Real-Time Video Summarization Using Incremental Frame Selection
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Solution Overview
Problem
Existing video summarization algorithms require significant processing and storage resources, making them impractical for ultra-low power devices like wearable cameras, which struggle to summarize video streams in real-time without transferring large data to backend machines.
Innovation Solution
A real-time video summarization method that incrementally summarizes video streams by selecting and storing salient frames on the device, using a combination of coverage and diversity scoring to optimize frame selection, allowing for ultra-low power operation and reduced storage and communication requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If automated video summarization algorithms process the entire pre-recorded video file, then comprehensive summary coverage is achieved, but processing and storage resources are heavily consumed
Solution Approach 1:
The system performs preliminary action by selecting and storing salient frames incrementally as the video stream arrives, rather than waiting to process the entire video file. This allows the summarization to begin early and continue with minimal resource usage throughout video playback, achieving comprehensive coverage without the heavy resource burden of post-processing the complete video.
Solution Approach 2:
The video stream is segmented into individual frames that are processed independently. The system divides the video into discrete frame units and selectively processes only those frames deemed salient based on diversity and coverage scoring, rather than processing the entire video as a single unit. This segmentation enables efficient resource utilization while maintaining summary quality.
2Loss of information
If the entire video stream is transferred to a backend machine for processing, then summarization quality is improved, but communication channel load increases
Solution Approach 1:
The system extracts only the essential information needed for summarization by selecting salient frames directly on the device. Instead of transferring the entire video stream to a backend machine, the system takes out only the critical frames that represent key events and scenes, performing summarization locally with minimal data transmission requirements.
3Use of energy by moving object
If video summarization is performed in real-time as stream arrives, then resource consumption is reduced, but summarization completeness may be compromised
Solution Approach 1:
The system implements feedback mechanisms by continuously evaluating incoming frames against previously selected summary frames using diversity and coverage scoring. This feedback loop allows the system to adaptively select frames that maintain summary completeness while consuming minimal resources, ensuring that each selected frame contributes unique value to the overall summary.
Data Source
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Figure 3
AI summary
System, apparatus, method, and computer readable media for on-the-fly captured video summarization. A video stream is incrementally summarized in concurrence with generation of the stream by a camera module. Saliency of the video stream summary is maintained as the stream evolves by updating the summary to include only the most significant frames. In one exemplary embodiment, saliency is determined by optimizing an objective function including terms that are indicative of both the diversity of a selection, and how representative the selection is to the processed portion of the video data corpus. A device platform including a CM and comporting with the exemplary architecture may provide video camera functionality at ultra-low power, and/or with ultra-low storage resources, and/or with ultra-low communication channel bandwidth.