Real-time Video Summary Generation via Person Recognition
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Solution Overview
Problem
Existing digital video processing systems struggle to generate video summaries on digital capture devices with minimal delay, especially when users want to highlight specific features like people, pets, events, or objects, as existing automatic summarization algorithms require decompressing the video data, making it impractical for immediate review and sharing.
Innovation Solution
A digital video camera system that captures video sequences and generates summaries by analyzing image frames in real-time using a person recognition algorithm, storing the summary in metadata without decompressing the video data, allowing for immediate viewing and sharing on the device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If automatic video summarization algorithms are used to generate video summaries, then video content analysis is improved, but processing time and device complexity increase significantly due to the need to decompress video data
Solution Approach 1:
The system performs preliminary analysis of video frames during the capture process itself, identifying key frames and features before the video is fully recorded or compressed. This allows the summarization to be prepared in advance, eliminating the need for time-consuming decompression and re-analysis after capture.
Solution Approach 2:
The patent extracts only the essential visual information from video frames during capture, storing condensed representations rather than full-frame data. This extraction of key features enables rapid summarization without requiring complete video decompression, significantly reducing processing time while maintaining content analysis quality.
2Loss of information
If automatic video summarization algorithms are used to generate video summaries, then video content analysis is improved, but device complexity increases making it impractical for digital capture devices
Solution Approach 1:
The video processing system is segmented into distinct functional modules: frame capture, key frame identification, feature extraction, and summary generation. Each module performs a specific task independently, reducing overall system complexity while maintaining comprehensive video analysis capabilities.
Solution Approach 2:
The patent extracts only the essential visual information from video frames during capture, storing condensed representations rather than full-frame data. This extraction of key features enables rapid summarization without requiring complete video decompression, significantly reducing processing time while maintaining content analysis quality.
3Adaptability or versatility
If manual video editing is used to create tailored video summaries, then customization to specific features is improved, but time consumption and labor intensity increase
Solution Approach 1:
The system automatically identifies and selects video frames containing specific features (people, pets, events, objects) without requiring manual user input. The algorithm autonomously analyzes video content, detects desired features, and generates customized summaries, eliminating the need for time-consuming manual editing while maintaining high adaptability to user preferences.
Solution Approach 2:
The system incorporates feedback mechanisms where user selections of desired features (people, pets, events, objects) are used to train and refine the automatic summarization algorithm. This feedback loop enables the system to progressively improve its ability to create customized summaries matching user preferences without requiring manual editing of each video.
Data Source
AI summary
A digital video camera system that provides a video summary using a method that includes: designating a reference image containing a particular person; capturing a video sequence of the scene using the image sensor, the video sequence including a time sequence of image frames; processing the captured video sequence using a video processing path to form a digital video file; during the capturing of the video sequence, analyzing the captured image frames using a person recognition algorithm to identify a subset of the image frames that contain the particular person; forming the video summary including fewer than all of the image frames in the captured video sequence, wherein the video summary includes at least part of the identified subset of image frames containing the particular person; storing the digital video file in the storage memory; and storing a representation of the video summary in the storage memory.