Motion Recap Images for Faster Video Event Review
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Solution Overview
Problem
Current video review systems are resource-intensive and time-consuming due to the large volume of video data that needs to be analyzed, especially when identifying interesting events, which can burden users and consume significant CPU, memory, storage, and bandwidth resources.
Innovation Solution
Generate motion recap images by superimposing or stacking instances of moving objects from multiple frames onto a single frame, allowing users to quickly assess video content and reduce resource utilization by enabling efficient video review, even in network failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video footage is reviewed to identify interesting events, then event detection accuracy is improved, but time consumption and resource usage increase significantly
Solution Approach 1:
The patent segments video review into two stages: first, generate condensed motion recap images that capture essential motion information from video clips; second, review these condensed images instead of full video footage. This segmentation reduces the volume of content to be reviewed while preserving event detection capability, directly addressing the time consumption problem without sacrificing detection accuracy.
Solution Approach 2:
The patent creates condensed motion recap images as simplified copies of the original video content. These recap images replicate the essential motion information and key events from the video clips in a compressed visual format, allowing users to review events efficiently without watching the entire video footage, thus reducing time consumption while maintaining event detection accuracy.
2Measurement precision
If video footage is reviewed to identify interesting events, then event detection accuracy is improved, but resource usage (CPU, memory, storage, bandwidth, power) increases significantly
Solution Approach 1:
The patent segments the resource-intensive video review process into two phases: (1) automated generation of condensed motion recap images that capture essential motion information, and (2) review of these condensed images. This segmentation shifts the computational burden to the initial recap generation phase, while the review phase requires minimal resources, thereby reducing overall resource usage while maintaining event detection accuracy.
Solution Approach 2:
The patent creates condensed motion recap images as resource-efficient copies of video content. These recap images preserve key event information in a compressed format that requires minimal computational resources to process and review, directly reducing CPU, memory, storage, bandwidth, and power consumption compared to reviewing full video footage while maintaining event detection capability.
3Loss of information
If multiple clips and lengthy individual clips are reviewed, then comprehensive event coverage is improved, but time consumption and resource usage increase
Solution Approach 1:
The patent creates condensed motion recap images that serve as comprehensive yet compressed representations of multiple video clips. These recap images capture motion information and key events from all clips in a single reviewable format, ensuring complete event coverage while reducing the review time from reviewing multiple lengthy clips to reviewing condensed visual summaries.
4Measurement precision
If security camera systems excerpt clips meeting certain criteria, then event identification is improved, but resource usage increases when there are large numbers of clips
Solution Approach 1:
The patent creates condensed motion recap images as efficient visual copies that summarize the content of multiple video clips. These recap images preserve event identification information in a compressed format, allowing users to review and identify events across large numbers of clips without the resource burden of reviewing each individual clip, thus maintaining event identification accuracy while reducing resource usage.
Data Source
Figure 1A~1B
Figure 2A
Figure 2B
AI summary
Systems and methods provide for optimizing video review using motion recap images. A video review system can identify background image data of a video clip including an amount of motion satisfying a motion threshold. The video review system can generate foreground mask data segmenting foreground image data, representing a moving object in the video clip, from the background image data. The video review system can select a set of instances of the moving object represented in the foreground image data. The video review system can generate a motion recap image by superimposing the set of instances of the moving object represented in the foreground image data onto the background data.