system

Abstract

We provide the system. [Solution] Means for acquiring image and video data, A means for analyzing the acquired image and video data and generating three-dimensional spatial information, A means for reconstructing the generated three-dimensional spatial information within a virtual reality space, A means for presenting the aforementioned virtual reality space to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventional photos and videos are static and two-dimensional, making it difficult for users to vividly relive past events and memories. In particular, there have been limited means to more realistically preserve memories of growth, travel, and especially memories of deceased people and pets. As a result, there has been a problem that important past moments are not fully reproduced, making it difficult to deepen emotional connections.

Means for Solving the Problems

[0005] This invention provides a system comprising means for acquiring image and video data, means for analyzing the acquired data to generate three-dimensional spatial information, means for reconstructing the generated information in a virtual reality space, and means for presenting that space to the user. Furthermore, by combining means for analyzing the movement of objects in images and dynamically reproducing it in the virtual reality space, and means for adjusting the viewpoint and time based on user instructions, the invention provides an environment in which past events can be re-experienced in three dimensions and dynamically. This makes it possible for users to recreate memories in a realistic way and experience them with rich emotions.

[0006] "Image and video data" refers to digital files containing visual information acquired using cameras or other devices.

[0007] "Analysis" is the process of examining data in detail to understand its structure and characteristics.

[0008] "Three-dimensional spatial information" refers to data that shows the three-dimensional shape and positional relationships of objects and environments, and is the information necessary for generating 3D models.

[0009] A "virtual reality space" is an artificial three-dimensional environment created using computer technology that users can experience visually and sensorially.

[0010] "Reconstruction" is the process of creating new forms and structures based on existing data and information.

[0011] "Presentation" refers to the act of showing information or data to a user through visual or other sensory means.

[0012] "Object movement" refers to information that describes how a particular object changes its position and orientation over time.

[0013] "Dynamic reproduction" is a process of representing information and situations not in a static state, but in a way that changes over time.

[0014] "Adjusting the viewpoint and time" refers to the process of changing the visual and temporal conditions within the virtual space experienced by the user in a selectable manner. [Brief explanation of the drawing]

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

Embodiment for Carrying Out the Invention

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

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

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

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

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

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

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

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

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

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0036] The following program and system configuration are provided as specific embodiments of the present invention.

[0037] Data acquisition and analysis

[0038] First, the user uploads photos and videos they have taken to the system through a dedicated interface. The terminal sends the selected data to the server. The server stores the received data and begins analysis by the generative AI module. Based on the received data, the generative AI recognizes objects and landscapes in the image and reconstructs them as three-dimensional spatial information.

[0039] Building a virtual reality space

[0040] The server constructs a virtual reality space using the generated three-dimensional spatial information and the analyzed motion data of the objects. This information is then reflected in the virtual environment on the metaverse server, and prepared in a form that users can experience.

[0041] Providing a user experience

[0042] The device accesses the constructed virtual reality space and provides the user with that experience. Using a VR device on the device, the user can recreate and relive past memories by becoming immersed in the virtual reality space. Furthermore, they can freely change their viewpoint and time within the metaverse, enabling them to gain new visual experiences.

[0043] Specific example

[0044] For example, consider a scenario where a user uploads a video they recorded of their child's growth to the system. The server analyzes the child's movements in the video and generates a three-dimensional model. By placing this model in a virtual reality space, the user can experience what it was like to be present at that moment. In this process, the child's movements and facial expressions are dynamically reproduced, making past events feel more realistic.

[0045] In this way, the present invention provides a means to virtually extend the static video assets that users possess, allowing them to enjoy them in a more emotionally rich and intuitive way.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] The user logs into the system on their device, selects and uploads photos and video data. The device then sends the selected data to the server.

[0049] Step 2:

[0050] The server temporarily stores the received data and adds it to a queue awaiting analysis. The data is checked to ensure reliability and security.

[0051] Step 3:

[0052] The generation AI module on the server sequentially retrieves the stored data and analyzes the image and video data. The generation AI uses image analysis algorithms to perform object detection, boundary extraction, pose estimation, and other operations from the data to generate three-dimensional spatial information.

[0053] Step 4:

[0054] The server uses the generated three-dimensional spatial information to create 3D models and animation data. This data is then converted into a format usable in the virtual reality space.

[0055] Step 5:

[0056] The server sends the generated model data to the metaverse server, where it is integrated into the virtual reality space. The metaverse server then prepares to reflect this data in the virtual space.

[0057] Step 6:

[0058] The user accesses the metaverse space from their device and explores the virtual reality space using VR equipment. The device connects to the metaverse server and displays a 3D model to the user in real time.

[0059] Step 7:

[0060] Users can interactively manipulate the virtual reality space, adjusting their viewpoint and time to obtain different visual experiences. The device reflects these actions in the metaverse space, instantly changing the display.

[0061] (Example 1)

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

[0063] Traditional image and video data only allowed for static playback, making it difficult for users to experience past moments with a sense of presence. Furthermore, user manipulation of viewpoint and time was limited, preventing the provision of new, immersive experiences.

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

[0065] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired data and generating three-dimensional spatial information, means for reconstructing it in a virtual reality space, means for presenting the virtual reality space to the user, means for changing the viewpoint and time based on the user's instructions, and means for analyzing the data using a generation AI model and automatically generating three-dimensional spatial information. As a result, the user can experience the virtual reality space with a dynamic and free viewpoint, making past events feel more real.

[0066] "Image data" refers to visual information represented in a digital format.

[0067] "Video data" refers to the digital representation of moving images and videos.

[0068] "Means of acquisition" refers to the devices and methods used to capture data.

[0069] "Means of analysis" refers to methods and devices for analyzing data and extracting necessary information.

[0070] "Three-dimensional spatial information" refers to information generated from data that has three dimensions: length, width, and depth.

[0071] A "virtual reality space" is an artificial three-dimensional environment generated by a computer.

[0072] "Means of reconstruction" refers to methods or devices for creating a new structure based on the original data.

[0073] "Means of presentation" refers to methods or devices used to show information to the recipient.

[0074] "User instructions" refers to operations or commands given by the user.

[0075] A "generative AI model" is an artificial intelligence model that automatically processes and analyzes data to output specific results.

[0076] This invention is a system that constructs a virtual reality space based on static image and video data owned by the user, allowing them to recreate and experience past events. Specific embodiments of this system are shown below.

[0077] Users upload image and video data to the system via a dedicated interface. The terminal sends this data to the server for secure storage. The server inputs the data into a generating AI model (for example, an image analysis module provided by a specific AI provider) and performs image recognition and video analysis. This analysis recognizes objects and landscapes within the data and reconstructs them as three-dimensional spatial information.

[0078] The server constructs a virtual reality space based on the obtained three-dimensional information. This process utilizes game engines such as Unity and Unreal Engine. Through these engines, visual data is realistically reproduced, creating a virtual environment that users can experience.

[0079] This system can be used in the following specific example: A user enters a prompt message regarding a video recording of their child's growth, such as, "Create a 3D model of my child's birthday party video and recreate it in a virtual reality space." Based on this request, the server analyzes the video and generates a virtual environment that recreates the child's movements, surroundings, and facial expressions. The terminal sends this to the user's VR device, allowing the user to relive past events in that virtual space.

[0080] In this way, the system provides users with a means to virtually extend past static video assets and experience them in an emotionally rich manner. By utilizing generative AI models, it can efficiently analyze image and video data and generate three-dimensional spatial information, providing users with an innovative experience.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] Users select and upload image and video data using a dedicated interface. The terminal receives this selected data as input and sends it to the server using a data transfer protocol. Specifically, the user presses the "upload" button, the terminal checks the file format and size, compresses it, and sends it to the server.

[0084] Step 2:

[0085] The server stores the data received from the terminal in its storage system. As preparation for data analysis, it performs preprocessing to pass the data to the generating AI model. Specifically, this includes format verification, filtering of abnormal data, and adding metadata. At this stage, the input is a raw data file, and the output is in a parseable data format.

[0086] Step 3:

[0087] The server analyzes received data using a generative AI model and generates three-dimensional spatial information. The input is pre-processed data, and the generative AI model recognizes and labels objects in images and videos, and reconstructs them into three-dimensional information. Specifically, the AI ​​model extracts feature points from images and generates a three-dimensional point cloud using deep learning technology. The output is the reconstructed three-dimensional spatial information.

[0088] Step 4:

[0089] The server uses the generated three-dimensional spatial information to construct a virtual reality space. Using a game engine, it creates a real-time visual space and adds visual and lighting effects. Three-dimensional spatial information is provided as input, and the output is the data of the virtual reality space experienced by the user. Specifically, this involves the server executing engine scripts and placing objects within the virtual space.

[0090] Step 5:

[0091] The terminal displays virtual reality data received from the server, providing the user with an experience. The user immerses themselves in the virtual space using a VR device and can freely change their viewpoint and time based on input data from the server. Specific operations include visual updates using the terminal's rendering device and interaction processing through a control device. The output is the virtual environment that the user visually experiences.

[0092] (Application Example 1)

[0093] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0094] In modern content distribution services, users often reminisce about past memories using static video assets, but this experience is visually limited. There is a need for users to re-experience past memories in a more intuitive and emotionally rich way, but traditional methods cannot adequately meet this need.

[0095] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0096] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired image and video data and generating shared space information, and means for reconstructing the generated shared space information within a virtual environment. This enables users to obtain a realistic and immersive visual experience based on static video assets.

[0097] "Image and video data" refers to digital information in still image and video formats, including visual media captured or collected by the user.

[0098] "Shared spatial information" refers to three-dimensional digital information generated from analyzed image and video data, and is used to construct virtual environments.

[0099] A "virtual environment" refers to a three-dimensional space created using digital technology, an immersive simulation space that users can experience visually.

[0100] "Means of providing a visual experience" refers to technologies or devices for visually reproducing and presenting generated content within a virtual environment to a user.

[0101] The system for realizing this application consists of a user terminal, a server, and a VR device. The user uploads captured images and video data to the server via the terminal. The server receives this data, analyzes it using a generative AI model, and generates shared spatial information. Specifically, the server constructs a three-dimensional space using generative AI tools such as Stable Diffusion and DALL-E.

[0102] Next, the server reconstructs the constructed shared space information as a virtual environment and provides it to the user. The user can access the virtual environment and enjoy the visual experience using VR devices such as head-mounted displays. In this process, Google Cloud and AWS are used as meta-platforms.

[0103] As a concrete example, suppose a user uploads photos and videos of a special day spent with their family. Based on this data, the server virtually recreates the space where the family gathered and the atmosphere of that day, allowing the user to move through it and experience it as if they were back in that moment.

[0104] An example of a prompt for the generative AI model would be, "Please realistically recreate my child's birthday party in a 3D virtual space." This allows users to richly recreate past experiences while fostering a deeper emotional connection.

[0105] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0106] Step 1:

[0107] The user uploads images and video data captured using their device to the server. The input is media files stored on the user's local device, and the output is the transfer and storage of this data on the server. Specifically, the user operates a file selection interface, selects multiple files, and begins the upload.

[0108] Step 2:

[0109] The server receives uploaded image and video data and performs analysis using a generative AI model. The input is the media data received in step 1, and the output is the three-dimensional spatial information obtained through the analysis. Stable Diffusion and DALL-E are used for this process. The server inputs prompt messages to the AI ​​model, giving instructions in the form of "Generate a three-dimensional space from this image."

[0110] Step 3:

[0111] The server reconstructs the virtual environment based on the generated three-dimensional spatial information. The input is the shared spatial information generated in step 2, and the output is the virtual environment data that the user can experience. To reconstruct this data, the server uses a 3D rendering engine to prepare the virtual reality space.

[0112] Step 4:

[0113] The server sends the reconstructed virtual environment to the user's terminal. The input is the virtual environment data completed in step 3, and the output is data converted into a format that can be visually experienced on the user's VR device. Specifically, the server sends this data in stream format, enabling real-time display on the user's VR device.

[0114] Step 5:

[0115] The user wears a VR device and experiences a virtual environment. The input is the virtual environment data received from the server in step 4, and the output is the user's immersive experience. The user uses a controller or eye-tracking controls to change their viewpoint and the time of day within the virtual space, allowing them to recreate and enjoy past memories in a three-dimensional and dynamic way.

[0116] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0117] This invention provides a more personalized experience by incorporating an emotion engine that recognizes user emotions, in addition to a system that generates a three-dimensional space based on image and video data and provides that experience within a virtual reality space. The details are described below through examples.

[0118] Data acquisition and analysis

[0119] Users upload photos and video data to the system via their devices. The devices send this data to a server, which then uses a generation AI module to generate three-dimensional spatial information. This process also analyzes the movement of objects within the video and reconstructs them as dynamic three-dimensional models.

[0120] Creation and presentation of virtual reality spaces

[0121] The server sends the 3D model and dynamic data it generates to the metaverse server. The metaverse server constructs a virtual reality space based on the received data and prepares to provide that space to the user. The user can then use a VR device on their terminal to enter the virtual space and enjoy the visual experience.

[0122] Personalization powered by an emotion engine

[0123] The emotion engine embedded in the server analyzes the user's biometric data, voice, and facial expressions to recognize their current emotional state. Based on this data, it adjusts the visual, auditory, and other elements of the virtual reality space to match the user's emotions, personalizing the user experience.

[0124] Specific example

[0125] For example, if a user wants to relive a travel memory, they can upload a photo album to the system, recreating that travel destination in a virtual reality space. If the emotion engine detects the user's smile or cheerful voice, it adjusts the colors and music of the virtual world to be brighter and more harmonious. Conversely, if a calm and soothing emotion is recognized, the lighting in the virtual space is reduced, creating a quiet and relaxing environment. In this way, users can enjoy a more personalized and immersive experience.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The user accesses the system via their device and selects the photos or videos they want to experience. The device then uploads the selected files to the server.

[0129] Step 2:

[0130] The server temporarily stores the received data and prepares it for analysis. It checks the data format and quality and then passes it on to the generating AI module.

[0131] Step 3:

[0132] The AI ​​generation module on the server analyzes the data and extracts three-dimensional information about objects and backgrounds within the image. Furthermore, in the case of video data, it performs motion analysis and generates a dynamic three-dimensional model.

[0133] Step 4:

[0134] The server formats the three-dimensional spatial information and dynamic model it generates for the metaverse and sends it to the metaverse server. The metaverse server then constructs a virtual reality space based on this data.

[0135] Step 5:

[0136] The server analyzes voice and facial expression data collected from the user's device through an emotion engine to recognize the user's emotional state. The device uses sensors and cameras to acquire the necessary data for this purpose.

[0137] Step 6:

[0138] The metaverse server dynamically adjusts the visual and auditory settings of the virtual reality space according to the user's emotions, based on emotion data obtained from the server. This allows the user to experience a personalized space.

[0139] Step 7:

[0140] Users enter a virtual reality space using a VR device on their device and explore a constructed three-dimensional model and a space adjusted based on emotions. Users can interactively manipulate the space and re-experience past memories emotionally and visually.

[0141] (Example 2)

[0142] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0143] Traditional virtual environment systems have the drawback of not considering the emotional state of the user, thus failing to provide an optimized experience for each individual user. Furthermore, the reproduction of dynamic objects within the virtual space is difficult, sometimes limiting the user experience. In addition, users cannot freely adjust various viewpoints, resulting in insufficient interactivity in the virtual environment.

[0144] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0145] In this invention, the server includes means for analyzing image and video data and generating three-dimensional spatial information; means for acquiring user emotion information and adjusting the virtual environment according to the user's emotional state; means for analyzing the movement of objects in images and dynamically reproducing them within the virtual environment; and means for adjusting the display of the virtual environment from different times or viewpoints. This makes it possible to provide a personalized experience tailored to the user's emotions and realize a dynamic and interactive virtual space.

[0146] "Image and video data" refers to visual information acquired by cameras and recording devices, including still images and video.

[0147] "Analysis" refers to processing acquired data and performing calculations and operations to extract or understand necessary information.

[0148] "Three-dimensional spatial data" refers to a dataset containing information for representing real or virtual space in three dimensions, capable of representing the position, shape, and movement of objects.

[0149] A "virtual environment" refers to an artificial and interactive space created by a computer that a user can experience through their sight, hearing, and other senses.

[0150] "User" refers to an individual who experiences a virtual environment through this system.

[0151] "Emotional information" refers to data that indicates the user's biological and psychological state, and is obtained from facial expressions, voice tone, biosignals, etc.

[0152] "Dynamic reproduction" refers to making objects and scenes change moment by moment for the user, enabling real-time interaction.

[0153] "Adjusting the display" means changing the viewpoint and content on the screen according to the user's instructions or environment, in order to provide the optimal visual experience.

[0154] This system realizes a virtual environment through collaborative operation between users, terminals, and servers. Users upload photos and video data via their terminals, which then send this data to the server. The server analyzes the data using a generative AI model and generates three-dimensional spatial data. Specifically, it utilizes deep learning technology for image recognition and reconstructs detailed spatial features. The hardware used should be a server equipped with a high-performance GPU, and the software should include machine learning frameworks.

[0155] The generated 3D model is sent to a metaverse server and constructed as a virtual environment. Users can access this virtual environment using a VR device connected to their terminal. The emotion engine acquires the user's biometric data, for example, through a camera and microphone, and analyzes their emotional state in real time. Based on these emotions, the server dynamically adjusts the visual and auditory information of the virtual environment to provide a personalized experience.

[0156] As a concrete example, suppose a user wants to relive a past trip. In this case, uploading a photo album to the system recreates the travel destination in a virtual space. When the emotion engine recognizes that the user is enjoying themselves from their facial expressions, the colors and music in the virtual space are adjusted to be brighter. Also, when the user wants to relax, the scenery changes to something quiet and peaceful.

[0157] An example of a prompt message is, "Recreate travel memories and provide a virtual environment that reflects the user's current emotions."

[0158] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0159] Step 1:

[0160] Users upload photos and video data to the system via their device. Specifically, they select data files using the device's interface and click the upload button. This action causes the device to collect the selected data and prepare it for transmission to the server for the next processing step. The input is the photos and video data selected by the user, and the output is the data securely transmitted to the server.

[0161] Step 2:

[0162] The device sends the uploaded data to the server. To ensure data security, the communication is encrypted using the SSL / TLS protocol. The server verifies the integrity of the received data and stores it in a database. The input is the encrypted data sent from the device, and the output is the raw data stored in the database.

[0163] Step 3:

[0164] The server inputs data stored in the database into a generating AI model to create three-dimensional spatial information. During this process, the AI ​​model uses deep learning techniques to analyze images and identify the movement and shape of objects in the video. This creates a dynamic three-dimensional model. The input is image and video data, and the output is the generated three-dimensional spatial data.

[0165] Step 4:

[0166] The server sends the generated three-dimensional spatial data to the metaverse server, which then prepares it for reconstruction as a virtual environment. The metaverse server builds the virtual environment based on the received data and makes it available to the user. The input is three-dimensional spatial data, and the output is a dataset with the virtual environment completed.

[0167] Step 5:

[0168] The user accesses a virtual environment using a VR device. Here, the server's emotion engine analyzes the user's biometric data and adjusts the visual and auditory elements of the virtual environment based on their emotional state in real time. The input is the user's biometric data, and the output is the adjusted visual and auditory elements of the virtual environment.

[0169] Step 6:

[0170] Users experience a virtual environment tailored to their emotions. For example, when recreating travel memories, if the emotion engine determines that the user is enjoying themselves, bright and cheerful colors and music will be provided. The input is the user's emotional state based on the emotion engine's output, and the output is a personalized virtual environment.

[0171] (Application Example 2)

[0172] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0173] While virtual reality spaces are a technology that provides users with a sense of immersion, they lack sufficient consistency with the real world and personalization that takes into account individual user experiences. Furthermore, they lack the functionality to adjust the virtual space in response to changes in emotions. This invention aims to integrate the user's real environment with the virtual space and provide individualized visual and auditory experiences based on emotions.

[0174] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0175] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired image and video data and generating three-dimensional spatial information, means for reconstructing the generated three-dimensional spatial information in a virtual reality space, and means for recognizing the user's emotions and adjusting the visual and auditory elements of the virtual reality space. This enables a personalized, immersive virtual experience based on the user's actual environment and emotional state.

[0176] "Image and video data" refers to photos and videos provided by users, and is fundamental information for constructing the virtual reality space.

[0177] "Three-dimensional spatial information" refers to a three-dimensional digital representation generated based on acquired image and video data, and is a component of virtual reality space.

[0178] A "virtual reality space" is a digital virtual environment constructed based on three-dimensional spatial information, providing users with a sense of immersion.

[0179] "Means of recognizing user emotions" refers to a function that analyzes biometric data, voice, and facial expressions to determine the emotional state the user is experiencing.

[0180] "Means for adjusting visual and auditory elements" refers to functions that dynamically change the images and sounds of the virtual reality space based on the perceived emotions of the user, thereby optimizing the user experience.

[0181] "Means of integrating the user's real environment with the virtual space" refers to technology that overlays a virtual reality space onto the user's current physical environment, thereby achieving a unification of reality and virtuality.

[0182] In the system implementing this invention, the user uploads image and video data to a server using a terminal such as a smartphone or smart glasses. The server receives this data and generates three-dimensional spatial information using a generative AI model. In this process, AI technology for image analysis (e.g., computer vision technology) is utilized to analyze the movement of objects in the video, thereby constructing a dynamic three-dimensional model.

[0183] The constructed three-dimensional model is reconstructed within the virtual reality space. Specifically, a server manages this data and presents it visually to the user's terminal via a VR device. During this process, an emotion analysis engine (e.g., emotion recognition software) analyzes biometric data, voice, and facial expressions to recognize the user's emotions. Based on this, the visual and auditory elements within the virtual reality space are adjusted to transform the environment to suit the user's emotions.

[0184] For example, if a user wants to relive memories of a past trip, they upload a photo album from their device to the system. Based on this data, the travel destination is recreated in a virtual reality space. When the emotion analysis engine detects joy as the user's emotion, the system adjusts the colors and music in the virtual space to make it a happier experience.

[0185] An example of a prompt message might be, "Overlay a virtual historical cityscape based on photographs onto reality, and interactively adjust the experience according to the user's emotions." This allows users to enjoy a personalized virtual experience.

[0186] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0187] Step 1:

[0188] The user uploads images and video data captured using their device. The input consists of image and video files. Once the data is sent from the user to the server, the following processing becomes possible.

[0189] Step 2:

[0190] The server analyzes the image and video data it receives. This analysis uses a generative AI model and image recognition technology. The input is image and video data from the user, and the output is analyzed three-dimensional spatial information. Based on this data, the server calculates the three-dimensional structure and generates a three-dimensional model that includes dynamic elements.

[0191] Step 3:

[0192] Using the generated three-dimensional spatial information, the server constructs a virtual reality space. The input is the analyzed three-dimensional spatial information, and the output is the virtual reality space itself. The server prepares the virtual environment as visual data and sends it to the user's VR terminal.

[0193] Step 4:

[0194] The user accesses the constructed virtual reality space using a VR device on their device. The input in this step is visual data sent from the server, and the output is the 3D virtual space experienced by the user. The device projects the visual data onto the VR device, providing the user with an immersive experience.

[0195] Step 5:

[0196] The server analyzes the user's biometric data and recognizes emotions using an emotion analysis engine. Input is the user's biosensor data and voice data, and output is the user's emotional state. Based on this emotional information, the server adjusts the visual and auditory elements within the virtual reality space.

[0197] Step 6:

[0198] A personalized experience is provided based on the user's emotions. The server sends adjusted environmental data to the user's device, and the device modifies the characteristics of the virtual space according to the user's emotions. This enables a real-time interactive experience.

[0199] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0200] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0201] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may be performed by the smart device 14.

[0202] [Second Embodiment]

[0203] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0204] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0205] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0206] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0207] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0208] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0209] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0210] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0211] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0212] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0213] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0214] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0215] The following program and system configuration are provided as specific embodiments of the present invention.

[0216] Data acquisition and analysis

[0217] First, the user uploads photos and videos they have taken to the system through a dedicated interface. The terminal sends the selected data to the server. The server stores the received data and begins analysis by the generative AI module. Based on the received data, the generative AI recognizes objects and landscapes in the image and reconstructs them as three-dimensional spatial information.

[0218] Building a virtual reality space

[0219] The server constructs a virtual reality space using the generated three-dimensional spatial information and the analyzed motion data of the objects. This information is then reflected in the virtual environment on the metaverse server, and prepared in a form that users can experience.

[0220] Providing a user experience

[0221] The device accesses the constructed virtual reality space and provides the user with that experience. Using a VR device on the device, the user can recreate and relive past memories by becoming immersed in the virtual reality space. Furthermore, they can freely change their viewpoint and time within the metaverse, enabling them to gain new visual experiences.

[0222] Specific example

[0223] For example, consider a scenario where a user uploads a video they recorded of their child's growth to the system. The server analyzes the child's movements in the video and generates a three-dimensional model. By placing this model in a virtual reality space, the user can experience what it was like to be present at that moment. In this process, the child's movements and facial expressions are dynamically reproduced, making past events feel more realistic.

[0224] In this way, the present invention provides a means to virtually extend the static video assets that users possess, allowing them to enjoy them in a more emotionally rich and intuitive way.

[0225] The following describes the processing flow.

[0226] Step 1:

[0227] The user logs into the system on their device, selects and uploads photos and video data. The device then sends the selected data to the server.

[0228] Step 2:

[0229] The server temporarily stores the received data and adds it to a queue awaiting analysis. The data is checked to ensure reliability and security.

[0230] Step 3:

[0231] The generation AI module on the server sequentially retrieves the stored data and analyzes the image and video data. The generation AI uses image analysis algorithms to perform object detection, boundary extraction, pose estimation, and other operations from the data to generate three-dimensional spatial information.

[0232] Step 4:

[0233] The server uses the generated three-dimensional spatial information to create 3D models and animation data. This data is then converted into a format usable in the virtual reality space.

[0234] Step 5:

[0235] The server sends the generated model data to the metaverse server, where it is integrated into the virtual reality space. The metaverse server then prepares to reflect this data in the virtual space.

[0236] Step 6:

[0237] The user accesses the metaverse space from their device and explores the virtual reality space using VR equipment. The device connects to the metaverse server and displays a 3D model to the user in real time.

[0238] Step 7:

[0239] Users can interactively manipulate the virtual reality space, adjusting their viewpoint and time to obtain different visual experiences. The device reflects these actions in the metaverse space, instantly changing the display.

[0240] (Example 1)

[0241] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0242] Traditional image and video data only allowed for static playback, making it difficult for users to experience past moments with a sense of presence. Furthermore, user manipulation of viewpoint and time was limited, preventing the provision of new, immersive experiences.

[0243] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0244] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired data and generating three-dimensional spatial information, means for reconstructing it in a virtual reality space, means for presenting the virtual reality space to the user, means for changing the viewpoint and time based on the user's instructions, and means for analyzing the data using a generation AI model and automatically generating three-dimensional spatial information. As a result, the user can experience the virtual reality space with a dynamic and free viewpoint, making past events feel more real.

[0245] "Image data" refers to visual information represented in a digital format.

[0246] "Video data" refers to the digital representation of moving images and videos.

[0247] "Means of acquisition" refers to the devices and methods used to capture data.

[0248] "Means of analysis" refers to methods and devices for analyzing data and extracting necessary information.

[0249] "Three-dimensional spatial information" refers to information generated from data that has three dimensions: length, width, and depth.

[0250] A "virtual reality space" is an artificial three-dimensional environment generated by a computer.

[0251] "Means of reconstruction" refers to methods or devices for creating a new structure based on the original data.

[0252] "Means of presentation" refers to methods or devices used to show information to the recipient.

[0253] "User instructions" refers to operations or commands given by the user.

[0254] A "generative AI model" is an artificial intelligence model that automatically processes and analyzes data to output specific results.

[0255] This invention is a system that constructs a virtual reality space based on static image and video data owned by the user, allowing them to recreate and experience past events. Specific embodiments of this system are shown below.

[0256] Users upload image and video data to the system via a dedicated interface. The terminal sends this data to the server for secure storage. The server inputs the data into a generating AI model (for example, an image analysis module provided by a specific AI provider) and performs image recognition and video analysis. This analysis recognizes objects and landscapes within the data and reconstructs them as three-dimensional spatial information.

[0257] The server constructs a virtual reality space based on the obtained three-dimensional information. This process utilizes game engines such as Unity and Unreal Engine. Through these engines, visual data is realistically reproduced, creating a virtual environment that users can experience.

[0258] This system can be used in the following specific example: A user enters a prompt message regarding a video recording of their child's growth, such as, "Create a 3D model of my child's birthday party video and recreate it in a virtual reality space." Based on this request, the server analyzes the video and generates a virtual environment that recreates the child's movements, surroundings, and facial expressions. The terminal sends this to the user's VR device, allowing the user to relive past events in that virtual space.

[0259] In this way, the system provides users with a means to virtually extend past static video assets and experience them in an emotionally rich manner. By utilizing generative AI models, it can efficiently analyze image and video data and generate three-dimensional spatial information, providing users with an innovative experience.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] Users select and upload image and video data using a dedicated interface. The terminal receives this selected data as input and sends it to the server using a data transfer protocol. Specifically, the user presses the "upload" button, the terminal checks the file format and size, compresses it, and sends it to the server.

[0263] Step 2:

[0264] The server stores the data received from the terminal in its storage system. As preparation for data analysis, it performs preprocessing to pass the data to the generating AI model. Specifically, this includes format verification, filtering of abnormal data, and adding metadata. At this stage, the input is a raw data file, and the output is in a parseable data format.

[0265] Step 3:

[0266] The server analyzes received data using a generative AI model and generates three-dimensional spatial information. The input is pre-processed data, and the generative AI model recognizes and labels objects in images and videos, and reconstructs them into three-dimensional information. Specifically, the AI ​​model extracts feature points from images and generates a three-dimensional point cloud using deep learning technology. The output is the reconstructed three-dimensional spatial information.

[0267] Step 4:

[0268] The server uses the generated three-dimensional spatial information to construct a virtual reality space. Using a game engine, it creates a real-time visual space and adds visual and lighting effects. Three-dimensional spatial information is provided as input, and the output is the data of the virtual reality space experienced by the user. Specifically, this involves the server executing engine scripts and placing objects within the virtual space.

[0269] Step 5:

[0270] The terminal displays virtual reality data received from the server, providing the user with an experience. The user immerses themselves in the virtual space using a VR device and can freely change their viewpoint and time based on input data from the server. Specific operations include visual updates using the terminal's rendering device and interaction processing through a control device. The output is the virtual environment that the user visually experiences.

[0271] (Application Example 1)

[0272] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0273] In modern content distribution services, users often reminisce about past memories using static video assets, but this experience is visually limited. There is a need for users to re-experience past memories in a more intuitive and emotionally rich way, but traditional methods cannot adequately meet this need.

[0274] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0275] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired image and video data and generating shared space information, and means for reconstructing the generated shared space information within a virtual environment. This enables users to obtain a realistic and immersive visual experience based on static video assets.

[0276] "Image and video data" refers to digital information in still image and video formats, including visual media captured or collected by the user.

[0277] "Shared spatial information" refers to three-dimensional digital information generated from analyzed image and video data, and is used to construct virtual environments.

[0278] A "virtual environment" refers to a three-dimensional space created using digital technology, an immersive simulation space that users can experience visually.

[0279] "Means of providing a visual experience" refers to technologies or devices for visually reproducing and presenting generated content within a virtual environment to a user.

[0280] The system for realizing this application example consists of a user terminal, a server, and a VR device. The user uploads the captured images and video data to the server through the terminal. The server receives these data, analyzes the data using a generated AI model, and generates shared space information. Specifically, the server constructs a three-dimensional space using generation AI tools such as Stable Diffusion and DALL-E.

[0281] Next, the server reconstructs the constructed shared space information as a virtual environment and provides it to the user. The user can use a VR device such as a head-mounted display to access the virtual environment and enjoy a visual experience. At this time, Google Cloud or AWS is used as the meta-platform.

[0282] As a specific example, assume that the user uploads photos and videos of a special day spent with family. Based on this data, the server virtually reproduces the space where the family gathered and the atmosphere of that day, and the user can move around in it and experience as if they had returned to that moment.

[0283] As an example of the prompt text for the generated AI model, it is input in the form of "Please realistically reproduce a children's birthday party in a 3D virtual space". This enables the user to richly reproduce past experiences while having a deeper emotional connection.

[0284] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0285] Step 1:

[0286] The user uploads the images and video data captured using the terminal to the server. The input is the media files stored on the user's local device, and the output is that this data is transferred to and stored on the server. As a specific operation, the user operates the file selection interface, selects multiple files, and starts the upload.

[0287] Step 2:

[0288] The server receives the uploaded image and video data and performs analysis using the generated AI model. The input is the media data received in Step 1, and the output is the three-dimensional spatial information obtained through analysis. Stable Diffusion or DALL-E is used for this process. The server inputs the prompt text into the AI model and gives instructions in the form of "Please generate a three-dimensional space from this image."

[0289] Step 3:

[0290] The server reconstructs the virtual environment based on the generated three-dimensional spatial information. The input is the shared space information generated in Step 2, and the output is the virtual environment data that the user can experience. To reconstruct this data, the server uses a 3D rendering engine on its side to prepare the virtual reality space.

[0291] Step 4:

[0292] The server sends the reconstructed virtual environment to the user's terminal. The input is the virtual environment data completed in Step 3, and the output is the data converted into a form that can be visually experienced on the user's VR device. As a specific operation, the server sends this data in a stream format to enable real-time display on the user's VR device.

[0293] Step 5:

[0294] The user wears the VR device and experiences the virtual environment. The input is the virtual environment data received from the server in Step 4, and the output is the immersive experience of the user. The user uses the controller or eye movement operation at hand to change the viewpoint and time in the virtual space, and reproduces and enjoys past memories in a three-dimensional and dynamic manner.

[0295] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0296] This invention provides a more personalized experience by incorporating an emotion engine that recognizes user emotions, in addition to a system that generates a three-dimensional space based on image and video data and provides that experience within a virtual reality space. The details are described below through examples.

[0297] Data acquisition and analysis

[0298] Users upload photos and video data to the system via their devices. The devices send this data to a server, which then uses a generation AI module to generate three-dimensional spatial information. This process also analyzes the movement of objects within the video and reconstructs them as dynamic three-dimensional models.

[0299] Creation and presentation of virtual reality spaces

[0300] The server sends the 3D model and dynamic data it generates to the metaverse server. The metaverse server constructs a virtual reality space based on the received data and prepares to provide that space to the user. The user can then use a VR device on their terminal to enter the virtual space and enjoy the visual experience.

[0301] Personalization powered by an emotion engine

[0302] The emotion engine embedded in the server analyzes the user's biometric data, voice, and facial expressions to recognize their current emotional state. Based on this data, it adjusts the visual, auditory, and other elements of the virtual reality space to match the user's emotions, personalizing the user experience.

[0303] Specific example

[0304] For example, when a user wants to relive the memories of a trip, they can upload a photo album to the system to reproduce the travel destination within the virtual reality space. When the emotion engine detects the user's smiling face or happy voice, it adjusts the colors and music in that virtual world to be brighter and have a happy resonance. Conversely, when an emotion of wanting to be calm and healed is recognized, the light intensity in the virtual space is reduced to create a quiet and relaxing environment. In this way, the user can enjoy a more personalized immersive experience.

[0305] The following describes the processing flow.

[0306] Step 1:

[0307] The user accesses the system via the terminal and selects the photos or videos they want to experience. The terminal uploads the selected files to the server.

[0308] Step 2:

[0309] The server temporarily stores the received data and prepares for analysis processing. It checks the format and quality of the data and passes it to the generation AI module.

[0310] Step 3:

[0311] The generation AI module in the server analyzes the data and extracts the three-dimensional information of the objects and backgrounds in the image. Furthermore, in the case of video data, motion analysis is performed to generate a dynamic three-dimensional model.

[0312] Step 4:

[0313] The server formats the three-dimensional space information and dynamic model generated by it for the metaverse and sends it to the metaverse server. The metaverse server constructs the virtual reality space based on these data.

[0314] Step 5:

[0315] The server analyzes voice and facial expression data collected from the user's device through an emotion engine to recognize the user's emotional state. The device uses sensors and cameras to acquire the necessary data for this purpose.

[0316] Step 6:

[0317] The metaverse server dynamically adjusts the visual and auditory settings of the virtual reality space according to the user's emotions, based on emotion data obtained from the server. This allows the user to experience a personalized space.

[0318] Step 7:

[0319] Users enter a virtual reality space using a VR device on their device and explore a constructed three-dimensional model and a space adjusted based on emotions. Users can interactively manipulate the space and re-experience past memories emotionally and visually.

[0320] (Example 2)

[0321] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0322] Traditional virtual environment systems have the drawback of not considering the emotional state of the user, thus failing to provide an optimized experience for each individual user. Furthermore, the reproduction of dynamic objects within the virtual space is difficult, sometimes limiting the user experience. In addition, users cannot freely adjust various viewpoints, resulting in insufficient interactivity in the virtual environment.

[0323] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0324] In this invention, the server includes means for analyzing image and video data and generating three-dimensional spatial information; means for acquiring user emotion information and adjusting the virtual environment according to the user's emotional state; means for analyzing the movement of objects in images and dynamically reproducing them within the virtual environment; and means for adjusting the display of the virtual environment from different times or viewpoints. This makes it possible to provide a personalized experience tailored to the user's emotions and realize a dynamic and interactive virtual space.

[0325] "Image and video data" refers to visual information acquired by cameras and recording devices, including still images and video.

[0326] "Analysis" refers to processing acquired data and performing calculations and operations to extract or understand necessary information.

[0327] "Three-dimensional spatial data" refers to a dataset containing information for representing real or virtual space in three dimensions, capable of representing the position, shape, and movement of objects.

[0328] A "virtual environment" refers to an artificial and interactive space created by a computer that a user can experience through sight, sound, and other senses.

[0329] "User" refers to an individual who experiences a virtual environment through this system.

[0330] "Emotional information" refers to data that indicates the user's biological and psychological state, and is obtained from facial expressions, voice tone, biosignals, etc.

[0331] "Dynamic reproduction" refers to making objects and scenes change moment by moment for the user, enabling real-time interaction.

[0332] "Adjusting the display" means changing the viewpoint and content on the screen according to the user's instructions or environment, in order to provide the optimal visual experience.

[0333] This system realizes a virtual environment through collaborative operation between users, terminals, and servers. Users upload photos and video data via their terminals, which then send this data to the server. The server analyzes the data using a generative AI model and generates three-dimensional spatial data. Specifically, it utilizes deep learning technology for image recognition and reconstructs detailed spatial features. The hardware used should be a server equipped with a high-performance GPU, and the software should include machine learning frameworks.

[0334] The generated 3D model is sent to a metaverse server and constructed as a virtual environment. Users can access this virtual environment using a VR device connected to their terminal. The emotion engine acquires the user's biometric data, for example, through a camera and microphone, and analyzes their emotional state in real time. Based on these emotions, the server dynamically adjusts the visual and auditory information of the virtual environment to provide a personalized experience.

[0335] As a concrete example, suppose a user wants to relive a past trip. In this case, uploading a photo album to the system recreates the travel destination in a virtual space. When the emotion engine recognizes that the user is enjoying themselves from their facial expressions, the colors and music in the virtual space are adjusted to be brighter. Also, when the user wants to relax, the scenery changes to something quiet and peaceful.

[0336] An example of a prompt message is, "Recreate travel memories and provide a virtual environment that reflects the user's current emotions."

[0337] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0338] Step 1:

[0339] Users upload photos and video data to the system via their device. Specifically, they select data files using the device's interface and click the upload button. This action causes the device to collect the selected data and prepare it for transmission to the server for the next processing step. The input is the photos and video data selected by the user, and the output is the data securely transmitted to the server.

[0340] Step 2:

[0341] The device sends the uploaded data to the server. To ensure data security, the communication is encrypted using the SSL / TLS protocol. The server verifies the integrity of the received data and stores it in a database. The input is the encrypted data sent from the device, and the output is the raw data stored in the database.

[0342] Step 3:

[0343] The server inputs data stored in the database into a generating AI model to create three-dimensional spatial information. During this process, the AI ​​model uses deep learning techniques to analyze images and identify the movement and shape of objects in the video. This creates a dynamic three-dimensional model. The input is image and video data, and the output is the generated three-dimensional spatial data.

[0344] Step 4:

[0345] The server sends the generated three-dimensional spatial data to the metaverse server, which then prepares it for reconstruction as a virtual environment. The metaverse server builds the virtual environment based on the received data and makes it available to the user. The input is three-dimensional spatial data, and the output is a dataset with the virtual environment completed.

[0346] Step 5:

[0347] The user accesses a virtual environment using a VR device. Here, the server's emotion engine analyzes the user's biometric data and adjusts the visual and auditory elements of the virtual environment based on their emotional state in real time. The input is the user's biometric data, and the output is the adjusted visual and auditory elements of the virtual environment.

[0348] Step 6:

[0349] Users experience a virtual environment tailored to their emotions. For example, when recreating travel memories, if the emotion engine determines that the user is enjoying themselves, bright and cheerful colors and music will be provided. The input is the user's emotional state based on the emotion engine's output, and the output is a personalized virtual environment.

[0350] (Application Example 2)

[0351] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0352] While virtual reality spaces are a technology that provides users with a sense of immersion, they lack sufficient consistency with the real world and personalization that takes into account individual user experiences. Furthermore, they lack the functionality to adjust the virtual space in response to changes in emotions. This invention aims to integrate the user's real environment with the virtual space and provide individualized visual and auditory experiences based on emotions.

[0353] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0354] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired image and video data and generating three-dimensional spatial information, means for reconstructing the generated three-dimensional spatial information in a virtual reality space, and means for recognizing the user's emotions and adjusting the visual and auditory elements of the virtual reality space. This enables a personalized, immersive virtual experience based on the user's actual environment and emotional state.

[0355] "Image and video data" refers to photos and videos provided by users, and is fundamental information for constructing the virtual reality space.

[0356] "Three-dimensional spatial information" refers to a three-dimensional digital representation generated based on acquired image and video data, and is a component of virtual reality space.

[0357] A "virtual reality space" is a digital virtual environment constructed based on three-dimensional spatial information, providing users with a sense of immersion.

[0358] "Means of recognizing user emotions" refers to a function that analyzes biometric data, voice, and facial expressions to determine the emotional state the user is experiencing.

[0359] "Means for adjusting visual and auditory elements" refers to functions that dynamically change the images and sounds of the virtual reality space based on the perceived emotions of the user, thereby optimizing the user experience.

[0360] "Means of integrating the user's real environment with the virtual space" refers to technology that overlays a virtual reality space onto the user's current physical environment, thereby achieving a unification of reality and virtuality.

[0361] In the system implementing this invention, the user uploads image and video data to a server using a terminal such as a smartphone or smart glasses. The server receives this data and generates three-dimensional spatial information using a generative AI model. In this process, AI technology for image analysis (e.g., computer vision technology) is utilized to analyze the movement of objects in the video, thereby constructing a dynamic three-dimensional model.

[0362] The constructed three-dimensional model is reconstructed within the virtual reality space. Specifically, a server manages this data and presents it visually to the user's terminal via a VR device. During this process, an emotion analysis engine (e.g., emotion recognition software) analyzes biometric data, voice, and facial expressions to recognize the user's emotions. Based on this, the visual and auditory elements within the virtual reality space are adjusted to transform the environment to suit the user's emotions.

[0363] For example, if a user wants to relive memories of a past trip, they upload a photo album from their device to the system. Based on this data, the travel destination is recreated in a virtual reality space. When the emotion analysis engine detects joy as the user's emotion, the system adjusts the colors and music in the virtual space to make it a happier experience.

[0364] An example of a prompt message might be, "Overlay a virtual historical cityscape based on photographs onto reality, and interactively adjust the experience according to the user's emotions." This allows users to enjoy a personalized virtual experience.

[0365] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0366] Step 1:

[0367] The user uploads images and video data captured using their device. The input consists of image and video files. Once the data is sent from the user to the server, the following processing becomes possible.

[0368] Step 2:

[0369] The server analyzes the image and video data it receives. This analysis uses a generative AI model and image recognition technology. The input is image and video data from the user, and the output is analyzed three-dimensional spatial information. Based on this data, the server calculates the three-dimensional structure and generates a three-dimensional model that includes dynamic elements.

[0370] Step 3:

[0371] Using the generated three-dimensional spatial information, the server constructs a virtual reality space. The input is the analyzed three-dimensional spatial information, and the output is the virtual reality space itself. The server prepares the virtual environment as visual data and sends it to the user's VR terminal.

[0372] Step 4:

[0373] The user accesses the constructed virtual reality space using a VR device on their device. The input in this step is visual data sent from the server, and the output is the 3D virtual space experienced by the user. The device projects the visual data onto the VR device, providing the user with an immersive experience.

[0374] Step 5:

[0375] The server analyzes the user's biometric data and recognizes emotions using an emotion analysis engine. Input is the user's biosensor data and voice data, and output is the user's emotional state. Based on this emotional information, the server adjusts the visual and auditory elements within the virtual reality space.

[0376] Step 6:

[0377] A personalized experience is provided based on the user's emotions. The server sends adjusted environmental data to the user's device, and the device modifies the characteristics of the virtual space according to the user's emotions. This enables a real-time interactive experience.

[0378] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0379] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0380] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0381] [Third Embodiment]

[0382] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0383] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0384] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0385] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0386] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0387] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0388] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0389] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0390] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0391] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0392] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0393] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0394] The following program and system configuration are provided as specific embodiments of the present invention.

[0395] Data acquisition and analysis

[0396] First, the user uploads photos and videos they have taken to the system through a dedicated interface. The terminal sends the selected data to the server. The server stores the received data and begins analysis by the generative AI module. Based on the received data, the generative AI recognizes objects and landscapes in the image and reconstructs them as three-dimensional spatial information.

[0397] Building a virtual reality space

[0398] The server constructs a virtual reality space using the generated three-dimensional spatial information and the analyzed motion data of the objects. This information is then reflected in the virtual environment on the metaverse server, and prepared in a form that users can experience.

[0399] Providing a user experience

[0400] The device accesses the constructed virtual reality space and provides the user with that experience. Using a VR device on the device, the user can recreate and relive past memories by becoming immersed in the virtual reality space. Furthermore, they can freely change their viewpoint and time within the metaverse, enabling them to gain new visual experiences.

[0401] Specific example

[0402] For example, consider a scenario where a user uploads a video they recorded of their child's growth to the system. The server analyzes the child's movements in the video and generates a three-dimensional model. By placing this model in a virtual reality space, the user can experience what it was like to be present at that moment. In this process, the child's movements and facial expressions are dynamically reproduced, making past events feel more realistic.

[0403] In this way, the present invention provides a means to virtually extend the static video assets that users possess, allowing them to enjoy them in a more emotionally rich and intuitive way.

[0404] The following describes the processing flow.

[0405] Step 1:

[0406] The user logs into the system on their device, selects and uploads photos and video data. The device then sends the selected data to the server.

[0407] Step 2:

[0408] The server temporarily stores the received data and adds it to a queue awaiting analysis. The data is checked to ensure reliability and security.

[0409] Step 3:

[0410] The generation AI module on the server sequentially retrieves the stored data and analyzes the image and video data. The generation AI uses image analysis algorithms to perform object detection, boundary extraction, pose estimation, and other operations from the data to generate three-dimensional spatial information.

[0411] Step 4:

[0412] The server uses the generated three-dimensional spatial information to create 3D models and animation data. This data is then converted into a format usable in the virtual reality space.

[0413] Step 5:

[0414] The server sends the generated model data to the metaverse server, where it is integrated into the virtual reality space. The metaverse server then prepares to reflect this data in the virtual space.

[0415] Step 6:

[0416] The user accesses the metaverse space from their device and explores the virtual reality space using VR equipment. The device connects to the metaverse server and displays a 3D model to the user in real time.

[0417] Step 7:

[0418] Users can interactively manipulate the virtual reality space, adjusting their viewpoint and time to obtain different visual experiences. The device reflects these actions in the metaverse space, instantly changing the display.

[0419] (Example 1)

[0420] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0421] Traditional image and video data only allowed for static playback, making it difficult for users to experience past moments with a sense of presence. Furthermore, user manipulation of viewpoint and time was limited, preventing the provision of new, immersive experiences.

[0422] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0423] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired data and generating three-dimensional spatial information, means for reconstructing it in a virtual reality space, means for presenting the virtual reality space to the user, means for changing the viewpoint and time based on the user's instructions, and means for analyzing the data using a generation AI model and automatically generating three-dimensional spatial information. As a result, the user can experience the virtual reality space with a dynamic and free viewpoint, making past events feel more real.

[0424] "Image data" refers to visual information represented in a digital format.

[0425] "Video data" refers to the digital representation of moving images and videos.

[0426] "Means of acquisition" refers to the devices and methods used to capture data.

[0427] "Means of analysis" refers to methods and devices for analyzing data and extracting necessary information.

[0428] "Three-dimensional spatial information" refers to information generated from data that has three dimensions: length, width, and depth.

[0429] A "virtual reality space" is an artificial three-dimensional environment generated by a computer.

[0430] "Means of reconstruction" refers to methods or devices for creating a new structure based on the original data.

[0431] "Means of presentation" refers to methods or devices used to show information to the recipient.

[0432] "User instructions" refers to operations or commands given by the user.

[0433] A "generative AI model" is an artificial intelligence model that automatically processes and analyzes data to output specific results.

[0434] This invention is a system that constructs a virtual reality space based on static image and video data owned by the user, allowing them to recreate and experience past events. Specific embodiments of this system are shown below.

[0435] Users upload image and video data to the system via a dedicated interface. The terminal sends this data to the server for secure storage. The server inputs the data into a generating AI model (for example, an image analysis module provided by a specific AI provider) and performs image recognition and video analysis. This analysis recognizes objects and landscapes within the data and reconstructs them as three-dimensional spatial information.

[0436] The server constructs a virtual reality space based on the obtained three-dimensional information. This process utilizes game engines such as Unity and Unreal Engine. Through these engines, visual data is realistically reproduced, creating a virtual environment that users can experience.

[0437] This system can be used in the following specific example: A user enters a prompt message regarding a video recording of their child's growth, such as, "Create a 3D model of my child's birthday party video and recreate it in a virtual reality space." Based on this request, the server analyzes the video and generates a virtual environment that recreates the child's movements, surroundings, and facial expressions. The terminal sends this to the user's VR device, allowing the user to relive past events in that virtual space.

[0438] In this way, the system provides users with a means to virtually extend past static video assets and experience them in an emotionally rich manner. By utilizing generative AI models, it can efficiently analyze image and video data and generate three-dimensional spatial information, providing users with an innovative experience.

[0439] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0440] Step 1:

[0441] Users select and upload image and video data using a dedicated interface. The terminal receives this selected data as input and sends it to the server using a data transfer protocol. Specifically, the user presses the "upload" button, the terminal checks the file format and size, compresses it, and sends it to the server.

[0442] Step 2:

[0443] The server stores the data received from the terminal in its storage system. As preparation for data analysis, it performs preprocessing to pass the data to the generating AI model. Specifically, this includes format verification, filtering of abnormal data, and adding metadata. At this stage, the input is a raw data file, and the output is in a parseable data format.

[0444] Step 3:

[0445] The server analyzes received data using a generative AI model and generates three-dimensional spatial information. The input is pre-processed data, and the generative AI model recognizes and labels objects in images and videos, and reconstructs them into three-dimensional information. Specifically, the AI ​​model extracts feature points from images and generates a three-dimensional point cloud using deep learning technology. The output is the reconstructed three-dimensional spatial information.

[0446] Step 4:

[0447] The server uses the generated three-dimensional spatial information to construct a virtual reality space. Using a game engine, it creates a real-time visual space and adds visual and lighting effects. Three-dimensional spatial information is provided as input, and the output is the data of the virtual reality space experienced by the user. Specifically, this involves the server executing engine scripts and placing objects within the virtual space.

[0448] Step 5:

[0449] The terminal displays virtual reality data received from the server, providing the user with an experience. The user immerses themselves in the virtual space using a VR device and can freely change their viewpoint and time based on input data from the server. Specific operations include visual updates using the terminal's rendering device and interaction processing through a control device. The output is the virtual environment that the user visually experiences.

[0450] (Application Example 1)

[0451] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0452] In modern content distribution services, users often reminisce about past memories using static video assets, but this experience is visually limited. There is a need for users to re-experience past memories in a more intuitive and emotionally rich way, but traditional methods cannot adequately meet this need.

[0453] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0454] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired image and video data and generating shared space information, and means for reconstructing the generated shared space information within a virtual environment. This enables users to obtain a realistic and immersive visual experience based on static video assets.

[0455] "Image and video data" refers to digital information in still image and video formats, including visual media captured or collected by the user.

[0456] "Shared spatial information" refers to three-dimensional digital information generated from analyzed image and video data, and is used to construct virtual environments.

[0457] A "virtual environment" refers to a three-dimensional space created using digital technology, an immersive simulation space that users can experience visually.

[0458] "Means of providing a visual experience" refers to technologies or devices for visually reproducing and presenting generated content within a virtual environment to a user.

[0459] The system for realizing this application consists of a user terminal, a server, and a VR device. The user uploads captured images and video data to the server via the terminal. The server receives this data, analyzes it using a generative AI model, and generates shared spatial information. Specifically, the server constructs a three-dimensional space using generative AI tools such as Stable Diffusion and DALL-E.

[0460] Next, the server reconstructs the constructed shared space information as a virtual environment and provides it to the user. The user can access the virtual environment and enjoy the visual experience using VR devices such as head-mounted displays. Google Cloud or AWS is used as the meta-platform for this process.

[0461] As a concrete example, suppose a user uploads photos and videos of a special day spent with their family. Based on this data, the server virtually recreates the space where the family gathered and the atmosphere of that day, allowing the user to move through it and experience it as if they were back in that moment.

[0462] An example of a prompt for the generative AI model would be, "Please realistically recreate my child's birthday party in a 3D virtual space." This allows users to richly recreate past experiences while fostering a deeper emotional connection.

[0463] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0464] Step 1:

[0465] The user uploads images and video data captured using their device to the server. The input is media files stored on the user's local device, and the output is the transfer and storage of this data on the server. Specifically, the user operates a file selection interface, selects multiple files, and begins the upload.

[0466] Step 2:

[0467] The server receives uploaded image and video data and performs analysis using a generative AI model. The input is the media data received in step 1, and the output is the three-dimensional spatial information obtained through the analysis. Stable Diffusion and DALL-E are used for this process. The server inputs prompt messages to the AI ​​model, giving instructions in the form of "Generate a three-dimensional space from this image."

[0468] Step 3:

[0469] The server reconstructs the virtual environment based on the generated three-dimensional spatial information. The input is the shared spatial information generated in step 2, and the output is the virtual environment data that the user can experience. To reconstruct this data, the server uses a 3D rendering engine to prepare the virtual reality space.

[0470] Step 4:

[0471] The server sends the reconstructed virtual environment to the user's terminal. The input is the virtual environment data completed in step 3, and the output is data converted into a format that can be visually experienced on the user's VR device. Specifically, the server sends this data in stream format, enabling real-time display on the user's VR device.

[0472] Step 5:

[0473] The user wears a VR device and experiences a virtual environment. The input is the virtual environment data received from the server in step 4, and the output is the user's immersive experience. The user uses a controller or eye-tracking controls to change their viewpoint and the time of day within the virtual space, allowing them to recreate and enjoy past memories in a three-dimensional and dynamic way.

[0474] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0475] This invention provides a more personalized experience by incorporating an emotion engine that recognizes user emotions, in addition to a system that generates a three-dimensional space based on image and video data and provides that experience within a virtual reality space. The details are described below through examples.

[0476] Data acquisition and analysis

[0477] Users upload photos and video data to the system via their devices. The devices send this data to a server, which then uses a generation AI module to generate three-dimensional spatial information. This process also analyzes the movement of objects within the video and reconstructs them as dynamic three-dimensional models.

[0478] Creation and presentation of virtual reality spaces

[0479] The server sends the 3D model and dynamic data it generates to the metaverse server. The metaverse server constructs a virtual reality space based on the received data and prepares to provide that space to the user. The user can then use a VR device on their terminal to enter the virtual space and enjoy the visual experience.

[0480] Personalization powered by an emotion engine

[0481] The emotion engine embedded in the server analyzes the user's biometric data, voice, and facial expressions to recognize their current emotional state. Based on this data, it adjusts the visual, auditory, and other elements of the virtual reality space to match the user's emotions, personalizing the user experience.

[0482] Specific example

[0483] For example, if a user wants to relive a travel memory, they can upload a photo album to the system, recreating that travel destination in a virtual reality space. If the emotion engine detects the user's smile or cheerful voice, it adjusts the colors and music of the virtual world to be brighter and more harmonious. Conversely, if a calm and soothing emotion is recognized, the lighting in the virtual space is reduced, creating a quiet and relaxing environment. In this way, users can enjoy a more personalized and immersive experience.

[0484] The following describes the processing flow.

[0485] Step 1:

[0486] The user accesses the system via their device and selects the photos or videos they want to experience. The device then uploads the selected files to the server.

[0487] Step 2:

[0488] The server temporarily stores the received data and prepares it for analysis. It checks the data format and quality and then passes it on to the generating AI module.

[0489] Step 3:

[0490] The AI ​​generation module on the server analyzes the data and extracts three-dimensional information about objects and backgrounds within the image. Furthermore, in the case of video data, it performs motion analysis and generates a dynamic three-dimensional model.

[0491] Step 4:

[0492] The server formats the three-dimensional spatial information and dynamic model it generates for the metaverse and sends it to the metaverse server. The metaverse server then constructs a virtual reality space based on this data.

[0493] Step 5:

[0494] The server analyzes voice and facial expression data collected from the user's device through an emotion engine to recognize the user's emotional state. The device uses sensors and cameras to acquire the necessary data for this purpose.

[0495] Step 6:

[0496] The metaverse server dynamically adjusts the visual and auditory settings of the virtual reality space according to the user's emotions, based on emotion data obtained from the server. This allows the user to experience a personalized space.

[0497] Step 7:

[0498] Users enter a virtual reality space using a VR device on their device and explore a constructed three-dimensional model and a space adjusted based on emotions. Users can interactively manipulate the space and re-experience past memories emotionally and visually.

[0499] (Example 2)

[0500] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0501] Traditional virtual environment systems have the drawback of not considering the emotional state of the user, thus failing to provide an optimized experience for each individual user. Furthermore, the reproduction of dynamic objects within the virtual space is difficult, sometimes limiting the user experience. In addition, users cannot freely adjust various viewpoints, resulting in insufficient interactivity in the virtual environment.

[0502] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0503] In this invention, the server includes means for analyzing image and video data and generating three-dimensional spatial information; means for acquiring user emotion information and adjusting the virtual environment according to the user's emotional state; means for analyzing the movement of objects in images and dynamically reproducing them within the virtual environment; and means for adjusting the display of the virtual environment from different times or viewpoints. This makes it possible to provide a personalized experience tailored to the user's emotions and realize a dynamic and interactive virtual space.

[0504] "Image and video data" refers to visual information acquired by cameras and recording devices, including still images and video.

[0505] "Analysis" refers to processing acquired data and performing calculations and operations to extract or understand necessary information.

[0506] "Three-dimensional spatial data" refers to a dataset containing information for representing real or virtual space in three dimensions, capable of representing the position, shape, and movement of objects.

[0507] A "virtual environment" refers to an artificial and interactive space created by a computer that a user can experience through sight, sound, and other senses.

[0508] "User" refers to an individual who experiences a virtual environment through this system.

[0509] "Emotional information" refers to data that indicates the user's biological and psychological state, and is obtained from facial expressions, voice tone, biosignals, etc.

[0510] "Dynamic reproduction" refers to making objects and scenes change moment by moment for the user, enabling real-time interaction.

[0511] "Adjusting the display" means changing the viewpoint and content on the screen according to the user's instructions or environment, in order to provide the optimal visual experience.

[0512] This system realizes a virtual environment through collaborative operation between users, terminals, and servers. Users upload photos and video data via their terminals, which then send this data to the server. The server analyzes the data using a generative AI model and generates three-dimensional spatial data. Specifically, it utilizes deep learning technology for image recognition and reconstructs detailed spatial features. The hardware used should be a server equipped with a high-performance GPU, and the software should include machine learning frameworks.

[0513] The generated 3D model is sent to a metaverse server and constructed as a virtual environment. Users can access this virtual environment using a VR device connected to their terminal. The emotion engine acquires the user's biometric data, for example, through a camera and microphone, and analyzes their emotional state in real time. Based on these emotions, the server dynamically adjusts the visual and auditory information of the virtual environment to provide a personalized experience.

[0514] As a concrete example, suppose a user wants to relive a past trip. In this case, uploading a photo album to the system recreates the travel destination in a virtual space. When the emotion engine recognizes that the user is enjoying themselves from their facial expressions, the colors and music in the virtual space are adjusted to be brighter. Also, when the user wants to relax, the scenery changes to something quiet and peaceful.

[0515] An example of a prompt message is, "Recreate travel memories and provide a virtual environment that reflects the user's current emotions."

[0516] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0517] Step 1:

[0518] Users upload photos and video data to the system via their device. Specifically, they select data files using the device's interface and click the upload button. This action causes the device to collect the selected data and prepare it for transmission to the server for the next processing step. The input is the photos and video data selected by the user, and the output is the data securely transmitted to the server.

[0519] Step 2:

[0520] The device sends the uploaded data to the server. To ensure data security, the communication is encrypted using the SSL / TLS protocol. The server verifies the integrity of the received data and stores it in a database. The input is the encrypted data sent from the device, and the output is the raw data stored in the database.

[0521] Step 3:

[0522] The server inputs data stored in the database into a generating AI model to create three-dimensional spatial information. During this process, the AI ​​model uses deep learning techniques to analyze images and identify the movement and shape of objects in the video. This creates a dynamic three-dimensional model. The input is image and video data, and the output is the generated three-dimensional spatial data.

[0523] Step 4:

[0524] The server sends the generated three-dimensional spatial data to the metaverse server, which then prepares it for reconstruction as a virtual environment. The metaverse server builds the virtual environment based on the received data and makes it available to the user. The input is three-dimensional spatial data, and the output is a dataset with the virtual environment completed.

[0525] Step 5:

[0526] The user accesses a virtual environment using a VR device. Here, the server's emotion engine analyzes the user's biometric data and adjusts the visual and auditory elements of the virtual environment based on their emotional state in real time. The input is the user's biometric data, and the output is the adjusted visual and auditory elements of the virtual environment.

[0527] Step 6:

[0528] Users experience a virtual environment tailored to their emotions. For example, when recreating travel memories, if the emotion engine determines that the user is enjoying themselves, bright and cheerful colors and music will be provided. The input is the user's emotional state based on the emotion engine's output, and the output is a personalized virtual environment.

[0529] (Application Example 2)

[0530] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0531] While virtual reality spaces are a technology that provides users with a sense of immersion, they lack sufficient consistency with the real world and personalization that takes into account individual user experiences. Furthermore, they lack the functionality to adjust the virtual space in response to changes in emotions. This invention aims to integrate the user's real environment with the virtual space and provide individualized visual and auditory experiences based on emotions.

[0532] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0533] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired image and video data and generating three-dimensional spatial information, means for reconstructing the generated three-dimensional spatial information in a virtual reality space, and means for recognizing the user's emotions and adjusting the visual and auditory elements of the virtual reality space. This enables a personalized, immersive virtual experience based on the user's actual environment and emotional state.

[0534] "Image and video data" refers to photos and videos provided by users, and is fundamental information for constructing the virtual reality space.

[0535] "Three-dimensional spatial information" refers to a three-dimensional digital representation generated based on acquired image and video data, and is a component of virtual reality space.

[0536] A "virtual reality space" is a digital virtual environment constructed based on three-dimensional spatial information, providing users with a sense of immersion.

[0537] "Means of recognizing user emotions" refers to a function that analyzes biometric data, voice, and facial expressions to determine the emotional state the user is experiencing.

[0538] "Means for adjusting visual and auditory elements" refers to functions that dynamically change the images and sounds of the virtual reality space based on the perceived emotions of the user, thereby optimizing the user experience.

[0539] "Means of integrating the user's real environment with the virtual space" refers to technology that overlays a virtual reality space onto the user's current physical environment, thereby achieving a unification of reality and virtuality.

[0540] In the system implementing this invention, the user uploads image and video data to a server using a terminal such as a smartphone or smart glasses. The server receives this data and generates three-dimensional spatial information using a generative AI model. In this process, AI technology for image analysis (e.g., computer vision technology) is utilized to analyze the movement of objects in the video, thereby constructing a dynamic three-dimensional model.

[0541] The constructed three-dimensional model is reconstructed within the virtual reality space. Specifically, a server manages this data and presents it visually to the user's terminal via a VR device. During this process, an emotion analysis engine (e.g., emotion recognition software) analyzes biometric data, voice, and facial expressions to recognize the user's emotions. Based on this, the visual and auditory elements within the virtual reality space are adjusted to transform the environment to suit the user's emotions.

[0542] For example, if a user wants to relive memories of a past trip, they upload a photo album from their device to the system. Based on this data, the travel destination is recreated in a virtual reality space. When the emotion analysis engine detects joy as the user's emotion, the system adjusts the colors and music in the virtual space to make it a happier experience.

[0543] An example of a prompt message might be, "Overlay a virtual historical cityscape based on photographs onto reality, and interactively adjust the experience according to the user's emotions." This allows users to enjoy a personalized virtual experience.

[0544] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0545] Step 1:

[0546] The user uploads images and video data captured using their device. The input consists of image and video files. Once the data is sent from the user to the server, the following processing becomes possible.

[0547] Step 2:

[0548] The server analyzes the image and video data it receives. This analysis uses a generative AI model and image recognition technology. The input is image and video data from the user, and the output is analyzed three-dimensional spatial information. Based on this data, the server calculates the three-dimensional structure and generates a three-dimensional model that includes dynamic elements.

[0549] Step 3:

[0550] Using the generated three-dimensional spatial information, the server constructs a virtual reality space. The input is the analyzed three-dimensional spatial information, and the output is the virtual reality space itself. The server prepares the virtual environment as visual data and sends it to the user's VR terminal.

[0551] Step 4:

[0552] The user accesses the constructed virtual reality space using a VR device on their device. The input in this step is visual data sent from the server, and the output is the 3D virtual space experienced by the user. The device projects the visual data onto the VR device, providing the user with an immersive experience.

[0553] Step 5:

[0554] The server analyzes the user's biometric data and recognizes emotions using an emotion analysis engine. Input is the user's biosensor data and voice data, and output is the user's emotional state. Based on this emotional information, the server adjusts the visual and auditory elements within the virtual reality space.

[0555] Step 6:

[0556] A personalized experience is provided based on the user's emotions. The server sends adjusted environmental data to the user's device, and the device modifies the characteristics of the virtual space according to the user's emotions. This enables a real-time interactive experience.

[0557] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0558] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0559] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0560] [Fourth Embodiment]

[0561] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0562] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0563] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0564] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0565] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0566] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0567] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0568] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0569] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0570] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0571] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0572] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0573] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0574] The following program and system configuration are provided as specific embodiments of the present invention.

[0575] Data acquisition and analysis

[0576] First, the user uploads photos and videos they have taken to the system through a dedicated interface. The terminal sends the selected data to the server. The server stores the received data and begins analysis by the generative AI module. Based on the received data, the generative AI recognizes objects and landscapes in the image and reconstructs them as three-dimensional spatial information.

[0577] Building a virtual reality space

[0578] The server constructs a virtual reality space using the generated three-dimensional spatial information and the analyzed motion data of the objects. This information is then reflected in the virtual environment on the metaverse server, and prepared in a form that users can experience.

[0579] Providing a user experience

[0580] The device accesses the constructed virtual reality space and provides the user with that experience. Using a VR device on the device, the user can recreate and relive past memories by becoming immersed in the virtual reality space. Furthermore, they can freely change their viewpoint and time within the metaverse, enabling them to gain new visual experiences.

[0581] Specific example

[0582] For example, consider a scenario where a user uploads a video they recorded of their child's growth to the system. The server analyzes the child's movements in the video and generates a three-dimensional model. By placing this model in a virtual reality space, the user can experience what it was like to be present at that moment. In this process, the child's movements and facial expressions are dynamically reproduced, making past events feel more realistic.

[0583] In this way, the present invention provides a means to virtually extend the static video assets that users possess, allowing them to enjoy them in a more emotionally rich and intuitive way.

[0584] The following describes the processing flow.

[0585] Step 1:

[0586] The user logs into the system on their device, selects and uploads photos and video data. The device then sends the selected data to the server.

[0587] Step 2:

[0588] The server temporarily stores the received data and adds it to a queue awaiting analysis. The data is checked to ensure reliability and security.

[0589] Step 3:

[0590] The generation AI module on the server sequentially retrieves the stored data and analyzes the image and video data. The generation AI uses image analysis algorithms to perform object detection, boundary extraction, pose estimation, and other operations from the data to generate three-dimensional spatial information.

[0591] Step 4:

[0592] The server uses the generated three-dimensional spatial information to create 3D models and animation data. This data is then converted into a format usable in the virtual reality space.

[0593] Step 5:

[0594] The server sends the generated model data to the metaverse server, where it is integrated into the virtual reality space. The metaverse server then prepares to reflect this data in the virtual space.

[0595] Step 6:

[0596] The user accesses the metaverse space from their device and explores the virtual reality space using VR equipment. The device connects to the metaverse server and displays a 3D model to the user in real time.

[0597] Step 7:

[0598] Users can interactively manipulate the virtual reality space, adjusting their viewpoint and time to obtain different visual experiences. The device reflects these actions in the metaverse space, instantly changing the display.

[0599] (Example 1)

[0600] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0601] Traditional image and video data only allowed for static playback, making it difficult for users to experience past moments with a sense of presence. Furthermore, user manipulation of viewpoint and time was limited, preventing the provision of new, immersive experiences.

[0602] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0603] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired data and generating three-dimensional spatial information, means for reconstructing it in a virtual reality space, means for presenting the virtual reality space to the user, means for changing the viewpoint and time based on the user's instructions, and means for analyzing the data using a generation AI model and automatically generating three-dimensional spatial information. As a result, the user can experience the virtual reality space with a dynamic and free viewpoint, making past events feel more real.

[0604] "Image data" refers to visual information represented in a digital format.

[0605] "Video data" refers to the digital representation of moving images and videos.

[0606] "Means of acquisition" refers to the devices and methods used to capture data.

[0607] "Means of analysis" refers to methods and devices for analyzing data and extracting necessary information.

[0608] "Three-dimensional spatial information" refers to information generated from data that has three dimensions: length, width, and depth.

[0609] A "virtual reality space" is an artificial three-dimensional environment generated by a computer.

[0610] "Means of reconstruction" refers to methods or devices for creating a new structure based on the original data.

[0611] "Means of presentation" refers to methods or devices used to show information to the recipient.

[0612] "User instructions" refers to operations or commands given by the user.

[0613] A "generative AI model" is an artificial intelligence model that automatically processes and analyzes data to output specific results.

[0614] This invention is a system that constructs a virtual reality space based on static image and video data owned by the user, allowing them to recreate and experience past events. Specific embodiments of this system are shown below.

[0615] Users upload image and video data to the system via a dedicated interface. The terminal sends this data to the server for secure storage. The server inputs the data into a generating AI model (for example, an image analysis module provided by a specific AI provider) and performs image recognition and video analysis. This analysis recognizes objects and landscapes within the data and reconstructs them as three-dimensional spatial information.

[0616] The server constructs a virtual reality space based on the obtained three-dimensional information. This process utilizes game engines such as Unity and Unreal Engine. Through these engines, visual data is realistically reproduced, creating a virtual environment that users can experience.

[0617] This system can be used in the following specific example: A user enters a prompt message regarding a video recording of their child's growth, such as, "Create a 3D model of my child's birthday party video and recreate it in a virtual reality space." Based on this request, the server analyzes the video and generates a virtual environment that recreates the child's movements, surroundings, and facial expressions. The terminal sends this to the user's VR device, allowing the user to relive past events in that virtual space.

[0618] In this way, the system provides users with a means to virtually extend past static video assets and experience them in an emotionally rich manner. By utilizing generative AI models, it can efficiently analyze image and video data and generate three-dimensional spatial information, providing users with an innovative experience.

[0619] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0620] Step 1:

[0621] Users select and upload image and video data using a dedicated interface. The terminal receives this selected data as input and sends it to the server using a data transfer protocol. Specifically, the user presses the "upload" button, the terminal checks the file format and size, compresses it, and sends it to the server.

[0622] Step 2:

[0623] The server stores the data received from the terminal in its storage system. As preparation for data analysis, it performs preprocessing to pass the data to the generating AI model. Specifically, this includes format verification, filtering of abnormal data, and adding metadata. At this stage, the input is a raw data file, and the output is in a parseable data format.

[0624] Step 3:

[0625] The server analyzes received data using a generative AI model and generates three-dimensional spatial information. The input is pre-processed data, and the generative AI model recognizes and labels objects in images and videos, and reconstructs them into three-dimensional information. Specifically, the AI ​​model extracts feature points from images and generates a three-dimensional point cloud using deep learning technology. The output is the reconstructed three-dimensional spatial information.

[0626] Step 4:

[0627] The server uses the generated three-dimensional spatial information to construct a virtual reality space. Using a game engine, it creates a real-time visual space and adds visual and lighting effects. Three-dimensional spatial information is provided as input, and the output is the data of the virtual reality space experienced by the user. Specifically, this involves the server executing engine scripts and placing objects within the virtual space.

[0628] Step 5:

[0629] The terminal displays virtual reality data received from the server, providing the user with an experience. The user immerses themselves in the virtual space using a VR device and can freely change their viewpoint and time based on input data from the server. Specific operations include visual updates using the terminal's rendering device and interaction processing through a control device. The output is the virtual environment that the user visually experiences.

[0630] (Application Example 1)

[0631] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0632] In modern content distribution services, users often reminisce about past memories using static video assets, but this experience is visually limited. There is a need for users to re-experience past memories in a more intuitive and emotionally rich way, but traditional methods cannot adequately meet this need.

[0633] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0634] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired image and video data and generating shared space information, and means for reconstructing the generated shared space information within a virtual environment. This enables users to obtain a realistic and immersive visual experience based on static video assets.

[0635] "Image and video data" refers to digital information in still image and video formats, including visual media captured or collected by the user.

[0636] "Shared spatial information" refers to three-dimensional digital information generated from analyzed image and video data, and is used to construct virtual environments.

[0637] A "virtual environment" refers to a three-dimensional space created using digital technology, an immersive simulation space that users can experience visually.

[0638] "Means of providing a visual experience" refers to technologies or devices for visually reproducing and presenting generated content within a virtual environment to a user.

[0639] The system for realizing this application consists of a user terminal, a server, and a VR device. The user uploads captured images and video data to the server via the terminal. The server receives this data, analyzes it using a generative AI model, and generates shared spatial information. Specifically, the server constructs a three-dimensional space using generative AI tools such as Stable Diffusion and DALL-E.

[0640] Next, the server reconstructs the constructed shared space information as a virtual environment and provides it to the user. The user can access the virtual environment and enjoy the visual experience using VR devices such as head-mounted displays. Google Cloud or AWS is used as the meta-platform for this process.

[0641] As a concrete example, suppose a user uploads photos and videos of a special day spent with their family. Based on this data, the server virtually recreates the space where the family gathered and the atmosphere of that day, allowing the user to move through it and experience it as if they were back in that moment.

[0642] An example of a prompt for the generative AI model would be, "Please realistically recreate my child's birthday party in a 3D virtual space." This allows users to richly recreate past experiences while fostering a deeper emotional connection.

[0643] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0644] Step 1:

[0645] The user uploads images and video data captured using their device to the server. The input is media files stored on the user's local device, and the output is the transfer and storage of this data on the server. Specifically, the user operates a file selection interface, selects multiple files, and begins the upload.

[0646] Step 2:

[0647] The server receives uploaded image and video data and performs analysis using a generative AI model. The input is the media data received in step 1, and the output is the three-dimensional spatial information obtained through the analysis. Stable Diffusion and DALL-E are used for this process. The server inputs prompt messages to the AI ​​model, giving instructions in the form of "Generate a three-dimensional space from this image."

[0648] Step 3:

[0649] The server reconstructs the virtual environment based on the generated three-dimensional spatial information. The input is the shared spatial information generated in step 2, and the output is the virtual environment data that the user can experience. To reconstruct this data, the server uses a 3D rendering engine to prepare the virtual reality space.

[0650] Step 4:

[0651] The server sends the reconstructed virtual environment to the user's terminal. The input is the virtual environment data completed in step 3, and the output is data converted into a format that can be visually experienced on the user's VR device. Specifically, the server sends this data in stream format, enabling real-time display on the user's VR device.

[0652] Step 5:

[0653] The user wears a VR device and experiences a virtual environment. The input is the virtual environment data received from the server in step 4, and the output is the user's immersive experience. The user uses a controller or eye-tracking controls to change their viewpoint and the time of day within the virtual space, allowing them to recreate and enjoy past memories in a three-dimensional and dynamic way.

[0654] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0655] This invention provides a more personalized experience by incorporating an emotion engine that recognizes user emotions, in addition to a system that generates a three-dimensional space based on image and video data and provides that experience within a virtual reality space. The details are described below through examples.

[0656] Data acquisition and analysis

[0657] Users upload photos and video data to the system via their devices. The devices send this data to a server, which then uses a generation AI module to generate three-dimensional spatial information. This process also analyzes the movement of objects within the video and reconstructs them as dynamic three-dimensional models.

[0658] Creation and presentation of virtual reality spaces

[0659] The server sends the 3D model and dynamic data it generates to the metaverse server. The metaverse server constructs a virtual reality space based on the received data and prepares to provide that space to the user. The user can then use a VR device on their terminal to enter the virtual space and enjoy the visual experience.

[0660] Personalization powered by an emotion engine

[0661] The emotion engine embedded in the server analyzes the user's biometric data, voice, and facial expressions to recognize their current emotional state. Based on this data, it adjusts the visual, auditory, and other elements of the virtual reality space to match the user's emotions, personalizing the user experience.

[0662] Specific example

[0663] For example, if a user wants to relive a travel memory, they can upload a photo album to the system, recreating that travel destination in a virtual reality space. If the emotion engine detects the user's smile or cheerful voice, it adjusts the colors and music of the virtual world to be brighter and more harmonious. Conversely, if a calm and soothing emotion is recognized, the lighting in the virtual space is reduced, creating a quiet and relaxing environment. In this way, users can enjoy a more personalized and immersive experience.

[0664] The following describes the processing flow.

[0665] Step 1:

[0666] The user accesses the system via their device and selects the photos or videos they want to experience. The device then uploads the selected files to the server.

[0667] Step 2:

[0668] The server temporarily stores the received data and prepares it for analysis. It checks the data format and quality and then passes it on to the generating AI module.

[0669] Step 3:

[0670] The AI ​​generation module on the server analyzes the data and extracts three-dimensional information about objects and backgrounds within the image. Furthermore, in the case of video data, it performs motion analysis and generates a dynamic three-dimensional model.

[0671] Step 4:

[0672] The server formats the three-dimensional spatial information and dynamic model it generates for the metaverse and sends it to the metaverse server. The metaverse server then constructs a virtual reality space based on this data.

[0673] Step 5:

[0674] The server analyzes voice and facial expression data collected from the user's device through an emotion engine to recognize the user's emotional state. The device uses sensors and cameras to acquire the necessary data for this purpose.

[0675] Step 6:

[0676] The metaverse server dynamically adjusts the visual and auditory settings of the virtual reality space according to the user's emotions, based on emotion data obtained from the server. This allows the user to experience a personalized space.

[0677] Step 7:

[0678] Users enter a virtual reality space using a VR device on their device and explore a constructed three-dimensional model and a space adjusted based on emotions. Users can interactively manipulate the space and re-experience past memories emotionally and visually.

[0679] (Example 2)

[0680] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0681] Traditional virtual environment systems have the drawback of not considering the emotional state of the user, thus failing to provide an optimized experience for each individual user. Furthermore, the reproduction of dynamic objects within the virtual space is difficult, sometimes limiting the user experience. In addition, users cannot freely adjust various viewpoints, resulting in insufficient interactivity in the virtual environment.

[0682] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0683] In this invention, the server includes means for analyzing image and video data and generating three-dimensional spatial information; means for acquiring user emotion information and adjusting the virtual environment according to the user's emotional state; means for analyzing the movement of objects in images and dynamically reproducing them within the virtual environment; and means for adjusting the display of the virtual environment from different times or viewpoints. This makes it possible to provide a personalized experience tailored to the user's emotions and realize a dynamic and interactive virtual space.

[0684] "Image and video data" refers to visual information acquired by cameras and recording devices, including still images and video.

[0685] "Analysis" refers to processing acquired data and performing calculations and operations to extract or understand necessary information.

[0686] "Three-dimensional spatial data" refers to a dataset containing information for representing real or virtual space in three dimensions, capable of representing the position, shape, and movement of objects.

[0687] A "virtual environment" refers to an artificial and interactive space created by a computer that a user can experience through sight, sound, and other senses.

[0688] "User" refers to an individual who experiences a virtual environment through this system.

[0689] "Emotional information" refers to data that indicates the user's biological and psychological state, and is obtained from facial expressions, voice tone, biosignals, etc.

[0690] "Dynamic reproduction" refers to making objects and scenes change moment by moment for the user, enabling real-time interaction.

[0691] "Adjusting the display" means changing the viewpoint and content on the screen according to the user's instructions or environment, in order to provide the optimal visual experience.

[0692] This system realizes a virtual environment through collaborative operation between users, terminals, and servers. Users upload photos and video data via their terminals, which then send this data to the server. The server analyzes the data using a generative AI model and generates three-dimensional spatial data. Specifically, it utilizes deep learning technology for image recognition and reconstructs detailed spatial features. The hardware used should be a server equipped with a high-performance GPU, and the software should include machine learning frameworks.

[0693] The generated 3D model is sent to a metaverse server and constructed as a virtual environment. Users can access this virtual environment using a VR device connected to their terminal. The emotion engine acquires the user's biometric data, for example, through a camera and microphone, and analyzes their emotional state in real time. Based on these emotions, the server dynamically adjusts the visual and auditory information of the virtual environment to provide a personalized experience.

[0694] As a concrete example, suppose a user wants to relive a past trip. In this case, uploading a photo album to the system recreates the travel destination in a virtual space. When the emotion engine recognizes that the user is enjoying themselves from their facial expressions, the colors and music in the virtual space are adjusted to be brighter. Also, when the user wants to relax, the scenery changes to something quiet and peaceful.

[0695] An example of a prompt message is, "Recreate travel memories and provide a virtual environment that reflects the user's current emotions."

[0696] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0697] Step 1:

[0698] Users upload photos and video data to the system via their device. Specifically, they select data files using the device's interface and click the upload button. This action causes the device to collect the selected data and prepare it for transmission to the server for the next processing step. The input is the photos and video data selected by the user, and the output is the data securely transmitted to the server.

[0699] Step 2:

[0700] The device sends the uploaded data to the server. To ensure data security, the communication is encrypted using the SSL / TLS protocol. The server verifies the integrity of the received data and stores it in a database. The input is the encrypted data sent from the device, and the output is the raw data stored in the database.

[0701] Step 3:

[0702] The server inputs data stored in the database into a generating AI model to create three-dimensional spatial information. During this process, the AI ​​model uses deep learning techniques to analyze images and identify the movement and shape of objects in the video. This creates a dynamic three-dimensional model. The input is image and video data, and the output is the generated three-dimensional spatial data.

[0703] Step 4:

[0704] The server sends the generated three-dimensional spatial data to the metaverse server, which then prepares it for reconstruction as a virtual environment. The metaverse server builds the virtual environment based on the received data and makes it available to the user. The input is three-dimensional spatial data, and the output is a dataset with the virtual environment completed.

[0705] Step 5:

[0706] The user accesses a virtual environment using a VR device. Here, the server's emotion engine analyzes the user's biometric data and adjusts the visual and auditory elements of the virtual environment based on their emotional state in real time. The input is the user's biometric data, and the output is the adjusted visual and auditory elements of the virtual environment.

[0707] Step 6:

[0708] Users experience a virtual environment tailored to their emotions. For example, when recreating travel memories, if the emotion engine determines that the user is enjoying themselves, bright and cheerful colors and music will be provided. The input is the user's emotional state based on the emotion engine's output, and the output is a personalized virtual environment.

[0709] (Application Example 2)

[0710] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0711] While virtual reality spaces are a technology that provides users with a sense of immersion, they lack sufficient consistency with the real world and personalization that takes into account individual user experiences. Furthermore, they lack the functionality to adjust the virtual space in response to changes in emotions. This invention aims to integrate the user's real environment with the virtual space and provide individualized visual and auditory experiences based on emotions.

[0712] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0713] In this invention, the server includes means for acquiring image and video data, means for analyzing the acquired image and video data and generating three-dimensional spatial information, means for reconstructing the generated three-dimensional spatial information in a virtual reality space, and means for recognizing the user's emotions and adjusting the visual and auditory elements of the virtual reality space. This enables a personalized, immersive virtual experience based on the user's actual environment and emotional state.

[0714] "Image and video data" refers to photos and videos provided by users, and is fundamental information for constructing the virtual reality space.

[0715] "Three-dimensional spatial information" refers to a three-dimensional digital representation generated based on acquired image and video data, and is a component of virtual reality space.

[0716] A "virtual reality space" is a digital virtual environment constructed based on three-dimensional spatial information, providing users with a sense of immersion.

[0717] "Means of recognizing user emotions" refers to a function that analyzes biometric data, voice, and facial expressions to determine the emotional state the user is experiencing.

[0718] "Means for adjusting visual and auditory elements" refers to functions that dynamically change the images and sounds of the virtual reality space based on the perceived emotions of the user, thereby optimizing the user experience.

[0719] "Means of integrating the user's real environment with the virtual space" refers to technology that overlays a virtual reality space onto the user's current physical environment, thereby achieving a unification of reality and virtuality.

[0720] In the system implementing this invention, the user uploads image and video data to a server using a terminal such as a smartphone or smart glasses. The server receives this data and generates three-dimensional spatial information using a generative AI model. In this process, AI technology for image analysis (e.g., computer vision technology) is utilized to analyze the movement of objects in the video, thereby constructing a dynamic three-dimensional model.

[0721] The constructed three-dimensional model is reconstructed within the virtual reality space. Specifically, a server manages this data and presents it visually to the user's terminal via a VR device. During this process, an emotion analysis engine (e.g., emotion recognition software) analyzes biometric data, voice, and facial expressions to recognize the user's emotions. Based on this, the visual and auditory elements within the virtual reality space are adjusted to transform the environment to suit the user's emotions.

[0722] For example, if a user wants to relive memories of a past trip, they upload a photo album from their device to the system. Based on this data, the travel destination is recreated in a virtual reality space. When the emotion analysis engine detects joy as the user's emotion, the system adjusts the colors and music in the virtual space to make it a happier experience.

[0723] An example of a prompt message might be, "Overlay a virtual historical cityscape based on photographs onto reality, and interactively adjust the experience according to the user's emotions." This allows users to enjoy a personalized virtual experience.

[0724] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0725] Step 1:

[0726] The user uploads images and video data captured using their device. The input consists of image and video files. Once the data is sent from the user to the server, the following processing becomes possible.

[0727] Step 2:

[0728] The server analyzes the image and video data it receives. This analysis uses a generative AI model and image recognition technology. The input is image and video data from the user, and the output is analyzed three-dimensional spatial information. Based on this data, the server calculates the three-dimensional structure and generates a three-dimensional model that includes dynamic elements.

[0729] Step 3:

[0730] Using the generated three-dimensional spatial information, the server constructs a virtual reality space. The input is the analyzed three-dimensional spatial information, and the output is the virtual reality space itself. The server prepares the virtual environment as visual data and sends it to the user's VR terminal.

[0731] Step 4:

[0732] The user accesses the constructed virtual reality space using a VR device on their device. The input in this step is visual data sent from the server, and the output is the 3D virtual space experienced by the user. The device projects the visual data onto the VR device, providing the user with an immersive experience.

[0733] Step 5:

[0734] The server analyzes the user's biometric data and recognizes emotions using an emotion analysis engine. Input is the user's biosensor data and voice data, and output is the user's emotional state. Based on this emotional information, the server adjusts the visual and auditory elements within the virtual reality space.

[0735] Step 6:

[0736] A personalized experience is provided based on the user's emotions. The server sends adjusted environmental data to the user's device, and the device modifies the characteristics of the virtual space according to the user's emotions. This enables a real-time interactive experience.

[0737] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0738] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0739] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0740] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0741] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0742] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0743] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0744] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0745] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0746] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0747] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0748] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0749] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0750] 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.

[0751] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0752] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0753] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0754] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0755] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0756] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0757] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0758] The following is further disclosed regarding the embodiments described above.

[0759] (Claim 1)

[0760] Means for acquiring image and video data,

[0761] A means for analyzing the acquired image and video data and generating three-dimensional spatial information,

[0762] A means for reconstructing the generated three-dimensional spatial information within a virtual reality space,

[0763] A means for presenting the aforementioned virtual reality space to the user,

[0764] A system that includes this.

[0765] (Claim 2)

[0766] The system according to claim 1, further comprising means for analyzing the movement of an object in an image and dynamically reproducing it in the virtual reality space.

[0767] (Claim 3)

[0768] The system according to claim 1, further comprising means for adjusting the display of a virtual reality space from various times or viewpoints based on instructions from the user.

[0769] "Example 1"

[0770] (Claim 1)

[0771] Means for acquiring image and video data,

[0772] A means for analyzing the acquired image and video data and generating three-dimensional spatial information,

[0773] A means for reconstructing the generated three-dimensional spatial information within a virtual reality space,

[0774] A means for presenting the aforementioned virtual reality space to the user,

[0775] The means by which the user receives instructions to change the viewpoint and time within the virtual reality space,

[0776] A system that includes this.

[0777] (Claim 2)

[0778] The system according to claim 1, further comprising means for analyzing the movement of an object in an image and dynamically reproducing it in the virtual reality space.

[0779] (Claim 3)

[0780] The system according to claim 1, further comprising means for analyzing the image and video data using a generative AI model and automatically generating three-dimensional spatial information using the model.

[0781] "Application Example 1"

[0782] (Claim 1)

[0783] Means for acquiring image and video data,

[0784] A means for analyzing the acquired image and video data and generating shared spatial information,

[0785] Means for reconstructing the generated shared space information within the virtual environment,

[0786] A means for presenting the aforementioned virtual environment to the user,

[0787] Means of providing a visual experience within a virtual environment,

[0788] A system that includes this.

[0789] (Claim 2)

[0790] The system according to claim 1, further comprising means for analyzing the movement of an object in an image and dynamically reproducing it in the virtual environment.

[0791] (Claim 3)

[0792] The system according to claim 1, further comprising means for adjusting the display of a virtual environment from various times or viewpoints based on instructions from the user.

[0793] "Example 2 of combining an emotion engine"

[0794] (Claim 1)

[0795] Means for acquiring image and video data,

[0796] A means for analyzing the acquired image and video data and generating three-dimensional spatial data,

[0797] A means for reconstructing the generated three-dimensional spatial data within a virtual environment,

[0798] A means for presenting the aforementioned virtual environment to the user,

[0799] A means for acquiring user emotional information and adjusting the virtual environment according to the user's emotional state,

[0800] A system that includes this.

[0801] (Claim 2)

[0802] The system according to claim 1, further comprising means for analyzing the movement of an object in an image and dynamically reproducing it in the virtual environment.

[0803] (Claim 3)

[0804] The system according to claim 1, further comprising means for adjusting the display of a virtual environment from different times or viewpoints based on instructions from a user.

[0805] "Application example 2 when combining with an emotional engine"

[0806] (Claim 1)

[0807] Means for acquiring image and video data,

[0808] A means for analyzing the acquired image and video data and generating three-dimensional spatial information,

[0809] A means for reconstructing the generated three-dimensional spatial information within a virtual reality space,

[0810] A means for presenting the aforementioned virtual reality space to the user,

[0811] A means for recognizing user emotions and adjusting the visual and auditory elements of a virtual reality space,

[0812] A system that includes this.

[0813] (Claim 2)

[0814] The system according to claim 1, further comprising means for analyzing the movement of an object in an image and dynamically reproducing it in the virtual reality space.

[0815] (Claim 3)

[0816] The system according to claim 1, further comprising means for adjusting the display of a virtual reality space from various times or viewpoints based on instructions from the user, and means for overlaying the virtual reality space onto the scenery of the real environment in which the user is present. [Explanation of symbols]

[0817] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for acquiring image and video data, A means for analyzing the acquired image and video data and generating three-dimensional spatial information, A means for reconstructing the generated three-dimensional spatial information within a virtual reality space, A means for presenting the aforementioned virtual reality space to the user, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing the movement of an object in an image and dynamically reproducing it in the virtual reality space.

3. The system according to claim 1, further comprising means for adjusting the display of a virtual reality space from various times or viewpoints based on instructions from the user.

Images