Directional Detection Vector for Video Intrusion Alarm Reduction
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Solution Overview
Problem
Current video motion detection systems are prone to false alarms due to sensitivity to all changes in intensity, including shadows and headlights of moving vehicles, which can lead to incorrect detection of targets outside the designated detection area, and the use of trigger lines does not fully mitigate this issue.
Innovation Solution
A method and system that utilize a detection vector specifying a minimum displacement and direction within a defined image detection area, allowing for the tracking of target objects and activation of an alarm only when the target's displacement exceeds this minimum displacement in the specified direction, thereby reducing false alarms from shadows and headlights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video motion detection is sensitive to all changes in intensity, then detection coverage is comprehensive, but false alarms increase due to shadows and headlights
Solution Approach 1:
The detection area is segmented into multiple regions of interest (ROIs), allowing different sensitivity levels and detection parameters to be applied to different zones. This enables the system to focus detection resources on critical areas while reducing sensitivity in areas prone to false alarms, thereby improving overall detection accuracy without increasing false positives.
Solution Approach 2:
Different detection parameters, sensitivity thresholds, and vector configurations are applied locally to different regions within the detection area. By tailoring detection characteristics to specific zones, the system can maintain high sensitivity where needed while reducing false alarm susceptibility in other areas, resolving the contradiction between comprehensive detection and false alarm reduction.
2Object-affected harmful factors
If trigger lines are used to reduce false alarms, then specificity improves, but detection reliability decreases due to track loss
Solution Approach 1:
The system transitions from two-dimensional trigger line detection to three-dimensional vector-based detection with depth information. By incorporating depth data and volumetric detection zones, the system can distinguish between objects that merely cross a plane and those that truly intrude, maintaining high specificity while improving reliability through enhanced spatial discrimination.
Solution Approach 2:
The detection parameters are dynamically adjusted based on object characteristics, trajectory analysis, and contextual information. By changing parameters such as detection threshold, vector direction, and minimum displacement requirements adaptively, the system maintains high detection reliability while minimizing false alarms without relying solely on static trigger lines.
3Reliability
If multiple parallel trigger lines are used, then detection reliability improves, but system complexity increases
Solution Approach 1:
The detection vector mechanism serves multiple functions simultaneously: it defines detection direction, establishes minimum intrusion depth, filters out lateral movements, and provides alarm triggering. This multi-functionality replaces the need for multiple parallel trigger lines, maintaining detection reliability while significantly reducing system complexity through a unified detection approach.
4Area of stationary object
If detection areas are expanded to cover more regions, then detection coverage improves, but false alarms from adjacent areas increase
Solution Approach 1:
The expanded detection area is divided into multiple regions of interest with different detection parameters and vector configurations. By segmenting the large detection area into manageable zones, the system can maintain comprehensive coverage while applying localized detection strategies that reduce false alarms from specific problem areas such as adjacent roads or parking lots.
Data Source
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AI summary
A method and system of intrusion detection, which includes displaying sensing device output data as one or more images of a field of view of a sensing device (14.1, 14.2, 14.3). Through interaction with a graphical user interface: a user input to define and display an image detection area in relation to the one or more images of the field of view is received, wherein the image detection area is correlated to a detection area to be monitored by the sensing device (14.1, 4.2, 14.3) for intrusion detection. One or more user inputs that define a detection vector in the image detection area are received, the detection vector specifying a predetermined minimum displacement and direction of displacement in the field of view to be monitored. A graphical representation of the detection vector may be displayed on the image detection area. The method further includes detecting a target object and tracking the target object at least partially through the detection area and determining whether the progressive displacement of the target object has a component which exceeds the minimum displacement in the direction of the detection vector.