Video Surveillance System with Automated Object Tracking
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Solution Overview
Problem
Current video surveillance systems require numerous cameras to monitor large areas effectively, leading to inefficiencies as security personnel can only efficiently monitor a limited number of cameras, and existing technologies fail to electronically filter and alert personnel to unauthorized activity while distinguishing between authorized and unauthorized movements.
Innovation Solution
The system views a three-dimensional space from multiple angles, using intensity and chromaticity data to create pixel models for background subtraction, processing novel pixels into foreground figures, and maintaining a central object and world model to alert personnel only to significant changes, allowing for efficient monitoring and reduced false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the number of cameras is increased to monitor larger areas, then the coverage area is improved, but the number of security personnel required increases proportionally
Solution Approach 1:
The patent replaces manual mechanical monitoring with automated electronic image processing systems. The system automatically detects moving objects through pixel analysis, chromaticity comparison, and background subtraction algorithms, eliminating the need for human operators to manually watch multiple camera feeds. This substitution enables monitoring of hundreds or thousands of cameras by a single operator or completely autonomously.
Solution Approach 2:
The surveillance system performs self-monitoring through automated object detection and tracking. The image processing system automatically identifies moving objects, tracks their paths across multiple cameras, and generates alerts without human intervention. The system serves itself by autonomously analyzing video streams, maintaining object models, and determining when security events occur.
2Reliability
If manual monitoring of multiple cameras is performed, then real-time detection is achieved, but false alarms increase due to inability to distinguish authorized from unauthorized activity
Solution Approach 1:
The system changes the parameters used for object identification by analyzing multiple characteristics simultaneously: chromaticity values, intensity patterns, motion vectors, and temporal consistency. By monitoring changes in these parameters over time and comparing them against learned object models, the system can distinguish between authorized personnel following normal patterns and unauthorized individuals exhibiting anomalous behavior, thereby reducing false alarms while maintaining high detection accuracy.
3Reliability
If numerous cameras are deployed to cover large areas, then surveillance completeness is improved, but the complexity of monitoring and processing increases
Solution Approach 1:
The patent segments the surveillance system into independent modular components: individual camera modules that capture video feeds, separate image processing modules that analyze each feed, object tracking modules that follow detected objects across cameras, and central coordination modules that manage data flow. This segmentation allows the system to scale to hundreds of cameras by simply adding more identical modular units rather than increasing overall system complexity, as each module operates semi-independently with standardized interfaces.
Data Source
AI summary
Viewing a three dimensional area from numerous camera angles at different exposures using intensity and chromaticity data at the different exposures to create a pixel model for each pixel. A current image is compared with the background model to find pixels that have changed from their pixel model. These novel pixels are processed using contiguous region detection and grouped into foreground figures. For each camera, software extracts features from each foreground figure. A central processor maintains an object model for each foreground figure. A graphical user interface displays the relative locations of foreground figures in a world model. The location and identification of the foreground figures is checked against a table of permissions so as to selectively generate an alert. If a figure leaves or is about to leave a cell, the invention accounts for its approximate position and notifies adjacent cells of the expected arrival of the foreground figure.