Automated Live Video Clip Generation via Scene Detection
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Solution Overview
Problem
Current social video platforms face challenges in enabling effective collaboration among users for producing video content based on live events, such as newscasts or sporting events.
Innovation Solution
A method for automatically producing live video content involves receiving input video from user devices, processing it using object recognition and scene detection algorithms, generating a sequence of video clips, and sending them to client devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual collaboration methods are used for producing video content, then user interaction is possible, but productivity and real-time processing capability are reduced
Solution Approach 1:
The system enables self-service by implementing automated video processing capabilities that independently perform scene detection, object recognition, and clip generation without requiring manual intervention. The processor automatically receives input video, processes it through AI algorithms, and generates output clips, allowing the system to serve itself in the content production workflow.
Solution Approach 2:
The patent replaces manual mechanical operations with automated computational processes. Instead of human operators manually editing and organizing video content, the system uses processors executing scene detection and object recognition algorithms to automatically generate video clips, substituting mechanical human labor with automated digital processing.
2Productivity
If automated processing is implemented, then productivity increases, but device complexity increases
Solution Approach 1:
The video processing system is segmented into distinct functional modules: scene detection algorithms, object recognition algorithms, and clip generation processes. Each module handles a specific aspect of video processing independently, allowing the complex task of automated video production to be divided into manageable segments that can be processed in sequence by the processor.
3Productivity
If real-time processing is performed, then collaboration efficiency improves, but use of energy increases
Solution Approach 1:
The system performs preliminary action by pre-processing video content through scene detection and object recognition before final clip generation. The processor identifies and tags scenes and objects in advance, organizing the video data structure beforehand, which enables faster real-time clip generation without requiring intensive energy consumption during the actual production moment.
Data Source
AI summary
Systems and methods described herein are configured to enhance the understanding and experience of news and live events in real-time. The systems and methods leverage a distributed network of professional and amateur journalists/correspondents using technology to create unique experiences and/or provide views and perspectives different from experiences, views and/or perspectives provided by existing newscasts and/or sportscasts.