System

Abstract

A system is provided.SOLUTION: A system, comprising: means for a user to input filtering settings; means for capturing visual information using a camera; means for transmitting the captured visual information to a server; means for analyzing the visual information at the server to identify unwanted information based on the filtering settings; means for modifying the identified unwanted information; means for transmitting the modified visual information to a terminal; and means for displaying the modified visual information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's information-overloaded environment, it is difficult for individuals to access the information they need without being exposed to unnecessary or unpleasant information. It is particularly difficult to visually avoid advertisements, war information, and other such information. By solving this problem, users can focus only on the information they need, creating a more comfortable, stress-free information environment. [Means for solving the problem]

[0005] The information filtering eyewear system according to the present invention includes the following means: a means for a user to input filtering settings, a means for capturing visual information using a camera, a means for transmitting the captured visual information to a server, a means for analyzing the visual information in the server and identifying unnecessary information based on the filtering settings, a means for modifying the identified unnecessary information, a means for transmitting the modified visual information to a terminal, and a means for displaying the modified visual information. In particular, the filtering settings include specific keywords, categories, or images, and the system includes a means for masking or mosaic-processing the unnecessary information. This configuration allows a user to visually avoid unnecessary or unpleasant information.

[0006] A "user" is an individual or entity that uses an information filtering eyewear system.

[0007] "Filtering settings" refer to the criteria or conditions that a user inputs into the system to identify unwanted or objectionable information from the visually available information.

[0008] A "camera" is a photographic device for capturing visual information.

[0009] "Visual information" refers to images and video data of the user's surroundings captured by a camera.

[0010] A "server" is a computer system or network service for receiving, analyzing, and filtering visual information.

[0011] "Analysis" is the process of using techniques such as image recognition and text analysis to identify unwanted information in visual information.

[0012] "Unwanted information" refers to information that a user wants removed from view based on filtering settings.

[0013] "Modifying" refers to processing the visual information so that it cannot be visually recognized by the user, for example by masking or mosaic-processing unnecessary information contained in the visual information.

[0014] A "terminal" is a computing device that is used in conjunction with the eyewear used by a user.

[0015] "Display" refers to the terminal displaying the modified visual information on the eyewear display. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention relates to an information filtering eyewear system that is a system for filtering information visually perceived by an individual, eliminating unnecessary or unpleasant information and providing necessary and comfortable information to the user.

[0038] Program processing explanation

[0039] System Configuration

[0040] 1. Equipment configuration

[0041] The eyewear worn by the user includes a built-in camera and display.

[0042] The terminals are devices such as smartphones and tablets, and have a dedicated filtering application installed.

[0043] The server is a high performance computer system for performing the analysis and filtering processes.

[0044] 2. System Operation

[0045] The user puts on the eyewear and launches the dedicated app on their device.

[0046] Users configure filtering settings within the app, including specific keywords, categories (e.g., ads, news), and images.

[0047] Information collection and transmission

[0048] 3. Information gathering

[0049] The device's camera captures visual information in real time, which is then saved as images or videos.

[0050] 4. Data transmission

[0051] The device sends the captured visual information to a server, where the data is encrypted to ensure security.

[0052] Filtering Process

[0053] 5. Analysis and Processing

[0054] The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted information based on the filtering settings.

[0055] 6. Corrective Actions

[0056] The server then modifies the identified unwanted information by masking or mosaicking it, etc. At this stage, the unwanted information is removed from the user's view.

[0057] Receiving and displaying data

[0058] 7. Sending and Receiving Data

[0059] The server then sends the corrected visual information to the device, and the data sent is also encrypted.

[0060] 8. Display of correction information

[0061] The device displays the corrected visual information on the eyewear, allowing the user to visually recognize the filtered information.

[0062] Specific examples

[0063] Ad filtering

[0064] If a user indicates that they do not want to see ads for a particular brand in the shopping mall:

[0065] 1. As the user walks around town, the device's camera captures store advertisements.

[0066] 2. The device sends the image data to the server.

[0067] 3. The server analyzes the received image data and identifies advertisements that match the filtering settings.

[0068] 4. The server blurs the advertisement portion and sends the corrected data to the device.

[0069] 5. The device displays the modified image on the eyewear, preventing the user from seeing the specific brand advertisements.

[0070] Filtering unpleasant news

[0071] If the user does not want to see news about wars or disasters:

[0072] 1. The device's camera captures an image of a newspaper stand.

[0073] 2. The device sends the image data to the server.

[0074] 3. The server performs text analysis to identify articles about war and disasters.

[0075] 4. The server masks that portion and sends the corrected data to the terminal.

[0076] 5. The device displays the corrected image on the eyewear, preventing the user from seeing the unpleasant news.

[0077] This allows users to focus on necessary information without being exposed to unnecessary or unpleasant information. This system functions as an effective means of maintaining a comfortable personal information environment.

[0078] The processing flow will be explained below.

[0079] Step 1:

[0080] Users launch the dedicated application on their device. After launching the application, users access the filtering settings screen and set criteria for unwanted information, including specific keywords, categories (e.g., ads, news), and images. These settings are then saved.

[0081] Step 2:

[0082] The device activates the camera and captures visual information in real time, which is then temporarily stored in the device's memory.

[0083] Step 3:

[0084] The device sends the captured visual information to a server, encrypted for security purposes, over Wi-Fi or mobile data networks.

[0085] Step 4:

[0086] The server prepares the received visual information for analysis, applying image recognition techniques (e.g., object recognition, OCR text analysis) to the visual information to search for unwanted content that matches the filtering settings.

[0087] Step 5:

[0088] The server identifies unwanted content based on the filtering settings, such as advertising banners or text containing specific keywords, and records the location of any content identified as unwanted.

[0089] Step 6:

[0090] The server then corrects the identified unnecessary information by masking the unnecessary information (e.g., by pixelating the image), so that the user cannot see the unnecessary information.

[0091] Step 7:

[0092] The server then sends the corrected visual information to the terminal, where the corrected data is encrypted again to ensure security.

[0093] Step 8:

[0094] The device receives the corrected visual information and displays it on the eyewear. By displaying the corrected visual information on the eyewear display in real time, the user can enjoy a comfortable information environment with unnecessary information removed.

[0095] Example 1

[0096] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0097] In today's information-overloaded environment, users are often exposed to unnecessary or unpleasant visual information. This information can disrupt users' concentration and cause psychological stress. In response, there is a need for a system that allows users to filter out unnecessary information and visually perceive only the necessary and pleasant information.

[0098] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0099] In this invention, the server includes means for using object recognition technology and text analysis technology when correcting visual information based on filtering settings, means for displaying the corrected visual information on the eyewear in real time, and means for encrypting communications between the server and the terminal, thereby enabling the user to automatically filter unnecessary information in real time and view only visual information that is comfortable to the user.

[0100] "User" refers to the individual who wears the eyewear and configures the filtering settings.

[0101] "Filtering settings" refers to settings of specific keywords, categories, or images that a user enters to identify unwanted information.

[0102] "Camera" refers to a photographic device used to capture visual information.

[0103] "Visual information" refers to image and video data captured by a camera.

[0104] "Server" refers to a high performance computer system for analyzing and filtering visual information.

[0105] "Terminal" refers to a device such as a smartphone or tablet on which a dedicated filtering application is installed.

[0106] "Object recognition technology" refers to technology that automatically identifies specific objects within visual information.

[0107] "Text analysis technology" refers to technology that analyzes text within visual information and understands its meaning.

[0108] "Masking" refers to the process of painting over part of visual information to hide unnecessary information.

[0109] "Mosaicing" refers to the process of covering part of visual information with a fine block-like pattern in order to hide unnecessary information.

[0110] "Real time" refers to processing and display occurring immediately, without delay.

[0111] "Encryption" refers to the technology of converting data so that its contents cannot be recognized by third parties.

[0112] "Eyewear" refers to glasses-type devices that incorporate a camera and a display.

[0113] The present invention relates to a system for filtering information visually perceived by an individual, and more particularly to an information filtering eyewear system that eliminates unnecessary or unpleasant information and provides necessary and comfortable information to the user.

[0114] System configuration and operation overview

[0115] The system consists of three main components:

[0116] 1. Eyewear worn by the user

[0117] 2. A device with the dedicated application installed

[0118] 3. Server that performs information analysis and filtering

[0119] 1. Eyewear worn by the user

[0120] The eyewear includes a built-in camera for capturing visual information and a display for displaying the corrected visual information. The eyewear communicates with the device using Bluetooth or Wi-Fi.

[0121] 2. A device with the dedicated application installed

[0122] A dedicated filtering application is installed on a user's device (such as a smartphone or tablet), and this application provides an interface for the user to input filtering settings.

[0123] 3. Server that performs information analysis and filtering

[0124] The server is a high-performance computer system that receives and analyzes the visual information sent from the device, using object recognition and text analysis techniques.

[0125] Specific processing details

[0126] Enter filtering settings

[0127] Using a dedicated application, users input their desired filtering settings, such as specific keywords (such as "advertising" or "news"), categories, or images (such as a particular brand logo).

[0128] Visual information capture

[0129] While the user is walking or moving around, the built-in camera in the eyewear captures visual information from the surroundings in real time, which is then transmitted to the device.

[0130] Data transmission and analysis

[0131] The device transmits the captured visual information to a server, which encrypts and secures the data. The server then analyzes the received data and identifies unwanted content based on the filtering settings. For example, the server uses object recognition technology to identify specific brand advertisements and text analysis technology to identify offensive news articles.

[0132] Correcting and Viewing Information

[0133] The server then corrects the identified unwanted information (specifically, by masking or mosaicing) and sends the corrected visual information to the device, which then displays the corrected information in real time on the eyewear display, allowing the user to view the filtered, comfortable visual information.

[0134] Specific use cases

[0135] Ad filtering example

[0136] 1. A user sets a filtering app to "I don't want to see ads for a specific brand X."

[0137] 2. When the user enters the shopping mall, the eyewear captures the advertisement.

[0138] 3. The device sends the captured image data to the server.

[0139] 4. The server parses the ad and identifies the ad for Brand X.

[0140] 5. The server blurs the advertisement portion and sends the correction data to the terminal.

[0141] 6. The device displays the corrected information on the eyewear, and the user no longer sees Brand X's advertisements.

[0142] Prompt Sentence Examples

[0143] "Filter ads for brands you don't want to see in the mall."

[0144] Example of filtering unpleasant news

[0145] 1. The user sets a filtering app to "I don't want to see news about war or disasters."

[0146] 2. The device's camera captures an image of the newsstand.

[0147] 3. The device sends the image data to the server.

[0148] 4. The server analyzes the received data and identifies articles about wars and disasters.

[0149] 5. The server masks that portion and sends the corrected data to the terminal.

[0150] 6. The device displays the corrected information on the eyewear, and the user no longer sees the unpleasant news.

[0151] Prompt Sentence Examples

[0152] "Filter news about wars and disasters."

[0153] This system allows users to focus on the information they need without being exposed to unnecessary or unpleasant information.

[0154] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0155] Step 1:

[0156] The user launches the dedicated filtering app and puts on the eyewear, which then communicates with the device via Bluetooth or Wi-Fi to check the connection status.

[0157] Specific behavior:

[0158] The user taps on the device to launch the app.

[0159] The app screen will open and you can check the connection status with your eyewear.

[0160] The user puts on the eyewear and confirms that "Connection complete" is displayed on the app screen.

[0161] Input: Application launch, eyewear connection

[0162] Output: Eyewear and device are connected properly

[0163] Step 2:

[0164] The user enters their filtering preferences: they select specific keywords, categories, or images in the app's settings screen.

[0165] Specific behavior:

[0166] Select a filtering category from the list displayed on the settings screen.

[0167] Enter a word or phrase in the text field provided for entering specific keywords.

[0168] For image filtering, select an image from your camera roll.

[0169] Input: Filtering settings (keywords, categories, images)

[0170] Output: User filtering settings data

[0171] Step 3:

[0172] While the user is active, the eyewear's camera captures visual information in real time, which is then stored on the device as images or videos.

[0173] Specific behavior:

[0174] The eyewear's camera automatically captures visual information from your surroundings.

[0175] The captured information is transferred to the device in real time.

[0176] Input: Real-world visual information

[0177] Output: Captured visual information (images, videos)

[0178] Step 4:

[0179] The device encrypts the captured visual information and sends it to the server, ensuring security.

[0180] Specific behavior:

[0181] The terminal receives the captured visual information.

[0182] The received data is encrypted and sent to the server.

[0183] Input: Captured visual information

[0184] Output: Encrypted visual information

[0185] Step 5:

[0186] The server decodes the received visual information and begins analyzing it, using object recognition and text analysis techniques to identify unwanted content based on the filtering settings.

[0187] Specific behavior:

[0188] The server decrypts the encrypted data.

[0189] Object recognition algorithms are used to detect specific objects within the visual information.

[0190] Text analysis techniques are used to analyze text within visual information.

[0191] Input: Encrypted visual information

[0192] Output: Analysis results (identification of unnecessary information)

[0193] Step 6:

[0194] The server then modifies the identified unwanted information, for example by masking or mosaicing it, to generate modified visual information.

[0195] Specific behavior:

[0196] The server identifies the garbage.

[0197] Apply masking or mosaic processing to unwanted information.

[0198] Input: Analysis results (identification of unnecessary information)

[0199] Output: Corrected visual information

[0200] Step 7:

[0201] The server re-encrypts the corrected visual information and sends it to the terminal. For security reasons, the transmitted data is encrypted.

[0202] Specific behavior:

[0203] The server encrypts the modified visual information.

[0204] The encrypted data is sent to the terminal.

[0205] Input: Corrected visual information

[0206] Output: Encrypted revision information

[0207] Step 8:

[0208] The terminal receives the modified visual information, decodes it, and displays it on the eyewear, allowing the user to visually perceive the filtered information.

[0209] Specific behavior:

[0210] The terminal receives the encrypted modification information.

[0211] Decrypt the received data.

[0212] The decoded information is displayed on the eyewear display.

[0213] Input: Encrypted correction information

[0214] Output: Corrected visual information displayed on eyewear

[0215] (Application example 1)

[0216] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0217] In surveillance work, it is necessary to provide an environment in which surveillance personnel can perform their work efficiently and comfortably, reducing the stress caused by being exposed to visually unpleasant or unnecessary information.In addition, it is necessary to focus on monitoring specific targets within the surveillance area, which is necessary to prevent crime and ensure the safety of citizens.

[0218] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0219] In this invention, the server includes a means for a user to input filtering settings, a means for capturing visual information using a camera, a means for transmitting the captured visual information to the server, a means for analyzing the visual information in the server and identifying unnecessary information based on the filtering settings, a means for correcting the identified unnecessary information, a means for transmitting the corrected visual information to a terminal, a means for displaying the corrected visual information, and a means for focused monitoring of specific targets within a monitoring area. This allows monitors to work without visually recognizing unpleasant information, enabling efficient and comfortable monitoring work. Furthermore, focused monitoring of targets contributes to crime prevention and ensuring the safety of citizens.

[0220] A "user" is a person who uses the system to configure filtering settings for visual information.

[0221] The "filtering settings" are settings that specify the conditions for removing unnecessary information from visual information.

[0222] A "camera" is a device that captures visual information.

[0223] "Visual information" refers to image and video data acquired through a camera.

[0224] A "server" is a high performance computer system that analyzes the captured visual information and identifies and modifies unwanted information based on filtering settings.

[0225] "Analysis" is the process of analyzing acquired visual information and extracting specific data.

[0226] "Unwanted information" is information that should be removed from the visual information as specified by the user in the filtering settings.

[0227] "Correction" refers to the process of removing unwanted information from visual information, and includes masking and mosaic processes.

[0228] "Terminal" means a device that receives and displays modified visual information to a user, including a smartphone or smart glasses.

[0229] "Display" is the process of visually presenting the modified visual information to the user at the terminal.

[0230] A "specific target" is an object or person within a surveillance area that requires focused monitoring.

[0231] "Monitoring" is the process of continuously watching a specific target and issuing alarms or notifications as needed.

[0232] The present invention is a system for filtering information visually perceived by a user, and is designed to be particularly useful for surveillance personnel. A specific embodiment of this system and its operating procedure will be described below.

[0233] First, the user (the monitor) puts on the smart glasses and launches a dedicated filtering application on their device (smartphone or tablet). The user configures filtering settings within the application, including specific keywords and categories (e.g., violent images, offensive information).

[0234] Hardware Configuration

[0235] The system includes the following hardware:

[0236] 1. Smart glasses: Equipped with a built-in camera and display, they capture visual information in real time and display the processed information.

[0237] 2. Device: Install and use a filtering application on your smartphone or tablet.

[0238] 3. Server: A high-performance computer system that analyzes the captured visual information and filters out unnecessary information.

[0239] Software Configuration

[0240] The system uses the following software technologies:

[0241] 1. Python: A programming language used for image processing and frame capture.

[0242] 2. OpenCV: A library used for capturing and displaying images.

[0243] 3. Deep learning libraries (e.g., TensorFlow, PyTorch): Used for object recognition and text analysis on the server side.

[0244] Data processing and calculation flow

[0245] 1. Information collection: The smart glasses' built-in camera captures visual information in real time, which is then saved as images or videos.

[0246] 2. Data transmission: The device encrypts the captured visual information and sends it to the server, ensuring security of the transmitted data.

[0247] 3. Analysis: The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted information based on the filtering settings.

[0248] 4. Correction: The server corrects the identified unwanted information by masking or mosaicking it.

[0249] 5. Receiving and displaying data: The corrected visual information is sent to the terminal, which then displays it on the smart glasses display.

[0250] An example of how this system can be used is when a security officer filters out violent graffiti in a city and focuses on monitoring specific targets (such as lost children or suspicious people) within the surveillance area.

[0251] For example, if a security officer is on patrol and there is violent signage or graffiti in the images captured by the smart glasses camera, the system will analyze it and mask it based on the specified filtering criteria, allowing the officer to continue working without visually perceiving the offensive information.

[0252] Example prompt sentence:

[0253] "Generate a Python program to analyze images captured by the smart glasses camera for violent signs and graffiti and mask out specific areas."

[0254] By inputting this prompt sentence into the generative AI model, a program is generated to remove unnecessary information based on the filtering conditions.

[0255] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0256] Step 1:

[0257] Information gathering

[0258] A user wears smart glasses and launches a filtering application on the device. The smart glasses' built-in camera captures the visual information the user sees in real time. The input is image or video data acquired by the camera. The output is the captured visual information data.

[0259] Step 2:

[0260] Data transmission

[0261] The device transmits the captured visual information to the server, where the transmitted data is encrypted for security. The input is the visual information data acquired from the smart glasses. The output is the encrypted visual information data, which is transmitted to the server.

[0262] Step 3:

[0263] Analysis processing

[0264] The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted content based on the filtering settings. For example, it uses a generative AI model to detect violent signs and graffiti according to a prompt. The input is the encrypted visual information data. The output is metadata about the identified unwanted content.

[0265] Step 4:

[0266] Corrective Action

[0267] The server then corrects the identified unwanted information by masking or mosaicking it. At this stage, unwanted information is removed from the visual data. The input is the metadata of the identified unwanted information and the original visual data. The output is the visual data with the unwanted information corrected.

[0268] Step 5:

[0269] Data reception and display

[0270] The server sends the corrected visual information to the terminal. The transmitted data is also encrypted. The terminal receives the corrected visual information and displays it on the display of the smart glasses. The user can view the corrected visual information in real time. The input is the corrected visual information data. The output is the corrected information displayed on the display of the smart glasses.

[0271] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0272] This invention combines an emotion engine with an information filtering eyewear system to achieve dynamic filtering based on the user's emotions, automatically adjusting filtering settings according to the user's emotional state and providing more advanced and comfortable information.

[0273] System Configuration

[0274] Device configuration

[0275] 1. Eyewear

[0276] It has a built-in camera and display.

[0277] It also includes sensors (e.g., facial recognition camera, microphone) to monitor the user's emotions.

[0278] 2. Terminal

[0279] A device such as a smartphone or tablet with a dedicated filtering and emotion recognition application installed.

[0280] 3. Server

[0281] It is a high-performance computer system that analyzes visual information and emotional data and performs filtering processes.

[0282] 4. Emotion Engine

[0283] A system for analyzing emotions in real time using a user's facial recognition data and voice data.

[0284] Program processing explanation

[0285] System Operation

[0286] 1. The user puts on the eyewear and launches the dedicated app on their device. After launching the app, the user configures the filtering settings and simultaneously launches the emotion engine.

[0287] 2. The device camera captures visual information in real time, and the facial recognition camera and microphone obtain the user's emotional data.

[0288] 3. The device transmits the captured visual and emotional data to a server, where it is encrypted for security.

[0289] Filtering and Sentiment Analysis

[0290] 4. The server analyzes the received visual information and identifies unwanted information based on the filtering settings. It also analyzes the emotional data to determine the user's current emotional state.

[0291] 5. The server dynamically adjusts filtering settings based on the emotion engine analysis results. For example, if the user is feeling stressed, stricter filtering will be implemented.

[0292] 6. The server masks or mosaics the identified unwanted information to generate a modified visual representation.

[0293] Submitting and Viewing Corrections

[0294] 7. The server sends the corrected visual information to the device. The data sent is also encrypted.

[0295] 8. The device displays the corrected visual information on the eyewear to prevent the user from seeing unnecessary information. The filtering strength is also adjusted according to the user's emotional state.

[0296] Specific examples

[0297] Ad filtering example

[0298] If a user has opted out of seeing ads from a particular brand and is feeling stressed:

[0299] 1. As a user walks around town, the device's camera captures store advertisements while an emotion sensor detects stress levels.

[0300] 2. The device sends the image data and emotion data to the server.

[0301] 3. The server identifies advertisements from the image data and applies strict filtering due to high stress levels.

[0302] 4. The server sends the modified data with the advertisement portion pixelated to the terminal.

[0303] 5. The device displays the modified image on the eyewear, allowing the user to walk comfortably without seeing brand advertising.

[0304] Example of filtering unpleasant news

[0305] If the user has indicated that they do not want to see war-related news and are in a stable mood:

[0306] 1. The device's camera captures an image of the newspaper stand, and an emotion sensor monitors the user's mood.

[0307] 2. The device sends the image data and emotion data to the server.

[0308] 3. The server analyzes the image data and identifies war-related articles.

[0309] 4. Because the mood is stable, masking is performed at normal filtering strength.

[0310] 5. The server sends the correction data to the terminal, and the terminal displays the corrected image on the eyewear.

[0311] 6. The user can view the newsstand without seeing certain unpleasant news.

[0312] This allows the user to filter information optimally according to their emotional state, providing a more comfortable information environment.

[0313] The processing flow will be explained below.

[0314] Step 1:

[0315] Users launch the dedicated application on their device, access the filtering settings screen, and set criteria for unwanted information, including specific keywords, categories (e.g., ads, news), and images. Additionally, they enable the emotion engine.

[0316] Step 2:

[0317] The device's camera captures visual information in real time, while the facial recognition camera and microphone simultaneously capture the user's emotional data (e.g., facial expressions, tone of voice), which are then stored on the device.

[0318] Step 3:

[0319] The device encrypts the captured visual and emotional data and sends it to the server, along with the user's filtering settings.

[0320] Step 4:

[0321] The server analyzes the received visual information and uses image analysis techniques (e.g., OCR, object recognition) to identify unwanted information that matches the filtering settings.

[0322] Step 5:

[0323] The server analyzes the received emotional data, and the emotion engine determines the user's current emotional state based on facial recognition and voice data, assessing their stress level and mood stability.

[0324] Step 6:

[0325] The server dynamically adjusts filtering settings based on the analysis results of the emotion engine. For example, if a user's stress level is high, the filtering strength will be strengthened to remove a wider range of unnecessary information.

[0326] Step 7:

[0327] The server then modifies the identified unwanted information, masking or mosaicing the unwanted information to generate a modified visual representation. The modifications are tailored based on the emotion data.

[0328] Step 8:

[0329] The server re-encrypts the corrected visual information and sends it to the device, which receives the corrected visual information and displays it on the eyewear.

[0330] Step 9:

[0331] The device then displays the corrected visual information on the eyewear display in real time, allowing the user to enjoy an information environment that has been properly adjusted or cleared of unnecessary information.

[0332] Specific examples

[0333] Example 1: Filtering Ads

[0334] Step 1:

[0335] A user visits a shopping mall and sets up their device to block ads from certain brands.

[0336] Step 2:

[0337] The device's camera captures visual information, and an emotion sensor collects the user's emotion data.

[0338] Step 3:

[0339] The terminal transmits this data to the server.

[0340] Step 4:

[0341] The server analyzes the visual information and identifies brand advertisements.

[0342] Step 5:

[0343] The server analyzes the emotional data and determines that the user's stress level is high.

[0344] Step 6:

[0345] The server applies strict filtering and removes advertisements completely.

[0346] Step 7:

[0347] The server sends the modified visual information to the terminal.

[0348] Step 8:

[0349] The device displays the modified image on the eyewear, allowing the user to enjoy shopping without seeing brand advertisements.

[0350] Example 2: Filtering unpleasant news

[0351] Step 1:

[0352] Users can set their preferences to block war-related news.

[0353] Step 2:

[0354] The device's camera captures images of the newspaper stand and collects emotion data.

[0355] Step 3:

[0356] The terminal transmits this data to the server.

[0357] Step 4:

[0358] The server analyzes the image data and identifies war-related articles.

[0359] Step 5:

[0360] The server analyzes the emotional data and determines that the user's mood is stable.

[0361] Step 6:

[0362] The server performs masking processing using normal filtering.

[0363] Step 7:

[0364] The server sends the modified visual information to the terminal.

[0365] Step 8:

[0366] The terminal displays the corrected image on the eyewear, allowing the user to read the newspaper without seeing the unpleasant news.

[0367] In this way, the user can enjoy a more comfortable information environment through dynamic filtering settings according to the user's emotional state.

[0368] Example 2

[0369] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0370] In today's information society, users are exposed to a huge amount of information, including information that is unnecessary or unpleasant to them. Furthermore, there is a growing need for information filtering based on the user's emotional state. However, conventional systems have difficulty in dynamically filtering information that takes the user's emotional state into account, making it difficult to provide optimal information to each individual user.

[0371] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing visual information and emotional data, identifying unnecessary information based on filtering settings and the emotional state, and dynamically adjusting the filtering settings, means for correcting the identified unnecessary information, and means for transmitting the corrected visual information to the terminal. This allows the user to eliminate unpleasant information in real time and enables optimal information filtering according to the emotional state.

[0372] A "user" is an individual or entity that uses a system.

[0373] "Filtering settings" are setting items for the user to specify information that the user wants to exclude or restrict from being displayed.

[0374] A "camera" is a device for capturing visual information and affective data.

[0375] "Visual information" refers to image and video data captured by a camera.

[0376] "Emotion data" refers to data relating to the emotional state of the user that is obtained by analyzing the user's facial expressions and voice.

[0377] The "server" is a high-performance computer system that analyzes visual information and emotional data and performs filtering processing.

[0378] "Masking" is a process for hiding unnecessary information in visual information.

[0379] "Mosaic processing" is an image processing technique for blurring unnecessary information in visual information.

[0380] A "terminal" is a device such as a smartphone or tablet on which the filtering and emotion recognition application is installed.

[0381] The "Emotion Engine" is a system that analyzes emotions in real time using a user's facial recognition data and voice data.

[0382] The present invention realizes dynamic filtering based on the user's emotions by combining an emotion engine with an information filtering eyewear system. Hereinafter, an embodiment of the present invention will be described in detail.

[0383] System Configuration

[0384] 1. Eyewear

[0385] It has a built-in camera and display, and also contains sensors (e.g., facial recognition camera, microphone) to monitor the user's emotions.

[0386] 2. Terminal

[0387] These devices, such as smartphones and tablets, are equipped with specialized filtering and emotion recognition applications. These devices capture visual and emotional data and transmit it to a server.

[0388] 3. Server

[0389] It is a high-performance computer system that analyzes visual information and emotional data and performs filtering processing. For visual information processing, machine learning models such as OpenCV and TensorFlow are used.

[0390] 4. Emotion Engine

[0391] This is a system that analyzes emotions in real time using facial recognition data and voice data. The emotion engine analyzes the emotion data and determines the user's current emotional state.

[0392] Program processing details

[0393] Acquiring and Sending Data

[0394] The user wears the eyewear and launches a dedicated app on their device. The device's camera captures visual information in real time, while the facial recognition camera and microphone capture the user's emotional data. The captured visual information and emotional data are encrypted for security and sent to a server.

[0395] Data analysis and filtering

[0396] The server analyzes the received visual information and identifies unwanted information based on the filtering settings. At the same time, it uses an emotion engine to analyze the user's emotion data and determine the user's current emotional state, allowing the server to dynamically adjust the filtering settings based on the user's emotional state.

[0397] Correcting and Viewing Information

[0398] The identified unwanted information is masked or pixelated on the server. The corrected visual information is then encrypted and sent to the device. The device then displays the corrected visual information on the eyewear, preventing the user from seeing the unwanted information. The filtering strength is also automatically adjusted according to the user's emotional state.

[0399] Specific examples

[0400] Ad filtering example

[0401] If a user has opted out of seeing ads from a particular brand and is feeling stressed:

[0402] 1. As a user walks around town, the device's camera captures store advertisements and the emotion sensor detects stress levels.

[0403] 2. The device sends the image data and emotion data to the server.

[0404] 3. The server identifies advertisements from the image data and applies strict filtering due to high stress levels.

[0405] 4. The server sends the modified data with the advertisement portion pixelated to the terminal.

[0406] 5. The device displays the modified image on the eyewear, allowing the user to walk comfortably without seeing brand advertising.

[0407] Example of filtering unpleasant news

[0408] If the user has indicated that they do not want to see war-related news and are in a stable mood:

[0409] 1. The device's camera captures an image of the newspaper stand, and an emotion sensor monitors the user's mood.

[0410] 2. The device sends the image data and emotion data to the server.

[0411] 3. The server analyzes the image data and identifies war-related articles.

[0412] 4. Because the mood is stable, masking is performed at normal filtering strength.

[0413] 5. The server sends the correction data to the terminal, and the terminal displays the corrected image on the eyewear.

[0414] 6. The user can view the newsstand without seeing certain unpleasant news.

[0415] This allows the user to filter information optimally according to their emotional state, providing a more comfortable information environment.

[0416] Prompt Sentence Examples

[0417] "If a user is stressed and has set their preferences to not see certain brand ads, what kind of filtering is applied?"

[0418] "What would be the filtering strength if the user set their device to not want to see war-related news and their mood was stable?"

[0419] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0420] Step 1:

[0421] The user puts on the eyewear and launches the dedicated app on their device. The user configures the filtering settings and simultaneously launches the emotion engine. Specifically, the user selects specific keywords and categories on the app's settings screen and sets the filtering strength.

[0422] Input: User filtering settings, app launch

[0423] Output: Filtering setting data, emotion engine activation signal

[0424] Step 2:

[0425] The device uses a camera to capture visual information in real time, and the eyewear's built-in facial recognition camera and microphone capture the user's emotional data, which is then temporarily stored on the device.

[0426] Input: Visual information from camera, emotion data from face recognition camera and microphone

[0427] Output: Visual information data, emotion data

[0428] Specifically, the device's camera captures images of the street or advertisements, and the facial recognition camera analyzes the user's facial expressions to generate emotional data.

[0429] Step 3:

[0430] The device encrypts the captured visual and emotional data and sends it to a server, ensuring data security.

[0431] Input: Visual information data, emotion data

[0432] Output: Encrypted visual information data, encrypted emotion data

[0433] Specifically, the device encrypts the collected data using an encryption algorithm (e.g., AES) and issues a signal to send it to the server.

[0434] Step 4:

[0435] The server analyzes the received visual information and identifies unwanted information based on the filtering settings, while simultaneously analyzing the emotional data using an emotion engine to determine the user's current emotional state.

[0436] Input: Encrypted visual information data, encrypted emotion data

[0437] Output: Unwanted information identification data, emotional state data

[0438] Specifically, the server uses machine learning models (e.g., OpenCV, TensorFlow) to analyze images and identify unnecessary information, and the emotion engine analyzes the user's emotional state.

[0439] Step 5:

[0440] The server dynamically adjusts the filtering settings based on the emotional state data, thereby applying filtering that best suits the user's emotional state.

[0441] Input: Unwanted information identification data, emotional state data

[0442] Output: Adjusted filtering setting data

[0443] Specifically, the server dynamically changes the parameters of the filtering algorithm according to the emotional state, adjusting the strictness of the filtering, etc.

[0444] Step 6:

[0445] The identified unwanted information is masked or pixelated on the server to generate modified visual information.

[0446] Input: Adjusted filtering setting data, unnecessary information identification data

[0447] Output: Corrected visual information data

[0448] Specifically, the server applies an image processing algorithm based on the filtering settings to mask or mosaic unwanted information.

[0449] Step 7:

[0450] The server re-encrypts the modified visual information and sends it to the device, where this data is also encrypted for security reasons.

[0451] Input: Corrected visual information data

[0452] Output: Encrypted modified visual information data

[0453] Specifically, the server begins the process of encrypting the modified image data and sending it to the terminal.

[0454] Step 8:

[0455] The device decodes the corrected visual information and displays it on the eyewear, adjusting the filtering strength accordingly to prevent the user from viewing unnecessary information.

[0456] Input: Encrypted modified visual information data

[0457] Output: Corrected visual information displayed on eyewear

[0458] Specifically, the terminal performs the function of decrypting the encrypted data and displaying it on the eyewear display.

[0459] Through the above specific processing steps, the information filtering eyewear system realizes dynamic filtering based on the user's emotional state, providing a comfortable information environment.

[0460] (Application example 2)

[0461] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0462] Conventional information filtering systems are unable to dynamically adjust to the user's emotional state and always apply the same filtering settings, resulting in the problem of not providing users with sufficient information to make them comfortable.In addition, they are unable to provide optimal product recommendations or advertisements that match the customer's purchasing motivation or stress level, making it difficult to improve the quality of the shopping experience in physical stores.

[0463] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for monitoring the user's emotional state, means for transmitting the user's emotional data to the server, and means for analyzing the emotional data in the server and dynamically adjusting filtering settings based on the user's emotional state. This enables appropriate information filtering and product recommendations according to the user's emotional state, improving the shopping experience in physical stores.

[0464] "User" refers to a person who uses the system.

[0465] "Filtering settings" refers to the criteria and conditions that a user sets to remove unnecessary information from visual information.

[0466] "Visual information" refers to images and video data captured through devices such as cameras.

[0467] A "server" refers to a high-performance computer system that analyzes and processes data.

[0468] "Unnecessary information" refers to information that is determined not to need to be displayed or provided based on the user's filtering settings.

[0469] "Correction" refers to processing unnecessary information so that it is not visible to the user, using masking or mosaic processing.

[0470] "Terminal" refers to a mobile device such as a smartphone or tablet.

[0471] "Emotional state" refers to a user's psychological emotional state (e.g., stress, joy, anger, etc.).

[0472] "Emotion data" is data that indicates the user's emotional state, and includes facial expressions, voice, and the like.

[0473] "Dynamic adjustment" refers to changing settings and conditions in real time depending on the user's emotional state.

[0474] The present invention relates to a system for realizing dynamic information filtering based on user emotions. To understand and implement this system, it is necessary to incorporate the following elements and processes.

[0475] System Configuration

[0476] Hardware

[0477] Eyewear: The device is equipped with a built-in camera, display, microphone, and facial recognition camera.

[0478] Device: A handheld device such as a smartphone or tablet.

[0479] Server: A high-performance computer system for data analysis and processing.

[0480] software

[0481] Emotion Recognition and Filtering Applications

[0482] Emotion Engine

[0483] Deep learning libraries (e.g. TensorFlow, PyTorch)

[0484] Program processing flow

[0485] 1. The user puts on the eyewear and launches the dedicated app on their device. After launching the app, the user configures the filtering settings and simultaneously launches the emotion engine.

[0486] 2. The device camera captures visual information in real time, and the facial recognition camera and microphone capture the user's emotional data, which is encrypted for security.

[0487] 3. The device transmits the captured visual information and emotional data to the server, which receives the data and uses an emotion engine to analyze the user's current emotional state.

[0488] 4. The server dynamically adjusts filtering settings based on the analysis of the emotional data. For example, if the user is feeling stressed, stricter filtering will be implemented.

[0489] 5. The server analyzes the received visual information and identifies unwanted information based on the filtering settings. The identified unwanted information is masked or pixelated to generate the corrected visual information.

[0490] 6. The server sends the corrected visual information to the device. The data sent is also encrypted.

[0491] 7. The device displays the corrected visual information on the eyewear to prevent the user from seeing unnecessary information. The filtering strength is also adjusted according to the user's emotional state.

[0492] Specific examples

[0493] 1. When the user is walking around town

[0494] If a user has indicated that they do not want to see ads for a particular brand and are feeling stressed, use the following prompt:

[0495] Users are frustrated. Please tighten up your filtering and hide ads from certain brands.

[0496] 2. When the user is shopping in-store

[0497] If the user is feeling good and is looking for relaxation products, use the following prompt:

[0498] The user is relaxed. Please recommend some relaxation-related products.

[0499] These features enable users to receive optimal information filtering and product recommendations according to their emotional state, providing a more comfortable shopping experience.

[0500] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0501] Step 1:

[0502] The user puts on the eyewear and launches the dedicated app on the device. After launching the application, the user configures the filtering settings and simultaneously launches the emotion engine. The input is the user's filtering settings and start command, and the output is the start of the emotion engine and initial setting data. In this step, setting information is collected and the system is initialized.

[0503] Step 2:

[0504] The device's camera captures visual information in real time, while the facial recognition camera and microphone acquire the user's emotional data. The input is the live feed from the camera and microphone, and the output is the captured visual information and audio data. In this step, the camera and microphone are used to continuously collect the user's visual information and emotional state.

[0505] Step 3:

[0506] The device transmits the captured visual information and emotional data to the server. The input is the visual information and emotional data obtained in step 2, and the output is the data to be transmitted to the server. In this step, the collected data is encrypted and securely transmitted to the server.

[0507] Step 4:

[0508] The server analyzes the received visual information and emotional data. The input is the encrypted visual information and emotional data, and the output is the analysis result. During the analysis, the emotion engine uses a deep learning library to determine the user's emotional state in real time, while the content of the visual information is analyzed.

[0509] Step 5:

[0510] The server dynamically adjusts the filtering settings based on the analysis results of the emotional data. The inputs are the analysis results and the initial filtering settings, and the output is the adjusted filtering settings. In this step, the server changes the filtering strictness according to the user's emotional state.

[0511] Step 6:

[0512] The server analyzes the received visual information and identifies unwanted information based on the filtering settings. The input is the adjusted filtering settings and the visual information, and the output is the identified unwanted information. In this step, the filtering algorithm performs the operation of identifying unwanted information.

[0513] Step 7:

[0514] The server corrects the identified unwanted information and generates a corrected visual representation. The input is the list of unwanted information and the original visual representation, and the output is the corrected visual representation. The correction is performed using mossing or mosaic processes.

[0515] Step 8:

[0516] The server sends the corrected visual information to the terminal. The input is the corrected visual information, and the output is the data to be sent to the terminal. In this step, the corrected data is encrypted again and sent to the terminal.

[0517] Step 9:

[0518] The terminal displays the corrected visual information on the eyewear to prevent the user from viewing unnecessary information. The input is the corrected visual information, and the output is the visual information displayed on the eyewear. In this step, the user is finally provided with visual information from which unnecessary information has been removed.

[0519] At each step, data processing and calculations are performed based on the collected data, and the information necessary for the next step is generated, allowing the entire system to operate seamlessly.

[0520] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0521] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0522] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0523] [Second embodiment]

[0524] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0525] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0526] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0527] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0528] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0529] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0530] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0531] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0532] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0533] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0534] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0535] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0536] The present invention relates to an information filtering eyewear system that is a system for filtering information visually perceived by an individual, eliminating unnecessary or unpleasant information and providing necessary and comfortable information to the user.

[0537] Program processing explanation

[0538] System Configuration

[0539] 1. Equipment configuration

[0540] The eyewear worn by the user includes a built-in camera and display.

[0541] The terminals are devices such as smartphones and tablets, and have a dedicated filtering application installed.

[0542] The server is a high performance computer system for performing the analysis and filtering processes.

[0543] 2. System Operation

[0544] The user puts on the eyewear and launches the dedicated app on their device.

[0545] Users configure filtering settings within the app, including specific keywords, categories (e.g., ads, news), and images.

[0546] Information collection and transmission

[0547] 3. Information gathering

[0548] The device's camera captures visual information in real time, which is then saved as images or videos.

[0549] 4. Data transmission

[0550] The device sends the captured visual information to a server, where the data is encrypted to ensure security.

[0551] Filtering Process

[0552] 5. Analysis and Processing

[0553] The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted information based on the filtering settings.

[0554] 6. Corrective Actions

[0555] The server then modifies the identified unwanted information by masking or mosaicking it, etc. At this stage, the unwanted information is removed from the user's view.

[0556] Receiving and displaying data

[0557] 7. Sending and Receiving Data

[0558] The server then sends the corrected visual information to the device, and the data sent is also encrypted.

[0559] 8. Display of correction information

[0560] The device displays the corrected visual information on the eyewear, allowing the user to visually recognize the filtered information.

[0561] Specific examples

[0562] Ad filtering

[0563] If a user indicates that they do not want to see ads for a particular brand in the shopping mall:

[0564] 1. As the user walks around town, the device's camera captures store advertisements.

[0565] 2. The device sends the image data to the server.

[0566] 3. The server analyzes the received image data and identifies advertisements that match the filtering settings.

[0567] 4. The server blurs the advertisement portion and sends the corrected data to the device.

[0568] 5. The device displays the modified image on the eyewear, preventing the user from seeing the specific brand advertisements.

[0569] Filtering unpleasant news

[0570] If the user does not want to see news about wars or disasters:

[0571] 1. The device's camera captures an image of a newspaper stand.

[0572] 2. The device sends the image data to the server.

[0573] 3. The server performs text analysis to identify articles about war and disasters.

[0574] 4. The server masks that portion and sends the corrected data to the terminal.

[0575] 5. The device displays the corrected image on the eyewear, preventing the user from seeing the unpleasant news.

[0576] This allows users to focus on necessary information without being exposed to unnecessary or unpleasant information. This system functions as an effective means of maintaining a comfortable personal information environment.

[0577] The processing flow will be explained below.

[0578] Step 1:

[0579] Users launch the dedicated application on their device. After launching the application, users access the filtering settings screen and set criteria for unwanted information, including specific keywords, categories (e.g., ads, news), and images. These settings are then saved.

[0580] Step 2:

[0581] The device activates the camera and captures visual information in real time, which is then temporarily stored in the device's memory.

[0582] Step 3:

[0583] The device sends the captured visual information to a server, encrypted for security purposes, over Wi-Fi or mobile data networks.

[0584] Step 4:

[0585] The server prepares the received visual information for analysis, applying image recognition techniques (e.g., object recognition, OCR text analysis) to the visual information to search for unwanted content that matches the filtering settings.

[0586] Step 5:

[0587] The server identifies unwanted content based on the filtering settings, such as advertising banners or text containing specific keywords, and records the location of any content identified as unwanted.

[0588] Step 6:

[0589] The server then corrects the identified unnecessary information by masking the unnecessary information (e.g., by pixelating the image), so that the user cannot see the unnecessary information.

[0590] Step 7:

[0591] The server then sends the corrected visual information to the terminal, where the corrected data is encrypted again to ensure security.

[0592] Step 8:

[0593] The device receives the corrected visual information and displays it on the eyewear. By displaying the corrected visual information on the eyewear display in real time, the user can enjoy a comfortable information environment with unnecessary information removed.

[0594] Example 1

[0595] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0596] In today's information-overloaded environment, users are often exposed to unnecessary or unpleasant visual information. This information can disrupt users' concentration and cause psychological stress. In response, there is a need for a system that allows users to filter out unnecessary information and visually perceive only the necessary and pleasant information.

[0597] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0598] In this invention, the server includes means for using object recognition technology and text analysis technology when correcting visual information based on filtering settings, means for displaying the corrected visual information on the eyewear in real time, and means for encrypting communications between the server and the terminal, thereby enabling the user to automatically filter unnecessary information in real time and view only visual information that is comfortable to the user.

[0599] "User" refers to the individual who wears the eyewear and configures the filtering settings.

[0600] "Filtering settings" refers to settings of specific keywords, categories, or images that a user enters to identify unwanted information.

[0601] "Camera" refers to a photographic device used to capture visual information.

[0602] "Visual information" refers to image and video data captured by a camera.

[0603] "Server" refers to a high performance computer system for analyzing and filtering visual information.

[0604] "Terminal" refers to a device such as a smartphone or tablet on which a dedicated filtering application is installed.

[0605] "Object recognition technology" refers to technology that automatically identifies specific objects within visual information.

[0606] "Text analysis technology" refers to technology that analyzes text within visual information and understands its meaning.

[0607] "Masking" refers to the process of painting over part of visual information to hide unnecessary information.

[0608] "Mosaicing" refers to the process of covering part of visual information with a fine block-like pattern in order to hide unnecessary information.

[0609] "Real time" refers to processing and display occurring immediately, without delay.

[0610] "Encryption" refers to the technology of converting data so that its contents cannot be recognized by third parties.

[0611] "Eyewear" refers to glasses-type devices that incorporate a camera and a display.

[0612] The present invention relates to a system for filtering information visually perceived by an individual, and more particularly to an information filtering eyewear system that eliminates unnecessary or unpleasant information and provides necessary and comfortable information to the user.

[0613] System configuration and operation overview

[0614] The system consists of three main components:

[0615] 1. Eyewear worn by the user

[0616] 2. A device with the dedicated application installed

[0617] 3. Server that performs information analysis and filtering

[0618] 1. Eyewear worn by the user

[0619] The eyewear includes a built-in camera for capturing visual information and a display for displaying the corrected visual information. The eyewear communicates with the device using Bluetooth or Wi-Fi.

[0620] 2. A device with the dedicated application installed

[0621] A dedicated filtering application is installed on a user's device (such as a smartphone or tablet), and this application provides an interface for the user to input filtering settings.

[0622] 3. Server that performs information analysis and filtering

[0623] The server is a high-performance computer system that receives and analyzes the visual information sent from the device, using object recognition and text analysis techniques.

[0624] Specific processing details

[0625] Enter filtering settings

[0626] Using a dedicated application, users input their desired filtering settings, such as specific keywords (such as "advertising" or "news"), categories, or images (such as a particular brand logo).

[0627] Visual information capture

[0628] While the user is walking or moving around, the built-in camera in the eyewear captures visual information from the surroundings in real time, which is then transmitted to the device.

[0629] Data transmission and analysis

[0630] The device transmits the captured visual information to a server, which encrypts and secures the data. The server then analyzes the received data and identifies unwanted content based on the filtering settings. For example, the server uses object recognition technology to identify specific brand advertisements and text analysis technology to identify offensive news articles.

[0631] Correcting and Viewing Information

[0632] The server then corrects the identified unwanted information (specifically, by masking or mosaicing) and sends the corrected visual information to the device, which then displays the corrected information in real time on the eyewear display, allowing the user to view the filtered, comfortable visual information.

[0633] Specific use cases

[0634] Ad filtering example

[0635] 1. A user sets a filtering app to "I don't want to see ads for a specific brand X."

[0636] 2. When the user enters the shopping mall, the eyewear captures the advertisement.

[0637] 3. The device sends the captured image data to the server.

[0638] 4. The server parses the ad and identifies the ad for Brand X.

[0639] 5. The server blurs the advertisement portion and sends the correction data to the terminal.

[0640] 6. The device displays the corrected information on the eyewear, and the user no longer sees Brand X's advertisements.

[0641] Prompt Sentence Examples

[0642] "Filter ads for brands you don't want to see in the mall."

[0643] Example of filtering unpleasant news

[0644] 1. The user sets a filtering app to "I don't want to see news about war or disasters."

[0645] 2. The device's camera captures an image of the newsstand.

[0646] 3. The device sends the image data to the server.

[0647] 4. The server analyzes the received data and identifies articles about wars and disasters.

[0648] 5. The server masks that portion and sends the corrected data to the terminal.

[0649] 6. The device displays the corrected information on the eyewear, and the user no longer sees the unpleasant news.

[0650] Prompt Sentence Examples

[0651] "Filter news about wars and disasters."

[0652] This system allows users to focus on the information they need without being exposed to unnecessary or unpleasant information.

[0653] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0654] Step 1:

[0655] The user launches the dedicated filtering app and puts on the eyewear, which then communicates with the device via Bluetooth or Wi-Fi to check the connection status.

[0656] Specific behavior:

[0657] The user taps on the device to launch the app.

[0658] The app screen will open and you can check the connection status with your eyewear.

[0659] The user puts on the eyewear and confirms that "Connection complete" is displayed on the app screen.

[0660] Input: Application launch, eyewear connection

[0661] Output: Eyewear and device are connected properly

[0662] Step 2:

[0663] The user enters their filtering preferences: they select specific keywords, categories, or images in the app's settings screen.

[0664] Specific behavior:

[0665] Select a filtering category from the list displayed on the settings screen.

[0666] Enter a word or phrase in the text field provided for entering specific keywords.

[0667] For image filtering, select an image from your camera roll.

[0668] Input: Filtering settings (keywords, categories, images)

[0669] Output: User filtering settings data

[0670] Step 3:

[0671] While the user is active, the eyewear's camera captures visual information in real time, which is then stored on the device as images or videos.

[0672] Specific behavior:

[0673] The eyewear's camera automatically captures visual information from your surroundings.

[0674] The captured information is transferred to the device in real time.

[0675] Input: Real-world visual information

[0676] Output: Captured visual information (images, videos)

[0677] Step 4:

[0678] The device encrypts the captured visual information and sends it to the server, ensuring security.

[0679] Specific behavior:

[0680] The terminal receives the captured visual information.

[0681] The received data is encrypted and sent to the server.

[0682] Input: Captured visual information

[0683] Output: Encrypted visual information

[0684] Step 5:

[0685] The server decodes the received visual information and begins analyzing it, using object recognition and text analysis techniques to identify unwanted content based on the filtering settings.

[0686] Specific behavior:

[0687] The server decrypts the encrypted data.

[0688] Object recognition algorithms are used to detect specific objects within the visual information.

[0689] Text analysis techniques are used to analyze text within visual information.

[0690] Input: Encrypted visual information

[0691] Output: Analysis results (identification of unnecessary information)

[0692] Step 6:

[0693] The server then modifies the identified unwanted information, for example by masking or mosaicing it, to generate modified visual information.

[0694] Specific behavior:

[0695] The server identifies the garbage.

[0696] Apply masking or mosaic processing to unwanted information.

[0697] Input: Analysis results (identification of unnecessary information)

[0698] Output: Corrected visual information

[0699] Step 7:

[0700] The server re-encrypts the corrected visual information and sends it to the terminal. For security reasons, the transmitted data is encrypted.

[0701] Specific behavior:

[0702] The server encrypts the modified visual information.

[0703] The encrypted data is sent to the terminal.

[0704] Input: Corrected visual information

[0705] Output: Encrypted revision information

[0706] Step 8:

[0707] The terminal receives the modified visual information, decodes it, and displays it on the eyewear, allowing the user to visually perceive the filtered information.

[0708] Specific behavior:

[0709] The terminal receives the encrypted modification information.

[0710] Decrypt the received data.

[0711] The decoded information is displayed on the eyewear display.

[0712] Input: Encrypted correction information

[0713] Output: Corrected visual information displayed on eyewear

[0714] (Application example 1)

[0715] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0716] In surveillance work, it is necessary to provide an environment in which surveillance personnel can perform their work efficiently and comfortably, reducing the stress caused by being exposed to visually unpleasant or unnecessary information.In addition, it is necessary to focus on monitoring specific targets within the surveillance area, which is necessary to prevent crime and ensure the safety of citizens.

[0717] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0718] In this invention, the server includes a means for a user to input filtering settings, a means for capturing visual information using a camera, a means for transmitting the captured visual information to the server, a means for analyzing the visual information in the server and identifying unnecessary information based on the filtering settings, a means for correcting the identified unnecessary information, a means for transmitting the corrected visual information to a terminal, a means for displaying the corrected visual information, and a means for focused monitoring of specific targets within a monitoring area. This allows monitors to work without visually recognizing unpleasant information, enabling efficient and comfortable monitoring work. Furthermore, focused monitoring of targets contributes to crime prevention and ensuring the safety of citizens.

[0719] A "user" is a person who uses the system to configure filtering settings for visual information.

[0720] The "filtering settings" are settings that specify the conditions for removing unnecessary information from visual information.

[0721] A "camera" is a device that captures visual information.

[0722] "Visual information" refers to image and video data acquired through a camera.

[0723] A "server" is a high performance computer system that analyzes the captured visual information and identifies and modifies unwanted information based on filtering settings.

[0724] "Analysis" is the process of analyzing acquired visual information and extracting specific data.

[0725] "Unwanted information" is information that should be removed from the visual information as specified by the user in the filtering settings.

[0726] "Correction" refers to the process of removing unwanted information from visual information, and includes masking and mosaic processes.

[0727] "Terminal" means a device that receives and displays modified visual information to a user, including a smartphone or smart glasses.

[0728] "Display" is the process of visually presenting the modified visual information to the user at the terminal.

[0729] A "specific target" is an object or person within a surveillance area that requires focused monitoring.

[0730] "Monitoring" is the process of continuously watching a specific target and issuing alarms or notifications as needed.

[0731] The present invention is a system for filtering information visually perceived by a user, and is designed to be particularly useful for surveillance personnel. A specific embodiment of this system and its operating procedure will be described below.

[0732] First, the user (the monitor) puts on the smart glasses and launches a dedicated filtering application on their device (smartphone or tablet). The user configures filtering settings within the application, including specific keywords and categories (e.g., violent images, offensive information).

[0733] Hardware Configuration

[0734] The system includes the following hardware:

[0735] 1. Smart glasses: Equipped with a built-in camera and display, they capture visual information in real time and display the processed information.

[0736] 2. Device: Install and use a filtering application on your smartphone or tablet.

[0737] 3. Server: A high-performance computer system that analyzes the captured visual information and filters out unnecessary information.

[0738] Software Configuration

[0739] The system uses the following software technologies:

[0740] 1. Python: A programming language used for image processing and frame capture.

[0741] 2. OpenCV: A library used for capturing and displaying images.

[0742] 3. Deep learning libraries (e.g., TensorFlow, PyTorch): Used for object recognition and text analysis on the server side.

[0743] Data processing and calculation flow

[0744] 1. Information collection: The smart glasses' built-in camera captures visual information in real time, which is then saved as images or videos.

[0745] 2. Data transmission: The device encrypts the captured visual information and sends it to the server, ensuring security of the transmitted data.

[0746] 3. Analysis: The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted information based on the filtering settings.

[0747] 4. Correction: The server corrects the identified unwanted information by masking or mosaicking it.

[0748] 5. Receiving and displaying data: The corrected visual information is sent to the terminal, which then displays it on the smart glasses display.

[0749] An example of how this system can be used is when a security officer filters out violent graffiti in a city and focuses on monitoring specific targets (such as lost children or suspicious people) within the surveillance area.

[0750] For example, if a security officer is on patrol and there is violent signage or graffiti in the images captured by the smart glasses camera, the system will analyze it and mask it based on the specified filtering criteria, allowing the officer to continue working without visually perceiving the offensive information.

[0751] Example prompt sentence:

[0752] "Generate a Python program to analyze images captured by the smart glasses camera for violent signs and graffiti and mask out specific areas."

[0753] By inputting this prompt sentence into the generative AI model, a program is generated to remove unnecessary information based on the filtering conditions.

[0754] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0755] Step 1:

[0756] Information gathering

[0757] A user wears smart glasses and launches a filtering application on the device. The smart glasses' built-in camera captures the visual information the user sees in real time. The input is image or video data acquired by the camera. The output is the captured visual information data.

[0758] Step 2:

[0759] Data transmission

[0760] The device transmits the captured visual information to the server, where the transmitted data is encrypted for security. The input is the visual information data acquired from the smart glasses. The output is the encrypted visual information data, which is transmitted to the server.

[0761] Step 3:

[0762] Analysis processing

[0763] The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted content based on the filtering settings. For example, it uses a generative AI model to detect violent signs and graffiti according to a prompt. The input is the encrypted visual information data. The output is metadata about the identified unwanted content.

[0764] Step 4:

[0765] Corrective Action

[0766] The server then corrects the identified unwanted information by masking or mosaicking it. At this stage, unwanted information is removed from the visual data. The input is the metadata of the identified unwanted information and the original visual data. The output is the visual data with the unwanted information corrected.

[0767] Step 5:

[0768] Data reception and display

[0769] The server sends the corrected visual information to the terminal. The transmitted data is also encrypted. The terminal receives the corrected visual information and displays it on the display of the smart glasses. The user can view the corrected visual information in real time. The input is the corrected visual information data. The output is the corrected information displayed on the display of the smart glasses.

[0770] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0771] This invention combines an emotion engine with an information filtering eyewear system to achieve dynamic filtering based on the user's emotions, automatically adjusting filtering settings according to the user's emotional state and providing more advanced and comfortable information.

[0772] System Configuration

[0773] Device configuration

[0774] 1. Eyewear

[0775] It has a built-in camera and display.

[0776] It also includes sensors (e.g., facial recognition camera, microphone) to monitor the user's emotions.

[0777] 2. Terminal

[0778] A device such as a smartphone or tablet with a dedicated filtering and emotion recognition application installed.

[0779] 3. Server

[0780] It is a high-performance computer system that analyzes visual information and emotional data and performs filtering processes.

[0781] 4. Emotion Engine

[0782] A system for analyzing emotions in real time using a user's facial recognition data and voice data.

[0783] Program processing explanation

[0784] System Operation

[0785] 1. The user puts on the eyewear and launches the dedicated app on their device. After launching the app, the user configures the filtering settings and simultaneously launches the emotion engine.

[0786] 2. The device camera captures visual information in real time, and the facial recognition camera and microphone obtain the user's emotional data.

[0787] 3. The device transmits the captured visual and emotional data to a server, where it is encrypted for security.

[0788] Filtering and Sentiment Analysis

[0789] 4. The server analyzes the received visual information and identifies unwanted information based on the filtering settings. It also analyzes the emotional data to determine the user's current emotional state.

[0790] 5. The server dynamically adjusts filtering settings based on the emotion engine analysis results. For example, if the user is feeling stressed, stricter filtering will be implemented.

[0791] 6. The server masks or mosaics the identified unwanted information to generate a modified visual representation.

[0792] Submitting and Viewing Corrections

[0793] 7. The server sends the corrected visual information to the device. The data sent is also encrypted.

[0794] 8. The device displays the corrected visual information on the eyewear to prevent the user from seeing unnecessary information. The filtering strength is also adjusted according to the user's emotional state.

[0795] Specific examples

[0796] Ad filtering example

[0797] If a user has opted out of seeing ads from a particular brand and is feeling stressed:

[0798] 1. As a user walks around town, the device's camera captures store advertisements while an emotion sensor detects stress levels.

[0799] 2. The device sends the image data and emotion data to the server.

[0800] 3. The server identifies advertisements from the image data and applies strict filtering due to high stress levels.

[0801] 4. The server sends the modified data with the advertisement portion pixelated to the terminal.

[0802] 5. The device displays the modified image on the eyewear, allowing the user to walk comfortably without seeing brand advertising.

[0803] Example of filtering unpleasant news

[0804] If the user has indicated that they do not want to see war-related news and are in a stable mood:

[0805] 1. The device's camera captures an image of the newspaper stand, and an emotion sensor monitors the user's mood.

[0806] 2. The device sends the image data and emotion data to the server.

[0807] 3. The server analyzes the image data and identifies war-related articles.

[0808] 4. Because the mood is stable, masking is performed at normal filtering strength.

[0809] 5. The server sends the correction data to the terminal, and the terminal displays the corrected image on the eyewear.

[0810] 6. The user can view the newsstand without seeing certain unpleasant news.

[0811] This allows the user to filter information optimally according to their emotional state, providing a more comfortable information environment.

[0812] The processing flow will be explained below.

[0813] Step 1:

[0814] Users launch the dedicated application on their device, access the filtering settings screen, and set criteria for unwanted information, including specific keywords, categories (e.g., ads, news), and images. Additionally, they enable the emotion engine.

[0815] Step 2:

[0816] The device's camera captures visual information in real time, while the facial recognition camera and microphone simultaneously capture the user's emotional data (e.g., facial expressions, tone of voice), which are then stored on the device.

[0817] Step 3:

[0818] The device encrypts the captured visual and emotional data and sends it to the server, along with the user's filtering settings.

[0819] Step 4:

[0820] The server analyzes the received visual information and uses image analysis techniques (e.g., OCR, object recognition) to identify unwanted information that matches the filtering settings.

[0821] Step 5:

[0822] The server analyzes the received emotional data, and the emotion engine determines the user's current emotional state based on facial recognition and voice data, assessing their stress level and mood stability.

[0823] Step 6:

[0824] The server dynamically adjusts filtering settings based on the analysis results of the emotion engine. For example, if a user's stress level is high, the filtering strength will be strengthened to remove a wider range of unnecessary information.

[0825] Step 7:

[0826] The server then modifies the identified unwanted information, masking or mosaicing the unwanted information to generate a modified visual representation. The modifications are tailored based on the emotion data.

[0827] Step 8:

[0828] The server re-encrypts the corrected visual information and sends it to the device, which receives the corrected visual information and displays it on the eyewear.

[0829] Step 9:

[0830] The device then displays the corrected visual information on the eyewear display in real time, allowing the user to enjoy an information environment that has been properly adjusted or cleared of unnecessary information.

[0831] Specific examples

[0832] Example 1: Filtering Ads

[0833] Step 1:

[0834] A user visits a shopping mall and sets up their device to block ads from certain brands.

[0835] Step 2:

[0836] The device's camera captures visual information, and an emotion sensor collects the user's emotion data.

[0837] Step 3:

[0838] The terminal transmits this data to the server.

[0839] Step 4:

[0840] The server analyzes the visual information and identifies brand advertisements.

[0841] Step 5:

[0842] The server analyzes the emotional data and determines that the user's stress level is high.

[0843] Step 6:

[0844] The server applies strict filtering and removes advertisements completely.

[0845] Step 7:

[0846] The server sends the modified visual information to the terminal.

[0847] Step 8:

[0848] The device displays the modified image on the eyewear, allowing the user to enjoy shopping without seeing brand advertisements.

[0849] Example 2: Filtering unpleasant news

[0850] Step 1:

[0851] Users can set their preferences to block war-related news.

[0852] Step 2:

[0853] The device's camera captures images of the newspaper stand and collects emotion data.

[0854] Step 3:

[0855] The terminal transmits this data to the server.

[0856] Step 4:

[0857] The server analyzes the image data and identifies war-related articles.

[0858] Step 5:

[0859] The server analyzes the emotional data and determines that the user's mood is stable.

[0860] Step 6:

[0861] The server performs masking processing using normal filtering.

[0862] Step 7:

[0863] The server sends the modified visual information to the terminal.

[0864] Step 8:

[0865] The terminal displays the corrected image on the eyewear, allowing the user to read the newspaper without seeing the unpleasant news.

[0866] In this way, the user can enjoy a more comfortable information environment through dynamic filtering settings according to the user's emotional state.

[0867] Example 2

[0868] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0869] In today's information society, users are exposed to a huge amount of information, including information that is unnecessary or unpleasant to them. Furthermore, there is a growing need for information filtering based on the user's emotional state. However, conventional systems have difficulty in dynamically filtering information that takes the user's emotional state into account, making it difficult to provide optimal information to each individual user.

[0870] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing visual information and emotional data, identifying unnecessary information based on filtering settings and the emotional state, and dynamically adjusting the filtering settings, means for correcting the identified unnecessary information, and means for transmitting the corrected visual information to the terminal. This allows the user to eliminate unpleasant information in real time and enables optimal information filtering according to the emotional state.

[0871] A "user" is an individual or entity that uses a system.

[0872] "Filtering settings" are setting items for the user to specify information that the user wants to exclude or restrict from being displayed.

[0873] A "camera" is a device for capturing visual information and affective data.

[0874] "Visual information" refers to image and video data captured by a camera.

[0875] "Emotion data" refers to data relating to the emotional state of the user that is obtained by analyzing the user's facial expressions and voice.

[0876] The "server" is a high-performance computer system that analyzes visual information and emotional data and performs filtering processing.

[0877] "Masking" is a process for hiding unnecessary information in visual information.

[0878] "Mosaic processing" is an image processing technique for blurring unnecessary information in visual information.

[0879] A "terminal" is a device such as a smartphone or tablet on which the filtering and emotion recognition application is installed.

[0880] The "Emotion Engine" is a system that analyzes emotions in real time using a user's facial recognition data and voice data.

[0881] The present invention realizes dynamic filtering based on the user's emotions by combining an emotion engine with an information filtering eyewear system. Hereinafter, an embodiment of the present invention will be described in detail.

[0882] System Configuration

[0883] 1. Eyewear

[0884] It has a built-in camera and display, and also contains sensors (e.g., facial recognition camera, microphone) to monitor the user's emotions.

[0885] 2. Terminal

[0886] These devices, such as smartphones and tablets, are equipped with specialized filtering and emotion recognition applications. These devices capture visual and emotional data and transmit it to a server.

[0887] 3. Server

[0888] It is a high-performance computer system that analyzes visual information and emotional data and performs filtering processing. For visual information processing, machine learning models such as OpenCV and TensorFlow are used.

[0889] 4. Emotion Engine

[0890] This is a system that analyzes emotions in real time using facial recognition data and voice data. The emotion engine analyzes the emotion data and determines the user's current emotional state.

[0891] Program processing details

[0892] Acquiring and Sending Data

[0893] The user wears the eyewear and launches a dedicated app on their device. The device's camera captures visual information in real time, while the facial recognition camera and microphone capture the user's emotional data. The captured visual information and emotional data are encrypted for security and sent to a server.

[0894] Data analysis and filtering

[0895] The server analyzes the received visual information and identifies unwanted information based on the filtering settings. At the same time, it uses an emotion engine to analyze the user's emotion data and determine the user's current emotional state, allowing the server to dynamically adjust the filtering settings based on the user's emotional state.

[0896] Correcting and Viewing Information

[0897] The identified unwanted information is masked or pixelated on the server. The corrected visual information is then encrypted and sent to the device. The device then displays the corrected visual information on the eyewear, preventing the user from seeing the unwanted information. The filtering strength is also automatically adjusted according to the user's emotional state.

[0898] Specific examples

[0899] Ad filtering example

[0900] If a user has opted out of seeing ads from a particular brand and is feeling stressed:

[0901] 1. As a user walks around town, the device's camera captures store advertisements and the emotion sensor detects stress levels.

[0902] 2. The device sends the image data and emotion data to the server.

[0903] 3. The server identifies advertisements from the image data and applies strict filtering due to high stress levels.

[0904] 4. The server sends the modified data with the advertisement portion pixelated to the terminal.

[0905] 5. The device displays the modified image on the eyewear, allowing the user to walk comfortably without seeing brand advertising.

[0906] Example of filtering unpleasant news

[0907] If the user has indicated that they do not want to see war-related news and are in a stable mood:

[0908] 1. The device's camera captures an image of the newspaper stand, and an emotion sensor monitors the user's mood.

[0909] 2. The device sends the image data and emotion data to the server.

[0910] 3. The server analyzes the image data and identifies war-related articles.

[0911] 4. Because the mood is stable, masking is performed at normal filtering strength.

[0912] 5. The server sends the correction data to the terminal, and the terminal displays the corrected image on the eyewear.

[0913] 6. The user can view the newsstand without seeing certain unpleasant news.

[0914] This allows the user to filter information optimally according to their emotional state, providing a more comfortable information environment.

[0915] Prompt Sentence Examples

[0916] "If a user is stressed and has set their preferences to not see certain brand ads, what kind of filtering is applied?"

[0917] "What would be the filtering strength if the user set their device to not want to see war-related news and their mood was stable?"

[0918] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0919] Step 1:

[0920] The user puts on the eyewear and launches the dedicated app on their device. The user configures the filtering settings and simultaneously launches the emotion engine. Specifically, the user selects specific keywords and categories on the app's settings screen and sets the filtering strength.

[0921] Input: User filtering settings, app launch

[0922] Output: Filtering setting data, emotion engine activation signal

[0923] Step 2:

[0924] The device uses a camera to capture visual information in real time, and the eyewear's built-in facial recognition camera and microphone capture the user's emotional data, which is then temporarily stored on the device.

[0925] Input: Visual information from camera, emotion data from face recognition camera and microphone

[0926] Output: Visual information data, emotion data

[0927] Specifically, the device's camera captures images of the street or advertisements, and the facial recognition camera analyzes the user's facial expressions to generate emotional data.

[0928] Step 3:

[0929] The device encrypts the captured visual and emotional data and sends it to a server, ensuring data security.

[0930] Input: Visual information data, emotion data

[0931] Output: Encrypted visual information data, encrypted emotion data

[0932] Specifically, the device encrypts the collected data using an encryption algorithm (e.g., AES) and issues a signal to send it to the server.

[0933] Step 4:

[0934] The server analyzes the received visual information and identifies unwanted information based on the filtering settings, while simultaneously analyzing the emotional data using an emotion engine to determine the user's current emotional state.

[0935] Input: Encrypted visual information data, encrypted emotion data

[0936] Output: Unwanted information identification data, emotional state data

[0937] Specifically, the server uses machine learning models (e.g., OpenCV, TensorFlow) to analyze images and identify unnecessary information, and the emotion engine analyzes the user's emotional state.

[0938] Step 5:

[0939] The server dynamically adjusts the filtering settings based on the emotional state data, thereby applying filtering that best suits the user's emotional state.

[0940] Input: Unwanted information identification data, emotional state data

[0941] Output: Adjusted filtering setting data

[0942] Specifically, the server dynamically changes the parameters of the filtering algorithm according to the emotional state, adjusting the strictness of the filtering, etc.

[0943] Step 6:

[0944] The identified unwanted information is masked or pixelated on the server to generate modified visual information.

[0945] Input: Adjusted filtering setting data, unnecessary information identification data

[0946] Output: Corrected visual information data

[0947] Specifically, the server applies an image processing algorithm based on the filtering settings to mask or mosaic unwanted information.

[0948] Step 7:

[0949] The server re-encrypts the modified visual information and sends it to the device, where this data is also encrypted for security reasons.

[0950] Input: Corrected visual information data

[0951] Output: Encrypted modified visual information data

[0952] Specifically, the server begins the process of encrypting the modified image data and sending it to the terminal.

[0953] Step 8:

[0954] The device decodes the corrected visual information and displays it on the eyewear, adjusting the filtering strength accordingly to prevent the user from viewing unnecessary information.

[0955] Input: Encrypted modified visual information data

[0956] Output: Corrected visual information displayed on eyewear

[0957] Specifically, the terminal performs the function of decrypting the encrypted data and displaying it on the eyewear display.

[0958] Through the above specific processing steps, the information filtering eyewear system realizes dynamic filtering based on the user's emotional state, providing a comfortable information environment.

[0959] (Application example 2)

[0960] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0961] Conventional information filtering systems are unable to dynamically adjust to the user's emotional state and always apply the same filtering settings, resulting in the problem of not providing users with sufficient information to make them comfortable.In addition, they are unable to provide optimal product recommendations or advertisements that match the customer's purchasing motivation or stress level, making it difficult to improve the quality of the shopping experience in physical stores.

[0962] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for monitoring the user's emotional state, means for transmitting the user's emotional data to the server, and means for analyzing the emotional data in the server and dynamically adjusting filtering settings based on the user's emotional state. This enables appropriate information filtering and product recommendations according to the user's emotional state, improving the shopping experience in physical stores.

[0963] "User" refers to a person who uses the system.

[0964] "Filtering settings" refers to the criteria and conditions that a user sets to remove unnecessary information from visual information.

[0965] "Visual information" refers to images and video data captured through devices such as cameras.

[0966] A "server" refers to a high-performance computer system that analyzes and processes data.

[0967] "Unnecessary information" refers to information that is determined not to need to be displayed or provided based on the user's filtering settings.

[0968] "Correction" refers to processing unnecessary information so that it is not visible to the user, using masking or mosaic processing.

[0969] "Terminal" refers to a mobile device such as a smartphone or tablet.

[0970] "Emotional state" refers to a user's psychological emotional state (e.g., stress, joy, anger, etc.).

[0971] "Emotion data" is data that indicates the user's emotional state, and includes facial expressions, voice, and the like.

[0972] "Dynamic adjustment" refers to changing settings and conditions in real time depending on the user's emotional state.

[0973] The present invention relates to a system for realizing dynamic information filtering based on user emotions. To understand and implement this system, it is necessary to incorporate the following elements and processes.

[0974] System Configuration

[0975] Hardware

[0976] Eyewear: The device is equipped with a built-in camera, display, microphone, and facial recognition camera.

[0977] Device: A handheld device such as a smartphone or tablet.

[0978] Server: A high-performance computer system for data analysis and processing.

[0979] software

[0980] Emotion Recognition and Filtering Applications

[0981] Emotion Engine

[0982] Deep learning libraries (e.g. TensorFlow, PyTorch)

[0983] Program processing flow

[0984] 1. The user puts on the eyewear and launches the dedicated app on their device. After launching the app, the user configures the filtering settings and simultaneously launches the emotion engine.

[0985] 2. The device camera captures visual information in real time, and the facial recognition camera and microphone capture the user's emotional data, which is encrypted for security.

[0986] 3. The device transmits the captured visual information and emotional data to the server, which receives the data and uses an emotion engine to analyze the user's current emotional state.

[0987] 4. The server dynamically adjusts filtering settings based on the analysis of the emotional data. For example, if the user is feeling stressed, stricter filtering will be implemented.

[0988] 5. The server analyzes the received visual information and identifies unwanted information based on the filtering settings. The identified unwanted information is masked or pixelated to generate the corrected visual information.

[0989] 6. The server sends the corrected visual information to the device. The data sent is also encrypted.

[0990] 7. The device displays the corrected visual information on the eyewear to prevent the user from seeing unnecessary information. The filtering strength is also adjusted according to the user's emotional state.

[0991] Specific examples

[0992] 1. When the user is walking around town

[0993] If a user has indicated that they do not want to see ads for a particular brand and are feeling stressed, use the following prompt:

[0994] Users are frustrated. Please tighten up your filtering and hide ads from certain brands.

[0995] 2. When the user is shopping in-store

[0996] If the user is feeling good and is looking for relaxation products, use the following prompt:

[0997] The user is relaxed. Please recommend some relaxation-related products.

[0998] These features enable users to receive optimal information filtering and product recommendations according to their emotional state, providing a more comfortable shopping experience.

[0999] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1000] Step 1:

[1001] The user puts on the eyewear and launches the dedicated app on the device. After launching the application, the user configures the filtering settings and simultaneously launches the emotion engine. The input is the user's filtering settings and start command, and the output is the start of the emotion engine and initial setting data. In this step, setting information is collected and the system is initialized.

[1002] Step 2:

[1003] The device's camera captures visual information in real time, while the facial recognition camera and microphone acquire the user's emotional data. The input is the live feed from the camera and microphone, and the output is the captured visual information and audio data. In this step, the camera and microphone are used to continuously collect the user's visual information and emotional state.

[1004] Step 3:

[1005] The device transmits the captured visual information and emotional data to the server. The input is the visual information and emotional data obtained in step 2, and the output is the data to be transmitted to the server. In this step, the collected data is encrypted and securely transmitted to the server.

[1006] Step 4:

[1007] The server analyzes the received visual information and emotional data. The input is the encrypted visual information and emotional data, and the output is the analysis result. During the analysis, the emotion engine uses a deep learning library to determine the user's emotional state in real time, while the content of the visual information is analyzed.

[1008] Step 5:

[1009] The server dynamically adjusts the filtering settings based on the analysis results of the emotional data. The inputs are the analysis results and the initial filtering settings, and the output is the adjusted filtering settings. In this step, the server changes the filtering strictness according to the user's emotional state.

[1010] Step 6:

[1011] The server analyzes the received visual information and identifies unwanted information based on the filtering settings. The input is the adjusted filtering settings and the visual information, and the output is the identified unwanted information. In this step, the filtering algorithm performs the operation of identifying unwanted information.

[1012] Step 7:

[1013] The server corrects the identified unwanted information and generates a corrected visual representation. The input is the list of unwanted information and the original visual representation, and the output is the corrected visual representation. The correction is performed using mossing or mosaic processes.

[1014] Step 8:

[1015] The server sends the corrected visual information to the terminal. The input is the corrected visual information, and the output is the data to be sent to the terminal. In this step, the corrected data is encrypted again and sent to the terminal.

[1016] Step 9:

[1017] The terminal displays the corrected visual information on the eyewear to prevent the user from viewing unnecessary information. The input is the corrected visual information, and the output is the visual information displayed on the eyewear. In this step, the user is finally provided with visual information from which unnecessary information has been removed.

[1018] At each step, data processing and calculations are performed based on the collected data, and the information necessary for the next step is generated, allowing the entire system to operate seamlessly.

[1019] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1020] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1021] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1022] [Third embodiment]

[1023] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1024] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1026] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1027] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1028] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1030] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1031] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1033] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1034] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1035] The present invention relates to an information filtering eyewear system that is a system for filtering information visually perceived by an individual, eliminating unnecessary or unpleasant information and providing necessary and comfortable information to the user.

[1036] Program processing explanation

[1037] System Configuration

[1038] 1. Equipment configuration

[1039] The eyewear worn by the user includes a built-in camera and display.

[1040] The terminals are devices such as smartphones and tablets, and have a dedicated filtering application installed.

[1041] The server is a high performance computer system for performing the analysis and filtering processes.

[1042] 2. System Operation

[1043] The user puts on the eyewear and launches the dedicated app on their device.

[1044] Users configure filtering settings within the app, including specific keywords, categories (e.g., ads, news), and images.

[1045] Information collection and transmission

[1046] 3. Information gathering

[1047] The device's camera captures visual information in real time, which is then saved as images or videos.

[1048] 4. Data transmission

[1049] The device sends the captured visual information to a server, where the data is encrypted to ensure security.

[1050] Filtering Process

[1051] 5. Analysis and Processing

[1052] The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted information based on the filtering settings.

[1053] 6. Corrective Actions

[1054] The server then modifies the identified unwanted information by masking or mosaicking it, etc. At this stage, the unwanted information is removed from the user's view.

[1055] Receiving and displaying data

[1056] 7. Sending and Receiving Data

[1057] The server then sends the corrected visual information to the device, and the data sent is also encrypted.

[1058] 8. Display of correction information

[1059] The device displays the corrected visual information on the eyewear, allowing the user to visually recognize the filtered information.

[1060] Specific examples

[1061] Ad filtering

[1062] If a user indicates that they do not want to see ads for a particular brand in the shopping mall:

[1063] 1. As the user walks around town, the device's camera captures store advertisements.

[1064] 2. The device sends the image data to the server.

[1065] 3. The server analyzes the received image data and identifies advertisements that match the filtering settings.

[1066] 4. The server blurs the advertisement portion and sends the corrected data to the device.

[1067] 5. The device displays the modified image on the eyewear, preventing the user from seeing the specific brand advertisements.

[1068] Filtering unpleasant news

[1069] If the user does not want to see news about wars or disasters:

[1070] 1. The device's camera captures an image of a newspaper stand.

[1071] 2. The device sends the image data to the server.

[1072] 3. The server performs text analysis to identify articles about war and disasters.

[1073] 4. The server masks that portion and sends the corrected data to the terminal.

[1074] 5. The device displays the corrected image on the eyewear, preventing the user from seeing the unpleasant news.

[1075] This allows users to focus on necessary information without being exposed to unnecessary or unpleasant information. This system functions as an effective means of maintaining a comfortable personal information environment.

[1076] The processing flow will be explained below.

[1077] Step 1:

[1078] Users launch a dedicated application on their device. After launching the application, users access a filtering settings screen and set criteria for unwanted content, including specific keywords, categories (e.g., ads, news), and images. These settings are then saved.

[1079] Step 2:

[1080] The device activates the camera and captures visual information in real time, which is then temporarily stored in the device's memory.

[1081] Step 3:

[1082] The device sends the captured visual information to a server, encrypted for security purposes, over Wi-Fi or mobile data networks.

[1083] Step 4:

[1084] The server prepares the received visual information for analysis, applying image recognition techniques (e.g., object recognition, OCR text analysis) to the visual information to search for unwanted content that matches the filtering settings.

[1085] Step 5:

[1086] The server identifies unwanted content based on the filtering settings, such as advertising banners or text containing specific keywords, and records the location of any content identified as unwanted.

[1087] Step 6:

[1088] The server then corrects the identified unnecessary information by masking the unnecessary information (e.g., by pixelating the image), so that the user cannot see the unnecessary information.

[1089] Step 7:

[1090] The server then sends the corrected visual information to the terminal, where the corrected data is encrypted again to ensure security.

[1091] Step 8:

[1092] The device receives the corrected visual information and displays it on the eyewear. By displaying the corrected visual information on the eyewear display in real time, the user can enjoy a comfortable information environment with unnecessary information removed.

[1093] Example 1

[1094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1095] In today's information-overloaded environment, users are often exposed to unnecessary or unpleasant visual information. This information can disrupt users' concentration and cause psychological stress. In response, there is a need for a system that allows users to filter out unnecessary information and visually perceive only the necessary and pleasant information.

[1096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1097] In this invention, the server includes means for using object recognition technology and text analysis technology when correcting visual information based on filtering settings, means for displaying the corrected visual information on the eyewear in real time, and means for encrypting communications between the server and the terminal, thereby enabling the user to automatically filter unnecessary information in real time and view only visual information that is comfortable to the user.

[1098] "User" refers to the individual who wears the eyewear and configures the filtering settings.

[1099] "Filtering settings" refers to settings of specific keywords, categories, or images that a user enters to identify unwanted information.

[1100] "Camera" refers to a photographic device used to capture visual information.

[1101] "Visual information" refers to image and video data captured by a camera.

[1102] "Server" refers to a high performance computer system for analyzing and filtering visual information.

[1103] "Terminal" refers to a device such as a smartphone or tablet on which a dedicated filtering application is installed.

[1104] "Object recognition technology" refers to technology that automatically identifies specific objects within visual information.

[1105] "Text analysis technology" refers to technology that analyzes text within visual information and understands its meaning.

[1106] "Masking" refers to the process of painting over part of visual information to hide unnecessary information.

[1107] "Mosaicing" refers to the process of covering part of visual information with a fine block-like pattern in order to hide unnecessary information.

[1108] "Real time" refers to processing and display occurring immediately, without delay.

[1109] "Encryption" refers to the technology of converting data so that its contents cannot be recognized by third parties.

[1110] "Eyewear" refers to glasses-type devices that incorporate a camera and a display.

[1111] The present invention relates to a system for filtering information visually perceived by an individual, and more particularly to an information filtering eyewear system that eliminates unnecessary or unpleasant information and provides necessary and comfortable information to the user.

[1112] System configuration and operation overview

[1113] The system consists of three main components:

[1114] 1. Eyewear worn by the user

[1115] 2. A device with the dedicated application installed

[1116] 3. Server that performs information analysis and filtering

[1117] 1. Eyewear worn by the user

[1118] The eyewear includes a built-in camera for capturing visual information and a display for displaying the corrected visual information. The eyewear communicates with the device using Bluetooth or Wi-Fi.

[1119] 2. A device with the dedicated application installed

[1120] A dedicated filtering application is installed on a user's device (such as a smartphone or tablet), and this application provides an interface for the user to input filtering settings.

[1121] 3. Server that performs information analysis and filtering

[1122] The server is a high-performance computer system that receives and analyzes the visual information sent from the device, using object recognition and text analysis techniques.

[1123] Specific processing details

[1124] Enter filtering settings

[1125] Using a dedicated application, users input their desired filtering settings, such as specific keywords (such as "advertising" or "news"), categories, or images (such as a particular brand logo).

[1126] Visual information capture

[1127] While the user is walking or moving around, the built-in camera in the eyewear captures visual information from the surroundings in real time, which is then transmitted to the device.

[1128] Data transmission and analysis

[1129] The device transmits the captured visual information to a server, which encrypts and secures the data. The server then analyzes the received data and identifies unwanted content based on the filtering settings. For example, the server uses object recognition technology to identify specific brand advertisements and text analysis technology to identify offensive news articles.

[1130] Correcting and Viewing Information

[1131] The server then corrects the identified unwanted information (specifically, by masking or mosaicing) and sends the corrected visual information to the device, which then displays the corrected information in real time on the eyewear display, allowing the user to view the filtered, comfortable visual information.

[1132] Specific use cases

[1133] Ad filtering example

[1134] 1. A user sets a filtering app to "I don't want to see ads for a specific brand X."

[1135] 2. When the user enters the shopping mall, the eyewear captures the advertisement.

[1136] 3. The device sends the captured image data to the server.

[1137] 4. The server parses the ad and identifies the ad for Brand X.

[1138] 5. The server blurs the advertisement portion and sends the correction data to the terminal.

[1139] 6. The device displays the corrected information on the eyewear, and the user no longer sees Brand X's advertisements.

[1140] Prompt Sentence Examples

[1141] "Filter ads for brands you don't want to see in the mall."

[1142] Example of filtering unpleasant news

[1143] 1. The user sets a filtering app to "I don't want to see news about war or disasters."

[1144] 2. The device's camera captures an image of the newsstand.

[1145] 3. The device sends the image data to the server.

[1146] 4. The server analyzes the received data and identifies articles about wars and disasters.

[1147] 5. The server masks that portion and sends the corrected data to the terminal.

[1148] 6. The device displays the corrected information on the eyewear, and the user no longer sees the unpleasant news.

[1149] Prompt Sentence Examples

[1150] "Filter news about wars and disasters."

[1151] This system allows users to focus on the information they need without being exposed to unnecessary or unpleasant information.

[1152] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1153] Step 1:

[1154] The user launches the dedicated filtering app and puts on the eyewear, which then communicates with the device via Bluetooth or Wi-Fi to check the connection status.

[1155] Specific behavior:

[1156] The user taps on the device to launch the app.

[1157] The app screen will open and you can check the connection status with your eyewear.

[1158] The user puts on the eyewear and confirms that "Connection complete" is displayed on the app screen.

[1159] Input: Application launch, eyewear connection

[1160] Output: Eyewear and device are connected properly

[1161] Step 2:

[1162] The user enters their filtering preferences: they select specific keywords, categories, or images in the app's settings screen.

[1163] Specific behavior:

[1164] Select a filtering category from the list displayed on the settings screen.

[1165] Enter a word or phrase in the text field provided for entering specific keywords.

[1166] For image filtering, select an image from your camera roll.

[1167] Input: Filtering settings (keywords, categories, images)

[1168] Output: User filtering settings data

[1169] Step 3:

[1170] While the user is active, the eyewear's camera captures visual information in real time, which is then stored on the device as images or videos.

[1171] Specific behavior:

[1172] The eyewear's camera automatically captures visual information from your surroundings.

[1173] The captured information is transferred to the device in real time.

[1174] Input: Real-world visual information

[1175] Output: Captured visual information (images, videos)

[1176] Step 4:

[1177] The device encrypts the captured visual information and sends it to the server, ensuring security.

[1178] Specific behavior:

[1179] The terminal receives the captured visual information.

[1180] The received data is encrypted and sent to the server.

[1181] Input: Captured visual information

[1182] Output: Encrypted visual information

[1183] Step 5:

[1184] The server decodes the received visual information and begins analyzing it, using object recognition and text analysis techniques to identify unwanted content based on the filtering settings.

[1185] Specific behavior:

[1186] The server decrypts the encrypted data.

[1187] Object recognition algorithms are used to detect specific objects within the visual information.

[1188] Text analysis techniques are used to analyze text within visual information.

[1189] Input: Encrypted visual information

[1190] Output: Analysis results (identification of unnecessary information)

[1191] Step 6:

[1192] The server then modifies the identified unwanted information, for example by masking or mosaicing it, to generate modified visual information.

[1193] Specific behavior:

[1194] The server identifies the garbage.

[1195] Apply masking or mosaic processing to unwanted information.

[1196] Input: Analysis results (identification of unnecessary information)

[1197] Output: Corrected visual information

[1198] Step 7:

[1199] The server re-encrypts the corrected visual information and sends it to the terminal. For security reasons, the transmitted data is encrypted.

[1200] Specific behavior:

[1201] The server encrypts the modified visual information.

[1202] The encrypted data is sent to the terminal.

[1203] Input: Corrected visual information

[1204] Output: Encrypted revision information

[1205] Step 8:

[1206] The terminal receives the modified visual information, decodes it, and displays it on the eyewear, allowing the user to visually perceive the filtered information.

[1207] Specific behavior:

[1208] The terminal receives the encrypted modification information.

[1209] Decrypt the received data.

[1210] The decoded information is displayed on the eyewear display.

[1211] Input: Encrypted correction information

[1212] Output: Corrected visual information displayed on eyewear

[1213] (Application example 1)

[1214] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1215] In surveillance work, it is necessary to provide an environment in which surveillance personnel can perform their work efficiently and comfortably, reducing the stress caused by being exposed to visually unpleasant or unnecessary information.In addition, it is necessary to focus on monitoring specific targets within the surveillance area, which is necessary to prevent crime and ensure the safety of citizens.

[1216] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1217] In this invention, the server includes a means for a user to input filtering settings, a means for capturing visual information using a camera, a means for transmitting the captured visual information to the server, a means for analyzing the visual information in the server and identifying unnecessary information based on the filtering settings, a means for correcting the identified unnecessary information, a means for transmitting the corrected visual information to a terminal, a means for displaying the corrected visual information, and a means for focused monitoring of specific targets within a monitoring area. This allows monitors to work without visually recognizing unpleasant information, enabling efficient and comfortable monitoring work. Furthermore, focused monitoring of targets contributes to crime prevention and ensuring the safety of citizens.

[1218] A "user" is a person who uses the system to configure filtering settings for visual information.

[1219] The "filtering settings" are settings that specify the conditions for removing unnecessary information from visual information.

[1220] A "camera" is a device that captures visual information.

[1221] "Visual information" refers to image and video data acquired through a camera.

[1222] A "server" is a high performance computer system that analyzes the captured visual information and identifies and modifies unwanted information based on filtering settings.

[1223] "Analysis" is the process of analyzing acquired visual information and extracting specific data.

[1224] "Unwanted information" is information that should be removed from the visual information as specified by the user in the filtering settings.

[1225] "Correction" refers to the process of removing unwanted information from visual information, and includes masking and mosaic processes.

[1226] "Terminal" means a device that receives and displays modified visual information to a user, including a smartphone or smart glasses.

[1227] "Display" is the process of visually presenting the modified visual information to the user at the terminal.

[1228] A "specific target" is an object or person within a surveillance area that requires focused monitoring.

[1229] "Monitoring" is the process of continuously watching a specific target and issuing alarms or notifications as needed.

[1230] The present invention is a system for filtering information visually perceived by a user, and is designed to be particularly useful for surveillance personnel. A specific embodiment of this system and its operating procedure will be described below.

[1231] First, the user (the monitor) puts on the smart glasses and launches a dedicated filtering application on their device (smartphone or tablet). The user configures filtering settings within the application, including specific keywords and categories (e.g., violent images, offensive information).

[1232] Hardware Configuration

[1233] The system includes the following hardware:

[1234] 1. Smart glasses: Equipped with a built-in camera and display, they capture visual information in real time and display the processed information.

[1235] 2. Device: Install and use a filtering application on your smartphone or tablet.

[1236] 3. Server: A high-performance computer system that analyzes the captured visual information and filters out unnecessary information.

[1237] Software Configuration

[1238] The system uses the following software technologies:

[1239] 1. Python: A programming language used for image processing and frame capture.

[1240] 2. OpenCV: A library used for capturing and displaying images.

[1241] 3. Deep learning libraries (e.g., TensorFlow, PyTorch): Used for object recognition and text analysis on the server side.

[1242] Data processing and calculation flow

[1243] 1. Information collection: The smart glasses' built-in camera captures visual information in real time, which is then saved as images or videos.

[1244] 2. Data transmission: The device encrypts the captured visual information and sends it to the server, ensuring security of the transmitted data.

[1245] 3. Analysis: The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted information based on the filtering settings.

[1246] 4. Correction: The server corrects the identified unwanted information by masking or mosaicking it.

[1247] 5. Receiving and displaying data: The corrected visual information is sent to the terminal, which then displays it on the smart glasses display.

[1248] An example of how this system can be used is when a security officer filters out violent graffiti in a city and focuses on monitoring specific targets (such as lost children or suspicious people) within the surveillance area.

[1249] For example, if a security officer is on patrol and there is violent signage or graffiti in the images captured by the smart glasses camera, the system will analyze it and mask it based on the specified filtering criteria, allowing the officer to continue working without visually perceiving the offensive information.

[1250] Example prompt sentence:

[1251] "Generate a Python program to analyze images captured by the smart glasses camera for violent signs and graffiti and mask out specific areas."

[1252] By inputting this prompt sentence into the generative AI model, a program is generated to remove unnecessary information based on the filtering conditions.

[1253] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1254] Step 1:

[1255] Information gathering

[1256] A user wears smart glasses and launches a filtering application on the device. The smart glasses' built-in camera captures the visual information the user sees in real time. The input is image or video data acquired by the camera. The output is the captured visual information data.

[1257] Step 2:

[1258] Data transmission

[1259] The device transmits the captured visual information to the server, where the transmitted data is encrypted for security. The input is the visual information data acquired from the smart glasses. The output is the encrypted visual information data, which is transmitted to the server.

[1260] Step 3:

[1261] Analysis processing

[1262] The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted content based on the filtering settings. For example, it uses a generative AI model to detect violent signs and graffiti according to a prompt. The input is the encrypted visual information data. The output is metadata about the identified unwanted content.

[1263] Step 4:

[1264] Corrective Action

[1265] The server then corrects the identified unwanted information by masking or mosaicking it. At this stage, unwanted information is removed from the visual data. The input is the metadata of the identified unwanted information and the original visual data. The output is the visual data with the unwanted information corrected.

[1266] Step 5:

[1267] Data reception and display

[1268] The server sends the corrected visual information to the terminal. The transmitted data is also encrypted. The terminal receives the corrected visual information and displays it on the display of the smart glasses. The user can view the corrected visual information in real time. The input is the corrected visual information data. The output is the corrected information displayed on the display of the smart glasses.

[1269] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1270] This invention combines an emotion engine with an information filtering eyewear system to achieve dynamic filtering based on the user's emotions, automatically adjusting filtering settings according to the user's emotional state and providing more advanced and comfortable information.

[1271] System Configuration

[1272] Device configuration

[1273] 1. Eyewear

[1274] It has a built-in camera and display.

[1275] It also includes sensors (e.g., facial recognition camera, microphone) to monitor the user's emotions.

[1276] 2. Terminal

[1277] A device such as a smartphone or tablet with a dedicated filtering and emotion recognition application installed.

[1278] 3. Server

[1279] It is a high-performance computer system that analyzes visual information and emotional data and performs filtering processes.

[1280] 4. Emotion Engine

[1281] A system for analyzing emotions in real time using a user's facial recognition data and voice data.

[1282] Program processing explanation

[1283] System Operation

[1284] 1. The user puts on the eyewear and launches the dedicated app on their device. After launching the app, the user configures the filtering settings and simultaneously launches the emotion engine.

[1285] 2. The device camera captures visual information in real time, and the facial recognition camera and microphone obtain the user's emotional data.

[1286] 3. The device transmits the captured visual and emotional data to a server, where it is encrypted for security.

[1287] Filtering and Sentiment Analysis

[1288] 4. The server analyzes the received visual information and identifies unwanted information based on the filtering settings. It also analyzes the emotional data to determine the user's current emotional state.

[1289] 5. The server dynamically adjusts filtering settings based on the emotion engine analysis results. For example, if the user is feeling stressed, stricter filtering will be implemented.

[1290] 6. The server masks or mosaics the identified unwanted information to generate a modified visual representation.

[1291] Submitting and Viewing Corrections

[1292] 7. The server sends the corrected visual information to the device. The data sent is also encrypted.

[1293] 8. The device displays the corrected visual information on the eyewear to prevent the user from seeing unnecessary information. The filtering strength is also adjusted according to the user's emotional state.

[1294] Specific examples

[1295] Ad filtering example

[1296] If a user has opted out of seeing ads from a particular brand and is feeling stressed:

[1297] 1. As a user walks around town, the device's camera captures store advertisements while an emotion sensor detects stress levels.

[1298] 2. The device sends the image data and emotion data to the server.

[1299] 3. The server identifies advertisements from the image data and applies strict filtering due to high stress levels.

[1300] 4. The server sends the modified data with the advertisement portion pixelated to the terminal.

[1301] 5. The device displays the modified image on the eyewear, allowing the user to walk comfortably without seeing brand advertising.

[1302] Example of filtering unpleasant news

[1303] If the user has indicated that they do not want to see war-related news and are in a stable mood:

[1304] 1. The device's camera captures an image of the newspaper stand, and an emotion sensor monitors the user's mood.

[1305] 2. The device sends the image data and emotion data to the server.

[1306] 3. The server analyzes the image data and identifies war-related articles.

[1307] 4. Because the mood is stable, masking is performed at normal filtering strength.

[1308] 5. The server sends the correction data to the terminal, and the terminal displays the corrected image on the eyewear.

[1309] 6. The user can view the newsstand without seeing certain unpleasant news.

[1310] This allows the user to filter information optimally according to their emotional state, providing a more comfortable information environment.

[1311] The processing flow will be explained below.

[1312] Step 1:

[1313] Users launch the dedicated application on their device, access the filtering settings screen, and set criteria for unwanted information, including specific keywords, categories (e.g., ads, news), and images. Additionally, they enable the emotion engine.

[1314] Step 2:

[1315] The device's camera captures visual information in real time, while the facial recognition camera and microphone simultaneously capture the user's emotional data (e.g., facial expressions, tone of voice), which are then stored on the device.

[1316] Step 3:

[1317] The device encrypts the captured visual and emotional data and sends it to the server, along with the user's filtering settings.

[1318] Step 4:

[1319] The server analyzes the received visual information and uses image analysis techniques (e.g., OCR, object recognition) to identify unwanted information that matches the filtering settings.

[1320] Step 5:

[1321] The server analyzes the received emotional data, and the emotion engine determines the user's current emotional state based on facial recognition and voice data, assessing their stress level and mood stability.

[1322] Step 6:

[1323] The server dynamically adjusts filtering settings based on the analysis results of the emotion engine. For example, if a user's stress level is high, the filtering strength will be strengthened to remove a wider range of unnecessary information.

[1324] Step 7:

[1325] The server then modifies the identified unwanted information, masking or mosaicing the unwanted information to generate a modified visual representation. The modifications are tailored based on the emotion data.

[1326] Step 8:

[1327] The server re-encrypts the corrected visual information and sends it to the device, which receives the corrected visual information and displays it on the eyewear.

[1328] Step 9:

[1329] The device then displays the corrected visual information on the eyewear display in real time, allowing the user to enjoy an information environment that has been properly adjusted or cleared of unnecessary information.

[1330] Specific examples

[1331] Example 1: Filtering Ads

[1332] Step 1:

[1333] A user visits a shopping mall and sets up their device to block ads from certain brands.

[1334] Step 2:

[1335] The device's camera captures visual information, and an emotion sensor collects the user's emotion data.

[1336] Step 3:

[1337] The terminal transmits this data to the server.

[1338] Step 4:

[1339] The server analyzes the visual information and identifies brand advertisements.

[1340] Step 5:

[1341] The server analyzes the emotional data and determines that the user's stress level is high.

[1342] Step 6:

[1343] The server applies strict filtering and removes advertisements completely.

[1344] Step 7:

[1345] The server sends the modified visual information to the terminal.

[1346] Step 8:

[1347] The device displays the modified image on the eyewear, allowing the user to enjoy shopping without seeing brand advertisements.

[1348] Example 2: Filtering unpleasant news

[1349] Step 1:

[1350] Users can set their preferences to block war-related news.

[1351] Step 2:

[1352] The device's camera captures images of the newspaper stand and collects emotion data.

[1353] Step 3:

[1354] The terminal transmits this data to the server.

[1355] Step 4:

[1356] The server analyzes the image data and identifies war-related articles.

[1357] Step 5:

[1358] The server analyzes the emotional data and determines that the user's mood is stable.

[1359] Step 6:

[1360] The server performs masking processing using normal filtering.

[1361] Step 7:

[1362] The server sends the modified visual information to the terminal.

[1363] Step 8:

[1364] The terminal displays the corrected image on the eyewear, allowing the user to read the newspaper without seeing the unpleasant news.

[1365] In this way, the user can enjoy a more comfortable information environment through dynamic filtering settings according to the user's emotional state.

[1366] Example 2

[1367] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1368] In today's information society, users are exposed to a huge amount of information, including information that is unnecessary or unpleasant to them. Furthermore, there is a growing need for information filtering based on the user's emotional state. However, conventional systems have difficulty in dynamically filtering information that takes the user's emotional state into account, making it difficult to provide optimal information to each individual user.

[1369] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing visual information and emotional data, identifying unnecessary information based on filtering settings and the emotional state, and dynamically adjusting the filtering settings, means for correcting the identified unnecessary information, and means for transmitting the corrected visual information to the terminal. This allows the user to eliminate unpleasant information in real time and enables optimal information filtering according to the emotional state.

[1370] A "user" is an individual or entity that uses a system.

[1371] "Filtering settings" are setting items for the user to specify information that the user wants to exclude or restrict from being displayed.

[1372] A "camera" is a device for capturing visual information and affective data.

[1373] "Visual information" refers to image and video data captured by a camera.

[1374] "Emotion data" refers to data relating to the emotional state of the user that is obtained by analyzing the user's facial expressions and voice.

[1375] The "server" is a high-performance computer system that analyzes visual information and emotional data and performs filtering processing.

[1376] "Masking" is a process for hiding unnecessary information in visual information.

[1377] "Mosaic processing" is an image processing technique for blurring unnecessary information in visual information.

[1378] A "terminal" is a device such as a smartphone or tablet on which the filtering and emotion recognition application is installed.

[1379] The "Emotion Engine" is a system that analyzes emotions in real time using a user's facial recognition data and voice data.

[1380] The present invention realizes dynamic filtering based on the user's emotions by combining an emotion engine with an information filtering eyewear system. Hereinafter, an embodiment of the present invention will be described in detail.

[1381] System Configuration

[1382] 1. Eyewear

[1383] It has a built-in camera and display, and also contains sensors (e.g., facial recognition camera, microphone) to monitor the user's emotions.

[1384] 2. Terminal

[1385] These devices, such as smartphones and tablets, are equipped with specialized filtering and emotion recognition applications. These devices capture visual and emotional data and transmit it to a server.

[1386] 3. Server

[1387] It is a high-performance computer system that analyzes visual information and emotional data and performs filtering processing. For visual information processing, machine learning models such as OpenCV and TensorFlow are used.

[1388] 4. Emotion Engine

[1389] This is a system that analyzes emotions in real time using facial recognition data and voice data. The emotion engine analyzes the emotion data and determines the user's current emotional state.

[1390] Program processing details

[1391] Acquiring and Sending Data

[1392] The user wears the eyewear and launches a dedicated app on their device. The device's camera captures visual information in real time, while the facial recognition camera and microphone capture the user's emotional data. The captured visual information and emotional data are encrypted for security and sent to a server.

[1393] Data analysis and filtering

[1394] The server analyzes the received visual information and identifies unwanted information based on the filtering settings. At the same time, it uses an emotion engine to analyze the user's emotion data and determine the user's current emotional state, allowing the server to dynamically adjust the filtering settings based on the user's emotional state.

[1395] Correcting and Viewing Information

[1396] The identified unwanted information is masked or pixelated on the server. The corrected visual information is then encrypted and sent to the device. The device then displays the corrected visual information on the eyewear, preventing the user from seeing the unwanted information. The filtering strength is also automatically adjusted according to the user's emotional state.

[1397] Specific examples

[1398] Ad filtering example

[1399] If a user has opted out of seeing ads from a particular brand and is feeling stressed:

[1400] 1. As a user walks around town, the device's camera captures store advertisements and the emotion sensor detects stress levels.

[1401] 2. The device sends the image data and emotion data to the server.

[1402] 3. The server identifies advertisements from the image data and applies strict filtering due to high stress levels.

[1403] 4. The server sends the modified data with the advertisement portion pixelated to the terminal.

[1404] 5. The device displays the modified image on the eyewear, allowing the user to walk comfortably without seeing brand advertising.

[1405] Example of filtering unpleasant news

[1406] If the user has indicated that they do not want to see war-related news and are in a stable mood:

[1407] 1. The device's camera captures an image of the newspaper stand, and an emotion sensor monitors the user's mood.

[1408] 2. The device sends the image data and emotion data to the server.

[1409] 3. The server analyzes the image data and identifies war-related articles.

[1410] 4. Because the mood is stable, masking is performed at normal filtering strength.

[1411] 5. The server sends the correction data to the terminal, and the terminal displays the corrected image on the eyewear.

[1412] 6. The user can view the newsstand without seeing certain unpleasant news.

[1413] This allows the user to filter information optimally according to their emotional state, providing a more comfortable information environment.

[1414] Prompt Sentence Examples

[1415] "If a user is stressed and has set their preferences to not see certain brand ads, what kind of filtering is applied?"

[1416] "What would be the filtering strength if the user set their device to not want to see war-related news and their mood was stable?"

[1417] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1418] Step 1:

[1419] The user puts on the eyewear and launches the dedicated app on their device. The user configures the filtering settings and simultaneously launches the emotion engine. Specifically, the user selects specific keywords and categories on the app's settings screen and sets the filtering strength.

[1420] Input: User filtering settings, app launch

[1421] Output: Filtering setting data, emotion engine activation signal

[1422] Step 2:

[1423] The device uses a camera to capture visual information in real time, and the eyewear's built-in facial recognition camera and microphone capture the user's emotional data, which is then temporarily stored on the device.

[1424] Input: Visual information from camera, emotion data from face recognition camera and microphone

[1425] Output: Visual information data, emotion data

[1426] Specifically, the device's camera captures images of the street or advertisements, and the facial recognition camera analyzes the user's facial expressions to generate emotional data.

[1427] Step 3:

[1428] The device encrypts the captured visual and emotional data and sends it to a server, ensuring data security.

[1429] Input: Visual information data, emotion data

[1430] Output: Encrypted visual information data, encrypted emotion data

[1431] Specifically, the device encrypts the collected data using an encryption algorithm (e.g., AES) and issues a signal to send it to the server.

[1432] Step 4:

[1433] The server analyzes the received visual information and identifies unwanted information based on the filtering settings, while simultaneously analyzing the emotional data using an emotion engine to determine the user's current emotional state.

[1434] Input: Encrypted visual information data, encrypted emotion data

[1435] Output: Unwanted information identification data, emotional state data

[1436] Specifically, the server uses machine learning models (e.g., OpenCV, TensorFlow) to analyze images and identify unnecessary information, and the emotion engine analyzes the user's emotional state.

[1437] Step 5:

[1438] The server dynamically adjusts the filtering settings based on the emotional state data, thereby applying filtering that best suits the user's emotional state.

[1439] Input: Unwanted information identification data, emotional state data

[1440] Output: Adjusted filtering setting data

[1441] Specifically, the server dynamically changes the parameters of the filtering algorithm according to the emotional state, adjusting the strictness of the filtering, etc.

[1442] Step 6:

[1443] The identified unwanted information is masked or pixelated on the server to generate modified visual information.

[1444] Input: Adjusted filtering setting data, unnecessary information identification data

[1445] Output: Corrected visual information data

[1446] Specifically, the server applies an image processing algorithm based on the filtering settings to mask or mosaic unwanted information.

[1447] Step 7:

[1448] The server re-encrypts the modified visual information and sends it to the device, where this data is also encrypted for security reasons.

[1449] Input: Corrected visual information data

[1450] Output: Encrypted modified visual information data

[1451] Specifically, the server begins the process of encrypting the modified image data and sending it to the terminal.

[1452] Step 8:

[1453] The device decodes the corrected visual information and displays it on the eyewear, adjusting the filtering strength accordingly to prevent the user from viewing unnecessary information.

[1454] Input: Encrypted modified visual information data

[1455] Output: Corrected visual information displayed on eyewear

[1456] Specifically, the terminal performs the function of decrypting the encrypted data and displaying it on the eyewear display.

[1457] Through the above specific processing steps, the information filtering eyewear system realizes dynamic filtering based on the user's emotional state, providing a comfortable information environment.

[1458] (Application example 2)

[1459] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1460] Conventional information filtering systems are unable to dynamically adjust to the user's emotional state and always apply the same filtering settings, resulting in the problem of not providing users with sufficient information to make them comfortable.In addition, they are unable to provide optimal product recommendations or advertisements that match the customer's purchasing motivation or stress level, making it difficult to improve the quality of the shopping experience in physical stores.

[1461] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for monitoring the user's emotional state, means for transmitting the user's emotional data to the server, and means for analyzing the emotional data in the server and dynamically adjusting filtering settings based on the user's emotional state. This enables appropriate information filtering and product recommendations according to the user's emotional state, improving the shopping experience in physical stores.

[1462] "User" refers to a person who uses the system.

[1463] "Filtering settings" refers to the criteria and conditions that a user sets to remove unnecessary information from visual information.

[1464] "Visual information" refers to images and video data captured through devices such as cameras.

[1465] A "server" refers to a high-performance computer system that analyzes and processes data.

[1466] "Unnecessary information" refers to information that is determined not to need to be displayed or provided based on the user's filtering settings.

[1467] "Correction" refers to processing unnecessary information so that it is not visible to the user, using masking or mosaic processing.

[1468] "Terminal" refers to a mobile device such as a smartphone or tablet.

[1469] "Emotional state" refers to a user's psychological emotional state (e.g., stress, joy, anger, etc.).

[1470] "Emotion data" is data that indicates the user's emotional state, and includes facial expressions, voice, and the like.

[1471] "Dynamic adjustment" refers to changing settings and conditions in real time depending on the user's emotional state.

[1472] The present invention relates to a system for realizing dynamic information filtering based on user emotions. To understand and implement this system, it is necessary to incorporate the following elements and processes.

[1473] System Configuration

[1474] Hardware

[1475] Eyewear: The device is equipped with a built-in camera, display, microphone, and facial recognition camera.

[1476] Device: A handheld device such as a smartphone or tablet.

[1477] Server: A high-performance computer system for data analysis and processing.

[1478] software

[1479] Emotion Recognition and Filtering Applications

[1480] Emotion Engine

[1481] Deep learning libraries (e.g. TensorFlow, PyTorch)

[1482] Program processing flow

[1483] 1. The user puts on the eyewear and launches the dedicated app on their device. After launching the app, the user configures the filtering settings and simultaneously launches the emotion engine.

[1484] 2. The device camera captures visual information in real time, and the facial recognition camera and microphone capture the user's emotional data, which is encrypted for security.

[1485] 3. The device transmits the captured visual information and emotional data to the server, which receives the data and uses an emotion engine to analyze the user's current emotional state.

[1486] 4. The server dynamically adjusts filtering settings based on the analysis of the emotional data. For example, if the user is feeling stressed, stricter filtering will be implemented.

[1487] 5. The server analyzes the received visual information and identifies unwanted information based on the filtering settings. The identified unwanted information is masked or pixelated to generate the corrected visual information.

[1488] 6. The server sends the corrected visual information to the device. The data sent is also encrypted.

[1489] 7. The device displays the corrected visual information on the eyewear to prevent the user from seeing unnecessary information. The filtering strength is also adjusted according to the user's emotional state.

[1490] Specific examples

[1491] 1. When the user is walking around town

[1492] If a user has indicated that they do not want to see ads for a particular brand and are feeling stressed, use the following prompt:

[1493] Users are frustrated. Please tighten up your filtering and hide ads from certain brands.

[1494] 2. When the user is shopping in-store

[1495] If the user is feeling good and is looking for relaxation products, use the following prompt:

[1496] The user is relaxed. Please recommend some relaxation-related products.

[1497] These features enable users to receive optimal information filtering and product recommendations according to their emotional state, providing a more comfortable shopping experience.

[1498] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1499] Step 1:

[1500] The user puts on the eyewear and launches the dedicated app on the device. After launching the application, the user configures the filtering settings and simultaneously launches the emotion engine. The input is the user's filtering settings and start command, and the output is the start of the emotion engine and initial setting data. In this step, setting information is collected and the system is initialized.

[1501] Step 2:

[1502] The device's camera captures visual information in real time, while the facial recognition camera and microphone acquire the user's emotional data. The input is the live feed from the camera and microphone, and the output is the captured visual information and audio data. In this step, the camera and microphone are used to continuously collect the user's visual information and emotional state.

[1503] Step 3:

[1504] The device transmits the captured visual information and emotional data to the server. The input is the visual information and emotional data obtained in step 2, and the output is the data to be transmitted to the server. In this step, the collected data is encrypted and securely transmitted to the server.

[1505] Step 4:

[1506] The server analyzes the received visual information and emotional data. The input is the encrypted visual information and emotional data, and the output is the analysis result. During the analysis, the emotion engine uses a deep learning library to determine the user's emotional state in real time, while the content of the visual information is analyzed.

[1507] Step 5:

[1508] The server dynamically adjusts the filtering settings based on the analysis results of the emotional data. The inputs are the analysis results and the initial filtering settings, and the output is the adjusted filtering settings. In this step, the server changes the filtering strictness according to the user's emotional state.

[1509] Step 6:

[1510] The server analyzes the received visual information and identifies unwanted information based on the filtering settings. The input is the adjusted filtering settings and the visual information, and the output is the identified unwanted information. In this step, the filtering algorithm performs the operation of identifying unwanted information.

[1511] Step 7:

[1512] The server corrects the identified unwanted information and generates a corrected visual representation. The input is the list of unwanted information and the original visual representation, and the output is the corrected visual representation. The correction is performed using mossing or mosaic processes.

[1513] Step 8:

[1514] The server sends the corrected visual information to the terminal. The input is the corrected visual information, and the output is the data to be sent to the terminal. In this step, the corrected data is encrypted again and sent to the terminal.

[1515] Step 9:

[1516] The terminal displays the corrected visual information on the eyewear to prevent the user from viewing unnecessary information. The input is the corrected visual information, and the output is the visual information displayed on the eyewear. In this step, the user is finally provided with visual information from which unnecessary information has been removed.

[1517] At each step, data processing and calculations are performed based on the collected data, and the information necessary for the next step is generated, allowing the entire system to operate seamlessly.

[1518] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1519] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1520] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1521] [Fourth embodiment]

[1522] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1523] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1524] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1525] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1526] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1527] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1528] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1529] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1530] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1531] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1532] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1533] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1534] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1535] The present invention relates to an information filtering eyewear system that is a system for filtering information visually perceived by an individual, eliminating unnecessary or unpleasant information and providing necessary and comfortable information to the user.

[1536] Program processing explanation

[1537] System Configuration

[1538] 1. Equipment configuration

[1539] The eyewear worn by the user includes a built-in camera and display.

[1540] The terminals are devices such as smartphones and tablets, and have a dedicated filtering application installed.

[1541] The server is a high performance computer system for performing the analysis and filtering processes.

[1542] 2. System Operation

[1543] The user puts on the eyewear and launches the dedicated app on their device.

[1544] Users configure filtering settings within the app, including specific keywords, categories (e.g., ads, news), and images.

[1545] Information collection and transmission

[1546] 3. Information gathering

[1547] The device's camera captures visual information in real time, which is then saved as images or videos.

[1548] 4. Data transmission

[1549] The device sends the captured visual information to a server, where the data is encrypted to ensure security.

[1550] Filtering Process

[1551] 5. Analysis and Processing

[1552] The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted information based on the filtering settings.

[1553] 6. Corrective Actions

[1554] The server then modifies the identified unwanted information by masking or mosaicking it, etc. At this stage, the unwanted information is removed from the user's view.

[1555] Receiving and displaying data

[1556] 7. Sending and Receiving Data

[1557] The server then sends the corrected visual information to the device, and the data sent is also encrypted.

[1558] 8. Display of correction information

[1559] The device displays the corrected visual information on the eyewear, allowing the user to visually recognize the filtered information.

[1560] Specific examples

[1561] Ad filtering

[1562] If a user indicates that they do not want to see ads for a particular brand in the shopping mall:

[1563] 1. As the user walks around town, the device's camera captures store advertisements.

[1564] 2. The device sends the image data to the server.

[1565] 3. The server analyzes the received image data and identifies advertisements that match the filtering settings.

[1566] 4. The server blurs the advertisement portion and sends the corrected data to the device.

[1567] 5. The device displays the modified image on the eyewear, preventing the user from seeing the specific brand advertisements.

[1568] Filtering unpleasant news

[1569] If the user does not want to see news about wars or disasters:

[1570] 1. The device's camera captures an image of a newspaper stand.

[1571] 2. The device sends the image data to the server.

[1572] 3. The server performs text analysis to identify articles about war and disasters.

[1573] 4. The server masks that portion and sends the corrected data to the terminal.

[1574] 5. The device displays the corrected image on the eyewear, preventing the user from seeing the unpleasant news.

[1575] This allows users to focus on necessary information without being exposed to unnecessary or unpleasant information. This system functions as an effective means of maintaining a comfortable personal information environment.

[1576] The processing flow will be explained below.

[1577] Step 1:

[1578] Users launch a dedicated application on their device. After launching the application, users access a filtering settings screen and set criteria for unwanted content, including specific keywords, categories (e.g., ads, news), and images. These settings are then saved.

[1579] Step 2:

[1580] The device activates the camera and captures visual information in real time, which is then temporarily stored in the device's memory.

[1581] Step 3:

[1582] The device sends the captured visual information to a server, encrypted for security purposes, over Wi-Fi or mobile data networks.

[1583] Step 4:

[1584] The server prepares the received visual information for analysis, applying image recognition techniques (e.g., object recognition, OCR text analysis) to the visual information to search for unwanted content that matches the filtering settings.

[1585] Step 5:

[1586] The server identifies unwanted content based on the filtering settings, such as advertising banners or text containing specific keywords, and records the location of any content identified as unwanted.

[1587] Step 6:

[1588] The server then corrects the identified unnecessary information by masking the unnecessary information (e.g., by pixelating the image), so that the user cannot see the unnecessary information.

[1589] Step 7:

[1590] The server then sends the corrected visual information to the terminal, where the corrected data is encrypted again to ensure security.

[1591] Step 8:

[1592] The device receives the corrected visual information and displays it on the eyewear. By displaying the corrected visual information on the eyewear display in real time, the user can enjoy a comfortable information environment with unnecessary information removed.

[1593] Example 1

[1594] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1595] In today's information-overloaded environment, users are often exposed to unnecessary or unpleasant visual information. This information can disrupt users' concentration and cause psychological stress. In response, there is a need for a system that allows users to filter out unnecessary information and visually perceive only the necessary and pleasant information.

[1596] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1597] In this invention, the server includes means for using object recognition technology and text analysis technology when correcting visual information based on filtering settings, means for displaying the corrected visual information on the eyewear in real time, and means for encrypting communications between the server and the terminal, thereby enabling the user to automatically filter unnecessary information in real time and view only visual information that is comfortable to the user.

[1598] "User" refers to the individual who wears the eyewear and configures the filtering settings.

[1599] "Filtering settings" refers to settings of specific keywords, categories, or images that a user enters to identify unwanted information.

[1600] "Camera" refers to a photographic device used to capture visual information.

[1601] "Visual information" refers to image and video data captured by a camera.

[1602] "Server" refers to a high performance computer system for analyzing and filtering visual information.

[1603] "Terminal" refers to a device such as a smartphone or tablet on which a dedicated filtering application is installed.

[1604] "Object recognition technology" refers to technology that automatically identifies specific objects within visual information.

[1605] "Text analysis technology" refers to technology that analyzes text within visual information and understands its meaning.

[1606] "Masking" refers to the process of painting over part of visual information to hide unnecessary information.

[1607] "Mosaicing" refers to the process of covering part of visual information with a fine block-like pattern in order to hide unnecessary information.

[1608] "Real time" refers to processing and display occurring immediately, without delay.

[1609] "Encryption" refers to the technology of converting data so that its contents cannot be recognized by third parties.

[1610] "Eyewear" refers to glasses-type devices that incorporate a camera and a display.

[1611] The present invention relates to a system for filtering information visually perceived by an individual, and more particularly to an information filtering eyewear system that eliminates unnecessary or unpleasant information and provides necessary and comfortable information to the user.

[1612] System configuration and operation overview

[1613] The system consists of three main components:

[1614] 1. Eyewear worn by the user

[1615] 2. A device with the dedicated application installed

[1616] 3. Server that performs information analysis and filtering

[1617] 1. Eyewear worn by the user

[1618] The eyewear includes a built-in camera for capturing visual information and a display for displaying the corrected visual information. The eyewear communicates with the device using Bluetooth or Wi-Fi.

[1619] 2. A device with the dedicated application installed

[1620] A dedicated filtering application is installed on a user's device (such as a smartphone or tablet), and this application provides an interface for the user to input filtering settings.

[1621] 3. Server that performs information analysis and filtering

[1622] The server is a high-performance computer system that receives and analyzes the visual information sent from the device, using object recognition and text analysis techniques.

[1623] Specific processing details

[1624] Enter filtering settings

[1625] Using a dedicated application, users input their desired filtering settings, such as specific keywords (such as "advertising" or "news"), categories, or images (such as a particular brand logo).

[1626] Visual information capture

[1627] While the user is walking or moving around, the built-in camera in the eyewear captures visual information from the surroundings in real time, which is then transmitted to the device.

[1628] Data transmission and analysis

[1629] The device transmits the captured visual information to a server, which encrypts and secures the data. The server then analyzes the received data and identifies unwanted content based on the filtering settings. For example, the server uses object recognition technology to identify specific brand advertisements and text analysis technology to identify offensive news articles.

[1630] Correcting and Viewing Information

[1631] The server then corrects the identified unwanted information (specifically, by masking or mosaicing) and sends the corrected visual information to the device, which then displays the corrected information in real time on the eyewear display, allowing the user to view the filtered, comfortable visual information.

[1632] Specific use cases

[1633] Ad filtering example

[1634] 1. A user sets a filtering app to "I don't want to see ads for a specific brand X."

[1635] 2. When the user enters the shopping mall, the eyewear captures the advertisement.

[1636] 3. The device sends the captured image data to the server.

[1637] 4. The server parses the ad and identifies the ad for Brand X.

[1638] 5. The server blurs the advertisement portion and sends the correction data to the terminal.

[1639] 6. The device displays the corrected information on the eyewear, and the user no longer sees Brand X's advertisements.

[1640] Prompt Sentence Examples

[1641] "Filter ads for brands you don't want to see in the mall."

[1642] Example of filtering unpleasant news

[1643] 1. The user sets a filtering app to "I don't want to see news about war or disasters."

[1644] 2. The device's camera captures an image of the newsstand.

[1645] 3. The device sends the image data to the server.

[1646] 4. The server analyzes the received data and identifies articles about wars and disasters.

[1647] 5. The server masks that portion and sends the corrected data to the terminal.

[1648] 6. The device displays the corrected information on the eyewear, and the user no longer sees the unpleasant news.

[1649] Prompt Sentence Examples

[1650] "Filter news about wars and disasters."

[1651] This system allows users to focus on the information they need without being exposed to unnecessary or unpleasant information.

[1652] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1653] Step 1:

[1654] The user launches the dedicated filtering app and puts on the eyewear, which then communicates with the device via Bluetooth or Wi-Fi to check the connection status.

[1655] Specific behavior:

[1656] The user taps on the device to launch the app.

[1657] The app screen will open and you can check the connection status with your eyewear.

[1658] The user puts on the eyewear and confirms that "Connection complete" is displayed on the app screen.

[1659] Input: Application launch, eyewear connection

[1660] Output: Eyewear and device are connected properly

[1661] Step 2:

[1662] The user enters their filtering preferences: they select specific keywords, categories, or images in the app's settings screen.

[1663] Specific behavior:

[1664] Select a filtering category from the list displayed on the settings screen.

[1665] Enter a word or phrase in the text field provided for entering specific keywords.

[1666] For image filtering, select an image from your camera roll.

[1667] Input: Filtering settings (keywords, categories, images)

[1668] Output: User filtering settings data

[1669] Step 3:

[1670] While the user is active, the eyewear's camera captures visual information in real time, which is then stored on the device as images or videos.

[1671] Specific behavior:

[1672] The eyewear's camera automatically captures visual information from your surroundings.

[1673] The captured information is transferred to the device in real time.

[1674] Input: Real-world visual information

[1675] Output: Captured visual information (images, videos)

[1676] Step 4:

[1677] The device encrypts the captured visual information and sends it to the server, ensuring security.

[1678] Specific behavior:

[1679] The terminal receives the captured visual information.

[1680] The received data is encrypted and sent to the server.

[1681] Input: Captured visual information

[1682] Output: Encrypted visual information

[1683] Step 5:

[1684] The server decodes the received visual information and begins analyzing it, using object recognition and text analysis techniques to identify unwanted content based on the filtering settings.

[1685] Specific behavior:

[1686] The server decrypts the encrypted data.

[1687] Object recognition algorithms are used to detect specific objects within the visual information.

[1688] Text analysis techniques are used to analyze text within visual information.

[1689] Input: Encrypted visual information

[1690] Output: Analysis results (identification of unnecessary information)

[1691] Step 6:

[1692] The server then modifies the identified unwanted information, for example by masking or mosaicing it, to generate modified visual information.

[1693] Specific behavior:

[1694] The server identifies the garbage.

[1695] Apply masking or mosaic processing to unwanted information.

[1696] Input: Analysis results (identification of unnecessary information)

[1697] Output: Corrected visual information

[1698] Step 7:

[1699] The server re-encrypts the corrected visual information and sends it to the terminal. For security reasons, the transmitted data is encrypted.

[1700] Specific behavior:

[1701] The server encrypts the modified visual information.

[1702] The encrypted data is sent to the terminal.

[1703] Input: Corrected visual information

[1704] Output: Encrypted revision information

[1705] Step 8:

[1706] The terminal receives the modified visual information, decodes it, and displays it on the eyewear, allowing the user to visually perceive the filtered information.

[1707] Specific behavior:

[1708] The terminal receives the encrypted modification information.

[1709] Decrypt the received data.

[1710] The decoded information is displayed on the eyewear display.

[1711] Input: Encrypted correction information

[1712] Output: Corrected visual information displayed on eyewear

[1713] (Application example 1)

[1714] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1715] In surveillance work, it is necessary to provide an environment in which surveillance personnel can perform their work efficiently and comfortably, reducing the stress caused by being exposed to visually unpleasant or unnecessary information.In addition, it is necessary to focus on monitoring specific targets within the surveillance area, which is necessary to prevent crime and ensure the safety of citizens.

[1716] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1717] In this invention, the server includes a means for a user to input filtering settings, a means for capturing visual information using a camera, a means for transmitting the captured visual information to the server, a means for analyzing the visual information in the server and identifying unnecessary information based on the filtering settings, a means for correcting the identified unnecessary information, a means for transmitting the corrected visual information to a terminal, a means for displaying the corrected visual information, and a means for focused monitoring of specific targets within a monitoring area. This allows monitors to work without visually recognizing unpleasant information, enabling efficient and comfortable monitoring work. Furthermore, focused monitoring of targets contributes to crime prevention and ensuring the safety of citizens.

[1718] A "user" is a person who uses the system to configure filtering settings for visual information.

[1719] The "filtering settings" are settings that specify the conditions for removing unnecessary information from visual information.

[1720] A "camera" is a device that captures visual information.

[1721] "Visual information" refers to image and video data acquired through a camera.

[1722] A "server" is a high performance computer system that analyzes the captured visual information and identifies and modifies unwanted information based on filtering settings.

[1723] "Analysis" is the process of analyzing acquired visual information and extracting specific data.

[1724] "Unwanted information" is information that should be removed from the visual information as specified by the user in the filtering settings.

[1725] "Correction" refers to the process of removing unwanted information from visual information, and includes masking and mosaic processes.

[1726] "Terminal" means a device that receives and displays modified visual information to a user, including a smartphone or smart glasses.

[1727] "Display" is the process of visually presenting the modified visual information to the user at the terminal.

[1728] A "specific target" is an object or person within a surveillance area that requires focused monitoring.

[1729] "Monitoring" is the process of continuously watching a specific target and issuing alarms or notifications as needed.

[1730] The present invention is a system for filtering information visually perceived by a user, and is designed to be particularly useful for surveillance personnel. A specific embodiment of this system and its operating procedure will be described below.

[1731] First, the user (the monitor) puts on the smart glasses and launches a dedicated filtering application on their device (smartphone or tablet). The user configures filtering settings within the application, including specific keywords and categories (e.g., violent images, offensive information).

[1732] Hardware Configuration

[1733] The system includes the following hardware:

[1734] 1. Smart glasses: Equipped with a built-in camera and display, they capture visual information in real time and display the processed information.

[1735] 2. Device: Install and use a filtering application on your smartphone or tablet.

[1736] 3. Server: A high-performance computer system that analyzes the captured visual information and filters out unnecessary information.

[1737] Software Configuration

[1738] The system uses the following software technologies:

[1739] 1. Python: A programming language used for image processing and frame capture.

[1740] 2. OpenCV: A library used for capturing and displaying images.

[1741] 3. Deep learning libraries (e.g., TensorFlow, PyTorch): Used for object recognition and text analysis on the server side.

[1742] Data processing and calculation flow

[1743] 1. Information collection: The smart glasses' built-in camera captures visual information in real time, which is then saved as images or videos.

[1744] 2. Data transmission: The device encrypts the captured visual information and sends it to the server, ensuring security of the transmitted data.

[1745] 3. Analysis: The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted information based on the filtering settings.

[1746] 4. Correction: The server corrects the identified unwanted information by masking or mosaicking it.

[1747] 5. Receiving and displaying data: The corrected visual information is sent to the terminal, which then displays it on the smart glasses display.

[1748] An example of how this system can be used is when a security officer filters out violent graffiti in a city and focuses on monitoring specific targets (such as lost children or suspicious people) within the surveillance area.

[1749] For example, if a security officer is on patrol and there is violent signage or graffiti in the images captured by the smart glasses camera, the system will analyze it and mask it based on the specified filtering criteria, allowing the officer to continue working without visually perceiving the offensive information.

[1750] Example prompt sentence:

[1751] "Generate a Python program to analyze images captured by the smart glasses camera for violent signs and graffiti and mask out specific areas."

[1752] By inputting this prompt sentence into the generative AI model, a program is generated to remove unnecessary information based on the filtering conditions.

[1753] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1754] Step 1:

[1755] Information gathering

[1756] A user wears smart glasses and launches a filtering application on the device. The smart glasses' built-in camera captures the visual information the user sees in real time. The input is image or video data acquired by the camera. The output is the captured visual information data.

[1757] Step 2:

[1758] Data transmission

[1759] The device transmits the captured visual information to the server, where the transmitted data is encrypted for security. The input is the visual information data acquired from the smart glasses. The output is the encrypted visual information data, which is transmitted to the server.

[1760] Step 3:

[1761] Analysis processing

[1762] The server analyzes the received visual information using object recognition and text analysis techniques to identify unwanted content based on the filtering settings. For example, it uses a generative AI model to detect violent signs and graffiti according to a prompt. The input is the encrypted visual information data. The output is metadata about the identified unwanted content.

[1763] Step 4:

[1764] Corrective Action

[1765] The server then corrects the identified unwanted information by masking or mosaicking it. At this stage, unwanted information is removed from the visual data. The input is the metadata of the identified unwanted information and the original visual data. The output is the visual data with the unwanted information corrected.

[1766] Step 5:

[1767] Data reception and display

[1768] The server sends the corrected visual information to the terminal. The transmitted data is also encrypted. The terminal receives the corrected visual information and displays it on the display of the smart glasses. The user can view the corrected visual information in real time. The input is the corrected visual information data. The output is the corrected information displayed on the display of the smart glasses.

[1769] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1770] This invention combines an emotion engine with an information filtering eyewear system to achieve dynamic filtering based on the user's emotions, automatically adjusting filtering settings according to the user's emotional state and providing more advanced and comfortable information.

[1771] System Configuration

[1772] Device configuration

[1773] 1. Eyewear

[1774] It has a built-in camera and display.

[1775] It also includes sensors (e.g., facial recognition camera, microphone) to monitor the user's emotions.

[1776] 2. Terminal

[1777] A device such as a smartphone or tablet with a dedicated filtering and emotion recognition application installed.

[1778] 3. Server

[1779] It is a high-performance computer system that analyzes visual information and emotional data and performs filtering processes.

[1780] 4. Emotion Engine

[1781] A system for analyzing emotions in real time using a user's facial recognition data and voice data.

[1782] Program processing explanation

[1783] System Operation

[1784] 1. The user puts on the eyewear and launches the dedicated app on their device. After launching the app, the user configures the filtering settings and simultaneously launches the emotion engine.

[1785] 2. The device camera captures visual information in real time, and the facial recognition camera and microphone obtain the user's emotional data.

[1786] 3. The device transmits the captured visual and emotional data to a server, where it is encrypted for security.

[1787] Filtering and Sentiment Analysis

[1788] 4. The server analyzes the received visual information and identifies unwanted information based on the filtering settings. It also analyzes the emotional data to determine the user's current emotional state.

[1789] 5. The server dynamically adjusts filtering settings based on the emotion engine analysis results. For example, if the user is feeling stressed, stricter filtering will be implemented.

[1790] 6. The server masks or mosaics the identified unwanted information to generate a modified visual representation.

[1791] Submitting and Viewing Corrections

[1792] 7. The server sends the corrected visual information to the device. The data sent is also encrypted.

[1793] 8. The device displays the corrected visual information on the eyewear to prevent the user from seeing unnecessary information. The filtering strength is also adjusted according to the user's emotional state.

[1794] Specific examples

[1795] Ad filtering example

[1796] If a user has opted out of seeing ads from a particular brand and is feeling stressed:

[1797] 1. As a user walks around town, the device's camera captures store advertisements while an emotion sensor detects stress levels.

[1798] 2. The device sends the image data and emotion data to the server.

[1799] 3. The server identifies advertisements from the image data and applies strict filtering due to high stress levels.

[1800] 4. The server sends the modified data with the advertisement portion pixelated to the terminal.

[1801] 5. The device displays the modified image on the eyewear, allowing the user to walk comfortably without seeing brand advertising.

[1802] Example of filtering unpleasant news

[1803] If the user has indicated that they do not want to see war-related news and are in a stable mood:

[1804] 1. The device's camera captures an image of the newspaper stand, and an emotion sensor monitors the user's mood.

[1805] 2. The device sends the image data and emotion data to the server.

[1806] 3. The server analyzes the image data and identifies war-related articles.

[1807] 4. Because the mood is stable, masking is performed at normal filtering strength.

[1808] 5. The server sends the correction data to the terminal, and the terminal displays the corrected image on the eyewear.

[1809] 6. The user can view the newsstand without seeing certain unpleasant news.

[1810] This allows the user to filter information optimally according to their emotional state, providing a more comfortable information environment.

[1811] The processing flow will be explained below.

[1812] Step 1:

[1813] Users launch the dedicated application on their device, access the filtering settings screen, and set criteria for unwanted information, including specific keywords, categories (e.g., ads, news), and images. Additionally, they enable the emotion engine.

[1814] Step 2:

[1815] The device's camera captures visual information in real time, while the facial recognition camera and microphone simultaneously capture the user's emotional data (e.g., facial expressions, tone of voice), which are then stored on the device.

[1816] Step 3:

[1817] The device encrypts the captured visual and emotional data and sends it to the server, along with the user's filtering settings.

[1818] Step 4:

[1819] The server analyzes the received visual information and uses image analysis techniques (e.g., OCR, object recognition) to identify unwanted information that matches the filtering settings.

[1820] Step 5:

[1821] The server analyzes the received emotional data, and the emotion engine determines the user's current emotional state based on facial recognition and voice data, assessing their stress level and mood stability.

[1822] Step 6:

[1823] The server dynamically adjusts filtering settings based on the analysis results of the emotion engine. For example, if a user's stress level is high, the filtering strength will be strengthened to remove a wider range of unnecessary information.

[1824] Step 7:

[1825] The server then modifies the identified unwanted information, masking or mosaicing the unwanted information to generate a modified visual representation. The modifications are tailored based on the emotion data.

[1826] Step 8:

[1827] The server re-encrypts the corrected visual information and sends it to the device, which receives the corrected visual information and displays it on the eyewear.

[1828] Step 9:

[1829] The device then displays the corrected visual information on the eyewear display in real time, allowing the user to enjoy an information environment that has been properly adjusted or cleared of unnecessary information.

[1830] Specific examples

[1831] Example 1: Filtering Ads

[1832] Step 1:

[1833] A user visits a shopping mall and sets up their device to block ads from certain brands.

[1834] Step 2:

[1835] The device's camera captures visual information, and an emotion sensor collects the user's emotion data.

[1836] Step 3:

[1837] The terminal transmits this data to the server.

[1838] Step 4:

[1839] The server analyzes the visual information and identifies brand advertisements.

[1840] Step 5:

[1841] The server analyzes the emotional data and determines that the user's stress level is high.

[1842] Step 6:

[1843] The server applies strict filtering and removes advertisements completely.

[1844] Step 7:

[1845] The server sends the modified visual information to the terminal.

[1846] Step 8:

[1847] The device displays the modified image on the eyewear, allowing the user to enjoy shopping without seeing brand advertisements.

[1848] Example 2: Filtering unpleasant news

[1849] Step 1:

[1850] Users can set their preferences to block war-related news.

[1851] Step 2:

[1852] The device's camera captures images of the newspaper stand and collects emotion data.

[1853] Step 3:

[1854] The terminal transmits this data to the server.

[1855] Step 4:

[1856] The server analyzes the image data and identifies war-related articles.

[1857] Step 5:

[1858] The server analyzes the emotional data and determines that the user's mood is stable.

[1859] Step 6:

[1860] The server performs masking processing using normal filtering.

[1861] Step 7:

[1862] The server sends the modified visual information to the terminal.

[1863] Step 8:

[1864] The terminal displays the corrected image on the eyewear, allowing the user to read the newspaper without seeing the unpleasant news.

[1865] In this way, the user can enjoy a more comfortable information environment through dynamic filtering settings according to the user's emotional state.

[1866] Example 2

[1867] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1868] In today's information society, users are exposed to a huge amount of information, including information that is unnecessary or unpleasant to them. Furthermore, there is a growing need for information filtering based on the user's emotional state. However, conventional systems have difficulty in dynamically filtering information that takes the user's emotional state into account, making it difficult to provide optimal information to each individual user.

[1869] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for analyzing visual information and emotional data, identifying unnecessary information based on filtering settings and the emotional state, and dynamically adjusting the filtering settings, means for correcting the identified unnecessary information, and means for transmitting the corrected visual information to the terminal. This allows the user to eliminate unpleasant information in real time and enables optimal information filtering according to the emotional state.

[1870] A "user" is an individual or entity that uses a system.

[1871] "Filtering settings" are setting items for the user to specify information that the user wants to exclude or restrict from being displayed.

[1872] A "camera" is a device for capturing visual information and affective data.

[1873] "Visual information" refers to image and video data captured by a camera.

[1874] "Emotion data" refers to data relating to the emotional state of the user that is obtained by analyzing the user's facial expressions and voice.

[1875] The "server" is a high-performance computer system that analyzes visual information and emotional data and performs filtering processing.

[1876] "Masking" is a process for hiding unnecessary information in visual information.

[1877] "Mosaic processing" is an image processing technique for blurring unnecessary information in visual information.

[1878] A "terminal" is a device such as a smartphone or tablet on which the filtering and emotion recognition application is installed.

[1879] The "Emotion Engine" is a system that analyzes emotions in real time using a user's facial recognition data and voice data.

[1880] The present invention realizes dynamic filtering based on the user's emotions by combining an emotion engine with an information filtering eyewear system. Hereinafter, an embodiment of the present invention will be described in detail.

[1881] System Configuration

[1882] 1. Eyewear

[1883] It has a built-in camera and display, and also contains sensors (e.g., facial recognition camera, microphone) to monitor the user's emotions.

[1884] 2. Terminal

[1885] These devices, such as smartphones and tablets, are equipped with specialized filtering and emotion recognition applications. These devices capture visual and emotional data and transmit it to a server.

[1886] 3. Server

[1887] It is a high-performance computer system that analyzes visual information and emotional data and performs filtering processing. For visual information processing, machine learning models such as OpenCV and TensorFlow are used.

[1888] 4. Emotion Engine

[1889] This is a system that analyzes emotions in real time using facial recognition data and voice data. The emotion engine analyzes the emotion data and determines the user's current emotional state.

[1890] Program processing details

[1891] Acquiring and Sending Data

[1892] The user wears the eyewear and launches a dedicated app on their device. The device's camera captures visual information in real time, while the facial recognition camera and microphone capture the user's emotional data. The captured visual information and emotional data are encrypted for security and sent to a server.

[1893] Data analysis and filtering

[1894] The server analyzes the received visual information and identifies unwanted information based on the filtering settings. At the same time, it uses an emotion engine to analyze the user's emotion data and determine the user's current emotional state, allowing the server to dynamically adjust the filtering settings based on the user's emotional state.

[1895] Correcting and Viewing Information

[1896] The identified unwanted information is masked or pixelated on the server. The corrected visual information is then encrypted and sent to the device. The device then displays the corrected visual information on the eyewear, preventing the user from seeing the unwanted information. The filtering strength is also automatically adjusted according to the user's emotional state.

[1897] Specific examples

[1898] Ad filtering example

[1899] If a user has opted out of seeing ads from a particular brand and is feeling stressed:

[1900] 1. As a user walks around town, the device's camera captures store advertisements and the emotion sensor detects stress levels.

[1901] 2. The device sends the image data and emotion data to the server.

[1902] 3. The server identifies advertisements from the image data and applies strict filtering due to high stress levels.

[1903] 4. The server sends the modified data with the advertisement portion pixelated to the terminal.

[1904] 5. The device displays the modified image on the eyewear, allowing the user to walk comfortably without seeing brand advertising.

[1905] Example of filtering unpleasant news

[1906] If the user has indicated that they do not want to see war-related news and are in a stable mood:

[1907] 1. The device's camera captures an image of the newspaper stand, and an emotion sensor monitors the user's mood.

[1908] 2. The device sends the image data and emotion data to the server.

[1909] 3. The server analyzes the image data and identifies war-related articles.

[1910] 4. Because the mood is stable, masking is performed at normal filtering strength.

[1911] 5. The server sends the correction data to the terminal, and the terminal displays the corrected image on the eyewear.

[1912] 6. The user can view the newsstand without seeing certain unpleasant news.

[1913] This allows the user to filter information optimally according to their emotional state, providing a more comfortable information environment.

[1914] Prompt Sentence Examples

[1915] "If a user is stressed and has set their preferences to not see certain brand ads, what kind of filtering is applied?"

[1916] "What would be the filtering strength if the user set their device to not want to see war-related news and their mood was stable?"

[1917] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1918] Step 1:

[1919] The user puts on the eyewear and launches the dedicated app on their device. The user configures the filtering settings and simultaneously launches the emotion engine. Specifically, the user selects specific keywords and categories on the app's settings screen and sets the filtering strength.

[1920] Input: User filtering settings, app launch

[1921] Output: Filtering setting data, emotion engine activation signal

[1922] Step 2:

[1923] The device uses a camera to capture visual information in real time, and the eyewear's built-in facial recognition camera and microphone capture the user's emotional data, which is then temporarily stored on the device.

[1924] Input: Visual information from camera, emotion data from face recognition camera and microphone

[1925] Output: Visual information data, emotion data

[1926] Specifically, the device's camera captures images of the street or advertisements, and the facial recognition camera analyzes the user's facial expressions to generate emotional data.

[1927] Step 3:

[1928] The device encrypts the captured visual and emotional data and sends it to a server, ensuring data security.

[1929] Input: Visual information data, emotion data

[1930] Output: Encrypted visual information data, encrypted emotion data

[1931] Specifically, the device encrypts the collected data using an encryption algorithm (e.g., AES) and issues a signal to send it to the server.

[1932] Step 4:

[1933] The server analyzes the received visual information and identifies unwanted information based on the filtering settings, while simultaneously analyzing the emotional data using an emotion engine to determine the user's current emotional state.

[1934] Input: Encrypted visual information data, encrypted emotion data

[1935] Output: Unwanted information identification data, emotional state data

[1936] Specifically, the server uses machine learning models (e.g., OpenCV, TensorFlow) to analyze images and identify unnecessary information, and the emotion engine analyzes the user's emotional state.

[1937] Step 5:

[1938] The server dynamically adjusts the filtering settings based on the emotional state data, thereby applying filtering that best suits the user's emotional state.

[1939] Input: Unwanted information identification data, emotional state data

[1940] Output: Adjusted filtering setting data

[1941] Specifically, the server dynamically changes the parameters of the filtering algorithm according to the emotional state, adjusting the strictness of the filtering, etc.

[1942] Step 6:

[1943] The identified unwanted information is masked or pixelated on the server to generate modified visual information.

[1944] Input: Adjusted filtering setting data, unnecessary information identification data

[1945] Output: Corrected visual information data

[1946] Specifically, the server applies an image processing algorithm based on the filtering settings to mask or mosaic unwanted information.

[1947] Step 7:

[1948] The server re-encrypts the modified visual information and sends it to the device, where this data is also encrypted for security reasons.

[1949] Input: Corrected visual information data

[1950] Output: Encrypted modified visual information data

[1951] Specifically, the server begins the process of encrypting the modified image data and sending it to the terminal.

[1952] Step 8:

[1953] The device decodes the corrected visual information and displays it on the eyewear, adjusting the filtering strength accordingly to prevent the user from viewing unnecessary information.

[1954] Input: Encrypted modified visual information data

[1955] Output: Corrected visual information displayed on eyewear

[1956] Specifically, the terminal performs the function of decrypting the encrypted data and displaying it on the eyewear display.

[1957] Through the above specific processing steps, the information filtering eyewear system realizes dynamic filtering based on the user's emotional state, providing a comfortable information environment.

[1958] (Application example 2)

[1959] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1960] Conventional information filtering systems are unable to dynamically adjust to the user's emotional state and always apply the same filtering settings, resulting in the problem of not providing users with sufficient information to make them comfortable.In addition, they are unable to provide optimal product recommendations or advertisements that match the customer's purchasing motivation or stress level, making it difficult to improve the quality of the shopping experience in physical stores.

[1961] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for monitoring the user's emotional state, means for transmitting the user's emotional data to the server, and means for analyzing the emotional data in the server and dynamically adjusting filtering settings based on the user's emotional state. This enables appropriate information filtering and product recommendations according to the user's emotional state, improving the shopping experience in physical stores.

[1962] "User" refers to a person who uses the system.

[1963] "Filtering settings" refers to the criteria and conditions that a user sets to remove unnecessary information from visual information.

[1964] "Visual information" refers to images and video data captured through devices such as cameras.

[1965] A "server" refers to a high-performance computer system that analyzes and processes data.

[1966] "Unnecessary information" refers to information that is determined not to need to be displayed or provided based on the user's filtering settings.

[1967] "Correction" refers to processing unnecessary information so that it is not visible to the user, using masking or mosaic processing.

[1968] "Terminal" refers to a mobile device such as a smartphone or tablet.

[1969] "Emotional state" refers to a user's psychological emotional state (e.g., stress, joy, anger, etc.).

[1970] "Emotion data" is data that indicates the user's emotional state, and includes facial expressions, voice, and the like.

[1971] "Dynamic adjustment" refers to changing settings and conditions in real time depending on the user's emotional state.

[1972] The present invention relates to a system for realizing dynamic information filtering based on user emotions. To understand and implement this system, it is necessary to incorporate the following elements and processes.

[1973] System Configuration

[1974] Hardware

[1975] Eyewear: The device is equipped with a built-in camera, display, microphone, and facial recognition camera.

[1976] Device: A handheld device such as a smartphone or tablet.

[1977] Server: A high-performance computer system for data analysis and processing.

[1978] software

[1979] Emotion Recognition and Filtering Applications

[1980] Emotion Engine

[1981] Deep learning libraries (e.g. TensorFlow, PyTorch)

[1982] Program processing flow

[1983] 1. The user puts on the eyewear and launches the dedicated app on their device. After launching the app, the user configures the filtering settings and simultaneously launches the emotion engine.

[1984] 2. The device camera captures visual information in real time, and the facial recognition camera and microphone capture the user's emotional data, which is encrypted for security.

[1985] 3. The device transmits the captured visual information and emotional data to the server, which receives the data and uses an emotion engine to analyze the user's current emotional state.

[1986] 4. The server dynamically adjusts filtering settings based on the analysis of the emotional data. For example, if the user is feeling stressed, stricter filtering will be implemented.

[1987] 5. The server analyzes the received visual information and identifies unwanted information based on the filtering settings. The identified unwanted information is masked or pixelated to generate the corrected visual information.

[1988] 6. The server sends the corrected visual information to the device. The data sent is also encrypted.

[1989] 7. The device displays the corrected visual information on the eyewear to prevent the user from seeing unnecessary information. The filtering strength is also adjusted according to the user's emotional state.

[1990] Specific examples

[1991] 1. When the user is walking around town

[1992] If a user has indicated that they do not want to see ads for a particular brand and are feeling stressed, use the following prompt:

[1993] Users are frustrated. Please tighten up your filtering and hide ads from certain brands.

[1994] 2. When the user is shopping in-store

[1995] If the user is feeling good and is looking for relaxation products, use the following prompt:

[1996] The user is relaxed. Please recommend some relaxation-related products.

[1997] These features enable users to receive optimal information filtering and product recommendations according to their emotional state, providing a more comfortable shopping experience.

[1998] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1999] Step 1:

[2000] The user puts on the eyewear and launches the dedicated app on the device. After launching the application, the user configures the filtering settings and simultaneously launches the emotion engine. The input is the user's filtering settings and start command, and the output is the start of the emotion engine and initial setting data. In this step, setting information is collected and the system is initialized.

[2001] Step 2:

[2002] The device's camera captures visual information in real time, while the facial recognition camera and microphone acquire the user's emotional data. The input is the live feed from the camera and microphone, and the output is the captured visual information and audio data. In this step, the camera and microphone are used to continuously collect the user's visual information and emotional state.

[2003] Step 3:

[2004] The device transmits the captured visual information and emotional data to the server. The input is the visual information and emotional data obtained in step 2, and the output is the data to be transmitted to the server. In this step, the collected data is encrypted and securely transmitted to the server.

[2005] Step 4:

[2006] The server analyzes the received visual information and emotional data. The input is the encrypted visual information and emotional data, and the output is the analysis result. During the analysis, the emotion engine uses a deep learning library to determine the user's emotional state in real time, while the content of the visual information is analyzed.

[2007] Step 5:

[2008] The server dynamically adjusts the filtering settings based on the analysis results of the emotional data. The inputs are the analysis results and the initial filtering settings, and the output is the adjusted filtering settings. In this step, the server changes the filtering strictness according to the user's emotional state.

[2009] Step 6:

[2010] The server analyzes the received visual information and identifies unwanted information based on the filtering settings. The input is the adjusted filtering settings and the visual information, and the output is the identified unwanted information. In this step, the filtering algorithm performs the operation of identifying unwanted information.

[2011] Step 7:

[2012] The server corrects the identified unwanted information and generates a corrected visual representation. The input is the list of unwanted information and the original visual representation, and the output is the corrected visual representation. The correction is performed using mossing or mosaic processes.

[2013] Step 8:

[2014] The server sends the corrected visual information to the terminal. The input is the corrected visual information, and the output is the data to be sent to the terminal. In this step, the corrected data is encrypted again and sent to the terminal.

[2015] Step 9:

[2016] The terminal displays the corrected visual information on the eyewear to prevent the user from viewing unnecessary information. The input is the corrected visual information, and the output is the visual information displayed on the eyewear. In this step, the user is finally provided with visual information from which unnecessary information has been removed.

[2017] At each step, data processing and calculations are performed based on the collected data, and the information necessary for the next step is generated, allowing the entire system to operate seamlessly.

[2018] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2019] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2020] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2021] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2022] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2023] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2024] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2025] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2026] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2027] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2028] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2029] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2030] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2031] 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.

[2032] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2033] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2034] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2035] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2036] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2037] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2038] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2039] The following is further disclosed regarding the above embodiment.

[2040] (Claim 1)

[2041] a means for a user to input filtering settings;

[2042] means for capturing visual information using a camera;

[2043] means for transmitting the captured visual information to a server;

[2044] means for analyzing visual information in the server and identifying unnecessary information based on filtering settings;

[2045] a means for correcting the identified unwanted information;

[2046] means for transmitting the corrected visual information to the terminal;

[2047] a means for displaying the modified visual information;

[2048] A system including:

[2049] (Claim 2)

[2050] 10. The system of claim 1, wherein the filtering settings include specific keywords, categories, or images.

[2051] (Claim 3)

[2052] 10. The system of claim 1, further comprising means for masking or mosaicking unwanted information.

[2053] "Example 1"

[2054] (Claim 1)

[2055] a means for a user to input filtering settings;

[2056] means for capturing visual information using a camera;

[2057] means for transmitting the captured visual information to a server;

[2058] means for analyzing visual information in the server and identifying unnecessary information based on filtering settings;

[2059] a means for correcting the identified unwanted information;

[2060] means for transmitting the corrected visual information to the terminal;

[2061] a means for displaying the modified visual information;

[2062] a means for the system of the present invention to use object recognition and text analysis techniques to modify the visual information based on the user's filtering settings;

[2063] a means for displaying the corrected visual information in real time on the eyewear;

[2064] A means for encrypting communications between the server and the terminal;

[2065] A system including:

[2066] (Claim 2)

[2067] 10. The system of claim 1, wherein the filtering settings include specific keywords, categories, or images.

[2068] (Claim 3)

[2069] 10. The system of claim 1, further comprising means for masking or mosaicking unwanted information.

[2070] "Application Example 1"

[2071] (Claim 1)

[2072] a means for a user to input filtering settings;

[2073] means for capturing visual information using a camera;

[2074] means for transmitting the captured visual information to a server;

[2075] means for analyzing visual information in the server and identifying unnecessary information based on filtering settings;

[2076] a means for correcting the identified unwanted information;

[2077] means for transmitting the corrected visual information to the terminal;

[2078] a means for displaying the modified visual information;

[2079] a means for focused monitoring of specific targets within the surveillance area;

[2080] A system including:

[2081] (Claim 2)

[2082] 10. The system of claim 1, wherein the filtering settings include specific keywords, categories, or images.

[2083] (Claim 3)

[2084] 10. The system of claim 1, further comprising means for masking or mosaicking unwanted information.

[2085] (Claim 4)

[2086] 2. The system according to claim 1, further comprising means for eliminating unpleasant information from visual information during monitoring work to provide a comfortable monitoring environment.

[2087] (Claim 5)

[2088] The system of claim 1, wherein the means uses a generative AI model to perform the analysis and filtering process.

[2089] (Claim 6)

[2090] The system of claim 5, further comprising means for inputting a prompt sentence to the generative AI model to set filtering conditions.

[2091] "Example 2: Combining Emotion Engines"

[2092] (Claim 1)

[2093] a means for a user to input filtering settings;

[2094] means for capturing visual information and emotional data using a camera;

[2095] means for transmitting the captured visual information and emotion data to a server;

[2096] means for analyzing the visual information and emotional data at the server, identifying unwanted information based on the filtering settings and the emotional state, and dynamically adjusting the filtering settings;

[2097] a means for correcting the identified unwanted information;

[2098] means for transmitting the corrected visual information to the terminal;

[2099] a means for displaying the modified visual information;

[2100] A system including:

[2101] (Claim 2)

[2102] 10. The system of claim 1, wherein the filtering settings include specific keywords, categories, or images, and further dynamically adjusts filtering strength based on emotional state.

[2103] (Claim 3)

[2104] 10. The system of claim 1, further comprising means for masking or mosaicking unwanted information and means for dynamically adjusting filtering settings based on emotional state.

[2105] "Application example 2 when combining emotion engines"

[2106] (Claim 1)

[2107] a means for a user to input filtering settings;

[2108] means for capturing visual information using a camera;

[2109] means for transmitting the captured visual information to a server;

[2110] means for analyzing visual information in the server and identifying unnecessary information based on filtering settings;

[2111] a means for correcting the identified unwanted information;

[2112] means for transmitting the corrected visual information to the terminal;

[2113] a means for displaying the modified visual information;

[2114] means for monitoring the emotional state of a user;

[2115] means for transmitting user emotion data to a server;

[2116] means for analyzing the emotion data at the server and dynamically adjusting filtering settings based on the user's emotional state;

[2117] A system including:

[2118] (Claim 2)

[2119] 10. The system of claim 1, wherein the filtering settings include specific keywords, categories, or images, and are further dynamically adjusted based on emotion recognition.

[2120] (Claim 3)

[2121] 10. The system of claim 1, further comprising means for masking or mosaicking unwanted information. [Explanation of symbols]

[2122] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to input filtering settings; means for capturing visual information using a camera; means for transmitting the captured visual information to a server; means for analyzing visual information in the server and identifying unnecessary information based on filtering settings; a means for correcting the identified unwanted information; means for transmitting the corrected visual information to the terminal; a means for displaying the modified visual information; A system including:

2. The system of claim 1 , wherein the filtering settings include specific keywords, categories, or images.

3. 10. The system of claim 1, further comprising means for masking or mosaicking unwanted information.

Images