system

Abstract

We provide the system. [Solution] Means for receiving digital data, A means for analyzing the aforementioned digital data to identify important scenes, A means for automatically editing based on the identified important scenes, Means of providing edited digital data to users, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When editing photos and videos as growth records manually, time and skills are required, and there is a problem that it is not easy, especially in busy families. Also, the management of digital data is complicated, and it is difficult to effectively record and save emotional moments.

Means for Solving the Problems

[0005] The present invention provides a system that receives digital data and enables automated editing work by identifying important scenes using AI technology. This system enables easy uploading of data through a user interface, and also enables users to easily create high-quality growth records by using sentiment analysis technology to emphasize emotional moments in the edited content.

[0006] "Digital data" refers to information that can be stored and transmitted electronically, such as photographs and videos.

[0007] "Means of receiving" refers to a system that has the function of taking in digital data from an external source.

[0008] "Methods for analyzing and identifying important scenes" refers to technologies that analyze the content of digital data and identify scenes that are valuable to the user.

[0009] "Methods for automatic editing" refer to mechanisms that process digital data based on analysis results without requiring human intervention.

[0010] "Means of providing to users" refers to a system that presents edited digital data in a form accessible to users.

[0011] "User interface" refers to the points of contact and operating environment through which a user interacts with a system and exchanges information.

[0012] "Emotional analysis" refers to the process of identifying and quantifying or classifying the emotions and moods of individuals contained in digital data. [Brief explanation of the drawing]

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

MODE FOR CARRYING OUT THE INVENTION

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0016] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

[0018] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

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

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is implemented as a system that allows users to easily edit and manage digital data as growth records via their own devices. Users can upload digital data to a server through their usual communication applications. This data includes photos and videos taken by the user.

[0035] The server uses advanced AI technology to analyze the received digital data. In the first stage of analysis, facial recognition and object recognition are used to identify scenes that are important to the user. Next, emotion analysis technology is applied to identify scenes of emotion such as joy and excitement. This allows for the automatic detection of special moments within the family.

[0036] Once the analysis is complete, the server performs automated editing accordingly. During editing, the selected important scenes are trimmed and combined with optimal visual and audio effects for output. These edited digital data are then presented to the user in a visually easy-to-understand manner through the user interface.

[0037] Users can download the completed content and then share their memories with family and friends using the system's sharing function. This system allows users to automatically and efficiently generate professional-quality growth records and effectively manage family memories.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The user opens a communication application on their device and selects photos and videos to record their child's growth. The process of uploading the selected digital data to the server then begins.

[0041] Step 2:

[0042] The terminal packets the digital data selected by the user and encodes it according to a security protocol. This encoded data is then sent to the server over the internet.

[0043] Step 3:

[0044] The server decodes the encoded digital data received from the terminal and securely stores it in cloud storage. It also simultaneously records data metadata (e.g., date and time of capture, data format).

[0045] Step 4:

[0046] The server activates an AI analysis module to analyze the stored digital data. It uses a facial recognition algorithm to identify family members. Furthermore, it performs emotion analysis to detect emotional moments such as smiling or crying.

[0047] Step 5:

[0048] Based on the analysis results, the server begins automatically editing the digital data. It extracts important scenes, applies corresponding editing templates, and performs trimming, scene transition effects, and music insertion.

[0049] Step 6:

[0050] The server temporarily stores the completed, edited content in cloud storage and sends a download link to the user's device.

[0051] Step 7:

[0052] Users download the edited content using a link sent to their device and share the memories with family and friends.

[0053] (Example 1)

[0054] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0055] In modern society, a vast amount of digital information is generated, and there is a need for a means to efficiently identify important moments and information with emotional value from this data, and to effectively manage and edit it as a record. However, conventional methods require manual editing, which is time-consuming and labor-intensive, and often requires specialized editing skills. To solve this problem, the challenge is to provide a system that automatically analyzes and edits important scenes and delivers them to the user.

[0056] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0057] In this invention, the server includes means for receiving information, means for analyzing the information to recognize important scenes, and means for automatically making changes based on the recognized important scenes. This makes it possible for users to easily identify valuable moments from a vast amount of digital information, automatically edit them, and use them as professional-quality content.

[0058] "Means for receiving information" refers to a configuration that has the function of taking in digital data from an external source.

[0059] "Means of analyzing information to recognize important scenes" refers to a function that uses advanced algorithms to analyze captured digital data and automatically identify scenes that are considered important to the user.

[0060] "Means of making changes automatically" refers to a function that automatically edits digital data based on recognized important scenes.

[0061] "Means of presentation" refers to functions that provide edited digital data in a way that is easy for users to review.

[0062] A "user interface" is an interactive interface that allows users to operate a system and send and receive information.

[0063] "Methods for performing sentiment analysis and highlighting emotional moments during changes" refers to functions that analyze the emotions contained in scenes within digital data and highlight those emotionally valuable moments during recording.

[0064] This invention provides a system for users to efficiently manage and edit digital data. Users can typically upload photos and videos they take on a daily basis using devices such as smartphones or personal computers to a server via common communication applications. This uploaded data is securely stored in the system's cloud storage.

[0065] The server utilizes advanced AI technology to analyze this digital data. Specifically, it uses an AI platform (for example, a general-purpose cloud AI service) for processing such as face recognition and object recognition. In the first stage of analysis, the server uses these AI technologies to identify important scenes within the digital data. This process makes it possible, for example, to automatically extract particularly precious moments from family photos.

[0066] Next, the server performs sentiment analysis. This is to identify emotional scenes, such as joy and excitement, contained in the photos and videos. By using AI technology, it is possible to highlight and edit scenes that contain emotional value.

[0067] During the editing process, the server uses an automated editing function to trim the selected key scenes. It then uses dedicated software (e.g., general video editing software) to combine optimal visual and audio effects for the final output. The edited content is presented to the user through a dedicated user interface.

[0068] Users can download the completed content and easily share it with family and friends using the system's sharing function. This system allows users to efficiently create professional-quality growth records and easily manage their memories.

[0069] An example of a prompt might be: "I've uploaded photos and videos from our family trip. Please generate a 5-minute video clip summarizing our heartwarming memories."

[0070] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0071] Step 1:

[0072] Users upload digital data (e.g., photos and videos) to a server using their device. The input consists of files selected on the device, and the output is saved to the server's cloud storage. This process is conducted via a communication application over a secure network connection.

[0073] Step 2:

[0074] The server analyzes the uploaded data. The input is the digital data saved in step 1. The server uses AI technology to perform face recognition and object recognition to identify important scenes within the digital data. The output generates various metadata for the identified important scenes. In this specific operation, the AI ​​algorithm extracts patterns of people and objects from the data and determines their importance.

[0075] Step 3:

[0076] The server performs sentiment analysis on the identified scenes. The input is metadata of the key scenes obtained in step 2. The server runs its sentiment analysis engine and assigns emotional labels such as joy and emotion to each scene. This data processing generates a dataset as output in which emotional value is quantified. In the specific operation of this step, the AI ​​evaluates the emotional tone by analyzing changes in voice and facial expressions.

[0077] Step 4:

[0078] The server executes an automated editing process based on the data generated in the previous step. The input here is scene metadata with emotion labels assigned to it. The server automatically performs trimming, color adjustment, and background music insertion using appropriate visual editing software. The output is a professional-quality edited content file. In this specific operation, the video and music are effectively combined using a specified template.

[0079] Step 5:

[0080] The server presents the edited content to the user through a user interface. The input is the content file generated in step 4. The server displays this file in a way that is easily visually evaluateable by humans. This process allows the user to interactively review the editing results as output. Specifically, this step involves playing the content using a preview function.

[0081] Step 6:

[0082] The user downloads the final content or shares it within the system. The input is the edited content presented by the server. The user downloads the file via their terminal or generates a link to share it with family and friends. The output is the URL of the downloaded file or shared content. This specific operation involves selecting and transferring the file format.

[0083] (Application Example 1)

[0084] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0085] Traditional methods for automatically analyzing user-submitted photos and videos to identify and edit important scenes require manual editing, which is time-consuming and labor-intensive. Furthermore, there is a lack of readily available and convenient ways to share the edited digital content.

[0086] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0087] In this invention, the server includes means for receiving digital information, means for analyzing the digital information to identify important scenes, and means for automatically editing based on the identified important scenes. This enables users to automatically and efficiently generate and easily share professional-quality edited digital content.

[0088] "Digital information" refers to all data stored and transmitted in electronic format, including photographs, videos, and audio files.

[0089] A "user interface" is a means by which a user operates a system or device and accesses its functions, and can take the form of physical buttons, touchscreens, voice input, etc.

[0090] An "information processing device" refers to a device used for inputting, processing, and outputting data, and includes personal computers, smartphones, and cloud servers.

[0091] "Emotion analysis" is a technology that detects and analyzes emotional elements in digital information, and is a process of determining a person's emotional state from text, images, audio, etc.

[0092] A "critical moment" refers to a phase or moment in the digital information in question that the user should pay particular attention to, and which is identified by the system.

[0093] "Automatic editing" refers to a system independently processing digital information and creating final content without manual intervention from the user.

[0094] To realize this invention, a system is required in which a server and a user's terminal play the main roles. The server receives digital information from the user's terminal. This digital information includes data such as photographs and videos. The server uses AI technology to analyze the received digital information and perform a process of identifying important and emotionally significant scenes. Specifically, it uses software such as a facial recognition API and an emotion analysis API to identify scenes that are important and emotionally valuable to the user.

[0095] Next, based on the identified scenes, the server automatically performs editing. This editing involves trimming and adding optimal audio and visual effects to create visually appealing content for the user. The edited digital information is then provided in a downloadable format to the user's information processing device.

[0096] Users can control this entire process through the user interface. The interface includes features for uploading digital information, and for previewing, downloading, and sharing edited data.

[0097] As a concrete example, consider a scenario where a user takes photos and videos of a picnic in a park and uses this system to create an original video story. This video would automatically compile photos of the happy, smiling family and clips capturing touching moments. An example of a prompt to the generation AI model would be, "Create a video documenting a fun family holiday." This prompt would cause the system to generate content in the expected format.

[0098] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0099] Step 1:

[0100] The user's device prepares the captured photos and video data as digital information. This includes adding metadata after shooting and standardizing file formats. The digital information is uploaded to the server via the user interface. At this stage, the input is the photos and video files on the user's device, and the output is the files registered in the input queue on the server.

[0101] Step 2:

[0102] The server receives uploaded digital information and analyzes the received data. First, it uses a facial recognition API to identify people in photos and videos. Next, it applies an emotion analysis API to identify the emotions expressed by the detected people. The input is raw data uploaded by the user, and the output is analyzed data with facial recognition and emotion information attached.

[0103] Step 3:

[0104] The server identifies important scenes based on the analyzed data. In particular, it selects scenes that strongly express emotions such as joy and excitement. The input is the analyzed data, and the output is the selected important scene data.

[0105] Step 4:

[0106] The server automatically edits based on selected key scenes. It optimizes visual and auditory effects by trimming, applying filters, and adding music and sound effects. The input is key scene data, and the output is edited digital content.

[0107] Step 5:

[0108] The server provides the completed, edited content in a downloadable format to the user's information processing device. It also allows content preview through the user interface. The input is the edited digital data, and the output is the final file downloaded to the user's terminal.

[0109] Step 6:

[0110] The user downloads the provided content and shares it with friends and family using the sharing function as needed. The input is downloadable content, and the output is a video story saved in a format usable by the user. During this process, the prompt "Create a video documenting a fun family holiday" is applied to the generating AI model.

[0111] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0112] This invention relates to a system for efficiently editing digital data captured by a user, which incorporates an emotion engine to achieve advanced content editing based on the user's emotions. This system mainly consists of three main components: a server, a terminal, and a user interface.

[0113] Users upload digital data to a server via a communication application through their device. The server receives this digital data and analyzes it using AI technology. During the analysis phase, an emotion engine combining facial recognition and emotion analysis identifies the emotions of the user and the subject. This identifies scenes in the data that should be emphasized.

[0114] Next, the server selects an editing style optimized for the user's emotions based on the emotion data obtained from the emotion engine. This process results in an edit that effectively conveys the atmosphere and emotions the user desires. For example, if the user has a strong emotion of "joy," the system will apply bright and lively background music and effects to the edit.

[0115] Once editing is complete, the content is temporarily stored on the server, and a download link is sent to the user's device. Through this link, the user can easily download the edited content and share it with family and friends.

[0116] This system allows users to automatically and easily create special memories that reflect individual emotions and are of professional quality. For example, when users upload digital data taken at a family event, if the system detects the emotion of "emotion," it adds soothing background music and a slow-motion effect, generating a warm video suitable for a family album.

[0117] The following describes the processing flow.

[0118] Step 1:

[0119] The user opens a communication application on their device and selects the digital data (photos and videos) they want to edit. The user then begins uploading the data through the device's operation.

[0120] Step 2:

[0121] The terminal packets the selected digital data and encodes it based on a secure communication protocol. This encoded data is then sent to the server via the internet.

[0122] Step 3:

[0123] The server decodes the data received from the terminal and saves it to cloud storage. At the same time, it also records metadata about the data (such as the date and time of capture and location information).

[0124] Step 4:

[0125] The server analyzes the stored digital data using an emotion engine. It uses facial recognition technology to identify people in the video and emotion analysis algorithms to determine the emotional state of each person.

[0126] Step 5:

[0127] The server selects an appropriate editing style based on the identified emotion. For example, if the emotion of "joy" is dominant, it will run a program that selects bright visual effects and lively music.

[0128] Step 6:

[0129] Based on this information, the server automatically edits the digital data. It trims important scenes and applies selected effects and music to generate the edited content.

[0130] Step 7:

[0131] Once the edited content is complete, the server saves the file to cloud storage and sends a notification to the user's device. The notification includes a link to download the edited content.

[0132] Step 8:

[0133] Users can use their devices to check notifications and download edited content. They can then easily share their finished work with family and friends.

[0134] (Example 2)

[0135] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0136] In recent years, with the increase in digital data, there has been a growing need for methods that allow users to easily edit content based on their emotions. However, with conventional systems, editing in line with user emotions has been time-consuming and technically demanding, making it difficult. Therefore, there is a need for a system that can automatically and efficiently perform editing that reflects user emotions.

[0137] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0138] In this invention, the server includes a device for receiving digital information, a device for analyzing the digital information to identify a specific scene, a device for using an emotion engine that combines facial recognition and emotion analysis, a device for selecting an editing style based on prompt text using generative AI technology, a device for automatically editing according to the user's emotions, and a device for providing the edited digital information. This enables users to automatically and easily create special content of professional quality that reflects their individual emotions.

[0139] "Digital information" refers to all data expressed in electronic format, including images, audio, and video.

[0140] "Analysis" refers to the process of systematically examining data and extracting meaningful information from it.

[0141] "Facial recognition" refers to the technology that detects human faces from images and videos and identifies their characteristics.

[0142] "Emotional analysis" refers to the technology of analyzing and expressing a person's emotional state using numerical values ​​or indicators.

[0143] An "emotion engine" refers to a system that combines facial recognition and emotion analysis to analyze the emotional elements within digital information and output the results.

[0144] "Generative AI technology" refers to technology that uses artificial intelligence to automatically generate new data and content.

[0145] A "prompt message" refers to a sentence that indicates an instruction or inquiry input to a generative AI technology in order to produce a specific output.

[0146] "Editing style" refers to the format and method of editing applied to digital information according to its purpose and theme.

[0147] This invention provides a system for efficiently editing digital information captured by a user based on their emotions. This system mainly consists of a server, a terminal, and a user interface.

[0148] Users send digital information to a server via a communication application through their device. The server analyzes the received digital information and identifies specific scenes within it. The analysis uses an emotion engine that combines facial recognition and emotion analysis, along with video processing libraries and machine learning frameworks. Specifically, technologies such as OpenCV and TENSORFLOW® are utilized.

[0149] Based on data extracted through emotion analysis, the server uses generative AI technology to select an editing style. The selected editing style is optimized to match the user's desired atmosphere, and appropriate background music and effects are applied from the template library.

[0150] The edited content is temporarily stored on the server, and a download link is sent to the user's device. The user can then retrieve the edited content from this link and share it according to their individual needs.

[0151] As a concrete example, if a user uploads a video they filmed at a family gathering to the system, and the system detects the emotion of "emotion," the server will edit the video by combining soothing background music and a slow-motion effect. In this case, an example of a prompt to the generating AI model could be, "Please make the family gathering more emotionally moving."

[0152] This system allows users to automatically and easily create special content that is professional in quality and reflects their emotions.

[0153] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0154] Step 1:

[0155] The user uploads digital information captured using their device to a server via a communication application. At this stage, digital images and videos are used as input and transmitted to the server using a communication protocol. The data is then stored on the server as output.

[0156] Step 2:

[0157] The server analyzes the received digital information. Specifically, it uses libraries such as OpenCV to perform face recognition and detect human faces within the digital information. The received digital information is used as input, and metadata containing facial features is generated as output. Based on this metadata, candidate important scenes are identified.

[0158] Step 3:

[0159] The server performs sentiment analysis using an emotion engine. This utilizes AI frameworks such as TensorFlow to analyze the emotional state in each scene based on facial features. The input is the facial metadata and digital information, which are the output of step 2, and the output is the emotional information for each scene.

[0160] Step 4:

[0161] Based on the sentiment analysis results, the server uses generative AI technology to select an appropriate editing style. Specifically, a prompt sentence corresponding to the sentiment is input to the AI ​​model, and corresponding background music and effects are selected from a template library and output. The input consists of sentiment information and pre-configured prompt sentences, while the output consists of the selected editing style and related content.

[0162] Step 5:

[0163] The server applies the selected editing style and re-edits the digital information. This step involves actual video editing using video editing software. The input is the original digital information and editing style, and the output is the final edited digital information.

[0164] Step 6:

[0165] The server temporarily stores the edited digital information and sends a download link to the user's device. The input is the edited digital information, and the output is the download link. This link allows the user to download and share the content from their device.

[0166] (Application Example 2)

[0167] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0168] In today's world, where capturing and sharing digital data is easy, users are seeking to create unique content that reflects their individual emotions. However, traditional editing tools require manual editing, demanding high technical skills to achieve professional quality. Furthermore, providing a personalized experience based on user emotions has been difficult. Against this backdrop, there is a need for a system that allows users to easily and automatically perform advanced editing based on their own emotions.

[0169] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0170] In this invention, the server includes means for receiving digital data, means for analyzing the digital data to identify important scenes, means for automatically editing based on the identified important scenes, means for providing the edited digital data to the user, and means for selecting an emotion-based editing style using emotion analysis. This makes it possible for the user to automatically and easily create special content that corresponds to their own emotions.

[0171] "Digital data" refers to information resources such as audio, images, videos, and documents that have been converted into a digital format and can be processed, stored, and transmitted using electronic devices.

[0172] "Means of receiving" refers to methods or technologies for acquiring or incorporating digital data from external sources.

[0173] "Means of analysis to identify important scenes" refers to methods and techniques for analyzing digital data and identifying particularly noteworthy scenes or moments within it.

[0174] "Means of automatic editing" refer to systems and methods that minimize user intervention and perform editing tasks using programs or algorithms.

[0175] "Means of providing edited digital data" refers to methods and technologies that enable users to view, download, or use the edited digital data.

[0176] "Emotional analysis" is a technique or method for inferring and identifying a person's emotional state from facial expressions, tone of voice, and other factors.

[0177] "Methods for selecting an emotion-based editing style" refer to methods and techniques for determining the optimal editing method based on analyzed emotion data and then applying it.

[0178] The system implementing this invention mainly consists of a server, a terminal, and a user. The user can use the terminal to capture digital data and upload that data to the server via the terminal. The server analyzes the received digital data using facial recognition libraries such as OpenCV and deep learning frameworks such as TensorFlow and PyTorch to perform emotion analysis from facial expressions and voice tone. This allows for the identification of important scenes within the digital data and the determination of emotion-based editing content.

[0179] The server selects an editing style based on predefined emotional data, using identified key scenes. Based on the selected editing style, it uses the FFmpeg library to add background music and apply special effects to the digital data. Once the editing process is complete, the server temporarily stores the edited digital data and generates a link accessible to the user. The user can use this link to download, view, and share the edited digital data.

[0180] For example, when a user uploads a video they shot while traveling to the platform, the server detects scenes that convey emotions such as "surprise" or "joy." Based on the emotion analysis, exciting music and visual effects are automatically added to the video, providing the user with a customized viewing experience. This allows users to easily obtain an emotionally personalized experience that goes beyond simple video sharing.

[0181] An example of a prompt message could be: "The user has uploaded a video they filmed during their vacation. Analyze the user's main emotions from this video. Then, apply an editing style based on those emotions to create a distinctive and unique video."

[0182] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0183] Step 1:

[0184] The user uploads digital data captured with their smartphone camera to the system using a terminal. The input is the digital data captured by the user, and the uploaded data is stored on the server. The output is the state in which the server has received the digital data.

[0185] Step 2:

[0186] The server analyzes the received digital data. At this stage, it uses a face recognition library such as OpenCV to identify faces and expressions within the digital data. The input is the digital data received in step 1, and the output from the analysis is the identified face and expression information within the digital data.

[0187] Step 3:

[0188] Based on the analysis results, the server performs sentiment analysis using TensorFlow or PyTorch. This identifies emotional moments within the digital data. The input is the face and facial expression information obtained in step 2, and the output is the identified emotional moments and their tags.

[0189] Step 4:

[0190] The server selects the appropriate editing style based on the identified emotional moment. This includes selecting background music and applying special effects. The input is the emotional moment and its tag from step 3, and the output is the result of selecting the editing style to apply.

[0191] Step 5:

[0192] The server uses the FFmpeg library to edit the digital data according to the selected editing style. The input is the result of the editing style selection in step 4 and the original digital data, and the output is the edited digital data.

[0193] Step 6:

[0194] The edited digital data is temporarily stored on the server, and a download link is issued to the user. The input is the digital data edited in step 5, and the output is the state in which the download link has been generated.

[0195] Step 7:

[0196] The user can use their device to download, view, and share the edited digital data via the received download link. The input is the download link generated in step 6, and the output is the edited digital data saved on the user's device.

[0197] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0198] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0199] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0200] [Second Embodiment]

[0201] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0202] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0203] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0204] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0205] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0206] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0207] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0208] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0209] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0210] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0211] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0212] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0213] This invention is implemented as a system that allows users to easily edit and manage digital data as growth records via their own devices. Users can upload digital data to a server through their usual communication applications. This data includes photos and videos taken by the user.

[0214] The server uses advanced AI technology to analyze the received digital data. In the first stage of analysis, facial recognition and object recognition are used to identify scenes that are important to the user. Next, emotion analysis technology is applied to identify scenes of emotion such as joy and excitement. This allows for the automatic detection of special moments in the family.

[0215] Once the analysis is complete, the server performs automated editing accordingly. During editing, the selected important scenes are trimmed and combined with optimal visual and audio effects for output. These edited digital data are then presented to the user in a visually easy-to-understand manner through the user interface.

[0216] Users can download the completed content and then share their memories with family and friends using the system's sharing function. This system allows users to automatically and efficiently generate professional-quality growth records and effectively manage family memories.

[0217] The following describes the processing flow.

[0218] Step 1:

[0219] The user opens a communication application on their device and selects photos and videos to record their child's growth. The process of uploading the selected digital data to the server then begins.

[0220] Step 2:

[0221] The terminal packets the digital data selected by the user and encodes it according to a security protocol. This encoded data is then sent to the server over the internet.

[0222] Step 3:

[0223] The server decodes the encoded digital data received from the terminal and securely stores it in cloud storage. It also simultaneously records data metadata (e.g., date and time of capture, data format).

[0224] Step 4:

[0225] The server activates an AI analysis module to analyze the stored digital data. It uses a facial recognition algorithm to identify family members. Furthermore, it performs emotion analysis to detect emotional moments such as smiling or crying.

[0226] Step 5:

[0227] Based on the analysis results, the server begins automatically editing the digital data. It extracts important scenes, applies corresponding editing templates, and performs trimming, scene transition effects, and music insertion.

[0228] Step 6:

[0229] The server temporarily stores the completed, edited content in cloud storage and sends a download link to the user's device.

[0230] Step 7:

[0231] Users download the edited content using a link sent to their device and share the memories with family and friends.

[0232] (Example 1)

[0233] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0234] In modern society, a vast amount of digital information is generated, and there is a need for a means to efficiently identify important moments and information with emotional value from this data, and to effectively manage and edit it as a record. However, conventional methods require manual editing, which is time-consuming and labor-intensive, and often requires specialized editing skills. To solve this problem, the challenge is to provide a system that automatically analyzes and edits important scenes and delivers them to the user.

[0235] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0236] In this invention, the server includes means for receiving information, means for analyzing the information to recognize important scenes, and means for automatically making changes based on the recognized important scenes. This makes it possible for users to easily identify valuable moments from a vast amount of digital information, automatically edit them, and use them as professional-quality content.

[0237] "Means for receiving information" refers to a configuration that has the function of taking in digital data from an external source.

[0238] "Means of analyzing information to recognize important scenes" refers to a function that uses advanced algorithms to analyze captured digital data and automatically identify scenes that are considered important to the user.

[0239] "Means of making changes automatically" refers to a function that automatically edits digital data based on recognized important scenes.

[0240] "Means of presentation" refers to functions that provide edited digital data in a way that is easy for users to review.

[0241] A "user interface" is an interactive interface that allows users to operate a system and send and receive information.

[0242] "Methods for performing sentiment analysis and highlighting emotional moments during changes" refers to functions that analyze the emotions contained in scenes within digital data and highlight those emotionally valuable moments during recording.

[0243] This invention provides a system for users to efficiently manage and edit digital data. Users can typically upload photos and videos they take on a daily basis using devices such as smartphones or personal computers to a server via common communication applications. This uploaded data is securely stored in the system's cloud storage.

[0244] The server utilizes advanced AI technology to analyze this digital data. Specifically, it uses an AI platform (for example, a general-purpose cloud AI service) for processing such as face recognition and object recognition. In the first stage of analysis, the server uses these AI technologies to identify important scenes within the digital data. This process makes it possible, for example, to automatically extract particularly precious moments from family photos.

[0245] Next, the server performs sentiment analysis. This is to identify emotional scenes, such as joy and excitement, contained in the photos and videos. By using AI technology, it is possible to highlight and edit scenes that contain emotional value.

[0246] During the editing process, the server uses an automated editing function to trim the selected key scenes. It then uses dedicated software (e.g., general video editing software) to combine optimal visual and audio effects for the final output. The edited content is presented to the user through a dedicated user interface.

[0247] Users can download the completed content and easily share it with family and friends using the system's sharing function. This system allows users to efficiently create professional-quality growth records and easily manage their memories.

[0248] An example of a prompt might be: "I've uploaded photos and videos from our family trip. Please generate a 5-minute video clip summarizing our heartwarming memories."

[0249] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0250] Step 1:

[0251] Users upload digital data (e.g., photos and videos) to a server using their device. The input consists of files selected on the device, and the output is saved to the server's cloud storage. This process is conducted via a communication application over a secure network connection.

[0252] Step 2:

[0253] The server analyzes the uploaded data. The input is the digital data saved in step 1. The server uses AI technology to perform face recognition and object recognition to identify important scenes within the digital data. The output generates various metadata for the identified important scenes. In this specific operation, the AI ​​algorithm extracts patterns of people and objects from the data and determines their importance.

[0254] Step 3:

[0255] The server performs sentiment analysis on the identified scenes. The input is metadata of the key scenes obtained in step 2. The server runs its sentiment analysis engine and assigns emotional labels such as joy and emotion to each scene. This data processing generates a dataset as output in which emotional value is quantified. In the specific operation of this step, the AI ​​evaluates the emotional tone by analyzing changes in voice and facial expressions.

[0256] Step 4:

[0257] The server executes an automated editing process based on the data generated in the previous step. The input here is scene metadata with emotion labels assigned to it. The server automatically performs trimming, color adjustment, and background music insertion using appropriate visual editing software. The output is a professional-quality edited content file. In this specific operation, the video and music are effectively combined using a specified template.

[0258] Step 5:

[0259] The server presents the edited content to the user through a user interface. The input is the content file generated in step 4. The server displays this file in a way that is easily visually evaluateable by humans. This process allows the user to interactively review the editing results as output. Specifically, this step involves playing the content using a preview function.

[0260] Step 6:

[0261] The user downloads the final content or shares it within the system. The input is the edited content presented by the server. The user downloads the file via their terminal or generates a link to share it with family and friends. The output is the URL of the downloaded file or shared content. This specific operation involves selecting and transferring the file format.

[0262] (Application Example 1)

[0263] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0264] Traditional methods for automatically analyzing user-submitted photos and videos to identify and edit important scenes require manual editing, which is time-consuming and labor-intensive. Furthermore, there is a lack of readily available and convenient ways to share the edited digital content.

[0265] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0266] In this invention, the server includes means for receiving digital information, means for analyzing the digital information to identify important scenes, and means for automatically editing based on the identified important scenes. This enables users to automatically and efficiently generate and easily share professional-quality edited digital content.

[0267] "Digital information" refers to all data stored and transmitted in electronic format, including photographs, videos, and audio files.

[0268] A "user interface" is a means by which a user operates a system or device and accesses its functions, and can take the form of physical buttons, touchscreens, voice input, etc.

[0269] An "information processing device" refers to a device used for inputting, processing, and outputting data, and includes personal computers, smartphones, and cloud servers.

[0270] "Emotion analysis" is a technology that detects and analyzes emotional elements in digital information, and is a process of determining a person's emotional state from text, images, audio, etc.

[0271] A "critical moment" refers to a phase or moment in the digital information in question that the user should pay particular attention to, and which is identified by the system.

[0272] "Automatic editing" refers to a system independently processing digital information and creating final content without manual intervention from the user.

[0273] To realize this invention, a system is required in which a server and a user's terminal play the main roles. The server receives digital information from the user's terminal. This digital information includes data such as photographs and videos. The server uses AI technology to analyze the received digital information and perform a process of identifying important and emotionally significant scenes. Specifically, it uses software such as a facial recognition API and an emotion analysis API to identify scenes that are important and emotionally valuable to the user.

[0274] Next, based on the identified scenes, the server automatically performs editing. This editing involves trimming and adding optimal audio and visual effects to create visually appealing content for the user. The edited digital information is then provided in a downloadable format to the user's information processing device.

[0275] Users can control this entire process through the user interface. The interface includes features for uploading digital information, and for previewing, downloading, and sharing edited data.

[0276] As a concrete example, consider a scenario where a user takes photos and videos of a picnic in a park and uses this system to create an original video story. This video would automatically compile photos of the happy, smiling family and clips capturing touching moments. An example of a prompt to the generation AI model would be, "Create a video documenting a fun family holiday." This prompt would cause the system to generate content in the expected format.

[0277] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0278] Step 1:

[0279] The user's device prepares the captured photos and video data as digital information. This includes adding metadata after shooting and standardizing file formats. The digital information is uploaded to the server via the user interface. At this stage, the input is the photos and video files on the user's device, and the output is the files registered in the input queue on the server.

[0280] Step 2:

[0281] The server receives uploaded digital information and analyzes the received data. First, it uses a facial recognition API to identify people in photos and videos. Next, it applies an emotion analysis API to identify the emotions expressed by the detected people. The input is raw data uploaded by the user, and the output is analyzed data with facial recognition and emotion information attached.

[0282] Step 3:

[0283] The server identifies important scenes based on the analysis data. In particular, it selects scenes where emotions such as joy and感动 are strongly expressed. The input is the analyzed data, and the output is the selected important scene data.

[0284] Step 4:

[0285] The server performs automatic editing based on the selected important scenes. It performs trimming processing, applies filters, and adds music and sound effects to optimize visual and acoustic effects. The input is the important scene data, and the output is the edited digital content.

[0286] Step 5:

[0287] The server provides the completed edited content in a format that can be downloaded to the user's information processing device. It also enables preview of the content through the user interface. The input is the edited digital data, and the output is the final file downloaded to the user terminal.

[0288] Step 6:

[0289] The user downloads the provided content and shares the content with friends and family using the sharing function if necessary. The input is the downloadable content, and the output is the video story saved in a form that can be used by the user. In this process, "Create a video recording a happy family holiday" is applied as a prompt sentence to the generation AI model.

[0290] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions.

[0291] This invention relates to a system for efficiently editing digital data captured by a user, which incorporates an emotion engine to achieve advanced content editing based on the user's emotions. This system mainly consists of three main components: a server, a terminal, and a user interface.

[0292] Users upload digital data to a server via a communication application through their device. The server receives this digital data and analyzes it using AI technology. During the analysis phase, an emotion engine combining facial recognition and emotion analysis identifies the emotions of the user and the subject. This identifies scenes in the data that should be emphasized.

[0293] Next, the server selects an editing style optimized for the user's emotions based on the emotion data obtained from the emotion engine. This process results in an edit that effectively conveys the atmosphere and emotions the user desires. For example, if the user has a strong emotion of "joy," the system will apply bright and lively background music and effects to the edit.

[0294] Once editing is complete, the content is temporarily stored on the server, and a download link is sent to the user's device. Through this link, the user can easily download the edited content and share it with family and friends.

[0295] This system allows users to automatically and easily create special memories that reflect individual emotions and are of professional quality. For example, when users upload digital data taken at a family event, if the system detects the emotion of "emotion," it adds soothing background music and a slow-motion effect, generating a warm video suitable for a family album.

[0296] The following describes the processing flow.

[0297] Step 1:

[0298] The user opens a communication application using their own terminal and selects the digital data (photos or videos) to be edited. The user starts uploading the data through the operations of the terminal.

[0299] Step 2:

[0300] The terminal packets the selected digital data and encodes it based on a secure communication protocol. This encoded data is sent to the server via the Internet.

[0301] Step 3:

[0302] The server decodes the data received from the terminal and stores it in cloud storage. At the same time, it also records the meta-information of the data (such as shooting date and location information).

[0303] Step 4:

[0304] The server analyzes the stored digital data using an emotion engine. It uses face recognition technology to identify the people in the video and an emotion analysis algorithm to determine the emotional state of each person.

[0305] Step 5:

[0306] Based on the identified emotions, the server selects an appropriate editing style. For example, if the emotion of "joy" is dominant, it executes a program to select bright video effects and lively music.

[0307] Step 6:

[0308] Based on this information, the server automatically edits the digital data. By trimming important scenes and applying the selected effects and music, it generates the edited content.

[0309] Step 7:

[0310] Once the edited content is complete, the server saves the file to cloud storage and sends a notification to the user's device. The notification includes a link to download the edited content.

[0311] Step 8:

[0312] Users can use their devices to check notifications and download edited content. They can then easily share their finished work with family and friends.

[0313] (Example 2)

[0314] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0315] In recent years, with the increase in digital data, there has been a growing need for methods that allow users to easily edit content based on their emotions. However, with conventional systems, editing in line with user emotions has been time-consuming and technically demanding, making it difficult. Therefore, there is a need for a system that can automatically and efficiently perform editing that reflects user emotions.

[0316] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0317] In this invention, the server includes a device for receiving digital information, a device for analyzing the digital information to identify a specific scene, a device for using an emotion engine that combines facial recognition and emotion analysis, a device for selecting an editing style based on prompt text using generative AI technology, a device for automatically editing according to the user's emotions, and a device for providing the edited digital information. This enables users to automatically and easily create special content of professional quality that reflects their individual emotions.

[0318] "Digital information" refers to all data expressed in electronic format, including images, audio, and video.

[0319] "Analysis" refers to the process of systematically examining data and extracting meaningful information from it.

[0320] "Facial recognition" refers to the technology that detects human faces from images and videos and identifies their characteristics.

[0321] "Emotional analysis" refers to the technology of analyzing and expressing a person's emotional state using numerical values ​​or indicators.

[0322] An "emotion engine" refers to a system that combines facial recognition and emotion analysis to analyze the emotional elements within digital information and output the results.

[0323] "Generative AI technology" refers to technology that uses artificial intelligence to automatically generate new data and content.

[0324] A "prompt message" refers to a sentence that indicates an instruction or inquiry input to a generative AI technology in order to produce a specific output.

[0325] "Editing style" refers to the format and method of editing applied to digital information according to its purpose and theme.

[0326] This invention provides a system for efficiently editing digital information captured by a user based on their emotions. This system mainly consists of a server, a terminal, and a user interface.

[0327] Users send digital information to a server via a communication application through their device. The server analyzes the received digital information and identifies specific scenes within it. The analysis uses an emotion engine that combines facial recognition and emotion analysis, along with video processing libraries and machine learning frameworks. Specifically, technologies such as OpenCV and TensorFlow are utilized.

[0328] Based on data extracted through emotion analysis, the server uses generative AI technology to select an editing style. The selected editing style is optimized to match the user's desired atmosphere, and appropriate background music and effects are applied from the template library.

[0329] The edited content is temporarily stored on the server, and a download link is sent to the user's device. The user can then retrieve the edited content from this link and share it according to their individual needs.

[0330] As a concrete example, if a user uploads a video they filmed at a family gathering to the system, and the system detects the emotion of "emotion," the server will edit the video by combining soothing background music and a slow-motion effect. In this case, an example of a prompt to the generating AI model could be, "Please make the family gathering more emotionally moving."

[0331] This system allows users to automatically and easily create special content that is professional in quality and reflects their emotions.

[0332] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0333] Step 1:

[0334] The user uploads digital information captured using their device to a server via a communication application. At this stage, digital images and videos are used as input and transmitted to the server using a communication protocol. The data is then stored on the server as output.

[0335] Step 2:

[0336] The server analyzes the received digital information. Specifically, it uses libraries such as OpenCV to perform face recognition and detect human faces within the digital information. The received digital information is used as input, and metadata containing facial features is generated as output. Based on this metadata, candidate important scenes are identified.

[0337] Step 3:

[0338] The server performs sentiment analysis using an emotion engine. This utilizes AI frameworks such as TensorFlow to analyze the emotional state in each scene based on facial features. The input is the facial metadata and digital information, which are the output of step 2, and the output is the emotional information for each scene.

[0339] Step 4:

[0340] Based on the sentiment analysis results, the server uses generative AI technology to select an appropriate editing style. Specifically, a prompt sentence corresponding to the sentiment is input to the AI ​​model, and corresponding background music and effects are selected from a template library and output. The input consists of sentiment information and pre-configured prompt sentences, while the output consists of the selected editing style and related content.

[0341] Step 5:

[0342] The server applies the selected editing style and re-edits the digital information. This step involves actual video editing using video editing software. The input is the original digital information and editing style, and the output is the final edited digital information.

[0343] Step 6:

[0344] The server temporarily stores the edited digital information and sends a download link to the user's device. The input is the edited digital information, and the output is the download link. This link allows the user to download and share the content from their device.

[0345] (Application Example 2)

[0346] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0347] In today's world, where capturing and sharing digital data is easy, users are seeking to create unique content that reflects their individual emotions. However, traditional editing tools require manual editing, demanding high technical skills to achieve professional quality. Furthermore, providing a personalized experience based on user emotions has been difficult. Against this backdrop, there is a need for a system that allows users to easily and automatically perform advanced editing based on their own emotions.

[0348] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0349] In this invention, the server includes means for receiving digital data, means for analyzing the digital data to identify important scenes, means for automatically editing based on the identified important scenes, means for providing the edited digital data to the user, and means for selecting an emotion-based editing style using emotion analysis. This makes it possible for the user to automatically and easily create special content that corresponds to their own emotions.

[0350] "Digital data" refers to information resources such as audio, images, videos, and documents that have been converted into a digital format and can be processed, stored, and transmitted using electronic devices.

[0351] "Means of receiving" refers to methods or technologies for acquiring or incorporating digital data from external sources.

[0352] "Means of analysis to identify important scenes" refers to methods and techniques for analyzing digital data and identifying particularly noteworthy scenes or moments within it.

[0353] "Means of automatic editing" refer to systems and methods that minimize user intervention and perform editing tasks using programs or algorithms.

[0354] "Means of providing edited digital data" refers to methods and technologies that enable users to view, download, or use the edited digital data.

[0355] "Emotional analysis" is a technique or method for inferring and identifying a person's emotional state from facial expressions, tone of voice, and other factors.

[0356] "Methods for selecting an emotion-based editing style" refer to methods and techniques for determining the optimal editing method based on analyzed emotion data and then applying it.

[0357] The system implementing this invention mainly consists of a server, a terminal, and a user. The user can use the terminal to capture digital data and upload that data to the server via the terminal. The server analyzes the received digital data using facial recognition libraries such as OpenCV and deep learning frameworks such as TensorFlow and PyTorch to perform emotion analysis from facial expressions and voice tone. This allows for the identification of important scenes within the digital data and the determination of emotion-based editing content.

[0358] The server selects an editing style based on predefined emotional data, using identified key scenes. Based on the selected editing style, it uses the FFmpeg library to add background music and apply special effects to the digital data. Once the editing process is complete, the server temporarily stores the edited digital data and generates a link accessible to the user. The user can use this link to download, view, and share the edited digital data.

[0359] For example, when a user uploads a video they shot while traveling to the platform, the server detects scenes that convey emotions such as "surprise" or "joy." Based on the emotion analysis, exciting music and visual effects are automatically added to the video, providing the user with a customized viewing experience. This allows users to easily obtain an emotionally personalized experience that goes beyond simple video sharing.

[0360] An example of a prompt message could be: "The user has uploaded a video they filmed during their vacation. Analyze the user's main emotions from this video. Then, apply an editing style based on those emotions to create a distinctive and unique video."

[0361] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0362] Step 1:

[0363] The user uploads digital data captured with their smartphone camera to the system using a terminal. The input is the digital data captured by the user, and the uploaded data is stored on the server. The output is the state in which the server has received the digital data.

[0364] Step 2:

[0365] The server analyzes the received digital data. At this stage, it uses a face recognition library such as OpenCV to identify faces and expressions within the digital data. The input is the digital data received in step 1, and the output from the analysis is the identified face and expression information within the digital data.

[0366] Step 3:

[0367] Based on the analysis results, the server performs sentiment analysis using TensorFlow or PyTorch. This identifies emotional moments within the digital data. The input is the face and facial expression information obtained in step 2, and the output is the identified emotional moments and their tags.

[0368] Step 4:

[0369] The server selects the appropriate editing style based on the identified emotional moment. This includes selecting background music and applying special effects. The input is the emotional moment and its tag from step 3, and the output is the result of selecting the editing style to apply.

[0370] Step 5:

[0371] The server uses the FFmpeg library to edit the digital data according to the selected editing style. The input is the result of the editing style selection in step 4 and the original digital data, and the output is the edited digital data.

[0372] Step 6:

[0373] The edited digital data is temporarily stored on the server, and a download link is issued to the user. The input is the digital data edited in step 5, and the output is the state in which the download link has been generated.

[0374] Step 7:

[0375] The user can use their device to download, view, and share the edited digital data via the received download link. The input is the download link generated in step 6, and the output is the edited digital data saved on the user's device.

[0376] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0377] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0378] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0379] [Third Embodiment]

[0380] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0381] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0382] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0383] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0384] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0385] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0386] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0387] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0388] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0389] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0390] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0391] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0392] This invention is implemented as a system that allows users to easily edit and manage digital data as growth records via their own devices. Users can upload digital data to a server through their usual communication applications. This data includes photos and videos taken by the user.

[0393] The server uses advanced AI technology to analyze the received digital data. In the first stage of analysis, facial recognition and object recognition are used to identify scenes that are important to the user. Next, emotion analysis technology is applied to identify scenes of emotion such as joy and excitement. This allows for the automatic detection of special moments in the family.

[0394] Once the analysis is complete, the server performs automated editing accordingly. During editing, the selected important scenes are trimmed and combined with optimal visual and audio effects for output. These edited digital data are then presented to the user in a visually easy-to-understand manner through the user interface.

[0395] Users can download the completed content and then share their memories with family and friends using the system's sharing function. This system allows users to automatically and efficiently generate professional-quality growth records and effectively manage family memories.

[0396] The following describes the processing flow.

[0397] Step 1:

[0398] The user opens a communication application on their device and selects photos and videos to record their child's growth. The process of uploading the selected digital data to the server then begins.

[0399] Step 2:

[0400] The terminal packets the digital data selected by the user and encodes it according to a security protocol. This encoded data is then sent to the server over the internet.

[0401] Step 3:

[0402] The server decodes the encoded digital data received from the terminal and securely stores it in cloud storage. It also simultaneously records data metadata (e.g., date and time of capture, data format).

[0403] Step 4:

[0404] The server activates an AI analysis module to analyze the stored digital data. It uses a facial recognition algorithm to identify family members. Furthermore, it performs emotion analysis to detect emotional moments such as smiling or crying.

[0405] Step 5:

[0406] Based on the analysis results, the server begins automatically editing the digital data. It extracts important scenes, applies corresponding editing templates, and performs trimming, scene transition effects, and music insertion.

[0407] Step 6:

[0408] The server temporarily stores the completed, edited content in cloud storage and sends a download link to the user's device.

[0409] Step 7:

[0410] Users download the edited content using a link sent to their device and share the memories with family and friends.

[0411] (Example 1)

[0412] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0413] In modern society, a vast amount of digital information is generated, and there is a need for a means to efficiently identify important moments and information with emotional value from this data, and to effectively manage and edit it as a record. However, conventional methods require manual editing, which is time-consuming and labor-intensive, and often requires specialized editing skills. To solve this problem, the challenge is to provide a system that automatically analyzes and edits important scenes and delivers them to the user.

[0414] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0415] In this invention, the server includes means for receiving information, means for analyzing the information to recognize important scenes, and means for automatically making changes based on the recognized important scenes. This makes it possible for users to easily identify valuable moments from a vast amount of digital information, automatically edit them, and use them as professional-quality content.

[0416] "Means for receiving information" refers to a configuration that has the function of taking in digital data from an external source.

[0417] "Means of analyzing information to recognize important scenes" refers to a function that uses advanced algorithms to analyze captured digital data and automatically identify scenes that are considered important to the user.

[0418] "Means of making changes automatically" refers to a function that automatically edits digital data based on recognized important scenes.

[0419] "Means of presentation" refers to functions that provide edited digital data in a way that is easy for users to review.

[0420] A "user interface" is an interactive interface that allows users to operate a system and send and receive information.

[0421] "Methods for performing sentiment analysis and highlighting emotional moments during changes" refers to functions that analyze the emotions contained in scenes within digital data and highlight those emotionally valuable moments during recording.

[0422] This invention provides a system for users to efficiently manage and edit digital data. Users can typically upload photos and videos they take on a daily basis using devices such as smartphones or personal computers to a server via common communication applications. This uploaded data is securely stored in the system's cloud storage.

[0423] The server utilizes advanced AI technology to analyze this digital data. Specifically, it uses an AI platform (for example, a general-purpose cloud AI service) for processing such as face recognition and object recognition. In the first stage of analysis, the server uses these AI technologies to identify important scenes within the digital data. This process makes it possible, for example, to automatically extract particularly precious moments from family photos.

[0424] Next, the server performs sentiment analysis. This is to identify emotional scenes, such as joy and excitement, contained in the photos and videos. By using AI technology, it is possible to highlight and edit scenes that contain emotional value.

[0425] During the editing process, the server uses an automated editing function to trim the selected key scenes. It then uses dedicated software (e.g., general video editing software) to combine optimal visual and audio effects for the final output. The edited content is presented to the user through a dedicated user interface.

[0426] Users can download the completed content and easily share it with family and friends using the system's sharing function. This system allows users to efficiently create professional-quality growth records and easily manage their memories.

[0427] An example of a prompt might be: "I've uploaded photos and videos from our family trip. Please generate a 5-minute video clip summarizing our heartwarming memories."

[0428] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0429] Step 1:

[0430] Users upload digital data (e.g., photos and videos) to a server using their device. The input consists of files selected on the device, and the output is saved to the server's cloud storage. This process is conducted via a communication application over a secure network connection.

[0431] Step 2:

[0432] The server analyzes the uploaded data. The input is the digital data saved in step 1. The server uses AI technology to perform face recognition and object recognition to identify important scenes within the digital data. The output generates various metadata for the identified important scenes. In this specific operation, the AI ​​algorithm extracts patterns of people and objects from the data and determines their importance.

[0433] Step 3:

[0434] The server performs sentiment analysis on the identified scenes. The input is metadata of the key scenes obtained in step 2. The server runs its sentiment analysis engine and assigns emotional labels such as joy and emotion to each scene. This data processing generates a dataset as output in which emotional value is quantified. In the specific operation of this step, the AI ​​evaluates the emotional tone by analyzing changes in voice and facial expressions.

[0435] Step 4:

[0436] The server executes an automated editing process based on the data generated in the previous step. The input here is scene metadata with emotion labels assigned to it. The server automatically performs trimming, color adjustment, and background music insertion using appropriate visual editing software. The output is a professional-quality edited content file. In this specific operation, the video and music are effectively combined using a specified template.

[0437] Step 5:

[0438] The server presents the edited content to the user through a user interface. The input is the content file generated in step 4. The server displays this file in a way that is easily visually evaluateable by humans. This process allows the user to interactively review the editing results as output. Specifically, this step involves playing the content using a preview function.

[0439] Step 6:

[0440] The user downloads the final content or shares it within the system. The input is the edited content presented by the server. The user downloads the file via their terminal or generates a link to share it with family and friends. The output is the URL of the downloaded file or shared content. This specific operation involves selecting and transferring the file format.

[0441] (Application Example 1)

[0442] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0443] Traditional methods for automatically analyzing user-submitted photos and videos to identify and edit important scenes require manual editing, which is time-consuming and labor-intensive. Furthermore, there is a lack of readily available and convenient ways to share the edited digital content.

[0444] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0445] In this invention, the server includes means for receiving digital information, means for analyzing the digital information to identify important scenes, and means for automatically editing based on the identified important scenes. This enables users to automatically and efficiently generate and easily share professional-quality edited digital content.

[0446] "Digital information" refers to all data stored and transmitted in electronic format, including photographs, videos, and audio files.

[0447] A "user interface" is a means by which a user operates a system or device and accesses its functions, and can take the form of physical buttons, touchscreens, voice input, etc.

[0448] An "information processing device" refers to a device used for inputting, processing, and outputting data, and includes personal computers, smartphones, and cloud servers.

[0449] "Emotion analysis" is a technology that detects and analyzes emotional elements in digital information, and is a process of determining a person's emotional state from text, images, audio, etc.

[0450] A "critical moment" refers to a phase or moment in the digital information in question that the user should pay particular attention to, and which is identified by the system.

[0451] "Automatic editing" refers to a system independently processing digital information and creating final content without manual intervention from the user.

[0452] To realize this invention, a system is required in which a server and a user's terminal play the main roles. The server receives digital information from the user's terminal. This digital information includes data such as photographs and videos. The server uses AI technology to analyze the received digital information and perform a process of identifying important and emotionally significant scenes. Specifically, it uses software such as a facial recognition API and an emotion analysis API to identify scenes that are important and emotionally valuable to the user.

[0453] Next, based on the identified scenes, the server automatically performs editing. This editing involves trimming and adding optimal audio and visual effects to create visually appealing content for the user. The edited digital information is then provided in a downloadable format to the user's information processing device.

[0454] Users can control this entire process through the user interface. The interface includes features for uploading digital information, and for previewing, downloading, and sharing edited data.

[0455] As a concrete example, consider a scenario where a user takes photos and videos of a picnic in a park and uses this system to create an original video story. This video would automatically compile photos of the happy, smiling family and clips capturing touching moments. An example of a prompt to the generation AI model would be, "Create a video documenting a fun family holiday." This prompt would cause the system to generate content in the expected format.

[0456] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0457] Step 1:

[0458] The user's device prepares the captured photos and video data as digital information. This includes adding metadata after shooting and standardizing file formats. The digital information is uploaded to the server via the user interface. At this stage, the input is the photos and video files on the user's device, and the output is the files registered in the input queue on the server.

[0459] Step 2:

[0460] The server receives uploaded digital information and analyzes the received data. First, it uses a facial recognition API to identify people in photos and videos. Next, it applies an emotion analysis API to identify the emotions expressed by the detected people. The input is raw data uploaded by the user, and the output is analyzed data with facial recognition and emotion information attached.

[0461] Step 3:

[0462] The server identifies important scenes based on the analyzed data. In particular, it selects scenes that strongly express emotions such as joy and excitement. The input is the analyzed data, and the output is the selected important scene data.

[0463] Step 4:

[0464] The server automatically edits based on selected key scenes. It optimizes visual and auditory effects by trimming, applying filters, and adding music and sound effects. The input is key scene data, and the output is edited digital content.

[0465] Step 5:

[0466] The server provides the completed, edited content in a downloadable format to the user's information processing device. It also allows content preview through the user interface. The input is the edited digital data, and the output is the final file downloaded to the user's terminal.

[0467] Step 6:

[0468] The user downloads the provided content and shares it with friends and family using the sharing function as needed. The input is downloadable content, and the output is a video story saved in a format usable by the user. During this process, the prompt "Create a video documenting a fun family holiday" is applied to the generating AI model.

[0469] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0470] This invention relates to a system for efficiently editing digital data captured by a user, which incorporates an emotion engine to achieve advanced content editing based on the user's emotions. This system mainly consists of three main components: a server, a terminal, and a user interface.

[0471] Users upload digital data to a server via a communication application through their device. The server receives this digital data and analyzes it using AI technology. During the analysis phase, an emotion engine combining facial recognition and emotion analysis identifies the emotions of the user and the subject. This identifies scenes in the data that should be emphasized.

[0472] Next, the server selects an editing style optimized for the user's emotions based on the emotion data obtained from the emotion engine. This process results in an edit that effectively conveys the atmosphere and emotions the user desires. For example, if the user has a strong emotion of "joy," the system will apply bright and lively background music and effects to the edit.

[0473] Once editing is complete, the content is temporarily stored on the server, and a download link is sent to the user's device. Through this link, the user can easily download the edited content and share it with family and friends.

[0474] This system allows users to automatically and easily create special memories that reflect individual emotions and are of professional quality. For example, when users upload digital data taken at a family event, if the system detects the emotion of "emotion," it adds soothing background music and a slow-motion effect, generating a warm video suitable for a family album.

[0475] The following describes the processing flow.

[0476] Step 1:

[0477] The user opens a communication application on their device and selects the digital data (photos and videos) they want to edit. The user then begins uploading the data through the device's operation.

[0478] Step 2:

[0479] The terminal packets the selected digital data and encodes it based on a secure communication protocol. This encoded data is then sent to the server via the internet.

[0480] Step 3:

[0481] The server decodes the data received from the terminal and saves it to cloud storage. At the same time, it also records metadata about the data (such as the date and time of capture and location information).

[0482] Step 4:

[0483] The server analyzes the stored digital data using an emotion engine. It uses facial recognition technology to identify people in the video and emotion analysis algorithms to determine the emotional state of each person.

[0484] Step 5:

[0485] The server selects an appropriate editing style based on the identified emotion. For example, if the emotion of "joy" is dominant, it will run a program that selects bright visual effects and lively music.

[0486] Step 6:

[0487] Based on this information, the server automatically edits the digital data. It trims important scenes and applies selected effects and music to generate the edited content.

[0488] Step 7:

[0489] Once the edited content is complete, the server saves the file to cloud storage and sends a notification to the user's device. The notification includes a link to download the edited content.

[0490] Step 8:

[0491] Users can use their devices to check notifications and download edited content. They can then easily share their finished work with family and friends.

[0492] (Example 2)

[0493] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0494] In recent years, with the increase in digital data, there has been a growing need for methods that allow users to easily edit content based on their emotions. However, with conventional systems, editing in line with user emotions has been time-consuming and technically demanding, making it difficult. Therefore, there is a need for a system that can automatically and efficiently perform editing that reflects user emotions.

[0495] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0496] In this invention, the server includes a device for receiving digital information, a device for analyzing the digital information to identify a specific scene, a device for using an emotion engine that combines facial recognition and emotion analysis, a device for selecting an editing style based on prompt text using generative AI technology, a device for automatically editing according to the user's emotions, and a device for providing the edited digital information. This enables users to automatically and easily create special content of professional quality that reflects their individual emotions.

[0497] "Digital information" refers to all data expressed in electronic format, including images, audio, and video.

[0498] "Analysis" refers to the process of systematically examining data and extracting meaningful information from it.

[0499] "Facial recognition" refers to the technology that detects human faces from images and videos and identifies their characteristics.

[0500] "Emotional analysis" refers to the technology of analyzing and expressing a person's emotional state using numerical values ​​or indicators.

[0501] An "emotion engine" refers to a system that combines facial recognition and emotion analysis to analyze the emotional elements within digital information and output the results.

[0502] "Generative AI technology" refers to technology that uses artificial intelligence to automatically generate new data and content.

[0503] A "prompt message" refers to a sentence that indicates an instruction or inquiry input to a generative AI technology in order to produce a specific output.

[0504] "Editing style" refers to the format and method of editing applied to digital information according to its purpose and theme.

[0505] This invention provides a system for efficiently editing digital information captured by a user based on their emotions. This system mainly consists of a server, a terminal, and a user interface.

[0506] Users send digital information to a server via a communication application through their device. The server analyzes the received digital information and identifies specific scenes within it. The analysis uses an emotion engine that combines facial recognition and emotion analysis, along with video processing libraries and machine learning frameworks. Specifically, technologies such as OpenCV and TensorFlow are utilized.

[0507] Based on data extracted through emotion analysis, the server uses generative AI technology to select an editing style. The selected editing style is optimized to match the user's desired atmosphere, and appropriate background music and effects are applied from the template library.

[0508] The edited content is temporarily stored on the server, and a download link is sent to the user's device. The user can then retrieve the edited content from this link and share it according to their individual needs.

[0509] As a concrete example, if a user uploads a video they filmed at a family gathering to the system, and the system detects the emotion of "emotion," the server will edit the video by combining soothing background music and a slow-motion effect. In this case, an example of a prompt to the generating AI model could be, "Please make the family gathering more emotionally moving."

[0510] This system allows users to automatically and easily create special content that is professional in quality and reflects their emotions.

[0511] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0512] Step 1:

[0513] The user uploads digital information captured using their device to a server via a communication application. At this stage, digital images and videos are used as input and transmitted to the server using a communication protocol. The data is then stored on the server as output.

[0514] Step 2:

[0515] The server analyzes the received digital information. Specifically, it uses libraries such as OpenCV to perform face recognition and detect human faces within the digital information. The received digital information is used as input, and metadata containing facial features is generated as output. Based on this metadata, candidate important scenes are identified.

[0516] Step 3:

[0517] The server performs sentiment analysis using an emotion engine. This utilizes AI frameworks such as TensorFlow to analyze the emotional state in each scene based on facial features. The input is the facial metadata and digital information, which are the output of step 2, and the output is the emotional information for each scene.

[0518] Step 4:

[0519] Based on the sentiment analysis results, the server uses generative AI technology to select an appropriate editing style. Specifically, a prompt sentence corresponding to the sentiment is input to the AI ​​model, and corresponding background music and effects are selected from a template library and output. The input consists of sentiment information and pre-configured prompt sentences, while the output consists of the selected editing style and related content.

[0520] Step 5:

[0521] The server applies the selected editing style and re-edits the digital information. This step involves actual video editing using video editing software. The input is the original digital information and editing style, and the output is the final edited digital information.

[0522] Step 6:

[0523] The server temporarily stores the edited digital information and sends a download link to the user's device. The input is the edited digital information, and the output is the download link. This link allows the user to download and share the content from their device.

[0524] (Application Example 2)

[0525] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0526] In today's world, where capturing and sharing digital data is easy, users are seeking to create unique content that reflects their individual emotions. However, traditional editing tools require manual editing, demanding high technical skills to achieve professional quality. Furthermore, providing a personalized experience based on user emotions has been difficult. Against this backdrop, there is a need for a system that allows users to easily and automatically perform advanced editing based on their own emotions.

[0527] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0528] In this invention, the server includes means for receiving digital data, means for analyzing the digital data to identify important scenes, means for automatically editing based on the identified important scenes, means for providing the edited digital data to the user, and means for selecting an emotion-based editing style using emotion analysis. This makes it possible for the user to automatically and easily create special content that corresponds to their own emotions.

[0529] "Digital data" refers to information resources such as audio, images, videos, and documents that have been converted into a digital format and can be processed, stored, and transmitted using electronic devices.

[0530] "Means of receiving" refers to methods or technologies for acquiring or incorporating digital data from external sources.

[0531] "Means of analysis to identify important scenes" refers to methods and techniques for analyzing digital data and identifying particularly noteworthy scenes or moments within it.

[0532] "Means of automatic editing" refer to systems and methods that minimize user intervention and perform editing tasks using programs or algorithms.

[0533] "Means of providing edited digital data" refers to methods and technologies that enable users to view, download, or use the edited digital data.

[0534] "Emotional analysis" is a technique or method for inferring and identifying a person's emotional state from facial expressions, tone of voice, and other factors.

[0535] "Methods for selecting an emotion-based editing style" refer to methods and techniques for determining the optimal editing method based on analyzed emotion data and then applying it.

[0536] The system implementing this invention mainly consists of a server, a terminal, and a user. The user can use the terminal to capture digital data and upload that data to the server via the terminal. The server analyzes the received digital data using facial recognition libraries such as OpenCV and deep learning frameworks such as TensorFlow and PyTorch to perform emotion analysis from facial expressions and voice tone. This allows for the identification of important scenes within the digital data and the determination of emotion-based editing content.

[0537] The server selects an editing style based on predefined emotional data, using identified key scenes. Based on the selected editing style, it uses the FFmpeg library to add background music and apply special effects to the digital data. Once the editing process is complete, the server temporarily stores the edited digital data and generates a link accessible to the user. The user can use this link to download, view, and share the edited digital data.

[0538] For example, when a user uploads a video they shot while traveling to the platform, the server detects scenes that convey emotions such as "surprise" or "joy." Based on the emotion analysis, exciting music and visual effects are automatically added to the video, providing the user with a customized viewing experience. This allows users to easily obtain an emotionally personalized experience that goes beyond simple video sharing.

[0539] An example of a prompt message could be: "The user has uploaded a video they filmed during their vacation. Analyze the user's main emotions from this video. Then, apply an editing style based on those emotions to create a distinctive and unique video."

[0540] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0541] Step 1:

[0542] The user uploads digital data captured with their smartphone camera to the system using a terminal. The input is the digital data captured by the user, and the uploaded data is stored on the server. The output is the state in which the server has received the digital data.

[0543] Step 2:

[0544] The server analyzes the received digital data. At this stage, it uses a face recognition library such as OpenCV to identify faces and expressions within the digital data. The input is the digital data received in step 1, and the output from the analysis is the identified face and expression information within the digital data.

[0545] Step 3:

[0546] Based on the analysis results, the server performs sentiment analysis using TensorFlow or PyTorch. This identifies emotional moments within the digital data. The input is the face and facial expression information obtained in step 2, and the output is the identified emotional moments and their tags.

[0547] Step 4:

[0548] The server selects the appropriate editing style based on the identified emotional moment. This includes selecting background music and applying special effects. The input is the emotional moment and its tag from step 3, and the output is the result of selecting the editing style to apply.

[0549] Step 5:

[0550] The server uses the FFmpeg library to edit the digital data according to the selected editing style. The input is the result of the editing style selection in step 4 and the original digital data, and the output is the edited digital data.

[0551] Step 6:

[0552] The edited digital data is temporarily stored on the server, and a download link is issued to the user. The input is the digital data edited in step 5, and the output is the state in which the download link has been generated.

[0553] Step 7:

[0554] The user can use their device to download, view, and share the edited digital data via the received download link. The input is the download link generated in step 6, and the output is the edited digital data saved on the user's device.

[0555] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0556] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0557] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0558] [Fourth Embodiment]

[0559] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0560] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0561] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0562] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0563] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0564] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0565] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0566] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0567] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0568] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0569] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0570] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0571] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0572] This invention is implemented as a system that allows users to easily edit and manage digital data as growth records via their own devices. Users can upload digital data to a server through their usual communication applications. This data includes photos and videos taken by the user.

[0573] The server uses advanced AI technology to analyze the received digital data. In the first stage of analysis, facial recognition and object recognition are used to identify scenes that are important to the user. Next, emotion analysis technology is applied to identify scenes of emotion such as joy and excitement. This allows for the automatic detection of special moments within the family.

[0574] Once the analysis is complete, the server performs automated editing accordingly. During editing, the selected important scenes are trimmed and combined with optimal visual and audio effects for output. These edited digital data are then presented to the user in a visually easy-to-understand manner through the user interface.

[0575] Users can download the completed content and then share their memories with family and friends using the system's sharing function. This system allows users to automatically and efficiently generate professional-quality growth records and effectively manage family memories.

[0576] The following describes the processing flow.

[0577] Step 1:

[0578] The user opens a communication application on their device and selects photos and videos to record their child's growth. The process of uploading the selected digital data to the server then begins.

[0579] Step 2:

[0580] The terminal packets the digital data selected by the user and encodes it according to a security protocol. This encoded data is then sent to the server over the internet.

[0581] Step 3:

[0582] The server decodes the encoded digital data received from the terminal and securely stores it in cloud storage. It also simultaneously records data metadata (e.g., date and time of capture, data format).

[0583] Step 4:

[0584] The server activates an AI analysis module to analyze the stored digital data. It uses a facial recognition algorithm to identify family members. Furthermore, it performs emotion analysis to detect emotional moments such as smiling or crying.

[0585] Step 5:

[0586] Based on the analysis results, the server begins automatically editing the digital data. It extracts important scenes, applies corresponding editing templates, and performs trimming, scene transition effects, and music insertion.

[0587] Step 6:

[0588] The server temporarily stores the completed, edited content in cloud storage and sends a download link to the user's device.

[0589] Step 7:

[0590] Users download the edited content using a link sent to their device and share the memories with family and friends.

[0591] (Example 1)

[0592] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0593] In modern society, a vast amount of digital information is generated, and there is a need for a means to efficiently identify important moments and information with emotional value from this data, and to effectively manage and edit it as a record. However, conventional methods require manual editing, which is time-consuming and labor-intensive, and often requires specialized editing skills. To solve this problem, the challenge is to provide a system that automatically analyzes and edits important scenes and delivers them to the user.

[0594] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0595] In this invention, the server includes means for receiving information, means for analyzing the information to recognize important scenes, and means for automatically making changes based on the recognized important scenes. This makes it possible for users to easily identify valuable moments from a vast amount of digital information, automatically edit them, and use them as professional-quality content.

[0596] "Means for receiving information" refers to a configuration that has the function of taking in digital data from an external source.

[0597] "Means of analyzing information to recognize important scenes" refers to a function that uses advanced algorithms to analyze captured digital data and automatically identify scenes that are considered important to the user.

[0598] "Means of making changes automatically" refers to a function that automatically edits digital data based on recognized important scenes.

[0599] "Means of presentation" refers to functions that provide edited digital data in a way that is easy for users to review.

[0600] A "user interface" is an interactive interface that allows users to operate a system and send and receive information.

[0601] "Methods for performing sentiment analysis and highlighting emotional moments during changes" refers to functions that analyze the emotions contained in scenes within digital data and highlight those emotionally valuable moments during recording.

[0602] This invention provides a system for users to efficiently manage and edit digital data. Users can typically upload photos and videos they take on a daily basis using devices such as smartphones or personal computers to a server via common communication applications. This uploaded data is securely stored in the system's cloud storage.

[0603] The server utilizes advanced AI technology to analyze this digital data. Specifically, it uses an AI platform (for example, a general-purpose cloud AI service) for processing such as face recognition and object recognition. In the first stage of analysis, the server uses these AI technologies to identify important scenes within the digital data. This process makes it possible, for example, to automatically extract particularly precious moments from family photos.

[0604] Next, the server performs sentiment analysis. This is to identify emotional scenes, such as joy and excitement, contained in the photos and videos. By using AI technology, it is possible to highlight and edit scenes that contain emotional value.

[0605] During the editing process, the server uses an automated editing function to trim the selected key scenes. It then uses dedicated software (e.g., general video editing software) to combine optimal visual and audio effects for the final output. The edited content is presented to the user through a dedicated user interface.

[0606] Users can download the completed content and easily share it with family and friends using the system's sharing function. This system allows users to efficiently create professional-quality growth records and easily manage their memories.

[0607] An example of a prompt might be: "I've uploaded photos and videos from our family trip. Please generate a 5-minute video clip summarizing our heartwarming memories."

[0608] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0609] Step 1:

[0610] Users upload digital data (e.g., photos and videos) to a server using their device. The input consists of files selected on the device, and the output is saved to the server's cloud storage. This process is conducted via a communication application over a secure network connection.

[0611] Step 2:

[0612] The server analyzes the uploaded data. The input is the digital data saved in step 1. The server uses AI technology to perform face recognition and object recognition to identify important scenes within the digital data. The output generates various metadata for the identified important scenes. In this specific operation, the AI ​​algorithm extracts patterns of people and objects from the data and determines their importance.

[0613] Step 3:

[0614] The server performs sentiment analysis on the identified scenes. The input is metadata of the key scenes obtained in step 2. The server runs its sentiment analysis engine and assigns emotional labels such as joy and emotion to each scene. This data processing generates a dataset as output in which emotional value is quantified. In the specific operation of this step, the AI ​​evaluates the emotional tone by analyzing changes in voice and facial expressions.

[0615] Step 4:

[0616] The server executes an automated editing process based on the data generated in the previous step. The input here is scene metadata with emotion labels assigned to it. The server automatically performs trimming, color adjustment, and background music insertion using appropriate visual editing software. The output is a professional-quality edited content file. In this specific operation, the video and music are effectively combined using a specified template.

[0617] Step 5:

[0618] The server presents the edited content to the user through a user interface. The input is the content file generated in step 4. The server displays this file in a way that is easily visually evaluateable by humans. This process allows the user to interactively review the editing results as output. Specifically, this step involves playing the content using a preview function.

[0619] Step 6:

[0620] The user downloads the final content or shares it within the system. The input is the edited content presented by the server. The user downloads the file via their terminal or generates a link to share it with family and friends. The output is the URL of the downloaded file or shared content. This specific operation involves selecting and transferring the file format.

[0621] (Application Example 1)

[0622] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0623] Traditional methods for automatically analyzing user-submitted photos and videos to identify and edit important scenes require manual editing, which is time-consuming and labor-intensive. Furthermore, there is a lack of readily available and convenient ways to share the edited digital content.

[0624] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0625] In this invention, the server includes means for receiving digital information, means for analyzing the digital information to identify important scenes, and means for automatically editing based on the identified important scenes. This enables users to automatically and efficiently generate and easily share professional-quality edited digital content.

[0626] "Digital information" refers to all data stored and transmitted in electronic format, including photographs, videos, and audio files.

[0627] A "user interface" is a means by which a user operates a system or device and accesses its functions, and can take the form of physical buttons, touchscreens, voice input, etc.

[0628] An "information processing device" refers to a device used for inputting, processing, and outputting data, and includes personal computers, smartphones, and cloud servers.

[0629] "Emotion analysis" is a technology that detects and analyzes emotional elements in digital information, and is a process of determining a person's emotional state from text, images, audio, etc.

[0630] A "critical moment" refers to a phase or moment in the digital information in question that the user should pay particular attention to, and which is identified by the system.

[0631] "Automatic editing" refers to a system independently processing digital information and creating final content without manual intervention from the user.

[0632] To realize this invention, a system is required in which a server and a user's terminal play the main roles. The server receives digital information from the user's terminal. This digital information includes data such as photographs and videos. The server uses AI technology to analyze the received digital information and perform a process of identifying important and emotionally significant scenes. Specifically, it uses software such as a facial recognition API and an emotion analysis API to identify scenes that are important and emotionally valuable to the user.

[0633] Next, based on the identified scenes, the server automatically performs editing. This editing involves trimming and adding optimal audio and visual effects to create visually appealing content for the user. The edited digital information is then provided in a downloadable format to the user's information processing device.

[0634] Users can control this entire process through the user interface. The interface includes features for uploading digital information, and for previewing, downloading, and sharing edited data.

[0635] As a concrete example, consider a scenario where a user takes photos and videos of a picnic in a park and uses this system to create an original video story. This video would automatically compile photos of the happy, smiling family and clips capturing touching moments. An example of a prompt to the generation AI model would be, "Create a video documenting a fun family holiday." This prompt would cause the system to generate content in the expected format.

[0636] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0637] Step 1:

[0638] The user's device prepares the captured photos and video data as digital information. This includes adding metadata after shooting and standardizing file formats. The digital information is uploaded to the server via the user interface. At this stage, the input is the photos and video files on the user's device, and the output is the files registered in the input queue on the server.

[0639] Step 2:

[0640] The server receives uploaded digital information and analyzes the received data. First, it uses a facial recognition API to identify people in photos and videos. Next, it applies an emotion analysis API to identify the emotions expressed by the detected people. The input is raw data uploaded by the user, and the output is analyzed data with facial recognition and emotion information attached.

[0641] Step 3:

[0642] The server identifies important scenes based on the analyzed data. In particular, it selects scenes that strongly express emotions such as joy and excitement. The input is the analyzed data, and the output is the selected important scene data.

[0643] Step 4:

[0644] The server automatically edits based on selected key scenes. It optimizes visual and auditory effects by trimming, applying filters, and adding music and sound effects. The input is key scene data, and the output is edited digital content.

[0645] Step 5:

[0646] The server provides the completed, edited content in a downloadable format to the user's information processing device. It also allows content preview through the user interface. The input is the edited digital data, and the output is the final file downloaded to the user's terminal.

[0647] Step 6:

[0648] The user downloads the provided content and shares it with friends and family using the sharing function as needed. The input is downloadable content, and the output is a video story saved in a format usable by the user. During this process, the prompt "Create a video documenting a fun family holiday" is applied to the generating AI model.

[0649] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0650] This invention relates to a system for efficiently editing digital data captured by a user, which incorporates an emotion engine to achieve advanced content editing based on the user's emotions. This system mainly consists of three main components: a server, a terminal, and a user interface.

[0651] Users upload digital data to a server via a communication application through their device. The server receives this digital data and analyzes it using AI technology. During the analysis phase, an emotion engine combining facial recognition and emotion analysis identifies the emotions of the user and the subject. This identifies scenes in the data that should be emphasized.

[0652] Next, the server selects an editing style optimized for the user's emotions based on the emotion data obtained from the emotion engine. This process results in an edit that effectively conveys the atmosphere and emotions the user desires. For example, if the user has a strong emotion of "joy," the system will apply bright and lively background music and effects to the edit.

[0653] Once editing is complete, the content is temporarily stored on the server, and a download link is sent to the user's device. Through this link, the user can easily download the edited content and share it with family and friends.

[0654] This system allows users to automatically and easily create special memories that reflect individual emotions and are of professional quality. For example, when users upload digital data taken at a family event, if the system detects the emotion of "emotion," it adds soothing background music and a slow-motion effect, generating a warm video suitable for a family album.

[0655] The following describes the processing flow.

[0656] Step 1:

[0657] The user opens a communication application on their device and selects the digital data (photos and videos) they want to edit. The user then begins uploading the data through the device's operation.

[0658] Step 2:

[0659] The terminal packets the selected digital data and encodes it based on a secure communication protocol. This encoded data is then sent to the server via the internet.

[0660] Step 3:

[0661] The server decodes the data received from the terminal and saves it to cloud storage. At the same time, it also records metadata about the data (such as the date and time of capture and location information).

[0662] Step 4:

[0663] The server analyzes the stored digital data using an emotion engine. It uses facial recognition technology to identify people in the video and emotion analysis algorithms to determine the emotional state of each person.

[0664] Step 5:

[0665] The server selects an appropriate editing style based on the identified emotion. For example, if the emotion of "joy" is dominant, it will run a program that selects bright visual effects and lively music.

[0666] Step 6:

[0667] Based on this information, the server automatically edits the digital data. It trims important scenes and applies selected effects and music to generate the edited content.

[0668] Step 7:

[0669] Once the edited content is complete, the server saves the file to cloud storage and sends a notification to the user's device. The notification includes a link to download the edited content.

[0670] Step 8:

[0671] Users can use their devices to check notifications and download edited content. They can then easily share their finished work with family and friends.

[0672] (Example 2)

[0673] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0674] In recent years, with the increase in digital data, there has been a growing need for methods that allow users to easily edit content based on their emotions. However, with conventional systems, editing in line with user emotions has been time-consuming and technically demanding, making it difficult. Therefore, there is a need for a system that can automatically and efficiently perform editing that reflects user emotions.

[0675] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0676] In this invention, the server includes a device for receiving digital information, a device for analyzing the digital information to identify a specific scene, a device for using an emotion engine that combines facial recognition and emotion analysis, a device for selecting an editing style based on prompt text using generative AI technology, a device for automatically editing according to the user's emotions, and a device for providing the edited digital information. This enables users to automatically and easily create special content of professional quality that reflects their individual emotions.

[0677] "Digital information" refers to all data expressed in electronic format, including images, audio, and video.

[0678] "Analysis" refers to the process of systematically examining data and extracting meaningful information from it.

[0679] "Facial recognition" refers to the technology that detects human faces from images and videos and identifies their characteristics.

[0680] "Emotional analysis" refers to the technology of analyzing and expressing a person's emotional state using numerical values ​​or indicators.

[0681] An "emotion engine" refers to a system that combines facial recognition and emotion analysis to analyze the emotional elements within digital information and output the results.

[0682] "Generative AI technology" refers to technology that uses artificial intelligence to automatically generate new data and content.

[0683] A "prompt message" refers to a sentence that indicates an instruction or inquiry input to a generative AI technology in order to produce a specific output.

[0684] "Editing style" refers to the format and method of editing applied to digital information according to its purpose and theme.

[0685] This invention provides a system for efficiently editing digital information captured by a user based on their emotions. This system mainly consists of a server, a terminal, and a user interface.

[0686] Users send digital information to a server via a communication application through their device. The server analyzes the received digital information and identifies specific scenes within it. The analysis uses an emotion engine that combines facial recognition and emotion analysis, along with video processing libraries and machine learning frameworks. Specifically, technologies such as OpenCV and TensorFlow are utilized.

[0687] Based on data extracted through emotion analysis, the server uses generative AI technology to select an editing style. The selected editing style is optimized to match the user's desired atmosphere, and appropriate background music and effects are applied from the template library.

[0688] The edited content is temporarily stored on the server, and a download link is sent to the user's device. The user can then retrieve the edited content from this link and share it according to their individual needs.

[0689] As a concrete example, if a user uploads a video they filmed at a family gathering to the system, and the system detects the emotion of "emotion," the server will edit the video by combining soothing background music and a slow-motion effect. In this case, an example of a prompt to the generating AI model could be, "Please make the family gathering more emotionally moving."

[0690] This system allows users to automatically and easily create special content that is professional in quality and reflects their emotions.

[0691] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0692] Step 1:

[0693] The user uploads digital information captured using their device to a server via a communication application. At this stage, digital images and videos are used as input and transmitted to the server using a communication protocol. The data is then stored on the server as output.

[0694] Step 2:

[0695] The server analyzes the received digital information. Specifically, it uses libraries such as OpenCV to perform face recognition and detect human faces within the digital information. The received digital information is used as input, and metadata containing facial features is generated as output. Based on this metadata, candidate important scenes are identified.

[0696] Step 3:

[0697] The server performs sentiment analysis using an emotion engine. This utilizes AI frameworks such as TensorFlow to analyze the emotional state in each scene based on facial features. The input is the facial metadata and digital information, which are the output of step 2, and the output is the emotional information for each scene.

[0698] Step 4:

[0699] Based on the sentiment analysis results, the server uses generative AI technology to select an appropriate editing style. Specifically, a prompt sentence corresponding to the sentiment is input to the AI ​​model, and corresponding background music and effects are selected from a template library and output. The input consists of sentiment information and pre-configured prompt sentences, while the output consists of the selected editing style and related content.

[0700] Step 5:

[0701] The server applies the selected editing style and re-edits the digital information. This step involves actual video editing using video editing software. The input is the original digital information and editing style, and the output is the final edited digital information.

[0702] Step 6:

[0703] The server temporarily stores the edited digital information and sends a download link to the user's device. The input is the edited digital information, and the output is the download link. This link allows the user to download and share the content from their device.

[0704] (Application Example 2)

[0705] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] In today's world, where capturing and sharing digital data is easy, users are seeking to create unique content that reflects their individual emotions. However, traditional editing tools require manual editing, demanding high technical skills to achieve professional quality. Furthermore, providing a personalized experience based on user emotions has been difficult. Against this backdrop, there is a need for a system that allows users to easily and automatically perform advanced editing based on their own emotions.

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

[0708] In this invention, the server includes means for receiving digital data, means for analyzing the digital data to identify important scenes, means for automatically editing based on the identified important scenes, means for providing the edited digital data to the user, and means for selecting an emotion-based editing style using emotion analysis. This makes it possible for the user to automatically and easily create special content that corresponds to their own emotions.

[0709] "Digital data" refers to information resources such as audio, images, videos, and documents that have been converted into a digital format and can be processed, stored, and transmitted using electronic devices.

[0710] "Means of receiving" refers to methods or technologies for acquiring or incorporating digital data from external sources.

[0711] "Means of analysis to identify important scenes" refers to methods and techniques for analyzing digital data and identifying particularly noteworthy scenes or moments within it.

[0712] "Means of automatic editing" refer to systems and methods that minimize user intervention and perform editing tasks using programs or algorithms.

[0713] "Means of providing edited digital data" refers to methods and technologies that enable users to view, download, or use the edited digital data.

[0714] "Emotional analysis" is a technique or method for inferring and identifying a person's emotional state from facial expressions, tone of voice, and other factors.

[0715] "Methods for selecting an emotion-based editing style" refer to methods and techniques for determining the optimal editing method based on analyzed emotion data and then applying it.

[0716] The system implementing this invention mainly consists of a server, a terminal, and a user. The user can use the terminal to capture digital data and upload that data to the server via the terminal. The server analyzes the received digital data using facial recognition libraries such as OpenCV and deep learning frameworks such as TensorFlow and PyTorch to perform emotion analysis from facial expressions and voice tone. This allows for the identification of important scenes within the digital data and the determination of emotion-based editing content.

[0717] The server selects an editing style based on predefined emotional data, using identified key scenes. Based on the selected editing style, it uses the FFmpeg library to add background music and apply special effects to the digital data. Once the editing process is complete, the server temporarily stores the edited digital data and generates a link accessible to the user. The user can use this link to download, view, and share the edited digital data.

[0718] For example, when a user uploads a video they shot while traveling to the platform, the server detects scenes that convey emotions such as "surprise" or "joy." Based on the emotion analysis, exciting music and visual effects are automatically added to the video, providing the user with a customized viewing experience. This allows users to easily obtain an emotionally personalized experience that goes beyond simple video sharing.

[0719] An example of a prompt message could be: "The user has uploaded a video they filmed during their vacation. Analyze the user's main emotions from this video. Then, apply an editing style based on those emotions to create a distinctive and unique video."

[0720] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0721] Step 1:

[0722] The user uploads digital data captured with their smartphone camera to the system using a terminal. The input is the digital data captured by the user, and the uploaded data is stored on the server. The output is the state in which the server has received the digital data.

[0723] Step 2:

[0724] The server analyzes the received digital data. At this stage, it uses a face recognition library such as OpenCV to identify faces and expressions within the digital data. The input is the digital data received in step 1, and the output from the analysis is the identified face and expression information within the digital data.

[0725] Step 3:

[0726] Based on the analysis results, the server performs sentiment analysis using TensorFlow or PyTorch. This identifies emotional moments within the digital data. The input is the face and facial expression information obtained in step 2, and the output is the identified emotional moments and their tags.

[0727] Step 4:

[0728] The server selects the appropriate editing style based on the identified emotional moment. This includes selecting background music and applying special effects. The input is the emotional moment and its tag from step 3, and the output is the result of selecting the editing style to apply.

[0729] Step 5:

[0730] The server uses the FFmpeg library to edit the digital data according to the selected editing style. The input is the result of the editing style selection in step 4 and the original digital data, and the output is the edited digital data.

[0731] Step 6:

[0732] The edited digital data is temporarily stored on the server, and a download link is issued to the user. The input is the digital data edited in step 5, and the output is the state in which the download link has been generated.

[0733] Step 7:

[0734] The user can use their device to download, view, and share the edited digital data via the received download link. The input is the download link generated in step 6, and the output is the edited digital data saved on the user's device.

[0735] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0736] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0737] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0738] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0739] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0740] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0741] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0742] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0743] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0744] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0745] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0746] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0747] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0748] 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.

[0749] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0750] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0751] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0752] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0753] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0754] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0755] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0756] The following is further disclosed regarding the embodiments described above.

[0757] (Claim 1)

[0758] Means for receiving digital data,

[0759] A means for analyzing the aforementioned digital data to identify important scenes,

[0760] A means for automatically editing based on the identified important scenes,

[0761] Means of providing edited digital data to users,

[0762] A system that includes this.

[0763] (Claim 2)

[0764] The system according to claim 1, comprising means for enabling the uploading of digital data through a user interface.

[0765] (Claim 3)

[0766] The system according to claim 1, comprising means for applying sentiment analysis to analyzed digital data and highlighting emotional moments during editing.

[0767] "Example 1"

[0768] (Claim 1)

[0769] Means of receiving information,

[0770] A means for analyzing the aforementioned information to recognize important scenes,

[0771] A means for automatically making changes based on the recognized important scenes,

[0772] A means of presenting the changed information to the user,

[0773] A system that includes this.

[0774] (Claim 2)

[0775] The system according to claim 1, comprising means for enabling the transmission of information through a user interface.

[0776] (Claim 3)

[0777] The system according to claim 1, comprising means of applying sentiment analysis to the analyzed information and highlighting emotional moments during changes.

[0778] "Application Example 1"

[0779] (Claim 1)

[0780] Means for receiving digital information,

[0781] A means for analyzing the aforementioned digital information to identify important scenes,

[0782] A means for automatically editing based on the identified important scenes,

[0783] Means of providing edited digital information to users,

[0784] A means of making edited digital information downloadable to an information processing device,

[0785] A system that includes this.

[0786] (Claim 2)

[0787] The system according to claim 1, comprising means for enabling the uploading of digital information through a user interface.

[0788] (Claim 3)

[0789] The system according to claim 1, comprising means for applying sentiment analysis to analyzed digital information and for highlighting emotional scenes during editing.

[0790] "Example 2 of combining an emotion engine"

[0791] (Claim 1)

[0792] A device for receiving digital information,

[0793] A device that analyzes the aforementioned digital information to identify a specific scene,

[0794] A device that uses an emotion engine that combines facial recognition and emotion analysis,

[0795] A device that uses generative AI technology to select an editing style based on a prompt sentence,

[0796] A device that automatically edits according to the user's emotions,

[0797] A device that provides edited digital information,

[0798] A system that includes this.

[0799] (Claim 2)

[0800] The system according to claim 1, comprising a device that enables the uploading of digital information via a user interface.

[0801] (Claim 3)

[0802] The system according to claim 1, comprising a device that applies sentiment analysis to analyzed digital information and emphasizes emotional characteristics during editing.

[0803] "Application example 2 when combining with an emotional engine"

[0804] (Claim 1)

[0805] Means for receiving digital data,

[0806] A means for analyzing the aforementioned digital data to identify important scenes,

[0807] A means for automatically editing based on the identified important scenes,

[0808] Means of providing edited digital data to users,

[0809] A method for selecting an emotionally-based editing style using emotion analysis,

[0810] ...

[0811] A system that includes this.

[0812] (Claim 2)

[0813] The system according to claim 1, comprising means for enabling the uploading of digital data through a user interface.

[0814] (Claim 3)

[0815] The system according to claim 1, comprising means for applying sentiment analysis to analyzed digital data and highlighting emotional moments during editing. [Explanation of Symbols]

[0816] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for receiving digital data, A means for analyzing the aforementioned digital data to identify important scenes, A means for automatically editing based on the identified important scenes, Means of providing edited digital data to users, A system that includes this.

2. The system according to claim 1, comprising means for enabling the uploading of digital data through a user interface.

3. The system according to claim 1, comprising means for applying sentiment analysis to analyzed digital data and for highlighting emotional moments during editing.

Images