Intrusion Detection Filtering for Repeated Object Movement
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Solution Overview
Problem
Camera-to-camera control systems are prone to false alarms due to objects moving periodically or sporadically within the captured scene, often caused by environmental conditions such as rain, snow, or wind, which affect the accuracy of intrusion detection.
Innovation Solution
A system that identifies an area of interest around detected objects and ignores their movement if it persists within that area for a predetermined time or exceeds a threshold, resetting intrusion detection parameters when the total area of such objects exceeds a defined threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the intrusion detection system detects all moving objects within the field of view, then the detection sensitivity is improved, but false alarms increase due to periodic or sporadic movement caused by environmental conditions
Solution Approach 1:
The system performs preliminary analysis by tracking object movement over a predetermined time period before triggering an alarm. It establishes a baseline of normal periodic movement patterns and only generates alerts when movement exceeds these pre-established thresholds, thereby distinguishing between environmental disturbances and actual intrusions
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring movement patterns and adjusting detection sensitivity based on learned behaviors. When periodic movement is detected, the system adapts its response threshold, reducing false alarms while maintaining sensitivity to abnormal movement patterns that deviate from the established feedback loop
2Reliability
If the system ignores moving objects to reduce false alarms, then the false alarm rate decreases, but the detection of actual intruders may be compromised
Solution Approach 1:
The system applies different detection rules to different spatial regions within the field of view. Areas with confirmed periodic environmental movement receive reduced sensitivity (ignoring mode), while other regions maintain high detection sensitivity. This localized quality adjustment allows the system to suppress false alarms in specific zones without compromising overall intrusion detection capability
Solution Approach 2:
The system dynamically adjusts its detection parameters based on real-time analysis of movement patterns. When an object exhibits periodic movement characteristic of environmental conditions, the system temporarily reduces sensitivity for that specific object and region. However, if the movement pattern changes or new objects appear, the system automatically recalibrates, ensuring dynamic adaptation that prevents both false alarms and missed detections
Data Source
AI summary
The present application describes a system and method for mitigating false alarms caused by repeated and/or sporadic movement of objects in a field of view of an image capture device.