system

Abstract

Provide a system. A means for a user to input ideas; means for receiving the ideas and transmitting them to a server; A means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting confirmation and correction instructions from the user; means for regenerating the virtual content based on the modification instructions; a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; A system including:

Description

[Technical Field]

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

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

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

[0004] Conventional VR / AR content creation requires specialized knowledge and skills, making it difficult for ordinary users without advanced technology. Furthermore, the content creation process is time-consuming and requires a lot of effort for setup and adjustment, placing a heavy burden on creators. This situation makes it difficult to quickly realize new ideas and share virtual experiences. Therefore, there is a need for a system that allows users to easily generate VR / AR content and project it into reality. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means: a system including: means for a user to input an idea; means for receiving the idea and transmitting it to a server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; and means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality. This provides an environment in which users can easily embody their ideas and quickly project them into reality without having specialized knowledge or skills.

[0006] "User" refers to the entity that uses this system to input ideas and generate, check, modify, and project VR / AR content.

[0007] "Ideas" refer to the specific content and requests for VR / AR content that users want to realize.

[0008] "Server" refers to a remotely located computing system that receives data submitted by users and generates and modifies content using generative AI models.

[0009] "Terminal" refers to a device that is directly operated by a user, a tool that provides the means to send input ideas to a server, receive generated content, display it to the user, and ultimately project it into reality.

[0010] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates VR / AR content based on user ideas.

[0011] "Parameters" refer to the various settings and conditions required by a generative AI model when generating VR / AR content.

[0012] "Virtual content" refers to 3D models and AR objects automatically generated by generative AI models.

[0013] "Confirmation and correction instructions" refers to the act of the user checking the generated virtual content and instructing on necessary changes and improvements.

[0014] "Projection" refers to the act of displaying the final confirmed virtual content in real space. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

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

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] To specifically implement this invention, it is necessary to build a system in which a user, a terminal, and a server work together. In this system, a user inputs an idea, a server analyzes the idea, and generates VR / AR content using a generative AI model, which is then provided to the user through the terminal. Specific embodiments are described below.

[0037] User idea input

[0038] Users can use a dedicated application or web interface to input their ideas for the VR / AR content they want to create in text format. For example, a user can enter a specific request such as "I want to add a red sofa to my living room."

[0039] Submit an idea

[0040] The terminal receives the idea data entered by the user and transmits it to the server. At this time, basic information about the user (such as the user ID and location information) may also be attached along with the content of the idea.

[0041] Idea analysis and parameter extraction

[0042] The server analyzes the received idea data and extracts the necessary parameters to input into the generative AI model. For example, from the idea "I want to add a red sofa to my living room," the server identifies the keyword "red sofa" and determines the specific parameters of the sofa, such as its size, shape, and color.

[0043] Virtual Content Generation

[0044] The server generates virtual content using a generative AI model based on the extracted parameters. In this case, a 3D model of a "red sofa" is generated and temporarily stored on the server.

[0045] Sending content to user devices

[0046] The generated virtual content is sent from the server to the user's device, which provides a user interface for displaying the received 3D model, allowing the user to confirm the content.

[0047] User confirmation and correction

[0048] The device displays the generated 3D model or AR object, and the user can check its contents. If the user is dissatisfied with the generated content or if corrections are required, the user can input correction instructions through the device. For example, "I would like the color of the sofa to be a little darker."

[0049] Sending modifications to the server

[0050] The device retransmits the user's correction instructions to the server, which then reuses the generative AI model based on the correction instructions and regenerates the content.

[0051] Final confirmation and projection into reality

[0052] The revised virtual content is then sent back to the device from the server for final confirmation by the user. If the user is satisfied, the device projects the virtual content into real space using an AR headset or smartphone. For example, a life-size red sofa is virtually displayed in the user's living room.

[0053] Specific examples

[0054] Example 1: Adding furniture

[0055] A user types, "I want to add a red sofa to my living room," and the device sends this idea to the server. The server analyzes the idea and generates a 3D model of the "red sofa." The generated model is sent to the device, where the user can review it. If the user is satisfied, the device projects the sofa in life-size onto the living room.

[0056] Example 2: Adding a character

[0057] The user types, "I want to add a barista character to the cafe scene," and the device sends the idea to the server. The server analyzes the idea and generates a 3D model of the "barista character." The model is then sent to the device, where the user can review, edit, and finalize the model, after which the barista character is projected onto the cafe scene.

[0058] In this way, the present invention allows users to easily generate VR / AR content and project it into real space, accelerating creative projects and making it easier for general users to share virtual experiences.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] User: Accesses a dedicated application or web interface and enters in text format the idea for the VR / AR content they want to realize. For example, they might enter a request such as, "I want to add a red sofa to my living room."

[0062] Step 2:

[0063] Terminal: Receives idea data entered by the user. The received data includes details of the idea and basic information of the user (ID, location information, etc.).

[0064] Step 3:

[0065] The terminal transmits the received idea data to the server. The transmitted data includes the content of the idea entered by the user and any accompanying information.

[0066] Step 4:

[0067] Server: Receives idea data sent from the terminal, checks the received data, and performs appropriate processing.

[0068] Step 5:

[0069] Server: Analyzes the received ideas. Extracts parameters to be input into the generative AI model and creates specific generation instructions. For example, for the idea of ​​a "red sofa," it identifies parameters such as color (red), size, shape, and material.

[0070] Step 6:

[0071] Server: Using the extracted parameters, a generative AI model is used to generate virtual content. Specifically, a 3D model of a "red sofa" is automatically created.

[0072] Step 7:

[0073] Server: The server sends the generated virtual content (3D model) to the device. The sent data includes the 3D model file and related metadata.

[0074] Step 8:

[0075] Terminal: Receives the 3D model data sent from the server and displays it to the user, allowing the user to check the generated content through a user interface.

[0076] Step 9:

[0077] User: Checks the generated 3D model and inputs corrections as necessary. For example, the user may request that the color of the sofa be made a little darker.

[0078] Step 10:

[0079] Terminal: Receives the user's correction instructions and sends them back to the server. The transmitted data includes details of the corrections.

[0080] Step 11:

[0081] Server: Receives correction instructions sent from the device and analyzes them again. Adjusts necessary parameters and regenerates the content using the generative AI model.

[0082] Step 12:

[0083] Server: Retransmits the modified virtual content to the device, including data for final confirmation.

[0084] Step 13:

[0085] Terminal: The modified virtual content is displayed to the user, who then performs a final check and approves it if satisfied.

[0086] Step 14:

[0087] Device: The content that the user has finally approved is projected into the real world using an AR headset or smartphone. A life-size red sofa is virtually displayed in the living room.

[0088] Example 1

[0089] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0090] In conventional VR / AR content generation systems, even if a user inputs a specific idea, it is difficult to generate virtual content that accurately reflects that idea. Furthermore, there is a lack of effective means for modifying and finalizing the generated virtual content, making it difficult to easily create content that satisfies the user. The present invention solves these problems by providing a system that generates highly accurate VR / AR content based on an idea input by a user, and that allows modification and finalization to be performed quickly and easily.

[0091] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0092] In this invention, the server includes: a means for a user to input an idea; a means for receiving the idea and transmitting it to the server; a means for analyzing the idea and extracting parameters to be input into a generative AI model; a means for generating virtual content based on the parameters; a means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; a means for regenerating the virtual content based on the correction instructions; a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; a means for generating the virtual content using 3D modeling software; and a means for projecting the final confirmed virtual content into real space using an AR headset or a smartphone. This enables quick and easy generation, modification, and final confirmation of virtual content that accurately reflects the idea input by the user.

[0093] "User" refers to a person who uses the system to input ideas and review and modify generated content.

[0094] "Ideas" refer to specific requests and creative ideas about the VR / AR content that users want to realize.

[0095] "Server" refers to the computer system utilized to analyze user-submitted ideas and generate, modify, and retransmit virtual content.

[0096] "Generative AI model" refers to an artificial intelligence model used to extract and generate appropriate parameters based on a user's ideas and create virtual content.

[0097] "Virtual Content" refers to 3D models and other virtual objects generated by a generative AI model based on a user's ideas.

[0098] "Parameters" refer to various settings and attributes (e.g., color, shape, size, etc.) required to materialize a user's idea.

[0099] "3D Modeling Software" means software tools used to generate 3D models of Virtual Content.

[0100] "User terminal" refers to an electronic device (e.g., smartphone, tablet, PC) used by a user to input ideas and review and modify generated virtual content.

[0101] "Modification instructions" refer to requests for changes or improvements made by a user to the generated virtual content.

[0102] "Projecting into reality" refers to virtually displaying the generated virtual content in real space using an AR headset or smartphone.

[0103] To specifically implement the present invention, it is necessary to build a system in which a user, a terminal, and a server work together. In this system, a user inputs an idea, a server analyzes the idea, and generates virtual content using a generative AI model, which is then provided to the user via the terminal. Specific embodiments are described below.

[0104] User idea input

[0105] Using a dedicated application or web interface, users can enter textual ideas about the virtual content they want to create. For example, a user might enter a specific request, such as "I want to add a red sofa to my living room."

[0106] Sending and receiving ideas

[0107] The terminal receives the idea data entered by the user and transmits it to the server. At this time, basic information about the user (such as the user ID and location information) may also be attached along with the content of the idea.

[0108] Idea analysis and parameter extraction

[0109] The server analyzes the received idea data and extracts the necessary parameters to input into a generative AI model (for example, a general natural language processing AI model). Specifically, from the idea "I want to add a red sofa to my living room," the server identifies the keyword "red sofa" and determines the sofa's specific parameters, such as its size, shape, and color.

[0110] Virtual Content Generation

[0111] The server generates virtual content using a generative AI model based on the extracted parameters. For example, it generates a 3D model of a "red sofa" using 3D modeling software such as Blender or Maya. This 3D model is temporarily stored on the server.

[0112] Sending content to user devices

[0113] The generated virtual content is sent from the server to the user's device, which provides a user interface for displaying the received 3D model, allowing the user to view the model.

[0114] User confirmation and correction

[0115] The user can check the generated 3D model on their device. If they are dissatisfied with the generated content or if corrections are needed, they can input correction instructions through their device. For example, they can input specific correction instructions such as "I would like the color of the sofa to be a little darker."

[0116] Sending modifications to the server and regenerating

[0117] The device retransmits the user's correction instructions to the server, which then reuses the generative AI model based on the correction instructions and regenerates the virtual content.

[0118] Final confirmation and projection into reality

[0119] The revised virtual content is then sent back to the device from the server for final confirmation by the user. If the user is satisfied, the device projects the virtual content into real space using an AR headset or smartphone. For example, a life-size red sofa is virtually displayed in the user's living room.

[0120] Specific examples

[0121] Example 1: Adding furniture

[0122] The user types, "I want to add a red sofa to my living room," and the device sends this to the server. The server analyzes the idea, extracts the necessary parameters, and generates a 3D model of the "red sofa." The generated model is sent to the device, where the user can check it. If the user is satisfied, the device projects the sofa in life-size onto the living room.

[0123] Example 2: Adding a character

[0124] The user inputs "I want to add a barista character to the cafe scene," and the device sends this to the server. The server analyzes the data and generates a 3D model of the "barista character." The model is sent to the device, where the user can review, edit, and finalize the model, after which the barista character is projected onto the cafe scene.

[0125] Examples of prompt statements

[0126] Adding Furniture

[0127] "I would like to add a red sofa to my living room. The sofa should be 200cm wide, 90cm high, and 100cm deep. I would like it to be a dark red."

[0128] Adding characters

[0129] "I want to add a barista character to the cafe scene. The barista's outfit is a young man wearing an apron and a friendly smile."

[0130] Based on these prompts, the generative AI model can generate the desired VR / AR content, allowing users to easily generate VR / AR content and project it into the real world.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Step 1:

[0133] Users input their ideas using a dedicated application or web interface. They enter their ideas in text format in an input field, describing specific requests such as "I want to add a red sofa to my living room." The input data is the text information entered by the user. The output data is temporarily stored on the device.

[0134] Step 2:

[0135] The device sends the ideas entered by the user to the server. Specifically, it uses the REST API to send idea data to the server. At this time, basic information such as the user ID and timestamp is also sent. The input data consists of temporarily saved text information and basic information. This data is sent to the server as output.

[0136] Step 3:

[0137] The server analyzes the received ideas and extracts parameters to feed into the generative AI model. It uses a natural language processing API to analyze the text and identify important keywords such as "red sofa" and "living room." The input data is the text information sent. The output is the extracted parameters.

[0138] Step 4:

[0139] The server generates virtual content using a generative AI model based on the extracted parameters. Specifically, it generates a 3D model of a "red sofa" using 3D modeling software (e.g., Blender or Maya). The input data is the extracted parameters, such as "red sofa." The output is a 3D model based on these parameters.

[0140] Step 5:

[0141] The server sends the generated virtual content to the user's device. The generated 3D model file (e.g., .fbx format) is sent to the device via a REST API. The input data is the generated 3D model. The output is the model sent to the device.

[0142] Step 6:

[0143] The device provides a user interface to display the received 3D model, allowing the user to check the content. The input data is the transmitted 3D model. The output is the user's view of the 3D model through the interface.

[0144] Step 7:

[0145] The user checks the 3D model generated on the device, and if there are any complaints or corrections that need to be made, they can input correction instructions through the device. For example, they can write down specific requests for corrections, such as "I would like the color of the sofa to be a little darker." The input data is the correction instructions written by the user. As output, these instructions are temporarily saved on the device.

[0146] Step 8:

[0147] The device resubmits the user's correction instructions to the server. It again uses the REST API to send the correction instruction data to the server. The input data is the temporarily saved correction instructions. The output is this instruction sent to the server.

[0148] Step 9:

[0149] The server reuses the generative AI model based on the modification instructions to recreate the virtual content. It regenerates the 3D model based on new parameters (e.g., color changes). The input data are the parameters based on the modification instructions. The output is the modified 3D model.

[0150] Step 10:

[0151] The server resends the modified virtual content to the user's device. It sends the regenerated 3D model file to the device. The input data is the modified 3D model. The output data is sent to the device.

[0152] Step 11:

[0153] The user then checks the revised 3D model on the device again. If the user is satisfied, they can use the device to project the virtual content into real space via an AR headset or smartphone. The input data is the revised 3D model that was sent. The output is the virtual projection of this model into real space.

[0154] (Application example 1)

[0155] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0156] In conventional virtual object viewing systems, when users want to customize an object, they lack a mechanism to directly reflect their wishes, which reduces user satisfaction. In particular, the inability to easily customize the color, shape, and placement of an object limits the user experience.

[0157] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0158] In this invention, the server includes: means for a user to input an idea; means for receiving the idea and transmitting it to the server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; means for providing a user interface for customizing specifications of an item in a virtual space; and means for exploring the virtual space in real time and reflecting changes to the item. This allows users to freely customize the specifications of items in the virtual space, and the changes are reflected in real time, enabling a more satisfying user experience.

[0159] The "means for the user to input ideas" refers to a device that includes an interface that allows the user to provide specific requests or ideas to the system as text or voice input.

[0160] The "means for receiving the idea and transmitting it to the server" is a device including a communication means for receiving idea data input by the user and transmitting it to the server side.

[0161] "Means for analyzing the idea and extracting parameters to be input into the generative AI model" refers to a device that includes a process for analyzing received idea data and extracting specific parameters required by the generative AI model.

[0162] The "means for generating virtual content based on the parameters" is a device that includes a process for running a generative AI model using the extracted parameters to generate the specified virtual content.

[0163] The "means for transmitting the generated virtual content to a user terminal and accepting user confirmation and modification instructions" refers to a device that includes a communication means and an interface for transmitting the generated virtual content to a user terminal and accepting user confirmation and modification instructions.

[0164] The "means for regenerating virtual content based on the modification instructions" is a device that includes a process and a generation AI model for regenerating virtual content based on modification instructions from a user.

[0165] The "means for retransmitting the modified virtual content to the user terminal and projecting the final confirmed virtual content into reality" refers to a device for retransmitting the modified virtual content to the user terminal and projecting the final confirmed virtual content into a real environment.

[0166] The "means for providing a user interface for customizing the specifications of an item in a virtual space" is a device that provides a user interface for customizing the color, shape, placement, etc. of an item in a virtual space.

[0167] The "means for searching the virtual space in real time and reflecting changes to the item" is a device for reflecting changes to the item made by the user in real time while searching the virtual space.

[0168] To implement this invention, it is necessary to build a system using a server, a user terminal, and a generative AI model. A specific embodiment of this system will be described below.

[0169] Hardware and software used

[0170] Head-mounted display (HMD): For example, using a device such as Oculus Quest 2.

[0171] User interface: Virtual keyboard and voice interface to enter requests in text format.

[0172] Generative AI model: For example, DALL-E from OpenAI (registered trademark) or Imagen from Google (registered trademark) DeepMind is used.

[0173] Server system: Idea analysis and content generation will be handled on a cloud server (AWS (registered trademark), Google Cloud, etc.).

[0174] System operation flow

[0175] First, the user wears a head-mounted display and freely explores the virtual store. If the user becomes interested in a particular item during the exploration and wants to customize its color, shape, or placement, they can input their idea via text or voice. For example, they could say, "I want the color of this sofa to be changed to blue."

[0176] The user's device receives the idea and sends it to the server, which analyzes the idea and extracts parameters (product type, color, shape, etc.) for the generative AI model. Next, the generative AI model (e.g., DALL-E or Imagen) generates a customized item and creates its 3D model data.

[0177] The generated 3D model data is sent to the user's HMD in real time, and the new object model is immediately reflected in the virtual space. The user can review the changes and, if necessary, input any corrections.

[0178] Specific examples

[0179] For example, a user finds a sofa in a virtual store and requests, "I want the color of this sofa changed to blue." The request is sent to the server, which analyzes it and generates a 3D model of a new sofa using a generative AI model. The generated sofa is then displayed in the virtual store in real time for the user to review. By issuing further corrections as necessary, the user can finally experience the ideal product.

[0180] Examples of prompt statements

[0181] "I want this sofa changed to blue."

[0182] Move this table to the window.

[0183] Make this bed a little bigger

[0184] This allows users to freely customize the specifications of items in virtual space, and the changes are reflected in real time, allowing for a more satisfying user experience.

[0185] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0186] Step 1:

[0187] The user wears a head-mounted display and explores the virtual store. The input is the user's motion information and viewpoint information, and based on this information, the user interface displays the environment in real time. The output is display data of the virtual store.

[0188] Step 2:

[0189] The user inputs customization requests for a particular item by text or voice. The input is the user's text or voice customization requests, which are communicated to the user interface. The output is the user's customization request data.

[0190] Step 3:

[0191] The terminal receives this customization request data and sends it to the server. The input is the customization request data entered by the user, which is sent to the server using a communication means. The output is the transfer of the customization request data to the server.

[0192] Step 4:

[0193] The server analyzes the received customization request data and extracts parameters to be input into the generative AI model. The input is the customization request data, which is analyzed using natural language processing technology. The output is specific parameters to be input into the generative AI model (e.g., "blue sofa").

[0194] Step 5:

[0195] The server uses the extracted parameters to activate a generative AI model and generate virtual content. The input is the parameters required by the generative AI model, and a 3D model is generated using the generative AI model (e.g., DALL-E or Imagen). The output is the generated 3D model data.

[0196] Step 6:

[0197] The server sends the generated 3D model data to the user's device. The input is the generated 3D model data, which is then sent back to the user's device via a communication means. The output is the transfer of the 3D model data to the user's device.

[0198] Step 7:

[0199] The terminal reflects the received 3D model in the virtual store in real time and displays it to the user. The input is the received 3D model data, and the data is processed to be placed in the virtual space. The output is a display of customized items in the virtual store that the user can visually confirm.

[0200] Step 8:

[0201] The user checks the displayed 3D model and, if necessary, inputs any correction requests again by text or voice. The input is the user's correction request, which is again transmitted to the user interface. The output is the correction request data.

[0202] Step 9:

[0203] The terminal retransmits the requested modification data to the server, and the server retransmits the regenerated 3D model to the user terminal. The input is the requested modification data, which is analyzed and the regeneration AI model is activated. The output is a retransmission of the modified 3D model data.

[0204] Step 10:

[0205] The 3D model that the user has finalized is projected into reality. The input is the finalized 3D model data, which is used to process it for projection into real space. The output is the projection of the item customized in the virtual space into reality.

[0206] Through the above processing steps, this system enables users to easily customize items in a virtual space and check the changes in real time.

[0207] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0208] This invention relates to a system that generates VR / AR content based on a user's ideas and projects that content into real space. In particular, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide a more personalized experience. Specific embodiments are described below.

[0209] User idea input

[0210] Users access a dedicated application or web interface and input their ideas, such as "I want to add a red sofa to my living room" in text format.

[0211] Emotion Engine Operation

[0212] When a user inputs an idea, the device's built-in emotion engine automatically recognizes the user's emotional state. The emotion engine identifies the user's emotions by analyzing biometric information such as facial expressions, voice, and heart rate. For example, it uses a camera and microphone to analyze the emotions (surprise, joy, sadness, etc.) the user is feeling while inputting in real time.

[0213] Submitting ideas and emotional data

[0214] The device transmits the user's idea data and the emotion data recognized at that time to the server. The transmitted data includes details of the idea, the user's emotional state, and basic information (user ID, location information, etc.).

[0215] Idea and emotion data analysis

[0216] The server analyzes the received idea data and emotion data to extract parameters to be input into the generative AI model. Specific parameters such as color, shape, and size are identified based on the content of the idea. At the same time, the design and color of the content are adjusted based on the user's emotion data.

[0217] Virtual Content Generation

[0218] The server uses a generative AI model based on the extracted parameters to generate virtual content, for example, a 3D model of a "red sofa" that adjusts according to the user's emotional state (e.g., a rounded design if the user is relaxed).

[0219] Sending content and user confirmation

[0220] The generated virtual content is sent from the server to the terminal and displayed to the user. The user can check the generated content and input corrections as needed. For example, the user can input a request for correction, such as "I would like the color of the sofa to be a little darker."

[0221] Parsing and regenerating correction instructions

[0222] The device sends the user's correction instructions to the server, which then regenerates the content using the generative AI model based on the correction instructions and retransmits the corrected virtual content to the device.

[0223] Final confirmation and projection into reality

[0224] Once the user has finally confirmed and approved the content, it is projected into the real world via the device, where a life-size 3D model is displayed in the real world using an AR headset or smartphone.

[0225] Specific examples

[0226] Example 1: Adding furniture

[0227] The user inputs "I want to add a red sofa to my living room," and the device's emotion engine recognizes the user's relaxed emotion. The server generates a 3D model of a red sofa designed to reflect the feeling of relaxation and sends it to the device. After the user confirms and gives their final approval, the sofa is projected onto the living room.

[0228] Example 2: Adding a character

[0229] The user inputs "I want to add a barista character to the cafe scene," and the device's emotion engine recognizes the user's excited emotion. The server generates a 3D model of the barista character with lively movements and sends it to the device. After the user confirms, modifies, and gives final approval, the barista character is projected onto the cafe scene.

[0230] In this way, by taking the user's emotions into consideration when generating and projecting VR / AR content, we can provide a system that is more personalized and improves the user experience.

[0231] The processing flow will be explained below.

[0232] Step 1:

[0233] User: Accesses a specialized application or web interface and enters in text format the idea for the VR / AR content they want to realize. For example, they might enter a request such as, "I want to add a red sofa to my living room."

[0234] Step 2:

[0235] Terminal: The emotion engine is activated while the user is typing. The emotion engine analyzes the user's facial expressions and voice tone through a camera and microphone to recognize their emotional state. For example, it determines whether the user is relaxed.

[0236] Step 3:

[0237] The terminal sends the idea data entered by the user and the recognized emotion data to the server. The sent data includes details of the idea, the user's emotional state, and basic information (user ID, location, etc.).

[0238] Step 4:

[0239] Server: Receives idea data and emotion data sent from the device. Checks the received data and performs appropriate processing.

[0240] Step 5:

[0241] Server: Analyzes the received idea. Extracts the necessary parameters to input into the generative AI model and creates specific generation instructions. For example, for the idea of ​​a "red sofa," it identifies parameters such as color (red), size, shape, and material. At the same time, it adjusts the parameters based on the user's emotional data.

[0242] Step 6:

[0243] Server: Using the extracted parameters, the server uses a generative AI model to generate virtual content. For example, if the user is relaxing, it generates a soft red sofa.

[0244] Step 7:

[0245] Server: The server transmits the generated virtual content (3D model) to the terminal. The transmitted data includes the 3D model file and related metadata.

[0246] Step 8:

[0247] Terminal: Receives the 3D model data sent from the server and displays it to the user, allowing the user to check the generated content through a user interface.

[0248] Step 9:

[0249] User: Checks the generated 3D model and inputs correction instructions as necessary. For example, the user can input a request for correction such as "I would like the color of the sofa to be a little darker."

[0250] Step 10:

[0251] Terminal: Receives the user's correction instructions and sends them back to the server. The transmitted data includes details of the corrections.

[0252] Step 11:

[0253] Server: Receives correction instructions sent from the device and analyzes them again. Adjusts necessary parameters and regenerates the virtual content using the generative AI model.

[0254] Step 12:

[0255] Server: Retransmits the modified virtual content to the device, including data for final confirmation.

[0256] Step 13:

[0257] Terminal: The modified virtual content is displayed to the user, who then performs a final check and approves it if satisfied.

[0258] Step 14:

[0259] Device: The content that the user has finally approved is projected into the real world using an AR headset or smartphone. A life-size red sofa is virtually displayed in the living room.

[0260] Example 2

[0261] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0262] Conventional VR / AR content generation systems generate content without considering the user's emotions, making it difficult to provide a personalized experience for each user. Furthermore, because design and color are not adjusted according to the user's emotions, it is not possible to generate content that truly satisfies the user. This leads to issues such as a poor user experience and a decrease in the value of the system.

[0263] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0264] In this invention, the server includes: a means for a user to input an idea; a means for receiving the idea and transmitting it to the server; a means for acquiring emotion data using an emotion engine that recognizes the user's emotion; a means for transmitting the idea data and the emotion data to the server; a means for analyzing the idea and the emotion data and extracting parameters to be input into a generative AI model; a means for generating virtual content based on the parameters and the emotion data; a means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; a means for regenerating the virtual content based on the correction instructions; and a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality, thereby enabling the generation and projection of personalized VR / AR content according to the user's emotions.

[0265] "User" means an individual or organization that uses information devices or systems to input ideas and generate VR / AR content.

[0266] An "idea" is a concrete expression of instructions or requests input by a user, and includes, for example, adding furniture or arranging characters.

[0267] An "emotion engine" is a software or hardware system that analyzes a user's facial expressions, voice, and biometric information to recognize the user's emotional state in real time.

[0268] "Emotion data" is data that indicates the emotional state of the user analyzed by the emotion engine, and includes emotions such as surprise, joy, and sadness.

[0269] "Parameters" are specific settings or instructions extracted to be fed into a generative AI model, including color, shape, size, etc.

[0270] A "generative AI model" is an artificial intelligence system, such as a deep learning model, that generates VR / AR content based on input parameters.

[0271] "Virtual content" refers to 3D models and scenes generated by generative AI models, and is VR / AR content based on user ideas and emotional data.

[0272] "User device" means a device used by a user to input ideas and review and modify generated virtual content, including a smartphone or PC.

[0273] "Projecting into reality" refers to displaying the final confirmed virtual content in real space, using an AR headset or an AR app on a smartphone.

[0274] "Modification instructions" are requests for changes or adjustments made by the user to the generated virtual content.

[0275] This invention relates to a system that generates VR / AR content based on a user's ideas and projects that content into real space. In particular, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide a more personalized experience.

[0276] First, users access a dedicated application or web interface and enter their idea in text form, such as "I want to add a red sofa to my living room."

[0277] Next, as the user inputs their idea, the device's built-in emotion engine recognizes the user's emotional state in real time. The emotion engine uses a camera and microphone to analyze the user's facial expressions, voice, and biometric information (such as heart rate) to identify the user's current emotion. For example, if the user is relaxed, that emotional state is recognized.

[0278] The device transmits the user's idea data and emotion data to the server using a secure communication protocol. This data includes details of the idea, the user's emotional state, the user ID, and location information.

[0279] The server analyzes the received idea data and emotion data to extract parameters to be input into the generative AI model. Specifically, parameters such as color, shape, and size are identified. At the same time, the design and color of the content are adjusted based on the user's emotion data.

[0280] The server generates virtual content using a generative AI model based on the extracted parameters. For example, a "red sofa with a relaxing design" is created by the generative AI model. An example of a prompt sentence is "I want to add a red sofa to my living room. The user is in a relaxed state."

[0281] The generated virtual content is sent from the server to the device and displayed to the user. The user can check this content and input correction instructions (e.g., "I want the color of the sofa to be a little darker") if necessary.

[0282] The device sends correction instructions to the server, which then uses the generative AI model to generate the corrected virtual content and resends it to the device. Once the user has finally confirmed and approved the content, it is projected into real space via the device. This can be done using an AR headset or an AR app on a smartphone, and a life-size 3D model can be displayed in an environment such as a living room.

[0283] This system enables the generation and projection of personalized VR / AR content according to the user's emotions, improving the user experience. For example, if a user inputs "I want to add a red sofa to my living room" and the emotion engine recognizes the emotion of relaxation, the server will generate a red sofa with a design that reflects the feeling of relaxation and project it into the real world. As a result, the user will be able to enjoy a more satisfying experience.

[0284] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0285] Step 1:

[0286] Users access a dedicated application or web interface and enter their ideas in text format.

[0287] Input: A user-entered text idea (e.g., "I want to add a red sofa to my living room").

[0288] Data processing: Converting text input into digital data.

[0289] Output: The input idea data.

[0290] Specific operation: A user uses a text field in a smartphone or PC application to write down an idea.

[0291] Step 2:

[0292] When a user inputs an idea, the device's built-in emotion engine recognizes the user's emotional state in real time.

[0293] Input: User facial expressions, voice, and biometric information (heart rate, etc.) captured through cameras and microphones.

[0294] Data Processing: The emotion engine analyzes these raw data and identifies the emotional state (e.g., relaxed).

[0295] Output: Emotion data (e.g., relaxed state).

[0296] How it works: The device's camera captures the user's facial expressions, the microphone records their voice, and the emotion engine analyzes this data.

[0297] Step 3:

[0298] The terminal transmits the user's idea data and emotion data to the server using a secure communication protocol.

[0299] Input: Idea data, emotion data, and basic information such as user ID and location.

[0300] Data processing: Idea data and emotion data are packaged and encoded using security protocols.

[0301] Output: The packaged data that is sent to the server.

[0302] Specific operation: The device establishes network communication to send data to the server in bulk.

[0303] Step 4:

[0304] The server analyzes the received data and extracts parameters to be input into the generative AI model.

[0305] Input: Received idea and sentiment data.

[0306] Data processing: The server analyzes the idea data and extracts specific parameters such as color, shape, and size. It also adjusts the design and color based on the emotion data.

[0307] Output: Parameters to feed into a generative AI model.

[0308] Specific operation: The server uses a text analysis algorithm to analyze the content of the idea in detail and extract the necessary parameters.

[0309] Step 5:

[0310] The server generates virtual content using a generative AI model based on the extracted parameters.

[0311] Input: Extracted parameters and emotion data.

[0312] Data processing: Input parameters into the generative AI model to generate virtual content.

[0313] Output: The generated virtual content (e.g., a 3D model).

[0314] Specific operation: The generative AI model generates a 3D model based on the prompt text.

[0315] Step 6:

[0316] The generated virtual content is sent from the server to the terminal and displayed to the user, who then confirms it and inputs any necessary correction instructions.

[0317] Input: The generated virtual content.

[0318] Data processing: Converting content into a format suitable for the user's device.

[0319] Output: The virtual content displayed on the user's device.

[0320] Specific operation: The generated content is sent to the device, and the user inputs correction instructions such as "I would like the color of the sofa to be a little darker."

[0321] Step 7:

[0322] The device sends the user's correction instructions to the server, which then regenerates the virtual content using the generative AI model and resends the corrected virtual content to the device.

[0323] Input: User correction instructions.

[0324] Data processing: Analyze the correction instructions and input them back into the generative AI model.

[0325] Output: The modified virtual content.

[0326] Specific operation: The server retransmits the regenerated virtual content to the device.

[0327] Step 8:

[0328] Once the user has finally confirmed and approved the content, it is projected into the real world via the device.

[0329] Input: Final verified virtual content.

[0330] Data processing: Formatting virtual content to project it into real space.

[0331] Output: The content projected into reality by the AR device.

[0332] What it does: Using an AR headset or an AR app on a smartphone, a 3D model of the final approved red sofa is projected into the living room.

[0333] By performing detailed processing at each step, the system generates personalized VR / AR content based on the user's ideas and emotions, and projects it seamlessly into real space.

[0334] (Application example 2)

[0335] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0336] While conventional technologies could generate virtual content based on user-input ideas, they had the drawback of not being able to adjust the settings based on user emotions or dynamically adjust security device settings. This resulted in a uniform user experience, making it difficult to generate personalized and effective content or security settings.

[0337] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input an idea; means for receiving the idea and transmitting it to the server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; means for collecting user emotion data and adjusting the virtual content based on the emotion; and means for dynamically adjusting security device settings based on the emotion data. This enables personalized virtual content to be generated and projected into the real world based on the user's emotion, and further realizes dynamic adjustment of security devices according to the user's emotional state.

[0338] "User" refers to a person who uses the system to input ideas and review and modify the generated content.

[0339] An "idea" refers to a specific request or wish input by a user, and is information that serves as the basis for generating virtual content.

[0340] "Server" refers to a device that receives ideas and emotional data sent by users, analyzes and processes them, and generates and transmits virtual content.

[0341] A "generative AI model" refers to an artificial intelligence model that generates virtual content by inputting user ideas and emotional data.

[0342] "Virtual content" refers to 3D models and digital data generated based on users' ideas and emotional data.

[0343] A "user terminal" is a device used by a user to operate the system, and includes a smartphone, a head-mounted display, etc.

[0344] "Emotion data" refers to data that indicates the emotional state of a user analyzed from facial expressions, voice, biometric information, and the like.

[0345] "Security appliance" refers to a device for crime prevention or surveillance that adjusts its settings based on the user's emotional state.

[0346] "Dynamic adjustment" refers to automatically changing the settings and operation of security devices based on real-time user emotional data.

[0347] "Projection" refers to displaying the generated virtual content in the real world, using an AR headset or smartphone.

[0348] This invention is a system that generates virtual content based on a user's ideas and emotions, projects it into real space, and dynamically adjusts security equipment settings.

[0349] Hardware and software used

[0350] 1. User Device:

[0351] Hardware: Smartphones (e.g., iPhone (registered trademark), Android (registered trademark) devices), AR headsets, etc.

[0352] Software: OpenCV (facial expression analysis), Google Cloud Speech-to-Text (voice analysis).

[0353] 2. Server:

[0354] Software: Emotion API (Microsoft® Azure®), Custom TENSORFLOW® emotion analysis model, Smart Camera API (control of security devices).

[0355] 3. Security equipment:

[0356] Hardware: Network-enabled security cameras (e.g., ARLO Pro, Nest Cam).

[0357] Invention Process Overview

[0358] 1. Inputting Idea and Emotion Data:

[0359] Users enter their ideas in text through a smartphone application, such as "I want to add a red sofa to my living room."

[0360] 2. Collecting Emotional Data:

[0361] Using the smartphone's camera and microphone, the system collects the user's facial expressions, voice, and biometric information (such as heart rate), and uses this data to analyze the user's emotions in real time.

[0362] 3. Sending ideas and emotional data:

[0363] The collected idea and emotion data is transmitted from the user terminal to a server.

[0364] 4. Data analysis and parameter extraction:

[0365] The server analyzes the received idea data and emotion data to extract input parameters for the generative AI model. For example, for a "red sofa," it identifies parameters related to color, shape, and size, and adjusts the design and color based on the emotion data.

[0366] 5. Virtual Content Generation:

[0367] The server uses the generative AI model to generate virtual content (e.g., a 3D model of a rounded red sofa that reflects the user's sense of relaxation).

[0368] 6. User confirmation and correction:

[0369] The generated virtual content is sent to the user terminal, where the user can check it. If necessary, the user can input correction instructions, such as "I want the color of the sofa to be a little darker."

[0370] 7. Regenerate correction instructions:

[0371] The modification instructions are sent back to the server, where they are regenerated using the generative AI model, and the modified virtual content is then sent back to the user device.

[0372] 8. Final confirmation and reality projection:

[0373] Once the user has finally confirmed and approved the virtual content, it is projected into the real world through the user's device and displayed in the real world using an AR headset or smartphone.

[0374] 9. Dynamically Adjust Security Devices:

[0375] Based on the user's emotional data, the settings of the security equipment are dynamically adjusted. For example, if the user feels anxious, the settings of the security camera are changed to widen the viewing angle and increase the recording sensitivity.

[0376] Examples and explanations of prompt sentences

[0377] Examples of prompts:

[0378] "When a user feels anxious, analyze their emotional data, widen the field of view of the security camera, and change the recording mode to high sensitivity."

[0379] This allows the system to generate personalized virtual content based on the user's emotions and dynamically adjust security devices according to their emotional state.

[0380] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0381] Step 1:

[0382] Users use a smartphone application to input their ideas, such as "I want to add a red sofa to my living room." This input becomes the initial data for the system.

[0383] Input: Text data of ideas

[0384] Output: Text data of ideas

[0385] Step 2:

[0386] The user device collects emotional data along with the input idea. Specifically, it uses the smartphone's camera and microphone to collect the user's facial expressions, voice, and biometric information (such as heart rate). OpenCV and Google Cloud Speech-to-Text are used to analyze and identify the user's emotional state.

[0387] Input: User's facial expression, voice, biometric information

[0388] Output: Emotion data (e.g., relaxed, anxious)

[0389] Step 3:

[0390] The device sends the collected idea data and emotion data to the server. Basic information such as the user ID and location information is also sent at the same time. The server receives this data and proceeds to the next processing step.

[0391] Input: idea data, emotion data, user ID, location information

[0392] Output: Send data to the server

[0393] Step 4:

[0394] The server analyzes the received idea data and emotion data to extract parameters to be fed into the generative AI model. These parameters include the color, shape, and size of the virtual content. The design and color are also adjusted based on the emotion data.

[0395] Input: idea data, emotion data

[0396] Output: Parameters to the generative AI model

[0397] Step 5:

[0398] The server generates virtual content using a generative AI model based on the extracted parameters. For example, for an idea like "add a red sofa to the living room," a 3D model of a rounded red sofa that reflects a relaxing feeling is generated.

[0399] Input: Parameters to the generative AI model

[0400] Output: Virtual content (3D model)

[0401] Step 6:

[0402] The server transmits the generated virtual content to the user terminal, which displays the content to the user and prompts the user to confirm the content, allowing the user to input correction instructions.

[0403] Input: Virtual content (3D model)

[0404] Output: Sending content to the user's device

[0405] Step 7:

[0406] The user checks the virtual content and inputs correction instructions as necessary, for example, "I would like the color of the sofa to be a little darker."

[0407] Input: Correction instructions (text data)

[0408] Output: Correction instruction data

[0409] Step 8:

[0410] The device transmits the user's correction instructions to the server, which then regenerates the virtual content using the generative AI model based on the correction instructions and retransmits the corrected virtual content to the device.

[0411] Input: Correction instruction data

[0412] Output: Modified virtual content (3D model)

[0413] Step 9:

[0414] Once the user has finally reviewed and approved the virtual content, it is projected into the real world, where a life-size 3D model is displayed in the real environment using an AR headset or smartphone.

[0415] Input: Final confirmed virtual content (3D model)

[0416] Output: Virtual content projected into real space

[0417] Step 10:

[0418] Dynamically adjust security device settings based on user emotional data. For example, if a user feels anxious, the security camera's viewing angle will be widened and the recording mode will be set to high sensitivity.

[0419] Input: Emotion data (anxiety)

[0420] Output: Dynamically adjusted security appliance configuration

[0421] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0422] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0423] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0424] [Second embodiment]

[0425] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0426] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0427] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0428] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0429] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0430] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0431] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0432] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0433] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0434] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0435] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0436] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0437] To specifically implement this invention, it is necessary to build a system in which a user, a terminal, and a server work together. In this system, a user inputs an idea, a server analyzes the idea, and generates VR / AR content using a generative AI model, which is then provided to the user through the terminal. Specific embodiments are described below.

[0438] User idea input

[0439] Users can use a dedicated application or web interface to input their ideas for the VR / AR content they want to create in text format. For example, a user can enter a specific request such as "I want to add a red sofa to my living room."

[0440] Submit an idea

[0441] The terminal receives the idea data entered by the user and transmits it to the server. At this time, basic information about the user (such as the user ID and location information) may also be attached along with the content of the idea.

[0442] Idea analysis and parameter extraction

[0443] The server analyzes the received idea data and extracts the necessary parameters to input into the generative AI model. For example, from the idea "I want to add a red sofa to my living room," the server identifies the keyword "red sofa" and determines the specific parameters of the sofa, such as its size, shape, and color.

[0444] Virtual Content Generation

[0445] The server generates virtual content using a generative AI model based on the extracted parameters. In this case, a 3D model of a "red sofa" is generated and temporarily stored on the server.

[0446] Sending content to user devices

[0447] The generated virtual content is sent from the server to the user's device, which provides a user interface for displaying the received 3D model, allowing the user to confirm the content.

[0448] User confirmation and correction

[0449] The device displays the generated 3D model or AR object, and the user can check its contents. If the user is dissatisfied with the generated content or if corrections are required, the user can input correction instructions through the device. For example, "I would like the color of the sofa to be a little darker."

[0450] Sending modifications to the server

[0451] The device retransmits the user's correction instructions to the server, which then reuses the generative AI model based on the correction instructions and regenerates the content.

[0452] Final confirmation and projection into reality

[0453] The revised virtual content is then sent back to the device from the server for final confirmation by the user. If the user is satisfied, the device projects the virtual content into real space using an AR headset or smartphone. For example, a life-size red sofa is virtually displayed in the user's living room.

[0454] Specific examples

[0455] Example 1: Adding furniture

[0456] A user types, "I want to add a red sofa to my living room," and the device sends this idea to the server. The server analyzes the idea and generates a 3D model of the "red sofa." The generated model is sent to the device, where the user can review it. If the user is satisfied, the device projects the sofa in life-size onto the living room.

[0457] Example 2: Adding a character

[0458] The user types, "I want to add a barista character to the cafe scene," and the device sends the idea to the server. The server analyzes the idea and generates a 3D model of the "barista character." The model is then sent to the device, where the user can review, edit, and finalize the model, after which the barista character is projected onto the cafe scene.

[0459] In this way, the present invention allows users to easily generate VR / AR content and project it into real space, accelerating creative projects and making it easier for general users to share virtual experiences.

[0460] The processing flow will be explained below.

[0461] Step 1:

[0462] User: Accesses a dedicated application or web interface and enters in text format the idea for the VR / AR content they want to realize. For example, they might enter a request such as, "I want to add a red sofa to my living room."

[0463] Step 2:

[0464] Terminal: Receives idea data entered by the user. The received data includes details of the idea and basic information of the user (ID, location information, etc.).

[0465] Step 3:

[0466] The terminal transmits the received idea data to the server. The transmitted data includes the content of the idea entered by the user and any accompanying information.

[0467] Step 4:

[0468] Server: Receives idea data sent from the terminal, checks the received data, and performs appropriate processing.

[0469] Step 5:

[0470] Server: Analyzes the received ideas. Extracts parameters to be input into the generative AI model and creates specific generation instructions. For example, for the idea of ​​a "red sofa," it identifies parameters such as color (red), size, shape, and material.

[0471] Step 6:

[0472] Server: Using the extracted parameters, a generative AI model is used to generate virtual content. Specifically, a 3D model of a "red sofa" is automatically created.

[0473] Step 7:

[0474] Server: The server sends the generated virtual content (3D model) to the device. The sent data includes the 3D model file and related metadata.

[0475] Step 8:

[0476] Terminal: Receives the 3D model data sent from the server and displays it to the user, allowing the user to check the generated content through a user interface.

[0477] Step 9:

[0478] User: Checks the generated 3D model and inputs corrections as necessary. For example, the user may request that the color of the sofa be made a little darker.

[0479] Step 10:

[0480] Terminal: Receives the user's correction instructions and sends them back to the server. The transmitted data includes details of the corrections.

[0481] Step 11:

[0482] Server: Receives correction instructions sent from the device and analyzes them again. Adjusts necessary parameters and regenerates the content using the generative AI model.

[0483] Step 12:

[0484] Server: Retransmits the modified virtual content to the device, including data for final confirmation.

[0485] Step 13:

[0486] Terminal: The modified virtual content is displayed to the user, who then performs a final check and approves it if satisfied.

[0487] Step 14:

[0488] Device: The content that the user has finally approved is projected into the real world using an AR headset or smartphone. A life-size red sofa is virtually displayed in the living room.

[0489] Example 1

[0490] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0491] In conventional VR / AR content generation systems, even if a user inputs a specific idea, it is difficult to generate virtual content that accurately reflects that idea. Furthermore, there is a lack of effective means for modifying and finalizing the generated virtual content, making it difficult to easily create content that satisfies the user. The present invention solves these problems by providing a system that generates highly accurate VR / AR content based on an idea input by a user, and that allows modification and finalization to be performed quickly and easily.

[0492] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0493] In this invention, the server includes: a means for a user to input an idea; a means for receiving the idea and transmitting it to the server; a means for analyzing the idea and extracting parameters to be input into a generative AI model; a means for generating virtual content based on the parameters; a means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; a means for regenerating the virtual content based on the correction instructions; a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; a means for generating the virtual content using 3D modeling software; and a means for projecting the final confirmed virtual content into real space using an AR headset or a smartphone. This enables quick and easy generation, modification, and final confirmation of virtual content that accurately reflects the idea input by the user.

[0494] "User" refers to a person who uses the system to input ideas and review and modify generated content.

[0495] "Ideas" refer to specific requests and creative ideas about the VR / AR content that users want to realize.

[0496] "Server" refers to the computer system utilized to analyze user-submitted ideas and generate, modify, and retransmit virtual content.

[0497] "Generative AI model" refers to an artificial intelligence model used to extract and generate appropriate parameters based on a user's ideas and create virtual content.

[0498] "Virtual Content" refers to 3D models and other virtual objects generated by a generative AI model based on a user's ideas.

[0499] "Parameters" refer to various settings and attributes (e.g., color, shape, size, etc.) required to materialize a user's idea.

[0500] "3D Modeling Software" means software tools used to generate 3D models of Virtual Content.

[0501] "User terminal" refers to an electronic device (e.g., smartphone, tablet, PC) used by a user to input ideas and review and modify generated virtual content.

[0502] "Modification instructions" refer to requests for changes or improvements made by a user to the generated virtual content.

[0503] "Projecting into reality" refers to virtually displaying the generated virtual content in real space using an AR headset or smartphone.

[0504] To specifically implement the present invention, it is necessary to build a system in which a user, a terminal, and a server work together. In this system, a user inputs an idea, a server analyzes the idea, and generates virtual content using a generative AI model, which is then provided to the user via the terminal. Specific embodiments are described below.

[0505] User idea input

[0506] Using a dedicated application or web interface, users can enter textual ideas about the virtual content they want to create. For example, a user might enter a specific request, such as "I want to add a red sofa to my living room."

[0507] Sending and receiving ideas

[0508] The terminal receives the idea data entered by the user and transmits it to the server. At this time, basic information about the user (such as the user ID and location information) may also be attached along with the content of the idea.

[0509] Idea analysis and parameter extraction

[0510] The server analyzes the received idea data and extracts the necessary parameters to input into a generative AI model (for example, a general natural language processing AI model). Specifically, from the idea "I want to add a red sofa to my living room," the server identifies the keyword "red sofa" and determines the sofa's specific parameters, such as its size, shape, and color.

[0511] Virtual Content Generation

[0512] The server generates virtual content using a generative AI model based on the extracted parameters. For example, it generates a 3D model of a "red sofa" using 3D modeling software such as Blender or Maya. This 3D model is temporarily stored on the server.

[0513] Sending content to user devices

[0514] The generated virtual content is sent from the server to the user's device, which provides a user interface for displaying the received 3D model, allowing the user to view the model.

[0515] User confirmation and correction

[0516] The user can check the generated 3D model on their device. If they are dissatisfied with the generated content or if corrections are needed, they can input correction instructions through their device. For example, they can input specific correction instructions such as "I would like the color of the sofa to be a little darker."

[0517] Sending modifications to the server and regenerating

[0518] The device retransmits the user's correction instructions to the server, which then reuses the generative AI model based on the correction instructions and regenerates the virtual content.

[0519] Final confirmation and projection into reality

[0520] The revised virtual content is then sent back to the device from the server for final confirmation by the user. If the user is satisfied, the device projects the virtual content into real space using an AR headset or smartphone. For example, a life-size red sofa is virtually displayed in the user's living room.

[0521] Specific examples

[0522] Example 1: Adding furniture

[0523] The user types, "I want to add a red sofa to my living room," and the device sends this to the server. The server analyzes the idea, extracts the necessary parameters, and generates a 3D model of the "red sofa." The generated model is sent to the device, where the user can check it. If the user is satisfied, the device projects the sofa in life-size onto the living room.

[0524] Example 2: Adding a character

[0525] The user inputs "I want to add a barista character to the cafe scene," and the device sends this to the server. The server analyzes the data and generates a 3D model of the "barista character." The model is sent to the device, where the user can review, edit, and finalize the model, after which the barista character is projected onto the cafe scene.

[0526] Examples of prompt statements

[0527] Adding Furniture

[0528] "I would like to add a red sofa to my living room. The sofa should be 200cm wide, 90cm high, and 100cm deep. I would like it to be a dark red."

[0529] Adding characters

[0530] "I want to add a barista character to the cafe scene. The barista's outfit is a young man wearing an apron and a friendly smile."

[0531] Based on these prompts, the generative AI model can generate the desired VR / AR content, allowing users to easily generate VR / AR content and project it into the real world.

[0532] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0533] Step 1:

[0534] Users input their ideas using a dedicated application or web interface. They enter their ideas in text format in an input field, describing specific requests such as "I want to add a red sofa to my living room." The input data is the text information entered by the user. The output data is temporarily stored on the device.

[0535] Step 2:

[0536] The device sends the ideas entered by the user to the server. Specifically, it uses the REST API to send idea data to the server. At this time, basic information such as the user ID and timestamp is also sent. The input data consists of temporarily saved text information and basic information. This data is sent to the server as output.

[0537] Step 3:

[0538] The server analyzes the received ideas and extracts parameters to feed into the generative AI model. It uses a natural language processing API to analyze the text and identify important keywords such as "red sofa" and "living room." The input data is the text information sent. The output is the extracted parameters.

[0539] Step 4:

[0540] The server generates virtual content using a generative AI model based on the extracted parameters. Specifically, it generates a 3D model of a "red sofa" using 3D modeling software (e.g., Blender or Maya). The input data is the extracted parameters, such as "red sofa." The output is a 3D model based on these parameters.

[0541] Step 5:

[0542] The server sends the generated virtual content to the user's device. The generated 3D model file (e.g., .fbx format) is sent to the device via a REST API. The input data is the generated 3D model. The output is the model sent to the device.

[0543] Step 6:

[0544] The device provides a user interface to display the received 3D model, allowing the user to check the content. The input data is the transmitted 3D model. The output is the user's view of the 3D model through the interface.

[0545] Step 7:

[0546] The user checks the 3D model generated on the device, and if there are any complaints or corrections that need to be made, they can input correction instructions through the device. For example, they can write down specific requests for corrections, such as "I would like the color of the sofa to be a little darker." The input data is the correction instructions written by the user. As output, these instructions are temporarily saved on the device.

[0547] Step 8:

[0548] The device resubmits the user's correction instructions to the server. It again uses the REST API to send the correction instruction data to the server. The input data is the temporarily saved correction instructions. The output is this instruction sent to the server.

[0549] Step 9:

[0550] The server reuses the generative AI model based on the modification instructions to recreate the virtual content. It regenerates the 3D model based on new parameters (e.g., color changes). The input data are the parameters based on the modification instructions. The output is the modified 3D model.

[0551] Step 10:

[0552] The server resends the modified virtual content to the user's device. It sends the regenerated 3D model file to the device. The input data is the modified 3D model. The output data is sent to the device.

[0553] Step 11:

[0554] The user then checks the revised 3D model on the device again. If the user is satisfied, they can use the device to project the virtual content into real space via an AR headset or smartphone. The input data is the revised 3D model that was sent. The output is the virtual projection of this model into real space.

[0555] (Application example 1)

[0556] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0557] In conventional virtual object viewing systems, when users want to customize an object, they lack a mechanism to directly reflect their wishes, which reduces user satisfaction. In particular, the inability to easily customize the color, shape, and placement of an object limits the user experience.

[0558] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0559] In this invention, the server includes: means for a user to input an idea; means for receiving the idea and transmitting it to the server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; means for providing a user interface for customizing specifications of an item in a virtual space; and means for exploring the virtual space in real time and reflecting changes to the item. This allows users to freely customize the specifications of items in the virtual space, and the changes are reflected in real time, enabling a more satisfying user experience.

[0560] The "means for the user to input ideas" refers to a device that includes an interface that allows the user to provide specific requests or ideas to the system as text or voice input.

[0561] The "means for receiving the idea and transmitting it to the server" is a device including a communication means for receiving idea data input by the user and transmitting it to the server side.

[0562] "Means for analyzing the idea and extracting parameters to be input into the generative AI model" refers to a device that includes a process for analyzing received idea data and extracting specific parameters required by the generative AI model.

[0563] The "means for generating virtual content based on the parameters" is a device that includes a process for running a generative AI model using the extracted parameters to generate the specified virtual content.

[0564] The "means for transmitting the generated virtual content to a user terminal and accepting user confirmation and modification instructions" refers to a device that includes a communication means and an interface for transmitting the generated virtual content to a user terminal and accepting user confirmation and modification instructions.

[0565] The "means for regenerating virtual content based on the modification instructions" is a device that includes a process and a generation AI model for regenerating virtual content based on modification instructions from a user.

[0566] The "means for retransmitting the modified virtual content to the user terminal and projecting the final confirmed virtual content into reality" refers to a device for retransmitting the modified virtual content to the user terminal and projecting the final confirmed virtual content into a real environment.

[0567] The "means for providing a user interface for customizing the specifications of an item in a virtual space" is a device that provides a user interface for customizing the color, shape, placement, etc. of an item in a virtual space.

[0568] The "means for searching the virtual space in real time and reflecting changes to the item" is a device for reflecting changes to the item made by the user in real time while searching the virtual space.

[0569] To implement this invention, it is necessary to build a system using a server, a user terminal, and a generative AI model. A specific embodiment of this system will be described below.

[0570] Hardware and software used

[0571] Head-mounted display (HMD): For example, using a device such as Oculus Quest 2.

[0572] User interface: Virtual keyboard and voice interface to enter requests in text format.

[0573] Generative AI models: For example, OpenAI's DALL-E or Google DeepMind's Imagen.

[0574] Server system: Responsible for idea analysis and content generation on cloud servers (AWS, Google Cloud, etc.).

[0575] System operation flow

[0576] First, the user wears a head-mounted display and freely explores the virtual store. If the user becomes interested in a particular item during the exploration and wants to customize its color, shape, or placement, they can input their idea via text or voice. For example, they could say, "I want the color of this sofa to be changed to blue."

[0577] The user's device receives the idea and sends it to the server, which analyzes the idea and extracts parameters (product type, color, shape, etc.) for the generative AI model. Next, the generative AI model (e.g., DALL-E or Imagen) generates a customized item and creates its 3D model data.

[0578] The generated 3D model data is sent to the user's HMD in real time, and the new object model is immediately reflected in the virtual space. The user can review the changes and, if necessary, input any corrections.

[0579] Specific examples

[0580] For example, a user finds a sofa in a virtual store and requests, "I want the color of this sofa changed to blue." The request is sent to the server, which analyzes it and generates a 3D model of a new sofa using a generative AI model. The generated sofa is then displayed in the virtual store in real time for the user to review. By issuing further corrections as necessary, the user can finally experience the ideal product.

[0581] Examples of prompt statements

[0582] "I want this sofa changed to blue."

[0583] Move this table to the window.

[0584] Make this bed a little bigger

[0585] This allows users to freely customize the specifications of items in virtual space, and the changes are reflected in real time, allowing for a more satisfying user experience.

[0586] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0587] Step 1:

[0588] The user wears a head-mounted display and explores the virtual store. The input is the user's motion information and viewpoint information, and based on this information, the user interface displays the environment in real time. The output is display data of the virtual store.

[0589] Step 2:

[0590] The user inputs customization requests for a particular item by text or voice. The input is the user's text or voice customization requests, which are communicated to the user interface. The output is the user's customization request data.

[0591] Step 3:

[0592] The terminal receives this customization request data and sends it to the server. The input is the customization request data entered by the user, which is sent to the server using a communication means. The output is the transfer of the customization request data to the server.

[0593] Step 4:

[0594] The server analyzes the received customization request data and extracts parameters to be input into the generative AI model. The input is the customization request data, which is analyzed using natural language processing technology. The output is specific parameters to be input into the generative AI model (e.g., "blue sofa").

[0595] Step 5:

[0596] The server uses the extracted parameters to activate a generative AI model and generate virtual content. The input is the parameters required by the generative AI model, and a 3D model is generated using the generative AI model (e.g., DALL-E or Imagen). The output is the generated 3D model data.

[0597] Step 6:

[0598] The server sends the generated 3D model data to the user's device. The input is the generated 3D model data, which is then sent back to the user's device via a communication means. The output is the transfer of the 3D model data to the user's device.

[0599] Step 7:

[0600] The terminal reflects the received 3D model in the virtual store in real time and displays it to the user. The input is the received 3D model data, and the data is processed to be placed in the virtual space. The output is a display of customized items in the virtual store that the user can visually confirm.

[0601] Step 8:

[0602] The user checks the displayed 3D model and, if necessary, inputs any correction requests again by text or voice. The input is the user's correction request, which is again transmitted to the user interface. The output is the correction request data.

[0603] Step 9:

[0604] The terminal retransmits the requested modification data to the server, and the server retransmits the regenerated 3D model to the user terminal. The input is the requested modification data, which is analyzed and the regeneration AI model is activated. The output is a retransmission of the modified 3D model data.

[0605] Step 10:

[0606] The 3D model that the user has finalized is projected into reality. The input is the finalized 3D model data, which is used to process it for projection into real space. The output is the projection of the item customized in the virtual space into reality.

[0607] Through the above processing steps, this system enables users to easily customize items in a virtual space and check the changes in real time.

[0608] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0609] This invention relates to a system that generates VR / AR content based on a user's ideas and projects that content into real space. In particular, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide a more personalized experience. Specific embodiments are described below.

[0610] User idea input

[0611] Users access a dedicated application or web interface and input their ideas, such as "I want to add a red sofa to my living room" in text format.

[0612] Emotion Engine Operation

[0613] When a user inputs an idea, the device's built-in emotion engine automatically recognizes the user's emotional state. The emotion engine identifies the user's emotions by analyzing biometric information such as facial expressions, voice, and heart rate. For example, it uses a camera and microphone to analyze the emotions (surprise, joy, sadness, etc.) the user is feeling while inputting in real time.

[0614] Submitting ideas and emotional data

[0615] The device transmits the user's idea data and the emotion data recognized at that time to the server. The transmitted data includes details of the idea, the user's emotional state, and basic information (user ID, location information, etc.).

[0616] Idea and emotion data analysis

[0617] The server analyzes the received idea data and emotion data to extract parameters to be input into the generative AI model. Specific parameters such as color, shape, and size are identified based on the content of the idea. At the same time, the design and color of the content are adjusted based on the user's emotion data.

[0618] Virtual Content Generation

[0619] The server uses a generative AI model based on the extracted parameters to generate virtual content, for example, a 3D model of a "red sofa" that adjusts according to the user's emotional state (e.g., a rounded design if the user is relaxed).

[0620] Sending content and user confirmation

[0621] The generated virtual content is sent from the server to the terminal and displayed to the user. The user can check the generated content and input corrections as needed. For example, the user can input a request for correction, such as "I would like the color of the sofa to be a little darker."

[0622] Parsing and regenerating correction instructions

[0623] The device sends the user's correction instructions to the server, which then regenerates the content using the generative AI model based on the correction instructions and retransmits the corrected virtual content to the device.

[0624] Final confirmation and projection into reality

[0625] Once the user has finally confirmed and approved the content, it is projected into the real world via the device, where a life-size 3D model is displayed in the real world using an AR headset or smartphone.

[0626] Specific examples

[0627] Example 1: Adding furniture

[0628] The user inputs "I want to add a red sofa to my living room," and the device's emotion engine recognizes the user's relaxed emotion. The server generates a 3D model of a red sofa designed to reflect the feeling of relaxation and sends it to the device. After the user confirms and gives their final approval, the sofa is projected onto the living room.

[0629] Example 2: Adding a character

[0630] The user inputs "I want to add a barista character to the cafe scene," and the device's emotion engine recognizes the user's excited emotion. The server generates a 3D model of the barista character with lively movements and sends it to the device. After the user confirms, modifies, and gives final approval, the barista character is projected onto the cafe scene.

[0631] In this way, by taking the user's emotions into consideration when generating and projecting VR / AR content, we can provide a system that is more personalized and improves the user experience.

[0632] The processing flow will be explained below.

[0633] Step 1:

[0634] User: Accesses a specialized application or web interface and enters in text format the idea for the VR / AR content they want to realize. For example, they might enter a request such as, "I want to add a red sofa to my living room."

[0635] Step 2:

[0636] Terminal: The emotion engine is activated while the user is typing. The emotion engine analyzes the user's facial expressions and voice tone through a camera and microphone to recognize their emotional state. For example, it determines whether the user is relaxed.

[0637] Step 3:

[0638] The terminal sends the idea data entered by the user and the recognized emotion data to the server. The sent data includes details of the idea, the user's emotional state, and basic information (user ID, location, etc.).

[0639] Step 4:

[0640] Server: Receives idea data and emotion data sent from the device. Checks the received data and performs appropriate processing.

[0641] Step 5:

[0642] Server: Analyzes the received idea. Extracts the necessary parameters to input into the generative AI model and creates specific generation instructions. For example, for the idea of ​​a "red sofa," it identifies parameters such as color (red), size, shape, and material. At the same time, it adjusts the parameters based on the user's emotional data.

[0643] Step 6:

[0644] Server: Using the extracted parameters, the server uses a generative AI model to generate virtual content. For example, if the user is relaxing, it generates a soft red sofa.

[0645] Step 7:

[0646] Server: The server transmits the generated virtual content (3D model) to the terminal. The transmitted data includes the 3D model file and related metadata.

[0647] Step 8:

[0648] Terminal: Receives the 3D model data sent from the server and displays it to the user, allowing the user to check the generated content through a user interface.

[0649] Step 9:

[0650] User: Checks the generated 3D model and inputs correction instructions as necessary. For example, the user can input a request for correction such as "I would like the color of the sofa to be a little darker."

[0651] Step 10:

[0652] Terminal: Receives the user's correction instructions and sends them back to the server. The transmitted data includes details of the corrections.

[0653] Step 11:

[0654] Server: Receives correction instructions sent from the device and analyzes them again. Adjusts necessary parameters and regenerates the virtual content using the generative AI model.

[0655] Step 12:

[0656] Server: Retransmits the modified virtual content to the device, including data for final confirmation.

[0657] Step 13:

[0658] Terminal: The modified virtual content is displayed to the user, who then performs a final check and approves it if satisfied.

[0659] Step 14:

[0660] Device: The content that the user has finally approved is projected into the real world using an AR headset or smartphone. A life-size red sofa is virtually displayed in the living room.

[0661] Example 2

[0662] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0663] Conventional VR / AR content generation systems generate content without considering the user's emotions, making it difficult to provide a personalized experience for each user. Furthermore, because design and color are not adjusted according to the user's emotions, it is not possible to generate content that truly satisfies the user. This leads to issues such as a poor user experience and a decrease in the value of the system.

[0664] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0665] In this invention, the server includes: a means for a user to input an idea; a means for receiving the idea and transmitting it to the server; a means for acquiring emotion data using an emotion engine that recognizes the user's emotion; a means for transmitting the idea data and the emotion data to the server; a means for analyzing the idea and the emotion data and extracting parameters to be input into a generative AI model; a means for generating virtual content based on the parameters and the emotion data; a means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; a means for regenerating the virtual content based on the correction instructions; and a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality, thereby enabling the generation and projection of personalized VR / AR content according to the user's emotions.

[0666] "User" means an individual or organization that uses information devices or systems to input ideas and generate VR / AR content.

[0667] An "idea" is a concrete expression of instructions or requests input by a user, and includes, for example, adding furniture or arranging characters.

[0668] An "emotion engine" is a software or hardware system that analyzes a user's facial expressions, voice, and biometric information to recognize the user's emotional state in real time.

[0669] "Emotion data" is data that indicates the emotional state of the user analyzed by the emotion engine, and includes emotions such as surprise, joy, and sadness.

[0670] "Parameters" are specific settings or instructions extracted to be fed into a generative AI model, including color, shape, size, etc.

[0671] A "generative AI model" is an artificial intelligence system, such as a deep learning model, that generates VR / AR content based on input parameters.

[0672] "Virtual content" refers to 3D models and scenes generated by generative AI models, and is VR / AR content based on user ideas and emotional data.

[0673] "User device" means a device used by a user to input ideas and review and modify generated virtual content, including a smartphone or PC.

[0674] "Projecting into reality" refers to displaying the final confirmed virtual content in real space, using an AR headset or an AR app on a smartphone.

[0675] "Modification instructions" are requests for changes or adjustments made by the user to the generated virtual content.

[0676] This invention relates to a system that generates VR / AR content based on a user's ideas and projects that content into real space. In particular, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide a more personalized experience.

[0677] First, users access a dedicated application or web interface and enter their idea in text form, such as "I want to add a red sofa to my living room."

[0678] Next, as the user inputs their idea, the device's built-in emotion engine recognizes the user's emotional state in real time. The emotion engine uses a camera and microphone to analyze the user's facial expressions, voice, and biometric information (such as heart rate) to identify the user's current emotion. For example, if the user is relaxed, that emotional state is recognized.

[0679] The device transmits the user's idea data and emotion data to the server using a secure communication protocol. This data includes details of the idea, the user's emotional state, the user ID, and location information.

[0680] The server analyzes the received idea data and emotion data to extract parameters to be input into the generative AI model. Specifically, parameters such as color, shape, and size are identified. At the same time, the design and color of the content are adjusted based on the user's emotion data.

[0681] The server generates virtual content using a generative AI model based on the extracted parameters. For example, a "red sofa with a relaxing design" is created by the generative AI model. An example of a prompt sentence is "I want to add a red sofa to my living room. The user is in a relaxed state."

[0682] The generated virtual content is sent from the server to the device and displayed to the user. The user can check this content and input correction instructions (e.g., "I want the color of the sofa to be a little darker") if necessary.

[0683] The device sends correction instructions to the server, which then uses the generative AI model to generate the corrected virtual content and resends it to the device. Once the user has finally confirmed and approved the content, it is projected into real space via the device. This can be done using an AR headset or an AR app on a smartphone, and a life-size 3D model can be displayed in an environment such as a living room.

[0684] This system enables the generation and projection of personalized VR / AR content according to the user's emotions, improving the user experience. For example, if a user inputs "I want to add a red sofa to my living room" and the emotion engine recognizes the emotion of relaxation, the server will generate a red sofa with a design that reflects the feeling of relaxation and project it into the real world. As a result, the user will be able to enjoy a more satisfying experience.

[0685] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0686] Step 1:

[0687] Users access a dedicated application or web interface and enter their ideas in text format.

[0688] Input: A user-entered text idea (e.g., "I want to add a red sofa to my living room").

[0689] Data processing: Converting text input into digital data.

[0690] Output: The input idea data.

[0691] Specific operation: A user uses a text field in a smartphone or PC application to write down an idea.

[0692] Step 2:

[0693] When a user inputs an idea, the device's built-in emotion engine recognizes the user's emotional state in real time.

[0694] Input: User facial expressions, voice, and biometric information (heart rate, etc.) captured through cameras and microphones.

[0695] Data Processing: The emotion engine analyzes these raw data and identifies the emotional state (e.g., relaxed).

[0696] Output: Emotion data (e.g., relaxed state).

[0697] How it works: The device's camera captures the user's facial expressions, the microphone records their voice, and the emotion engine analyzes this data.

[0698] Step 3:

[0699] The terminal transmits the user's idea data and emotion data to the server using a secure communication protocol.

[0700] Input: Idea data, emotion data, and basic information such as user ID and location.

[0701] Data processing: Idea data and emotion data are packaged and encoded using security protocols.

[0702] Output: The packaged data that is sent to the server.

[0703] Specific operation: The device establishes network communication to send data to the server in bulk.

[0704] Step 4:

[0705] The server analyzes the received data and extracts parameters to be input into the generative AI model.

[0706] Input: Received idea and sentiment data.

[0707] Data processing: The server analyzes the idea data and extracts specific parameters such as color, shape, and size. It also adjusts the design and color based on the emotion data.

[0708] Output: Parameters to feed into a generative AI model.

[0709] Specific operation: The server uses a text analysis algorithm to analyze the content of the idea in detail and extract the necessary parameters.

[0710] Step 5:

[0711] The server generates virtual content using a generative AI model based on the extracted parameters.

[0712] Input: Extracted parameters and emotion data.

[0713] Data processing: Input parameters into the generative AI model to generate virtual content.

[0714] Output: The generated virtual content (e.g., a 3D model).

[0715] Specific operation: The generative AI model generates a 3D model based on the prompt text.

[0716] Step 6:

[0717] The generated virtual content is sent from the server to the terminal and displayed to the user, who then confirms it and inputs any necessary correction instructions.

[0718] Input: The generated virtual content.

[0719] Data processing: Converting content into a format suitable for the user's device.

[0720] Output: The virtual content displayed on the user's device.

[0721] Specific operation: The generated content is sent to the device, and the user inputs correction instructions such as "I would like the color of the sofa to be a little darker."

[0722] Step 7:

[0723] The device sends the user's correction instructions to the server, which then regenerates the virtual content using the generative AI model and resends the corrected virtual content to the device.

[0724] Input: User correction instructions.

[0725] Data processing: Analyze the correction instructions and input them back into the generative AI model.

[0726] Output: The modified virtual content.

[0727] Specific operation: The server retransmits the regenerated virtual content to the device.

[0728] Step 8:

[0729] Once the user has finally confirmed and approved the content, it is projected into the real world via the device.

[0730] Input: Final verified virtual content.

[0731] Data processing: Formatting virtual content to project it into real space.

[0732] Output: The content projected into reality by the AR device.

[0733] What it does: Using an AR headset or an AR app on a smartphone, a 3D model of the final approved red sofa is projected into the living room.

[0734] By performing detailed processing at each step, the system generates personalized VR / AR content based on the user's ideas and emotions, and projects it seamlessly into real space.

[0735] (Application example 2)

[0736] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0737] While conventional technologies could generate virtual content based on user-input ideas, they had the drawback of not being able to adjust the settings based on user emotions or dynamically adjust security device settings. This resulted in a uniform user experience, making it difficult to generate personalized and effective content or security settings.

[0738] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input an idea; means for receiving the idea and transmitting it to the server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; means for collecting user emotion data and adjusting the virtual content based on the emotion; and means for dynamically adjusting security device settings based on the emotion data. This enables personalized virtual content to be generated and projected into the real world based on the user's emotion, and further realizes dynamic adjustment of security devices according to the user's emotional state.

[0739] "User" refers to a person who uses the system to input ideas and review and modify the generated content.

[0740] An "idea" refers to a specific request or wish input by a user, and is information that serves as the basis for generating virtual content.

[0741] "Server" refers to a device that receives ideas and emotional data sent by users, analyzes and processes them, and generates and transmits virtual content.

[0742] A "generative AI model" refers to an artificial intelligence model that generates virtual content by inputting user ideas and emotional data.

[0743] "Virtual content" refers to 3D models and digital data generated based on users' ideas and emotional data.

[0744] A "user terminal" is a device used by a user to operate the system, and includes a smartphone, a head-mounted display, etc.

[0745] "Emotion data" refers to data that indicates the emotional state of a user analyzed from facial expressions, voice, biometric information, and the like.

[0746] "Security appliance" refers to a device for crime prevention or surveillance that adjusts its settings based on the user's emotional state.

[0747] "Dynamic adjustment" refers to automatically changing the settings and operation of security devices based on real-time user emotional data.

[0748] "Projection" refers to displaying the generated virtual content in the real world, using an AR headset or smartphone.

[0749] This invention is a system that generates virtual content based on a user's ideas and emotions, projects it into real space, and dynamically adjusts security equipment settings.

[0750] Hardware and software used

[0751] 1. User Device:

[0752] Hardware: Smartphones (e.g., iPhones, Android devices), AR headsets, etc.

[0753] Software: OpenCV (facial expression analysis), Google Cloud Speech-to-Text (voice analysis).

[0754] 2. Server:

[0755] Software: Emotion API (Microsoft Azure), Custom TensorFlow sentiment analysis model, Smart Camera API (security equipment control).

[0756] 3. Security equipment:

[0757] Hardware: Network-enabled security cameras (e.g., ARLO Pro, Nest Cam).

[0758] Invention Process Overview

[0759] 1. Inputting Idea and Emotion Data:

[0760] Users enter their ideas in text through a smartphone application, such as "I want to add a red sofa to my living room."

[0761] 2. Collecting Emotional Data:

[0762] Using the smartphone's camera and microphone, the system collects the user's facial expressions, voice, and biometric information (such as heart rate), and uses this data to analyze the user's emotions in real time.

[0763] 3. Sending ideas and emotional data:

[0764] The collected idea and emotion data is transmitted from the user terminal to a server.

[0765] 4. Data analysis and parameter extraction:

[0766] The server analyzes the received idea data and emotion data to extract input parameters for the generative AI model. For example, for a "red sofa," it identifies parameters related to color, shape, and size, and adjusts the design and color based on the emotion data.

[0767] 5. Virtual Content Generation:

[0768] The server uses the generative AI model to generate virtual content (e.g., a 3D model of a rounded red sofa that reflects the user's sense of relaxation).

[0769] 6. User confirmation and correction:

[0770] The generated virtual content is sent to the user terminal, where the user can check it. If necessary, the user can input correction instructions, such as "I want the color of the sofa to be a little darker."

[0771] 7. Regenerate correction instructions:

[0772] The modification instructions are sent back to the server, where they are regenerated using the generative AI model, and the modified virtual content is then sent back to the user device.

[0773] 8. Final confirmation and reality projection:

[0774] Once the user has finally confirmed and approved the virtual content, it is projected into the real world through the user's device and displayed in the real world using an AR headset or smartphone.

[0775] 9. Dynamically Adjust Security Devices:

[0776] Based on the user's emotional data, the settings of the security equipment are dynamically adjusted. For example, if the user feels anxious, the settings of the security camera are changed to widen the viewing angle and increase the recording sensitivity.

[0777] Examples and explanations of prompt sentences

[0778] Examples of prompts:

[0779] "When a user feels anxious, analyze their emotional data, widen the field of view of the security camera, and change the recording mode to high sensitivity."

[0780] This allows the system to generate personalized virtual content based on the user's emotions and dynamically adjust security devices according to their emotional state.

[0781] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0782] Step 1:

[0783] Users use a smartphone application to input their ideas, such as "I want to add a red sofa to my living room." This input becomes the initial data for the system.

[0784] Input: Text data of ideas

[0785] Output: Text data of ideas

[0786] Step 2:

[0787] The user device collects emotional data along with the input idea. Specifically, it uses the smartphone's camera and microphone to collect the user's facial expressions, voice, and biometric information (such as heart rate). OpenCV and Google Cloud Speech-to-Text are used to analyze and identify the user's emotional state.

[0788] Input: User's facial expression, voice, biometric information

[0789] Output: Emotion data (e.g., relaxed, anxious)

[0790] Step 3:

[0791] The device sends the collected idea data and emotion data to the server. Basic information such as the user ID and location information is also sent at the same time. The server receives this data and proceeds to the next processing step.

[0792] Input: idea data, emotion data, user ID, location information

[0793] Output: Send data to the server

[0794] Step 4:

[0795] The server analyzes the received idea data and emotion data to extract parameters to be fed into the generative AI model. These parameters include the color, shape, and size of the virtual content. The design and color are also adjusted based on the emotion data.

[0796] Input: idea data, emotion data

[0797] Output: Parameters to the generative AI model

[0798] Step 5:

[0799] The server generates virtual content using a generative AI model based on the extracted parameters. For example, for an idea like "add a red sofa to the living room," a 3D model of a rounded red sofa that reflects a relaxing feeling is generated.

[0800] Input: Parameters to the generative AI model

[0801] Output: Virtual content (3D model)

[0802] Step 6:

[0803] The server transmits the generated virtual content to the user terminal, which displays the content to the user and prompts the user to confirm the content, allowing the user to input correction instructions.

[0804] Input: Virtual content (3D model)

[0805] Output: Sending content to the user's device

[0806] Step 7:

[0807] The user checks the virtual content and inputs correction instructions as necessary, for example, "I would like the color of the sofa to be a little darker."

[0808] Input: Correction instructions (text data)

[0809] Output: Correction instruction data

[0810] Step 8:

[0811] The device transmits the user's correction instructions to the server, which then regenerates the virtual content using the generative AI model based on the correction instructions and retransmits the corrected virtual content to the device.

[0812] Input: Correction instruction data

[0813] Output: Modified virtual content (3D model)

[0814] Step 9:

[0815] Once the user has finally reviewed and approved the virtual content, it is projected into the real world, where a life-size 3D model is displayed in the real environment using an AR headset or smartphone.

[0816] Input: Final confirmed virtual content (3D model)

[0817] Output: Virtual content projected into real space

[0818] Step 10:

[0819] Dynamically adjust security device settings based on user emotional data. For example, if a user feels anxious, the security camera's viewing angle will be widened and the recording mode will be set to high sensitivity.

[0820] Input: Emotion data (anxiety)

[0821] Output: Dynamically adjusted security appliance configuration

[0822] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0823] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0824] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0825] [Third embodiment]

[0826] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0827] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0828] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0829] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0830] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0831] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0832] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0833] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0834] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0835] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0836] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0837] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0838] To specifically implement this invention, it is necessary to build a system in which a user, a terminal, and a server work together. In this system, a user inputs an idea, a server analyzes the idea, and generates VR / AR content using a generative AI model, which is then provided to the user through the terminal. Specific embodiments are described below.

[0839] User idea input

[0840] Users can use a dedicated application or web interface to input their ideas for the VR / AR content they want to create in text format. For example, a user can enter a specific request such as "I want to add a red sofa to my living room."

[0841] Submit an idea

[0842] The terminal receives the idea data entered by the user and transmits it to the server. At this time, basic information about the user (such as the user ID and location information) may also be attached along with the content of the idea.

[0843] Idea analysis and parameter extraction

[0844] The server analyzes the received idea data and extracts the necessary parameters to input into the generative AI model. For example, from the idea "I want to add a red sofa to my living room," the server identifies the keyword "red sofa" and determines the specific parameters of the sofa, such as its size, shape, and color.

[0845] Virtual Content Generation

[0846] The server generates virtual content using a generative AI model based on the extracted parameters. In this case, a 3D model of a "red sofa" is generated and temporarily stored on the server.

[0847] Sending content to user devices

[0848] The generated virtual content is sent from the server to the user's device, which provides a user interface for displaying the received 3D model, allowing the user to confirm the content.

[0849] User confirmation and correction

[0850] The device displays the generated 3D model or AR object, and the user can check its contents. If the user is dissatisfied with the generated content or if corrections are required, the user can input correction instructions through the device. For example, "I would like the color of the sofa to be a little darker."

[0851] Sending modifications to the server

[0852] The device retransmits the user's correction instructions to the server, which then reuses the generative AI model based on the correction instructions and regenerates the content.

[0853] Final confirmation and projection into reality

[0854] The revised virtual content is then sent back to the device from the server for final confirmation by the user. If the user is satisfied, the device projects the virtual content into real space using an AR headset or smartphone. For example, a life-size red sofa is virtually displayed in the user's living room.

[0855] Specific examples

[0856] Example 1: Adding furniture

[0857] A user types, "I want to add a red sofa to my living room," and the device sends this idea to the server. The server analyzes the idea and generates a 3D model of the "red sofa." The generated model is sent to the device, where the user can review it. If the user is satisfied, the device projects the sofa in life-size onto the living room.

[0858] Example 2: Adding a character

[0859] The user types, "I want to add a barista character to the cafe scene," and the device sends the idea to the server. The server analyzes the idea and generates a 3D model of the "barista character." The model is then sent to the device, where the user can review, edit, and finalize the model, after which the barista character is projected onto the cafe scene.

[0860] In this way, the present invention allows users to easily generate VR / AR content and project it into real space, accelerating creative projects and making it easier for general users to share virtual experiences.

[0861] The processing flow will be explained below.

[0862] Step 1:

[0863] User: Accesses a dedicated application or web interface and enters in text format the idea for the VR / AR content they want to realize. For example, they might enter a request such as, "I want to add a red sofa to my living room."

[0864] Step 2:

[0865] Terminal: Receives idea data entered by the user. The received data includes details of the idea and basic information of the user (ID, location information, etc.).

[0866] Step 3:

[0867] The terminal transmits the received idea data to the server. The transmitted data includes the content of the idea entered by the user and any accompanying information.

[0868] Step 4:

[0869] Server: Receives idea data sent from the terminal, checks the received data, and performs appropriate processing.

[0870] Step 5:

[0871] Server: Analyzes the received ideas. Extracts parameters to be input into the generative AI model and creates specific generation instructions. For example, for the idea of ​​a "red sofa," it identifies parameters such as color (red), size, shape, and material.

[0872] Step 6:

[0873] Server: Using the extracted parameters, a generative AI model is used to generate virtual content. Specifically, a 3D model of a "red sofa" is automatically created.

[0874] Step 7:

[0875] Server: The server sends the generated virtual content (3D model) to the device. The sent data includes the 3D model file and related metadata.

[0876] Step 8:

[0877] Terminal: Receives the 3D model data sent from the server and displays it to the user, allowing the user to check the generated content through a user interface.

[0878] Step 9:

[0879] User: Checks the generated 3D model and inputs corrections as necessary. For example, the user may request that the color of the sofa be made a little darker.

[0880] Step 10:

[0881] Terminal: Receives the user's correction instructions and sends them back to the server. The transmitted data includes details of the corrections.

[0882] Step 11:

[0883] Server: Receives correction instructions sent from the device and analyzes them again. Adjusts necessary parameters and regenerates the content using the generative AI model.

[0884] Step 12:

[0885] Server: Retransmits the modified virtual content to the device, including data for final confirmation.

[0886] Step 13:

[0887] Terminal: The modified virtual content is displayed to the user, who then performs a final check and approves it if satisfied.

[0888] Step 14:

[0889] Device: The content that the user has finally approved is projected into the real world using an AR headset or smartphone. A life-size red sofa is virtually displayed in the living room.

[0890] Example 1

[0891] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0892] In conventional VR / AR content generation systems, even if a user inputs a specific idea, it is difficult to generate virtual content that accurately reflects that idea. Furthermore, there is a lack of effective means for modifying and finalizing the generated virtual content, making it difficult to easily create content that satisfies the user. The present invention solves these problems by providing a system that generates highly accurate VR / AR content based on an idea input by a user, and that allows modification and finalization to be performed quickly and easily.

[0893] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0894] In this invention, the server includes: a means for a user to input an idea; a means for receiving the idea and transmitting it to the server; a means for analyzing the idea and extracting parameters to be input into a generative AI model; a means for generating virtual content based on the parameters; a means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; a means for regenerating the virtual content based on the correction instructions; a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; a means for generating the virtual content using 3D modeling software; and a means for projecting the final confirmed virtual content into real space using an AR headset or a smartphone. This enables quick and easy generation, modification, and final confirmation of virtual content that accurately reflects the idea input by the user.

[0895] "User" refers to a person who uses the system to input ideas and review and modify generated content.

[0896] "Ideas" refer to specific requests and creative ideas about the VR / AR content that users want to realize.

[0897] "Server" refers to the computer system utilized to analyze user-submitted ideas and generate, modify, and retransmit virtual content.

[0898] "Generative AI model" refers to an artificial intelligence model used to extract and generate appropriate parameters based on a user's ideas and create virtual content.

[0899] "Virtual Content" refers to 3D models and other virtual objects generated by a generative AI model based on a user's ideas.

[0900] "Parameters" refer to various settings and attributes (e.g., color, shape, size, etc.) required to materialize a user's idea.

[0901] "3D Modeling Software" means software tools used to generate 3D models of Virtual Content.

[0902] "User terminal" refers to an electronic device (e.g., smartphone, tablet, PC) used by a user to input ideas and review and modify generated virtual content.

[0903] "Modification instructions" refer to requests for changes or improvements made by a user to the generated virtual content.

[0904] "Projecting into reality" refers to virtually displaying the generated virtual content in real space using an AR headset or smartphone.

[0905] To specifically implement the present invention, it is necessary to build a system in which a user, a terminal, and a server work together. In this system, a user inputs an idea, a server analyzes the idea, and generates virtual content using a generative AI model, which is then provided to the user via the terminal. Specific embodiments are described below.

[0906] User idea input

[0907] Using a dedicated application or web interface, users can enter textual ideas about the virtual content they want to create. For example, a user might enter a specific request, such as "I want to add a red sofa to my living room."

[0908] Sending and receiving ideas

[0909] The terminal receives the idea data entered by the user and transmits it to the server. At this time, basic information about the user (such as the user ID and location information) may also be attached along with the content of the idea.

[0910] Idea analysis and parameter extraction

[0911] The server analyzes the received idea data and extracts the necessary parameters to input into a generative AI model (for example, a general natural language processing AI model). Specifically, from the idea "I want to add a red sofa to my living room," the server identifies the keyword "red sofa" and determines the sofa's specific parameters, such as its size, shape, and color.

[0912] Virtual Content Generation

[0913] The server generates virtual content using a generative AI model based on the extracted parameters. For example, it generates a 3D model of a "red sofa" using 3D modeling software such as Blender or Maya. This 3D model is temporarily stored on the server.

[0914] Sending content to user devices

[0915] The generated virtual content is sent from the server to the user's device, which provides a user interface for displaying the received 3D model, allowing the user to view the model.

[0916] User confirmation and correction

[0917] The user can check the generated 3D model on their device. If they are dissatisfied with the generated content or if corrections are needed, they can input correction instructions through their device. For example, they can input specific correction instructions such as "I would like the color of the sofa to be a little darker."

[0918] Sending modifications to the server and regenerating

[0919] The device retransmits the user's correction instructions to the server, which then reuses the generative AI model based on the correction instructions and regenerates the virtual content.

[0920] Final confirmation and projection into reality

[0921] The revised virtual content is then sent back to the device from the server for final confirmation by the user. If the user is satisfied, the device projects the virtual content into real space using an AR headset or smartphone. For example, a life-size red sofa is virtually displayed in the user's living room.

[0922] Specific examples

[0923] Example 1: Adding furniture

[0924] The user types, "I want to add a red sofa to my living room," and the device sends this to the server. The server analyzes the idea, extracts the necessary parameters, and generates a 3D model of the "red sofa." The generated model is sent to the device, where the user can check it. If the user is satisfied, the device projects the sofa in life-size onto the living room.

[0925] Example 2: Adding a character

[0926] The user inputs "I want to add a barista character to the cafe scene," and the device sends this to the server. The server analyzes the data and generates a 3D model of the "barista character." The model is sent to the device, where the user can review, edit, and finalize the model, after which the barista character is projected onto the cafe scene.

[0927] Examples of prompt statements

[0928] Adding Furniture

[0929] "I would like to add a red sofa to my living room. The sofa should be 200cm wide, 90cm high, and 100cm deep. I would like it to be a dark red."

[0930] Adding characters

[0931] "I want to add a barista character to the cafe scene. The barista's outfit is a young man wearing an apron and a friendly smile."

[0932] Based on these prompts, the generative AI model can generate the desired VR / AR content, allowing users to easily generate VR / AR content and project it into the real world.

[0933] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0934] Step 1:

[0935] Users input their ideas using a dedicated application or web interface. They enter their ideas in text format in an input field, describing specific requests such as "I want to add a red sofa to my living room." The input data is the text information entered by the user. The output data is temporarily stored on the device.

[0936] Step 2:

[0937] The device sends the ideas entered by the user to the server. Specifically, it uses the REST API to send idea data to the server. At this time, basic information such as the user ID and timestamp is also sent. The input data consists of temporarily saved text information and basic information. This data is sent to the server as output.

[0938] Step 3:

[0939] The server analyzes the received ideas and extracts parameters to feed into the generative AI model. It uses a natural language processing API to analyze the text and identify important keywords such as "red sofa" and "living room." The input data is the text information sent. The output is the extracted parameters.

[0940] Step 4:

[0941] The server generates virtual content using a generative AI model based on the extracted parameters. Specifically, it generates a 3D model of a "red sofa" using 3D modeling software (e.g., Blender or Maya). The input data is the extracted parameters, such as "red sofa." The output is a 3D model based on these parameters.

[0942] Step 5:

[0943] The server sends the generated virtual content to the user's device. The generated 3D model file (e.g., .fbx format) is sent to the device via a REST API. The input data is the generated 3D model. The output is the model sent to the device.

[0944] Step 6:

[0945] The device provides a user interface to display the received 3D model, allowing the user to check the content. The input data is the transmitted 3D model. The output is the user's view of the 3D model through the interface.

[0946] Step 7:

[0947] The user checks the 3D model generated on the device, and if there are any complaints or corrections that need to be made, they can input correction instructions through the device. For example, they can write down specific requests for corrections, such as "I would like the color of the sofa to be a little darker." The input data is the correction instructions written by the user. As output, these instructions are temporarily saved on the device.

[0948] Step 8:

[0949] The device resubmits the user's correction instructions to the server. It again uses the REST API to send the correction instruction data to the server. The input data is the temporarily saved correction instructions. The output is this instruction sent to the server.

[0950] Step 9:

[0951] The server reuses the generative AI model based on the modification instructions to recreate the virtual content. It regenerates the 3D model based on new parameters (e.g., color changes). The input data are the parameters based on the modification instructions. The output is the modified 3D model.

[0952] Step 10:

[0953] The server resends the modified virtual content to the user's device. It sends the regenerated 3D model file to the device. The input data is the modified 3D model. The output data is sent to the device.

[0954] Step 11:

[0955] The user then checks the revised 3D model on the device again. If the user is satisfied, they can use the device to project the virtual content into real space via an AR headset or smartphone. The input data is the revised 3D model that was sent. The output is the virtual projection of this model into real space.

[0956] (Application example 1)

[0957] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0958] In conventional virtual object viewing systems, when users want to customize an object, they lack a mechanism to directly reflect their wishes, which reduces user satisfaction. In particular, the inability to easily customize the color, shape, and placement of an object limits the user experience.

[0959] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0960] In this invention, the server includes: means for a user to input an idea; means for receiving the idea and transmitting it to the server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; means for providing a user interface for customizing specifications of an item in a virtual space; and means for exploring the virtual space in real time and reflecting changes to the item. This allows users to freely customize the specifications of items in the virtual space, and the changes are reflected in real time, enabling a more satisfying user experience.

[0961] The "means for the user to input ideas" refers to a device that includes an interface that allows the user to provide specific requests or ideas to the system as text or voice input.

[0962] The "means for receiving the idea and transmitting it to the server" is a device including a communication means for receiving idea data input by the user and transmitting it to the server side.

[0963] "Means for analyzing the idea and extracting parameters to be input into the generative AI model" refers to a device that includes a process for analyzing received idea data and extracting specific parameters required by the generative AI model.

[0964] The "means for generating virtual content based on the parameters" is a device that includes a process for running a generative AI model using the extracted parameters to generate the specified virtual content.

[0965] The "means for transmitting the generated virtual content to a user terminal and accepting user confirmation and modification instructions" refers to a device that includes a communication means and an interface for transmitting the generated virtual content to a user terminal and accepting user confirmation and modification instructions.

[0966] The "means for regenerating virtual content based on the modification instructions" is a device that includes a process and a generation AI model for regenerating virtual content based on modification instructions from a user.

[0967] The "means for retransmitting the modified virtual content to the user terminal and projecting the final confirmed virtual content into reality" refers to a device for retransmitting the modified virtual content to the user terminal and projecting the final confirmed virtual content into a real environment.

[0968] The "means for providing a user interface for customizing the specifications of an item in a virtual space" is a device that provides a user interface for customizing the color, shape, placement, etc. of an item in a virtual space.

[0969] The "means for searching the virtual space in real time and reflecting changes to the item" is a device for reflecting changes to the item made by the user in real time while searching the virtual space.

[0970] To implement this invention, it is necessary to build a system using a server, a user terminal, and a generative AI model. A specific embodiment of this system will be described below.

[0971] Hardware and software used

[0972] Head-mounted display (HMD): For example, using a device such as Oculus Quest 2.

[0973] User interface: Virtual keyboard and voice interface to enter requests in text format.

[0974] Generative AI models: For example, OpenAI's DALL-E or Google DeepMind's Imagen.

[0975] Server system: Responsible for idea analysis and content generation on cloud servers (AWS, Google Cloud, etc.).

[0976] System operation flow

[0977] First, the user wears a head-mounted display and freely explores the virtual store. If the user becomes interested in a particular item during the exploration and wants to customize its color, shape, or placement, they can input their idea via text or voice. For example, they could say, "I want the color of this sofa to be changed to blue."

[0978] The user's device receives the idea and sends it to the server, which analyzes the idea and extracts parameters (product type, color, shape, etc.) for the generative AI model. Next, the generative AI model (e.g., DALL-E or Imagen) generates a customized item and creates its 3D model data.

[0979] The generated 3D model data is sent to the user's HMD in real time, and the new object model is immediately reflected in the virtual space. The user can review the changes and, if necessary, input any corrections.

[0980] Specific examples

[0981] For example, a user finds a sofa in a virtual store and requests, "I want the color of this sofa changed to blue." The request is sent to the server, which analyzes it and generates a 3D model of a new sofa using a generative AI model. The generated sofa is then displayed in the virtual store in real time for the user to review. By issuing further corrections as necessary, the user can finally experience the ideal product.

[0982] Examples of prompt statements

[0983] "I want this sofa changed to blue."

[0984] Move this table to the window.

[0985] Make this bed a little bigger

[0986] This allows users to freely customize the specifications of items in virtual space, and the changes are reflected in real time, allowing for a more satisfying user experience.

[0987] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0988] Step 1:

[0989] The user wears a head-mounted display and explores the virtual store. The input is the user's motion information and viewpoint information, and based on this information, the user interface displays the environment in real time. The output is display data of the virtual store.

[0990] Step 2:

[0991] The user inputs customization requests for a particular item by text or voice. The input is the user's text or voice customization requests, which are communicated to the user interface. The output is the user's customization request data.

[0992] Step 3:

[0993] The terminal receives this customization request data and sends it to the server. The input is the customization request data entered by the user, which is sent to the server using a communication means. The output is the transfer of the customization request data to the server.

[0994] Step 4:

[0995] The server analyzes the received customization request data and extracts parameters to be input into the generative AI model. The input is the customization request data, which is analyzed using natural language processing technology. The output is specific parameters to be input into the generative AI model (e.g., "blue sofa").

[0996] Step 5:

[0997] The server uses the extracted parameters to activate a generative AI model and generate virtual content. The input is the parameters required by the generative AI model, and a 3D model is generated using the generative AI model (e.g., DALL-E or Imagen). The output is the generated 3D model data.

[0998] Step 6:

[0999] The server sends the generated 3D model data to the user's device. The input is the generated 3D model data, which is then sent back to the user's device via a communication means. The output is the transfer of the 3D model data to the user's device.

[1000] Step 7:

[1001] The terminal reflects the received 3D model in the virtual store in real time and displays it to the user. The input is the received 3D model data, and the data is processed to be placed in the virtual space. The output is a display of customized items in the virtual store that the user can visually confirm.

[1002] Step 8:

[1003] The user checks the displayed 3D model and, if necessary, inputs any correction requests again by text or voice. The input is the user's correction request, which is again transmitted to the user interface. The output is the correction request data.

[1004] Step 9:

[1005] The terminal retransmits the requested modification data to the server, and the server retransmits the regenerated 3D model to the user terminal. The input is the requested modification data, which is analyzed and the regeneration AI model is activated. The output is a retransmission of the modified 3D model data.

[1006] Step 10:

[1007] The 3D model that the user has finalized is projected into reality. The input is the finalized 3D model data, which is used to process it for projection into real space. The output is the projection of the item customized in the virtual space into reality.

[1008] Through the above processing steps, this system enables users to easily customize items in a virtual space and check the changes in real time.

[1009] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1010] This invention relates to a system that generates VR / AR content based on a user's ideas and projects that content into real space. In particular, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide a more personalized experience. Specific embodiments are described below.

[1011] User idea input

[1012] Users access a dedicated application or web interface and input their ideas, such as "I want to add a red sofa to my living room" in text format.

[1013] Emotion Engine Operation

[1014] When a user inputs an idea, the device's built-in emotion engine automatically recognizes the user's emotional state. The emotion engine identifies the user's emotions by analyzing biometric information such as facial expressions, voice, and heart rate. For example, it uses a camera and microphone to analyze the emotions (surprise, joy, sadness, etc.) the user is feeling while inputting in real time.

[1015] Submitting ideas and emotional data

[1016] The device transmits the user's idea data and the emotion data recognized at that time to the server. The transmitted data includes details of the idea, the user's emotional state, and basic information (user ID, location information, etc.).

[1017] Idea and emotion data analysis

[1018] The server analyzes the received idea data and emotion data to extract parameters to be input into the generative AI model. Specific parameters such as color, shape, and size are identified based on the content of the idea. At the same time, the design and color of the content are adjusted based on the user's emotion data.

[1019] Virtual Content Generation

[1020] The server uses a generative AI model based on the extracted parameters to generate virtual content, for example, a 3D model of a "red sofa" that adjusts according to the user's emotional state (e.g., a rounded design if the user is relaxed).

[1021] Sending content and user confirmation

[1022] The generated virtual content is sent from the server to the terminal and displayed to the user. The user can check the generated content and input corrections as needed. For example, the user can input a request for correction, such as "I would like the color of the sofa to be a little darker."

[1023] Parsing and regenerating correction instructions

[1024] The device sends the user's correction instructions to the server, which then regenerates the content using the generative AI model based on the correction instructions and retransmits the corrected virtual content to the device.

[1025] Final confirmation and projection into reality

[1026] Once the user has finally confirmed and approved the content, it is projected into the real world via the device, where a life-size 3D model is displayed in the real world using an AR headset or smartphone.

[1027] Specific examples

[1028] Example 1: Adding furniture

[1029] The user inputs "I want to add a red sofa to my living room," and the device's emotion engine recognizes the user's relaxed emotion. The server generates a 3D model of a red sofa designed to reflect the feeling of relaxation and sends it to the device. After the user confirms and gives their final approval, the sofa is projected onto the living room.

[1030] Example 2: Adding a character

[1031] The user inputs "I want to add a barista character to the cafe scene," and the device's emotion engine recognizes the user's excited emotion. The server generates a 3D model of the barista character with lively movements and sends it to the device. After the user confirms, modifies, and gives final approval, the barista character is projected onto the cafe scene.

[1032] In this way, by taking the user's emotions into consideration when generating and projecting VR / AR content, we can provide a system that is more personalized and improves the user experience.

[1033] The processing flow will be explained below.

[1034] Step 1:

[1035] User: Accesses a specialized application or web interface and enters in text format the idea for the VR / AR content they want to realize. For example, they might enter a request such as, "I want to add a red sofa to my living room."

[1036] Step 2:

[1037] Terminal: The emotion engine is activated while the user is typing. The emotion engine analyzes the user's facial expressions and voice tone through a camera and microphone to recognize their emotional state. For example, it determines whether the user is relaxed.

[1038] Step 3:

[1039] The terminal sends the idea data entered by the user and the recognized emotion data to the server. The sent data includes details of the idea, the user's emotional state, and basic information (user ID, location, etc.).

[1040] Step 4:

[1041] Server: Receives idea data and emotion data sent from the device. Checks the received data and performs appropriate processing.

[1042] Step 5:

[1043] Server: Analyzes the received idea. Extracts the necessary parameters to input into the generative AI model and creates specific generation instructions. For example, for the idea of ​​a "red sofa," it identifies parameters such as color (red), size, shape, and material. At the same time, it adjusts the parameters based on the user's emotional data.

[1044] Step 6:

[1045] Server: Using the extracted parameters, the server uses a generative AI model to generate virtual content. For example, if the user is relaxing, it generates a soft red sofa.

[1046] Step 7:

[1047] Server: The server transmits the generated virtual content (3D model) to the terminal. The transmitted data includes the 3D model file and related metadata.

[1048] Step 8:

[1049] Terminal: Receives the 3D model data sent from the server and displays it to the user, allowing the user to check the generated content through a user interface.

[1050] Step 9:

[1051] User: Checks the generated 3D model and inputs correction instructions as necessary. For example, the user can input a request for correction such as "I would like the color of the sofa to be a little darker."

[1052] Step 10:

[1053] Terminal: Receives the user's correction instructions and sends them back to the server. The transmitted data includes details of the corrections.

[1054] Step 11:

[1055] Server: Receives correction instructions sent from the device and analyzes them again. Adjusts necessary parameters and regenerates the virtual content using the generative AI model.

[1056] Step 12:

[1057] Server: Retransmits the modified virtual content to the device, including data for final confirmation.

[1058] Step 13:

[1059] Terminal: The modified virtual content is displayed to the user, who then performs a final check and approves it if satisfied.

[1060] Step 14:

[1061] Device: The content that the user has finally approved is projected into the real world using an AR headset or smartphone. A life-size red sofa is virtually displayed in the living room.

[1062] Example 2

[1063] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1064] Conventional VR / AR content generation systems generate content without considering the user's emotions, making it difficult to provide a personalized experience for each user. Furthermore, because design and color are not adjusted according to the user's emotions, it is not possible to generate content that truly satisfies the user. This leads to issues such as a poor user experience and a decrease in the value of the system.

[1065] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1066] In this invention, the server includes: a means for a user to input an idea; a means for receiving the idea and transmitting it to the server; a means for acquiring emotion data using an emotion engine that recognizes the user's emotion; a means for transmitting the idea data and the emotion data to the server; a means for analyzing the idea and the emotion data and extracting parameters to be input into a generative AI model; a means for generating virtual content based on the parameters and the emotion data; a means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; a means for regenerating the virtual content based on the correction instructions; and a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality, thereby enabling the generation and projection of personalized VR / AR content according to the user's emotions.

[1067] "User" means an individual or organization that uses information devices or systems to input ideas and generate VR / AR content.

[1068] An "idea" is a concrete expression of instructions or requests input by a user, and includes, for example, adding furniture or arranging characters.

[1069] An "emotion engine" is a software or hardware system that analyzes a user's facial expressions, voice, and biometric information to recognize the user's emotional state in real time.

[1070] "Emotion data" is data that indicates the emotional state of the user analyzed by the emotion engine, and includes emotions such as surprise, joy, and sadness.

[1071] "Parameters" are specific settings or instructions extracted to be fed into a generative AI model, including color, shape, size, etc.

[1072] A "generative AI model" is an artificial intelligence system, such as a deep learning model, that generates VR / AR content based on input parameters.

[1073] "Virtual content" refers to 3D models and scenes generated by generative AI models, and is VR / AR content based on user ideas and emotional data.

[1074] "User device" means a device used by a user to input ideas and review and modify generated virtual content, including a smartphone or PC.

[1075] "Projecting into reality" refers to displaying the final confirmed virtual content in real space, using an AR headset or an AR app on a smartphone.

[1076] "Modification instructions" are requests for changes or adjustments made by the user to the generated virtual content.

[1077] This invention relates to a system that generates VR / AR content based on a user's ideas and projects that content into real space. In particular, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide a more personalized experience.

[1078] First, users access a dedicated application or web interface and enter their idea in text form, such as "I want to add a red sofa to my living room."

[1079] Next, as the user inputs their idea, the device's built-in emotion engine recognizes the user's emotional state in real time. The emotion engine uses a camera and microphone to analyze the user's facial expressions, voice, and biometric information (such as heart rate) to identify the user's current emotion. For example, if the user is relaxed, that emotional state is recognized.

[1080] The device transmits the user's idea data and emotion data to the server using a secure communication protocol. This data includes details of the idea, the user's emotional state, the user ID, and location information.

[1081] The server analyzes the received idea data and emotion data to extract parameters to be input into the generative AI model. Specifically, parameters such as color, shape, and size are identified. At the same time, the design and color of the content are adjusted based on the user's emotion data.

[1082] The server generates virtual content using a generative AI model based on the extracted parameters. For example, a "red sofa with a relaxing design" is created by the generative AI model. An example of a prompt sentence is "I want to add a red sofa to my living room. The user is in a relaxed state."

[1083] The generated virtual content is sent from the server to the device and displayed to the user. The user can check this content and input correction instructions (e.g., "I want the color of the sofa to be a little darker") if necessary.

[1084] The device sends correction instructions to the server, which then uses the generative AI model to generate the corrected virtual content and resends it to the device. Once the user has finally confirmed and approved the content, it is projected into real space via the device. This can be done using an AR headset or an AR app on a smartphone, and a life-size 3D model can be displayed in an environment such as a living room.

[1085] This system enables the generation and projection of personalized VR / AR content according to the user's emotions, improving the user experience. For example, if a user inputs "I want to add a red sofa to my living room" and the emotion engine recognizes the emotion of relaxation, the server will generate a red sofa with a design that reflects the feeling of relaxation and project it into the real world. As a result, the user will be able to enjoy a more satisfying experience.

[1086] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1087] Step 1:

[1088] Users access a dedicated application or web interface and enter their ideas in text format.

[1089] Input: A user-entered text idea (e.g., "I want to add a red sofa to my living room").

[1090] Data processing: Converting text input into digital data.

[1091] Output: The input idea data.

[1092] Specific operation: A user uses a text field in a smartphone or PC application to write down an idea.

[1093] Step 2:

[1094] When a user inputs an idea, the device's built-in emotion engine recognizes the user's emotional state in real time.

[1095] Input: User facial expressions, voice, and biometric information (heart rate, etc.) captured through cameras and microphones.

[1096] Data Processing: The emotion engine analyzes these raw data and identifies the emotional state (e.g., relaxed).

[1097] Output: Emotion data (e.g., relaxed state).

[1098] How it works: The device's camera captures the user's facial expressions, the microphone records their voice, and the emotion engine analyzes this data.

[1099] Step 3:

[1100] The terminal transmits the user's idea data and emotion data to the server using a secure communication protocol.

[1101] Input: Idea data, emotion data, and basic information such as user ID and location.

[1102] Data processing: Idea data and emotion data are packaged and encoded using security protocols.

[1103] Output: The packaged data that is sent to the server.

[1104] Specific operation: The device establishes network communication to send data to the server in bulk.

[1105] Step 4:

[1106] The server analyzes the received data and extracts parameters to be input into the generative AI model.

[1107] Input: Received idea and sentiment data.

[1108] Data processing: The server analyzes the idea data and extracts specific parameters such as color, shape, and size. It also adjusts the design and color based on the emotion data.

[1109] Output: Parameters to feed into a generative AI model.

[1110] Specific operation: The server uses a text analysis algorithm to analyze the content of the idea in detail and extract the necessary parameters.

[1111] Step 5:

[1112] The server generates virtual content using a generative AI model based on the extracted parameters.

[1113] Input: Extracted parameters and emotion data.

[1114] Data processing: Input parameters into the generative AI model to generate virtual content.

[1115] Output: The generated virtual content (e.g., a 3D model).

[1116] Specific operation: The generative AI model generates a 3D model based on the prompt text.

[1117] Step 6:

[1118] The generated virtual content is sent from the server to the terminal and displayed to the user, who then confirms it and inputs any necessary correction instructions.

[1119] Input: The generated virtual content.

[1120] Data processing: Converting content into a format suitable for the user's device.

[1121] Output: The virtual content displayed on the user's device.

[1122] Specific operation: The generated content is sent to the device, and the user inputs correction instructions such as "I would like the color of the sofa to be a little darker."

[1123] Step 7:

[1124] The device sends the user's correction instructions to the server, which then regenerates the virtual content using the generative AI model and resends the corrected virtual content to the device.

[1125] Input: User correction instructions.

[1126] Data processing: Analyze the correction instructions and input them back into the generative AI model.

[1127] Output: The modified virtual content.

[1128] Specific operation: The server retransmits the regenerated virtual content to the device.

[1129] Step 8:

[1130] Once the user has finally confirmed and approved the content, it is projected into the real world via the device.

[1131] Input: Final verified virtual content.

[1132] Data processing: Formatting virtual content to project it into real space.

[1133] Output: The content projected into reality by the AR device.

[1134] What it does: Using an AR headset or an AR app on a smartphone, a 3D model of the final approved red sofa is projected into the living room.

[1135] By performing detailed processing at each step, the system generates personalized VR / AR content based on the user's ideas and emotions, and projects it seamlessly into real space.

[1136] (Application example 2)

[1137] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1138] While conventional technologies could generate virtual content based on user-input ideas, they had the drawback of not being able to adjust the settings based on user emotions or dynamically adjust security device settings. This resulted in a uniform user experience, making it difficult to generate personalized and effective content or security settings.

[1139] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input an idea; means for receiving the idea and transmitting it to the server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; means for collecting user emotion data and adjusting the virtual content based on the emotion; and means for dynamically adjusting security device settings based on the emotion data. This enables personalized virtual content to be generated and projected into the real world based on the user's emotion, and further realizes dynamic adjustment of security devices according to the user's emotional state.

[1140] "User" refers to a person who uses the system to input ideas and review and modify the generated content.

[1141] An "idea" refers to a specific request or wish input by a user, and is information that serves as the basis for generating virtual content.

[1142] "Server" refers to a device that receives ideas and emotional data sent by users, analyzes and processes them, and generates and transmits virtual content.

[1143] A "generative AI model" refers to an artificial intelligence model that generates virtual content by inputting user ideas and emotional data.

[1144] "Virtual content" refers to 3D models and digital data generated based on users' ideas and emotional data.

[1145] A "user terminal" is a device used by a user to operate the system, and includes a smartphone, a head-mounted display, etc.

[1146] "Emotion data" refers to data that indicates the emotional state of a user analyzed from facial expressions, voice, biometric information, and the like.

[1147] "Security appliance" refers to a device for crime prevention or surveillance that adjusts its settings based on the user's emotional state.

[1148] "Dynamic adjustment" refers to automatically changing the settings and operation of security devices based on real-time user emotional data.

[1149] "Projection" refers to displaying the generated virtual content in the real world, using an AR headset or smartphone.

[1150] This invention is a system that generates virtual content based on a user's ideas and emotions, projects it into real space, and dynamically adjusts security equipment settings.

[1151] Hardware and software used

[1152] 1. User Device:

[1153] Hardware: Smartphones (e.g., iPhones, Android devices), AR headsets, etc.

[1154] Software: OpenCV (facial expression analysis), Google Cloud Speech-to-Text (voice analysis).

[1155] 2. Server:

[1156] Software: Emotion API (Microsoft Azure), Custom TensorFlow sentiment analysis model, Smart Camera API (security equipment control).

[1157] 3. Security equipment:

[1158] Hardware: Network-enabled security cameras (e.g., ARLO Pro, Nest Cam).

[1159] Invention Process Overview

[1160] 1. Inputting Idea and Emotion Data:

[1161] Users enter their ideas in text through a smartphone application, such as "I want to add a red sofa to my living room."

[1162] 2. Collecting Emotional Data:

[1163] Using the smartphone's camera and microphone, the system collects the user's facial expressions, voice, and biometric information (such as heart rate), and uses this data to analyze the user's emotions in real time.

[1164] 3. Sending ideas and emotional data:

[1165] The collected idea and emotion data is transmitted from the user terminal to a server.

[1166] 4. Data analysis and parameter extraction:

[1167] The server analyzes the received idea data and emotion data to extract input parameters for the generative AI model. For example, for a "red sofa," it identifies parameters related to color, shape, and size, and adjusts the design and color based on the emotion data.

[1168] 5. Virtual Content Generation:

[1169] The server uses the generative AI model to generate virtual content (e.g., a 3D model of a rounded red sofa that reflects the user's sense of relaxation).

[1170] 6. User confirmation and correction:

[1171] The generated virtual content is sent to the user terminal, where the user can check it. If necessary, the user can input correction instructions, such as "I want the color of the sofa to be a little darker."

[1172] 7. Regenerate correction instructions:

[1173] The modification instructions are sent back to the server, where they are regenerated using the generative AI model, and the modified virtual content is then sent back to the user device.

[1174] 8. Final confirmation and reality projection:

[1175] Once the user has finally confirmed and approved the virtual content, it is projected into the real world through the user's device and displayed in the real world using an AR headset or smartphone.

[1176] 9. Dynamically Adjust Security Devices:

[1177] Based on the user's emotional data, the settings of the security equipment are dynamically adjusted. For example, if the user feels anxious, the settings of the security camera are changed to widen the viewing angle and increase the recording sensitivity.

[1178] Examples and explanations of prompt sentences

[1179] Examples of prompts:

[1180] "When a user feels anxious, analyze their emotional data, widen the field of view of the security camera, and change the recording mode to high sensitivity."

[1181] This allows the system to generate personalized virtual content based on the user's emotions and dynamically adjust security devices according to their emotional state.

[1182] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1183] Step 1:

[1184] Users use a smartphone application to input their ideas, such as "I want to add a red sofa to my living room." This input becomes the initial data for the system.

[1185] Input: Text data of ideas

[1186] Output: Text data of ideas

[1187] Step 2:

[1188] The user device collects emotional data along with the input idea. Specifically, it uses the smartphone's camera and microphone to collect the user's facial expressions, voice, and biometric information (such as heart rate). OpenCV and Google Cloud Speech-to-Text are used to analyze and identify the user's emotional state.

[1189] Input: User's facial expression, voice, biometric information

[1190] Output: Emotion data (e.g., relaxed, anxious)

[1191] Step 3:

[1192] The device sends the collected idea data and emotion data to the server. Basic information such as the user ID and location information is also sent at the same time. The server receives this data and proceeds to the next processing step.

[1193] Input: idea data, emotion data, user ID, location information

[1194] Output: Send data to the server

[1195] Step 4:

[1196] The server analyzes the received idea data and emotion data to extract parameters to be fed into the generative AI model. These parameters include the color, shape, and size of the virtual content. The design and color are also adjusted based on the emotion data.

[1197] Input: idea data, emotion data

[1198] Output: Parameters to the generative AI model

[1199] Step 5:

[1200] The server generates virtual content using a generative AI model based on the extracted parameters. For example, for an idea like "add a red sofa to the living room," a 3D model of a rounded red sofa that reflects a relaxing feeling is generated.

[1201] Input: Parameters to the generative AI model

[1202] Output: Virtual content (3D model)

[1203] Step 6:

[1204] The server transmits the generated virtual content to the user terminal, which displays the content to the user and prompts the user to confirm the content, allowing the user to input correction instructions.

[1205] Input: Virtual content (3D model)

[1206] Output: Sending content to the user's device

[1207] Step 7:

[1208] The user checks the virtual content and inputs correction instructions as necessary, for example, "I would like the color of the sofa to be a little darker."

[1209] Input: Correction instructions (text data)

[1210] Output: Correction instruction data

[1211] Step 8:

[1212] The device transmits the user's correction instructions to the server, which then regenerates the virtual content using the generative AI model based on the correction instructions and retransmits the corrected virtual content to the device.

[1213] Input: Correction instruction data

[1214] Output: Modified virtual content (3D model)

[1215] Step 9:

[1216] Once the user has finally reviewed and approved the virtual content, it is projected into the real world, where a life-size 3D model is displayed in the real environment using an AR headset or smartphone.

[1217] Input: Final confirmed virtual content (3D model)

[1218] Output: Virtual content projected into real space

[1219] Step 10:

[1220] Dynamically adjust security device settings based on user emotional data. For example, if a user feels anxious, the security camera's viewing angle will be widened and the recording mode will be set to high sensitivity.

[1221] Input: Emotion data (anxiety)

[1222] Output: Dynamically adjusted security appliance configuration

[1223] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1224] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1225] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1226] [Fourth embodiment]

[1227] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1228] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1229] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1230] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1231] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1232] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1233] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1234] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1235] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1236] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1237] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1238] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1239] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1240] To specifically implement this invention, it is necessary to build a system in which a user, a terminal, and a server work together. In this system, a user inputs an idea, a server analyzes the idea, and generates VR / AR content using a generative AI model, which is then provided to the user through the terminal. Specific embodiments are described below.

[1241] User idea input

[1242] Users can use a dedicated application or web interface to input their ideas for the VR / AR content they want to create in text format. For example, a user can enter a specific request such as "I want to add a red sofa to my living room."

[1243] Submit an idea

[1244] The terminal receives the idea data entered by the user and transmits it to the server. At this time, basic information about the user (such as the user ID and location information) may also be attached along with the content of the idea.

[1245] Idea analysis and parameter extraction

[1246] The server analyzes the received idea data and extracts the necessary parameters to input into the generative AI model. For example, from the idea "I want to add a red sofa to my living room," the server identifies the keyword "red sofa" and determines the specific parameters of the sofa, such as its size, shape, and color.

[1247] Virtual Content Generation

[1248] The server generates virtual content using a generative AI model based on the extracted parameters. In this case, a 3D model of a "red sofa" is generated and temporarily stored on the server.

[1249] Sending content to user devices

[1250] The generated virtual content is sent from the server to the user's device, which provides a user interface for displaying the received 3D model, allowing the user to confirm the content.

[1251] User confirmation and correction

[1252] The device displays the generated 3D model or AR object, and the user can check its contents. If the user is dissatisfied with the generated content or if corrections are required, the user can input correction instructions through the device. For example, "I would like the color of the sofa to be a little darker."

[1253] Sending modifications to the server

[1254] The device retransmits the user's correction instructions to the server, which then reuses the generative AI model based on the correction instructions and regenerates the content.

[1255] Final confirmation and projection into reality

[1256] The revised virtual content is then sent back to the device from the server for final confirmation by the user. If the user is satisfied, the device projects the virtual content into real space using an AR headset or smartphone. For example, a life-size red sofa is virtually displayed in the user's living room.

[1257] Specific examples

[1258] Example 1: Adding furniture

[1259] A user types, "I want to add a red sofa to my living room," and the device sends this idea to the server. The server analyzes the idea and generates a 3D model of the "red sofa." The generated model is sent to the device, where the user can review it. If the user is satisfied, the device projects the sofa in life-size onto the living room.

[1260] Example 2: Adding a character

[1261] The user types, "I want to add a barista character to the cafe scene," and the device sends the idea to the server. The server analyzes the idea and generates a 3D model of the "barista character." The model is then sent to the device, where the user can review, edit, and finalize the model, after which the barista character is projected onto the cafe scene.

[1262] In this way, the present invention allows users to easily generate VR / AR content and project it into real space, accelerating creative projects and making it easier for general users to share virtual experiences.

[1263] The processing flow will be explained below.

[1264] Step 1:

[1265] User: Accesses a dedicated application or web interface and enters in text format the idea for the VR / AR content they want to realize. For example, they might enter a request such as, "I want to add a red sofa to my living room."

[1266] Step 2:

[1267] Terminal: Receives idea data entered by the user. The received data includes details of the idea and basic information of the user (ID, location information, etc.).

[1268] Step 3:

[1269] The terminal transmits the received idea data to the server. The transmitted data includes the content of the idea entered by the user and any accompanying information.

[1270] Step 4:

[1271] Server: Receives idea data sent from the terminal, checks the received data, and performs appropriate processing.

[1272] Step 5:

[1273] Server: Analyzes the received ideas. Extracts parameters to be input into the generative AI model and creates specific generation instructions. For example, for the idea of ​​a "red sofa," it identifies parameters such as color (red), size, shape, and material.

[1274] Step 6:

[1275] Server: Using the extracted parameters, a generative AI model is used to generate virtual content. Specifically, a 3D model of a "red sofa" is automatically created.

[1276] Step 7:

[1277] Server: The server sends the generated virtual content (3D model) to the device. The sent data includes the 3D model file and related metadata.

[1278] Step 8:

[1279] Terminal: Receives the 3D model data sent from the server and displays it to the user, allowing the user to check the generated content through a user interface.

[1280] Step 9:

[1281] User: Checks the generated 3D model and inputs corrections as necessary. For example, the user may request that the color of the sofa be made a little darker.

[1282] Step 10:

[1283] Terminal: Receives the user's correction instructions and sends them back to the server. The transmitted data includes details of the corrections.

[1284] Step 11:

[1285] Server: Receives correction instructions sent from the device and analyzes them again. Adjusts necessary parameters and regenerates the content using the generative AI model.

[1286] Step 12:

[1287] Server: Retransmits the modified virtual content to the device, including data for final confirmation.

[1288] Step 13:

[1289] Terminal: The modified virtual content is displayed to the user, who then performs a final check and approves it if satisfied.

[1290] Step 14:

[1291] Device: The content that the user has finally approved is projected into the real world using an AR headset or smartphone. A life-size red sofa is virtually displayed in the living room.

[1292] Example 1

[1293] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1294] In conventional VR / AR content generation systems, even if a user inputs a specific idea, it is difficult to generate virtual content that accurately reflects that idea. Furthermore, there is a lack of effective means for modifying and finalizing the generated virtual content, making it difficult to easily create content that satisfies the user. The present invention solves these problems by providing a system that generates highly accurate VR / AR content based on an idea input by a user, and that allows modification and finalization to be performed quickly and easily.

[1295] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1296] In this invention, the server includes: a means for a user to input an idea; a means for receiving the idea and transmitting it to the server; a means for analyzing the idea and extracting parameters to be input into a generative AI model; a means for generating virtual content based on the parameters; a means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; a means for regenerating the virtual content based on the correction instructions; a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; a means for generating the virtual content using 3D modeling software; and a means for projecting the final confirmed virtual content into real space using an AR headset or a smartphone. This enables quick and easy generation, modification, and final confirmation of virtual content that accurately reflects the idea input by the user.

[1297] "User" refers to a person who uses the system to input ideas and review and modify generated content.

[1298] "Ideas" refer to specific requests and creative ideas about the VR / AR content that users want to realize.

[1299] "Server" refers to the computer system utilized to analyze user-submitted ideas and generate, modify, and retransmit virtual content.

[1300] "Generative AI model" refers to an artificial intelligence model used to extract and generate appropriate parameters based on a user's ideas and create virtual content.

[1301] "Virtual Content" refers to 3D models and other virtual objects generated by a generative AI model based on a user's ideas.

[1302] "Parameters" refer to various settings and attributes (e.g., color, shape, size, etc.) required to materialize a user's idea.

[1303] "3D Modeling Software" means software tools used to generate 3D models of Virtual Content.

[1304] "User terminal" refers to an electronic device (e.g., smartphone, tablet, PC) used by a user to input ideas and review and modify generated virtual content.

[1305] "Modification instructions" refer to requests for changes or improvements made by a user to the generated virtual content.

[1306] "Projecting into reality" refers to virtually displaying the generated virtual content in real space using an AR headset or smartphone.

[1307] To specifically implement the present invention, it is necessary to build a system in which a user, a terminal, and a server work together. In this system, a user inputs an idea, a server analyzes the idea, and generates virtual content using a generative AI model, which is then provided to the user via the terminal. Specific embodiments are described below.

[1308] User idea input

[1309] Using a dedicated application or web interface, users can enter textual ideas about the virtual content they want to create. For example, a user might enter a specific request, such as "I want to add a red sofa to my living room."

[1310] Sending and receiving ideas

[1311] The terminal receives the idea data entered by the user and transmits it to the server. At this time, basic information about the user (such as the user ID and location information) may also be attached along with the content of the idea.

[1312] Idea analysis and parameter extraction

[1313] The server analyzes the received idea data and extracts the necessary parameters to input into a generative AI model (for example, a general natural language processing AI model). Specifically, from the idea "I want to add a red sofa to my living room," the server identifies the keyword "red sofa" and determines the sofa's specific parameters, such as its size, shape, and color.

[1314] Virtual Content Generation

[1315] The server generates virtual content using a generative AI model based on the extracted parameters. For example, it generates a 3D model of a "red sofa" using 3D modeling software such as Blender or Maya. This 3D model is temporarily stored on the server.

[1316] Sending content to user devices

[1317] The generated virtual content is sent from the server to the user's device, which provides a user interface for displaying the received 3D model, allowing the user to view the model.

[1318] User confirmation and correction

[1319] The user can check the generated 3D model on their device. If they are dissatisfied with the generated content or if corrections are needed, they can input correction instructions through their device. For example, they can input specific correction instructions such as "I would like the color of the sofa to be a little darker."

[1320] Sending modifications to the server and regenerating

[1321] The device retransmits the user's correction instructions to the server, which then reuses the generative AI model based on the correction instructions and regenerates the virtual content.

[1322] Final confirmation and projection into reality

[1323] The revised virtual content is then sent back to the device from the server for final confirmation by the user. If the user is satisfied, the device projects the virtual content into real space using an AR headset or smartphone. For example, a life-size red sofa is virtually displayed in the user's living room.

[1324] Specific examples

[1325] Example 1: Adding furniture

[1326] The user types, "I want to add a red sofa to my living room," and the device sends this to the server. The server analyzes the idea, extracts the necessary parameters, and generates a 3D model of the "red sofa." The generated model is sent to the device, where the user can check it. If the user is satisfied, the device projects the sofa in life-size onto the living room.

[1327] Example 2: Adding a character

[1328] The user inputs "I want to add a barista character to the cafe scene," and the device sends this to the server. The server analyzes the data and generates a 3D model of the "barista character." The model is sent to the device, where the user can review, edit, and finalize the model, after which the barista character is projected onto the cafe scene.

[1329] Examples of prompt statements

[1330] Adding Furniture

[1331] "I would like to add a red sofa to my living room. The sofa should be 200cm wide, 90cm high, and 100cm deep. I would like it to be a dark red."

[1332] Adding characters

[1333] "I want to add a barista character to the cafe scene. The barista's outfit is a young man wearing an apron and a friendly smile."

[1334] Based on these prompts, the generative AI model can generate the desired VR / AR content, allowing users to easily generate VR / AR content and project it into the real world.

[1335] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1336] Step 1:

[1337] Users input their ideas using a dedicated application or web interface. They enter their ideas in text format in an input field, describing specific requests such as "I want to add a red sofa to my living room." The input data is the text information entered by the user. The output data is temporarily stored on the device.

[1338] Step 2:

[1339] The device sends the ideas entered by the user to the server. Specifically, it uses the REST API to send idea data to the server. At this time, basic information such as the user ID and timestamp is also sent. The input data consists of temporarily saved text information and basic information. This data is sent to the server as output.

[1340] Step 3:

[1341] The server analyzes the received ideas and extracts parameters to feed into the generative AI model. It uses a natural language processing API to analyze the text and identify important keywords such as "red sofa" and "living room." The input data is the text information sent. The output is the extracted parameters.

[1342] Step 4:

[1343] The server generates virtual content using a generative AI model based on the extracted parameters. Specifically, it generates a 3D model of a "red sofa" using 3D modeling software (e.g., Blender or Maya). The input data is the extracted parameters, such as "red sofa." The output is a 3D model based on these parameters.

[1344] Step 5:

[1345] The server sends the generated virtual content to the user's device. The generated 3D model file (e.g., .fbx format) is sent to the device via a REST API. The input data is the generated 3D model. The output is the model sent to the device.

[1346] Step 6:

[1347] The device provides a user interface to display the received 3D model, allowing the user to check the content. The input data is the transmitted 3D model. The output is the user's view of the 3D model through the interface.

[1348] Step 7:

[1349] The user checks the 3D model generated on the device, and if there are any complaints or corrections that need to be made, they can input correction instructions through the device. For example, they can write down specific requests for corrections, such as "I would like the color of the sofa to be a little darker." The input data is the correction instructions written by the user. As output, these instructions are temporarily saved on the device.

[1350] Step 8:

[1351] The device resubmits the user's correction instructions to the server. It again uses the REST API to send the correction instruction data to the server. The input data is the temporarily saved correction instructions. The output is this instruction sent to the server.

[1352] Step 9:

[1353] The server reuses the generative AI model based on the modification instructions to recreate the virtual content. It regenerates the 3D model based on new parameters (e.g., color changes). The input data are the parameters based on the modification instructions. The output is the modified 3D model.

[1354] Step 10:

[1355] The server resends the modified virtual content to the user's device. It sends the regenerated 3D model file to the device. The input data is the modified 3D model. The output data is sent to the device.

[1356] Step 11:

[1357] The user then checks the revised 3D model on the device again. If the user is satisfied, they can use the device to project the virtual content into real space via an AR headset or smartphone. The input data is the revised 3D model that was sent. The output is the virtual projection of this model into real space.

[1358] (Application example 1)

[1359] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1360] In conventional virtual object viewing systems, when users want to customize an object, they lack a mechanism to directly reflect their wishes, which reduces user satisfaction. In particular, the inability to easily customize the color, shape, and placement of an object limits the user experience.

[1361] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1362] In this invention, the server includes: means for a user to input an idea; means for receiving the idea and transmitting it to the server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; means for providing a user interface for customizing specifications of an item in a virtual space; and means for exploring the virtual space in real time and reflecting changes to the item. This allows users to freely customize the specifications of items in the virtual space, and the changes are reflected in real time, enabling a more satisfying user experience.

[1363] The "means for the user to input ideas" refers to a device that includes an interface that allows the user to provide specific requests or ideas to the system as text or voice input.

[1364] The "means for receiving the idea and transmitting it to the server" is a device including a communication means for receiving idea data input by the user and transmitting it to the server side.

[1365] "Means for analyzing the idea and extracting parameters to be input into the generative AI model" refers to a device that includes a process for analyzing received idea data and extracting specific parameters required by the generative AI model.

[1366] The "means for generating virtual content based on the parameters" is a device that includes a process for running a generative AI model using the extracted parameters to generate the specified virtual content.

[1367] The "means for transmitting the generated virtual content to a user terminal and accepting user confirmation and modification instructions" refers to a device that includes a communication means and an interface for transmitting the generated virtual content to a user terminal and accepting user confirmation and modification instructions.

[1368] The "means for regenerating virtual content based on the modification instructions" is a device that includes a process and a generation AI model for regenerating virtual content based on modification instructions from a user.

[1369] The "means for retransmitting the modified virtual content to the user terminal and projecting the final confirmed virtual content into reality" refers to a device for retransmitting the modified virtual content to the user terminal and projecting the final confirmed virtual content into a real environment.

[1370] The "means for providing a user interface for customizing the specifications of an item in a virtual space" is a device that provides a user interface for customizing the color, shape, placement, etc. of an item in a virtual space.

[1371] The "means for searching the virtual space in real time and reflecting changes to the item" is a device for reflecting changes to the item made by the user in real time while searching the virtual space.

[1372] To implement this invention, it is necessary to build a system using a server, a user terminal, and a generative AI model. A specific embodiment of this system will be described below.

[1373] Hardware and software used

[1374] Head-mounted display (HMD): For example, using a device such as Oculus Quest 2.

[1375] User interface: Virtual keyboard and voice interface to enter requests in text format.

[1376] Generative AI models: For example, OpenAI's DALL-E or Google DeepMind's Imagen.

[1377] Server system: Responsible for idea analysis and content generation on cloud servers (AWS, Google Cloud, etc.).

[1378] System operation flow

[1379] First, the user wears a head-mounted display and freely explores the virtual store. If the user becomes interested in a particular item during the exploration and wants to customize its color, shape, or placement, they can input their idea via text or voice. For example, they could say, "I want the color of this sofa to be changed to blue."

[1380] The user's device receives the idea and sends it to the server, which analyzes the idea and extracts parameters (product type, color, shape, etc.) for the generative AI model. Next, the generative AI model (e.g., DALL-E or Imagen) generates a customized item and creates its 3D model data.

[1381] The generated 3D model data is sent to the user's HMD in real time, and the new object model is immediately reflected in the virtual space. The user can review the changes and, if necessary, input any corrections.

[1382] Specific examples

[1383] For example, a user finds a sofa in a virtual store and requests, "I want the color of this sofa changed to blue." The request is sent to the server, which analyzes it and generates a 3D model of a new sofa using a generative AI model. The generated sofa is then displayed in the virtual store in real time for the user to review. By issuing further corrections as necessary, the user can finally experience the ideal product.

[1384] Examples of prompt statements

[1385] "I want this sofa changed to blue."

[1386] Move this table to the window.

[1387] Make this bed a little bigger

[1388] This allows users to freely customize the specifications of items in virtual space, and the changes are reflected in real time, allowing for a more satisfying user experience.

[1389] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1390] Step 1:

[1391] The user wears a head-mounted display and explores the virtual store. The input is the user's motion information and viewpoint information, and based on this information, the user interface displays the environment in real time. The output is display data of the virtual store.

[1392] Step 2:

[1393] The user inputs customization requests for a particular item by text or voice. The input is the user's text or voice customization requests, which are communicated to the user interface. The output is the user's customization request data.

[1394] Step 3:

[1395] The terminal receives this customization request data and sends it to the server. The input is the customization request data entered by the user, which is sent to the server using a communication means. The output is the transfer of the customization request data to the server.

[1396] Step 4:

[1397] The server analyzes the received customization request data and extracts parameters to be input into the generative AI model. The input is the customization request data, which is analyzed using natural language processing technology. The output is specific parameters to be input into the generative AI model (e.g., "blue sofa").

[1398] Step 5:

[1399] The server uses the extracted parameters to activate a generative AI model and generate virtual content. The input is the parameters required by the generative AI model, and a 3D model is generated using the generative AI model (e.g., DALL-E or Imagen). The output is the generated 3D model data.

[1400] Step 6:

[1401] The server sends the generated 3D model data to the user's device. The input is the generated 3D model data, which is then sent back to the user's device via a communication means. The output is the transfer of the 3D model data to the user's device.

[1402] Step 7:

[1403] The terminal reflects the received 3D model in the virtual store in real time and displays it to the user. The input is the received 3D model data, and the data is processed to be placed in the virtual space. The output is a display of customized items in the virtual store that the user can visually confirm.

[1404] Step 8:

[1405] The user checks the displayed 3D model and, if necessary, inputs any correction requests again by text or voice. The input is the user's correction request, which is again transmitted to the user interface. The output is the correction request data.

[1406] Step 9:

[1407] The terminal retransmits the requested modification data to the server, and the server retransmits the regenerated 3D model to the user terminal. The input is the requested modification data, which is analyzed and the regeneration AI model is activated. The output is a retransmission of the modified 3D model data.

[1408] Step 10:

[1409] The 3D model that the user has finalized is projected into reality. The input is the finalized 3D model data, which is used to process it for projection into real space. The output is the projection of the item customized in the virtual space into reality.

[1410] Through the above processing steps, this system enables users to easily customize items in a virtual space and check the changes in real time.

[1411] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1412] This invention relates to a system that generates VR / AR content based on a user's ideas and projects that content into real space. In particular, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide a more personalized experience. Specific embodiments are described below.

[1413] User idea input

[1414] Users access a dedicated application or web interface and input their ideas, such as "I want to add a red sofa to my living room" in text format.

[1415] Emotion Engine Operation

[1416] When a user inputs an idea, the device's built-in emotion engine automatically recognizes the user's emotional state. The emotion engine identifies the user's emotions by analyzing biometric information such as facial expressions, voice, and heart rate. For example, it uses a camera and microphone to analyze the emotions (surprise, joy, sadness, etc.) the user is feeling while inputting in real time.

[1417] Submitting ideas and emotional data

[1418] The device transmits the user's idea data and the emotion data recognized at that time to the server. The transmitted data includes details of the idea, the user's emotional state, and basic information (user ID, location information, etc.).

[1419] Idea and emotion data analysis

[1420] The server analyzes the received idea data and emotion data to extract parameters to be input into the generative AI model. Specific parameters such as color, shape, and size are identified based on the content of the idea. At the same time, the design and color of the content are adjusted based on the user's emotion data.

[1421] Virtual Content Generation

[1422] The server uses a generative AI model based on the extracted parameters to generate virtual content, for example, a 3D model of a "red sofa" that adjusts according to the user's emotional state (e.g., a rounded design if the user is relaxed).

[1423] Sending content and user confirmation

[1424] The generated virtual content is sent from the server to the terminal and displayed to the user. The user can check the generated content and input corrections as needed. For example, the user can input a request for correction, such as "I would like the color of the sofa to be a little darker."

[1425] Parsing and regenerating correction instructions

[1426] The device sends the user's correction instructions to the server, which then regenerates the content using the generative AI model based on the correction instructions and retransmits the corrected virtual content to the device.

[1427] Final confirmation and projection into reality

[1428] Once the user has finally confirmed and approved the content, it is projected into the real world via the device, where a life-size 3D model is displayed in the real world using an AR headset or smartphone.

[1429] Specific examples

[1430] Example 1: Adding furniture

[1431] The user inputs "I want to add a red sofa to my living room," and the device's emotion engine recognizes the user's relaxed emotion. The server generates a 3D model of a red sofa designed to reflect the feeling of relaxation and sends it to the device. After the user confirms and gives their final approval, the sofa is projected onto the living room.

[1432] Example 2: Adding a character

[1433] The user inputs "I want to add a barista character to the cafe scene," and the device's emotion engine recognizes the user's excited emotion. The server generates a 3D model of the barista character with lively movements and sends it to the device. After the user confirms, modifies, and gives final approval, the barista character is projected onto the cafe scene.

[1434] In this way, by taking the user's emotions into consideration when generating and projecting VR / AR content, we can provide a system that is more personalized and improves the user experience.

[1435] The processing flow will be explained below.

[1436] Step 1:

[1437] User: Accesses a specialized application or web interface and enters in text format the idea for the VR / AR content they want to realize. For example, they might enter a request such as, "I want to add a red sofa to my living room."

[1438] Step 2:

[1439] Terminal: The emotion engine is activated while the user is typing. The emotion engine analyzes the user's facial expressions and voice tone through a camera and microphone to recognize their emotional state. For example, it determines whether the user is relaxed.

[1440] Step 3:

[1441] The terminal sends the idea data entered by the user and the recognized emotion data to the server. The sent data includes details of the idea, the user's emotional state, and basic information (user ID, location, etc.).

[1442] Step 4:

[1443] Server: Receives idea data and emotion data sent from the device. Checks the received data and performs appropriate processing.

[1444] Step 5:

[1445] Server: Analyzes the received idea. Extracts the necessary parameters to input into the generative AI model and creates specific generation instructions. For example, for the idea of ​​a "red sofa," it identifies parameters such as color (red), size, shape, and material. At the same time, it adjusts the parameters based on the user's emotional data.

[1446] Step 6:

[1447] Server: Using the extracted parameters, the server uses a generative AI model to generate virtual content. For example, if the user is relaxing, it generates a soft red sofa.

[1448] Step 7:

[1449] Server: The server transmits the generated virtual content (3D model) to the terminal. The transmitted data includes the 3D model file and related metadata.

[1450] Step 8:

[1451] Terminal: Receives the 3D model data sent from the server and displays it to the user, allowing the user to check the generated content through a user interface.

[1452] Step 9:

[1453] User: Checks the generated 3D model and inputs correction instructions as necessary. For example, the user can input a request for correction such as "I would like the color of the sofa to be a little darker."

[1454] Step 10:

[1455] Terminal: Receives the user's correction instructions and sends them back to the server. The transmitted data includes details of the corrections.

[1456] Step 11:

[1457] Server: Receives correction instructions sent from the device and analyzes them again. Adjusts necessary parameters and regenerates the virtual content using the generative AI model.

[1458] Step 12:

[1459] Server: Retransmits the modified virtual content to the device, including data for final confirmation.

[1460] Step 13:

[1461] Terminal: The modified virtual content is displayed to the user, who then performs a final check and approves it if satisfied.

[1462] Step 14:

[1463] Device: The content that the user has finally approved is projected into the real world using an AR headset or smartphone. A life-size red sofa is virtually displayed in the living room.

[1464] Example 2

[1465] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1466] Conventional VR / AR content generation systems generate content without considering the user's emotions, making it difficult to provide a personalized experience for each user. Furthermore, because design and color are not adjusted according to the user's emotions, it is not possible to generate content that truly satisfies the user. This leads to issues such as a poor user experience and a decrease in the value of the system.

[1467] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1468] In this invention, the server includes: a means for a user to input an idea; a means for receiving the idea and transmitting it to the server; a means for acquiring emotion data using an emotion engine that recognizes the user's emotion; a means for transmitting the idea data and the emotion data to the server; a means for analyzing the idea and the emotion data and extracting parameters to be input into a generative AI model; a means for generating virtual content based on the parameters and the emotion data; a means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; a means for regenerating the virtual content based on the correction instructions; and a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality, thereby enabling the generation and projection of personalized VR / AR content according to the user's emotions.

[1469] "User" means an individual or organization that uses information devices or systems to input ideas and generate VR / AR content.

[1470] An "idea" is a concrete expression of instructions or requests input by a user, and includes, for example, adding furniture or arranging characters.

[1471] An "emotion engine" is a software or hardware system that analyzes a user's facial expressions, voice, and biometric information to recognize the user's emotional state in real time.

[1472] "Emotion data" is data that indicates the emotional state of the user analyzed by the emotion engine, and includes emotions such as surprise, joy, and sadness.

[1473] "Parameters" are specific settings or instructions extracted to be fed into a generative AI model, including color, shape, size, etc.

[1474] A "generative AI model" is an artificial intelligence system, such as a deep learning model, that generates VR / AR content based on input parameters.

[1475] "Virtual content" refers to 3D models and scenes generated by generative AI models, and is VR / AR content based on user ideas and emotional data.

[1476] "User device" means a device used by a user to input ideas and review and modify generated virtual content, including a smartphone or PC.

[1477] "Projecting into reality" refers to displaying the final confirmed virtual content in real space, using an AR headset or an AR app on a smartphone.

[1478] "Modification instructions" are requests for changes or adjustments made by the user to the generated virtual content.

[1479] This invention relates to a system that generates VR / AR content based on a user's ideas and projects that content into real space. In particular, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide a more personalized experience.

[1480] First, users access a dedicated application or web interface and enter their idea in text form, such as "I want to add a red sofa to my living room."

[1481] Next, as the user inputs their idea, the device's built-in emotion engine recognizes the user's emotional state in real time. The emotion engine uses a camera and microphone to analyze the user's facial expressions, voice, and biometric information (such as heart rate) to identify the user's current emotion. For example, if the user is relaxed, that emotional state is recognized.

[1482] The device transmits the user's idea data and emotion data to the server using a secure communication protocol. This data includes details of the idea, the user's emotional state, the user ID, and location information.

[1483] The server analyzes the received idea data and emotion data to extract parameters to be input into the generative AI model. Specifically, parameters such as color, shape, and size are identified. At the same time, the design and color of the content are adjusted based on the user's emotion data.

[1484] The server generates virtual content using a generative AI model based on the extracted parameters. For example, a "red sofa with a relaxing design" is created by the generative AI model. An example of a prompt sentence is "I want to add a red sofa to my living room. The user is in a relaxed state."

[1485] The generated virtual content is sent from the server to the device and displayed to the user. The user can check this content and input correction instructions (e.g., "I want the color of the sofa to be a little darker") if necessary.

[1486] The device sends correction instructions to the server, which then uses the generative AI model to generate the corrected virtual content and resends it to the device. Once the user has finally confirmed and approved the content, it is projected into real space via the device. This can be done using an AR headset or an AR app on a smartphone, and a life-size 3D model can be displayed in an environment such as a living room.

[1487] This system enables the generation and projection of personalized VR / AR content according to the user's emotions, improving the user experience. For example, if a user inputs "I want to add a red sofa to my living room" and the emotion engine recognizes the emotion of relaxation, the server will generate a red sofa with a design that reflects the feeling of relaxation and project it into the real world. As a result, the user will be able to enjoy a more satisfying experience.

[1488] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1489] Step 1:

[1490] Users access a dedicated application or web interface and enter their ideas in text format.

[1491] Input: A user-entered text idea (e.g., "I want to add a red sofa to my living room").

[1492] Data processing: Converting text input into digital data.

[1493] Output: The input idea data.

[1494] Specific operation: A user uses a text field in a smartphone or PC application to write down an idea.

[1495] Step 2:

[1496] When a user inputs an idea, the device's built-in emotion engine recognizes the user's emotional state in real time.

[1497] Input: User facial expressions, voice, and biometric information (heart rate, etc.) captured through cameras and microphones.

[1498] Data Processing: The emotion engine analyzes these raw data and identifies the emotional state (e.g., relaxed).

[1499] Output: Emotion data (e.g., relaxed state).

[1500] How it works: The device's camera captures the user's facial expressions, the microphone records their voice, and the emotion engine analyzes this data.

[1501] Step 3:

[1502] The terminal transmits the user's idea data and emotion data to the server using a secure communication protocol.

[1503] Input: Idea data, emotion data, and basic information such as user ID and location.

[1504] Data processing: Idea data and emotion data are packaged and encoded using security protocols.

[1505] Output: The packaged data that is sent to the server.

[1506] Specific operation: The device establishes network communication to send data to the server in bulk.

[1507] Step 4:

[1508] The server analyzes the received data and extracts parameters to be input into the generative AI model.

[1509] Input: Received idea and sentiment data.

[1510] Data processing: The server analyzes the idea data and extracts specific parameters such as color, shape, and size. It also adjusts the design and color based on the emotion data.

[1511] Output: Parameters to feed into a generative AI model.

[1512] Specific operation: The server uses a text analysis algorithm to analyze the content of the idea in detail and extract the necessary parameters.

[1513] Step 5:

[1514] The server generates virtual content using a generative AI model based on the extracted parameters.

[1515] Input: Extracted parameters and emotion data.

[1516] Data processing: Input parameters into the generative AI model to generate virtual content.

[1517] Output: The generated virtual content (e.g., a 3D model).

[1518] Specific operation: The generative AI model generates a 3D model based on the prompt text.

[1519] Step 6:

[1520] The generated virtual content is sent from the server to the terminal and displayed to the user, who then confirms it and inputs any necessary correction instructions.

[1521] Input: The generated virtual content.

[1522] Data processing: Converting content into a format suitable for the user's device.

[1523] Output: The virtual content displayed on the user's device.

[1524] Specific operation: The generated content is sent to the device, and the user inputs correction instructions such as "I would like the color of the sofa to be a little darker."

[1525] Step 7:

[1526] The device sends the user's correction instructions to the server, which then regenerates the virtual content using the generative AI model and resends the corrected virtual content to the device.

[1527] Input: User correction instructions.

[1528] Data processing: Analyze the correction instructions and input them back into the generative AI model.

[1529] Output: The modified virtual content.

[1530] Specific operation: The server retransmits the regenerated virtual content to the device.

[1531] Step 8:

[1532] Once the user has finally confirmed and approved the content, it is projected into the real world via the device.

[1533] Input: Final verified virtual content.

[1534] Data processing: Formatting virtual content to project it into real space.

[1535] Output: The content projected into reality by the AR device.

[1536] What it does: Using an AR headset or an AR app on a smartphone, a 3D model of the final approved red sofa is projected into the living room.

[1537] By performing detailed processing at each step, the system generates personalized VR / AR content based on the user's ideas and emotions, and projects it seamlessly into real space.

[1538] (Application example 2)

[1539] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1540] While conventional technologies could generate virtual content based on user-input ideas, they had the drawback of not being able to adjust the settings based on user emotions or dynamically adjust security device settings. This resulted in a uniform user experience, making it difficult to generate personalized and effective content or security settings.

[1541] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input an idea; means for receiving the idea and transmitting it to the server; means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting user confirmation and correction instructions; means for regenerating the virtual content based on the correction instructions; means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; means for collecting user emotion data and adjusting the virtual content based on the emotion; and means for dynamically adjusting security device settings based on the emotion data. This enables personalized virtual content to be generated and projected into the real world based on the user's emotion, and further realizes dynamic adjustment of security devices according to the user's emotional state.

[1542] "User" refers to a person who uses the system to input ideas and review and modify the generated content.

[1543] An "idea" refers to a specific request or wish input by a user, and is information that serves as the basis for generating virtual content.

[1544] "Server" refers to a device that receives ideas and emotional data sent by users, analyzes and processes them, and generates and transmits virtual content.

[1545] A "generative AI model" refers to an artificial intelligence model that generates virtual content by inputting user ideas and emotional data.

[1546] "Virtual content" refers to 3D models and digital data generated based on users' ideas and emotional data.

[1547] A "user terminal" is a device used by a user to operate the system, and includes a smartphone, a head-mounted display, etc.

[1548] "Emotion data" refers to data that indicates the emotional state of a user analyzed from facial expressions, voice, biometric information, and the like.

[1549] "Security appliance" refers to a device for crime prevention or surveillance that adjusts its settings based on the user's emotional state.

[1550] "Dynamic adjustment" refers to automatically changing the settings and operation of security devices based on real-time user emotional data.

[1551] "Projection" refers to displaying the generated virtual content in the real world, using an AR headset or smartphone.

[1552] This invention is a system that generates virtual content based on a user's ideas and emotions, projects it into real space, and dynamically adjusts security equipment settings.

[1553] Hardware and software used

[1554] 1. User Device:

[1555] Hardware: Smartphones (e.g., iPhones, Android devices), AR headsets, etc.

[1556] Software: OpenCV (facial expression analysis), Google Cloud Speech-to-Text (voice analysis).

[1557] 2. Server:

[1558] Software: Emotion API (Microsoft Azure), Custom TensorFlow sentiment analysis model, Smart Camera API (security equipment control).

[1559] 3. Security equipment:

[1560] Hardware: Network-enabled security cameras (e.g., ARLO Pro, Nest Cam).

[1561] Invention Process Overview

[1562] 1. Inputting Idea and Emotion Data:

[1563] Users enter their ideas in text through a smartphone application, such as "I want to add a red sofa to my living room."

[1564] 2. Collecting Emotional Data:

[1565] Using the smartphone's camera and microphone, the system collects the user's facial expressions, voice, and biometric information (such as heart rate), and uses this data to analyze the user's emotions in real time.

[1566] 3. Sending ideas and emotional data:

[1567] The collected idea and emotion data is transmitted from the user terminal to a server.

[1568] 4. Data analysis and parameter extraction:

[1569] The server analyzes the received idea data and emotion data to extract input parameters for the generative AI model. For example, for a "red sofa," it identifies parameters related to color, shape, and size, and adjusts the design and color based on the emotion data.

[1570] 5. Virtual Content Generation:

[1571] The server uses the generative AI model to generate virtual content (e.g., a 3D model of a rounded red sofa that reflects the user's sense of relaxation).

[1572] 6. User confirmation and correction:

[1573] The generated virtual content is sent to the user terminal, where the user can check it. If necessary, the user can input correction instructions, such as "I want the color of the sofa to be a little darker."

[1574] 7. Regenerate correction instructions:

[1575] The modification instructions are sent back to the server, where they are regenerated using the generative AI model, and the modified virtual content is then sent back to the user device.

[1576] 8. Final confirmation and reality projection:

[1577] Once the user has finally confirmed and approved the virtual content, it is projected into the real world through the user's device and displayed in the real world using an AR headset or smartphone.

[1578] 9. Dynamically Adjust Security Devices:

[1579] Based on the user's emotional data, the settings of the security equipment are dynamically adjusted. For example, if the user feels anxious, the settings of the security camera are changed to widen the viewing angle and increase the recording sensitivity.

[1580] Examples and explanations of prompt sentences

[1581] Examples of prompts:

[1582] "When a user feels anxious, analyze their emotional data, widen the field of view of the security camera, and change the recording mode to high sensitivity."

[1583] This allows the system to generate personalized virtual content based on the user's emotions and dynamically adjust security devices according to their emotional state.

[1584] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1585] Step 1:

[1586] Users use a smartphone application to input their ideas, such as "I want to add a red sofa to my living room." This input becomes the initial data for the system.

[1587] Input: Text data of ideas

[1588] Output: Text data of ideas

[1589] Step 2:

[1590] The user device collects emotional data along with the input idea. Specifically, it uses the smartphone's camera and microphone to collect the user's facial expressions, voice, and biometric information (such as heart rate). OpenCV and Google Cloud Speech-to-Text are used to analyze and identify the user's emotional state.

[1591] Input: User's facial expression, voice, biometric information

[1592] Output: Emotion data (e.g., relaxed, anxious)

[1593] Step 3:

[1594] The device sends the collected idea data and emotion data to the server. Basic information such as the user ID and location information is also sent at the same time. The server receives this data and proceeds to the next processing step.

[1595] Input: idea data, emotion data, user ID, location information

[1596] Output: Send data to the server

[1597] Step 4:

[1598] The server analyzes the received idea data and emotion data to extract parameters to be fed into the generative AI model. These parameters include the color, shape, and size of the virtual content. The design and color are also adjusted based on the emotion data.

[1599] Input: idea data, emotion data

[1600] Output: Parameters to the generative AI model

[1601] Step 5:

[1602] The server generates virtual content using a generative AI model based on the extracted parameters. For example, for an idea like "add a red sofa to the living room," a 3D model of a rounded red sofa that reflects a relaxing feeling is generated.

[1603] Input: Parameters to the generative AI model

[1604] Output: Virtual content (3D model)

[1605] Step 6:

[1606] The server transmits the generated virtual content to the user terminal, which displays the content to the user and prompts the user to confirm the content, allowing the user to input correction instructions.

[1607] Input: Virtual content (3D model)

[1608] Output: Sending content to the user's device

[1609] Step 7:

[1610] The user checks the virtual content and inputs correction instructions as necessary, for example, "I would like the color of the sofa to be a little darker."

[1611] Input: Correction instructions (text data)

[1612] Output: Correction instruction data

[1613] Step 8:

[1614] The device transmits the user's correction instructions to the server, which then regenerates the virtual content using the generative AI model based on the correction instructions and retransmits the corrected virtual content to the device.

[1615] Input: Correction instruction data

[1616] Output: Modified virtual content (3D model)

[1617] Step 9:

[1618] Once the user has finally reviewed and approved the virtual content, it is projected into the real world, where a life-size 3D model is displayed in the real environment using an AR headset or smartphone.

[1619] Input: Final confirmed virtual content (3D model)

[1620] Output: Virtual content projected into real space

[1621] Step 10:

[1622] Dynamically adjust security device settings based on user emotional data. For example, if a user feels anxious, the security camera's viewing angle will be widened and the recording mode will be set to high sensitivity.

[1623] Input: Emotion data (anxiety)

[1624] Output: Dynamically adjusted security appliance configuration

[1625] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1626] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1627] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1628] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1629] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1630] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1631] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1632] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1633] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1634] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1635] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1636] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1637] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1638] 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.

[1639] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1640] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1641] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1642] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1643] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1644] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1645] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1646] The following is further disclosed regarding the above embodiment.

[1647] (Claim 1)

[1648] a means for a user to input ideas;

[1649] means for receiving the ideas and transmitting them to a server;

[1650] A means for analyzing the idea and extracting parameters to be input into a generative AI model;

[1651] means for generating virtual content based on the parameters;

[1652] means for transmitting the generated virtual content to a user terminal and accepting confirmation and correction instructions from the user;

[1653] means for regenerating the virtual content based on the modification instructions;

[1654] a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality;

[1655] A system including:

[1656] (Claim 2)

[1657] 2. The system of claim 1, wherein the virtual content is a 3D model of furniture.

[1658] (Claim 3)

[1659] 2. The system of claim 1, wherein the virtual content is a 3D model of a character.

[1660] "Example 1"

[1661] (Claim 1)

[1662] a means for a user to input ideas;

[1663] means for receiving the ideas and transmitting them to a server;

[1664] A means for analyzing the idea and extracting parameters to be input into a generative AI model;

[1665] means for generating virtual content based on the parameters;

[1666] means for transmitting the generated virtual content to a user terminal and accepting confirmation and correction instructions from the user;

[1667] means for regenerating the virtual content based on the modification instructions;

[1668] a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality;

[1669] means for generating said virtual content using 3D modeling software;

[1670] a means for projecting the final confirmed virtual content into real space using an AR headset or a smartphone;

[1671] A system including:

[1672] (Claim 2)

[1673] 2. The system of claim 1, wherein the virtual content is a 3D model of furniture.

[1674] (Claim 3)

[1675] 2. The system of claim 1, wherein the virtual content is a 3D model of a character.

[1676] "Application Example 1"

[1677] (Claim 1)

[1678] a means for a user to input ideas;

[1679] means for receiving the ideas and transmitting them to a server;

[1680] A means for analyzing the idea and extracting parameters to be input into a generative AI model;

[1681] means for generating virtual content based on the parameters;

[1682] means for transmitting the generated virtual content to a user terminal and accepting confirmation and correction instructions from the user;

[1683] means for regenerating the virtual content based on the modification instructions;

[1684] a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality;

[1685] means for providing a user interface for customizing specifications of an item in a virtual space;

[1686] means for searching the virtual space in real time and reflecting changes to the item;

[1687] A system including:

[1688] (Claim 2)

[1689] 2. The system according to claim 1, wherein the virtual content is a three-dimensional model of furniture.

[1690] (Claim 3)

[1691] 2. The system according to claim 1, wherein the virtual content is a three-dimensional model of a character.

[1692] "Example 2: Combining Emotion Engines"

[1693] (Claim 1)

[1694] a means for a user to input ideas;

[1695] means for receiving the ideas and transmitting them to a server;

[1696] A means for acquiring emotion data using an emotion engine that recognizes the emotion of a user;

[1697] means for transmitting the idea data and emotion data to a server;

[1698] A means for analyzing the idea and emotion data and extracting parameters to be input into a generative AI model;

[1699] means for generating virtual content based on the parameters and emotion data;

[1700] means for transmitting the generated virtual content to a user terminal and accepting confirmation and correction instructions from the user;

[1701] means for regenerating the virtual content based on the modification instructions;

[1702] a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality;

[1703] A system including:

[1704] (Claim 2)

[1705] 2. The system of claim 1, wherein the virtual content is a 3D model of furniture.

[1706] (Claim 3)

[1707] 2. The system of claim 1, wherein the virtual content is a 3D model of a character.

[1708] "Application example 2 when combining emotion engines"

[1709] (Claim 1)

[1710] a means for a user to input ideas;

[1711] means for receiving the ideas and transmitting them to a server;

[1712] A means for analyzing the idea and extracting parameters to be input into a generative AI model;

[1713] means for generating virtual content based on the parameters;

[1714] means for transmitting the generated virtual content to a user terminal and accepting confirmation and correction instructions from the user;

[1715] means for regenerating the virtual content based on the modification instructions;

[1716] a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality;

[1717] means for collecting emotion data of the user and adjusting the virtual content based on the emotion;

[1718] means for dynamically adjusting settings of a security device based on said emotion data;

[1719] A system including:

[1720] (Claim 2)

[1721] 2. The system of claim 1, wherein the virtual content is a 3D model of furniture.

[1722] (Claim 3)

[1723] 2. The system of claim 1, wherein the virtual content is a 3D model of a character. [Explanation of symbols]

[1724] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to input ideas; means for receiving the ideas and transmitting them to a server; A means for analyzing the idea and extracting parameters to be input into a generative AI model; means for generating virtual content based on the parameters; means for transmitting the generated virtual content to a user terminal and accepting confirmation and correction instructions from the user; means for regenerating the virtual content based on the modification instructions; a means for retransmitting the corrected virtual content to the user terminal and projecting the final confirmed virtual content into reality; A system including:

2. The system of claim 1 , wherein the virtual content is a 3D model of furniture.

3. The system of claim 1, wherein the virtual content is a 3D model of a character.

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