysis algorithm to identify the user's head features from the image data and uses a generative AI model based on the sentiment data to refine the appearance change suggestions. This model generates the optimal appearance change option by comparing it with existing data.

[0547] For example, when a user requests a change in hairstyle, if the emotion engine detects anxiety, the server can suggest a style that provides reassurance by proposing gradual changes. This suggestion is sent to the user's device, where the user reviews the results and decides whether to accept them.

[0548] An example of a prompt message is: "Generate a predictive image that suggests appearance modification options tailored to the user's preferences, based on their current emotions."

[0549] This system aims to increase user satisfaction by generating personalized suggestions that take emotional data into consideration.

[0550] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0551] Step 1:

[0552] The user takes a picture of themselves using the camera function of their smartphone to obtain data on the parts of their appearance they wish to change. Subsequently, they input data on their desired appearance changes (e.g., wanting to shorten their hair) through a dedicated application. This data is temporarily stored on the device. Image data and desired data in text format are obtained as input data and used in the next processing step.

[0553] Step 2:

[0554] The device uses a built-in emotion engine to analyze the user's facial expressions and voice, and acquire emotional data. The emotion engine uses image analysis technology to extract facial features from image data and voice analysis technology to analyze voice tone, thereby inferring the emotional state. The input data consists of captured images and audio data, and the output data represents the user's emotional state.

[0555] Step 3:

[0556] The device sends image data acquired in Step 1, desired appearance change data, and emotion data acquired in Step 2 to the server. This transmission is performed using a secure communication protocol. The input data includes encrypted data to protect user privacy.

[0557] Step 4:

[0558] The server identifies the user's head features from image data using an image analysis algorithm. Next, it uses a generative AI model based on emotion data to refine suggestions for appearance changes appropriate to the user's emotional state. This creates a predicted image of the appearance change. The input data consists of user data and emotion data requiring image analysis, and the output consists of the generated predicted image and suggested data of the appearance change.

[0559] Step 5:

[0560] The server generates a predicted image of the appearance change and sends the adjusted suggestion to the terminal for the user to view. The user reviews this and determines whether the suggestion matches their preferences. A feedback function allows the user to send their thoughts on the suggestion back to the server. The output data is the appearance change suggestion that the user views on the screen.

[0561] Step 6:

[0562] If necessary, the server shares sentiment data and appearance change results with external experts. This sharing allows users to receive expert advice based on their emotions. Input data includes the shared sentiment data and appearance change results, while output includes feedback and additional suggestions from experts.

[0563] (Application Example 2)

[0564] 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."

[0565] When individuals request changes to their device's appearance, they typically only receive fixed style suggestions, lacking personalized options that take into account the user's emotional state. Furthermore, there is a need for a system that easily incorporates professional opinions. This presents a challenge in reducing user anxiety and dissatisfaction, and enabling appearance changes that better suit their needs.

[0566] 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.

[0567] In this invention, the server includes means for acquiring personal image data and analyzing features from said data; means for analyzing the personal emotional state and adjusting appearance modification options based on that emotion; and means for sharing the adjusted appearance modification suggestions with an external organization and obtaining expert advice. This enables personalized appearance modifications that respond to the user's emotional state, thereby improving user satisfaction.

[0568] "Personal image data" refers to visual data used to obtain information about a user's appearance.

[0569] "Means of feature analysis" refers to methods for analyzing the visual elements obtained from image data and numerically evaluating their structure and characteristics.

[0570] "Desired appearance change data" refers to information about the appearance changes that the user wishes to make.

[0571] "Data generation means" refers to a processing method that generates newly proposed appearance information based on analyzed features and desired changes.

[0572] "Means of presentation on a display device" refers to a method relating to an apparatus or system for visually showing the results of the generated changes in appearance.

[0573] "Methods for analyzing emotional state" refer to methods for processing information obtained from a user's facial expressions and voice to infer their current emotional state.

[0574] "Means of sharing data with external organizations" refers to methods of sharing generated data with other professional organizations or individuals to obtain further feedback and advice.

[0575] The system for implementing this invention mainly consists of a user's device (such as a smartphone) and a server connected via a network. First, the user uses the smartphone's camera function to acquire image data and temporarily stores that data. Next, the user enters their desired appearance changes into the application, and this data is also stored on the device.

[0576] The server analyzes image data transmitted from the user's terminal to identify individual characteristics. Image processing libraries such as OpenCV are used for the analysis. Additionally, a TensorFlow-based emotion engine is employed to perform emotion analysis based on the user's voice and facial expressions. The results of the emotion analysis are useful in inferring the user's current emotional state.

[0577] Based on this emotional state, the server adjusts the appearance change options and creates an optimized predictive image using a generative AI model. The adjusted appearance suggestions are sent to the user's terminal via a user interface such as Flask. The user reviews the presented options and decides whether to adopt the appearance change.

[0578] For example, if a user wants to relax on Sunday, the system will detect the user's calm mood and suggest a casual loungewear style in soft colors. To support this process, the generating AI model is input with the following prompt: "If the user wants to have a relaxing Sunday, please suggest the most appropriate casual clothing style."

[0579] This allows for the provision of appearance modification suggestions that better match the user's emotions and desires, resulting in increased user satisfaction.

[0580] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0581] Step 1:

[0582] The user uses their smartphone's camera to acquire image data of themselves and temporarily saves it to the device. In this process, the input is the user's face image, and the output is the image data saved to the device's local storage.

[0583] Step 2:

[0584] The user enters data requesting changes to the application's appearance. This data includes specific style and color preferences. The input represents the user's desired appearance information, while the output is the requested change data stored on the device.

[0585] Step 3:

[0586] The terminal sends image data and data requesting changes to the server. The input is the terminal's image data and change request data, and the output is user data securely transferred to the server.

[0587] Step 4:

[0588] The server analyzes the received image data using OpenCV to identify the user's features. The input for this step is image data, and the output generates numerical data about the structure and features of the face.

[0589] Step 5:

[0590] The server uses TensorFlow to analyze the user's emotional state. Facial expressions and audio data are input, and inferred data indicating the emotional state is output.

[0591] Step 6:

[0592] The server uses a generative AI model to adjust appearance change suggestions based on emotional states and user preferences. The input is analyzed emotional and preference data, and the server outputs adjusted appearance change options.

[0593] Step 7:

[0594] The server sends the adjusted appearance change suggestions to the user's terminal via Flask. The input here is the server-side appearance change options, and the output is the style suggestions displayed on the user's terminal.

[0595] Step 8:

[0596] The user reviews the received suggestions and decides whether to adopt the appearance changes. The input in this step is the appearance suggestions, and the user's selection is saved as the output.

[0597] Step 9:

[0598] If necessary, the server requests the generated AI model using specific prompt statements and shares data with external organizations. In this step, prompt statements are used as input, and external feedback and advice are output.

[0599] 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.

[0600] 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.

[0601] 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.

[0602] [Fourth Embodiment]

[0603] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0604] 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.

[0605] 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).

[0606] 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.

[0607] 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.

[0608] 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).

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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".

[0616] This invention is a system that allows users to visually confirm changes in their appearance based on their personal preferences while minimizing risks during the process. Specifically, it photographs the user's face and head, and then inputs their preferences for beauty treatments and haircuts as digital data. The system aims to improve user satisfaction through this series of processes.

[0617] The first step for the user is to take an image of their face or head using the camera on their smartphone. The device temporarily stores this image data and prepares to send it to the server. At the same time, the user selects their desired style from several provided appearance modification options and enters this information on the device. This information is also sent to the server.

[0618] The server analyzes the received image data to identify the user's head features and generates an image of the desired hairstyle based on that information. The generative model used here has learned from past data and the latest trends, enabling it to generate more accurate images. The generated image is sent to the user's terminal, where it can be viewed.

[0619] Furthermore, users can register health data, such as allergies, through their devices. This information is stored on a server and used, as needed, to verify whether the appearance modification options selected by the user pose any health risks. The system can also provide risk information tailored to the user's health status to external experts, thus contributing to improved safety.

[0620] For example, if a user selects a short bob style, the server generates an image of the most suitable hairstyle for that style based on the user's head characteristics and calculates risk avoidance information for each step. For instance, if an allergy to a specific chemical is registered, the server uses that information to check whether the modified style can be safely implemented.

[0621] This system provides users with predictive images of their desired appearance and helps them manage health risks in advance, thereby supporting the realization of ideal services.

[0622] The following describes the processing flow.

[0623] Step 1:

[0624] The user takes an image of their face or head using the camera on their smartphone. The device temporarily stores this image data in its internal memory.

[0625] Step 2:

[0626] The user enters their desired appearance change options through the application on their device. The device records the selected appearance change information and prepares to send it to the server.

[0627] Step 3:

[0628] The image data captured by the device and the user's selected appearance modification data are compressed and encrypted, and then securely transmitted to the server.

[0629] Step 4:

[0630] The server analyzes the received image data and uses facial recognition technology to identify the user's head features. Based on this information and the user's selected appearance changes, the server inputs the data into a generating AI model.

[0631] Step 5:

[0632] The server uses a generated AI model to create a predictive appearance image that best suits the user's head features. Furthermore, it analyzes potential risks to the user's health data.

[0633] Step 6:

[0634] The server sends back the predicted appearance image and risk analysis information it generates to the terminal. This data is also encrypted again and transferred securely.

[0635] Step 7:

[0636] The terminal decodes the received data and presents the generated appearance image to the user via the user interface. The user reviews the result and makes a decision on whether to change the appearance.

[0637] Step 8:

[0638] If necessary, the device transmits the user's health data and risk information to external professional experts. Based on this information, the user can receive advice on how to perform safe procedures.

[0639] (Example 1)

[0640] 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".

[0641] When individuals attempt to modify their appearance as they wish, a challenge exists in that it is difficult to confirm the visual image beforehand. Furthermore, there is a lack of means to assess the health risks associated with appearance changes in advance, making it difficult to ensure safety. Additionally, there are challenges in incorporating expert opinions into evaluations due to insufficient methods for smoothly sharing information with external experts.

[0642] 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.

[0643] In this invention, the server includes means for acquiring an individual's characteristics and analyzing the individual's head from those characteristics, means for inputting the individual's desired appearance changes based on their choices, and means for generating images corresponding to the head information and the desired changes for proposing multiple appearance change options. This allows the user to visually confirm the result before changing their appearance, evaluate health risks in advance, and safely change their appearance. Furthermore, by sharing the obtained information with external experts, they can receive more accurate advice.

[0644] "Personal characteristics" refer to specific attributes and data related to an individual's appearance, including facial and head shape, hairline, and skin tone.

[0645] "Methods for analyzing the head" refer to methods that use image processing and artificial intelligence technology to identify individual head features from captured images and extract specific information.

[0646] "Requests for changes to appearance" refer to the user's preferences and requests regarding changes to their appearance, such as hairstyle or makeup.

[0647] The "image generation method" is a technology that creates a virtual finished image using a generation AI model based on the user's head characteristics and desired style information.

[0648] "Health status information" refers to medical information related to maintaining health, such as an individual's allergies and medical history.

[0649] "Risk information" refers to an assessment of the safety of products and methods used for cosmetic modifications, and includes explanations and warnings about events that may affect the user's health.

[0650] "External experts" refer to professionals with advanced knowledge and skills in related fields such as beauty and medicine.

[0651] This invention is a system aimed at visually confirming desired appearance changes and pre-assessing health risks. Specifically, it is implemented in the following way.

[0652] The user takes an image of their face or head using the camera on a device such as a smartphone or tablet. The captured image data is temporarily stored by the device and then prepared to be sent to the server. At the same time, the user selects a desired style from several appearance modification options provided on the device and sends that information to the server as well.

[0653] Upon receiving a series of pieces of information, the server analyzes the user's head features using an image processing algorithm. This analysis employs a generative AI model, incorporating the results of learning from past data and trends. Based on the received head features and the user's desired appearance changes, the server generates an optimal finished image for the user. This generated image is sent to the user's device, where the user can review it.

[0654] Furthermore, users can input allergy information and health status data through their devices. This data is stored on a server and used to determine whether appearance modification options pose health risks. If necessary, this risk information is also provided to external experts to enhance safety.

[0655] For example, if a user requests a short bob hairstyle, the server will generate an image suitable for this style based on the user's head features. If allergy information to specific medications is registered, the server will also take that information into consideration to determine if the new style can be safely implemented.

[0656] An example of a prompt to input into the generating AI model is, "Based on the user's current facial image and their desired short bob hairstyle, generate the optimal finished image and calculate risk information." This prompt allows the system to provide highly accurate predictive images.

[0657] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0658] Step 1:

[0659] The user takes an image of their face or head using the camera on a device such as a smartphone. The captured image data is temporarily stored on the device. Specifically, the user launches the camera app and captures the image. The input at this stage is the user's face image, and the output is the saved image file.

[0660] Step 2:

[0661] The user reviews the appearance customization options provided on the device and selects their desired style. This information is then entered into the application on the device. Specifically, the user scrolls through different style options on the app screen and taps the style they like. The input at this stage is the appearance customization option, and the output is the style data selected by the user.

[0662] Step 3:

[0663] The terminal performs preprocessing to send the captured image data and selected style information to the server. Specifically, it converts this data into an appropriate format and then encrypts it for security. The input at this stage is the image data and style data, and the output is the encrypted data ready for transmission.

[0664] Step 4:

[0665] The server analyzes the received image data and style information. It extracts the user's head features from the image data and generates an image based on the style information. Specifically, it uses an image processing algorithm and a generative AI model to analyze head feature data and generate a visual image that best suits the desired style. The input at this stage is encrypted image data and style information, and the output is the generated finished image.

[0666] Step 5:

[0667] The server sends the generated image to the user's terminal, and the user views the image on the terminal. Specifically, the server receives response data from the server and displays the image through the application. At this stage, the input is the generated image data, and the output is the displayed visual image.

[0668] Step 6:

[0669] Users input allergy information and health status data through their devices and send this data to the server. Specifically, this involves filling in the required data in a health information input form and tapping the submit button. The input at this stage is health information, and the output is health data recorded on the server.

[0670] Step 7:

[0671] The server evaluates the potential risks associated with the selected appearance modification option based on the received health information. If risk information is identified, the user is notified. Specifically, the server performs a database search and makes an automatic determination based on registered health concerns. The inputs at this stage are the user's health data and appearance modification options, and the output is the risk assessment result.

[0672] (Application Example 1)

[0673] 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".

[0674] When individuals change their appearance, it is difficult to accurately predict how their desired style will look beforehand, and there is a need for appropriate means to manage the health risks involved in the process. Furthermore, there is a lack of systems that can facilitate individual style selection within the home and provide appropriate advice.

[0675] 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.

[0676] In this invention, the server includes means for acquiring an individual's image data and analyzing the individual's head features from the image data; means for inputting data on desired appearance changes based on the individual's choices; and means for generating images corresponding to the head features and the desired changes, for proposing a plurality of appearance change option data. This allows users to visually confirm the desired appearance changes in advance, and also enables the suggestion of lifestyle products that take health information into consideration.

[0677] "Image data" refers to visual information obtained in digital format from an individual's appearance and used for analysis.

[0678] "Head features" refer to characteristics related to the shape and pattern of an individual's face and head, and are elements used to predict changes in appearance.

[0679] "Requested change data" refers to information describing the appearance changes that an individual desires, and is based on style selection.

[0680] "Image generation means" refers to a technical means for visually presenting multiple appearance modification options based on analyzed data.

[0681] A "display device" is hardware used to visually present the generated appearance change results to the user.

[0682] "Health status information" refers to data about an individual's physical health, and is information that is considered in order to implement safe appearance alterations.

[0683] "Daily necessities" are items related to an individual's daily life, and are intended to support appropriate choices based on health information.

[0684] The system implementing this invention supports personal appearance modification, allowing users to send their appearance data to a server using a smartphone or home appliance. The server analyzes the individual's head features from the received image data and generates multiple appearance modification options using a generative AI model based on the user's selected desired appearance modification data. This allows users to visually confirm the changes beforehand.

[0685] Furthermore, the server considers the user's health data, analyzes the health risks associated with appearance changes, and provides this information to the user. This makes it possible to address health concerns related to appearance changes in advance. As a display device, a smartphone or robot display is used to visually show the user images of the generated style and information on health risks.

[0686] As a concrete example, there is a process where the user selects their desired hairstyle, and the server generates a style image based on that. The user can then choose an appearance that suits them based on this generated image, and at the same time, appropriate lifestyle products are suggested based on allergy test results.

[0687] By using a generative AI model, it becomes possible to provide users with the latest fashion trends and personalized style suggestions. An example of a prompt to input into the generative AI model is, "Generate a hairstyle as an image that reflects the user's desired appearance change, and display a suggestion that also takes health risks into consideration." This system makes it easy to implement personalized appearance changes tailored to individual needs.

[0688] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0689] Step 1:

[0690] The user takes an image of their face or head using a mobile device. The input data is image data, which the device temporarily stores and prepares for transmission to the server.

[0691] Step 2:

[0692] The terminal sends the desired appearance change data selected by the user to the server. At this point, the server receives both the image data and the desired change data. The input is the image data and the desired change data, and the output is this data stored on the server.

[0693] Step 3:

[0694] The server uses a generative AI model to begin analyzing the received image data. Head features are extracted at this stage. The input is image data, and the output is the analyzed head feature data. Data processing involves the extraction of specific features using image analysis algorithms.

[0695] Step 4:

[0696] The server generates multiple appearance modification options based on the analyzed head feature data and the user's selected style preference data. A generation AI model is used to generate style images. The input for this step is head feature data and appearance modification preference data, and the output is multiple appearance images.

[0697] Step 5:

[0698] The results are sent to the terminal, and the user confirms the generated style image through the display device. The input is the set of generated appearance images, and the output is the user's visual confirmation result.

[0699] Step 6:

[0700] Considering the user's health status data, the server analyzes health risks associated with the generation style. This includes allergy data. The input is health status data, and the output is the risk analysis results. Data calculations are performed to verify the safety of available products and modifications based on the generated image.

[0701] Step 7:

[0702] Finally, based on the information from the server, the user can select the optimal lifestyle products that minimize health risks. The input is the risk analysis results, and the output is a list of recommended products. The user then takes specific actions to make the best choice based on the information.

[0703] 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.

[0704] This invention relates to a system that recognizes a user's emotions and takes them into consideration when suggesting appearance changes to better suit the user's preferences. This system combines emotion data with information about the user's desired appearance changes to provide more personalized suggestions.

[0705] First, the user takes a picture of the requested image data using the camera function of their smartphone and temporarily saves it on the device. Next, the user enters information about the desired appearance changes into the application, and this data is also saved on the device. After this, the emotion engine infers and records the user's current emotional state from information such as their face, voice, and selected appearance.

[0706] The device sends image data, desired appearance change data, and emotion data to the server. The server receives this data, analyzes the image data to identify head features, and uses emotion data obtained from the emotion engine to adjust appearance change suggestions to suit the user's current emotional state. This process allows the generative AI model to optimize the predicted images of appearance change options.

[0707] The appearance change images generated from the server, along with the adjusted suggestions, are sent to the terminal and presented to the user. The user reviews these results and makes a decision on whether to adopt them. Furthermore, emotional data is shared with external professional experts, allowing for the provision of emotionally-driven professional advice.

[0708] As a concrete example, consider a user who is thinking about cutting their hair short but feels anxious. In this case, the emotion engine detects the user's anxiety and accordingly suggests a gradual style change that is not too drastic, presenting a style that provides reassurance. In this way, by utilizing emotion recognition, it is possible to implement appearance changes that are more personalized and result in higher user satisfaction.

[0709] The following describes the processing flow.

[0710] Step 1:

[0711] The user takes an image of their face or head using the camera on their smartphone. The device temporarily stores this image data in its memory.

[0712] Step 2:

[0713] The user enters their desired appearance changes on their device. For example, they can select a hairstyle or enter specific styling preferences and save them on their device.

[0714] Step 3:

[0715] The device analyzes the user's emotional state using an emotion engine based on their facial expressions and voice. The resulting emotional data is then stored on the device.

[0716] Step 4:

[0717] The device encrypts image data, appearance change request data, and emotion data and sends them to the server.

[0718] Step 5:

[0719] The server analyzes the received image data to identify the user's head features. Based on the analysis results, and taking into account emotional data and desired appearance changes, a generative AI model creates an image of the altered appearance.

[0720] Step 6:

[0721] The server generates a predicted appearance image and sends sentiment-based, optimized suggestions to the device. The data is encrypted and transmitted securely.

[0722] Step 7:

[0723] The device displays the received images and suggestions in the user interface. The user reviews the displayed information and decides whether it matches their preferences and feelings.

[0724] Step 8:

[0725] If there are changes based on the user's emotional state or preferences, feedback is sent from the device to the server. Furthermore, emotional data can be shared with external professional experts for advice as needed.

[0726] (Example 2)

[0727] 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".

[0728] In modern times, personal appearance customization is a significant concern for many people. However, conventional systems have struggled to provide flexible suggestions tailored to individual emotional states and specific needs. As a result, the accuracy and satisfaction of appearance customization often suffer from a decline in user expectations.

[0729] 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.

[0730] In this invention, the server includes means for acquiring personal image data and analyzing the personal head features from the image data; means for acquiring emotional data and adjusting appearance change suggestions based on the emotional data; and means for optimizing appearance change options using a generative AI model. This enables more personalized appearance change suggestions that are tailored to the user's emotional state and preferences.

[0731] "Personal image data" refers to digital data that represents visual information, including the user's physical characteristics.

[0732] "Means for analyzing head features" refers to a device or program that has the function of identifying and evaluating the shape of an individual's head and specific features from acquired personal image data.

[0733] "Desired appearance change data" refers to data that records information about the desired appearance state or changes that the user wants to achieve.

[0734] "Means for acquiring emotional data" refers to a device or software that analyzes the user's facial expressions and voice characteristics to generate data indicating their current emotional state.

[0735] "Means for optimizing appearance modification options" refers to a device or program that utilizes a generative AI model to calculate and present the most appropriate appearance modification options based on the user's preferences and emotional state.

[0736] "Data transmission means" refers to communication means for securely transmitting acquired and generated data to another device or user.

[0737] The following describes embodiments for carrying out the present invention.

[0738] This invention is a system for suggesting appearance changes that takes into account the user's emotional state. The user acquires image data of themselves using the camera function of their smartphone and inputs data on desired appearance changes into a dedicated application. This data is temporarily stored on the device.

[0739] The device uses a built-in emotion engine to acquire emotional data from the user's face and voice. The emotion engine utilizes image processing and voice analysis technologies to infer emotions from the user's facial expressions and tone of voice.

[0740] The device securely transmits acquired image data, desired appearance changes, and sentiment data to the server. The server uses a dedicated image analysis algorithm to identify the user's head features from the image data and uses a generative AI model based on the sentiment data to refine the appearance change suggestions. This model generates the optimal appearance change option by comparing it with existing data.

[0741] For example, when a user requests a change in hairstyle, if the emotion engine detects anxiety, the server can suggest a style that provides reassurance by proposing gradual changes. This suggestion is sent to the user's device, where the user reviews the results and decides whether to accept them.

[0742] An example of a prompt message is: "Generate a predictive image that suggests appearance modification options tailored to the user's preferences, based on their current emotions."

[0743] This system aims to increase user satisfaction by generating personalized suggestions that take emotional data into consideration.

[0744] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0745] Step 1:

[0746] The user takes a picture of themselves using the camera function of their smartphone to obtain data on the parts of their appearance they wish to change. Subsequently, they input data on their desired appearance changes (e.g., wanting to shorten their hair) through a dedicated application. This data is temporarily stored on the device. Image data and desired data in text format are obtained as input data and used in the next processing step.

[0747] Step 2:

[0748] The device uses a built-in emotion engine to analyze the user's facial expressions and voice, and acquire emotional data. The emotion engine uses image analysis technology to extract facial features from image data and voice analysis technology to analyze voice tone, thereby inferring the emotional state. The input data consists of captured images and audio data, and the output data represents the user's emotional state.

[0749] Step 3:

[0750] The device sends image data acquired in Step 1, desired appearance change data, and emotion data acquired in Step 2 to the server. This transmission is performed using a secure communication protocol. The input data includes encrypted data to protect user privacy.

[0751] Step 4:

[0752] The server identifies the user's head features from image data using an image analysis algorithm. Next, it uses a generative AI model based on emotion data to refine suggestions for appearance changes appropriate to the user's emotional state. This creates a predicted image of the appearance change. The input data consists of user data and emotion data requiring image analysis, and the output consists of the generated predicted image and suggested data of the appearance change.

[0753] Step 5:

[0754] The server generates a predicted image of the appearance change and sends the adjusted suggestion to the terminal for the user to view. The user reviews this and determines whether the suggestion matches their preferences. A feedback function allows the user to send their thoughts on the suggestion back to the server. The output data is the appearance change suggestion that the user views on the screen.

[0755] Step 6:

[0756] If necessary, the server shares sentiment data and appearance change results with external experts. This sharing allows users to receive expert advice based on their emotions. Input data includes the shared sentiment data and appearance change results, while output includes feedback and additional suggestions from experts.

[0757] (Application Example 2)

[0758] 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".

[0759] When individuals request changes to their device's appearance, they typically only receive fixed style suggestions, lacking personalized options that take into account the user's emotional state. Furthermore, there is a need for a system that easily incorporates professional opinions. This presents a challenge in reducing user anxiety and dissatisfaction, and enabling appearance changes that better suit their needs.

[0760] 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.

[0761] In this invention, the server includes means for acquiring personal image data and analyzing features from said data; means for analyzing the personal emotional state and adjusting appearance modification options based on that emotion; and means for sharing the adjusted appearance modification suggestions with an external organization and obtaining expert advice. This enables personalized appearance modifications that respond to the user's emotional state, thereby improving user satisfaction.

[0762] "Personal image data" refers to visual data used to obtain information about a user's appearance.

[0763] "Means of feature analysis" refers to methods for analyzing the visual elements obtained from image data and numerically evaluating their structure and characteristics.

[0764] "Desired appearance change data" refers to information about the appearance changes that the user wishes to make.

[0765] "Data generation means" refers to a processing method that generates newly proposed appearance information based on analyzed features and desired changes.

[0766] "Means of presentation on a display device" refers to a method relating to an apparatus or system for visually showing the results of the generated changes in appearance.

[0767] "Methods for analyzing emotional state" refer to methods for processing information obtained from a user's facial expressions and voice to infer their current emotional state.

[0768] "Means of sharing data with external organizations" refers to methods of sharing generated data with other professional organizations or individuals to obtain further feedback and advice.

[0769] The system for implementing this invention mainly consists of a user's device (such as a smartphone) and a server connected via a network. First, the user uses the smartphone's camera function to acquire image data and temporarily stores that data. Next, the user enters their desired appearance changes into the application, and this data is also stored on the device.

[0770] The server analyzes image data transmitted from the user's terminal to identify individual characteristics. Image processing libraries such as OpenCV are used for the analysis. Additionally, a TensorFlow-based emotion engine is employed to perform emotion analysis based on the user's voice and facial expressions. The results of the emotion analysis are useful in inferring the user's current emotional state.

[0771] Based on this emotional state, the server adjusts the appearance change options and creates an optimized predictive image using a generative AI model. The adjusted appearance suggestions are sent to the user's terminal via a user interface such as Flask. The user reviews the presented options and decides whether to adopt the appearance change.

[0772] For example, if a user wants to relax on Sunday, the system will detect the user's calm mood and suggest a casual loungewear style in soft colors. To support this process, the generating AI model is input with the following prompt: "If the user wants to have a relaxing Sunday, please suggest the most appropriate casual clothing style."

[0773] This allows for the provision of appearance modification suggestions that better match the user's emotions and desires, resulting in increased user satisfaction.

[0774] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0775] Step 1:

[0776] The user uses their smartphone's camera to acquire image data of themselves and temporarily saves it to the device. In this process, the input is the user's face image, and the output is the image data saved to the device's local storage.

[0777] Step 2:

[0778] The user enters data requesting changes to the application's appearance. This data includes specific style and color preferences. The input represents the user's desired appearance information, while the output is the requested change data stored on the device.

[0779] Step 3:

[0780] The terminal sends image data and data requesting changes to the server. The input is the terminal's image data and change request data, and the output is user data securely transferred to the server.

[0781] Step 4:

[0782] The server analyzes the received image data using OpenCV to identify the user's features. The input for this step is image data, and the output generates numerical data about the structure and features of the face.

[0783] Step 5:

[0784] The server uses TensorFlow to analyze the user's emotional state. Facial expressions and audio data are input, and inferred data indicating the emotional state is output.

[0785] Step 6:

[0786] The server uses a generative AI model to adjust appearance change suggestions based on emotional states and user preferences. The input is analyzed emotional and preference data, and the server outputs adjusted appearance change options.

[0787] Step 7:

[0788] The server sends the adjusted appearance change suggestions to the user's terminal via Flask. The input here is the server-side appearance change options, and the output is the style suggestions displayed on the user's terminal.

[0789] Step 8:

[0790] The user reviews the received suggestions and decides whether to adopt the appearance changes. The input in this step is the appearance suggestions, and the user's selection is saved as the output.

[0791] Step 9:

[0792] If necessary, the server requests the generated AI model using specific prompt statements and shares data with external organizations. In this step, prompt statements are used as input, and external feedback and advice are output.

[0793] 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.

[0794] 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.

[0795] 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 robot 414.

[0796] 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.

[0797] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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."

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] The following is further disclosed regarding the embodiments described above.

[0815] (Claim 1)

[0816] A means for acquiring personal image data and analyzing the personal head features from said image data,

[0817] A means of inputting data on desired appearance changes based on individual choices,

[0818] A means for generating images corresponding to the head features and the desired changes, for proposing multiple appearance modification option data,

[0819] A means for displaying the resulting changes in appearance on a display device,

[0820] A system that includes this.

[0821] (Claim 2)

[0822] The system according to claim 1, further comprising data transmission means for sharing generated appearance modification results with external professional experts.

[0823] (Claim 3)

[0824] The system according to claim 1, comprising means for inputting and storing individual health status data, and means for providing risk avoidance information based on the health status data to an external device.

[0825] "Example 1"

[0826] (Claim 1)

[0827] A means for acquiring an individual's characteristics and analyzing the individual's head from those characteristics,

[0828] A means of entering requests for appearance changes based on individual choices,

[0829] A means for proposing multiple appearance modification options, comprising the head information and the image generation means according to the desired outcome,

[0830] A means for presenting the generated appearance change results using a presentation device,

[0831] A means for performing processing to send the generated image to the user terminal,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, further comprising means for transmitting information to share the generated appearance modification results with external experts.

[0835] (Claim 3)

[0836] The system according to claim 1, comprising means for inputting and storing individual health status information, and means for providing risk information based on said health status information to an external device.

[0837] "Application Example 1"

[0838] (Claim 1)

[0839] A means for acquiring personal image data and analyzing the personal head features from said image data,

[0840] A means of inputting data on desired appearance changes based on individual choices,

[0841] A means for generating images corresponding to the head features and the desired changes, for proposing multiple appearance modification option data,

[0842] A means of presenting the results of the generated appearance changes using a machine equipped with a display device,

[0843] Based on the generated appearance modification results, a means to support the selection of daily necessities while taking health status information into consideration,

[0844] A system that includes this.

[0845] (Claim 2)

[0846] The system according to claim 1, further comprising data transmission means for sharing generated appearance change results and health status information with external professional experts.

[0847] (Claim 3)

[0848] The system according to claim 1, comprising means for inputting and storing individual health status data, and means for providing risk avoidance information based on the health status data to an external device or display device.

[0849] "Example 2 of combining an emotion engine"

[0850] (Claim 1)

[0851] A means for acquiring personal image data and analyzing the personal head features from said image data,

[0852] A means of inputting data on desired appearance changes based on individual choices,

[0853] A means for generating images corresponding to the head features and the desired changes, for proposing multiple appearance modification option data,

[0854] A means for displaying the resulting changes in appearance on a display device,

[0855] A means for acquiring emotional data and adjusting suggestions for appearance changes based on said emotional data,

[0856] A means for optimizing appearance modification options using a generative AI model,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, further comprising data transmission means for sharing generated appearance modification results with external professional experts.

[0860] (Claim 3)

[0861] The system according to claim 1, comprising means for inputting and storing individual health status data, and means for providing risk avoidance information based on the health status data to an external device.

[0862] "Application example 2 when combining with an emotional engine"

[0863] (Claim 1)

[0864] A means for acquiring personal image data and analyzing personal characteristics from said image data,

[0865] A means of inputting data on desired appearance changes based on individual choices,

[0866] A data generation means for proposing multiple appearance change option data according to the features and the desired changes,

[0867] A means for displaying the resulting changes in appearance on a display device,

[0868] A means of analyzing an individual's emotional state and adjusting appearance modification options based on that emotional state,

[0869] A means for presenting the aforementioned adjusted exterior modification proposal,

[0870] To obtain expert advice tailored to individual emotions, a means of sharing data with external organizations,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, comprising data transmission means for sharing generated appearance change results with external professional experts and receiving advice tailored to the individual's emotional state.

[0874] (Claim 3)

[0875] The system according to claim 1, comprising means for inputting and storing individual state data, and means for providing information based on the state data to an external device. [Explanation of symbols]

[0876] 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 for acquiring personal image data and analyzing the personal head features from said image data, A means of inputting data on desired appearance changes based on individual choices, A means for generating images corresponding to the head features and the desired changes, for proposing multiple appearance modification option data, A means of presenting the results of the generated appearance changes using a machine equipped with a display device, Based on the generated appearance modification results, a means to support the selection of daily necessities while taking health status information into consideration, A system that includes this.

2. The system according to claim 1, further comprising data transmission means for sharing generated appearance change results and health status information with external professional experts.

3. The system according to claim 1, comprising means for inputting and storing individual health status data, and means for providing risk avoidance information based on the health status data to an external device or display device.

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