Surveillance Module Background Analysis for Stationary Monitoring
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Solution Overview
Problem
Existing video surveillance systems focus on detecting and tracking moving objects, but they lack effective monitoring of stationary components and changes in the scene background, which can be critical for structural and functional state monitoring in buildings and equipment, often requiring extensive cabling and high installation costs for non-video-based security systems.
Innovation Solution
A surveillance module that analyzes the scene background for deviations from predefined base states, ignoring moving foreground objects and using image processing algorithms to monitor stationary and quasi-stationary regions or objects, allowing for the detection of changes in their states, such as open/closed doors or abnormal behavior, and enabling efficient installation with a single camera and cable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If video surveillance systems focus on detecting and tracking moving objects, then moving object detection capability is improved, but monitoring of stationary components and scene background changes deteriorates
Solution Approach 1:
The patent divides the surveillance scene into two distinct segments: moving foreground objects and stationary scene background. By separating the monitoring focus into these two segments, the system can apply different analysis methods to each - traditional motion detection for foreground objects and baseline comparison for background elements. This segmentation resolves the contradiction by allowing both moving object detection and stationary component monitoring to function effectively simultaneously.
Solution Approach 2:
The patent extracts the stationary scene background from the overall surveillance scene and subjects it to separate analysis using baseline state comparison. By taking out the background elements (walls, floors, ceilings, fixed equipment) and comparing them against stored baseline images, the system can detect changes in stationary components without being overwhelmed by the presence of moving objects. This extraction approach enables reliable stationary component monitoring while preserving moving object detection capabilities.
2Measurement precision
If non-video-based security systems are used for structural and functional state monitoring, then monitoring precision is improved, but installation complexity and cabling requirements worsen
Solution Approach 1:
The patent makes the video surveillance system multi-functional by enabling it to perform both traditional moving object detection and stationary component monitoring through baseline comparison. Instead of requiring separate non-video-based systems for structural monitoring, the same video surveillance infrastructure can detect changes in walls, floors, ceilings, and fixed equipment. This universality eliminates the need for extensive additional cabling and installation complexity while maintaining monitoring precision through image analysis.
Solution Approach 2:
The patent replaces mechanical sensing systems (such as sensors, switches, and physical monitoring devices) with optical image processing methods. By using video image analysis and baseline comparison algorithms, the system substitutes complex mechanical installation requirements with simpler camera-based monitoring. This substitution maintains the ability to detect structural and functional states while dramatically reducing installation complexity and cabling requirements.
3Area of stationary object
If scene background analysis is implemented to monitor stationary objects, then monitoring coverage is improved, but processing complexity worsens
Solution Approach 1:
The patent performs preliminary action by capturing and storing baseline images of the scene background during a calibration phase before actual monitoring begins. These baseline images represent the normal state of stationary components and are stored for comparison purposes. By preparing this reference data in advance, the system simplifies real-time processing - instead of performing complex analysis on every frame, the system only needs to compare current frames against the pre-established baseline, significantly reducing processing complexity while maintaining comprehensive monitoring coverage.
Data Source
AI summary
Video monitoring systems usually comprise one or more monitoring cameras directed to related monitored areas such as intersections, parking lots, manufacturing plants, etc., wherein the image data streams recorded by the monitoring camera (S) are often collected at a monitoring center. In the automated evaluation of image data streams, there are known methods that detect moving objects in the monitored area, track them and carry out evaluations based on the detection or tracking. On the other hand, a monitoring module 4 for a video monitoring system 1 is proposed, wherein the monitoring module 4 can be data-coupled and/or is data-coupled to at least one monitoring camera (2), wherein the at least one monitoring camera 2 is directed to a monitored area and the monitored area can be displayed or is displayed as a monitoring scene that includes or can include moving foreground objects and a scene background, and wherein the monitoring module 4 is designed for the analysis of the monitoring scene and for the output of a signal based on the analysis, wherein the output of the signal based on the analysis of the scene background occurs upon deviations in prescribed base states.