Automated Video Frame Extraction for High-Quality Image Capture
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Solution Overview
Problem
Conventional image capture techniques struggle to efficiently extract high-quality still images from videos, especially when capturing fleeting moments, due to the tedious and time-consuming manual process of sifting through video frames, which is exacerbated by the larger file size and bandwidth requirements of video files compared to images.
Innovation Solution
An automated system that calculates scores for each frame of a video segment based on factors like zoom, alignment, eyes openness, overlap, and motion, allowing for the automatic extraction and transcoding of the highest-scoring frame as a high-quality image, reducing the need for manual intervention and enhancing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video files are used to capture fleeting moments, then the ability to capture moving subjects and commotion is improved, but the file size and bandwidth requirements increase
Solution Approach 1:
The patent extracts only the essential frames from video sequences that contain the fleeting moments of interest, rather than transmitting or storing the entire video file. This extraction process identifies and isolates key frames that capture the critical moments while discarding redundant video data, thereby reducing file size while preserving the ability to capture and share important moments.
2Measurement precision
If manual frame-by-frame analysis is used to extract still images from video, then the ability to select specific moments is improved, but the time and effort required increases
Solution Approach 1:
The system performs self-service by automatically analyzing video frames and identifying fleeting moments without requiring manual user intervention. The patent implements automated detection algorithms that examine video content, identify key moments based on motion and change detection, and extract appropriate still images autonomously, eliminating the need for time-consuming manual frame-by-frame review by users.
3Reliability
If video files are uploaded to social media, then the ability to share fleeting moments is improved, but the bandwidth consumption and upload time increase
Solution Approach 1:
The patent extracts only the essential frames from video sequences that contain the fleeting moments of interest, rather than transmitting or storing the entire video file. This extraction process identifies and isolates key frames that capture the critical moments while discarding redundant video data, thereby reducing file size while preserving the ability to capture and share important moments.
Data Source
AI summary
Various embodiments calculate a score for each frame of a video segment based on various subject-related factors associated with a subject (e.g., face or other object) captured in a frame relative to corresponding factors of the subject in other frames of the video segment. A highest-scoring frame from the video segment can then be extracted based on a comparison of the score of each frame of the video segment with the score of each other frame of the video segment, and the extracted frame can be transcoded as an image for display via a display device. The score calculation, extraction, and transcoding actions are performed automatically and without user intervention, which improves previous approaches that use a primarily manual, tedious, and time consuming approach.