system

Abstract

A system is provided.SOLUTION: A system comprising: means for converting video on an old video tape to digital data; means for transmitting the digital data to a server; means for denoising the digital data received by the server; means for enhancing the resolution of the digital data received by the server; means for color correcting the digital data received by the server; means for converting the server enhanced video data to DVD format; and means for dubbing the DVD format data to a recording medium.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] As old videotapes age, their image quality deteriorates, noise increases, and resolution and color often deteriorate. Because it is difficult to store and play back such degraded video in today's high-resolution digital formats, a method is needed to preserve these memorable videos in high quality. Furthermore, conventional methods require manual work to remove noise, improve resolution, and correct color, which is time-consuming and labor-intensive, and there are limited systems that are easily accessible to the average user. To solve this problem, a method is needed that utilizes AI technology to efficiently improve the image quality of video and easily store it on digital media. [Means for solving the problem]

[0005] The present invention provides a system that converts video footage from old videotapes into digital data, removes noise, improves resolution, and performs color correction, then dubs the high-quality video data onto digital media. Specifically, the system includes a means for converting video footage from old videotapes into digital data and a means for transmitting the digital data to a server. The server then applies noise removal (spatial filtering or frequency filtering), resolution improvement using super-resolution technology, and color correction to the received digital data. The proposed system then provides a means for converting this high-quality video data into a digital format such as DVD format and dubbing it onto a recording medium. This system allows for efficient and rapid improvement of the quality of old video footage, making it easily accessible to general users.

[0006] "Videotape" is an analog recording medium that uses magnetic tape to record and play back video and audio.

[0007] "Digital data" refers to data that has been converted from an analog signal into binary (0 and 1) format.

[0008] "Noise reduction" is the process of removing unnecessary noise from video and audio.

[0009] "Spatial filtering" is a technique for removing noise by using pixel information of an image.

[0010] "Frequency filtering" is a technique for analyzing the frequency components of a signal and removing noise in a specific frequency band.

[0011] "Resolution" is a measure of the ability to express fine detail in an image or video, and is usually expressed in pixels.

[0012] "Super-resolution technology" is an image processing technology that converts low-resolution images and videos into high-resolution images.

[0013] "Color correction" is a process that adjusts the color tone of an image or video to achieve a natural color balance.

[0014] A "server" is a computer system that provides specific services and data.

[0015] A "terminal" is a computer or device that is directly operated by a user.

[0016] A "recording medium" is a medium for physically storing data, and in this case refers to a digital disc such as a DVD.

[0017] "Dubbing" refers to the act of copying data from one medium to another. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This system utilizes AI technology to convert footage from old videotapes into high-quality images, and then performs a series of processes to finally dub the footage onto digital media such as DVDs. The system consists of three parts: the user, the terminal, and the server. The specific roles and processes of each part are explained in detail below.

[0040] 1. Digitization of videotapes

[0041] First, the user inserts the old videotape into a dedicated digitizing device. This digitizing device is connected to a terminal and is responsible for converting the analog video signal from the videotape into a digital signal. The terminal then saves this digital signal into a digital data file, such as an AVI or MP4 format, and sends it to a server. Here, the terminal uses a video capture device and digital conversion equipment. Through this digitizing process, the contents of the old videotape are newly saved as digital data.

[0042] 2. Pretreatment

[0043] The server analyzes the digital data sent from the terminal and performs preprocessing. This preprocessing includes noise reduction, resolution enhancement, and color correction. First, the server applies a noise reduction algorithm to remove unwanted noise from the digital data. This noise reduction uses spatial and frequency filtering techniques. The server then uses super-resolution technology to improve the resolution of the digital data, which results in clearer image details and higher-quality images. The server then applies a color correction filter to adjust the color balance of the image. This series of preprocessing steps significantly improves the quality of the base image data.

[0044] 3. High image quality using AI

[0045] After preprocessing is complete, the server uses AI (deep learning models) to enhance the image quality of the video. Specifically, the server analyzes each frame of the video and processes it to reproduce fine details. This is done using technology that improves the clarity of each frame. AI-based image enhancement significantly improves the beauty and quality of the details of the video. The server repeats this process multiple times to generate video data of optimal quality.

[0046] 4. Digital conversion and dubbing

[0047] Once the high-quality video data is generated, the server converts it into a digital format, such as DVD format. Specifically, the server uses MPEG-2 encoding to convert the video data into a DVD-format ISO image file. This ISO image file can then be burned directly onto a DVD. This data is then sent from the server to the device.

[0048] The device connects the received ISO image file to a DVD burner and prompts the user to insert a DVD media, after which the device copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[0049] 5. Delivery to User

[0050] Finally, the user receives the completed DVD, which can be played back at home or in any other playback environment to enjoy the high-definition images.

[0051] Specific examples

[0052] For example, consider a user who wants to digitize a home videotape from the 1990s. The tape contains footage of a young child's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. The server then uses AI technology to further enhance the image quality and finally encodes it into DVD format. This data is then copied onto a DVD, which the user can then receive and play, allowing them to enjoy clear, vibrant images.

[0053] In this way, this system can revive images from old videotapes as modern, high-quality digital images and provide them in a format that users can easily use.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] A user inserts an old videotape into a dedicated digitizing device, and then operates the digitizing device to start playing the videotape.

[0057] Step 2:

[0058] The device captures the analog video signal from the videotape and converts it to a digital signal. The device uses a video capture device to save the video signal in a digital data format such as AVI or MP4.

[0059] Step 3:

[0060] The terminal transmits the digitized video data to the server, where it uses an appropriate compression format to optimize the data size.

[0061] Step 4:

[0062] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information), which is then used to evaluate the quality of the data.

[0063] Step 5:

[0064] The server applies noise reduction processing, specifically using noise reduction algorithms such as spatial filtering and frequency filtering to reduce noise in the video.

[0065] Step 6:

[0066] The server performs the resolution enhancement process, using super-resolution techniques based on deep learning models (e.g., SRGAN) to improve the image resolution. This process focuses on reproducing fine details.

[0067] Step 7:

[0068] The server performs color correction processing, adjusting the color balance of the video using automatic white balance adjustment and color correction filters. This process restores natural color tones.

[0069] Step 8:

[0070] The server then uses the pre-processed data to perform AI-based image enhancement, applying deep learning models to each frame of the video to improve detail and clarity. This process is repeated multiple times.

[0071] Step 9:

[0072] The server converts the high-quality video data into a DVD-format ISO image file, compressing and formatting the data using MPEG-2 encoding.

[0073] Step 10:

[0074] The server sends the generated ISO image file to the device, which receives the data and checks for errors.

[0075] Step 11:

[0076] The device prompts the user to insert a DVD, and the user inserts the DVD. The device uses a DVD writer to burn the ISO image file to a DVD. This process includes selecting the appropriate writing speed and checking for errors.

[0077] Step 12:

[0078] The user receives the completed DVD and can play it to check and enjoy the high-definition images.

[0079] Example 1

[0080] 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."

[0081] The conventional method of digitizing and preserving old videotape footage has the problem of degrading the quality of the video. Another issue is the time and labor required to perform individual processes such as noise reduction, resolution improvement, and color correction. Furthermore, there are limited means of achieving high image quality, and the final process of converting and dubbing the video to digital media is complicated.

[0082] 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.

[0083] In this invention, the server includes means for removing noise from the digital data, means for improving the resolution of the digital data, means for performing color correction on the digital data, and means for enhancing the image quality of the digital data using deep learning technology, thereby converting images from old videotapes into a high-quality digital format, allowing users to easily enjoy high-quality images.

[0084] Key Word Definitions

[0085] "Old videotapes" refers to magnetic tapes on which video is recorded in analog format, such as VHS and Betamax.

[0086] "Digital data" refers to data that has been converted from an analog signal into a digital signal, specifically video files in AVI or MP4 format.

[0087] "Server" refers to a computer system that receives, processes, and transmits data over a network.

[0088] "Noise reduction" is a process for reducing unnecessary noise from video and audio data, and specifically, spatial filtering and frequency filtering techniques are used.

[0089] "Resolution enhancement" is a process used to increase the detail of an image or video, particularly using super-resolution technology.

[0090] "Color correction" refers to the process of adjusting the color balance of an image, and is carried out to optimize the color and brightness of the image.

[0091] "Deep learning technology" is a technology that uses deep learning algorithms to analyze data and recognize patterns, and in this invention it is used to improve the image quality of videos.

[0092] The "DVD format" is a standard format for recording digital video data, and MPEG-2 encoding is commonly used.

[0093] An "ISO image file" is a digital file that contains the contents of an optical disc and is used to burn it onto a DVD or CD.

[0094] "Recording medium" refers to a physical medium for storing digital data, and specifically includes DVD discs and Blu-ray discs.

[0095] "Dubbing" refers to the process of writing digital data onto a recording medium.

[0096] MODE FOR CARRYING OUT THE INVENTION

[0097] This invention is a system that uses AI technology to convert old videotape footage into high-quality images and then dub them onto digital media. The system configuration and the specific roles of each piece of hardware and software are explained below.

[0098] (System configuration)

[0099] The system consists of three main parts: users, terminals, and servers.

[0100] 1. Digitization of videotapes

[0101] Users insert their old video tapes into a specialized digitizing device, which converts the analog video signal from the video tape into a digital signal. A typical example of a digitizing device used at this stage is a common video capture device.

[0102] The terminal activates the digitizing device, converts the analog video signal from the videotape into a digital signal, saves the converted digital signal into a digital data file in AVI or MP4 format, and transmits this digital data to the server.

[0103] 2. Pretreatment

[0104] The server analyzes and pre-processes the digital data received from the device, including noise reduction, resolution enhancement, and color correction.

[0105] Specifically, the server first applies a noise reduction algorithm, which uses spatial filtering techniques (such as OpenCV's GaussianBlur and MedianBlur) and frequency filtering techniques.

[0106] The server then uses super-resolution techniques to improve the resolution of the digital data, using techniques such as TensorFlow's ESRGAN.

[0107] Finally, the server applies a color correction filter to balance the color of the video. Specifically, it uses the Python PIL library to perform color correction.

[0108] 3. High image quality using AI

[0109] After preprocessing is complete, the server uses a deep learning model to enhance the image quality of the digital data. Specifically, the server uses deep learning technology (e.g., PyTorch's SRGAN model) to reproduce the details of the image and improve the overall image quality.

[0110] The server analyzes each frame of the video to enhance its clarity, and this process is repeated multiple times to produce video data of optimal quality.

[0111] 4. Digital conversion and dubbing

[0112] Once the high-quality video data is generated, the server converts it into a digital format, such as DVD format. Specifically, the server uses MPEG-2 encoding technology (e.g., FFmpeg) to convert the video data into a DVD-format ISO image file, which is then sent to the device.

[0113] The device connects the received ISO image file to a DVD writer (e.g., a general optical disc recording device) and prompts the user to insert a DVD media. The device then copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[0114] 5. Delivery to User

[0115] The user finally receives the finished DVD, which can be played at home or in any other playback environment, allowing them to enjoy the high-definition images.

[0116] Specific examples

[0117] For example, say a user wants to digitize a home videotape from the 1990s, which contains footage of young children's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data (AVI file). The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. The server then uses AI technology to further enhance the image quality and finally encodes it into DVD format. This data is then copied onto a DVD, which the user can then receive and play, allowing them to enjoy clear, vibrant images.

[0118] Prompt Sentence Examples

[0119] "Please explain the system that digitizes home videotapes, improves picture quality, and dubs them onto DVDs."

[0120] "Please tell me more about the process of converting videotape footage into digital data, enhancing the image quality with AI, and then dubbing it onto a DVD."

[0121] In this way, this system can provide high-quality digital images from old videotapes in a format that is easy for users to use.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Program processing steps

[0124] Step 1:

[0125] A user inserts an old videotape into a dedicated digitizing device. The input is the analog video signal from the videotape, which the digitizing device receives. The output is an analog signal sent from the digitizing device to a terminal.

[0126] Step 2:

[0127] The terminal activates a digitizing device that converts the analog video signal from the videotape into a digital signal. Specifically, a digital capture device (e.g., a video capture card) is used to receive the analog signal and output it as a digital signal. This digital signal is then saved as a digital data file in AVI or MP4 format.

[0128] Step 3:

[0129] The terminal sends the stored digital data to the server. The input is digital data in AVI or MP4 format, which is sent to the server via the terminal. The output is digital data sent to the server. This transmission uses the File Transfer Protocol (FTP) or HTTP.

[0130] Step 4:

[0131] The server analyzes the received digital data and performs noise reduction. The input is the digital data sent from the device, and the output is the data with noise removed. Specifically, the server uses algorithms such as GaussianBlur and MedianBlur from OpenCV to reduce unnecessary noise.

[0132] Step 5:

[0133] The server increases the resolution of the digital data. The input is the denoised digital data, and the output is the data with increased resolution. Super-resolution techniques such as TensorFlow's ESRGAN are used to increase the resolution of the video data.

[0134] Step 6:

[0135] The server performs color correction. The input is the digital data after resolution enhancement, and the output is the color-corrected data. The Python PIL library is used to adjust the color balance of the video.

[0136] Step 7:

[0137] The server uses deep learning technology to improve the image quality of digital data. The input is preprocessed digital data, and the output is image-enhanced data. Each frame is analyzed and improved using a PyTorch SRGAN model.

[0138] Step 8:

[0139] The server converts the high-definition video data into DVD format. The input is the digital data that has been converted to high definition, and the output is a DVD-format ISO image file. MPEG-2 encoding is performed using FFmpeg, and the digital data is converted into DVD format.

[0140] Step 9:

[0141] The server sends the generated ISO image file to the terminal. The input is the ISO image file sent from the server to the terminal. The output is the ISO image file received by the terminal.

[0142] Step 10:

[0143] After the terminal receives the ISO image file, it connects to the DVD writer and prompts the user to insert a DVD media. The input is the ISO image file, and it is connected to the DVD writer. When the user inserts the DVD, it proceeds to the next step.

[0144] Step 11:

[0145] The device will burn the ISO image file to a DVD. The input is the ISO image file inserted into the DVD burner, and the output is the finished DVD. This process includes proper burn speed optimization and error checking.

[0146] Step 12:

[0147] The process is complete when the user receives the finished DVD, allowing them to enjoy the high-definition video at home or in any other playback environment.

[0148] (Application example 1)

[0149] 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."

[0150] The deterioration of old video recording media (such as videotapes) leads to a decline in image quality, which is a major obstacle to the viewing and use of valuable video assets. Furthermore, the process of digitizing these old videos and converting them to high-quality images requires specialized knowledge and expensive equipment, making it difficult for average users to use. Another problem is the limited means of viewing digitized video in high quality. There is a need for a system that can resolve this situation and allow users to easily enjoy high-quality video.

[0151] 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.

[0152] In this invention, the server includes means for converting video from an old video recording medium into digital data, means for transmitting the digital data to a data storage device, means for removing noise from the digital data received by the data storage device, means for improving the resolution of the digital data received by the data storage device, means for color correcting the digital data received by the data storage device, means for converting the high-definition video data into a digital disc format by the data storage device, means for writing the digital disc format data to a physical medium, means for processing and streaming video owned by a user on the cloud, and means for enabling a user to view the high-definition video on a terminal. Thus, by digitizing video from an old video recording medium to high definition and processing it on the cloud, users can more easily view and use high-definition video assets.

[0153] "Video recording medium" means a physical medium for storing video in analog or digital form.

[0154] "Digital data" is data that has been converted from analog information into a digital format that can be processed by a computer.

[0155] A "data storage device" is a device that stores received data and processes or distributes it as necessary.

[0156] "Noise reduction" is a process for reducing unwanted signals and interference in digital data and improving the quality of the data.

[0157] "Resolution enhancement" is a process that increases the number of pixels in digital data to express details more clearly.

[0158] "Color correction" is a process that adjusts the color balance of an image to reproduce natural and beautiful colors.

[0159] "Digital disc format" refers to a digital format for recording on optical discs such as DVDs and Blu-ray discs.

[0160] A "physical medium" is a tangible medium for recording and storing digital data.

[0161] "Processing on the cloud" means processing data on a remote server accessible via the Internet.

[0162] "Streaming" is a distribution method that distributes digital data in real time, allowing users to view it continuously.

[0163] A "terminal" is a device such as a computer, smartphone, or tablet that is directly operated by a user.

[0164] This invention relates to a system that converts video stored on old video recording media into high-quality digital data, processes it on the cloud, and distributes it through streaming. This system is mainly composed of three parts: the user, the terminal, and the data storage device. The specific roles and processes of each part are explained in detail below.

[0165] First, a user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device. This digitizing device is connected to a terminal and is responsible for converting the analog video signal from the video recording medium into a digital signal. The terminal then stores this digital signal as a digital data file, usually in a common format such as AVI or MP4. This stored digital data is then sent by the terminal to a data storage device.

[0166] The data storage device analyzes the received digital data and first performs preprocessing. This preprocessing includes noise reduction, resolution enhancement, and color correction. Spatial and frequency filtering techniques are used for noise reduction. The data storage device then uses super-resolution technology to improve the resolution of the digital data. This process sharpens image details and significantly improves overall image quality. The data storage device then applies color correction filters to optimize the color balance of the image.

[0167] After preprocessing is complete, the data storage device uses AI (e.g., a generative AI model) to enhance the image quality. Specifically, each frame is analyzed in detail and advanced processing is performed to reproduce the details. AI-based image enhancement further improves the beauty and quality of the image. This process is repeated multiple times to produce optimal quality image data.

[0168] The high-quality video data is converted into a file in digital disc format (e.g., DVD format) by a data storage device. Specifically, the video data is converted into an ISO image file in digital disc format using MPEG-2 encoding. This data can be written directly to physical media. This data is then sent to a terminal for further writing to physical media (e.g., DVD).

[0169] The device connects to a device that writes the received ISO image file to physical media and prompts the user to insert the physical media. The device then writes the ISO image file to the physical media, providing high-quality video data on the physical media. This process includes appropriate optimization for writing speed and error checking.

[0170] In addition, by taking advantage of the fact that data is stored in the cloud, users can view high-definition video anytime, anywhere. A streaming function for this purpose is also built into the data storage device. Users can view video stored in the cloud in real time using a dedicated application (for example, an application installed on a smartphone or HMD).

[0171] As a concrete example, consider a user who wants to digitize a home videotape from the 1990s. This tape contains childhood family memories. The user first inserts the tape into a digitizer and converts it into digital data via a terminal. The data storage device receives the digital data, performs noise reduction, resolution enhancement, color correction, and further enhances the image quality using AI technology. Finally, the data storage device converts the enhanced video data into a digital disc format, and the terminal writes it to physical media. This physical media is then provided to the user, who can enjoy the enhanced video at home or in other playback environments. Furthermore, the high-quality video stored in the cloud can be viewed anywhere via a smartphone or HMD.

[0172] An example prompt is, "I want to improve the quality of a 1980s home videotape. I want to remove noise, improve resolution, and correct color frame by frame, and then finally stream it."

[0173] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0174] Step 1:

[0175] The user inserts an old video recording into a dedicated digitizing device.

[0176] Specific operation: A user inserts a video recording medium (e.g., a videotape) into the digitizing device and operates the device.

[0177] Input: Video recording medium

[0178] Output: Analog video signal

[0179] Step 2:

[0180] The device converts the analog video signal into a digital signal and stores it as a digital data file.

[0181] Specific operation: The terminal uses a video capture device to convert the analog video signal output from the digitizing device into a digital signal and saves it as an AVI or MP4 format file.

[0182] Input: Analog video signal

[0183] Output: Digital data file (AVI, MP4)

[0184] Step 3:

[0185] The terminal transmits the stored digital data file to the data storage device.

[0186] Specific operation: The terminal uploads the digital data file to the data storage device via the network.

[0187] Input: Digital data file

[0188] Output: Data sent to the data storage device

[0189] Step 4:

[0190] The data storage device removes noise from the received digital data.

[0191] Specific operation: The data storage device applies spatial filtering and frequency filtering techniques to the received digital data to reduce noise.

[0192] Input: Digital data file

[0193] Output: Noise-removed digital data

[0194] Step 5:

[0195] Data storage devices increase the resolution of digital data.

[0196] Specific operation: The data storage device uses super-resolution technology to improve the resolution of the received digital data, making the details of the image clearer.

[0197] Input: Noise-removed digital data

[0198] Output: High-resolution digital data

[0199] Step 6:

[0200] The data storage device performs color correction on the digital data.

[0201] Specific operation: The data storage device applies a color correction filter to optimize the color balance of the image.

[0202] Input: High-resolution digital data

[0203] Output: Color-corrected digital data

[0204] Step 7:

[0205] The data storage device uses AI (generative AI model) to process the image to improve its quality.

[0206] How it works: The data storage device uses a generative AI model to analyze each frame in detail and process it to recreate the details, further improving the beauty and quality of the image.

[0207] Input: Color-corrected digital data

[0208] Output: High-quality digital data

[0209] Step 8:

[0210] The data storage device converts the high-definition digital data into a digital disc format (e.g., DVD format).

[0211] Specific operation: The data storage device converts high-definition digital data into an ISO image file in digital disc format using MPEG-2 encoding.

[0212] Input: High-resolution digital data

[0213] Output: ISO image file

[0214] Step 9:

[0215] The device writes the ISO image file to physical media.

[0216] Specific operation: The device prompts the user to insert physical media (e.g., a DVD disc) and then writes the ISO image file to the physical media. This process includes proper write speed optimization and error checking.

[0217] Input: ISO image file

[0218] Output: Data written to physical media

[0219] Step 10:

[0220] The data storage device stores the high-definition data on the cloud, allowing users to view it via streaming.

[0221] Specific operation: The data storage device stores the high-definition data in the cloud and provides it to users through streaming distribution functions. Users can watch it in real time using a dedicated application.

[0222] Input: High-resolution digital data

[0223] Output: Streaming service

[0224] Example prompt: "I want to enhance the quality of a 1980s home videotape by removing noise, enhancing resolution, and correcting color frame by frame, and then finally streaming it."

[0225] 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.

[0226] This invention relates to a system that utilizes AI technology and an emotion engine to convert footage from old videotapes into high-quality images, and then performs a series of processes to ultimately dub the footage onto digital media such as DVDs. This system consists of four parts: the user, the terminal, the server, and the emotion engine. The specific roles and processes of each part are explained below in detail.

[0227] 1. Digitization of videotapes

[0228] First, the user inserts an old videotape into a dedicated digitizing device. The user operates the digitizing device and starts playing the videotape. The device captures the analog video signal from the videotape and converts it into a digital signal. The device uses the video capture device to save the video signal in a digital data format such as AVI or MP4 and transmits it to the server. Through this digitizing process, the contents of the old videotape are newly saved as digital data.

[0229] 2. Pretreatment

[0230] The server analyzes the digital data sent from the device and extracts basic video characteristics (resolution, frame rate, color information, etc.). This analysis is used to evaluate the quality of the data. The server then applies a noise reduction algorithm to remove unwanted noise from the digital data. This noise reduction uses spatial filtering and frequency filtering techniques. The server then uses super-resolution technology to improve the resolution of the digital data, which sharpens the image details and produces higher-quality images. The server then applies a color correction filter to adjust the color balance of the image. This series of pre-processing steps significantly improves the quality of the base video data.

[0231] 3. High image quality using AI

[0232] After preprocessing is complete, the server uses AI (deep learning models) to enhance the image quality of the video. Specifically, the server analyzes each frame of the video and processes it to reproduce fine details. This is done using technology that improves the clarity of each frame. AI-based image enhancement significantly improves the beauty and quality of the details of the video. The server repeats this process multiple times to generate video data of optimal quality.

[0233] 4. Video editing using emotion engine

[0234] The server uses an emotion engine to recognize the user's emotions. The emotion engine uses sensor devices such as cameras and microphones to analyze emotions from the user's facial expressions and voice. Based on the user's emotions, the server automatically adjusts video editing parameters. Specifically, if the user expresses joy, the server will make the video's color correction more vivid and add positive effects. On the other hand, if the user expresses sadness, the server will adjust the video's tone to a more subdued color tone.

[0235] 5. Digital conversion and dubbing

[0236] Once the high-quality, emotion-edited video data is generated, the server converts it into a DVD-format ISO image file. Specifically, the server compresses and formats the data using MPEG-2 encoding. This ISO image file can then be written directly to a DVD. This data is then sent from the server to the device.

[0237] The device connects the received ISO image file to a DVD burner and prompts the user to insert a DVD media. After the user inserts the DVD media, the device copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[0238] 6. Delivery to User

[0239] Finally, the user receives the completed DVD, which can be played back at home or in any other playback environment to enjoy the high-definition images.

[0240] Specific examples

[0241] For example, consider a user who wants to digitize a home videotape from the 1990s. The tape contains footage of a children's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. Next, the server uses AI technology to further enhance the image quality and uses an emotion engine to recognize the user's emotions, such as joy or nostalgia, and adjust the image's color tone and effects accordingly. Finally, the server encodes the video data into DVD format and copies the data to a DVD. The user receives the DVD, plays it, and enjoys the crisp, emotionally tailored video.

[0242] In this way, this system can revive old videotape footage as modern, high-definition digital video, and by editing the video according to the user's emotions, it can provide a more moving viewing experience.

[0243] The processing flow will be explained below.

[0244] Step 1:

[0245] A user inserts an old videotape into a dedicated digitizing device, and then operates the digitizing device to start playing the videotape.

[0246] Step 2:

[0247] The device captures the analog video signal from the videotape and converts it to a digital signal. The device uses a video capture device to save the video signal in a digital data format such as AVI or MP4.

[0248] Step 3:

[0249] The terminal transmits the digitized video data to the server, where it uses an appropriate compression format to optimize the data size.

[0250] Step 4:

[0251] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information), which is then used to evaluate the quality of the data.

[0252] Step 5:

[0253] The server applies noise reduction processing, specifically using noise reduction algorithms such as spatial filtering and frequency filtering to reduce noise in the video.

[0254] Step 6:

[0255] The server performs the resolution enhancement process, using super-resolution techniques based on deep learning models (e.g., SRGAN) to improve the image resolution. This process focuses on reproducing fine details.

[0256] Step 7:

[0257] The server performs color correction processing, adjusting the color balance of the video using automatic white balance adjustment and color correction filters. This process restores natural color tones.

[0258] Step 8:

[0259] The server then uses the pre-processed data to perform AI-based image enhancement, applying deep learning models to each frame of the video to improve detail and clarity. This process is repeated multiple times.

[0260] Step 9:

[0261] The server uses an emotion engine to recognize the user's emotions. The emotion engine captures and analyzes the user's facial expressions and voice through sensor devices such as the device's camera and microphone.

[0262] Step 10:

[0263] The emotion engine analyzes the user's emotions (e.g., joy or sadness) and sends the information to the server, which then automatically adjusts the video editing parameters based on this information.

[0264] Step 11:

[0265] The server applies color correction and effects to the video based on the user's emotions. Specifically, if the user expresses joy, the video will be adjusted to a clearer, brighter tone and a more positive effect will be added. If the user expresses sadness, the video will be adjusted to a more muted tone.

[0266] Step 12:

[0267] The server converts the high-quality, emotion-edited video data into a DVD-format ISO image file. Specifically, the server compresses and formats the data using MPEG-2 encoding.

[0268] Step 13:

[0269] The server sends the generated ISO image file to the device, which receives the data and checks for errors.

[0270] Step 14:

[0271] The device prompts the user to insert a DVD, and the user inserts the DVD. The device uses a DVD writer to burn the ISO image file to a DVD. This process includes selecting the appropriate writing speed and checking for errors.

[0272] Step 15:

[0273] The user receives the completed DVD and can play it to check and enjoy the high-definition, emotionally edited footage.

[0274] Example 2

[0275] 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."

[0276] Old video recording media, especially videotapes, often experience deterioration over time, leading to a deterioration in image quality. Furthermore, when these videos are converted to modern digital media, they can contain noise and are often stored at low resolution. Furthermore, with conventional technologies, the process of improving the image quality and editing the video is often performed manually, resulting in inefficiencies. The present invention aims to solve these problems and provide a system that also enables video editing based on the user's emotions.

[0277] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0278] In this invention, the server includes means for converting video from an old video recording medium into digital data, means for transmitting the digital data to a computing device, means for removing noise from the digital data received by the computing device, means for improving the resolution of the digital data received by the computing device, means for performing color correction on the digital data received by the computing device, means for converting the high-quality video data into a recording medium format by the computing device, means for dubbing the data in the recording medium format onto a recording medium, means for recognizing a user's emotions and automatically adjusting video editing parameters based on the emotions, and means for performing an iterative process using AI to improve the quality of the generated video data. This makes it possible to convert video from old video recording media into digital media with high quality and in a manner that takes user emotions into consideration.

[0279] "Old video recording media" refers to physical media used to record video in the past, including videotapes and laser discs.

[0280] "Digital data" is data that has been converted from analog signals into a digital format, and is usually saved in a common video format such as AVI or MP4.

[0281] "Computing device" refers to a computer or server used to process digital data, and is equipment that performs advanced calculations and data analysis.

[0282] "Noise reduction" is a process that reduces unnecessary noise contained in video data, and uses techniques such as spatial filtering and frequency filtering.

[0283] "Resolution enhancement" is the process of converting low-resolution images into high-resolution images, and is carried out using super-resolution technology and artificial intelligence (AI).

[0284] "Color correction" is a process that adjusts the color balance of digital video data to make the overall color tone of the video appropriate.

[0285] A "recording medium format" is the file format used to store digital data on a particular recording medium (e.g., DVD or Blu-ray).

[0286] A "recording medium" is a medium for physically storing digital data, and includes, for example, DVDs and Blu-ray discs.

[0287] "User emotion" refers to the psychological state of the user as it is inferred from the facial expressions and voice of the user watching the video, and is analyzed using emotion recognition technology.

[0288] "Video editing parameters" refer to the setting values ​​and effects applied when editing video, including color correction and the type and strength of the effect.

[0289] "Iterative processing" is a technique in which the same process is repeated multiple times in order to improve the quality of video data, and is particularly used to improve image quality using AI.

[0290] This invention relates to a system that utilizes AI technology and an emotion engine to convert video from old video recording media into high-quality video, and then performs a series of processes to finally dub the video onto digital media. This system consists of four parts: the user, the terminal, the server, and the emotion engine. The specific roles and processes of each part are explained below in detail.

[0291] First, a user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device. Next, the user presses the play button on the digitizing device's operation panel to start playing the videotape. The terminal uses a video capture device (e.g., a general video capture device) to convert the analog video signal from the videotape into a digital signal. The converted digital signal is stored on the hard disk in a digital data format such as AVI or MP4. The terminal then transmits this digital data to a server via File Transfer Protocol (FTP) or a cloud storage service.

[0292] The server analyzes the received digital data and extracts basic video characteristics (resolution, frame rate, color information, etc.). This analysis is performed using libraries such as the FFmpeg library. The server then applies a noise reduction algorithm to remove unwanted noise from the digital data. For example, it uses OpenCV to apply Gaussian and Median filters. It also uses super-resolution techniques (such as the ESRGAN model) to improve the resolution of the digital data. The server then uses a color correction filter to adjust the hue, saturation, and lightness (HSL) to balance the color of the image.

[0293] After pre-processing, the server uses AI technology (deep learning models, such as SRGAN) to analyze each frame of the video and reproduce the details. This high-quality image processing is repeated multiple times to generate video data of optimal quality.

[0294] The server uses an emotion engine to recognize the user's emotions through sensor devices (cameras and microphones). For example, it uses the OpenFace library to perform facial expression analysis. It analyzes emotions from the user's facial and voice data and automatically adjusts video editing parameters based on those emotions. For example, if the user expresses joy, it will make the video's color correction more vivid and add positive effects.

[0295] After the high-quality, emotion-based video data is generated, the server converts it into a recording medium format, an ISO image file. This conversion uses MPEG-2 encoding. The server then sends the ISO image file to the device via FTP or a cloud storage service. The device receives the ISO image file and prompts the user to insert a DVD. When the user inserts the DVD, the device writes the ISO image file to a DVD, optimizing for proper writing speed and performing error checking.

[0296] Finally, the user receives the completed DVD and can play it at home or in any other playback environment to enjoy the high-definition images.

[0297] As a concrete example, consider a scenario in which a video of a young child's sports day recorded on a home videotape from the 1990s is digitized and converted to high-quality video. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives this digital data and performs noise reduction, resolution enhancement, and color correction. Next, the server uses AI technology to further enhance the video quality and uses an emotion engine to recognize the user's emotions and adjust the video's color tone and effects. Finally, the server encodes the video data into DVD format and copies the data to a DVD. The user receives the DVD, plays it, and enjoys the clear, emotionally edited video.

[0298] An example of a prompt for a generative AI model is shown below.

[0299] "Convert footage of young children's sports day recorded on a home videotape from the 1990s into high-resolution footage and edit it to suit the user's emotions."

[0300] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0301] Step 1:

[0302] A user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device and presses the play button to start playing the tape. The inputs are the videotape and the digitizing device, and the output is an analog video signal. In operation, the user operates the device to play the videotape.

[0303] Step 2:

[0304] A device uses a video capture device to capture analog video signals and convert them to digital signals. The input is an analog video signal, and the output is digital video data (e.g., an AVI or MP4 file). In operation, the capture device receives the signal, converts it to digital data, and stores it on the hard disk.

[0305] Step 3:

[0306] The device sends the stored digital video data to the server. The input is the digital video file, and the output is the file transferred to the server. In operation, the device sends the data using the FTP protocol or a cloud storage service.

[0307] Step 4:

[0308] The server analyzes the received digital data and extracts basic video characteristics (e.g., resolution, frame rate, color information). The input is a digital video file, and the output is video characteristic data. In operation, the FFmpeg library is used to obtain video characteristic information.

[0309] Step 5:

[0310] The server applies a noise reduction algorithm to reduce unnecessary noise from the digital data. The input is image characteristic data and digital image data, and the output is noise-reduced digital image data. In operation, OpenCV is used to apply Gaussian and Median filters.

[0311] Step 6:

[0312] The server uses super-resolution technology to improve the resolution of digital data. The input is digital video data with reduced noise, and the output is digital video data with improved resolution. In operation, the ESRGAN model is applied to convert low-resolution video to high-resolution.

[0313] Step 7:

[0314] The server applies a color correction filter to balance the color of digital video. The input is high-resolution digital video data, and the output is color-corrected digital video data. The operation involves adjusting the hue, saturation, and lightness (HSL) values.

[0315] Step 8:

[0316] The server uses AI technology to analyze each frame of video and perform image quality enhancement processing. The input is color-corrected digital video data, and the output is image quality-enhanced digital video data. It operates by repeatedly analyzing each frame and reproducing details using an SRGAN model.

[0317] Step 9:

[0318] The server uses an emotion engine to recognize the user's emotions through sensor devices. The input is the user's facial expression and voice data, and the output is analyzed emotional data. Facial expression analysis is performed using the OpenFace library.

[0319] Step 10:

[0320] The server automatically adjusts video editing parameters based on the user's emotional data. The input is emotional data and high-quality digital video data, and the output is video data edited based on the emotion. The operation involves adjusting color tones and adding effects.

[0321] Step 11:

[0322] The server converts the emotion-edited video data into an ISO image file in a recording medium format. The input is emotion-edited video data, and the output is an ISO image file. In operation, the ISO file is generated using MPEG-2 encoding.

[0323] Step 12:

[0324] The server sends the generated ISO image file to the terminal. The input is the ISO image file, and the output is the ISO image file transferred to the terminal. The operation is to send data using the FTP protocol or cloud storage service.

[0325] Step 13:

[0326] The terminal receives the ISO image file and displays instructions to the user to insert the DVD media. The input is the ISO image file and the output is the display instructions to the user. The operation is to display the instructions through a GUI.

[0327] Step 14:

[0328] The user inserts a DVD media into the device, and the action is to insert the appropriate media to burn the ISO image file to a DVD.

[0329] Step 15:

[0330] The terminal writes the ISO image file to the DVD media inserted by the user. The input is the ISO image file and the DVD media, and the output is the completed DVD. The operation proceeds while optimizing the writing speed and checking for errors.

[0331] Step 16:

[0332] The user receives the completed DVD and can play it at home or in another playback environment to enjoy the high-definition video. The operation involves receiving the completed DVD and watching it on a playback device.

[0333] Example prompts for generative AI models

[0334] "Convert footage of young children's sports day recorded on a home videotape from the 1990s into high-resolution footage and edit it to suit the user's emotions."

[0335] (Application example 2)

[0336] 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."

[0337] Videos stored on old recording media generally have low image quality and a lot of noise, making the viewing experience inferior to modern high-definition video. Furthermore, there is no system that can digitize and store these videos, as well as edit them emotionally and stream them. Therefore, there is a need to revive old videos using modern technology and provide a more emotional viewing experience.

[0338] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0339] In this invention, the server includes a means for adjusting the effects of the high-definition video data based on emotion analysis, a means for converting the data into a digital medium format using a connection device, and a means for writing the converted data to a recording medium. This makes it possible to digitize and improve the image quality of video data stored on old recording media, edit the data based on emotions, and then stream the data.

[0340] "Old recording media" refers to videotapes and other analog storage media used to record video data in the past.

[0341] "Digital data" refers to video data that has been converted into a format that can be processed by a computer.

[0342] A "server" is a central computer that provides services to other computers and devices over a network.

[0343] "Noise reduction" is a process for removing unnecessary noise components from digital data.

[0344] "Resolution enhancement" is a technique for converting video data into a higher resolution in order to improve the image quality of the data.

[0345] "Color correction" is a process of adjusting the color tone of video data to create a more natural and visually pleasing image.

[0346] "Emotion analysis" is a technology that analyzes the user's emotions and adjusts the video effects and color tone based on the results.

[0347] A "digital media format" is a format in which digital data can be converted into a particular format and stored on a suitable recording medium.

[0348] "Recording media" refers to media such as DVDs and Blu-ray discs for storing digital data.

[0349] "Streaming distribution" is a technology that transfers data in real time over a network and plays it back.

[0350] This system converts video from old recording media into digital data, edits it based on the user's preferences, and delivers high-quality video via streaming. This section explains the basic components of this system and their roles.

[0351] 1. Digitizing Devices and User Operation

[0352] A user inserts an old recording medium (e.g., a videotape) into a dedicated digitizing device. The digitizing device uses a video capture device to convert the recording medium's analog video signal into a digital signal. This digital data is saved in a format such as AVI or MP4 and sent to a server via the terminal.

[0353] 2. Data Preprocessing

[0354] The server first analyzes the basic characteristics of the received digital data and extracts information such as resolution, frame rate, and color. It then uses specialized software (e.g., OpenCV) to perform preprocessing such as noise reduction, resolution enhancement, and color correction. Spatial filtering and frequency filtering are applied without omission for noise reduction.

[0355] 3. High image quality using AI

[0356] After preprocessing, the server applies a generative AI model (e.g., using TensorFlow or PyTorch) to the data to enhance image quality. Using deep learning models, it analyzes each frame of the video and performs operations such as enhancing details. This significantly improves the quality and detail of the image.

[0357] 4. Editing with Emotion Engine

[0358] The server uses an emotion engine (e.g., DeepFace) to analyze the user's emotions. This involves collecting and analyzing facial expressions and audio via a camera and microphone. The color tone and effects of the video are automatically adjusted according to the user's emotions. For example, if the user expresses happiness, the video will be adjusted to be more vibrant, and conversely, if the user expresses sadness, the colors will be muted.

[0359] 5. Digital media conversion and dubbing of video

[0360] The high-quality, emotion-edited video data is then converted by the server into a digital media format (e.g., a DVD-format ISO image file). This process uses MPEG-2 encoding to ensure optimal quality. The converted ISO image file is then written to a recording medium (e.g., a DVD) via the terminal.

[0361] 6. Streaming

[0362] Finally, the edited video data is streamed through a distribution server, and users can share the link to enjoy the high-quality, emotionally enriched video with family and friends.

[0363] Specific examples

[0364] For example, if a user digitizes a videotape of a child's birthday party and edits it based on the emotion of "joy," the footage will have a vibrant, positive effect. This footage can then be shared with family and friends through a streaming service, breathing new life into old recordings and providing a modern viewing experience.

[0365] Example prompt: "Based on your feelings of joy, edit a high-quality video of your child's birthday party and share it via streaming with your family."

[0366] This system brings old footage back to life vividly using modern technology, providing a special viewing experience tailored to the user's emotions.

[0367] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0368] Step 1:

[0369] Users insert old recording media (e.g., videotape) into a dedicated digitizing device. The digitizing device uses a video capture device to convert the analog video signal into a digital signal. This digital signal is then saved on a smartphone or PC in a format such as AVI or MP4. The input is the old recording media, and the output is video data in digital format. This conversion allows users to easily digitize past footage.

[0370] Step 2:

[0371] The terminal sends digitized video data to the server. The input is digitized video data, and the output is data sent to the server. The server receives and stores this data. Through this process, the digital video is aggregated on the server.

[0372] Step 3:

[0373] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information). The input is digital video data, and the output is the extracted video characteristic information. Computer vision techniques such as OpenCV are used for the analysis. This process allows for the quality evaluation of the video data.

[0374] Step 4:

[0375] The server performs noise reduction based on the extracted basic characteristic information. The input is the characteristic information and digital video data, and the output is the noise-removed video data. Spatial filtering and frequency filtering techniques are used for noise reduction, which removes unnecessary noise from the video.

[0376] Step 5:

[0377] The server performs resolution enhancement processing on the noise-removed video data. The input is noise-removed video data, and the output is video data with improved resolution. This processing uses super-resolution technology, which enhances the details of the image and achieves higher image quality.

[0378] Step 6:

[0379] The server performs color correction on the video data with improved resolution. The input is high-quality video data, and the output is color-corrected video data. This adjusts the color balance and makes the video's color tone natural.

[0380] Step 7:

[0381] The server uses an emotion engine to analyze the user's emotions. The input is the user's facial expressions and voice data, and the output is analyzed emotional information. This analysis uses data acquired through a camera and microphone. This results in a numerical evaluation of the user's emotions.

[0382] Step 8:

[0383] The server automatically adjusts the video effects and color tone based on the analyzed emotional information. The input is emotional information and color-corrected video data, and the output is video data edited based on the emotions. This allows the video to be customized to match the user's emotions.

[0384] Step 9:

[0385] The server converts the edited video data into a digital media format (e.g., a DVD-format ISO image file). The input is the emotion-based edited video data, and the output is the digital media format data. MPEG-2 encoding is used for the conversion, which prepares the video data in a format suitable for recording media.

[0386] Step 10:

[0387] The terminal writes the converted ISO image file to a recording medium. The input is data in digital media format, and the output is data written to the recording medium. Specifically, the user inserts a recording medium (e.g., a DVD) according to instructions, and the terminal executes the writing process.

[0388] Step 11:

[0389] The edited video data is distributed through a streaming distribution server. The input is data written to a recording medium, and the output is video data distributed in real time. Users can share the distribution link with family and friends, providing them with a high-quality, emotionally-driven viewing experience.

[0390] Example prompt: "Based on your feelings of joy, edit a high-quality video of your child's birthday party and share it via streaming with your family."

[0391] Through the above steps, the present invention provides a system that can enhance the quality of old footage using modern technology, and then edit it based on emotions before sharing it.

[0392] 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.

[0393] 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.

[0394] 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.

[0395] [Second embodiment]

[0396] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0397] 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.

[0398] 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).

[0399] 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.

[0400] 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.

[0401] 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).

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] 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."

[0408] This system utilizes AI technology to convert footage from old videotapes into high-quality images, and then performs a series of processes to finally dub the footage onto digital media such as DVDs. The system consists of three parts: the user, the terminal, and the server. The specific roles and processes of each part are explained in detail below.

[0409] 1. Digitization of videotapes

[0410] First, the user inserts the old videotape into a dedicated digitizing device. This digitizing device is connected to a terminal and is responsible for converting the analog video signal from the videotape into a digital signal. The terminal then saves this digital signal into a digital data file, such as an AVI or MP4 format, and sends it to a server. Here, the terminal uses a video capture device and digital conversion equipment. Through this digitizing process, the contents of the old videotape are newly saved as digital data.

[0411] 2. Pretreatment

[0412] The server analyzes the digital data sent from the terminal and performs preprocessing. This preprocessing includes noise reduction, resolution enhancement, and color correction. First, the server applies a noise reduction algorithm to remove unwanted noise from the digital data. This noise reduction uses spatial and frequency filtering techniques. The server then uses super-resolution technology to improve the resolution of the digital data, which results in clearer image details and higher-quality images. The server then applies a color correction filter to adjust the color balance of the image. This series of preprocessing steps significantly improves the quality of the base image data.

[0413] 3. High image quality using AI

[0414] After preprocessing is complete, the server uses AI (deep learning models) to enhance the image quality of the video. Specifically, the server analyzes each frame of the video and processes it to reproduce fine details. This is done using technology that improves the clarity of each frame. AI-based image enhancement significantly improves the beauty and quality of the details of the video. The server repeats this process multiple times to generate video data of optimal quality.

[0415] 4. Digital conversion and dubbing

[0416] Once the high-quality video data is generated, the server converts it into a digital format, such as DVD format. Specifically, the server uses MPEG-2 encoding to convert the video data into a DVD-format ISO image file. This ISO image file can then be burned directly onto a DVD. This data is then sent from the server to the device.

[0417] The device connects the received ISO image file to a DVD burner and prompts the user to insert a DVD media, after which the device copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[0418] 5. Delivery to User

[0419] Finally, the user receives the completed DVD, which can be played back at home or in any other playback environment to enjoy the high-definition images.

[0420] Specific examples

[0421] For example, consider a user who wants to digitize a home videotape from the 1990s. The tape contains footage of a young child's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. The server then uses AI technology to further enhance the image quality and finally encodes it into DVD format. This data is then copied onto a DVD, which the user can then receive and play, allowing them to enjoy clear, vibrant images.

[0422] In this way, this system can revive images from old videotapes as modern, high-quality digital images and provide them in a format that users can easily use.

[0423] The processing flow will be explained below.

[0424] Step 1:

[0425] A user inserts an old videotape into a dedicated digitizing device, and then operates the digitizing device to start playing the videotape.

[0426] Step 2:

[0427] The device captures the analog video signal from the videotape and converts it to a digital signal. The device uses a video capture device to save the video signal in a digital data format such as AVI or MP4.

[0428] Step 3:

[0429] The terminal transmits the digitized video data to the server, where it uses an appropriate compression format to optimize the data size.

[0430] Step 4:

[0431] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information), which is then used to evaluate the quality of the data.

[0432] Step 5:

[0433] The server applies noise reduction processing, specifically using noise reduction algorithms such as spatial filtering and frequency filtering to reduce noise in the video.

[0434] Step 6:

[0435] The server performs the resolution enhancement process, using super-resolution techniques based on deep learning models (e.g., SRGAN) to improve the image resolution. This process focuses on reproducing fine details.

[0436] Step 7:

[0437] The server performs color correction processing, adjusting the color balance of the video using automatic white balance adjustment and color correction filters. This process restores natural color tones.

[0438] Step 8:

[0439] The server then uses the pre-processed data to perform AI-based image enhancement, applying deep learning models to each frame of the video to improve detail and clarity. This process is repeated multiple times.

[0440] Step 9:

[0441] The server converts the high-quality video data into a DVD-format ISO image file, compressing and formatting the data using MPEG-2 encoding.

[0442] Step 10:

[0443] The server sends the generated ISO image file to the device, which receives the data and checks for errors.

[0444] Step 11:

[0445] The device prompts the user to insert a DVD, and the user inserts the DVD. The device uses a DVD writer to burn the ISO image file to a DVD. This process includes selecting the appropriate writing speed and checking for errors.

[0446] Step 12:

[0447] The user receives the completed DVD and can play it to check and enjoy the high-definition images.

[0448] Example 1

[0449] 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."

[0450] The conventional method of digitizing and preserving old videotape footage has the problem of degrading the quality of the video. Another issue is the time and labor required to perform individual processes such as noise reduction, resolution improvement, and color correction. Furthermore, there are limited means of achieving high image quality, and the final process of converting and dubbing the video to digital media is complicated.

[0451] 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.

[0452] In this invention, the server includes means for removing noise from the digital data, means for improving the resolution of the digital data, means for performing color correction on the digital data, and means for enhancing the image quality of the digital data using deep learning technology, thereby converting images from old videotapes into a high-quality digital format, allowing users to easily enjoy high-quality images.

[0453] Key Word Definitions

[0454] "Old videotapes" refers to magnetic tapes on which video is recorded in analog format, such as VHS and Betamax.

[0455] "Digital data" refers to data that has been converted from an analog signal into a digital signal, specifically video files in AVI or MP4 format.

[0456] "Server" refers to a computer system that receives, processes, and transmits data over a network.

[0457] "Noise reduction" is a process for reducing unnecessary noise from video and audio data, and specifically, spatial filtering and frequency filtering techniques are used.

[0458] "Resolution enhancement" is a process used to increase the detail of an image or video, particularly using super-resolution technology.

[0459] "Color correction" refers to the process of adjusting the color balance of an image, and is carried out to optimize the color and brightness of the image.

[0460] "Deep learning technology" is a technology that uses deep learning algorithms to analyze data and recognize patterns, and in this invention it is used to improve the image quality of videos.

[0461] The "DVD format" is a standard format for recording digital video data, and MPEG-2 encoding is commonly used.

[0462] An "ISO image file" is a digital file that contains the contents of an optical disc and is used to burn it onto a DVD or CD.

[0463] "Recording medium" refers to a physical medium for storing digital data, and specifically includes DVD discs and Blu-ray discs.

[0464] "Dubbing" refers to the process of writing digital data onto a recording medium.

[0465] MODE FOR CARRYING OUT THE INVENTION

[0466] This invention is a system that uses AI technology to convert old videotape footage into high-quality images and then dub them onto digital media. The system configuration and the specific roles of each piece of hardware and software are explained below.

[0467] (System configuration)

[0468] The system consists of three main parts: users, terminals, and servers.

[0469] 1. Digitization of videotapes

[0470] Users insert their old video tapes into a specialized digitizing device, which converts the analog video signal from the video tape into a digital signal. A typical example of a digitizing device used at this stage is a common video capture device.

[0471] The terminal activates the digitizing device, converts the analog video signal from the videotape into a digital signal, saves the converted digital signal into a digital data file in AVI or MP4 format, and transmits this digital data to the server.

[0472] 2. Pretreatment

[0473] The server analyzes and pre-processes the digital data received from the device, including noise reduction, resolution enhancement, and color correction.

[0474] Specifically, the server first applies a noise reduction algorithm, which uses spatial filtering techniques (such as OpenCV's GaussianBlur and MedianBlur) and frequency filtering techniques.

[0475] The server then uses super-resolution techniques to improve the resolution of the digital data, using techniques such as TensorFlow's ESRGAN.

[0476] Finally, the server applies a color correction filter to balance the color of the video. Specifically, it uses the Python PIL library to perform color correction.

[0477] 3. High image quality using AI

[0478] After preprocessing is complete, the server uses a deep learning model to enhance the image quality of the digital data. Specifically, the server uses deep learning technology (e.g., PyTorch's SRGAN model) to reproduce the details of the image and improve the overall image quality.

[0479] The server analyzes each frame of the video to enhance its clarity, and this process is repeated multiple times to produce video data of optimal quality.

[0480] 4. Digital conversion and dubbing

[0481] Once the high-quality video data is generated, the server converts it into a digital format, such as DVD format. Specifically, the server uses MPEG-2 encoding technology (e.g., FFmpeg) to convert the video data into a DVD-format ISO image file, which is then sent to the device.

[0482] The device connects the received ISO image file to a DVD writer (e.g., a general optical disc recording device) and prompts the user to insert a DVD media. The device then copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[0483] 5. Delivery to User

[0484] The user finally receives the finished DVD, which can be played at home or in any other playback environment, allowing them to enjoy the high-definition images.

[0485] Specific examples

[0486] For example, say a user wants to digitize a home videotape from the 1990s, which contains footage of young children's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data (AVI file). The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. The server then uses AI technology to further enhance the image quality and finally encodes it into DVD format. This data is then copied onto a DVD, which the user can then receive and play, allowing them to enjoy clear, vibrant images.

[0487] Prompt Sentence Examples

[0488] "Please explain the system that digitizes home videotapes, improves picture quality, and dubs them onto DVDs."

[0489] "Please tell me more about the process of converting videotape footage into digital data, enhancing the image quality with AI, and then dubbing it onto a DVD."

[0490] In this way, this system can provide high-quality digital images from old videotapes in a format that is easy for users to use.

[0491] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0492] Program processing steps

[0493] Step 1:

[0494] A user inserts an old videotape into a dedicated digitizing device. The input is the analog video signal from the videotape, which the digitizing device receives. The output is an analog signal sent from the digitizing device to a terminal.

[0495] Step 2:

[0496] The terminal activates a digitizing device that converts the analog video signal from the videotape into a digital signal. Specifically, a digital capture device (e.g., a video capture card) is used to receive the analog signal and output it as a digital signal. This digital signal is then saved as a digital data file in AVI or MP4 format.

[0497] Step 3:

[0498] The terminal sends the stored digital data to the server. The input is digital data in AVI or MP4 format, which is sent to the server via the terminal. The output is digital data sent to the server. This transmission uses the File Transfer Protocol (FTP) or HTTP.

[0499] Step 4:

[0500] The server analyzes the received digital data and performs noise reduction. The input is the digital data sent from the device, and the output is the data with noise removed. Specifically, the server uses algorithms such as GaussianBlur and MedianBlur from OpenCV to reduce unnecessary noise.

[0501] Step 5:

[0502] The server increases the resolution of the digital data. The input is the denoised digital data, and the output is the data with increased resolution. Super-resolution techniques such as TensorFlow's ESRGAN are used to increase the resolution of the video data.

[0503] Step 6:

[0504] The server performs color correction. The input is the digital data after resolution enhancement, and the output is the color-corrected data. The Python PIL library is used to adjust the color balance of the video.

[0505] Step 7:

[0506] The server uses deep learning technology to improve the image quality of digital data. The input is preprocessed digital data, and the output is image-enhanced data. Each frame is analyzed and improved using a PyTorch SRGAN model.

[0507] Step 8:

[0508] The server converts the high-definition video data into DVD format. The input is the digital data that has been converted to high definition, and the output is a DVD-format ISO image file. MPEG-2 encoding is performed using FFmpeg, and the digital data is converted into DVD format.

[0509] Step 9:

[0510] The server sends the generated ISO image file to the terminal. The input is the ISO image file sent from the server to the terminal. The output is the ISO image file received by the terminal.

[0511] Step 10:

[0512] After the terminal receives the ISO image file, it connects to the DVD writer and prompts the user to insert a DVD media. The input is the ISO image file, and it is connected to the DVD writer. When the user inserts the DVD, it proceeds to the next step.

[0513] Step 11:

[0514] The device will burn the ISO image file to a DVD. The input is the ISO image file inserted into the DVD burner, and the output is the finished DVD. This process includes proper burn speed optimization and error checking.

[0515] Step 12:

[0516] The process is complete when the user receives the finished DVD, allowing them to enjoy the high-definition video at home or in any other playback environment.

[0517] (Application example 1)

[0518] 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."

[0519] The deterioration of old video recording media (such as videotapes) leads to a decline in image quality, which is a major obstacle to the viewing and use of valuable video assets. Furthermore, the process of digitizing these old videos and converting them to high-quality images requires specialized knowledge and expensive equipment, making it difficult for average users to use. Another problem is the limited means of viewing digitized video in high quality. There is a need for a system that can resolve this situation and allow users to easily enjoy high-quality video.

[0520] 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.

[0521] In this invention, the server includes means for converting video from an old video recording medium into digital data, means for transmitting the digital data to a data storage device, means for removing noise from the digital data received by the data storage device, means for improving the resolution of the digital data received by the data storage device, means for color correcting the digital data received by the data storage device, means for converting the high-definition video data into a digital disc format by the data storage device, means for writing the digital disc format data to a physical medium, means for processing and streaming video owned by a user on the cloud, and means for enabling a user to view the high-definition video on a terminal. Thus, by digitizing video from an old video recording medium to high definition and processing it on the cloud, users can more easily view and use high-definition video assets.

[0522] "Video recording medium" means a physical medium for storing video in analog or digital form.

[0523] "Digital data" is data that has been converted from analog information into a digital format that can be processed by a computer.

[0524] A "data storage device" is a device that stores received data and processes or distributes it as necessary.

[0525] "Noise reduction" is a process for reducing unwanted signals and interference in digital data and improving the quality of the data.

[0526] "Resolution enhancement" is a process that increases the number of pixels in digital data to express details more clearly.

[0527] "Color correction" is a process that adjusts the color balance of an image to reproduce natural and beautiful colors.

[0528] "Digital disc format" refers to a digital format for recording on optical discs such as DVDs and Blu-ray discs.

[0529] A "physical medium" is a tangible medium for recording and storing digital data.

[0530] "Processing on the cloud" means processing data on a remote server accessible via the Internet.

[0531] "Streaming" is a distribution method that distributes digital data in real time, allowing users to view it continuously.

[0532] A "terminal" is a device such as a computer, smartphone, or tablet that is directly operated by a user.

[0533] This invention relates to a system that converts video stored on old video recording media into high-quality digital data, processes it on the cloud, and distributes it through streaming. This system is mainly composed of three parts: the user, the terminal, and the data storage device. The specific roles and processes of each part are explained in detail below.

[0534] First, a user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device. This digitizing device is connected to a terminal and is responsible for converting the analog video signal from the video recording medium into a digital signal. The terminal then stores this digital signal as a digital data file, usually in a common format such as AVI or MP4. This stored digital data is then sent by the terminal to a data storage device.

[0535] The data storage device analyzes the received digital data and first performs preprocessing. This preprocessing includes noise reduction, resolution enhancement, and color correction. Spatial and frequency filtering techniques are used for noise reduction. The data storage device then uses super-resolution technology to improve the resolution of the digital data. This process sharpens image details and significantly improves overall image quality. The data storage device then applies color correction filters to optimize the color balance of the image.

[0536] After preprocessing is complete, the data storage device uses AI (e.g., a generative AI model) to enhance the image quality. Specifically, each frame is analyzed in detail and advanced processing is performed to reproduce the details. AI-based image enhancement further improves the beauty and quality of the image. This process is repeated multiple times to produce optimal quality image data.

[0537] The high-quality video data is converted into a file in digital disc format (e.g., DVD format) by a data storage device. Specifically, the video data is converted into an ISO image file in digital disc format using MPEG-2 encoding. This data can be written directly to physical media. This data is then sent to a terminal for further writing to physical media (e.g., DVD).

[0538] The device connects to a device that writes the received ISO image file to physical media and prompts the user to insert the physical media. The device then writes the ISO image file to the physical media, providing high-quality video data on the physical media. This process includes appropriate optimization for writing speed and error checking.

[0539] In addition, by taking advantage of the fact that data is stored in the cloud, users can view high-definition video anytime, anywhere. A streaming function for this purpose is also built into the data storage device. Users can view video stored in the cloud in real time using a dedicated application (for example, an application installed on a smartphone or HMD).

[0540] As a concrete example, consider a user who wants to digitize a home videotape from the 1990s. This tape contains childhood family memories. The user first inserts the tape into a digitizer and converts it into digital data via a terminal. The data storage device receives the digital data, performs noise reduction, resolution enhancement, color correction, and further enhances the image quality using AI technology. Finally, the data storage device converts the enhanced video data into a digital disc format, and the terminal writes it to physical media. This physical media is then provided to the user, who can enjoy the enhanced video at home or in other playback environments. Furthermore, the high-quality video stored in the cloud can be viewed anywhere via a smartphone or HMD.

[0541] An example prompt is, "I want to improve the quality of a 1980s home videotape. I want to remove noise, improve resolution, and correct color frame by frame, and then finally stream it."

[0542] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0543] Step 1:

[0544] The user inserts an old video recording into a dedicated digitizing device.

[0545] Specific operation: A user inserts a video recording medium (e.g., a videotape) into the digitizing device and operates the device.

[0546] Input: Video recording medium

[0547] Output: Analog video signal

[0548] Step 2:

[0549] The device converts the analog video signal into a digital signal and stores it as a digital data file.

[0550] Specific operation: The terminal uses a video capture device to convert the analog video signal output from the digitizing device into a digital signal and saves it as an AVI or MP4 format file.

[0551] Input: Analog video signal

[0552] Output: Digital data file (AVI, MP4)

[0553] Step 3:

[0554] The terminal transmits the stored digital data file to the data storage device.

[0555] Specific operation: The terminal uploads the digital data file to the data storage device via the network.

[0556] Input: Digital data file

[0557] Output: Data sent to the data storage device

[0558] Step 4:

[0559] The data storage device removes noise from the received digital data.

[0560] Specific operation: The data storage device applies spatial filtering and frequency filtering techniques to the received digital data to reduce noise.

[0561] Input: Digital data file

[0562] Output: Noise-removed digital data

[0563] Step 5:

[0564] Data storage devices increase the resolution of digital data.

[0565] Specific operation: The data storage device uses super-resolution technology to improve the resolution of the received digital data, making the details of the image clearer.

[0566] Input: Noise-removed digital data

[0567] Output: High-resolution digital data

[0568] Step 6:

[0569] The data storage device performs color correction on the digital data.

[0570] Specific operation: The data storage device applies a color correction filter to optimize the color balance of the image.

[0571] Input: High-resolution digital data

[0572] Output: Color-corrected digital data

[0573] Step 7:

[0574] The data storage device uses AI (generative AI model) to process the image to improve its quality.

[0575] How it works: The data storage device uses a generative AI model to analyze each frame in detail and process it to recreate the details, further improving the beauty and quality of the image.

[0576] Input: Color-corrected digital data

[0577] Output: High-quality digital data

[0578] Step 8:

[0579] The data storage device converts the high-definition digital data into a digital disc format (e.g., DVD format).

[0580] Specific operation: The data storage device converts high-definition digital data into an ISO image file in digital disc format using MPEG-2 encoding.

[0581] Input: High-resolution digital data

[0582] Output: ISO image file

[0583] Step 9:

[0584] The device writes the ISO image file to physical media.

[0585] Specific operation: The device prompts the user to insert physical media (e.g., a DVD disc) and then writes the ISO image file to the physical media. This process includes proper write speed optimization and error checking.

[0586] Input: ISO image file

[0587] Output: Data written to physical media

[0588] Step 10:

[0589] The data storage device stores the high-definition data on the cloud, allowing users to view it via streaming.

[0590] Specific operation: The data storage device stores the high-definition data in the cloud and provides it to users through streaming distribution functions. Users can watch it in real time using a dedicated application.

[0591] Input: High-resolution digital data

[0592] Output: Streaming service

[0593] Example prompt: "I want to enhance the quality of a 1980s home videotape by removing noise, enhancing resolution, and correcting color frame by frame, and then finally streaming it."

[0594] 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.

[0595] This invention relates to a system that utilizes AI technology and an emotion engine to convert footage from old videotapes into high-quality images, and then performs a series of processes to ultimately dub the footage onto digital media such as DVDs. This system consists of four parts: the user, the terminal, the server, and the emotion engine. The specific roles and processes of each part are explained below in detail.

[0596] 1. Digitization of videotapes

[0597] First, the user inserts an old videotape into a dedicated digitizing device. The user operates the digitizing device and starts playing the videotape. The device captures the analog video signal from the videotape and converts it into a digital signal. The device uses the video capture device to save the video signal in a digital data format such as AVI or MP4 and transmits it to the server. Through this digitizing process, the contents of the old videotape are newly saved as digital data.

[0598] 2. Pretreatment

[0599] The server analyzes the digital data sent from the device and extracts basic video characteristics (resolution, frame rate, color information, etc.). This analysis is used to evaluate the quality of the data. The server then applies a noise reduction algorithm to remove unwanted noise from the digital data. This noise reduction uses spatial filtering and frequency filtering techniques. The server then uses super-resolution technology to improve the resolution of the digital data, which sharpens the image details and produces higher-quality images. The server then applies a color correction filter to adjust the color balance of the image. This series of pre-processing steps significantly improves the quality of the base video data.

[0600] 3. High image quality using AI

[0601] After preprocessing is complete, the server uses AI (deep learning models) to enhance the image quality of the video. Specifically, the server analyzes each frame of the video and processes it to reproduce fine details. This is done using technology that improves the clarity of each frame. AI-based image enhancement significantly improves the beauty and quality of the details of the video. The server repeats this process multiple times to generate video data of optimal quality.

[0602] 4. Video editing using emotion engine

[0603] The server uses an emotion engine to recognize the user's emotions. The emotion engine uses sensor devices such as cameras and microphones to analyze emotions from the user's facial expressions and voice. Based on the user's emotions, the server automatically adjusts video editing parameters. Specifically, if the user expresses joy, the server will make the video's color correction more vivid and add positive effects. On the other hand, if the user expresses sadness, the server will adjust the video's tone to a more subdued color tone.

[0604] 5. Digital conversion and dubbing

[0605] Once the high-quality, emotion-edited video data is generated, the server converts it into a DVD-format ISO image file. Specifically, the server compresses and formats the data using MPEG-2 encoding. This ISO image file can then be written directly to a DVD. This data is then sent from the server to the device.

[0606] The device connects the received ISO image file to a DVD burner and prompts the user to insert DVD media. After the user inserts DVD media, the device copies the ISO image file to DVD. This copying process includes proper optimization for writing speed and error checking.

[0607] 6. Delivery to User

[0608] Finally, the user receives the completed DVD, which can be played back at home or in any other playback environment to enjoy the high-definition images.

[0609] Specific examples

[0610] For example, consider a user who wants to digitize a home videotape from the 1990s. The tape contains footage of a children's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. Next, the server uses AI technology to further enhance the image quality and uses an emotion engine to recognize the user's emotions, such as joy or nostalgia, and adjust the image's color tone and effects accordingly. Finally, the server encodes the video data into DVD format and copies the data to a DVD. The user receives the DVD, plays it, and enjoys the crisp, emotionally tailored video.

[0611] In this way, this system can revive old videotape footage as modern, high-definition digital video, and by editing the video according to the user's emotions, it can provide a more moving viewing experience.

[0612] The processing flow will be explained below.

[0613] Step 1:

[0614] A user inserts an old videotape into a dedicated digitizing device, and then operates the digitizing device to start playing the videotape.

[0615] Step 2:

[0616] The device captures the analog video signal from the videotape and converts it to a digital signal. The device uses a video capture device to save the video signal in a digital data format such as AVI or MP4.

[0617] Step 3:

[0618] The terminal transmits the digitized video data to the server, where it uses an appropriate compression format to optimize the data size.

[0619] Step 4:

[0620] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information), which is then used to evaluate the quality of the data.

[0621] Step 5:

[0622] The server applies noise reduction processing, specifically using noise reduction algorithms such as spatial filtering and frequency filtering to reduce noise in the video.

[0623] Step 6:

[0624] The server performs the resolution enhancement process, using super-resolution techniques based on deep learning models (e.g., SRGAN) to improve the image resolution. This process focuses on reproducing fine details.

[0625] Step 7:

[0626] The server performs color correction processing, adjusting the color balance of the video using automatic white balance adjustment and color correction filters. This process restores natural color tones.

[0627] Step 8:

[0628] The server then uses the pre-processed data to perform AI-based image enhancement, applying deep learning models to each frame of the video to improve detail and clarity. This process is repeated multiple times.

[0629] Step 9:

[0630] The server uses an emotion engine to recognize the user's emotions. The emotion engine captures and analyzes the user's facial expressions and voice through sensor devices such as the device's camera and microphone.

[0631] Step 10:

[0632] The emotion engine analyzes the user's emotions (e.g., joy or sadness) and sends the information to the server, which then automatically adjusts the video editing parameters based on this information.

[0633] Step 11:

[0634] The server applies color correction and effects to the video based on the user's emotions. Specifically, if the user expresses joy, the video will be adjusted to a clearer, brighter tone and a more positive effect will be added. If the user expresses sadness, the video will be adjusted to a more muted tone.

[0635] Step 12:

[0636] The server converts the high-quality, emotion-edited video data into a DVD-format ISO image file. Specifically, the server compresses and formats the data using MPEG-2 encoding.

[0637] Step 13:

[0638] The server sends the generated ISO image file to the device, which receives the data and checks for errors.

[0639] Step 14:

[0640] The device prompts the user to insert a DVD, and the user inserts the DVD. The device uses a DVD writer to burn the ISO image file to a DVD. This process includes selecting the appropriate writing speed and checking for errors.

[0641] Step 15:

[0642] The user receives the completed DVD and can play it to check and enjoy the high-definition, emotionally edited footage.

[0643] Example 2

[0644] 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."

[0645] Old video recording media, especially videotapes, often experience deterioration over time, leading to a deterioration in image quality. Furthermore, when these videos are converted to modern digital media, they can contain noise and are often stored at low resolution. Furthermore, with conventional technologies, the process of improving the image quality and editing the video is often performed manually, resulting in inefficiencies. The present invention aims to solve these problems and provide a system that also enables video editing based on the user's emotions.

[0646] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0647] In this invention, the server includes means for converting video from an old video recording medium into digital data, means for transmitting the digital data to a computing device, means for removing noise from the digital data received by the computing device, means for improving the resolution of the digital data received by the computing device, means for performing color correction on the digital data received by the computing device, means for converting the high-quality video data into a recording medium format by the computing device, means for dubbing the data in the recording medium format onto a recording medium, means for recognizing a user's emotions and automatically adjusting video editing parameters based on the emotions, and means for performing an iterative process using AI to improve the quality of the generated video data. This makes it possible to convert video from old video recording media into digital media with high quality and in a manner that takes user emotions into consideration.

[0648] "Old video recording media" refers to physical media used to record video in the past, including videotapes and laser discs.

[0649] "Digital data" is data that has been converted from analog signals into a digital format, and is usually saved in a common video format such as AVI or MP4.

[0650] "Computing device" refers to a computer or server used to process digital data, and is equipment that performs advanced calculations and data analysis.

[0651] "Noise reduction" is a process that reduces unnecessary noise contained in video data, and uses techniques such as spatial filtering and frequency filtering.

[0652] "Resolution enhancement" is the process of converting low-resolution images into high-resolution images, and is carried out using super-resolution technology and artificial intelligence (AI).

[0653] "Color correction" is a process that adjusts the color balance of digital video data to make the overall color tone of the video appropriate.

[0654] A "recording medium format" is the file format used to store digital data on a particular recording medium (e.g., DVD or Blu-ray).

[0655] A "recording medium" is a medium for physically storing digital data, and includes, for example, DVDs and Blu-ray discs.

[0656] "User emotion" refers to the psychological state of the user as it is inferred from the facial expressions and voice of the user watching the video, and is analyzed using emotion recognition technology.

[0657] "Video editing parameters" refer to the setting values ​​and effects applied when editing video, including color correction and the type and strength of the effect.

[0658] "Iterative processing" is a technique in which the same process is repeated multiple times in order to improve the quality of video data, and is particularly used to improve image quality using AI.

[0659] This invention relates to a system that utilizes AI technology and an emotion engine to convert video from old video recording media into high-quality video, and then performs a series of processes to finally dub the video onto digital media. This system consists of four parts: the user, the terminal, the server, and the emotion engine. The specific roles and processes of each part are explained below in detail.

[0660] First, a user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device. Next, the user presses the play button on the digitizing device's operation panel to start playing the videotape. The terminal uses a video capture device (e.g., a general video capture device) to convert the analog video signal from the videotape into a digital signal. The converted digital signal is stored on the hard disk in a digital data format such as AVI or MP4. The terminal then transmits this digital data to a server via File Transfer Protocol (FTP) or a cloud storage service.

[0661] The server analyzes the received digital data and extracts basic video characteristics (resolution, frame rate, color information, etc.). This analysis is performed using libraries such as the FFmpeg library. The server then applies a noise reduction algorithm to remove unwanted noise from the digital data. For example, it uses OpenCV to apply Gaussian and Median filters. It also uses super-resolution techniques (such as the ESRGAN model) to improve the resolution of the digital data. The server then uses a color correction filter to adjust the hue, saturation, and lightness (HSL) to balance the color of the image.

[0662] After pre-processing, the server uses AI technology (deep learning models, such as SRGAN) to analyze each frame of the video and reproduce the details. This high-quality image processing is repeated multiple times to generate video data of optimal quality.

[0663] The server uses an emotion engine to recognize the user's emotions through sensor devices (cameras and microphones). For example, it uses the OpenFace library to perform facial expression analysis. It analyzes emotions from the user's facial and voice data and automatically adjusts video editing parameters based on those emotions. For example, if the user expresses joy, it will make the video's color correction more vivid and add positive effects.

[0664] After the high-quality, emotion-based video data is generated, the server converts it into a recording medium format, an ISO image file. This conversion uses MPEG-2 encoding. The server then sends the ISO image file to the device via FTP or a cloud storage service. The device receives the ISO image file and prompts the user to insert a DVD. When the user inserts the DVD, the device writes the ISO image file to a DVD, optimizing for proper writing speed and performing error checking.

[0665] Finally, the user receives the completed DVD and can play it at home or in any other playback environment to enjoy the high-definition images.

[0666] As a concrete example, consider a scenario in which a video of a young child's sports day recorded on a home videotape from the 1990s is digitized and converted to high-quality video. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives this digital data and performs noise reduction, resolution enhancement, and color correction. Next, the server uses AI technology to further enhance the video quality and uses an emotion engine to recognize the user's emotions and adjust the video's color tone and effects. Finally, the server encodes the video data into DVD format and copies the data to a DVD. The user receives the DVD, plays it, and enjoys the clear, emotionally edited video.

[0667] An example of a prompt for a generative AI model is shown below.

[0668] "Convert footage of young children's sports day recorded on a home videotape from the 1990s into high-resolution footage and edit it to suit the user's emotions."

[0669] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0670] Step 1:

[0671] A user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device and presses the play button to start playing the tape. The inputs are the videotape and the digitizing device, and the output is an analog video signal. In operation, the user operates the device to play the videotape.

[0672] Step 2:

[0673] A device uses a video capture device to capture analog video signals and convert them to digital signals. The input is an analog video signal, and the output is digital video data (e.g., an AVI or MP4 file). In operation, the capture device receives the signal, converts it to digital data, and stores it on the hard disk.

[0674] Step 3:

[0675] The device sends the stored digital video data to the server. The input is the digital video file, and the output is the file transferred to the server. In operation, the device sends the data using the FTP protocol or a cloud storage service.

[0676] Step 4:

[0677] The server analyzes the received digital data and extracts basic video characteristics (e.g., resolution, frame rate, color information). The input is a digital video file, and the output is video characteristic data. In operation, the FFmpeg library is used to obtain video characteristic information.

[0678] Step 5:

[0679] The server applies a noise reduction algorithm to reduce unnecessary noise from the digital data. The input is image characteristic data and digital image data, and the output is noise-reduced digital image data. In operation, OpenCV is used to apply Gaussian and Median filters.

[0680] Step 6:

[0681] The server uses super-resolution technology to improve the resolution of digital data. The input is digital video data with reduced noise, and the output is digital video data with improved resolution. In operation, the ESRGAN model is applied to convert low-resolution video to high-resolution.

[0682] Step 7:

[0683] The server applies a color correction filter to balance the color of digital video. The input is high-resolution digital video data, and the output is color-corrected digital video data. The operation involves adjusting the hue, saturation, and lightness (HSL) values.

[0684] Step 8:

[0685] The server uses AI technology to analyze each frame of video and perform image quality enhancement processing. The input is color-corrected digital video data, and the output is image quality-enhanced digital video data. It operates by repeatedly analyzing each frame and reproducing details using an SRGAN model.

[0686] Step 9:

[0687] The server uses an emotion engine to recognize the user's emotions through sensor devices. The input is the user's facial expression and voice data, and the output is analyzed emotional data. Facial expression analysis is performed using the OpenFace library.

[0688] Step 10:

[0689] The server automatically adjusts video editing parameters based on the user's emotional data. The input is emotional data and high-quality digital video data, and the output is video data edited based on the emotion. The operation involves adjusting color tones and adding effects.

[0690] Step 11:

[0691] The server converts the emotion-edited video data into an ISO image file in a recording medium format. The input is emotion-edited video data, and the output is an ISO image file. In operation, the ISO file is generated using MPEG-2 encoding.

[0692] Step 12:

[0693] The server sends the generated ISO image file to the terminal. The input is the ISO image file, and the output is the ISO image file transferred to the terminal. The operation is to send data using the FTP protocol or cloud storage service.

[0694] Step 13:

[0695] The terminal receives the ISO image file and displays instructions to the user to insert the DVD media. The input is the ISO image file and the output is the display instructions to the user. The operation is to display the instructions through a GUI.

[0696] Step 14:

[0697] The user inserts a DVD media into the device, and the action is to insert the appropriate media to burn the ISO image file to a DVD.

[0698] Step 15:

[0699] The terminal writes the ISO image file to the DVD media inserted by the user. The input is the ISO image file and the DVD media, and the output is the completed DVD. The operation proceeds while optimizing the writing speed and checking for errors.

[0700] Step 16:

[0701] The user receives the completed DVD and can play it at home or in another playback environment to enjoy the high-definition video. The operation involves receiving the completed DVD and watching it on a playback device.

[0702] Example prompts for generative AI models

[0703] "Convert footage of young children's sports day recorded on a home videotape from the 1990s into high-resolution footage and edit it to suit the user's emotions."

[0704] (Application example 2)

[0705] 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."

[0706] Videos stored on old recording media generally have low image quality and a lot of noise, making the viewing experience inferior to modern high-definition video. Furthermore, there is no system that can digitize and store these videos, as well as edit them emotionally and stream them. Therefore, there is a need to revive old videos using modern technology and provide a more emotional viewing experience.

[0707] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0708] In this invention, the server includes a means for adjusting the effects of the high-definition video data based on emotion analysis, a means for converting the data into a digital medium format using a connection device, and a means for writing the converted data to a recording medium. This makes it possible to digitize and improve the image quality of video data stored on old recording media, edit the data based on emotions, and then stream the data.

[0709] "Old recording media" refers to videotapes and other analog storage media used to record video data in the past.

[0710] "Digital data" refers to video data that has been converted into a format that can be processed by a computer.

[0711] A "server" is a central computer that provides services to other computers and devices over a network.

[0712] "Noise reduction" is a process for removing unnecessary noise components from digital data.

[0713] "Resolution enhancement" is a technique for converting video data into a higher resolution in order to improve the image quality of the data.

[0714] "Color correction" is a process of adjusting the color tone of video data to create a more natural and visually pleasing image.

[0715] "Emotion analysis" is a technology that analyzes the user's emotions and adjusts the video effects and color tone based on the results.

[0716] A "digital media format" is a format in which digital data can be converted into a particular format and stored on a suitable recording medium.

[0717] "Recording media" refers to media such as DVDs and Blu-ray discs for storing digital data.

[0718] "Streaming distribution" is a technology that transfers data in real time over a network and plays it back.

[0719] This system converts video from old recording media into digital data, edits it based on the user's preferences, and delivers high-quality video via streaming. This section explains the basic components of this system and their roles.

[0720] 1. Digitizing Devices and User Operation

[0721] A user inserts an old recording medium (e.g., a videotape) into a dedicated digitizing device. The digitizing device uses a video capture device to convert the recording medium's analog video signal into a digital signal. This digital data is saved in a format such as AVI or MP4 and sent to a server via the terminal.

[0722] 2. Data Preprocessing

[0723] The server first analyzes the basic characteristics of the received digital data and extracts information such as resolution, frame rate, and color. It then uses specialized software (e.g., OpenCV) to perform preprocessing such as noise reduction, resolution enhancement, and color correction. Spatial filtering and frequency filtering are applied without omission for noise reduction.

[0724] 3. High image quality using AI

[0725] After preprocessing, the server applies a generative AI model (e.g., using TensorFlow or PyTorch) to the data to enhance image quality. Using deep learning models, it analyzes each frame of the video and performs operations such as enhancing details. This significantly improves the quality and detail of the image.

[0726] 4. Editing with Emotion Engine

[0727] The server uses an emotion engine (e.g., DeepFace) to analyze the user's emotions. This involves collecting and analyzing facial expressions and audio via a camera and microphone. The color tone and effects of the video are automatically adjusted according to the user's emotions. For example, if the user expresses happiness, the video will be adjusted to be more vibrant, and conversely, if the user expresses sadness, the colors will be muted.

[0728] 5. Digital media conversion and dubbing of video

[0729] The high-quality, emotion-edited video data is then converted by the server into a digital media format (e.g., a DVD-format ISO image file). This process uses MPEG-2 encoding to ensure optimal quality. The converted ISO image file is then written to a recording medium (e.g., a DVD) via the terminal.

[0730] 6. Streaming

[0731] Finally, the edited video data is streamed through a distribution server, and users can share the link to enjoy the high-quality, emotionally enriched video with family and friends.

[0732] Specific examples

[0733] For example, if a user digitizes a videotape of a child's birthday party and edits it based on the emotion of "joy," the footage will have a vibrant, positive effect. This footage can then be shared with family and friends through a streaming service, breathing new life into old recordings and providing a modern viewing experience.

[0734] Example prompt: "Based on your feelings of joy, edit a high-quality video of your child's birthday party and share it via streaming with your family."

[0735] This system brings old footage back to life vividly using modern technology, providing a special viewing experience tailored to the user's emotions.

[0736] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0737] Step 1:

[0738] Users insert old recording media (e.g., videotape) into a dedicated digitizing device. The digitizing device uses a video capture device to convert the analog video signal into a digital signal. This digital signal is then saved on a smartphone or PC in a format such as AVI or MP4. The input is the old recording media, and the output is video data in digital format. This conversion allows users to easily digitize past footage.

[0739] Step 2:

[0740] The terminal sends digitized video data to the server. The input is digitized video data, and the output is data sent to the server. The server receives and stores this data. Through this process, the digital video is aggregated on the server.

[0741] Step 3:

[0742] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information). The input is digital video data, and the output is the extracted video characteristic information. Computer vision techniques such as OpenCV are used for the analysis. This process allows for the quality evaluation of the video data.

[0743] Step 4:

[0744] The server performs noise reduction based on the extracted basic characteristic information. The input is the characteristic information and digital video data, and the output is the noise-removed video data. Spatial filtering and frequency filtering techniques are used for noise reduction, which removes unnecessary noise from the video.

[0745] Step 5:

[0746] The server performs resolution enhancement processing on the noise-removed video data. The input is noise-removed video data, and the output is video data with improved resolution. This processing uses super-resolution technology, which enhances the details of the image and achieves higher image quality.

[0747] Step 6:

[0748] The server performs color correction on the video data with improved resolution. The input is high-quality video data, and the output is color-corrected video data. This adjusts the color balance and makes the video's color tone natural.

[0749] Step 7:

[0750] The server uses an emotion engine to analyze the user's emotions. The input is the user's facial expressions and voice data, and the output is analyzed emotional information. This analysis uses data acquired through a camera and microphone. This results in a numerical evaluation of the user's emotions.

[0751] Step 8:

[0752] The server automatically adjusts the video effects and color tone based on the analyzed emotional information. The input is emotional information and color-corrected video data, and the output is video data edited based on the emotions. This allows the video to be customized to match the user's emotions.

[0753] Step 9:

[0754] The server converts the edited video data into a digital media format (e.g., a DVD-format ISO image file). The input is the emotion-based edited video data, and the output is the digital media format data. MPEG-2 encoding is used for the conversion, which prepares the video data in a format suitable for recording media.

[0755] Step 10:

[0756] The terminal writes the converted ISO image file to a recording medium. The input is data in digital media format, and the output is data written to the recording medium. Specifically, the user inserts a recording medium (e.g., a DVD) according to instructions, and the terminal executes the writing process.

[0757] Step 11:

[0758] The edited video data is distributed through a streaming distribution server. The input is data written to a recording medium, and the output is video data distributed in real time. Users can share the distribution link with family and friends, providing them with a high-quality, emotionally-driven viewing experience.

[0759] Example prompt: "Based on your feelings of joy, edit a high-quality video of your child's birthday party and share it via streaming with your family."

[0760] Through the above steps, the present invention provides a system that can enhance the quality of old footage using modern technology, and then edit it based on emotions before sharing it.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] [Third embodiment]

[0765] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0766] 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.

[0767] 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).

[0768] 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.

[0769] 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.

[0770] 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).

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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."

[0777] This system utilizes AI technology to convert footage from old videotapes into high-quality images, and then performs a series of processes to finally dub the footage onto digital media such as DVDs. The system consists of three parts: the user, the terminal, and the server. The specific roles and processes of each part are explained in detail below.

[0778] 1. Digitization of videotapes

[0779] First, the user inserts the old videotape into a dedicated digitizing device. This digitizing device is connected to a terminal and is responsible for converting the analog video signal from the videotape into a digital signal. The terminal then saves this digital signal into a digital data file, such as an AVI or MP4 format, and sends it to a server. Here, the terminal uses a video capture device and digital conversion equipment. Through this digitizing process, the contents of the old videotape are newly saved as digital data.

[0780] 2. Pretreatment

[0781] The server analyzes the digital data sent from the terminal and performs preprocessing. This preprocessing includes noise reduction, resolution enhancement, and color correction. First, the server applies a noise reduction algorithm to remove unwanted noise from the digital data. This noise reduction uses spatial and frequency filtering techniques. The server then uses super-resolution technology to improve the resolution of the digital data, which results in clearer image details and higher-quality images. The server then applies a color correction filter to adjust the color balance of the image. This series of preprocessing steps significantly improves the quality of the base image data.

[0782] 3. High image quality using AI

[0783] After preprocessing is complete, the server uses AI (deep learning models) to enhance the image quality of the video. Specifically, the server analyzes each frame of the video and processes it to reproduce fine details. This is done using technology that improves the clarity of each frame. AI-based image enhancement significantly improves the beauty and quality of the details of the video. The server repeats this process multiple times to generate video data of optimal quality.

[0784] 4. Digital conversion and dubbing

[0785] Once the high-quality video data is generated, the server converts it into a digital format, such as DVD format. Specifically, the server uses MPEG-2 encoding to convert the video data into a DVD-format ISO image file. This ISO image file can then be burned directly onto a DVD. This data is then sent from the server to the device.

[0786] The device connects the received ISO image file to a DVD burner and prompts the user to insert a DVD media, after which the device copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[0787] 5. Delivery to User

[0788] Finally, the user receives the completed DVD, which can be played back at home or in any other playback environment to enjoy the high-definition images.

[0789] Specific examples

[0790] For example, consider a user who wants to digitize a home videotape from the 1990s. The tape contains footage of a young child's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. The server then uses AI technology to further enhance the image quality and finally encodes it into DVD format. This data is then copied onto a DVD, which the user can then receive and play, allowing them to enjoy clear, vibrant images.

[0791] In this way, this system can revive images from old videotapes as modern, high-quality digital images and provide them in a format that users can easily use.

[0792] The processing flow will be explained below.

[0793] Step 1:

[0794] A user inserts an old videotape into a dedicated digitizing device, and then operates the digitizing device to start playing the videotape.

[0795] Step 2:

[0796] The device captures the analog video signal from the videotape and converts it to a digital signal. The device uses a video capture device to save the video signal in a digital data format such as AVI or MP4.

[0797] Step 3:

[0798] The terminal transmits the digitized video data to the server, where it uses an appropriate compression format to optimize the data size.

[0799] Step 4:

[0800] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information), which is then used to evaluate the quality of the data.

[0801] Step 5:

[0802] The server applies noise reduction processing, specifically using noise reduction algorithms such as spatial filtering and frequency filtering to reduce noise in the video.

[0803] Step 6:

[0804] The server performs the resolution enhancement process, using super-resolution techniques based on deep learning models (e.g., SRGAN) to improve the image resolution. This process focuses on reproducing fine details.

[0805] Step 7:

[0806] The server performs color correction processing, adjusting the color balance of the video using automatic white balance adjustment and color correction filters. This process restores natural color tones.

[0807] Step 8:

[0808] The server then uses the pre-processed data to perform AI-based image enhancement, applying deep learning models to each frame of the video to improve detail and clarity. This process is repeated multiple times.

[0809] Step 9:

[0810] The server converts the high-quality video data into a DVD-format ISO image file, compressing and formatting the data using MPEG-2 encoding.

[0811] Step 10:

[0812] The server sends the generated ISO image file to the device, which receives the data and checks for errors.

[0813] Step 11:

[0814] The device prompts the user to insert a DVD, and the user inserts the DVD. The device uses a DVD writer to burn the ISO image file to a DVD. This process includes selecting the appropriate writing speed and checking for errors.

[0815] Step 12:

[0816] The user receives the completed DVD and can play it to check and enjoy the high-definition images.

[0817] Example 1

[0818] 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."

[0819] The conventional method of digitizing and preserving old videotape footage has the problem of degrading the quality of the video. Another issue is the time and labor required to perform individual processes such as noise reduction, resolution improvement, and color correction. Furthermore, there are limited means of achieving high image quality, and the final process of converting and dubbing the video to digital media is complicated.

[0820] 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.

[0821] In this invention, the server includes means for removing noise from the digital data, means for improving the resolution of the digital data, means for performing color correction on the digital data, and means for enhancing the image quality of the digital data using deep learning technology, thereby converting images from old videotapes into a high-quality digital format, allowing users to easily enjoy high-quality images.

[0822] Key Word Definitions

[0823] "Old videotapes" refers to magnetic tapes on which video is recorded in analog format, such as VHS and Betamax.

[0824] "Digital data" refers to data that has been converted from an analog signal into a digital signal, specifically video files in AVI or MP4 format.

[0825] "Server" refers to a computer system that receives, processes, and transmits data over a network.

[0826] "Noise reduction" is a process for reducing unnecessary noise from video and audio data, and specifically, spatial filtering and frequency filtering techniques are used.

[0827] "Resolution enhancement" is a process used to increase the detail of an image or video, particularly using super-resolution technology.

[0828] "Color correction" refers to the process of adjusting the color balance of an image, and is carried out to optimize the color and brightness of the image.

[0829] "Deep learning technology" is a technology that uses deep learning algorithms to analyze data and recognize patterns, and in this invention it is used to improve the image quality of videos.

[0830] The "DVD format" is a standard format for recording digital video data, and MPEG-2 encoding is commonly used.

[0831] An "ISO image file" is a digital file that contains the contents of an optical disc and is used to burn it onto a DVD or CD.

[0832] "Recording medium" refers to a physical medium for storing digital data, and specifically includes DVD discs and Blu-ray discs.

[0833] "Dubbing" refers to the process of writing digital data onto a recording medium.

[0834] MODE FOR CARRYING OUT THE INVENTION

[0835] This invention is a system that uses AI technology to convert old videotape footage into high-quality images and then dub them onto digital media. The system configuration and the specific roles of each piece of hardware and software are explained below.

[0836] (System configuration)

[0837] The system consists of three main parts: users, terminals, and servers.

[0838] 1. Digitization of videotapes

[0839] Users insert their old video tapes into a specialized digitizing device, which converts the analog video signal from the video tape into a digital signal. A typical example of a digitizing device used at this stage is a common video capture device.

[0840] The terminal activates the digitizing device, converts the analog video signal from the videotape into a digital signal, saves the converted digital signal into a digital data file in AVI or MP4 format, and transmits this digital data to the server.

[0841] 2. Pretreatment

[0842] The server analyzes and pre-processes the digital data received from the device, including noise reduction, resolution enhancement, and color correction.

[0843] Specifically, the server first applies a noise reduction algorithm, which uses spatial filtering techniques (such as OpenCV's GaussianBlur and MedianBlur) and frequency filtering techniques.

[0844] The server then uses super-resolution techniques to improve the resolution of the digital data, using techniques such as TensorFlow's ESRGAN.

[0845] Finally, the server applies a color correction filter to balance the color of the video. Specifically, it uses the Python PIL library to perform color correction.

[0846] 3. High image quality using AI

[0847] After preprocessing is complete, the server uses a deep learning model to enhance the image quality of the digital data. Specifically, the server uses deep learning technology (e.g., PyTorch's SRGAN model) to reproduce the details of the image and improve the overall image quality.

[0848] The server analyzes each frame of the video to enhance its clarity, and this process is repeated multiple times to produce video data of optimal quality.

[0849] 4. Digital conversion and dubbing

[0850] Once the high-quality video data is generated, the server converts it into a digital format, such as DVD format. Specifically, the server uses MPEG-2 encoding technology (e.g., FFmpeg) to convert the video data into a DVD-format ISO image file, which is then sent to the device.

[0851] The device connects the received ISO image file to a DVD writer (e.g., a general optical disc recording device) and prompts the user to insert a DVD media. The device then copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[0852] 5. Delivery to User

[0853] The user finally receives the finished DVD, which can be played at home or in any other playback environment, allowing them to enjoy the high-definition images.

[0854] Specific examples

[0855] For example, say a user wants to digitize a home videotape from the 1990s, which contains footage of young children's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data (AVI file). The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. The server then uses AI technology to further enhance the image quality and finally encodes it into DVD format. This data is then copied onto a DVD, which the user can then receive and play, allowing them to enjoy clear, vibrant images.

[0856] Prompt Sentence Examples

[0857] "Please explain the system that digitizes home videotapes, improves picture quality, and dubs them onto DVDs."

[0858] "Please tell me more about the process of converting videotape footage into digital data, enhancing the image quality with AI, and then dubbing it onto a DVD."

[0859] In this way, this system can provide high-quality digital images from old videotapes in a format that is easy for users to use.

[0860] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0861] Program processing steps

[0862] Step 1:

[0863] A user inserts an old videotape into a dedicated digitizing device. The input is the analog video signal from the videotape, which the digitizing device receives. The output is an analog signal sent from the digitizing device to a terminal.

[0864] Step 2:

[0865] The terminal activates a digitizing device that converts the analog video signal from the videotape into a digital signal. Specifically, a digital capture device (e.g., a video capture card) is used to receive the analog signal and output it as a digital signal. This digital signal is then saved as a digital data file in AVI or MP4 format.

[0866] Step 3:

[0867] The terminal sends the stored digital data to the server. The input is digital data in AVI or MP4 format, which is sent to the server via the terminal. The output is digital data sent to the server. This transmission uses the File Transfer Protocol (FTP) or HTTP.

[0868] Step 4:

[0869] The server analyzes the received digital data and performs noise reduction. The input is the digital data sent from the device, and the output is the data with noise removed. Specifically, the server uses algorithms such as GaussianBlur and MedianBlur from OpenCV to reduce unnecessary noise.

[0870] Step 5:

[0871] The server increases the resolution of the digital data. The input is the denoised digital data, and the output is the data with increased resolution. Super-resolution techniques such as TensorFlow's ESRGAN are used to increase the resolution of the video data.

[0872] Step 6:

[0873] The server performs color correction. The input is the digital data after resolution enhancement, and the output is the color-corrected data. The Python PIL library is used to adjust the color balance of the video.

[0874] Step 7:

[0875] The server uses deep learning technology to improve the image quality of digital data. The input is preprocessed digital data, and the output is image-enhanced data. Each frame is analyzed and improved using a PyTorch SRGAN model.

[0876] Step 8:

[0877] The server converts the high-definition video data into DVD format. The input is the digital data that has been converted to high definition, and the output is a DVD-format ISO image file. MPEG-2 encoding is performed using FFmpeg, and the digital data is converted into DVD format.

[0878] Step 9:

[0879] The server sends the generated ISO image file to the terminal. The input is the ISO image file sent from the server to the terminal. The output is the ISO image file received by the terminal.

[0880] Step 10:

[0881] After the terminal receives the ISO image file, it connects to the DVD writer and prompts the user to insert a DVD media. The input is the ISO image file, and it is connected to the DVD writer. When the user inserts the DVD, it proceeds to the next step.

[0882] Step 11:

[0883] The device will burn the ISO image file to a DVD. The input is the ISO image file inserted into the DVD burner, and the output is the finished DVD. This process includes proper burn speed optimization and error checking.

[0884] Step 12:

[0885] The process is complete when the user receives the finished DVD, allowing them to enjoy the high-definition video at home or in any other playback environment.

[0886] (Application example 1)

[0887] 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."

[0888] The deterioration of old video recording media (such as videotapes) leads to a decline in image quality, which is a major obstacle to the viewing and use of valuable video assets. Furthermore, the process of digitizing these old videos and converting them to high-quality images requires specialized knowledge and expensive equipment, making it difficult for average users to use. Another problem is the limited means of viewing digitized video in high quality. There is a need for a system that can resolve this situation and allow users to easily enjoy high-quality video.

[0889] 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.

[0890] In this invention, the server includes means for converting video from an old video recording medium into digital data, means for transmitting the digital data to a data storage device, means for removing noise from the digital data received by the data storage device, means for improving the resolution of the digital data received by the data storage device, means for color correcting the digital data received by the data storage device, means for converting the high-definition video data into a digital disc format by the data storage device, means for writing the digital disc format data to a physical medium, means for processing and streaming video owned by a user on the cloud, and means for enabling a user to view the high-definition video on a terminal. Thus, by digitizing video from an old video recording medium to high definition and processing it on the cloud, users can more easily view and use high-definition video assets.

[0891] "Video recording medium" means a physical medium for storing video in analog or digital form.

[0892] "Digital data" is data that has been converted from analog information into a digital format that can be processed by a computer.

[0893] A "data storage device" is a device that stores received data and processes or distributes it as necessary.

[0894] "Noise reduction" is a process for reducing unwanted signals and interference in digital data and improving the quality of the data.

[0895] "Resolution enhancement" is a process that increases the number of pixels in digital data to express details more clearly.

[0896] "Color correction" is a process that adjusts the color balance of an image to reproduce natural and beautiful colors.

[0897] "Digital disc format" refers to a digital format for recording on optical discs such as DVDs and Blu-ray discs.

[0898] A "physical medium" is a tangible medium for recording and storing digital data.

[0899] "Processing on the cloud" means processing data on a remote server accessible via the Internet.

[0900] "Streaming" is a distribution method that distributes digital data in real time, allowing users to view it continuously.

[0901] A "terminal" is a device such as a computer, smartphone, or tablet that is directly operated by a user.

[0902] This invention relates to a system that converts video stored on old video recording media into high-quality digital data, processes it on the cloud, and distributes it through streaming. This system is mainly composed of three parts: the user, the terminal, and the data storage device. The specific roles and processes of each part are explained in detail below.

[0903] First, a user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device. This digitizing device is connected to a terminal and is responsible for converting the analog video signal from the video recording medium into a digital signal. The terminal then stores this digital signal as a digital data file, usually in a common format such as AVI or MP4. This stored digital data is then sent by the terminal to a data storage device.

[0904] The data storage device analyzes the received digital data and first performs preprocessing. This preprocessing includes noise reduction, resolution enhancement, and color correction. Spatial and frequency filtering techniques are used for noise reduction. The data storage device then uses super-resolution technology to improve the resolution of the digital data. This process sharpens image details and significantly improves overall image quality. The data storage device then applies color correction filters to optimize the color balance of the image.

[0905] After preprocessing is complete, the data storage device uses AI (e.g., a generative AI model) to enhance the image quality. Specifically, each frame is analyzed in detail and advanced processing is performed to reproduce the details. AI-based image enhancement further improves the beauty and quality of the image. This process is repeated multiple times to produce optimal quality image data.

[0906] The high-quality video data is converted into a file in digital disc format (e.g., DVD format) by a data storage device. Specifically, the video data is converted into an ISO image file in digital disc format using MPEG-2 encoding. This data can be written directly to physical media. This data is then sent to a terminal for further writing to physical media (e.g., DVD).

[0907] The device connects to a device that writes the received ISO image file to physical media and prompts the user to insert the physical media. The device then writes the ISO image file to the physical media, providing high-quality video data on the physical media. This process includes appropriate optimization for writing speed and error checking.

[0908] In addition, by taking advantage of the fact that data is stored in the cloud, users can view high-definition video anytime, anywhere. A streaming function for this purpose is also built into the data storage device. Users can view video stored in the cloud in real time using a dedicated application (for example, an application installed on a smartphone or HMD).

[0909] As a concrete example, consider a user who wants to digitize a home videotape from the 1990s. This tape contains childhood family memories. The user first inserts the tape into a digitizer and converts it into digital data via a terminal. The data storage device receives the digital data, performs noise reduction, resolution enhancement, color correction, and further enhances the image quality using AI technology. Finally, the data storage device converts the enhanced video data into a digital disc format, and the terminal writes it to physical media. This physical media is then provided to the user, who can enjoy the enhanced video at home or in other playback environments. Furthermore, the high-quality video stored in the cloud can be viewed anywhere via a smartphone or HMD.

[0910] An example prompt is, "I want to improve the quality of a 1980s home videotape. I want to remove noise, improve resolution, and correct color frame by frame, and then finally stream it."

[0911] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0912] Step 1:

[0913] The user inserts an old video recording into a dedicated digitizing device.

[0914] Specific operation: A user inserts a video recording medium (e.g., a videotape) into the digitizing device and operates the device.

[0915] Input: Video recording medium

[0916] Output: Analog video signal

[0917] Step 2:

[0918] The device converts the analog video signal into a digital signal and stores it as a digital data file.

[0919] Specific operation: The terminal uses a video capture device to convert the analog video signal output from the digitizing device into a digital signal and saves it as an AVI or MP4 format file.

[0920] Input: Analog video signal

[0921] Output: Digital data file (AVI, MP4)

[0922] Step 3:

[0923] The terminal transmits the stored digital data file to the data storage device.

[0924] Specific operation: The terminal uploads the digital data file to the data storage device via the network.

[0925] Input: Digital data file

[0926] Output: Data sent to the data storage device

[0927] Step 4:

[0928] The data storage device removes noise from the received digital data.

[0929] Specific operation: The data storage device applies spatial filtering and frequency filtering techniques to the received digital data to reduce noise.

[0930] Input: Digital data file

[0931] Output: Noise-removed digital data

[0932] Step 5:

[0933] Data storage devices increase the resolution of digital data.

[0934] Specific operation: The data storage device uses super-resolution technology to improve the resolution of the received digital data, making the details of the image clearer.

[0935] Input: Noise-removed digital data

[0936] Output: High-resolution digital data

[0937] Step 6:

[0938] The data storage device performs color correction on the digital data.

[0939] Specific operation: The data storage device applies a color correction filter to optimize the color balance of the image.

[0940] Input: High-resolution digital data

[0941] Output: Color-corrected digital data

[0942] Step 7:

[0943] The data storage device uses AI (generative AI model) to process the image to improve its quality.

[0944] How it works: The data storage device uses a generative AI model to analyze each frame in detail and process it to recreate the details, further improving the beauty and quality of the image.

[0945] Input: Color-corrected digital data

[0946] Output: High-quality digital data

[0947] Step 8:

[0948] The data storage device converts the high-definition digital data into a digital disc format (e.g., DVD format).

[0949] Specific operation: The data storage device converts high-definition digital data into an ISO image file in digital disc format using MPEG-2 encoding.

[0950] Input: High-resolution digital data

[0951] Output: ISO image file

[0952] Step 9:

[0953] The device writes the ISO image file to physical media.

[0954] Specific operation: The device prompts the user to insert physical media (e.g., a DVD disc) and then writes the ISO image file to the physical media. This process includes proper write speed optimization and error checking.

[0955] Input: ISO image file

[0956] Output: Data written to physical media

[0957] Step 10:

[0958] The data storage device stores the high-definition data on the cloud, allowing users to view it via streaming.

[0959] Specific operation: The data storage device stores the high-definition data in the cloud and provides it to users through streaming distribution functions. Users can watch it in real time using a dedicated application.

[0960] Input: High-resolution digital data

[0961] Output: Streaming service

[0962] Example prompt: "I want to enhance the quality of a 1980s home videotape by removing noise, enhancing resolution, and correcting color frame by frame, and then finally streaming it."

[0963] 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.

[0964] This invention relates to a system that utilizes AI technology and an emotion engine to convert footage from old videotapes into high-quality images, and then performs a series of processes to ultimately dub the footage onto digital media such as DVDs. This system consists of four parts: the user, the terminal, the server, and the emotion engine. The specific roles and processes of each part are explained below in detail.

[0965] 1. Digitization of videotapes

[0966] First, the user inserts an old videotape into a dedicated digitizing device. The user operates the digitizing device and starts playing the videotape. The device captures the analog video signal from the videotape and converts it into a digital signal. The device uses the video capture device to save the video signal in a digital data format such as AVI or MP4 and transmits it to the server. Through this digitizing process, the contents of the old videotape are newly saved as digital data.

[0967] 2. Pretreatment

[0968] The server analyzes the digital data sent from the device and extracts basic video characteristics (resolution, frame rate, color information, etc.). This analysis is used to evaluate the quality of the data. The server then applies a noise reduction algorithm to remove unwanted noise from the digital data. This noise reduction uses spatial filtering and frequency filtering techniques. The server then uses super-resolution technology to improve the resolution of the digital data, which sharpens the image details and produces higher-quality images. The server then applies a color correction filter to adjust the color balance of the image. This series of pre-processing steps significantly improves the quality of the base video data.

[0969] 3. High image quality using AI

[0970] After preprocessing is complete, the server uses AI (deep learning models) to enhance the image quality of the video. Specifically, the server analyzes each frame of the video and processes it to reproduce fine details. This is done using technology that improves the clarity of each frame. AI-based image enhancement significantly improves the beauty and quality of the details of the video. The server repeats this process multiple times to generate video data of optimal quality.

[0971] 4. Video editing using emotion engine

[0972] The server uses an emotion engine to recognize the user's emotions. The emotion engine uses sensor devices such as cameras and microphones to analyze emotions from the user's facial expressions and voice. Based on the user's emotions, the server automatically adjusts video editing parameters. Specifically, if the user expresses joy, the server will make the video's color correction more vivid and add positive effects. On the other hand, if the user expresses sadness, the server will adjust the video's tone to a more subdued color tone.

[0973] 5. Digital conversion and dubbing

[0974] Once the high-quality, emotion-edited video data is generated, the server converts it into a DVD-format ISO image file. Specifically, the server compresses and formats the data using MPEG-2 encoding. This ISO image file can then be written directly to a DVD. This data is then sent from the server to the device.

[0975] The device connects the received ISO image file to a DVD burner and prompts the user to insert DVD media. After the user inserts DVD media, the device copies the ISO image file to DVD. This copying process includes proper optimization for writing speed and error checking.

[0976] 6. Delivery to User

[0977] Finally, the user receives the completed DVD, which can be played back at home or in any other playback environment to enjoy the high-definition images.

[0978] Specific examples

[0979] For example, consider a user who wants to digitize a home videotape from the 1990s. The tape contains footage of a children's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. Next, the server uses AI technology to further enhance the image quality and uses an emotion engine to recognize the user's emotions, such as joy or nostalgia, and adjust the image's color tone and effects accordingly. Finally, the server encodes the video data into DVD format and copies the data to a DVD. The user receives the DVD, plays it, and enjoys the crisp, emotionally tailored video.

[0980] In this way, this system can revive old videotape footage as modern, high-definition digital video, and by editing the video according to the user's emotions, it can provide a more moving viewing experience.

[0981] The processing flow will be explained below.

[0982] Step 1:

[0983] A user inserts an old videotape into a dedicated digitizing device, and then operates the digitizing device to start playing the videotape.

[0984] Step 2:

[0985] The device captures the analog video signal from the videotape and converts it to a digital signal. The device uses a video capture device to save the video signal in a digital data format such as AVI or MP4.

[0986] Step 3:

[0987] The terminal transmits the digitized video data to the server, where it uses an appropriate compression format to optimize the data size.

[0988] Step 4:

[0989] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information), which is then used to evaluate the quality of the data.

[0990] Step 5:

[0991] The server applies noise reduction processing, specifically using noise reduction algorithms such as spatial filtering and frequency filtering to reduce noise in the video.

[0992] Step 6:

[0993] The server performs the resolution enhancement process, using super-resolution techniques based on deep learning models (e.g., SRGAN) to improve the image resolution. This process focuses on reproducing fine details.

[0994] Step 7:

[0995] The server performs color correction processing, adjusting the color balance of the video using automatic white balance adjustment and color correction filters. This process restores natural color tones.

[0996] Step 8:

[0997] The server then uses the pre-processed data to perform AI-based image enhancement, applying deep learning models to each frame of the video to improve detail and clarity. This process is repeated multiple times.

[0998] Step 9:

[0999] The server uses an emotion engine to recognize the user's emotions. The emotion engine captures and analyzes the user's facial expressions and voice through sensor devices such as the device's camera and microphone.

[1000] Step 10:

[1001] The emotion engine analyzes the user's emotions (e.g., joy or sadness) and sends the information to the server, which then automatically adjusts the video editing parameters based on this information.

[1002] Step 11:

[1003] The server applies color correction and effects to the video based on the user's emotions. Specifically, if the user expresses joy, the video will be adjusted to a clearer, brighter tone and a more positive effect will be added. If the user expresses sadness, the video will be adjusted to a more muted tone.

[1004] Step 12:

[1005] The server converts the high-quality, emotion-edited video data into a DVD-format ISO image file. Specifically, the server compresses and formats the data using MPEG-2 encoding.

[1006] Step 13:

[1007] The server sends the generated ISO image file to the device, which receives the data and checks for errors.

[1008] Step 14:

[1009] The device prompts the user to insert a DVD, and the user inserts the DVD. The device uses a DVD writer to burn the ISO image file to a DVD. This process includes selecting the appropriate writing speed and checking for errors.

[1010] Step 15:

[1011] The user receives the completed DVD and can play it to check and enjoy the high-definition, emotionally edited footage.

[1012] Example 2

[1013] 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."

[1014] Old video recording media, especially videotapes, often experience deterioration over time, leading to a deterioration in image quality. Furthermore, when these videos are converted to modern digital media, they can contain noise and are often stored at low resolution. Furthermore, with conventional technologies, the process of improving the image quality and editing the video is often performed manually, resulting in inefficiencies. The present invention aims to solve these problems and provide a system that also enables video editing based on the user's emotions.

[1015] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1016] In this invention, the server includes means for converting video from an old video recording medium into digital data, means for transmitting the digital data to a computing device, means for removing noise from the digital data received by the computing device, means for improving the resolution of the digital data received by the computing device, means for performing color correction on the digital data received by the computing device, means for converting the high-quality video data into a recording medium format by the computing device, means for dubbing the data in the recording medium format onto a recording medium, means for recognizing a user's emotions and automatically adjusting video editing parameters based on the emotions, and means for performing an iterative process using AI to improve the quality of the generated video data. This makes it possible to convert video from old video recording media into digital media with high quality and in a manner that takes user emotions into consideration.

[1017] "Old video recording media" refers to physical media used to record video in the past, including videotapes and laser discs.

[1018] "Digital data" is data that has been converted from analog signals into a digital format, and is usually saved in a common video format such as AVI or MP4.

[1019] "Computing device" refers to a computer or server used to process digital data, and is equipment that performs advanced calculations and data analysis.

[1020] "Noise reduction" is a process that reduces unnecessary noise contained in video data, and uses techniques such as spatial filtering and frequency filtering.

[1021] "Resolution enhancement" is the process of converting low-resolution images into high-resolution images, and is carried out using super-resolution technology and artificial intelligence (AI).

[1022] "Color correction" is a process that adjusts the color balance of digital video data to make the overall color tone of the video appropriate.

[1023] A "recording medium format" is the file format used to store digital data on a particular recording medium (e.g., DVD or Blu-ray).

[1024] A "recording medium" is a medium for physically storing digital data, and includes, for example, DVDs and Blu-ray discs.

[1025] "User emotion" refers to the psychological state of the user as it is inferred from the facial expressions and voice of the user watching the video, and is analyzed using emotion recognition technology.

[1026] "Video editing parameters" refer to the setting values ​​and effects applied when editing video, including color correction and the type and strength of the effect.

[1027] "Iterative processing" is a technique in which the same process is repeated multiple times in order to improve the quality of video data, and is particularly used to improve image quality using AI.

[1028] This invention relates to a system that utilizes AI technology and an emotion engine to convert video from old video recording media into high-quality video, and then performs a series of processes to finally dub the video onto digital media. This system consists of four parts: the user, the terminal, the server, and the emotion engine. The specific roles and processes of each part are explained below in detail.

[1029] First, a user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device. Next, the user presses the play button on the digitizing device's operation panel to start playing the videotape. The terminal uses a video capture device (e.g., a general video capture device) to convert the analog video signal from the videotape into a digital signal. The converted digital signal is stored on the hard disk in a digital data format such as AVI or MP4. The terminal then transmits this digital data to a server via File Transfer Protocol (FTP) or a cloud storage service.

[1030] The server analyzes the received digital data and extracts basic video characteristics (resolution, frame rate, color information, etc.). This analysis is performed using libraries such as the FFmpeg library. The server then applies a noise reduction algorithm to remove unwanted noise from the digital data. For example, it uses OpenCV to apply Gaussian and Median filters. It also uses super-resolution techniques (such as the ESRGAN model) to improve the resolution of the digital data. The server then uses a color correction filter to adjust the hue, saturation, and lightness (HSL) to balance the color of the image.

[1031] After pre-processing, the server uses AI technology (deep learning models, such as SRGAN) to analyze each frame of the video and reproduce the details. This high-quality image processing is repeated multiple times to generate video data of optimal quality.

[1032] The server uses an emotion engine to recognize the user's emotions through sensor devices (cameras and microphones). For example, it uses the OpenFace library to perform facial expression analysis. It analyzes emotions from the user's facial and voice data and automatically adjusts video editing parameters based on those emotions. For example, if the user expresses joy, it will make the video's color correction more vivid and add positive effects.

[1033] After the high-quality, emotion-based video data is generated, the server converts it into a recording medium format, an ISO image file. This conversion uses MPEG-2 encoding. The server then sends the ISO image file to the device via FTP or a cloud storage service. The device receives the ISO image file and prompts the user to insert a DVD. When the user inserts the DVD, the device writes the ISO image file to a DVD, optimizing for proper writing speed and performing error checking.

[1034] Finally, the user receives the completed DVD and can play it at home or in any other playback environment to enjoy the high-definition images.

[1035] As a concrete example, consider a scenario in which a video of a young child's sports day recorded on a home videotape from the 1990s is digitized and converted to high-quality video. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives this digital data and performs noise reduction, resolution enhancement, and color correction. Next, the server uses AI technology to further enhance the video quality and uses an emotion engine to recognize the user's emotions and adjust the video's color tone and effects. Finally, the server encodes the video data into DVD format and copies the data to a DVD. The user receives the DVD, plays it, and enjoys the clear, emotionally edited video.

[1036] An example of a prompt for a generative AI model is shown below.

[1037] "Convert footage of young children's sports day recorded on a home videotape from the 1990s into high-resolution footage and edit it to suit the user's emotions."

[1038] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1039] Step 1:

[1040] A user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device and presses the play button to start playing the tape. The inputs are the videotape and the digitizing device, and the output is an analog video signal. In operation, the user operates the device to play the videotape.

[1041] Step 2:

[1042] A device uses a video capture device to capture analog video signals and convert them to digital signals. The input is an analog video signal, and the output is digital video data (e.g., an AVI or MP4 file). In operation, the capture device receives the signal, converts it to digital data, and stores it on the hard disk.

[1043] Step 3:

[1044] The device sends the stored digital video data to the server. The input is the digital video file, and the output is the file transferred to the server. In operation, the device sends the data using the FTP protocol or a cloud storage service.

[1045] Step 4:

[1046] The server analyzes the received digital data and extracts basic video characteristics (e.g., resolution, frame rate, color information). The input is a digital video file, and the output is video characteristic data. In operation, the FFmpeg library is used to obtain video characteristic information.

[1047] Step 5:

[1048] The server applies a noise reduction algorithm to reduce unnecessary noise from the digital data. The input is image characteristic data and digital image data, and the output is noise-reduced digital image data. In operation, OpenCV is used to apply Gaussian and Median filters.

[1049] Step 6:

[1050] The server uses super-resolution technology to improve the resolution of digital data. The input is digital video data with reduced noise, and the output is digital video data with improved resolution. In operation, the ESRGAN model is applied to convert low-resolution video to high-resolution.

[1051] Step 7:

[1052] The server applies a color correction filter to balance the color of digital video. The input is high-resolution digital video data, and the output is color-corrected digital video data. The operation involves adjusting the hue, saturation, and lightness (HSL) values.

[1053] Step 8:

[1054] The server uses AI technology to analyze each frame of video and perform image quality enhancement processing. The input is color-corrected digital video data, and the output is image quality-enhanced digital video data. It operates by repeatedly analyzing each frame and reproducing details using an SRGAN model.

[1055] Step 9:

[1056] The server uses an emotion engine to recognize the user's emotions through sensor devices. The input is the user's facial expression and voice data, and the output is analyzed emotional data. Facial expression analysis is performed using the OpenFace library.

[1057] Step 10:

[1058] The server automatically adjusts video editing parameters based on the user's emotional data. The input is emotional data and high-quality digital video data, and the output is video data edited based on the emotion. The operation involves adjusting color tones and adding effects.

[1059] Step 11:

[1060] The server converts the emotion-edited video data into an ISO image file in a recording medium format. The input is emotion-edited video data, and the output is an ISO image file. In operation, the ISO file is generated using MPEG-2 encoding.

[1061] Step 12:

[1062] The server sends the generated ISO image file to the terminal. The input is the ISO image file, and the output is the ISO image file transferred to the terminal. The operation is to send data using the FTP protocol or cloud storage service.

[1063] Step 13:

[1064] The terminal receives the ISO image file and displays instructions to the user to insert the DVD media. The input is the ISO image file and the output is the display instructions to the user. The operation is to display the instructions through a GUI.

[1065] Step 14:

[1066] The user inserts a DVD media into the device, and the action is to insert the appropriate media to burn the ISO image file to a DVD.

[1067] Step 15:

[1068] The terminal writes the ISO image file to the DVD media inserted by the user. The input is the ISO image file and the DVD media, and the output is the completed DVD. The operation proceeds while optimizing the writing speed and checking for errors.

[1069] Step 16:

[1070] The user receives the completed DVD and can play it at home or in another playback environment to enjoy the high-definition video. The operation involves receiving the completed DVD and watching it on a playback device.

[1071] Example prompts for generative AI models

[1072] "Convert footage of young children's sports day recorded on a home videotape from the 1990s into high-resolution footage and edit it to suit the user's emotions."

[1073] (Application example 2)

[1074] 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."

[1075] Videos stored on old recording media generally have low image quality and a lot of noise, making the viewing experience inferior to modern high-definition video. Furthermore, there is no system that can digitize and store these videos, as well as edit them emotionally and stream them. Therefore, there is a need to revive old videos using modern technology and provide a more emotional viewing experience.

[1076] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1077] In this invention, the server includes a means for adjusting the effects of the high-definition video data based on emotion analysis, a means for converting the data into a digital medium format using a connection device, and a means for writing the converted data to a recording medium. This makes it possible to digitize and improve the image quality of video data stored on old recording media, edit the data based on emotions, and then stream the data.

[1078] "Old recording media" refers to videotapes and other analog storage media used to record video data in the past.

[1079] "Digital data" refers to video data that has been converted into a format that can be processed by a computer.

[1080] A "server" is a central computer that provides services to other computers and devices over a network.

[1081] "Noise reduction" is a process for removing unnecessary noise components from digital data.

[1082] "Resolution enhancement" is a technique for converting video data into a higher resolution in order to improve the image quality of the data.

[1083] "Color correction" is a process of adjusting the color tone of video data to create a more natural and visually pleasing image.

[1084] "Emotion analysis" is a technology that analyzes the user's emotions and adjusts the video effects and color tone based on the results.

[1085] A "digital media format" is a format in which digital data can be converted into a particular format and stored on a suitable recording medium.

[1086] "Recording media" refers to media such as DVDs and Blu-ray discs for storing digital data.

[1087] "Streaming distribution" is a technology that transfers data in real time over a network and plays it back.

[1088] This system converts video from old recording media into digital data, edits it based on the user's preferences, and delivers high-quality video via streaming. This section explains the basic components of this system and their roles.

[1089] 1. Digitizing Devices and User Operation

[1090] A user inserts an old recording medium (e.g., a videotape) into a dedicated digitizing device. The digitizing device uses a video capture device to convert the recording medium's analog video signal into a digital signal. This digital data is saved in a format such as AVI or MP4 and sent to a server via the terminal.

[1091] 2. Data Preprocessing

[1092] The server first analyzes the basic characteristics of the received digital data and extracts information such as resolution, frame rate, and color. It then uses specialized software (e.g., OpenCV) to perform preprocessing such as noise reduction, resolution enhancement, and color correction. Spatial filtering and frequency filtering are applied without omission for noise reduction.

[1093] 3. High image quality using AI

[1094] After preprocessing, the server applies a generative AI model (e.g., using TensorFlow or PyTorch) to the data to enhance image quality. Using deep learning models, it analyzes each frame of the video and performs operations such as enhancing details. This significantly improves the quality and detail of the image.

[1095] 4. Editing with Emotion Engine

[1096] The server uses an emotion engine (e.g., DeepFace) to analyze the user's emotions. This involves collecting and analyzing facial expressions and audio via a camera and microphone. The color tone and effects of the video are automatically adjusted according to the user's emotions. For example, if the user expresses happiness, the video will be adjusted to be more vibrant, and conversely, if the user expresses sadness, the colors will be muted.

[1097] 5. Digital media conversion and dubbing of video

[1098] The high-quality, emotion-edited video data is then converted by the server into a digital media format (e.g., a DVD-format ISO image file). This process uses MPEG-2 encoding to ensure optimal quality. The converted ISO image file is then written to a recording medium (e.g., a DVD) via the terminal.

[1099] 6. Streaming

[1100] Finally, the edited video data is streamed through a distribution server, and users can share the link to enjoy the high-quality, emotionally enriched video with family and friends.

[1101] Specific examples

[1102] For example, if a user digitizes a videotape of a child's birthday party and edits it based on the emotion of "joy," the footage will have a vibrant, positive effect. This footage can then be shared with family and friends through a streaming service, breathing new life into old recordings and providing a modern viewing experience.

[1103] Example prompt: "Based on your feelings of joy, edit a high-quality video of your child's birthday party and share it via streaming with your family."

[1104] This system brings old footage back to life vividly using modern technology, providing a special viewing experience tailored to the user's emotions.

[1105] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1106] Step 1:

[1107] Users insert old recording media (e.g., videotape) into a dedicated digitizing device. The digitizing device uses a video capture device to convert the analog video signal into a digital signal. This digital signal is then saved on a smartphone or PC in a format such as AVI or MP4. The input is the old recording media, and the output is video data in digital format. This conversion allows users to easily digitize past footage.

[1108] Step 2:

[1109] The terminal sends digitized video data to the server. The input is digitized video data, and the output is data sent to the server. The server receives and stores this data. Through this process, the digital video is aggregated on the server.

[1110] Step 3:

[1111] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information). The input is digital video data, and the output is the extracted video characteristic information. Computer vision techniques such as OpenCV are used for the analysis. This process allows for the quality evaluation of the video data.

[1112] Step 4:

[1113] The server performs noise reduction based on the extracted basic characteristic information. The input is the characteristic information and digital video data, and the output is the noise-removed video data. Spatial filtering and frequency filtering techniques are used for noise reduction, which removes unnecessary noise from the video.

[1114] Step 5:

[1115] The server performs resolution enhancement processing on the noise-removed video data. The input is noise-removed video data, and the output is video data with improved resolution. This processing uses super-resolution technology, which enhances the details of the image and achieves higher image quality.

[1116] Step 6:

[1117] The server performs color correction on the video data with improved resolution. The input is high-quality video data, and the output is color-corrected video data. This adjusts the color balance and makes the video's color tone natural.

[1118] Step 7:

[1119] The server uses an emotion engine to analyze the user's emotions. The input is the user's facial expressions and voice data, and the output is analyzed emotional information. This analysis uses data acquired through a camera and microphone. This results in a numerical evaluation of the user's emotions.

[1120] Step 8:

[1121] The server automatically adjusts the video effects and color tone based on the analyzed emotional information. The input is emotional information and color-corrected video data, and the output is video data edited based on the emotions. This allows the video to be customized to match the user's emotions.

[1122] Step 9:

[1123] The server converts the edited video data into a digital media format (e.g., a DVD-format ISO image file). The input is the emotion-based edited video data, and the output is the digital media format data. MPEG-2 encoding is used for the conversion, which prepares the video data in a format suitable for recording media.

[1124] Step 10:

[1125] The terminal writes the converted ISO image file to a recording medium. The input is data in digital media format, and the output is data written to the recording medium. Specifically, the user inserts a recording medium (e.g., a DVD) according to instructions, and the terminal executes the writing process.

[1126] Step 11:

[1127] The edited video data is distributed through a streaming distribution server. The input is data written to a recording medium, and the output is video data distributed in real time. Users can share the distribution link with family and friends, providing them with a high-quality, emotionally-driven viewing experience.

[1128] Example prompt: "Based on your feelings of joy, edit a high-quality video of your child's birthday party and share it via streaming with your family."

[1129] Through the above steps, the present invention provides a system that can enhance the quality of old footage using modern technology, and then edit it based on emotions before sharing it.

[1130] 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.

[1131] 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.

[1132] 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.

[1133] [Fourth embodiment]

[1134] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1135] 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.

[1136] 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).

[1137] 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.

[1138] 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.

[1139] 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).

[1140] 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.

[1141] 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.

[1142] 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.

[1143] 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.

[1144] 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.

[1145] 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.

[1146] 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."

[1147] This system utilizes AI technology to convert footage from old videotapes into high-quality images, and then performs a series of processes to finally dub the footage onto digital media such as DVDs. The system consists of three parts: the user, the terminal, and the server. The specific roles and processes of each part are explained in detail below.

[1148] 1. Digitization of videotapes

[1149] First, the user inserts the old videotape into a dedicated digitizing device. This digitizing device is connected to a terminal and is responsible for converting the analog video signal from the videotape into a digital signal. The terminal then saves this digital signal into a digital data file, such as an AVI or MP4 format, and sends it to a server. Here, the terminal uses a video capture device and digital conversion equipment. Through this digitizing process, the contents of the old videotape are newly saved as digital data.

[1150] 2. Pretreatment

[1151] The server analyzes the digital data sent from the terminal and performs preprocessing. This preprocessing includes noise reduction, resolution enhancement, and color correction. First, the server applies a noise reduction algorithm to remove unwanted noise from the digital data. This noise reduction uses spatial and frequency filtering techniques. The server then uses super-resolution technology to improve the resolution of the digital data, which results in clearer image details and higher-quality images. The server then applies a color correction filter to adjust the color balance of the image. This series of preprocessing steps significantly improves the quality of the base image data.

[1152] 3. High image quality using AI

[1153] After preprocessing is complete, the server uses AI (deep learning models) to enhance the image quality of the video. Specifically, the server analyzes each frame of the video and processes it to reproduce fine details. This is done using technology that improves the clarity of each frame. AI-based image enhancement significantly improves the beauty and quality of the details of the video. The server repeats this process multiple times to generate video data of optimal quality.

[1154] 4. Digital conversion and dubbing

[1155] Once the high-quality video data is generated, the server converts it into a digital format, such as DVD format. Specifically, the server uses MPEG-2 encoding to convert the video data into a DVD-format ISO image file. This ISO image file can then be burned directly onto a DVD. This data is then sent from the server to the device.

[1156] The device connects the received ISO image file to a DVD burner and prompts the user to insert a DVD media, after which the device copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[1157] 5. Delivery to User

[1158] Finally, the user receives the completed DVD, which can be played back at home or in any other playback environment to enjoy the high-definition images.

[1159] Specific examples

[1160] For example, consider a user who wants to digitize a home videotape from the 1990s. The tape contains footage of a young child's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. The server then uses AI technology to further enhance the image quality and finally encodes it into DVD format. This data is then copied onto a DVD, which the user can then receive and play, allowing them to enjoy clear, vibrant images.

[1161] In this way, this system can revive images from old videotapes as modern, high-quality digital images and provide them in a format that users can easily use.

[1162] The processing flow will be explained below.

[1163] Step 1:

[1164] A user inserts an old videotape into a dedicated digitizing device, and then operates the digitizing device to start playing the videotape.

[1165] Step 2:

[1166] The device captures the analog video signal from the videotape and converts it to a digital signal. The device uses a video capture device to save the video signal in a digital data format such as AVI or MP4.

[1167] Step 3:

[1168] The terminal transmits the digitized video data to the server, where it uses an appropriate compression format to optimize the data size.

[1169] Step 4:

[1170] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information), which is then used to evaluate the quality of the data.

[1171] Step 5:

[1172] The server applies noise reduction processing, specifically using noise reduction algorithms such as spatial filtering and frequency filtering to reduce noise in the video.

[1173] Step 6:

[1174] The server performs the resolution enhancement process, using super-resolution techniques based on deep learning models (e.g., SRGAN) to improve the image resolution. This process focuses on reproducing fine details.

[1175] Step 7:

[1176] The server performs color correction processing, adjusting the color balance of the video using automatic white balance adjustment and color correction filters. This process restores natural color tones.

[1177] Step 8:

[1178] The server then uses the pre-processed data to perform AI-based image enhancement, applying deep learning models to each frame of the video to improve detail and clarity. This process is repeated multiple times.

[1179] Step 9:

[1180] The server converts the high-quality video data into a DVD-format ISO image file, compressing and formatting the data using MPEG-2 encoding.

[1181] Step 10:

[1182] The server sends the generated ISO image file to the device, which receives the data and checks for errors.

[1183] Step 11:

[1184] The device prompts the user to insert a DVD, and the user inserts the DVD. The device uses a DVD writer to burn the ISO image file to a DVD. This process includes selecting the appropriate writing speed and checking for errors.

[1185] Step 12:

[1186] The user receives the completed DVD and can play it to check and enjoy the high-definition images.

[1187] Example 1

[1188] 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."

[1189] The conventional method of digitizing and preserving old videotape footage has the problem of degrading the quality of the video. Another issue is the time and labor required to perform individual processes such as noise reduction, resolution improvement, and color correction. Furthermore, there are limited means of achieving high image quality, and the final process of converting and dubbing the video to digital media is complicated.

[1190] 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.

[1191] In this invention, the server includes means for removing noise from the digital data, means for improving the resolution of the digital data, means for performing color correction on the digital data, and means for enhancing the image quality of the digital data using deep learning technology, thereby converting images from old videotapes into a high-quality digital format, allowing users to easily enjoy high-quality images.

[1192] Key Word Definitions

[1193] "Old videotapes" refers to magnetic tapes on which video is recorded in analog format, such as VHS and Betamax.

[1194] "Digital data" refers to data that has been converted from an analog signal into a digital signal, specifically video files in AVI or MP4 format.

[1195] "Server" refers to a computer system that receives, processes, and transmits data over a network.

[1196] "Noise reduction" is a process for reducing unnecessary noise from video and audio data, and specifically, spatial filtering and frequency filtering techniques are used.

[1197] "Resolution enhancement" is a process used to increase the detail of an image or video, particularly using super-resolution technology.

[1198] "Color correction" refers to the process of adjusting the color balance of an image, and is carried out to optimize the color and brightness of the image.

[1199] "Deep learning technology" is a technology that uses deep learning algorithms to analyze data and recognize patterns, and in this invention it is used to improve the image quality of videos.

[1200] The "DVD format" is a standard format for recording digital video data, and MPEG-2 encoding is commonly used.

[1201] An "ISO image file" is a digital file that contains the contents of an optical disc and is used to burn it onto a DVD or CD.

[1202] "Recording medium" refers to a physical medium for storing digital data, and specifically includes DVD discs and Blu-ray discs.

[1203] "Dubbing" refers to the process of writing digital data onto a recording medium.

[1204] MODE FOR CARRYING OUT THE INVENTION

[1205] This invention is a system that uses AI technology to convert old videotape footage into high-quality images and then dub them onto digital media. The system configuration and the specific roles of each piece of hardware and software are explained below.

[1206] (System configuration)

[1207] The system consists of three main parts: users, terminals, and servers.

[1208] 1. Digitization of videotapes

[1209] Users insert their old video tapes into a specialized digitizing device, which converts the analog video signal from the video tape into a digital signal. A typical example of a digitizing device used at this stage is a common video capture device.

[1210] The terminal activates the digitizing device, converts the analog video signal from the videotape into a digital signal, saves the converted digital signal into a digital data file in AVI or MP4 format, and transmits this digital data to the server.

[1211] 2. Pretreatment

[1212] The server analyzes and pre-processes the digital data received from the device, including noise reduction, resolution enhancement, and color correction.

[1213] Specifically, the server first applies a noise reduction algorithm, which uses spatial filtering techniques (such as OpenCV's GaussianBlur and MedianBlur) and frequency filtering techniques.

[1214] The server then uses super-resolution techniques to improve the resolution of the digital data, using techniques such as TensorFlow's ESRGAN.

[1215] Finally, the server applies a color correction filter to balance the color of the video. Specifically, it uses the Python PIL library to perform color correction.

[1216] 3. High image quality using AI

[1217] After preprocessing is complete, the server uses a deep learning model to enhance the image quality of the digital data. Specifically, the server uses deep learning technology (e.g., PyTorch's SRGAN model) to reproduce the details of the image and improve the overall image quality.

[1218] The server analyzes each frame of the video to enhance its clarity, and this process is repeated multiple times to produce video data of optimal quality.

[1219] 4. Digital conversion and dubbing

[1220] Once the high-quality video data is generated, the server converts it into a digital format, such as DVD format. Specifically, the server uses MPEG-2 encoding technology (e.g., FFmpeg) to convert the video data into a DVD-format ISO image file, which is then sent to the device.

[1221] The device connects the received ISO image file to a DVD writer (e.g., a general optical disc recording device) and prompts the user to insert a DVD media. The device then copies the ISO image file to a DVD. This copying process includes proper optimization for writing speed and error checking.

[1222] 5. Delivery to User

[1223] The user finally receives the finished DVD, which can be played at home or in any other playback environment, allowing them to enjoy the high-definition images.

[1224] Specific examples

[1225] For example, say a user wants to digitize a home videotape from the 1990s, which contains footage of young children's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data (AVI file). The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. The server then uses AI technology to further enhance the image quality and finally encodes it into DVD format. This data is then copied onto a DVD, which the user can then receive and play, allowing them to enjoy clear, vibrant images.

[1226] Prompt Sentence Examples

[1227] "Please explain the system that digitizes home videotapes, improves picture quality, and dubs them onto DVDs."

[1228] "Please tell me more about the process of converting videotape footage into digital data, enhancing the image quality with AI, and then dubbing it onto a DVD."

[1229] In this way, this system can provide high-quality digital images from old videotapes in a format that is easy for users to use.

[1230] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1231] Program processing steps

[1232] Step 1:

[1233] A user inserts an old videotape into a dedicated digitizing device. The input is the analog video signal from the videotape, which the digitizing device receives. The output is an analog signal sent from the digitizing device to a terminal.

[1234] Step 2:

[1235] The terminal activates a digitizing device that converts the analog video signal from the videotape into a digital signal. Specifically, a digital capture device (e.g., a video capture card) is used to receive the analog signal and output it as a digital signal. This digital signal is then saved as a digital data file in AVI or MP4 format.

[1236] Step 3:

[1237] The terminal sends the stored digital data to the server. The input is digital data in AVI or MP4 format, which is sent to the server via the terminal. The output is digital data sent to the server. This transmission uses the File Transfer Protocol (FTP) or HTTP.

[1238] Step 4:

[1239] The server analyzes the received digital data and performs noise reduction. The input is the digital data sent from the device, and the output is the data with noise removed. Specifically, the server uses algorithms such as GaussianBlur and MedianBlur from OpenCV to reduce unnecessary noise.

[1240] Step 5:

[1241] The server increases the resolution of the digital data. The input is the denoised digital data, and the output is the data with increased resolution. Super-resolution techniques such as TensorFlow's ESRGAN are used to increase the resolution of the video data.

[1242] Step 6:

[1243] The server performs color correction. The input is the digital data after resolution enhancement, and the output is the color-corrected data. The Python PIL library is used to adjust the color balance of the video.

[1244] Step 7:

[1245] The server uses deep learning technology to improve the image quality of digital data. The input is preprocessed digital data, and the output is image-enhanced data. Each frame is analyzed and improved using a PyTorch SRGAN model.

[1246] Step 8:

[1247] The server converts the high-definition video data into DVD format. The input is the digital data that has been converted to high definition, and the output is a DVD-format ISO image file. MPEG-2 encoding is performed using FFmpeg, and the digital data is converted into DVD format.

[1248] Step 9:

[1249] The server sends the generated ISO image file to the terminal. The input is the ISO image file sent from the server to the terminal. The output is the ISO image file received by the terminal.

[1250] Step 10:

[1251] After the terminal receives the ISO image file, it connects to the DVD writer and prompts the user to insert a DVD media. The input is the ISO image file, and it is connected to the DVD writer. When the user inserts the DVD, it proceeds to the next step.

[1252] Step 11:

[1253] The device will burn the ISO image file to a DVD. The input is the ISO image file inserted into the DVD burner, and the output is the finished DVD. This process includes proper burn speed optimization and error checking.

[1254] Step 12:

[1255] The process is complete when the user receives the finished DVD, allowing them to enjoy the high-definition video at home or in any other playback environment.

[1256] (Application example 1)

[1257] 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."

[1258] The deterioration of old video recording media (such as videotapes) leads to a decline in image quality, which is a major obstacle to the viewing and use of valuable video assets. Furthermore, the process of digitizing these old videos and converting them to high-quality images requires specialized knowledge and expensive equipment, making it difficult for average users to use. Another problem is the limited means of viewing digitized video in high quality. There is a need for a system that can resolve this situation and allow users to easily enjoy high-quality video.

[1259] 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.

[1260] In this invention, the server includes means for converting video from an old video recording medium into digital data, means for transmitting the digital data to a data storage device, means for removing noise from the digital data received by the data storage device, means for improving the resolution of the digital data received by the data storage device, means for color correcting the digital data received by the data storage device, means for converting the high-definition video data into a digital disc format by the data storage device, means for writing the digital disc format data to a physical medium, means for processing and streaming video owned by a user on the cloud, and means for enabling a user to view the high-definition video on a terminal. Thus, by digitizing video from an old video recording medium to high definition and processing it on the cloud, users can more easily view and use high-definition video assets.

[1261] "Video recording medium" means a physical medium for storing video in analog or digital form.

[1262] "Digital data" is data that has been converted from analog information into a digital format that can be processed by a computer.

[1263] A "data storage device" is a device that stores received data and processes or distributes it as necessary.

[1264] "Noise reduction" is a process for reducing unwanted signals and interference in digital data and improving the quality of the data.

[1265] "Resolution enhancement" is a process that increases the number of pixels in digital data to express details more clearly.

[1266] "Color correction" is a process that adjusts the color balance of an image to reproduce natural and beautiful colors.

[1267] "Digital disc format" refers to a digital format for recording on optical discs such as DVDs and Blu-ray discs.

[1268] A "physical medium" is a tangible medium for recording and storing digital data.

[1269] "Processing on the cloud" means processing data on a remote server accessible via the Internet.

[1270] "Streaming" is a distribution method that distributes digital data in real time, allowing users to view it continuously.

[1271] A "terminal" is a device such as a computer, smartphone, or tablet that is directly operated by a user.

[1272] This invention relates to a system that converts video stored on old video recording media into high-quality digital data, processes it on the cloud, and distributes it through streaming. This system is mainly composed of three parts: the user, the terminal, and the data storage device. The specific roles and processes of each part are explained in detail below.

[1273] First, a user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device. This digitizing device is connected to a terminal and is responsible for converting the analog video signal from the video recording medium into a digital signal. The terminal then stores this digital signal as a digital data file, usually in a common format such as AVI or MP4. This stored digital data is then sent by the terminal to a data storage device.

[1274] The data storage device analyzes the received digital data and first performs preprocessing. This preprocessing includes noise reduction, resolution enhancement, and color correction. Spatial and frequency filtering techniques are used for noise reduction. The data storage device then uses super-resolution technology to improve the resolution of the digital data. This process sharpens image details and significantly improves overall image quality. The data storage device then applies color correction filters to optimize the color balance of the image.

[1275] After preprocessing is complete, the data storage device uses AI (e.g., a generative AI model) to enhance the image quality. Specifically, each frame is analyzed in detail and advanced processing is performed to reproduce the details. AI-based image enhancement further improves the beauty and quality of the image. This process is repeated multiple times to produce optimal quality image data.

[1276] The high-quality video data is converted into a file in digital disc format (e.g., DVD format) by a data storage device. Specifically, the video data is converted into an ISO image file in digital disc format using MPEG-2 encoding. This data can be written directly to physical media. This data is then sent to a terminal for further writing to physical media (e.g., DVD).

[1277] The device connects to a device that writes the received ISO image file to physical media and prompts the user to insert the physical media. The device then writes the ISO image file to the physical media, providing high-quality video data on the physical media. This process includes appropriate optimization for writing speed and error checking.

[1278] In addition, by taking advantage of the fact that data is stored in the cloud, users can view high-definition video anytime, anywhere. A streaming function for this purpose is also built into the data storage device. Users can view video stored in the cloud in real time using a dedicated application (for example, an application installed on a smartphone or HMD).

[1279] As a concrete example, consider a user who wants to digitize a home videotape from the 1990s. This tape contains childhood family memories. The user first inserts the tape into a digitizer and converts it into digital data via a terminal. The data storage device receives the digital data, performs noise reduction, resolution enhancement, color correction, and further enhances the image quality using AI technology. Finally, the data storage device converts the enhanced video data into a digital disc format, and the terminal writes it to physical media. This physical media is then provided to the user, who can enjoy the enhanced video at home or in other playback environments. Furthermore, the high-quality video stored in the cloud can be viewed anywhere via a smartphone or HMD.

[1280] An example prompt is, "I want to improve the quality of a 1980s home videotape. I want to remove noise, improve resolution, and correct color frame by frame, and then finally stream it."

[1281] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1282] Step 1:

[1283] The user inserts an old video recording into a dedicated digitizing device.

[1284] Specific operation: A user inserts a video recording medium (e.g., a videotape) into the digitizing device and operates the device.

[1285] Input: Video recording medium

[1286] Output: Analog video signal

[1287] Step 2:

[1288] The device converts the analog video signal into a digital signal and stores it as a digital data file.

[1289] Specific operation: The terminal uses a video capture device to convert the analog video signal output from the digitizing device into a digital signal and saves it as an AVI or MP4 format file.

[1290] Input: Analog video signal

[1291] Output: Digital data file (AVI, MP4)

[1292] Step 3:

[1293] The terminal transmits the stored digital data file to the data storage device.

[1294] Specific operation: The terminal uploads the digital data file to the data storage device via the network.

[1295] Input: Digital data file

[1296] Output: Data sent to the data storage device

[1297] Step 4:

[1298] The data storage device removes noise from the received digital data.

[1299] Specific operation: The data storage device applies spatial filtering and frequency filtering techniques to the received digital data to reduce noise.

[1300] Input: Digital data file

[1301] Output: Noise-removed digital data

[1302] Step 5:

[1303] Data storage devices increase the resolution of digital data.

[1304] Specific operation: The data storage device uses super-resolution technology to improve the resolution of the received digital data, making the details of the image clearer.

[1305] Input: Noise-removed digital data

[1306] Output: High-resolution digital data

[1307] Step 6:

[1308] The data storage device performs color correction on the digital data.

[1309] Specific operation: The data storage device applies a color correction filter to optimize the color balance of the image.

[1310] Input: High-resolution digital data

[1311] Output: Color-corrected digital data

[1312] Step 7:

[1313] The data storage device uses AI (generative AI model) to process the image to improve its quality.

[1314] How it works: The data storage device uses a generative AI model to analyze each frame in detail and process it to recreate the details, further improving the beauty and quality of the image.

[1315] Input: Color-corrected digital data

[1316] Output: High-quality digital data

[1317] Step 8:

[1318] The data storage device converts the high-definition digital data into a digital disc format (e.g., DVD format).

[1319] Specific operation: The data storage device converts high-definition digital data into an ISO image file in digital disc format using MPEG-2 encoding.

[1320] Input: High-resolution digital data

[1321] Output: ISO image file

[1322] Step 9:

[1323] The device writes the ISO image file to physical media.

[1324] Specific operation: The device prompts the user to insert physical media (e.g., a DVD disc) and then writes the ISO image file to the physical media. This process includes proper write speed optimization and error checking.

[1325] Input: ISO image file

[1326] Output: Data written to physical media

[1327] Step 10:

[1328] The data storage device stores the high-definition data on the cloud, allowing users to view it via streaming.

[1329] Specific operation: The data storage device stores the high-definition data in the cloud and provides it to users through streaming distribution functions. Users can watch it in real time using a dedicated application.

[1330] Input: High-resolution digital data

[1331] Output: Streaming service

[1332] Example prompt: "I want to enhance the quality of a 1980s home videotape by removing noise, enhancing resolution, and correcting color frame by frame, and then finally streaming it."

[1333] 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.

[1334] This invention relates to a system that utilizes AI technology and an emotion engine to convert footage from old videotapes into high-quality images, and then performs a series of processes to ultimately dub the footage onto digital media such as DVDs. This system consists of four parts: the user, the terminal, the server, and the emotion engine. The specific roles and processes of each part are explained below in detail.

[1335] 1. Digitization of videotapes

[1336] First, the user inserts an old videotape into a dedicated digitizing device. The user operates the digitizing device and starts playing the videotape. The device captures the analog video signal from the videotape and converts it into a digital signal. The device uses the video capture device to save the video signal in a digital data format such as AVI or MP4 and transmits it to the server. Through this digitizing process, the contents of the old videotape are newly saved as digital data.

[1337] 2. Pretreatment

[1338] The server analyzes the digital data sent from the device and extracts basic video characteristics (resolution, frame rate, color information, etc.). This analysis is used to evaluate the quality of the data. The server then applies a noise reduction algorithm to remove unwanted noise from the digital data. This noise reduction uses spatial filtering and frequency filtering techniques. The server then uses super-resolution technology to improve the resolution of the digital data, which sharpens the image details and produces higher-quality images. The server then applies a color correction filter to adjust the color balance of the image. This series of pre-processing steps significantly improves the quality of the base video data.

[1339] 3. High image quality using AI

[1340] After preprocessing is complete, the server uses AI (deep learning models) to enhance the image quality of the video. Specifically, the server analyzes each frame of the video and processes it to reproduce fine details. This is done using technology that improves the clarity of each frame. AI-based image enhancement significantly improves the beauty and quality of the details of the video. The server repeats this process multiple times to generate video data of optimal quality.

[1341] 4. Video editing using emotion engine

[1342] The server uses an emotion engine to recognize the user's emotions. The emotion engine uses sensor devices such as cameras and microphones to analyze emotions from the user's facial expressions and voice. Based on the user's emotions, the server automatically adjusts video editing parameters. Specifically, if the user expresses joy, the server will make the video's color correction more vivid and add positive effects. On the other hand, if the user expresses sadness, the server will adjust the video's tone to a more subdued color tone.

[1343] 5. Digital conversion and dubbing

[1344] Once the high-quality, emotion-edited video data is generated, the server converts it into a DVD-format ISO image file. Specifically, the server compresses and formats the data using MPEG-2 encoding. This ISO image file can then be written directly to a DVD. This data is then sent from the server to the device.

[1345] The device connects the received ISO image file to a DVD burner and prompts the user to insert DVD media. After the user inserts DVD media, the device copies the ISO image file to DVD. This copying process includes proper optimization for writing speed and error checking.

[1346] 6. Delivery to User

[1347] Finally, the user receives the completed DVD, which can be played back at home or in any other playback environment to enjoy the high-definition images.

[1348] Specific examples

[1349] For example, consider a user who wants to digitize a home videotape from the 1990s. The tape contains footage of a children's sports day. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives the digital data and performs noise reduction, resolution enhancement, and color correction. Next, the server uses AI technology to further enhance the image quality and uses an emotion engine to recognize the user's emotions, such as joy or nostalgia, and adjust the image's color tone and effects accordingly. Finally, the server encodes the video data into DVD format and copies the data to a DVD. The user receives the DVD, plays it, and enjoys the crisp, emotionally tailored video.

[1350] In this way, this system can revive old videotape footage as modern, high-definition digital video, and by editing the video according to the user's emotions, it can provide a more moving viewing experience.

[1351] The processing flow will be explained below.

[1352] Step 1:

[1353] A user inserts an old videotape into a dedicated digitizing device, and then operates the digitizing device to start playing the videotape.

[1354] Step 2:

[1355] The device captures the analog video signal from the videotape and converts it to a digital signal. The device uses a video capture device to save the video signal in a digital data format such as AVI or MP4.

[1356] Step 3:

[1357] The terminal transmits the digitized video data to the server, where it uses an appropriate compression format to optimize the data size.

[1358] Step 4:

[1359] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information), which is then used to evaluate the quality of the data.

[1360] Step 5:

[1361] The server applies noise reduction processing, specifically using noise reduction algorithms such as spatial filtering and frequency filtering to reduce noise in the video.

[1362] Step 6:

[1363] The server performs the resolution enhancement process, using super-resolution techniques based on deep learning models (e.g., SRGAN) to improve the image resolution. This process focuses on reproducing fine details.

[1364] Step 7:

[1365] The server performs color correction processing, adjusting the color balance of the video using automatic white balance adjustment and color correction filters. This process restores natural color tones.

[1366] Step 8:

[1367] The server then uses the pre-processed data to perform AI-based image enhancement, applying deep learning models to each frame of the video to improve detail and clarity. This process is repeated multiple times.

[1368] Step 9:

[1369] The server uses an emotion engine to recognize the user's emotions. The emotion engine captures and analyzes the user's facial expressions and voice through sensor devices such as the device's camera and microphone.

[1370] Step 10:

[1371] The emotion engine analyzes the user's emotions (e.g., joy or sadness) and sends the information to the server, which then automatically adjusts the video editing parameters based on this information.

[1372] Step 11:

[1373] The server applies color correction and effects to the video based on the user's emotions. Specifically, if the user expresses joy, the video will be adjusted to a clearer, brighter tone and a more positive effect will be added. If the user expresses sadness, the video will be adjusted to a more muted tone.

[1374] Step 12:

[1375] The server converts the high-quality, emotion-edited video data into a DVD-format ISO image file. Specifically, the server compresses and formats the data using MPEG-2 encoding.

[1376] Step 13:

[1377] The server sends the generated ISO image file to the device, which receives the data and checks for errors.

[1378] Step 14:

[1379] The device prompts the user to insert a DVD, and the user inserts the DVD. The device uses a DVD writer to burn the ISO image file to a DVD. This process includes selecting the appropriate writing speed and checking for errors.

[1380] Step 15:

[1381] The user receives the completed DVD and can play it to check and enjoy the high-definition, emotionally edited footage.

[1382] Example 2

[1383] 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."

[1384] Old video recording media, especially videotapes, often experience deterioration over time, leading to a deterioration in image quality. Furthermore, when these videos are converted to modern digital media, they can contain noise and are often stored at low resolution. Furthermore, with conventional technologies, the process of improving the image quality and editing the video is often performed manually, resulting in inefficiencies. The present invention aims to solve these problems and provide a system that also enables video editing based on the user's emotions.

[1385] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1386] In this invention, the server includes means for converting video from an old video recording medium into digital data, means for transmitting the digital data to a computing device, means for removing noise from the digital data received by the computing device, means for improving the resolution of the digital data received by the computing device, means for performing color correction on the digital data received by the computing device, means for converting the high-quality video data into a recording medium format by the computing device, means for dubbing the data in the recording medium format onto a recording medium, means for recognizing a user's emotions and automatically adjusting video editing parameters based on the emotions, and means for performing an iterative process using AI to improve the quality of the generated video data. This makes it possible to convert video from old video recording media into digital media with high quality and in a manner that takes user emotions into consideration.

[1387] "Old video recording media" refers to physical media used to record video in the past, including videotapes and laser discs.

[1388] "Digital data" is data that has been converted from analog signals into a digital format, and is usually saved in a common video format such as AVI or MP4.

[1389] "Computing device" refers to a computer or server used to process digital data, and is equipment that performs advanced calculations and data analysis.

[1390] "Noise reduction" is a process that reduces unnecessary noise contained in video data, and uses techniques such as spatial filtering and frequency filtering.

[1391] "Resolution enhancement" is the process of converting low-resolution images into high-resolution images, and is carried out using super-resolution technology and artificial intelligence (AI).

[1392] "Color correction" is a process that adjusts the color balance of digital video data to make the overall color tone of the video appropriate.

[1393] A "recording medium format" is the file format used to store digital data on a particular recording medium (e.g., DVD or Blu-ray).

[1394] A "recording medium" is a medium for physically storing digital data, and includes, for example, DVDs and Blu-ray discs.

[1395] "User emotion" refers to the psychological state of the user as it is inferred from the facial expressions and voice of the user watching the video, and is analyzed using emotion recognition technology.

[1396] "Video editing parameters" refer to the setting values ​​and effects applied when editing video, including color correction and the type and strength of the effect.

[1397] "Iterative processing" is a technique in which the same process is repeated multiple times in order to improve the quality of video data, and is particularly used to improve image quality using AI.

[1398] This invention relates to a system that utilizes AI technology and an emotion engine to convert video from old video recording media into high-quality video, and then performs a series of processes to finally dub the video onto digital media. This system consists of four parts: the user, the terminal, the server, and the emotion engine. The specific roles and processes of each part are explained below in detail.

[1399] First, a user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device. Next, the user presses the play button on the digitizing device's operation panel to start playing the videotape. The terminal uses a video capture device (e.g., a general video capture device) to convert the analog video signal from the videotape into a digital signal. The converted digital signal is stored on the hard disk in a digital data format such as AVI or MP4. The terminal then transmits this digital data to a server via File Transfer Protocol (FTP) or a cloud storage service.

[1400] The server analyzes the received digital data and extracts basic video characteristics (resolution, frame rate, color information, etc.). This analysis is performed using libraries such as the FFmpeg library. The server then applies a noise reduction algorithm to remove unwanted noise from the digital data. For example, it uses OpenCV to apply Gaussian and Median filters. It also uses super-resolution techniques (such as the ESRGAN model) to improve the resolution of the digital data. The server then uses a color correction filter to adjust the hue, saturation, and lightness (HSL) to balance the color of the image.

[1401] After pre-processing, the server uses AI technology (deep learning models, such as SRGAN) to analyze each frame of the video and reproduce the details. This high-quality image processing is repeated multiple times to generate video data of optimal quality.

[1402] The server uses an emotion engine to recognize the user's emotions through sensor devices (cameras and microphones). For example, it uses the OpenFace library to perform facial expression analysis. It analyzes emotions from the user's facial and voice data and automatically adjusts video editing parameters based on those emotions. For example, if the user expresses joy, it will make the video's color correction more vivid and add positive effects.

[1403] After the high-quality, emotion-based video data is generated, the server converts it into a recording medium format, an ISO image file. This conversion uses MPEG-2 encoding. The server then sends the ISO image file to the device via FTP or a cloud storage service. The device receives the ISO image file and prompts the user to insert a DVD. When the user inserts the DVD, the device writes the ISO image file to a DVD, optimizing for proper writing speed and performing error checking.

[1404] Finally, the user receives the completed DVD and can play it at home or in any other playback environment to enjoy the high-definition images.

[1405] As a concrete example, consider a scenario in which a video of a young child's sports day recorded on a home videotape from the 1990s is digitized and converted to high-quality video. The user first inserts the tape into a digitizing device, which converts it into digital data. The server receives this digital data and performs noise reduction, resolution enhancement, and color correction. Next, the server uses AI technology to further enhance the video quality and uses an emotion engine to recognize the user's emotions and adjust the video's color tone and effects. Finally, the server encodes the video data into DVD format and copies the data to a DVD. The user receives the DVD, plays it, and enjoys the clear, emotionally edited video.

[1406] An example of a prompt for a generative AI model is shown below.

[1407] "Convert footage of young children's sports day recorded on a home videotape from the 1990s into high-resolution footage and edit it to suit the user's emotions."

[1408] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1409] Step 1:

[1410] A user inserts an old video recording medium (e.g., a videotape) into a dedicated digitizing device and presses the play button to start playing the tape. The inputs are the videotape and the digitizing device, and the output is an analog video signal. In operation, the user operates the device to play the videotape.

[1411] Step 2:

[1412] A device uses a video capture device to capture analog video signals and convert them to digital signals. The input is an analog video signal, and the output is digital video data (e.g., an AVI or MP4 file). In operation, the capture device receives the signal, converts it to digital data, and stores it on the hard disk.

[1413] Step 3:

[1414] The device sends the stored digital video data to the server. The input is the digital video file, and the output is the file transferred to the server. In operation, the device sends the data using the FTP protocol or a cloud storage service.

[1415] Step 4:

[1416] The server analyzes the received digital data and extracts basic video characteristics (e.g., resolution, frame rate, color information). The input is a digital video file, and the output is video characteristic data. In operation, the FFmpeg library is used to obtain video characteristic information.

[1417] Step 5:

[1418] The server applies a noise reduction algorithm to reduce unnecessary noise from the digital data. The input is image characteristic data and digital image data, and the output is noise-reduced digital image data. In operation, OpenCV is used to apply Gaussian and Median filters.

[1419] Step 6:

[1420] The server uses super-resolution technology to improve the resolution of digital data. The input is digital video data with reduced noise, and the output is digital video data with improved resolution. In operation, the ESRGAN model is applied to convert low-resolution video to high-resolution.

[1421] Step 7:

[1422] The server applies a color correction filter to balance the color of digital video. The input is high-resolution digital video data, and the output is color-corrected digital video data. The operation involves adjusting the hue, saturation, and lightness (HSL) values.

[1423] Step 8:

[1424] The server uses AI technology to analyze each frame of video and perform image quality enhancement processing. The input is color-corrected digital video data, and the output is image quality-enhanced digital video data. It operates by repeatedly analyzing each frame and reproducing details using an SRGAN model.

[1425] Step 9:

[1426] The server uses an emotion engine to recognize the user's emotions through sensor devices. The input is the user's facial expression and voice data, and the output is analyzed emotional data. Facial expression analysis is performed using the OpenFace library.

[1427] Step 10:

[1428] The server automatically adjusts video editing parameters based on the user's emotional data. The input is emotional data and high-quality digital video data, and the output is video data edited based on the emotion. The operation involves adjusting color tones and adding effects.

[1429] Step 11:

[1430] The server converts the emotion-edited video data into an ISO image file in a recording medium format. The input is emotion-edited video data, and the output is an ISO image file. In operation, the ISO file is generated using MPEG-2 encoding.

[1431] Step 12:

[1432] The server sends the generated ISO image file to the terminal. The input is the ISO image file, and the output is the ISO image file transferred to the terminal. The operation is to send data using the FTP protocol or cloud storage service.

[1433] Step 13:

[1434] The terminal receives the ISO image file and displays instructions to the user to insert the DVD media. The input is the ISO image file and the output is the display instructions to the user. The operation is to display the instructions through a GUI.

[1435] Step 14:

[1436] The user inserts a DVD media into the device, and the action is to insert the appropriate media to burn the ISO image file to a DVD.

[1437] Step 15:

[1438] The terminal writes the ISO image file to the DVD media inserted by the user. The input is the ISO image file and the DVD media, and the output is the completed DVD. The operation proceeds while optimizing the writing speed and checking for errors.

[1439] Step 16:

[1440] The user receives the completed DVD and can play it at home or in another playback environment to enjoy the high-definition video. The operation involves receiving the completed DVD and watching it on a playback device.

[1441] Example prompts for generative AI models

[1442] "Convert footage of young children's sports day recorded on a home videotape from the 1990s into high-resolution footage and edit it to suit the user's emotions."

[1443] (Application example 2)

[1444] 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."

[1445] Videos stored on old recording media generally have low image quality and a lot of noise, making the viewing experience inferior to modern high-definition video. Furthermore, there is no system that can digitize and store these videos, as well as edit them emotionally and stream them. Therefore, there is a need to revive old videos using modern technology and provide a more emotional viewing experience.

[1446] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1447] In this invention, the server includes a means for adjusting the effects of the high-definition video data based on emotion analysis, a means for converting the data into a digital medium format using a connection device, and a means for writing the converted data to a recording medium. This makes it possible to digitize and improve the image quality of video data stored on old recording media, edit the data based on emotions, and then stream the data.

[1448] "Old recording media" refers to videotapes and other analog storage media used to record video data in the past.

[1449] "Digital data" refers to video data that has been converted into a format that can be processed by a computer.

[1450] A "server" is a central computer that provides services to other computers and devices over a network.

[1451] "Noise reduction" is a process for removing unnecessary noise components from digital data.

[1452] "Resolution enhancement" is a technique for converting video data into a higher resolution in order to improve the image quality of the data.

[1453] "Color correction" is a process of adjusting the color tone of video data to create a more natural and visually pleasing image.

[1454] "Emotion analysis" is a technology that analyzes the user's emotions and adjusts the video effects and color tone based on the results.

[1455] A "digital media format" is a format in which digital data can be converted into a particular format and stored on a suitable recording medium.

[1456] "Recording media" refers to media such as DVDs and Blu-ray discs for storing digital data.

[1457] "Streaming distribution" is a technology that transfers data in real time over a network and plays it back.

[1458] This system converts video from old recording media into digital data, edits it based on the user's preferences, and delivers high-quality video via streaming. This section explains the basic components of this system and their roles.

[1459] 1. Digitizing Devices and User Operation

[1460] A user inserts an old recording medium (e.g., a videotape) into a dedicated digitizing device. The digitizing device uses a video capture device to convert the recording medium's analog video signal into a digital signal. This digital data is saved in a format such as AVI or MP4 and sent to a server via the terminal.

[1461] 2. Data Preprocessing

[1462] The server first analyzes the basic characteristics of the received digital data and extracts information such as resolution, frame rate, and color. It then uses specialized software (e.g., OpenCV) to perform preprocessing such as noise reduction, resolution enhancement, and color correction. Spatial filtering and frequency filtering are applied without omission for noise reduction.

[1463] 3. High image quality using AI

[1464] After preprocessing, the server applies a generative AI model (e.g., using TensorFlow or PyTorch) to the data to enhance image quality. Using deep learning models, it analyzes each frame of the video and performs operations such as enhancing details. This significantly improves the quality and detail of the image.

[1465] 4. Editing with Emotion Engine

[1466] The server uses an emotion engine (e.g., DeepFace) to analyze the user's emotions. This involves collecting and analyzing facial expressions and audio via a camera and microphone. The color tone and effects of the video are automatically adjusted according to the user's emotions. For example, if the user expresses happiness, the video will be adjusted to be more vibrant, and conversely, if the user expresses sadness, the colors will be muted.

[1467] 5. Digital media conversion and dubbing of video

[1468] The high-quality, emotion-edited video data is then converted by the server into a digital media format (e.g., a DVD-format ISO image file). This process uses MPEG-2 encoding to ensure optimal quality. The converted ISO image file is then written to a recording medium (e.g., a DVD) via the terminal.

[1469] 6. Streaming

[1470] Finally, the edited video data is streamed through a distribution server, and users can share the link to enjoy the high-quality, emotionally enriched video with family and friends.

[1471] Specific examples

[1472] For example, if a user digitizes a videotape of a child's birthday party and edits it based on the emotion of "joy," the footage will have a vibrant, positive effect. This footage can then be shared with family and friends through a streaming service, breathing new life into old recordings and providing a modern viewing experience.

[1473] Example prompt: "Based on your feelings of joy, edit a high-quality video of your child's birthday party and share it via streaming with your family."

[1474] This system brings old footage back to life vividly using modern technology, providing a special viewing experience tailored to the user's emotions.

[1475] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1476] Step 1:

[1477] Users insert old recording media (e.g., videotape) into a dedicated digitizing device. The digitizing device uses a video capture device to convert the analog video signal into a digital signal. This digital signal is then saved on a smartphone or PC in a format such as AVI or MP4. The input is the old recording media, and the output is video data in digital format. This conversion allows users to easily digitize past footage.

[1478] Step 2:

[1479] The terminal sends digitized video data to the server. The input is digitized video data, and the output is data sent to the server. The server receives and stores this data. Through this process, the digital video is aggregated on the server.

[1480] Step 3:

[1481] The server analyzes the received digital data and extracts the basic characteristics of the video (resolution, frame rate, color information). The input is digital video data, and the output is the extracted video characteristic information. Computer vision techniques such as OpenCV are used for the analysis. This process allows for the quality evaluation of the video data.

[1482] Step 4:

[1483] The server performs noise reduction based on the extracted basic characteristic information. The input is the characteristic information and digital video data, and the output is the noise-removed video data. Spatial filtering and frequency filtering techniques are used for noise reduction, which removes unnecessary noise from the video.

[1484] Step 5:

[1485] The server performs resolution enhancement processing on the noise-removed video data. The input is noise-removed video data, and the output is video data with improved resolution. This processing uses super-resolution technology, which enhances the details of the image and achieves higher image quality.

[1486] Step 6:

[1487] The server performs color correction on the video data with improved resolution. The input is high-quality video data, and the output is color-corrected video data. This adjusts the color balance and makes the video's color tone natural.

[1488] Step 7:

[1489] The server uses an emotion engine to analyze the user's emotions. The input is the user's facial expressions and voice data, and the output is analyzed emotional information. This analysis uses data acquired through a camera and microphone. This results in a numerical evaluation of the user's emotions.

[1490] Step 8:

[1491] The server automatically adjusts the video effects and color tone based on the analyzed emotional information. The input is emotional information and color-corrected video data, and the output is video data edited based on the emotions. This allows the video to be customized to match the user's emotions.

[1492] Step 9:

[1493] The server converts the edited video data into a digital media format (e.g., a DVD-format ISO image file). The input is the emotion-based edited video data, and the output is the digital media format data. MPEG-2 encoding is used for the conversion, which prepares the video data in a format suitable for recording media.

[1494] Step 10:

[1495] The terminal writes the converted ISO image file to a recording medium. The input is data in digital media format, and the output is data written to the recording medium. Specifically, the user inserts a recording medium (e.g., a DVD) according to instructions, and the terminal executes the writing process.

[1496] Step 11:

[1497] The edited video data is distributed through a streaming distribution server. The input is data written to a recording medium, and the output is video data distributed in real time. Users can share the distribution link with family and friends, providing them with a high-quality, emotionally-driven viewing experience.

[1498] Example prompt: "Based on your feelings of joy, edit a high-quality video of your child's birthday party and share it via streaming with your family."

[1499] Through the above steps, the present invention provides a system that can enhance the quality of old footage using modern technology, and then edit it based on emotions before sharing it.

[1500] 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.

[1501] 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.

[1502] 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.

[1503] 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.

[1504] 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.

[1505] 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.

[1506] 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).

[1507] 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.

[1508] 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."

[1509] 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.

[1510] 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).

[1511] 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.

[1512] 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.

[1513] 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.

[1514] 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.

[1515] 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.

[1516] 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.

[1517] 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.

[1518] 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.

[1519] 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.

[1520] 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.

[1521] The following is further disclosed regarding the above embodiment.

[1522] (Claim 1)

[1523] A means of converting old videotape footage into digital data,

[1524] means for transmitting the digital data to a server;

[1525] means for filtering out noise from the digital data received by the server;

[1526] means for increasing the resolution of the digital data received by the server;

[1527] means for performing color correction on the digital data received by the server;

[1528] A means for the server to convert the high-definition video data into DVD format,

[1529] A means for dubbing DVD format data onto a recording medium;

[1530] A system including:

[1531] (Claim 2)

[1532] 2. The system of claim 1, wherein the denoising of the digital data is performed by spatial filtering or frequency filtering.

[1533] (Claim 3)

[1534] 2. The system according to claim 1, wherein the resolution of the digital data is increased by super-resolution technology.

[1535] "Example 1"

[1536] Claims

[1537] (Claim 1)

[1538] A means of converting old videotape footage into digital data,

[1539] means for transmitting the digital data to a server;

[1540] means for removing noise from the digital data received by the server from the terminal;

[1541] means for increasing the resolution of digital data received by the server from the terminal;

[1542] means for performing color correction on the digital data received by the server from the terminal;

[1543] The server uses deep learning technology to improve the image quality of digital data.

[1544] A means for the server to convert the high-definition video data into DVD format,

[1545] A means for dubbing DVD format data onto a recording medium;

[1546] A system including:

[1547] (Claim 2)

[1548] 2. The system of claim 1, wherein the denoising of the digital data is performed by spatial filtering or frequency filtering.

[1549] (Claim 3)

[1550] 2. The system according to claim 1, wherein the resolution of the digital data is increased by super-resolution technology.

[1551] "Application Example 1"

[1552] (Claim 1)

[1553] A means for converting images from old video recording media into digital data;

[1554] means for transmitting the digital data to a data storage device;

[1555] means for removing noise from the digital data received by the data storage device;

[1556] means for increasing the resolution of the digital data received by the data storage device;

[1557] means for performing color correction on the digital data received by the data storage device;

[1558] a means for converting the high-definition video data into a digital disc format by the data storage device;

[1559] means for writing data in digital disc format to a physical medium;

[1560] A means for processing and streaming user-owned video on the cloud;

[1561] A means for enabling a user to view high-definition video on a terminal;

[1562] A system including:

[1563] (Claim 2)

[1564] 2. The system of claim 1, wherein the denoising of the digital data is performed by spatial filtering or frequency filtering.

[1565] (Claim 3)

[1566] 2. The system according to claim 1, wherein the resolution of the digital data is increased by super-resolution technology.

[1567] "Example 2: Combining Emotion Engines"

[1568] (Claim 1)

[1569] A means for converting images from old video recording media into digital data;

[1570] means for transmitting the digital data to a computing device;

[1571] means for filtering noise from digital data received by the computing device;

[1572] means for increasing the resolution of digital data received by the computing device;

[1573] means for performing color correction on the digital data received by the computing device;

[1574] A means for converting the image data with high image quality into a recording medium format by a computing device;

[1575] means for dubbing data in a recording medium format onto a recording medium;

[1576] means for recognizing a user's emotion and automatically adjusting video editing parameters based on the emotion;

[1577] A means of iteratively improving the quality of the generated video data using AI;

[1578] A system including:

[1579] (Claim 2)

[1580] 2. The system of claim 1, wherein the denoising of the digital data is performed by spatial filtering or frequency filtering.

[1581] (Claim 3)

[1582] The system of claim 1, wherein the resolution of the digital data is improved using super-resolution technology and AI technology.

[1583] "Application example 2 when combining emotion engines"

[1584] (Claim 1)

[1585] A means of converting images from old recording media into digital data;

[1586] means for transmitting the digital data to a server;

[1587] means for filtering out noise from the digital data received by the server;

[1588] means for increasing the resolution of the digital data received by the server;

[1589] means for performing color correction on the digital data received by the server;

[1590] A means for adjusting the effect of the high-definition video data by the server based on emotion analysis;

[1591] A means for the server to convert the high-definition video data into a digital media format;

[1592] means for writing data in a digital medium format onto a recording medium;

[1593] means for distributing the written data;

[1594] A system including:

[1595] (Claim 2)

[1596] 2. The system of claim 1, wherein the denoising of the digital data is performed by spatial filtering or frequency filtering.

[1597] (Claim 3)

[1598] 2. The system according to claim 1, wherein the resolution of the digital data is increased by super-resolution technology. [Explanation of symbols]

[1599] 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 of converting old videotape footage into digital data, means for transmitting the digital data to a server; means for filtering out noise from the digital data received by the server; means for increasing the resolution of the digital data received by the server; means for performing color correction on the digital data received by the server; A means for the server to convert the high-definition video data into DVD format, A means for dubbing DVD format data onto a recording medium; A system including:

2. 2. The system of claim 1, wherein the denoising of the digital data is performed by spatial filtering or frequency filtering.

3. 2. The system according to claim 1, wherein the resolution of the digital data is increased by a super-resolution technique.

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