Virtual Boundary Crossing Detection via Ground Patch Analysis
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Solution Overview
Problem
Existing video surveillance systems face challenges in accurately detecting virtual boundary line crossings, particularly in crowded scenes or when objects are close together or connected by long shadows, leading to incorrect detection.
Innovation Solution
The method involves defining a virtual boundary line in a video region of interest, establishing ground patch regions, extracting attributes from these regions, updating a history model, and analyzing it to detect object crossings without relying on explicit object detection and tracking techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prior art tripwire approaches are used based on object detection and tracking, then the system can determine boundary crossings by detecting intersections, but detection accuracy deteriorates in crowded scenes, when objects are very close together, or when objects are connected by long shadows
Solution Approach 1:
The patent divides the monitoring region into multiple ground patch regions along the virtual boundary line. Each ground patch region is independently analyzed for attribute changes, allowing the system to detect crossings even when objects are crowded or connected by shadows. This segmentation approach avoids the need for complex object tracking and intersection detection that fail in difficult scenarios.
Solution Approach 2:
The patent introduces ground patch regions as intermediary elements between the virtual boundary line and the objects. Instead of directly detecting object-tripwire intersections, the system monitors attribute changes in these intermediate ground patches. This intermediary approach enables reliable detection by focusing on local ground characteristics rather than complex object trajectories.
2Reliability
If manual monitoring is used, then detection of various events can be performed, but the process becomes manually intensive and less efficient
Solution Approach 1:
The system performs automatic boundary crossing detection by analyzing attribute changes in ground patch regions without requiring manual monitoring. The automated analysis of ground patch attributes enables the system to independently detect crossings, eliminating the need for human operators to manually review video footage while maintaining high detection reliability.
3Extent of automation
If object detection and tracking techniques are used to detect tripwire crossings, then intersections can be identified, but false detections occur in crowded scenes and when objects are connected by long shadows
Solution Approach 1:
The patent extracts and analyzes only the relevant attributes from ground patch regions, ignoring irrelevant information about object identities, trajectories, and appearances. By extracting only the necessary attributes (such as pixel intensity changes, motion patterns) from the ground patches, the system achieves accurate detection without the complexity and errors associated with full object detection and tracking.
Data Source
AI summary
An approach that detects objects crossing a virtual boundary line is provided. Specifically, an object detection tool provides this capability. The object detection tool comprises a boundary component configured to define a virtual boundary line in a video region of interest, and establish a set of ground patch regions surrounding the virtual boundary line. The object detection tool further comprises an extraction component configured to extract a set of attributes from each of the set of ground patch regions, and update a ground patch history model with the set of attributes from each of the set of ground patch regions. An analysis component is configured to analyze the ground patch history model to detect whether an object captured in at least one of the set of ground patch regions is crossing the virtual boundary line in the video region of interest.