system

Abstract

We provide the system. [Solution] A means having a generative model for analyzing photographic or video data and extracting features, A means for generating a three-dimensional virtual space based on feature data obtained from the generative model, Means for providing access to the three-dimensional virtual space, 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] In modern times, there is an increasing need to more realistically and sensually experience memories recorded by photos and videos. However, two-dimensional data often lacks sufficient emotion and a sense of presence. With traditional methods, it is difficult to reproduce these data as a real three-dimensional space, and there is a particular lack of technology for restoring personal memories within the metaverse space.

Means for Solving the Problems

[0005] This invention provides a system that includes a generative model for analyzing photographic and video data to extract features, and means for generating a three-dimensional virtual space based on the obtained feature data. This makes it possible to reproduce conventional two-dimensional data as a realistic three-dimensional space that users can experience with a sense of immersion, providing an environment in which users can richly relive their memories.

[0006] "Photograph or video data" refers to digital data that includes two-dimensional visual information recording scenes or events in the real world.

[0007] "Analysis" refers to analytical methods used to extract useful information from data, and in particular, to processing techniques for extracting features.

[0008] A "generative model" is a mathematical model that uses machine learning algorithms to generate new data based on input data.

[0009] "Feature data" refers to data containing specific attribute information of an object, such as its shape, movement, and color, extracted from an analyzed photograph or video.

[0010] A "three-dimensional virtual space" is an artificial space generated by computer simulation that provides users with a three-dimensional visual environment.

[0011] "Providing access" means supplying an interface or means that allows users to connect to and operate in a three-dimensional virtual space.

[0012] "Interface" is a term that refers to the means or points of contact through which a user interacts with a system, and includes input and output devices. [Brief explanation of the drawing]

[0013] [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]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the labeled 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.

[0017] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the labeled 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.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] The system according to the present invention aims to generate an immersive three-dimensional virtual space using user-owned photo and video data, and to allow the user to access that space. This system consists of terminals, servers, and a communication network that links them.

[0035] First, the user selects specific photos or videos from an album application on their device. The selected data is sent to the server through a designated application program. The server converts the received data into a format that can be processed by the generative model and performs analysis. During the analysis, features within the photos and videos (for example, the posture of people or the shape of the scenery) are extracted.

[0036] Next, the server generates a three-dimensional virtual space based on the extracted feature data. In this process, computer vision techniques are used to construct a realistic three-dimensional model from the data. This includes backgrounds, object placement, and animations, creating a space in which the user can re-experience memories.

[0037] Subsequently, the server saves the generated three-dimensional virtual space to cloud storage and sends an access link to the user's device. The user can access the virtual space via this link through the application interface and interact with and experience the space using VR devices and accessories.

[0038] For example, if a user uses a photograph taken during a trip, the server analyzes the photo and generates a three-dimensional model that reflects mountain ranges, coastlines, and building shapes. As a result, the user can view the scenery of the place they were at at the time in the virtual space with greater realism. This makes it possible to transform two-dimensional visual data into a richer and more sensory experience.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user uses their device to select any photos or videos from the album application. Next, they operate the "Generate Metaverse" button within the application to send the selected data to the server.

[0042] Step 2:

[0043] The device converts the transmitted photo or video data into the specified format and transfers it to the server via the internet. During this process, protocols are applied to compress the data and ensure security.

[0044] Step 3:

[0045] When the server receives data from a terminal, it prepares the received data into a format that can be input into the AI ​​model for generation. It verifies the integrity and completeness of the data and prepares it for analysis processing.

[0046] Step 4:

[0047] The server uses a generative AI model to analyze photo and video data. Computer vision algorithms are used to extract key features from the image (e.g., people's posture, environment layout, color harmony).

[0048] Step 5:

[0049] The server generates a three-dimensional virtual space based on the feature data obtained through analysis. Using a 3D modeling engine, it constructs objects, backgrounds, and necessary animations within the digital space.

[0050] Step 6:

[0051] The server saves the generated three-dimensional virtual space to cloud storage and creates an access link. It then sends the link information to the user's device, preparing the user to access the virtual space.

[0052] Step 7:

[0053] Users access a three-dimensional virtual space generated through the application using a link notified to their device. This enables an immersive experience using devices such as VR headsets.

[0054] (Example 1)

[0055] 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."

[0056] Conventional two-dimensional visual data is limited to visual information, making it difficult to reproduce real-life experiences with a sense of realism. Furthermore, there was a need for technology that could efficiently analyze multiple photographic and video data and, based on that analysis, provide users with a realistic three-dimensional virtual space.

[0057] 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.

[0058] In this invention, the server includes a processing unit equipped with a generation algorithm for analyzing photographic or video data and extracting features, a device for constructing a three-dimensional virtual environment based on the feature information obtained from the generation algorithm, and a device for providing access to the three-dimensional virtual environment. This enables users to have a realistic three-dimensional experience based on photographic or video data.

[0059] "Photographic or video data" refers to visual information stored in the form of still or moving images, and is acquired in digital or analog format.

[0060] A "generative algorithm" is a computational method that analyzes and extracts specific patterns or features from input data and generates new information based on them.

[0061] A "processing device" is a set of hardware and software components used to perform calculations, analysis, and transformations of data.

[0062] "Feature information" refers to important patterns and characteristics extracted from photographic or video data through analysis, and is data used in subsequent processing.

[0063] A "three-dimensional virtual environment" is a three-dimensional space generated by computer technology that provides a visual experience similar to the real world.

[0064] A "device that provides access" is a mechanism that allows users to access and experience a three-dimensional virtual environment, and includes a system that incorporates network communication and interfaces.

[0065] A "visual device" is a device used by a user to receive information visually, and typically takes the form of a display, headset, or goggles.

[0066] An "interface" is a point of contact or means by which a user and a system interact with each other, and is usually provided through a screen or controller.

[0067] This invention relates to a system that generates a three-dimensional virtual environment based on photographic or video data, allowing users to experience that environment. The system includes terminals, servers, and a communication network connecting them as its main components.

[0068] The server first converts the received photo and video data into a format that can be analyzed by a generation algorithm. This process utilizes commonly used media processing frameworks and libraries (e.g., OpenCV, TENSORFLOW®). Next, the converted data is processed by the generation algorithm to extract feature information. This feature information is directly used to construct the three-dimensional virtual environment.

[0069] The server utilizes a 3D rendering engine (e.g., Unity, Unreal Engine) to construct a three-dimensional virtual environment based on the extracted feature information. Using these engines, a realistic and detailed virtual environment is generated based on the data provided by the user. The generated virtual environment is stored in cloud storage, and a link is sent to the user's device.

[0070] Users can access the virtual environment via this link and enjoy the experience within it using VR devices and accessories. Through this interaction, users can discover new visual experiences constructed from selected photos and video data.

[0071] As a concrete example, a user might create a virtual environment using photos taken during a trip. In this scenario, the server analyzes the shapes of mountains, seas, buildings, and other elements, and generates a realistic three-dimensional model that incorporates these elements. Through this model, the user can relive their memories of their trip.

[0072] An example of a prompt is: "Design a system that generates a virtual space based on photos taken during a trip, providing an immersive experience that recreates the scenery of that time."

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The user opens an album app on their device and selects photos and videos they want to import into the 3D virtual environment. The selected data becomes the input. This selection determines which memories the user will recreate in the virtual environment. The device then sends the selected data to the server through a designated application.

[0076] Step 2:

[0077] The server receives photo and video data sent from the terminal and converts it into a format that is easy for the generative AI model to process. This conversion process involves data processing such as adjusting the resolution and changing the format of the data, preparing the input data for the generative algorithm. From this, the processed data is obtained as output.

[0078] Step 3:

[0079] The server analyzes the transformed data using a generating AI model and extracts the necessary feature information. At this stage, image recognition technology (e.g., convolutional neural networks) is used to extract important patterns and features from the data. The extracted feature information is output, and the process proceeds to the next stage.

[0080] Step 4:

[0081] The server constructs a three-dimensional virtual environment based on the acquired feature information. Here, a 3D rendering engine (e.g., Unity or Unreal Engine) is used to generate specific three-dimensional objects and backgrounds based on the feature information. The generated virtual environment model is then output.

[0082] Step 5:

[0083] The server saves the completed 3D virtual environment to cloud storage and sends an access link to the user's terminal. A link to the saved data is provided to the user as output. This allows the user to access the virtual environment at any time.

[0084] Step 6:

[0085] Users access a three-dimensional virtual environment using a link received on their device. They use VR devices and accessories to enjoy the experience within the virtual space. Through this experience, users can enjoy an immersive memory reconstruction based on selected photos and videos.

[0086] (Application Example 1)

[0087] 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."

[0088] In generating three-dimensional virtual spaces using photo and video data, there was a challenge in creating a system that could build an attractive commercial environment through personalized experiences for users, allowing them to make immersive product selections.

[0089] 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.

[0090] In this invention, the server includes means having a generative model for analyzing photographic or video data and extracting features; means for generating a three-dimensional virtual space based on the feature data obtained from the generative model; and means for constructing a commercial environment in the three-dimensional virtual space in which the user can experience a personalized selection process. This makes it possible for the user to explore and experience products in a virtual environment that reflects their own memories.

[0091] "Photo or video data" refers to still or moving image information owned by the user and recorded visually.

[0092] "Analysis" is the process of examining in detail the information contained in photographic or video data and extracting specific features.

[0093] "Features" refer to important information related to shape and arrangement obtained from photographic or video data.

[0094] A "generative model" is an algorithm or program that extracts features from photographic or video data and constructs a three-dimensional virtual space.

[0095] A "three-dimensional virtual space" is a computer-generated visual environment with depth, a three-dimensional space that immerses the user's senses.

[0096] A "commercial environment" is a virtual space where users can search for, select, and purchase products.

[0097] "Means of providing access" refers to the technologies and methods that enable users to connect to and experience a three-dimensional virtual space.

[0098] "Interaction" refers to the process by which a user actively acts within a virtual environment and interacts with that environment.

[0099] This invention provides a system that allows users to generate an immersive three-dimensional virtual space using their own photos and video data, and to experience that space. This system utilizes the user's terminal, a server, and cloud storage.

[0100] The server receives and analyzes photo and video data sent from user terminals. During the analysis, computer vision technologies such as Google® Cloud Vision API are used to extract features from the data. This provides important feature information based on the data.

[0101] Next, the server constructs a three-dimensional virtual space based on the acquired feature data. This process uses a 3D engine such as Unity or Unreal Engine to configure the background and object placement, generating a virtual space that reflects the user's memories. This space functions as a commercial environment, designed to allow users to select and purchase products while experiencing them.

[0102] The generated three-dimensional virtual space is stored in cloud storage, and an access link is sent to the user's device. Through this link, the user can access the virtual space using a VR device such as Oculus Quest and enjoy an immersive experience.

[0103] For example, if a user uploads photos of a beach vacation with their family, they can then explore beach-related products within a virtual store generated based on those photos.

[0104] Example of a prompt:

[0105] "Use uploaded beach photos to design a virtual shop where users can relax. This virtual space should display beach-themed items and include interactive elements that allow users to purchase those items."

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The user selects specific photos or videos from the album application on their device. This media data becomes the initial input data for subsequent processing. The selected data is sent to the server through a designated application on the device.

[0109] Step 2:

[0110] The server prepares the received photo and video data for analysis. Specifically, it utilizes computer vision technologies such as the Google Cloud Vision API to extract features related to shape and arrangement within the photos and videos. The input for this analysis is the photos and videos submitted by the user, and the output is feature data.

[0111] Step 3:

[0112] The server generates a three-dimensional virtual space using Unity, Unreal Engine, or similar software, based on the feature data extracted in Step 2. The input is feature data, and it outputs a realistic virtual space through 3D modeling and scene construction. Specifically, it handles the placement of objects within the space, the construction of backgrounds, and the setting of interaction elements.

[0113] Step 4:

[0114] The generated three-dimensional virtual space is saved to cloud storage by the server. The server sends an access link to this virtual space to the user's terminal, preparing it for the user to experience it next. The output is a link to the virtual space.

[0115] Step 5:

[0116] Users access a virtual space via a VR device such as Oculus Quest using a received link. The input here is the access link, and the output is a virtual store where users can freely experience an immersive environment. Users explore products and interact with the virtual space through interactive elements.

[0117] 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.

[0118] This invention combines a system that generates a three-dimensional virtual space based on photographic or video data with an emotion engine that recognizes the user's emotions. This system includes means for analyzing the user's digital data and generating a three-dimensional virtual space, and provides the user with access to that virtual space. Furthermore, the emotion engine can recognize the user's emotions and bring about dynamic changes in the virtual space in response to those emotions.

[0119] In this system, the user first uses a terminal to select a specific photo or video and sends it to the server. The server inputs the selected data into a generative model and analyzes it. Through this analysis, features from the image or video are extracted, and a three-dimensional virtual space is constructed based on these features.

[0120] Next, the emotion engine recognizes the user's emotional state. For emotion recognition, real-time data is acquired from the user's facial recognition sensor and biometric information monitor and analyzed by the emotion engine. This analysis determines the user's most recent emotional state, and the atmosphere and content of the virtual space are optimized accordingly.

[0121] For example, if a user uses photos taken during a trip, the server generates a three-dimensional virtual space based on the characteristics of that location, providing a space where the user can recreate their trip. Furthermore, if the emotion engine recognizes the user's feelings of joy, it adjusts the intensity and hue of the light in the virtual space to create a brighter atmosphere.

[0122] In this way, this system not only provides an immersive experience that surpasses conventional two-dimensional media, but also realizes an interactive virtual space that responds to emotions. As a result, users can create new memories through a more personalized experience.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The user uses their device to select specific photos or videos they want to turn into 3D from their device's album application. The selected data is uploaded to the server via a dedicated application on the device.

[0126] Step 2:

[0127] When a device sends photo or video data, it applies data compression and security protocols before transferring the data to the server. The device monitors the data sequentially until it receives confirmation of transmission from the server.

[0128] Step 3:

[0129] Upon receiving uploaded data, the server checks its integrity and completeness. It then performs preprocessing to convert the data into an appropriate format for input into the generative AI model.

[0130] Step 4:

[0131] The server uses a generative AI model to analyze photographic or video data and extract features of the subject. In this extraction process, key elements such as people and backgrounds are identified, and information necessary for 3D modeling is collected.

[0132] Step 5:

[0133] Based on the acquired feature data, the server uses a 3D modeling engine to construct a virtual space. The position and movement of objects, background details, and other elements are set, creating the virtual environment provided to the user.

[0134] Step 6:

[0135] The emotion engine analyzes the user's biometric information and facial expression data acquired through the device or external devices. Based on these analysis results, it recognizes the user's emotional state in real time.

[0136] Step 7:

[0137] The server receives input from the emotion engine and dynamically adjusts the situation and visual elements of the three-dimensional virtual space. Specifically, if the user is fatigued, it changes the music and color scheme in the space to settings that promote relaxation.

[0138] Step 8:

[0139] Users access a three-dimensional virtual space generated via their device and begin interacting within that space using a VR headset or other interface devices. An interactive experience is provided that responds to the user's emotional state.

[0140] (Example 2)

[0141] 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".

[0142] In recent years, the construction of virtual environments using digital data has attracted attention, but conventional technologies have made it difficult to provide dynamic virtual environments that reflect the user's emotional state. Furthermore, there is a need for a means to intuitively generate three-dimensional virtual environments from the user's digital images and videos, enabling personalized experiences.

[0143] 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.

[0144] In this invention, the server includes means having a generation program for analyzing image or video information and extracting features; means for creating a three-dimensional virtual environment based on the feature information obtained from the generation program; means having an analysis engine for acquiring biometric data and recognizing the user's emotional state; and means for dynamically adjusting the elements of the three-dimensional virtual environment according to the emotional state. This makes it possible to provide an immersive three-dimensional virtual environment adapted to the user's emotional state.

[0145] "Image or video information" refers to data of still images or videos stored in digital format, and is the subject of analysis as visual information.

[0146] "Feature information" refers to specific patterns, attributes, or identifiable elements extracted from image or video information, and serves as the basic data when constructing a virtual environment.

[0147] A "generation program" refers to a computer program that analyzes image or video information, extracts feature information, and generates a virtual environment.

[0148] A "three-dimensional virtual environment" refers to a digital space reproduced in three dimensions, in which users can virtually enjoy visual and tactile experiences.

[0149] The term "analysis engine" refers to a component that performs computational processing to estimate a user's emotional state by analyzing biometric data and other data indicating emotions.

[0150] "Biometric data" refers to information that indicates a user's physical state, such as facial expressions, heart rate, and skin electrical responses, and is used to recognize emotions.

[0151] "User's emotional state" refers to the psychological or emotional situation a user is currently experiencing, and includes states such as joy, sadness, and surprise.

[0152] "Dynamically adjusting internal elements" refers to changing conditions and settings within the virtual environment (e.g., light, sound, hue, etc.) in real time in response to changes in the user's emotional state.

[0153] This invention is a system that generates a individually tailored three-dimensional virtual environment using the user's existing digital images or video information, providing an immersive experience linked to the user's emotions.

[0154] First, the user selects specific image or video information using a device. For example, a smartphone or personal computer can be used as the device. The selected data is sent from the device to the server. A secure communication protocol is used for this data transfer.

[0155] The receiving server inputs the image or video information into a generating AI model. The server implements a deep learning-based generation program that extracts a wide range of feature information. Specifically, it analyzes the location, shape, and color of natural objects and buildings in landscape photographs. Three-dimensional virtual environment generation software such as Unity or Unreal Engine can be used for this process.

[0156] Based on the feature information obtained from the analysis, the server constructs a three-dimensional virtual environment. This virtual environment can be experienced interactively by the user and provides a simulated sense of reality.

[0157] Next, the user's device uses facial recognition sensors and biometric monitors to recognize the user's emotional state in real time. This allows the user to acquire biometric data such as facial expressions and heart rate, which are then validated by the server's analysis engine. Based on the analysis results, the server adjusts the internal elements of the virtual environment. For example, if the analysis determines that the user is feeling happy, the intensity of the lighting and the tone of the music in the virtual environment are adjusted.

[0158] A concrete example would be using a photo of a sunset taken by the user during a trip. In this case, an example prompt might be, "Based on this sunset photo, please adjust the space to reflect the user's feelings of joy." The server would then generate a 3D virtual environment that recreates the vibrant colors of the sunset and the sounds of the seashore, allowing the user to enjoy an immersive experience that recreates the atmosphere of the location.

[0159] This system combines generative AI models and emotion recognition technology to create an interactive virtual experience that adapts to the user's individual emotional state.

[0160] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0161] Step 1:

[0162] The user selects digital images or video information using a device and sends it to the server. The device retrieves the data from local or cloud storage and sends it to the server using a secure communication protocol (e.g., HTTPS). The input is the selected image or video information, and the output is a notification to the server that the transmission is complete.

[0163] Step 2:

[0164] The server inputs the received image or video information into the generating AI model. The server checks the data format and converts it into a format that the generating AI model can process. Specifically, it adjusts the image resolution and crops out unnecessary parts. The input is the raw data sent by the user, and the output becomes the input data for the generating AI model.

[0165] Step 3:

[0166] The server uses a generative AI model to extract feature information from image or video data. This model utilizes deep learning algorithms to extract visual features (such as color, shape, and composition). The input is pre-prepared data for the generative AI model, and the output is a feature information dataset.

[0167] Step 4:

[0168] The server constructs a three-dimensional virtual space based on the extracted feature information. The server uses software such as Unity or Unreal Engine to generate the 3D scene. Specifically, it reflects the extracted visual features in the objects and environment settings of the virtual space. The input is a feature information dataset, and the output is the generated virtual space data.

[0169] Step 5:

[0170] The device uses biometric monitors and facial recognition sensors to measure the user's emotional state in real time. The device collects data in real time and transmits it to the server. The input is the user's real-time biometric data, and the output is data prepared for analysis and sent to the server.

[0171] Step 6:

[0172] The server processes the received biometric data using an analysis engine to recognize the user's emotional state. Specifically, it uses machine learning algorithms to estimate emotional characteristics (e.g., joy, surprise, sadness). The input is biometric data transmitted from the terminal, and the output is the evaluation result of the emotional state.

[0173] Step 7:

[0174] The server dynamically adjusts the internal elements of the virtual space according to the emotional state it recognizes. Lighting settings, music tone, object movement, and other elements are optimized based on the user's emotions. The input is the result of the emotional state evaluation, and the output is the optimized virtual space.

[0175] In this way, users can experience an immersive virtual environment that adapts to their emotions.

[0176] (Application Example 2)

[0177] 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".

[0178] Traditional virtual environments based on two-dimensional media have been unable to dynamically change in response to individual user emotions, making it difficult to provide an immersive and interactive experience. Similarly, in physical stores and online shopping, providing products and services tailored to user emotions is challenging, highlighting the need for improved user experience.

[0179] 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. In this invention, the server includes means having a generative model for analyzing photographic or video data and extracting features, means for generating a three-dimensional virtual environment based on the feature data obtained from the generative model, means using an emotion engine for determining the user's emotions, means for dynamically adjusting the atmosphere and content of the virtual environment based on the emotional state determined by the emotion engine, and means for providing access to the three-dimensional virtual environment. This makes it possible for the user to enjoy a personalized virtual experience that responds to their emotions.

[0180] "Photograph or video data" refers to still images or video information stored in a digital format.

[0181] "Analysis" refers to the process of breaking down data and detecting and identifying its constituent elements and characteristics.

[0182] "Features" refer to information that indicates characteristics or patterns in photographic or video data.

[0183] A "generative model" refers to an algorithm or learning model that extracts features from input data and converts them into other formats.

[0184] A "three-dimensional virtual environment" refers to a computer-generated environment with a three-dimensional space, constructed based on digital data.

[0185] A "user" refers to a person who operates or uses a system.

[0186] An "emotion engine" refers to a system or algorithm used to detect and analyze a user's emotional state.

[0187] "Dynamic adjustment of atmosphere and content" refers to a function that changes the visual or auditory elements within the virtual environment in real time according to the user's emotional state.

[0188] "Means of providing access" refers to methods or devices for providing the interfaces and connectivity environments necessary for users to utilize the system.

[0189] To realize this invention, the server includes a system that uses an advanced generative model to analyze photographic or video data. This generative model extracts features from the data and generates the information necessary to construct a three-dimensional virtual environment. The three-dimensional virtual environment generated using the analyzed data is displayed on the user's terminal, allowing the user to experience personalized interactions through emotion recognition.

[0190] In this process, an emotion engine is used to recognize emotions acquired from the user in real time. The emotion engine analyzes data acquired from facial recognition sensors and biometric monitors attached to the user's device to determine the user's emotional state. Based on the determined emotion, the server dynamically adjusts the lighting, color, and sound elements within the virtual environment to provide the user with a more immersive and interactive experience.

[0191] For example, if a user uploads travel photos from their smartphone to the server, a three-dimensional virtual space is generated that recreates the scene from that time based on that data. If the emotion engine recognizes the user's feelings of joy, the scenery in the virtual space is adjusted to be bright and cheerful, allowing the user to realistically relive those happy memories.

[0192] Furthermore, users can provide detailed instructions to the generated AI model by offering prompts such as the following.

[0193] Example of a prompt:

[0194] Photo data: [Image file taken by the user]

[0195] Emotional data: [User's real-time emotional state]

[0196] Generation purpose: To generate a three-dimensional virtual space and adjust the environment according to emotions.

[0197] In this way, this system makes it possible to provide users with a new experience that is more emotionally resonant and to give them an environment optimized according to their emotions.

[0198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0199] Step 1:

[0200] The user uses their device to select photo or video data and sends it to the server. The input is the digital data selected by the user. The output is that data waiting to be processed on the server.

[0201] Step 2:

[0202] The server inputs received photo or video data into a generating AI model for data analysis. The input is image data sent by the user. The server decomposes the data, finds specific structures and patterns, and extracts their features. The output is feature data necessary for generating a virtual space.

[0203] Step 3:

[0204] The server constructs a three-dimensional virtual environment based on the extracted feature data. The input is the feature data obtained in the previous step. The server uses this to generate a three-dimensional model and converts it into a form that the user can visualize. The output is visualizeable three-dimensional virtual environment data.

[0205] Step 4:

[0206] An emotion recognition sensor installed on the user's device collects the user's facial expressions and biometric information and transmits it to a server. The input is the user's biometric data, and the output is the emotion data transmitted to the server.

[0207] Step 5:

[0208] The server analyzes the received emotional data using an emotion engine to determine the user's emotional state. The input is emotional data sent by the user. The server analyzes biometric data to identify the user's current emotional state. The output is the result of the emotional state determination.

[0209] Step 6:

[0210] The server dynamically adjusts the atmosphere and content of the virtual environment based on the detected emotional state. The input is the user's emotional state. The server adjusts the lighting, color, and sound elements within the three-dimensional virtual environment to create an environment optimized for the user's emotions. As output, the adjusted virtual environment is displayed on the user's terminal.

[0211] 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.

[0212] 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.

[0213] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0214] [Second Embodiment]

[0215] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0216] 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.

[0217] 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).

[0218] 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.

[0219] 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.

[0220] 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).

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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".

[0227] The system according to the present invention aims to generate an immersive three-dimensional virtual space using user-owned photo and video data, and to allow the user to access that space. This system consists of terminals, servers, and a communication network that links them.

[0228] First, the user selects specific photos or videos from an album application on their device. The selected data is sent to the server through a designated application program. The server converts the received data into a format that can be processed by the generative model and performs analysis. During the analysis, features within the photos and videos (for example, the posture of people or the shape of the scenery) are extracted.

[0229] Next, the server generates a three-dimensional virtual space based on the extracted feature data. In this process, computer vision techniques are used to construct a realistic three-dimensional model from the data. This includes backgrounds, object placement, and animations, creating a space in which the user can re-experience memories.

[0230] Subsequently, the server saves the generated three-dimensional virtual space to cloud storage and sends an access link to the user's device. The user can access the virtual space via this link through the application interface and interact with and experience the space using VR devices and accessories.

[0231] For example, if a user uses a photograph taken during a trip, the server analyzes the photo and generates a three-dimensional model that reflects mountain ranges, coastlines, and building shapes. As a result, the user can view the scenery of the place they were at at the time in the virtual space with greater realism. This makes it possible to transform two-dimensional visual data into a richer and more sensory experience.

[0232] The following describes the processing flow.

[0233] Step 1:

[0234] The user uses their device to select any photos or videos from the album application. Next, they operate the "Generate Metaverse" button within the application to send the selected data to the server.

[0235] Step 2:

[0236] The device converts the transmitted photo or video data into the specified format and transfers it to the server via the internet. During this process, protocols are applied to compress the data and ensure security.

[0237] Step 3:

[0238] When the server receives data from a terminal, it prepares the received data into a format that can be input into the AI ​​model for generation. It verifies the integrity and completeness of the data and prepares it for analysis processing.

[0239] Step 4:

[0240] The server uses a generative AI model to analyze photo and video data. Computer vision algorithms are used to extract key features from the image (e.g., people's posture, environment layout, color harmony).

[0241] Step 5:

[0242] The server generates a three-dimensional virtual space based on the feature data obtained through analysis. Using a 3D modeling engine, it constructs objects, backgrounds, and necessary animations within the digital space.

[0243] Step 6:

[0244] The server saves the generated three-dimensional virtual space to cloud storage and creates an access link. It then sends the link information to the user's device, preparing the user to access the virtual space.

[0245] Step 7:

[0246] Users access a three-dimensional virtual space generated through the application using a link notified to their device. This enables an immersive experience using devices such as VR headsets.

[0247] (Example 1)

[0248] 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."

[0249] Conventional two-dimensional visual data is limited to visual information, making it difficult to reproduce real-life experiences with a sense of realism. Furthermore, there was a need for technology that could efficiently analyze multiple photographic and video data and, based on that analysis, provide users with a realistic three-dimensional virtual space.

[0250] 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.

[0251] In this invention, the server includes a processing unit equipped with a generation algorithm for analyzing photographic or video data and extracting features, a device for constructing a three-dimensional virtual environment based on the feature information obtained from the generation algorithm, and a device for providing access to the three-dimensional virtual environment. This enables users to have a realistic three-dimensional experience based on photographic or video data.

[0252] "Photographic or video data" refers to visual information stored in the form of still or moving images, and is acquired in digital or analog format.

[0253] A "generative algorithm" is a computational method that analyzes and extracts specific patterns or features from input data and generates new information based on them.

[0254] A "processing device" is a set of hardware and software components used to perform calculations, analysis, and transformations of data.

[0255] "Feature information" refers to important patterns and characteristics extracted from photographic or video data through analysis, and is data used in subsequent processing.

[0256] A "three-dimensional virtual environment" is a three-dimensional space generated by computer technology that provides a visual experience similar to the real world.

[0257] A "device that provides access" is a mechanism that allows users to access and experience a three-dimensional virtual environment, and includes a system that incorporates network communication and interfaces.

[0258] A "visual device" is a device used by a user to receive information visually, and typically takes the form of a display, headset, or goggles.

[0259] An "interface" is a point of contact or means by which a user and a system interact with each other, and is usually provided through a screen or controller.

[0260] This invention relates to a system that generates a three-dimensional virtual environment based on photographic or video data, allowing users to experience that environment. The system includes terminals, servers, and a communication network connecting them as its main components.

[0261] The server first converts the received photo and video data into a format that can be analyzed by a generation algorithm. This process utilizes commonly used media processing frameworks and libraries (e.g., OpenCV, TensorFlow). Next, the converted data is processed by the generation algorithm to extract feature information. This feature information is directly used to construct the three-dimensional virtual environment.

[0262] The server utilizes a 3D rendering engine (e.g., Unity, Unreal Engine) to construct a three-dimensional virtual environment based on the extracted feature information. Using these engines, a realistic and detailed virtual environment is generated based on the data provided by the user. The generated virtual environment is stored in cloud storage, and a link is sent to the user's device.

[0263] Users can access the virtual environment via this link and enjoy the experience within it using VR devices and accessories. Through this interaction, users can discover new visual experiences constructed from selected photos and video data.

[0264] As a concrete example, a user might create a virtual environment using photos taken during a trip. In this scenario, the server analyzes the shapes of mountains, seas, buildings, and other elements, and generates a realistic three-dimensional model that incorporates these elements. Through this model, the user can relive their memories of their trip.

[0265] An example of a prompt is: "Design a system that generates a virtual space based on photos taken during a trip, providing an immersive experience that recreates the scenery of that time."

[0266] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0267] Step 1:

[0268] The user opens an album app on their device and selects photos and videos they want to import into the 3D virtual environment. The selected data becomes the input. This selection determines which memories the user will recreate in the virtual environment. The device then sends the selected data to the server through a designated application.

[0269] Step 2:

[0270] The server receives photo and video data sent from the terminal and converts it into a format that is easy for the generative AI model to process. This conversion process involves data processing such as adjusting the resolution and changing the format of the data, preparing the input data for the generative algorithm. From this, the processed data is obtained as output.

[0271] Step 3:

[0272] The server analyzes the transformed data using a generating AI model and extracts the necessary feature information. At this stage, image recognition technology (e.g., convolutional neural networks) is used to extract important patterns and features from the data. The extracted feature information is output, and the process proceeds to the next stage.

[0273] Step 4:

[0274] The server constructs a three-dimensional virtual environment based on the acquired feature information. Here, a 3D rendering engine (e.g., Unity or Unreal Engine) is used to generate specific three-dimensional objects and backgrounds based on the feature information. The generated virtual environment model is then output.

[0275] Step 5:

[0276] The server saves the completed 3D virtual environment to cloud storage and sends an access link to the user's terminal. A link to the saved data is provided to the user as output. This allows the user to access the virtual environment at any time.

[0277] Step 6:

[0278] Users access a three-dimensional virtual environment using a link received on their device. They use VR devices and accessories to enjoy the experience within the virtual space. Through this experience, users can enjoy an immersive memory reconstruction based on selected photos and videos.

[0279] (Application Example 1)

[0280] 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."

[0281] In the generation of a three-dimensional virtual space utilizing photo and video data, there has been a problem that a system is required which can construct an attractive commercial environment through an individualized experience of the user and allow the user to select products with a sense of immersion.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0283] In this invention, the server includes means for analyzing photo or video data and having a generation model for extracting features, means for generating a three-dimensional virtual space based on the feature data obtained from the generation model, and means for constructing a commercial environment in the three-dimensional virtual space where a user can experience an individualized selection process. As a result, it becomes possible for the user to search for and experience products in a virtual environment that reflects the user's own memories.

[0284] "Photo or video data" refers to information of a still image or a moving image that is owned by the user and visually recorded.

[0285] <​​​​​​​​​​​​​​​​​​​​"Means of providing access" refers to the technologies and methods that enable users to connect to and experience a three-dimensional virtual space.

[0291] "Interaction" refers to the process by which a user actively acts within a virtual environment and interacts with that environment.

[0292] This invention provides a system that allows users to generate an immersive three-dimensional virtual space using their own photos and video data, and to experience that space. This system utilizes the user's terminal, a server, and cloud storage.

[0293] The server receives and analyzes photo and video data sent from user terminals. During the analysis, computer vision technologies such as the Google Cloud Vision API are used to extract features from the data. This provides important feature information based on the data.

[0294] Next, the server constructs a three-dimensional virtual space based on the acquired feature data. This process uses a 3D engine such as Unity or Unreal Engine to configure the background and object placement, generating a virtual space that reflects the user's memories. This space functions as a commercial environment, designed to allow users to select and purchase products while experiencing them.

[0295] The generated three-dimensional virtual space is stored in cloud storage, and an access link is sent to the user's device. Through this link, the user can access the virtual space using a VR device such as Oculus Quest and enjoy an immersive experience.

[0296] For example, if a user uploads photos of a beach vacation with their family, they can then explore beach-related products within a virtual store generated based on those photos.

[0297] Example of a prompt:

[0298] "Use uploaded beach photos to design a virtual shop where users can relax. This virtual space should display beach-themed items and include interactive elements that allow users to purchase those items."

[0299] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0300] Step 1:

[0301] The user selects specific photos or videos from the album application on their device. This media data becomes the initial input data for subsequent processing. The selected data is sent to the server through a designated application on the device.

[0302] Step 2:

[0303] The server prepares the received photo and video data for analysis. Specifically, it utilizes computer vision technologies such as the Google Cloud Vision API to extract features related to shape and arrangement within the photos and videos. The input for this analysis is the photos and videos submitted by the user, and the output is feature data.

[0304] Step 3:

[0305] The server generates a three-dimensional virtual space using Unity, Unreal Engine, or similar software, based on the feature data extracted in Step 2. The input is feature data, and it outputs a realistic virtual space through 3D modeling and scene construction. Specifically, it handles the placement of objects within the space, the construction of backgrounds, and the setting of interaction elements.

[0306] Step 4:

[0307] The generated three-dimensional virtual space is stored in cloud storage by the server. The server sends an access link to this virtual space to the user's terminal to prepare for the user to experience this virtual space next. The output is a link to the virtual space.

[0308] Step 5:

[0309] The user accesses the virtual space through a VR device such as Oculus Quest using the received link. The input here is the access link, and the output is a virtual store where the user can freely experience an immersive environment. The user explores products and interacts with the virtual space through interactive elements.

[0310] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0311] The present invention is in a form that combines an emotion engine for recognizing the user's emotions with a system for generating a three-dimensional virtual space based on photo or video data. This system includes means for analyzing the digital data possessed by the user and generating a three-dimensional virtual space, and provides the user with access to that virtual space. Furthermore, the emotion engine can recognize the user's emotions and bring about dynamic changes in the virtual space according to those emotions.

[0312] In this system, first, the user uses the terminal to select a specific photo or video and sends it to the server. The server inputs the selected data into the generation model and analyzes the data. Through this analysis, features in the image or video are extracted, and based on that, a three-dimensional virtual space is constructed.

[0313] Next, the emotion engine recognizes the user's emotional state. For emotion recognition, real-time data is acquired from the user's facial recognition sensor and biometric information monitor and analyzed by the emotion engine. This analysis determines the user's most recent emotional state, and the atmosphere and content of the virtual space are optimized accordingly.

[0314] For example, if a user uses photos taken during a trip, the server generates a three-dimensional virtual space based on the characteristics of that location, providing a space where the user can recreate their trip. Furthermore, if the emotion engine recognizes the user's feelings of joy, it adjusts the intensity and hue of the light in the virtual space to create a brighter atmosphere.

[0315] In this way, this system not only provides an immersive experience that surpasses conventional two-dimensional media, but also realizes an interactive virtual space that responds to emotions. As a result, users can create new memories through a more personalized experience.

[0316] The following describes the processing flow.

[0317] Step 1:

[0318] The user uses their device to select specific photos or videos they want to turn into 3D from their device's album application. The selected data is uploaded to the server via a dedicated application on the device.

[0319] Step 2:

[0320] When a device sends photo or video data, it applies data compression and security protocols before transferring the data to the server. The device monitors the data sequentially until it receives confirmation of transmission from the server.

[0321] Step 3:

[0322] Upon receiving uploaded data, the server checks its integrity and completeness. It then performs preprocessing to convert the data into an appropriate format for input into the generative AI model.

[0323] Step 4:

[0324] The server uses a generative AI model to analyze photographic or video data and extract features of the subject. In this extraction process, key elements such as people and backgrounds are identified, and information necessary for 3D modeling is collected.

[0325] Step 5:

[0326] Based on the acquired feature data, the server uses a 3D modeling engine to construct a virtual space. The position and movement of objects, background details, and other elements are set, creating the virtual environment provided to the user.

[0327] Step 6:

[0328] The emotion engine analyzes the user's biometric information and facial expression data acquired through the device or external devices. Based on these analysis results, it recognizes the user's emotional state in real time.

[0329] Step 7:

[0330] The server receives input from the emotion engine and dynamically adjusts the situation and visual elements of the three-dimensional virtual space. Specifically, if the user is fatigued, it changes the music and color scheme in the space to settings that promote relaxation.

[0331] Step 8:

[0332] Users access a three-dimensional virtual space generated via their device and begin interacting within that space using a VR headset or other interface devices. An interactive experience is provided that responds to the user's emotional state.

[0333] (Example 2)

[0334] 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".

[0335] In recent years, the construction of virtual environments using digital data has attracted attention, but conventional technologies have made it difficult to provide dynamic virtual environments that reflect the user's emotional state. Furthermore, there is a need for a means to intuitively generate three-dimensional virtual environments from the user's digital images and videos, enabling personalized experiences.

[0336] 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.

[0337] In this invention, the server includes means having a generation program for analyzing image or video information and extracting features; means for creating a three-dimensional virtual environment based on the feature information obtained from the generation program; means having an analysis engine for acquiring biometric data and recognizing the user's emotional state; and means for dynamically adjusting the elements of the three-dimensional virtual environment according to the emotional state. This makes it possible to provide an immersive three-dimensional virtual environment adapted to the user's emotional state.

[0338] "Image or video information" refers to data of still images or videos stored in digital format, and is the subject of analysis as visual information.

[0339] "Feature information" refers to specific patterns, attributes, or identifiable elements extracted from image or video information, and serves as the basic data when constructing a virtual environment.

[0340] A "generation program" refers to a computer program that analyzes image or video information, extracts feature information, and generates a virtual environment.

[0341] A "three-dimensional virtual environment" refers to a digital space reproduced in three dimensions, in which users can virtually enjoy visual and tactile experiences.

[0342] The term "analysis engine" refers to a component that performs computational processing to estimate a user's emotional state by analyzing biometric data and other data indicating emotions.

[0343] "Biometric data" refers to information that indicates a user's physical state, such as facial expressions, heart rate, and skin electrical responses, and is used to recognize emotions.

[0344] "User's emotional state" refers to the psychological or emotional situation a user is currently experiencing, and includes states such as joy, sadness, and surprise.

[0345] "Dynamically adjusting internal elements" refers to changing conditions and settings within the virtual environment (e.g., light, sound, hue, etc.) in real time in response to changes in the user's emotional state.

[0346] This invention is a system that generates a individually tailored three-dimensional virtual environment using the user's existing digital images or video information, providing an immersive experience linked to the user's emotions.

[0347] First, the user selects specific image or video information using a device. For example, a smartphone or personal computer can be used as the device. The selected data is sent from the device to the server. A secure communication protocol is used for this data transfer.

[0348] The receiving server inputs the image or video information into a generating AI model. The server implements a deep learning-based generation program that extracts a wide range of feature information. Specifically, it analyzes the location, shape, and color of natural objects and buildings in landscape photographs. Three-dimensional virtual environment generation software such as Unity or Unreal Engine can be used for this process.

[0349] Based on the feature information obtained from the analysis, the server constructs a three-dimensional virtual environment. This virtual environment can be experienced interactively by the user and provides a simulated sense of reality.

[0350] Next, the user's device uses facial recognition sensors and biometric monitors to recognize the user's emotional state in real time. This allows the user to acquire biometric data such as facial expressions and heart rate, which are then validated by the server's analysis engine. Based on the analysis results, the server adjusts the internal elements of the virtual environment. For example, if the analysis determines that the user is feeling happy, the intensity of the lighting and the tone of the music in the virtual environment are adjusted.

[0351] A concrete example would be using a photo of a sunset taken by the user during a trip. In this case, an example prompt might be, "Based on this sunset photo, please adjust the space to reflect the user's feelings of joy." The server would then generate a 3D virtual environment that recreates the vibrant colors of the sunset and the sounds of the seashore, allowing the user to enjoy an immersive experience that recreates the atmosphere of the location.

[0352] This system combines generative AI models and emotion recognition technology to create an interactive virtual experience that adapts to the user's individual emotional state.

[0353] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0354] Step 1:

[0355] The user selects digital images or video information using a device and sends it to the server. The device retrieves the data from local or cloud storage and sends it to the server using a secure communication protocol (e.g., HTTPS). The input is the selected image or video information, and the output is a notification to the server that the transmission is complete.

[0356] Step 2:

[0357] The server inputs the received image or video information into the generating AI model. The server checks the data format and converts it into a format that the generating AI model can process. Specifically, it adjusts the image resolution and crops out unnecessary parts. The input is the raw data sent by the user, and the output becomes the input data for the generating AI model.

[0358] Step 3:

[0359] The server uses a generative AI model to extract feature information from image or video data. This model utilizes deep learning algorithms to extract visual features (such as color, shape, and composition). The input is pre-prepared data for the generative AI model, and the output is a feature information dataset.

[0360] Step 4:

[0361] The server constructs a three-dimensional virtual space based on the extracted feature information. The server uses software such as Unity or Unreal Engine to generate the 3D scene. Specifically, it reflects the extracted visual features in the objects and environment settings of the virtual space. The input is a feature information dataset, and the output is the generated virtual space data.

[0362] Step 5:

[0363] The device uses biometric monitors and facial recognition sensors to measure the user's emotional state in real time. The device collects data in real time and transmits it to the server. The input is the user's real-time biometric data, and the output is data prepared for analysis and sent to the server.

[0364] Step 6:

[0365] The server processes the received biometric data using an analysis engine to recognize the user's emotional state. Specifically, it uses machine learning algorithms to estimate emotional characteristics (e.g., joy, surprise, sadness). The input is biometric data transmitted from the terminal, and the output is the evaluation result of the emotional state.

[0366] Step 7:

[0367] The server dynamically adjusts the internal elements of the virtual space according to the emotional state it recognizes. Lighting settings, music tone, object movement, and other elements are optimized based on the user's emotions. The input is the result of the emotional state evaluation, and the output is the optimized virtual space.

[0368] In this way, users can experience an immersive virtual environment that adapts to their emotions.

[0369] (Application Example 2)

[0370] 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."

[0371] Traditional virtual environments based on two-dimensional media have been unable to dynamically change in response to individual user emotions, making it difficult to provide an immersive and interactive experience. Similarly, in physical stores and online shopping, providing products and services tailored to user emotions is challenging, highlighting the need for improved user experience.

[0372] 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. In this invention, the server includes means having a generative model for analyzing photographic or video data and extracting features, means for generating a three-dimensional virtual environment based on the feature data obtained from the generative model, means using an emotion engine for determining the user's emotions, means for dynamically adjusting the atmosphere and content of the virtual environment based on the emotional state determined by the emotion engine, and means for providing access to the three-dimensional virtual environment. This makes it possible for the user to enjoy a personalized virtual experience that responds to their emotions.

[0373] "Photograph or video data" refers to still images or video information stored in a digital format.

[0374] "Analysis" refers to the process of breaking down data and detecting and identifying its constituent elements and characteristics.

[0375] "Features" refer to information that indicates characteristics or patterns in photographic or video data.

[0376] A "generative model" refers to an algorithm or learning model that extracts features from input data and converts them into other formats.

[0377] A "three-dimensional virtual environment" refers to a computer-generated environment with a three-dimensional space, constructed based on digital data.

[0378] A "user" refers to a person who operates or uses a system.

[0379] An "emotion engine" refers to a system or algorithm used to detect and analyze a user's emotional state.

[0380] "Dynamic adjustment of atmosphere and content" refers to a function that changes the visual or auditory elements within the virtual environment in real time according to the user's emotional state.

[0381] "Means of providing access" refers to methods or devices for providing the interfaces and connectivity environments necessary for users to utilize the system.

[0382] To realize this invention, the server includes a system that uses an advanced generative model to analyze photographic or video data. This generative model extracts features from the data and generates the information necessary to construct a three-dimensional virtual environment. The three-dimensional virtual environment generated using the analyzed data is displayed on the user's terminal, allowing the user to experience personalized interactions through emotion recognition.

[0383] In this process, an emotion engine is used to recognize emotions acquired from the user in real time. The emotion engine analyzes data acquired from facial recognition sensors and biometric monitors attached to the user's device to determine the user's emotional state. Based on the determined emotion, the server dynamically adjusts the lighting, color, and sound elements within the virtual environment to provide the user with a more immersive and interactive experience.

[0384] For example, if a user uploads travel photos from their smartphone to the server, a three-dimensional virtual space is generated that recreates the scene from that time based on that data. If the emotion engine recognizes the user's feelings of joy, the scenery in the virtual space is adjusted to be bright and cheerful, allowing the user to realistically relive those happy memories.

[0385] Furthermore, users can provide detailed instructions to the generated AI model by offering prompts such as the following.

[0386] Example of a prompt:

[0387] Photo data: [Image file taken by the user]

[0388] Emotional data: [User's real-time emotional state]

[0389] Generation purpose: To generate a three-dimensional virtual space and adjust the environment according to emotions.

[0390] In this way, this system makes it possible to provide users with a new experience that is more emotionally resonant and to give them an environment optimized according to their emotions.

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] The user uses their device to select photo or video data and sends it to the server. The input is the digital data selected by the user. The output is that data waiting to be processed on the server.

[0394] Step 2:

[0395] The server inputs received photo or video data into a generating AI model for data analysis. The input is image data sent by the user. The server decomposes the data, finds specific structures and patterns, and extracts their features. The output is feature data necessary for generating a virtual space.

[0396] Step 3:

[0397] The server constructs a three-dimensional virtual environment based on the extracted feature data. The input is the feature data obtained in the previous step. The server uses this to generate a three-dimensional model and converts it into a form that the user can visualize. The output is visualizeable three-dimensional virtual environment data.

[0398] Step 4:

[0399] An emotion recognition sensor installed on the user's device collects the user's facial expressions and biometric information and transmits it to a server. The input is the user's biometric data, and the output is the emotion data transmitted to the server.

[0400] Step 5:

[0401] The server analyzes the received emotional data using an emotion engine to determine the user's emotional state. The input is emotional data sent by the user. The server analyzes biometric data to identify the user's current emotional state. The output is the result of the emotional state determination.

[0402] Step 6:

[0403] The server dynamically adjusts the atmosphere and content of the virtual environment based on the detected emotional state. The input is the user's emotional state. The server adjusts the lighting, color, and sound elements within the three-dimensional virtual environment to create an environment optimized for the user's emotions. As output, the adjusted virtual environment is displayed on the user's terminal.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] [Third Embodiment]

[0408] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0409] 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.

[0410] 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).

[0411] 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.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] 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.

[0419] 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".

[0420] The system according to the present invention aims to generate an immersive three-dimensional virtual space using user-owned photo and video data, and to allow the user to access that space. This system consists of terminals, servers, and a communication network that links them.

[0421] First, the user selects specific photos or videos from an album application on their device. The selected data is sent to the server through a designated application program. The server converts the received data into a format that can be processed by the generative model and performs analysis. During the analysis, features within the photos and videos (for example, the posture of people or the shape of the scenery) are extracted.

[0422] Next, the server generates a three-dimensional virtual space based on the extracted feature data. In this process, computer vision techniques are used to construct a realistic three-dimensional model from the data. This includes backgrounds, object placement, and animations, creating a space in which the user can re-experience memories.

[0423] Subsequently, the server saves the generated three-dimensional virtual space to cloud storage and sends an access link to the user's device. The user can access the virtual space via this link through the application interface and interact with and experience the space using VR devices and accessories.

[0424] For example, if a user uses a photograph taken during a trip, the server analyzes the photo and generates a three-dimensional model that reflects mountain ranges, coastlines, and building shapes. As a result, the user can view the scenery of the place they were at at the time in the virtual space with greater realism. This makes it possible to transform two-dimensional visual data into a richer and more sensory experience.

[0425] The following describes the processing flow.

[0426] Step 1:

[0427] The user uses their device to select any photos or videos from the album application. Next, they operate the "Generate Metaverse" button within the application to send the selected data to the server.

[0428] Step 2:

[0429] The device converts the transmitted photo or video data into the specified format and transfers it to the server via the internet. During this process, protocols are applied to compress the data and ensure security.

[0430] Step 3:

[0431] When the server receives data from a terminal, it prepares the received data into a format that can be input into the AI ​​model for generation. It verifies the integrity and completeness of the data and prepares it for analysis processing.

[0432] Step 4:

[0433] The server uses a generative AI model to analyze photo and video data. Computer vision algorithms are used to extract key features from the image (e.g., people's posture, environment layout, color harmony).

[0434] Step 5:

[0435] The server generates a three-dimensional virtual space based on the feature data obtained through analysis. Using a 3D modeling engine, it constructs objects, backgrounds, and necessary animations within the digital space.

[0436] Step 6:

[0437] The server saves the generated three-dimensional virtual space to cloud storage and creates an access link. It then sends the link information to the user's device, preparing the user to access the virtual space.

[0438] Step 7:

[0439] Users access a three-dimensional virtual space generated through the application using a link notified to their device. This enables an immersive experience using devices such as VR headsets.

[0440] (Example 1)

[0441] 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."

[0442] Conventional two-dimensional visual data is limited to visual information, making it difficult to reproduce real-life experiences with a sense of realism. Furthermore, there was a need for technology that could efficiently analyze multiple photographic and video data and, based on that analysis, provide users with a realistic three-dimensional virtual space.

[0443] 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.

[0444] In this invention, the server includes a processing unit equipped with a generation algorithm for analyzing photographic or video data and extracting features, a device for constructing a three-dimensional virtual environment based on the feature information obtained from the generation algorithm, and a device for providing access to the three-dimensional virtual environment. This enables users to have a realistic three-dimensional experience based on photographic or video data.

[0445] "Photographic or video data" refers to visual information stored in the form of still or moving images, and is acquired in digital or analog format.

[0446] A "generative algorithm" is a computational method that analyzes and extracts specific patterns or features from input data and generates new information based on them.

[0447] A "processing device" is a set of hardware and software components used to perform calculations, analysis, and transformations of data.

[0448] "Feature information" refers to important patterns and characteristics extracted from photographic or video data through analysis, and is data used in subsequent processing.

[0449] A "three-dimensional virtual environment" is a three-dimensional space generated by computer technology that provides a visual experience similar to the real world.

[0450] A "device that provides access" is a mechanism that allows users to access and experience a three-dimensional virtual environment, and includes a system that incorporates network communication and interfaces.

[0451] A "visual device" is a device used by a user to receive information visually, and typically takes the form of a display, headset, or goggles.

[0452] An "interface" is a point of contact or means by which a user and a system interact with each other, and is usually provided through a screen or controller.

[0453] This invention relates to a system that generates a three-dimensional virtual environment based on photographic or video data, allowing users to experience that environment. The system includes terminals, servers, and a communication network connecting them as its main components.

[0454] The server first converts the received photo and video data into a format that can be analyzed by a generation algorithm. This process utilizes commonly used media processing frameworks and libraries (e.g., OpenCV, TensorFlow). Next, the converted data is processed by the generation algorithm to extract feature information. This feature information is directly used to construct the three-dimensional virtual environment.

[0455] The server utilizes a 3D rendering engine (e.g., Unity, Unreal Engine) to construct a three-dimensional virtual environment based on the extracted feature information. Using these engines, a realistic and detailed virtual environment is generated based on the data provided by the user. The generated virtual environment is stored in cloud storage, and a link is sent to the user's device.

[0456] Users can access the virtual environment via this link and enjoy the experience within it using VR devices and accessories. Through this interaction, users can discover new visual experiences constructed from selected photos and video data.

[0457] As a concrete example, a user might create a virtual environment using photos taken during a trip. In this scenario, the server analyzes the shapes of mountains, seas, buildings, and other elements, and generates a realistic three-dimensional model that incorporates these elements. Through this model, the user can relive their memories of their trip.

[0458] An example of a prompt is: "Design a system that generates a virtual space based on photos taken during a trip, providing an immersive experience that recreates the scenery of that time."

[0459] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0460] Step 1:

[0461] The user opens an album app on their device and selects photos and videos they want to import into the 3D virtual environment. The selected data becomes the input. This selection determines which memories the user will recreate in the virtual environment. The device then sends the selected data to the server through a designated application.

[0462] Step 2:

[0463] The server receives photo and video data sent from the terminal and converts it into a format that is easy for the generative AI model to process. This conversion process involves data processing such as adjusting the resolution and changing the format of the data, preparing the input data for the generative algorithm. From this, the processed data is obtained as output.

[0464] Step 3:

[0465] The server analyzes the transformed data using a generating AI model and extracts the necessary feature information. At this stage, image recognition technology (e.g., convolutional neural networks) is used to extract important patterns and features from the data. The extracted feature information is output, and the process proceeds to the next stage.

[0466] Step 4:

[0467] The server constructs a three-dimensional virtual environment based on the acquired feature information. Here, a 3D rendering engine (e.g., Unity or Unreal Engine) is used to generate specific three-dimensional objects and backgrounds based on the feature information. The generated virtual environment model is then output.

[0468] Step 5:

[0469] The server saves the completed 3D virtual environment to cloud storage and sends an access link to the user's terminal. A link to the saved data is provided to the user as output. This allows the user to access the virtual environment at any time.

[0470] Step 6:

[0471] Users access a three-dimensional virtual environment using a link received on their device. They use VR devices and accessories to enjoy the experience within the virtual space. Through this experience, users can enjoy an immersive memory reconstruction based on selected photos and videos.

[0472] (Application Example 1)

[0473] 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."

[0474] In generating three-dimensional virtual spaces using photo and video data, there was a challenge in creating a system that could build an attractive commercial environment through personalized experiences for users, allowing them to make immersive product selections.

[0475] 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.

[0476] In this invention, the server includes means having a generative model for analyzing photographic or video data and extracting features; means for generating a three-dimensional virtual space based on the feature data obtained from the generative model; and means for constructing a commercial environment in the three-dimensional virtual space in which the user can experience a personalized selection process. This makes it possible for the user to explore and experience products in a virtual environment that reflects their own memories.

[0477] "Photo or video data" refers to still or moving image information owned by the user and recorded visually.

[0478] "Analysis" is the process of examining in detail the information contained in photographic or video data and extracting specific features.

[0479] "Features" refer to important information related to shape and arrangement obtained from photographic or video data.

[0480] A "generative model" is an algorithm or program that extracts features from photographic or video data and constructs a three-dimensional virtual space.

[0481] A "three-dimensional virtual space" is a computer-generated visual environment with depth, a three-dimensional space that immerses the user's senses.

[0482] A "commercial environment" is a virtual space where users can search for, select, and purchase products.

[0483] "Means of providing access" refers to the technologies and methods that enable users to connect to and experience a three-dimensional virtual space.

[0484] "Interaction" refers to the process by which a user actively acts within a virtual environment and interacts with that environment.

[0485] This invention provides a system that allows users to generate an immersive three-dimensional virtual space using their own photos and video data, and to experience that space. This system utilizes the user's terminal, a server, and cloud storage.

[0486] The server receives and analyzes photo and video data sent from user terminals. During the analysis, computer vision technologies such as the Google Cloud Vision API are used to extract features from the data. This provides important feature information based on the data.

[0487] Next, the server constructs a three-dimensional virtual space based on the acquired feature data. This process uses a 3D engine such as Unity or Unreal Engine to configure the background and object placement, generating a virtual space that reflects the user's memories. This space functions as a commercial environment, designed to allow users to select and purchase products while experiencing them.

[0488] The generated three-dimensional virtual space is stored in cloud storage, and an access link is sent to the user's device. Through this link, the user can access the virtual space using a VR device such as Oculus Quest and enjoy an immersive experience.

[0489] For example, if a user uploads photos of a beach vacation with their family, they can then explore beach-related products within a virtual store generated based on those photos.

[0490] Example of a prompt:

[0491] "Use uploaded beach photos to design a virtual shop where users can relax. This virtual space should display beach-themed items and include interactive elements that allow users to purchase those items."

[0492] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0493] Step 1:

[0494] The user selects specific photos or videos from the album application on their device. This media data becomes the initial input data for subsequent processing. The selected data is sent to the server through a designated application on the device.

[0495] Step 2:

[0496] The server prepares the received photo and video data for analysis. Specifically, it utilizes computer vision technologies such as the Google Cloud Vision API to extract features related to shape and arrangement within the photos and videos. The input for this analysis is the photos and videos submitted by the user, and the output is feature data.

[0497] Step 3:

[0498] The server generates a three-dimensional virtual space using Unity, Unreal Engine, or similar software, based on the feature data extracted in Step 2. The input is feature data, and it outputs a realistic virtual space through 3D modeling and scene construction. Specifically, it handles the placement of objects within the space, the construction of backgrounds, and the setting of interaction elements.

[0499] Step 4:

[0500] The generated three-dimensional virtual space is saved to cloud storage by the server. The server sends an access link to this virtual space to the user's terminal, preparing it for the user to experience it next. The output is a link to the virtual space.

[0501] Step 5:

[0502] Users access a virtual space via a VR device such as Oculus Quest using a received link. The input here is the access link, and the output is a virtual store where users can freely experience an immersive environment. Users explore products and interact with the virtual space through interactive elements.

[0503] 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.

[0504] This invention combines a system that generates a three-dimensional virtual space based on photographic or video data with an emotion engine that recognizes the user's emotions. This system includes means for analyzing the user's digital data and generating a three-dimensional virtual space, and provides the user with access to that virtual space. Furthermore, the emotion engine can recognize the user's emotions and bring about dynamic changes in the virtual space in response to those emotions.

[0505] In this system, the user first uses a terminal to select a specific photo or video and sends it to the server. The server inputs the selected data into a generative model and analyzes it. Through this analysis, features from the image or video are extracted, and a three-dimensional virtual space is constructed based on these features.

[0506] Next, the emotion engine recognizes the user's emotional state. For emotion recognition, real-time data is acquired from the user's facial recognition sensor and biometric information monitor and analyzed by the emotion engine. This analysis determines the user's most recent emotional state, and the atmosphere and content of the virtual space are optimized accordingly.

[0507] For example, if a user uses photos taken during a trip, the server generates a three-dimensional virtual space based on the characteristics of that location, providing a space where the user can recreate their trip. Furthermore, if the emotion engine recognizes the user's feelings of joy, it adjusts the intensity and hue of the light in the virtual space to create a brighter atmosphere.

[0508] In this way, this system not only provides an immersive experience that surpasses conventional two-dimensional media, but also realizes an interactive virtual space that responds to emotions. As a result, users can create new memories through a more personalized experience.

[0509] The following describes the processing flow.

[0510] Step 1:

[0511] The user uses their device to select specific photos or videos they want to turn into 3D from their device's album application. The selected data is uploaded to the server via a dedicated application on the device.

[0512] Step 2:

[0513] When a device sends photo or video data, it applies data compression and security protocols before transferring the data to the server. The device monitors the data sequentially until it receives confirmation of transmission from the server.

[0514] Step 3:

[0515] Upon receiving uploaded data, the server checks its integrity and completeness. It then performs preprocessing to convert the data into an appropriate format for input into the generative AI model.

[0516] Step 4:

[0517] The server uses a generative AI model to analyze photographic or video data and extract features of the subject. In this extraction process, key elements such as people and backgrounds are identified, and information necessary for 3D modeling is collected.

[0518] Step 5:

[0519] Based on the acquired feature data, the server uses a 3D modeling engine to construct a virtual space. The position and movement of objects, background details, and other elements are set, creating the virtual environment provided to the user.

[0520] Step 6:

[0521] The emotion engine analyzes the user's biometric information and facial expression data acquired through the device or external devices. Based on these analysis results, it recognizes the user's emotional state in real time.

[0522] Step 7:

[0523] The server receives input from the emotion engine and dynamically adjusts the situation and visual elements of the three-dimensional virtual space. Specifically, if the user is fatigued, it changes the music and color scheme in the space to settings that promote relaxation.

[0524] Step 8:

[0525] Users access a three-dimensional virtual space generated via their device and begin interacting within that space using a VR headset or other interface devices. An interactive experience is provided that responds to the user's emotional state.

[0526] (Example 2)

[0527] 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."

[0528] In recent years, the construction of virtual environments using digital data has attracted attention, but conventional technologies have made it difficult to provide dynamic virtual environments that reflect the user's emotional state. Furthermore, there is a need for a means to intuitively generate three-dimensional virtual environments from the user's digital images and videos, enabling personalized experiences.

[0529] 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.

[0530] In this invention, the server includes means having a generation program for analyzing image or video information and extracting features; means for creating a three-dimensional virtual environment based on the feature information obtained from the generation program; means having an analysis engine for acquiring biometric data and recognizing the user's emotional state; and means for dynamically adjusting the elements of the three-dimensional virtual environment according to the emotional state. This makes it possible to provide an immersive three-dimensional virtual environment adapted to the user's emotional state.

[0531] "Image or video information" refers to data of still images or videos stored in digital format, and is the subject of analysis as visual information.

[0532] "Feature information" refers to specific patterns, attributes, or identifiable elements extracted from image or video information, and serves as the basic data when constructing a virtual environment.

[0533] A "generation program" refers to a computer program that analyzes image or video information, extracts feature information, and generates a virtual environment.

[0534] A "three-dimensional virtual environment" refers to a digital space reproduced in three dimensions, in which users can virtually enjoy visual and tactile experiences.

[0535] The term "analysis engine" refers to a component that performs computational processing to estimate a user's emotional state by analyzing biometric data and other data indicating emotions.

[0536] "Biometric data" refers to information that indicates a user's physical state, such as facial expressions, heart rate, and skin electrical responses, and is used to recognize emotions.

[0537] "User's emotional state" refers to the psychological or emotional situation a user is currently experiencing, and includes states such as joy, sadness, and surprise.

[0538] "Dynamically adjusting internal elements" refers to changing conditions and settings within the virtual environment (e.g., light, sound, hue, etc.) in real time in response to changes in the user's emotional state.

[0539] This invention is a system that generates a individually tailored three-dimensional virtual environment using the user's existing digital images or video information, providing an immersive experience linked to the user's emotions.

[0540] First, the user selects specific image or video information using a device. For example, a smartphone or personal computer can be used as the device. The selected data is sent from the device to the server. A secure communication protocol is used for this data transfer.

[0541] The receiving server inputs the image or video information into a generating AI model. The server implements a deep learning-based generation program that extracts a wide range of feature information. Specifically, it analyzes the location, shape, and color of natural objects and buildings in landscape photographs. Three-dimensional virtual environment generation software such as Unity or Unreal Engine can be used for this process.

[0542] Based on the feature information obtained from the analysis, the server constructs a three-dimensional virtual environment. This virtual environment can be experienced interactively by the user and provides a simulated sense of reality.

[0543] Next, the user's device uses facial recognition sensors and biometric monitors to recognize the user's emotional state in real time. This allows the user to acquire biometric data such as facial expressions and heart rate, which are then validated by the server's analysis engine. Based on the analysis results, the server adjusts the internal elements of the virtual environment. For example, if the analysis determines that the user is feeling happy, the intensity of the lighting and the tone of the music in the virtual environment are adjusted.

[0544] A concrete example would be using a photo of a sunset taken by the user during a trip. In this case, an example prompt might be, "Based on this sunset photo, please adjust the space to reflect the user's feelings of joy." The server would then generate a 3D virtual environment that recreates the vibrant colors of the sunset and the sounds of the seashore, allowing the user to enjoy an immersive experience that recreates the atmosphere of the location.

[0545] This system combines generative AI models and emotion recognition technology to create an interactive virtual experience that adapts to the user's individual emotional state.

[0546] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0547] Step 1:

[0548] The user selects digital images or video information using a device and sends it to the server. The device retrieves the data from local or cloud storage and sends it to the server using a secure communication protocol (e.g., HTTPS). The input is the selected image or video information, and the output is a notification to the server that the transmission is complete.

[0549] Step 2:

[0550] The server inputs the received image or video information into the generating AI model. The server checks the data format and converts it into a format that the generating AI model can process. Specifically, it adjusts the image resolution and crops out unnecessary parts. The input is the raw data sent by the user, and the output becomes the input data for the generating AI model.

[0551] Step 3:

[0552] The server uses a generative AI model to extract feature information from image or video data. This model utilizes deep learning algorithms to extract visual features (such as color, shape, and composition). The input is pre-prepared data for the generative AI model, and the output is a feature information dataset.

[0553] Step 4:

[0554] The server constructs a three-dimensional virtual space based on the extracted feature information. The server uses software such as Unity or Unreal Engine to generate the 3D scene. Specifically, it reflects the extracted visual features in the objects and environment settings of the virtual space. The input is a feature information dataset, and the output is the generated virtual space data.

[0555] Step 5:

[0556] The device uses biometric monitors and facial recognition sensors to measure the user's emotional state in real time. The device collects data in real time and transmits it to the server. The input is the user's real-time biometric data, and the output is data prepared for analysis and sent to the server.

[0557] Step 6:

[0558] The server processes the received biometric data using an analysis engine to recognize the user's emotional state. Specifically, it uses machine learning algorithms to estimate emotional characteristics (e.g., joy, surprise, sadness). The input is biometric data transmitted from the terminal, and the output is the evaluation result of the emotional state.

[0559] Step 7:

[0560] The server dynamically adjusts the internal elements of the virtual space according to the emotional state it recognizes. Lighting settings, music tone, object movement, and other elements are optimized based on the user's emotions. The input is the result of the emotional state evaluation, and the output is the optimized virtual space.

[0561] In this way, users can experience an immersive virtual environment that adapts to their emotions.

[0562] (Application Example 2)

[0563] 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."

[0564] Traditional virtual environments based on two-dimensional media have been unable to dynamically change in response to individual user emotions, making it difficult to provide an immersive and interactive experience. Similarly, in physical stores and online shopping, providing products and services tailored to user emotions is challenging, highlighting the need for improved user experience.

[0565] 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. In this invention, the server includes means having a generative model for analyzing photographic or video data and extracting features, means for generating a three-dimensional virtual environment based on the feature data obtained from the generative model, means using an emotion engine for determining the user's emotions, means for dynamically adjusting the atmosphere and content of the virtual environment based on the emotional state determined by the emotion engine, and means for providing access to the three-dimensional virtual environment. This makes it possible for the user to enjoy a personalized virtual experience that responds to their emotions.

[0566] "Photograph or video data" refers to still images or video information stored in a digital format.

[0567] "Analysis" refers to the process of breaking down data and detecting and identifying its constituent elements and characteristics.

[0568] "Features" refer to information that indicates characteristics or patterns in photographic or video data.

[0569] A "generative model" refers to an algorithm or learning model that extracts features from input data and converts them into other formats.

[0570] A "three-dimensional virtual environment" refers to a computer-generated environment with a three-dimensional space, constructed based on digital data.

[0571] A "user" refers to a person who operates or uses a system.

[0572] An "emotion engine" refers to a system or algorithm used to detect and analyze a user's emotional state.

[0573] "Dynamic adjustment of atmosphere and content" refers to a function that changes the visual or auditory elements within the virtual environment in real time according to the user's emotional state.

[0574] "Means of providing access" refers to methods or devices for providing the interfaces and connectivity environments necessary for users to utilize the system.

[0575] To realize this invention, the server includes a system that uses an advanced generative model to analyze photographic or video data. This generative model extracts features from the data and generates the information necessary to construct a three-dimensional virtual environment. The three-dimensional virtual environment generated using the analyzed data is displayed on the user's terminal, allowing the user to experience personalized interactions through emotion recognition.

[0576] In this process, an emotion engine is used to recognize emotions acquired from the user in real time. The emotion engine analyzes data acquired from facial recognition sensors and biometric monitors attached to the user's device to determine the user's emotional state. Based on the determined emotion, the server dynamically adjusts the lighting, color, and sound elements within the virtual environment to provide the user with a more immersive and interactive experience.

[0577] For example, if a user uploads travel photos from their smartphone to the server, a three-dimensional virtual space is generated that recreates the scene from that time based on that data. If the emotion engine recognizes the user's feelings of joy, the scenery in the virtual space is adjusted to be bright and cheerful, allowing the user to realistically relive those happy memories.

[0578] Furthermore, users can provide detailed instructions to the generated AI model by offering prompts such as the following.

[0579] Example of a prompt:

[0580] Photo data: [Image file taken by the user]

[0581] Emotional data: [User's real-time emotional state]

[0582] Generation purpose: To generate a three-dimensional virtual space and adjust the environment according to emotions.

[0583] In this way, this system makes it possible to provide users with a new experience that is more emotionally resonant and to give them an environment optimized according to their emotions.

[0584] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0585] Step 1:

[0586] The user uses their device to select photo or video data and sends it to the server. The input is the digital data selected by the user. The output is that data waiting to be processed on the server.

[0587] Step 2:

[0588] The server inputs received photo or video data into a generating AI model for data analysis. The input is image data sent by the user. The server decomposes the data, finds specific structures and patterns, and extracts their features. The output is feature data necessary for generating a virtual space.

[0589] Step 3:

[0590] The server constructs a three-dimensional virtual environment based on the extracted feature data. The input is the feature data obtained in the previous step. The server uses this to generate a three-dimensional model and converts it into a form that the user can visualize. The output is visualizeable three-dimensional virtual environment data.

[0591] Step 4:

[0592] An emotion recognition sensor installed on the user's device collects the user's facial expressions and biometric information and transmits it to a server. The input is the user's biometric data, and the output is the emotion data transmitted to the server.

[0593] Step 5:

[0594] The server analyzes the received emotional data using an emotion engine to determine the user's emotional state. The input is emotional data sent by the user. The server analyzes biometric data to identify the user's current emotional state. The output is the result of the emotional state determination.

[0595] Step 6:

[0596] The server dynamically adjusts the atmosphere and content of the virtual environment based on the detected emotional state. The input is the user's emotional state. The server adjusts the lighting, color, and sound elements within the three-dimensional virtual environment to create an environment optimized for the user's emotions. As output, the adjusted virtual environment is displayed on the user's terminal.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] [Fourth Embodiment]

[0601] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0602] 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.

[0603] 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).

[0604] 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.

[0605] 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.

[0606] 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).

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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.

[0611] 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.

[0612] 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.

[0613] 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".

[0614] The system according to the present invention aims to generate an immersive three-dimensional virtual space using user-owned photo and video data, and to allow the user to access that space. This system consists of terminals, servers, and a communication network that links them.

[0615] First, the user selects specific photos or videos from an album application on their device. The selected data is sent to the server through a designated application program. The server converts the received data into a format that can be processed by the generative model and performs analysis. During the analysis, features within the photos and videos (for example, the posture of people or the shape of the scenery) are extracted.

[0616] Next, the server generates a three-dimensional virtual space based on the extracted feature data. In this process, computer vision techniques are used to construct a realistic three-dimensional model from the data. This includes backgrounds, object placement, and animations, creating a space in which the user can re-experience memories.

[0617] Subsequently, the server saves the generated three-dimensional virtual space to cloud storage and sends an access link to the user's device. The user can access the virtual space via this link through the application interface and interact with and experience the space using VR devices and accessories.

[0618] For example, if a user uses a photograph taken during a trip, the server analyzes the photo and generates a three-dimensional model that reflects mountain ranges, coastlines, and building shapes. As a result, the user can view the scenery of the place they were at at the time in the virtual space with greater realism. This makes it possible to transform two-dimensional visual data into a richer and more sensory experience.

[0619] The following describes the processing flow.

[0620] Step 1:

[0621] The user uses their device to select any photos or videos from the album application. Next, they operate the "Generate Metaverse" button within the application to send the selected data to the server.

[0622] Step 2:

[0623] The device converts the transmitted photo or video data into the specified format and transfers it to the server via the internet. During this process, protocols are applied to compress the data and ensure security.

[0624] Step 3:

[0625] When the server receives data from a terminal, it prepares the received data into a format that can be input into the AI ​​model for generation. It verifies the integrity and completeness of the data and prepares it for analysis processing.

[0626] Step 4:

[0627] The server uses a generative AI model to analyze photo and video data. Computer vision algorithms are used to extract key features from the image (e.g., people's posture, environment layout, color harmony).

[0628] Step 5:

[0629] The server generates a three-dimensional virtual space based on the feature data obtained through analysis. Using a 3D modeling engine, it constructs objects, backgrounds, and necessary animations within the digital space.

[0630] Step 6:

[0631] The server saves the generated three-dimensional virtual space to cloud storage and creates an access link. It then sends the link information to the user's device, preparing the user to access the virtual space.

[0632] Step 7:

[0633] Users access a three-dimensional virtual space generated through the application using a link notified to their device. This enables an immersive experience using devices such as VR headsets.

[0634] (Example 1)

[0635] 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".

[0636] Conventional two-dimensional visual data is limited to visual information, making it difficult to reproduce real-life experiences with a sense of realism. Furthermore, there was a need for technology that could efficiently analyze multiple photographic and video data and, based on that analysis, provide users with a realistic three-dimensional virtual space.

[0637] 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.

[0638] In this invention, the server includes a processing unit equipped with a generation algorithm for analyzing photographic or video data and extracting features, a device for constructing a three-dimensional virtual environment based on the feature information obtained from the generation algorithm, and a device for providing access to the three-dimensional virtual environment. This enables users to have a realistic three-dimensional experience based on photographic or video data.

[0639] "Photographic or video data" refers to visual information stored in the form of still or moving images, and is acquired in digital or analog format.

[0640] A "generative algorithm" is a computational method that analyzes and extracts specific patterns or features from input data and generates new information based on them.

[0641] A "processing device" is a set of hardware and software components used to perform calculations, analysis, and transformations of data.

[0642] "Feature information" refers to important patterns and characteristics extracted from photographic or video data through analysis, and is data used in subsequent processing.

[0643] A "three-dimensional virtual environment" is a three-dimensional space generated by computer technology that provides a visual experience similar to the real world.

[0644] A "device that provides access" is a mechanism that allows users to access and experience a three-dimensional virtual environment, and includes a system that incorporates network communication and interfaces.

[0645] A "visual device" is a device used by a user to receive information visually, and typically takes the form of a display, headset, or goggles.

[0646] An "interface" is a point of contact or means by which a user and a system interact with each other, and is usually provided through a screen or controller.

[0647] This invention relates to a system that generates a three-dimensional virtual environment based on photographic or video data, allowing users to experience that environment. The system includes terminals, servers, and a communication network connecting them as its main components.

[0648] The server first converts the received photo and video data into a format that can be analyzed by a generation algorithm. This process utilizes commonly used media processing frameworks and libraries (e.g., OpenCV, TensorFlow). Next, the converted data is processed by the generation algorithm to extract feature information. This feature information is directly used to construct the three-dimensional virtual environment.

[0649] The server utilizes a 3D rendering engine (e.g., Unity, Unreal Engine) to construct a three-dimensional virtual environment based on the extracted feature information. Using these engines, a realistic and detailed virtual environment is generated based on the data provided by the user. The generated virtual environment is stored in cloud storage, and a link is sent to the user's device.

[0650] Users can access the virtual environment via this link and enjoy the experience within it using VR devices and accessories. Through this interaction, users can discover new visual experiences constructed from selected photos and video data.

[0651] As a concrete example, a user might create a virtual environment using photos taken during a trip. In this scenario, the server analyzes the shapes of mountains, seas, buildings, and other elements, and generates a realistic three-dimensional model that incorporates these elements. Through this model, the user can relive their memories of their trip.

[0652] An example of a prompt is: "Design a system that generates a virtual space based on photos taken during a trip, providing an immersive experience that recreates the scenery of that time."

[0653] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0654] Step 1:

[0655] The user opens an album app on their device and selects photos and videos they want to import into the 3D virtual environment. The selected data becomes the input. This selection determines which memories the user will recreate in the virtual environment. The device then sends the selected data to the server through a designated application.

[0656] Step 2:

[0657] The server receives photo and video data sent from the terminal and converts it into a format that is easy for the generative AI model to process. This conversion process involves data processing such as adjusting the resolution and changing the format of the data, preparing the input data for the generative algorithm. From this, the processed data is obtained as output.

[0658] Step 3:

[0659] The server analyzes the transformed data using a generating AI model and extracts the necessary feature information. At this stage, image recognition technology (e.g., convolutional neural networks) is used to extract important patterns and features from the data. The extracted feature information is output, and the process proceeds to the next stage.

[0660] Step 4:

[0661] The server constructs a three-dimensional virtual environment based on the acquired feature information. Here, a 3D rendering engine (e.g., Unity or Unreal Engine) is used to generate specific three-dimensional objects and backgrounds based on the feature information. The generated virtual environment model is then output.

[0662] Step 5:

[0663] The server saves the completed 3D virtual environment to cloud storage and sends an access link to the user's terminal. A link to the saved data is provided to the user as output. This allows the user to access the virtual environment at any time.

[0664] Step 6:

[0665] Users access a three-dimensional virtual environment using a link received on their device. They use VR devices and accessories to enjoy the experience within the virtual space. Through this experience, users can enjoy an immersive memory reconstruction based on selected photos and videos.

[0666] (Application Example 1)

[0667] 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".

[0668] In generating three-dimensional virtual spaces using photo and video data, there was a challenge in creating a system that could build an attractive commercial environment through personalized experiences for users, allowing them to make immersive product selections.

[0669] 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.

[0670] In this invention, the server includes means having a generative model for analyzing photographic or video data and extracting features; means for generating a three-dimensional virtual space based on the feature data obtained from the generative model; and means for constructing a commercial environment in the three-dimensional virtual space in which the user can experience a personalized selection process. This makes it possible for the user to explore and experience products in a virtual environment that reflects their own memories.

[0671] "Photo or video data" refers to still or moving image information owned by the user and recorded visually.

[0672] "Analysis" is the process of examining in detail the information contained in photographic or video data and extracting specific features.

[0673] "Features" refer to important information related to shape and arrangement obtained from photographic or video data.

[0674] A "generative model" is an algorithm or program that extracts features from photographic or video data and constructs a three-dimensional virtual space.

[0675] A "three-dimensional virtual space" is a computer-generated visual environment with depth, a three-dimensional space that immerses the user's senses.

[0676] A "commercial environment" is a virtual space where users can search for, select, and purchase products.

[0677] "Means of providing access" refers to the technologies and methods that enable users to connect to and experience a three-dimensional virtual space.

[0678] "Interaction" refers to the process by which a user actively acts within a virtual environment and interacts with that environment.

[0679] This invention provides a system that allows users to generate an immersive three-dimensional virtual space using their own photos and video data, and to experience that space. This system utilizes the user's terminal, a server, and cloud storage.

[0680] The server receives and analyzes photo and video data sent from user terminals. During the analysis, computer vision technologies such as the Google Cloud Vision API are used to extract features from the data. This provides important feature information based on the data.

[0681] Next, the server constructs a three-dimensional virtual space based on the acquired feature data. This process uses a 3D engine such as Unity or Unreal Engine to configure the background and object placement, generating a virtual space that reflects the user's memories. This space functions as a commercial environment, designed to allow users to select and purchase products while experiencing them.

[0682] The generated three-dimensional virtual space is stored in cloud storage, and an access link is sent to the user's device. Through this link, the user can access the virtual space using a VR device such as Oculus Quest and enjoy an immersive experience.

[0683] For example, if a user uploads photos of a beach vacation with their family, they can then explore beach-related products within a virtual store generated based on those photos.

[0684] Example of a prompt:

[0685] "Use uploaded beach photos to design a virtual shop where users can relax. This virtual space should display beach-themed items and include interactive elements that allow users to purchase those items."

[0686] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0687] Step 1:

[0688] The user selects specific photos or videos from the album application on their device. This media data becomes the initial input data for subsequent processing. The selected data is sent to the server through a designated application on the device.

[0689] Step 2:

[0690] The server prepares the received photo and video data for analysis. Specifically, it utilizes computer vision technologies such as the Google Cloud Vision API to extract features related to shape and arrangement within the photos and videos. The input for this analysis is the photos and videos submitted by the user, and the output is feature data.

[0691] Step 3:

[0692] The server generates a three-dimensional virtual space using Unity, Unreal Engine, or similar software, based on the feature data extracted in Step 2. The input is feature data, and it outputs a realistic virtual space through 3D modeling and scene construction. Specifically, it handles the placement of objects within the space, the construction of backgrounds, and the setting of interaction elements.

[0693] Step 4:

[0694] The generated three-dimensional virtual space is saved to cloud storage by the server. The server sends an access link to this virtual space to the user's terminal, preparing it for the user to experience it next. The output is a link to the virtual space.

[0695] Step 5:

[0696] Users access a virtual space via a VR device such as Oculus Quest using a received link. The input here is the access link, and the output is a virtual store where users can freely experience an immersive environment. Users explore products and interact with the virtual space through interactive elements.

[0697] 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.

[0698] This invention combines a system that generates a three-dimensional virtual space based on photographic or video data with an emotion engine that recognizes the user's emotions. This system includes means for analyzing the user's digital data and generating a three-dimensional virtual space, and provides the user with access to that virtual space. Furthermore, the emotion engine can recognize the user's emotions and bring about dynamic changes in the virtual space in response to those emotions.

[0699] In this system, the user first uses a terminal to select a specific photo or video and sends it to the server. The server inputs the selected data into a generative model and analyzes it. Through this analysis, features from the image or video are extracted, and a three-dimensional virtual space is constructed based on these features.

[0700] Next, the emotion engine recognizes the user's emotional state. For emotion recognition, real-time data is acquired from the user's facial recognition sensor and biometric information monitor and analyzed by the emotion engine. This analysis determines the user's most recent emotional state, and the atmosphere and content of the virtual space are optimized accordingly.

[0701] For example, if a user uses photos taken during a trip, the server generates a three-dimensional virtual space based on the characteristics of that location, providing a space where the user can recreate their trip. Furthermore, if the emotion engine recognizes the user's feelings of joy, it adjusts the intensity and hue of the light in the virtual space to create a brighter atmosphere.

[0702] In this way, this system not only provides an immersive experience that surpasses conventional two-dimensional media, but also realizes an interactive virtual space that responds to emotions. As a result, users can create new memories through a more personalized experience.

[0703] The following describes the processing flow.

[0704] Step 1:

[0705] The user uses their device to select specific photos or videos they want to turn into 3D from their device's album application. The selected data is uploaded to the server via a dedicated application on the device.

[0706] Step 2:

[0707] When a device sends photo or video data, it applies data compression and security protocols before transferring the data to the server. The device monitors the data sequentially until it receives confirmation of transmission from the server.

[0708] Step 3:

[0709] Upon receiving uploaded data, the server checks its integrity and completeness. It then performs preprocessing to convert the data into an appropriate format for input into the generative AI model.

[0710] Step 4:

[0711] The server uses a generative AI model to analyze photographic or video data and extract features of the subject. In this extraction process, key elements such as people and backgrounds are identified, and information necessary for 3D modeling is collected.

[0712] Step 5:

[0713] Based on the acquired feature data, the server uses a 3D modeling engine to construct a virtual space. The position and movement of objects, background details, and other elements are set, creating the virtual environment provided to the user.

[0714] Step 6:

[0715] The emotion engine analyzes the user's biometric information and facial expression data acquired through the device or external devices. Based on these analysis results, it recognizes the user's emotional state in real time.

[0716] Step 7:

[0717] The server receives input from the emotion engine and dynamically adjusts the situation and visual elements of the three-dimensional virtual space. Specifically, if the user is fatigued, it changes the music and color scheme in the space to settings that promote relaxation.

[0718] Step 8:

[0719] Users access a three-dimensional virtual space generated via their device and begin interacting within that space using a VR headset or other interface devices. An interactive experience is provided that responds to the user's emotional state.

[0720] (Example 2)

[0721] 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".

[0722] In recent years, the construction of virtual environments using digital data has attracted attention, but conventional technologies have made it difficult to provide dynamic virtual environments that reflect the user's emotional state. Furthermore, there is a need for a means to intuitively generate three-dimensional virtual environments from the user's digital images and videos, enabling personalized experiences.

[0723] 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.

[0724] In this invention, the server includes means having a generation program for analyzing image or video information and extracting features; means for creating a three-dimensional virtual environment based on the feature information obtained from the generation program; means having an analysis engine for acquiring biometric data and recognizing the user's emotional state; and means for dynamically adjusting the elements of the three-dimensional virtual environment according to the emotional state. This makes it possible to provide an immersive three-dimensional virtual environment adapted to the user's emotional state.

[0725] "Image or video information" refers to data of still images or videos stored in digital format, and is the subject of analysis as visual information.

[0726] "Feature information" refers to specific patterns, attributes, or identifiable elements extracted from image or video information, and serves as the basic data when constructing a virtual environment.

[0727] A "generation program" refers to a computer program that analyzes image or video information, extracts feature information, and generates a virtual environment.

[0728] A "three-dimensional virtual environment" refers to a digital space reproduced in three dimensions, in which users can virtually enjoy visual and tactile experiences.

[0729] The term "analysis engine" refers to a component that performs computational processing to estimate a user's emotional state by analyzing biometric data and other data indicating emotions.

[0730] "Biometric data" refers to information that indicates a user's physical state, such as facial expressions, heart rate, and skin electrical responses, and is used to recognize emotions.

[0731] "User's emotional state" refers to the psychological or emotional situation a user is currently experiencing, and includes states such as joy, sadness, and surprise.

[0732] "Dynamically adjusting internal elements" refers to changing conditions and settings within the virtual environment (e.g., light, sound, hue, etc.) in real time in response to changes in the user's emotional state.

[0733] This invention is a system that generates a individually tailored three-dimensional virtual environment using the user's existing digital images or video information, providing an immersive experience linked to the user's emotions.

[0734] First, the user selects specific image or video information using a device. For example, a smartphone or personal computer can be used as the device. The selected data is sent from the device to the server. A secure communication protocol is used for this data transfer.

[0735] The receiving server inputs the image or video information into a generating AI model. The server implements a deep learning-based generation program that extracts a wide range of feature information. Specifically, it analyzes the location, shape, and color of natural objects and buildings in landscape photographs. Three-dimensional virtual environment generation software such as Unity or Unreal Engine can be used for this process.

[0736] Based on the feature information obtained from the analysis, the server constructs a three-dimensional virtual environment. This virtual environment can be experienced interactively by the user and provides a simulated sense of reality.

[0737] Next, the user's device uses facial recognition sensors and biometric monitors to recognize the user's emotional state in real time. This allows the user to acquire biometric data such as facial expressions and heart rate, which are then validated by the server's analysis engine. Based on the analysis results, the server adjusts the internal elements of the virtual environment. For example, if the analysis determines that the user is feeling happy, the intensity of the lighting and the tone of the music in the virtual environment are adjusted.

[0738] A concrete example would be using a photo of a sunset taken by the user during a trip. In this case, an example prompt might be, "Based on this sunset photo, please adjust the space to reflect the user's feelings of joy." The server would then generate a 3D virtual environment that recreates the vibrant colors of the sunset and the sounds of the seashore, allowing the user to enjoy an immersive experience that recreates the atmosphere of the location.

[0739] This system combines generative AI models and emotion recognition technology to create an interactive virtual experience that adapts to the user's individual emotional state.

[0740] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0741] Step 1:

[0742] The user selects digital images or video information using a device and sends it to the server. The device retrieves the data from local or cloud storage and sends it to the server using a secure communication protocol (e.g., HTTPS). The input is the selected image or video information, and the output is a notification to the server that the transmission is complete.

[0743] Step 2:

[0744] The server inputs the received image or video information into the generating AI model. The server checks the data format and converts it into a format that the generating AI model can process. Specifically, it adjusts the image resolution and crops out unnecessary parts. The input is the raw data sent by the user, and the output becomes the input data for the generating AI model.

[0745] Step 3:

[0746] The server uses a generative AI model to extract feature information from image or video data. This model utilizes deep learning algorithms to extract visual features (such as color, shape, and composition). The input is pre-prepared data for the generative AI model, and the output is a feature information dataset.

[0747] Step 4:

[0748] The server constructs a three-dimensional virtual space based on the extracted feature information. The server uses software such as Unity or Unreal Engine to generate the 3D scene. Specifically, it reflects the extracted visual features in the objects and environment settings of the virtual space. The input is a feature information dataset, and the output is the generated virtual space data.

[0749] Step 5:

[0750] The device uses biometric monitors and facial recognition sensors to measure the user's emotional state in real time. The device collects data in real time and transmits it to the server. The input is the user's real-time biometric data, and the output is data prepared for analysis and sent to the server.

[0751] Step 6:

[0752] The server processes the received biometric data using an analysis engine to recognize the user's emotional state. Specifically, it uses machine learning algorithms to estimate emotional characteristics (e.g., joy, surprise, sadness). The input is biometric data transmitted from the terminal, and the output is the evaluation result of the emotional state.

[0753] Step 7:

[0754] The server dynamically adjusts the internal elements of the virtual space according to the emotional state it recognizes. Lighting settings, music tone, object movement, and other elements are optimized based on the user's emotions. The input is the result of the emotional state evaluation, and the output is the optimized virtual space.

[0755] In this way, users can experience an immersive virtual environment that adapts to their emotions.

[0756] (Application Example 2)

[0757] 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".

[0758] Traditional virtual environments based on two-dimensional media have been unable to dynamically change in response to individual user emotions, making it difficult to provide an immersive and interactive experience. Similarly, in physical stores and online shopping, providing products and services tailored to user emotions is challenging, highlighting the need for improved user experience.

[0759] 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. In this invention, the server includes means having a generative model for analyzing photographic or video data and extracting features, means for generating a three-dimensional virtual environment based on the feature data obtained from the generative model, means using an emotion engine for determining the user's emotions, means for dynamically adjusting the atmosphere and content of the virtual environment based on the emotional state determined by the emotion engine, and means for providing access to the three-dimensional virtual environment. This makes it possible for the user to enjoy a personalized virtual experience that responds to their emotions.

[0760] "Photograph or video data" refers to still images or video information stored in a digital format.

[0761] "Analysis" refers to the process of breaking down data and detecting and identifying its constituent elements and characteristics.

[0762] "Features" refer to information that indicates characteristics or patterns in photographic or video data.

[0763] A "generative model" refers to an algorithm or learning model that extracts features from input data and converts them into other formats.

[0764] A "three-dimensional virtual environment" refers to a computer-generated environment with a three-dimensional space, constructed based on digital data.

[0765] A "user" refers to a person who operates or uses a system.

[0766] An "emotion engine" refers to a system or algorithm used to detect and analyze a user's emotional state.

[0767] "Dynamic adjustment of atmosphere and content" refers to a function that changes the visual or auditory elements within the virtual environment in real time according to the user's emotional state.

[0768] "Means of providing access" refers to methods or devices for providing the interfaces and connectivity environments necessary for users to utilize the system.

[0769] To realize this invention, the server includes a system that uses an advanced generative model to analyze photographic or video data. This generative model extracts features from the data and generates the information necessary to construct a three-dimensional virtual environment. The three-dimensional virtual environment generated using the analyzed data is displayed on the user's terminal, allowing the user to experience personalized interactions through emotion recognition.

[0770] In this process, an emotion engine is used to recognize emotions acquired from the user in real time. The emotion engine analyzes data acquired from facial recognition sensors and biometric monitors attached to the user's device to determine the user's emotional state. Based on the determined emotion, the server dynamically adjusts the lighting, color, and sound elements within the virtual environment to provide the user with a more immersive and interactive experience.

[0771] For example, if a user uploads travel photos from their smartphone to the server, a three-dimensional virtual space is generated that recreates the scene from that time based on that data. If the emotion engine recognizes the user's feelings of joy, the scenery in the virtual space is adjusted to be bright and cheerful, allowing the user to realistically relive those happy memories.

[0772] Furthermore, users can provide detailed instructions to the generated AI model by offering prompts such as the following.

[0773] Example of a prompt:

[0774] Photo data: [Image file taken by the user]

[0775] Emotional data: [User's real-time emotional state]

[0776] Generation purpose: To generate a three-dimensional virtual space and adjust the environment according to emotions.

[0777] In this way, this system makes it possible to provide users with a new experience that is more emotionally resonant and to give them an environment optimized according to their emotions.

[0778] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0779] Step 1:

[0780] The user uses their device to select photo or video data and sends it to the server. The input is the digital data selected by the user. The output is that data waiting to be processed on the server.

[0781] Step 2:

[0782] The server inputs received photo or video data into a generating AI model for data analysis. The input is image data sent by the user. The server decomposes the data, finds specific structures and patterns, and extracts their features. The output is feature data necessary for generating a virtual space.

[0783] Step 3:

[0784] The server constructs a three-dimensional virtual environment based on the extracted feature data. The input is the feature data obtained in the previous step. The server uses this to generate a three-dimensional model and converts it into a form that the user can visualize. The output is visualizeable three-dimensional virtual environment data.

[0785] Step 4:

[0786] An emotion recognition sensor installed on the user's device collects the user's facial expressions and biometric information and transmits it to a server. The input is the user's biometric data, and the output is the emotion data transmitted to the server.

[0787] Step 5:

[0788] The server analyzes the received emotional data using an emotion engine to determine the user's emotional state. The input is emotional data sent by the user. The server analyzes biometric data to identify the user's current emotional state. The output is the result of the emotional state determination.

[0789] Step 6:

[0790] The server dynamically adjusts the atmosphere and content of the virtual environment based on the detected emotional state. The input is the user's emotional state. The server adjusts the lighting, color, and sound elements within the three-dimensional virtual environment to create an environment optimized for the user's emotions. As output, the adjusted virtual environment is displayed on the user's terminal.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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."

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] The following is further disclosed regarding the embodiments described above.

[0813] (Claim 1)

[0814] A means having a generative model for analyzing photographic or video data and extracting features,

[0815] A means for generating a three-dimensional virtual space based on feature data obtained from the generative model,

[0816] Means for providing access to the three-dimensional virtual space,

[0817] A system that includes this.

[0818] (Claim 2)

[0819] The system according to claim 1, further comprising means for receiving photographic or video data and preparing it as input data for a generative model.

[0820] (Claim 3)

[0821] The system according to claim 1, further comprising means for providing an interface for a user to interact in the generated three-dimensional virtual space.

[0822] "Example 1"

[0823] (Claim 1)

[0824] A processing device equipped with a generation algorithm for analyzing photographic or video data and extracting features,

[0825] A device for constructing a three-dimensional virtual environment based on feature information obtained from the generation algorithm,

[0826] A device that provides access to the three-dimensional virtual environment,

[0827] A means of conducting an experience within a virtual environment via the user's visual device,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, further comprising a device for receiving image or video data and modifying it as input information to a generation algorithm.

[0831] (Claim 3)

[0832] The system according to claim 1, further comprising a device that provides an interface for users to interact in the generated three-dimensional virtual environment.

[0833] "Application Example 1"

[0834] (Claim 1)

[0835] A means having a generative model for analyzing photographic or video data and extracting features,

[0836] A means for generating a three-dimensional virtual space based on feature data obtained from the generative model,

[0837] A means for constructing a commercial environment in the three-dimensional virtual space in which users can experience a personalized selection process,

[0838] Means for providing access to the three-dimensional virtual space,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, further comprising means for receiving photographic or video data and preparing it as input data for a generative model.

[0842] (Claim 3)

[0843] The system according to claim 1, further comprising means for providing an interface for a user to interact in the generated three-dimensional virtual space.

[0844] "Example 2 of combining an emotion engine"

[0845] (Claim 1)

[0846] A means having a generation program for analyzing image or video information and extracting features,

[0847] A means for creating a three-dimensional virtual environment based on the characteristic information obtained from the generation program,

[0848] A means having an analysis engine for acquiring biometric data and recognizing the user's emotional state,

[0849] A means for dynamically adjusting the elements of a three-dimensional virtual environment according to the emotional state,

[0850] Means for providing connection to the three-dimensional virtual environment,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, further comprising means for receiving image or video information and preparing it as input information for a generation program.

[0854] (Claim 3)

[0855] The system according to claim 1, further comprising means for providing a communication surface for users to interact in the generated three-dimensional virtual environment.

[0856] "Application example 2 when combining with an emotional engine"

[0857] (Claim 1)

[0858] A means having a generative model for analyzing photographic or video data and extracting features,

[0859] A means for generating a three-dimensional virtual environment based on feature data obtained from the generative model,

[0860] A method using an emotion engine to determine the user's emotions,

[0861] A means for dynamically adjusting the atmosphere and content of a virtual environment based on the emotional state determined by the emotion engine,

[0862] Means for providing access to the three-dimensional virtual environment,

[0863] A system that includes this.

[0864] (Claim 2)

[0865] The system according to claim 1, further comprising means for receiving photographic or video data and preparing it as input information for a generative model.

[0866] (Claim 3)

[0867] The system according to claim 1, further comprising means for providing an interface for a user to interact in the generated three-dimensional virtual environment. [Explanation of Symbols]

[0868] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means having a generative model for analyzing photographic or video data and extracting features, A means for generating a three-dimensional virtual space based on feature data obtained from the generative model, Means for providing access to the three-dimensional virtual space, A system that includes this.

2. The system according to claim 1, further comprising means for receiving photographic or video data and preparing it as input data for a generative model.

3. The system according to claim 1, further comprising means for providing an interface for a user to interact in the generated three-dimensional virtual space.

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