Surveillance Camera Obstruction Detection With Instance Segmentation
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Solution Overview
Problem
Surveillance cameras in industrial settings are often obstructed by vehicles or structures, reducing their effectiveness in monitoring and security, with conventional methods prone to false positives and requiring static environments.
Innovation Solution
An advanced instance segmentation technique is used to analyze video streams, calculating an obstruction ratio and generating alerts when the obstruction exceeds a threshold, with adaptive responses to dynamic environments, including timers and secondary camera views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional image quality monitoring is used to detect obstructions, then the system can identify potential blockages, but it produces false positives due to lighting or weather variations
Solution Approach 1:
The patent applies segmentation by dividing the video stream into individual object instances using instance segmentation techniques. This allows the system to distinguish between actual obstruction objects and environmental variations, as each segmented object can be analyzed independently for obstruction characteristics rather than relying on overall image quality changes that are susceptible to false positives.
Solution Approach 2:
The patent utilizes color and visual characteristics of segmented objects to differentiate between actual obstructions and environmental conditions. By analyzing the visual properties of detected objects, the system can distinguish between objects that represent true obstructions versus those caused by lighting or weather variations, thereby reducing false positive alerts.
2Reliability
If reference image comparison is used to detect obstructions, then the system can identify deviations from the reference scene, but it fails in dynamic environments where the background changes naturally
Solution Approach 1:
The patent implements dynamics by using instance segmentation that can identify and track individual objects in real-time video streams, rather than comparing against a static reference image. This dynamic approach allows the system to adapt to changing environments by continuously segmenting and analyzing current objects, distinguishing between actual obstructions and natural background changes through object instance tracking and temporal analysis.
Solution Approach 2:
The patent employs feedback mechanisms where the instance segmentation results are continuously analyzed and compared over time. The system uses feedback from object detection, tracking, and classification to dynamically adjust its obstruction detection, allowing it to adapt to environmental changes while maintaining accurate obstruction identification through continuous monitoring and learning from detected patterns.
3Stability of the object's composition
If surveillance cameras are fixed at specific locations, then the system provides stable monitoring coverage, but obstructions from vehicles or structures can completely block the field of view
Solution Approach 1:
The patent introduces an intermediary computational layer that processes video streams from fixed cameras to detect, segment, and analyze obstruction objects. This intermediary system acts as a mediator between the fixed camera and the monitoring objective, identifying and characterizing obstructions through instance segmentation and providing alerts or alternative views when obstructions are detected, thereby maintaining surveillance effectiveness despite fixed camera positions.
Solution Approach 2:
The patent replaces the mechanical solution of moving or repositioning cameras with a computational approach using instance segmentation and object detection algorithms. Instead of physically adjusting camera positions to avoid obstructions, the system uses software-based object identification, tracking, and analysis to detect and respond to obstructions, maintaining stable fixed camera installations while preserving monitoring reliability through intelligent video analysis.
Data Source
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AI summary
Disclosed is a method (100) and a system (200) for managing obstructions in a field of view of a surveillance camera (304a-304d). The method comprises receiving a video stream from the surveillance camera. The method further comprises processing the video stream to segment each object (306) within the video stream. The method further comprises calculating an obstruction ratio representing a proportion of the field of view of the surveillance camera occluded by the segmented object. The method further comprises comparing the obstruction ratio with a predetermined obstruction threshold. The method further comprises generating an output signal when the obstruction ratio exceeds the predetermined obstruction threshold. The method further comprises configuring an alert unit to issue an obstruction alert upon being triggered by the output signal.