Real-Time Video Movement Pattern Tracking Using Foreground Markings
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Solution Overview
Problem
Conventional methods for tracking movement patterns in digital video signals are complex, error-prone, and unable to identify patterns in real-time, especially with large sets of moving objects, and require continuous visual monitoring by human operators, which is impractical for systems with many cameras.
Innovation Solution
A method that analyzes digital video signals in real-time by identifying background and foreground regions, applying markings to detect relative movements, and calibrating PTZ cameras using an orthogonal coordinate system to determine their position, allowing for automatic analysis and evaluation of video data without continuous human oversight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional methods are used to track movement patterns in digital video signals, then tracking capability is provided, but the methods become very complicated and error-prone, and real-time identification is not possible
Solution Approach 1:
The patent divides the video analysis process into distinct segments: background determination, foreground region identification, and movement pattern detection. By segmenting the complex task into manageable components, the system achieves reliable tracking without requiring overly complicated methods. Each segment can be processed independently and efficiently.
Solution Approach 2:
The patent performs preliminary determination of background regions and foreground regions before detecting movement patterns. This preliminary action simplifies the subsequent movement detection process by pre-establishing reference frames and object regions, enabling real-time analysis without complex real-time processing of all video data.
2Area of stationary object
If conventional methods are used to monitor a large number of video cameras, then comprehensive coverage is achieved, but continuous visual monitoring requires excessive personnel resources
Solution Approach 1:
The patent implements automatic video analysis that performs background determination, foreground detection, and movement pattern identification without human intervention. The system serves itself by automatically processing video data from multiple cameras, generating alerts only when movement patterns are detected, thereby eliminating the need for continuous human monitoring while maintaining comprehensive coverage.
Solution Approach 2:
The patent replaces the mechanical system of human visual monitoring with an automated computational system. Instead of relying on human operators to watch multiple camera feeds, the system uses algorithms to automatically analyze video signals, detect movements, and identify patterns, significantly reducing personnel requirements while maintaining or improving monitoring effectiveness.
3Area of stationary object
If more video cameras are installed to increase security coverage, then monitoring area is expanded, but the number of recorded pictures increases making processing infeasible
Solution Approach 1:
The patent extracts only the essential information from video signals by determining background regions once and identifying only foreground regions that contain movement. Instead of processing all picture data from multiple cameras, the system extracts and analyzes only the relevant movement information, maintaining processing feasibility even as the number of cameras and monitoring area expand.
Solution Approach 2:
The patent applies partial action by focusing computational resources only on regions containing movement rather than analyzing entire video frames from all cameras. By performing background subtraction and detecting only changing foreground regions, the system achieves efficient processing that scales with the number of cameras without requiring proportional increases in computational power.
Data Source
AI summary
In a method for locating patterns of movement in a first digital video signal, wherein the first digital video signal comprising at least indirectly succeeding individual digital images is analyzed in real time, it is proposed for the locating of patterns of movement in a first digital video signal, during the occurrence of larger moving object volumes in real time, to assign at least a first location-changing foreground region in a first individual image in a predefined manner with a predefinable number of first markings, to subsequently determine the relative movement of the first markings between the first individual image and a subsequent second individual image, to subsequently associate each of the first markings with a predefinable first environment, to assign the first and/or at least one second location-changing foreground region in a predefined manner with a predefinable number of second markings, to remove the second markings disposed inside intersecting regions of a predefinable number of intersecting first environments, to subsequently determine the relative movement of the first and second markings between the second individual image and a subsequent third individual image, and to output the relative movements of the first and/or second markings as a first pattern of movement.