Key Frame Extraction for Blackboard Occlusion in Online Education
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Solution Overview
Problem
Current online education video systems struggle to provide clear context and user-friendly interaction, as users face difficulties in viewing blackboard content due to occlusions and lack of preprocessing, leading to restricted viewing experiences and high recording costs.
Innovation Solution
A method and system that automatically identifies and extracts key frames from video streams, focusing on blackboard content, by detecting object movements, occlusions, and information changes, and serializing these frames with timestamps, allowing for improved user interaction and reduced recording costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video recording of classroom is provided for online education, then accessibility is improved, but user experience is worsened due to restricted view of content context
Solution Approach 1:
The system segments the video content by identifying and extracting key frames that contain important blackboard information, separating essential content from redundant visual data. This allows users to access content more effectively without viewing the entire video stream.
Solution Approach 2:
The system extracts key frames containing blackboard content from the video stream, isolating important information from the full video. This extraction process removes occlusions and focuses on essential educational content, improving user experience while maintaining accessibility.
2Loss of information
If full video recording is provided, then complete content is available, but recording cost and complexity increase
Solution Approach 1:
The system performs preliminary processing by identifying and marking key frames during or after video capture. This preliminary action of selecting important frames reduces the overall data volume that needs to be stored and transmitted, simplifying the recording system while preserving essential content.
Solution Approach 2:
The system creates simplified copies of the video content in the form of key frames that represent essential blackboard information. These key frame copies capture the essential educational content without requiring storage and transmission of the complete high-resolution video stream.
3Device complexity
If video playback is provided without preprocessing, then simplicity is maintained, but user comprehension is reduced due to occlusions and playback difficulties
Solution Approach 1:
The system performs preliminary processing by identifying and marking key frames during or after video capture. This preliminary action of selecting important frames reduces the overall data volume that needs to be stored and transmitted, simplifying the recording system while preserving essential content.
4Ease of operation
If key frame extraction is implemented, then user experience is improved with clear blackboard focus, but processing complexity increases
Solution Approach 1:
The system employs automated algorithms that self-service the key frame extraction process without requiring manual intervention. The system automatically identifies blackboard regions, detects occlusions, and selects key frames based on content importance, reducing the need for complex manual processing while improving user experience.
Data Source
AI summary
A method stored in a computer readable medium, including identifying a predetermined object having viewable information from a plurality of frames, identifying a movement of the predetermined object from a video stream of the plurality of frames, identifying a current state of the predetermined object based on a movement of another object or region from the plurality of frames having an occlusion region of a current frame, determining an information change of the viewable information in the plurality of frames, marking a frame with maximum information of the viewable information in the predetermined object as a key frame; and serializing the key frame according to time stamps.