Motion Metadata Generation for Video Surveillance Search
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Solution Overview
Problem
Current video surveillance systems require users to pre-identify regions of interest before recording, which is impractical for unpredictable event locations, making it difficult to efficiently search for motion events in recorded video data.
Innovation Solution
The system processes video feeds in real-time by partitioning image frames into coarse-cells and macro-blocks, generating motion metadata that associates motion events with frame locations, allowing for efficient searching of motion events within specified regions post-recording.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users pre-identify regions of interest before recording, then processing efficiency is improved, but adaptability to unpredictable event locations deteriorates
Solution Approach 1:
The system performs preliminary action by partitioning the entire video frame into a grid of coarse-cells and further subdividing them into macro-blocks before recording. This pre-division structure is established in advance, allowing the system to efficiently locate and process motion events in any region without requiring users to pre-identify specific areas of interest. The preliminary grid structure enables both efficient processing and adaptability to unpredictable event locations.
Solution Approach 2:
The patent applies segmentation by dividing the video frame into multiple coarse-cells, which are further divided into macro-blocks. This hierarchical segmentation creates a structured framework that allows the system to process motion detection at different levels of granularity. The segmented structure enables efficient processing by limiting analysis to relevant macro-blocks while maintaining adaptability to any event location within the segmented grid.
2Loss of information
If motion metadata is generated for all video data, then search completeness is improved, but data processing overhead increases
Solution Approach 1:
The system segments the video data into coarse-cells and macro-blocks, generating motion metadata only for these segmented units rather than processing the entire video frame as a single unit. This segmentation reduces the volume of data requiring metadata generation while ensuring complete coverage of all potential motion events. The hierarchical segmentation allows for efficient processing overhead management.
Solution Approach 2:
The patent extracts and generates motion metadata only for the macro-block level, which are the functional units containing motion information. By taking out and processing only the relevant macro-block data rather than all video pixels, the system reduces processing overhead while maintaining search completeness for motion events. The extraction of macro-block level metadata provides sufficient information for effective search without unnecessary processing.
Data Source
AI summary
Aspects of the instant disclosure relate to methods for generating motion metadata for a newly captured video feed. In some aspects, methods of the subject technology can include steps for recording a video feed using the video capture system, partitioning the image frames into a plurality of pixel blocks, and processing the image frames to detect one or more motion events. In some aspects, the method may further include steps for generating motion metadata describing each of the one or more motion events. Systems and computer-readable media are also provided.