3D Video Surveillance System Using Stereo Vision Disparity Map
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Solution Overview
Problem
Video surveillance systems using single 2D cameras are prone to visual errors due to lighting and shadow issues, leading to inaccurate detection of objects entering or leaving monitored areas.
Innovation Solution
A three-dimensional detecting device utilizing a disparity map generated from data from two cameras to track objects in 3D space, mapping them onto a plane view and determining if they have crossed predetermined boundaries or sub-sections, thereby improving detection accuracy by accounting for depth and movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single 2D camera is used for video surveillance, then the device complexity is reduced, but the measurement precision of object position and intrusion detection deteriorates due to inability to accurately distinguish depth and spatial relationships
Solution Approach 1:
The patent transitions from 2D image capture to 3D spatial detection by introducing a second camera to create stereo vision. The system captures images from two different viewpoints and processes them to generate depth information, enabling accurate measurement of object positions in three-dimensional space rather than flat two-dimensional planes.
Solution Approach 2:
The patent introduces an image processing unit as an intermediary that receives images from both cameras and generates a disparity map. This intermediate processing step calculates depth information by comparing corresponding points in the two images, serving as a mediator that transforms raw image data into meaningful 3D spatial information for intrusion detection.
2Use of energy by moving object
If a single 2D camera is used for video surveillance, then the use of energy is reduced, but the reliability of intrusion detection deteriorates due to vulnerability to lighting and shadow errors
Solution Approach 1:
By adding the depth dimension through stereo vision, the system creates a third dimension of information that is independent of lighting conditions. The disparity map provides structural spatial relationships that remain consistent regardless of illumination variations, making intrusion detection more reliable while the energy penalty is limited to adding only one more camera.
3Measurement precision
If disparity map processing is implemented, then the measurement precision of depth information is improved, but the loss of time in processing images increases due to additional computational requirements
Solution Approach 1:
The system performs preliminary calibration of the two-camera system beforehand, storing extrinsic and intrinsic parameters for later use. This pre-processing step eliminates the need to calculate camera geometry during real-time operation, allowing the disparity map generation to focus only on the essential depth calculation from captured images, thus reducing processing time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy of intrusion detection by reducing false positives and improving the system's ability to track objects in real-time, even when they are moving, by calculating depth and movement within a 3D space, thus reducing vulnerability to lighting and shadow-related errors.
Implementation Method 1
a three dimensional detecting device which uses optical parallax of an object to calculate the depth of the object
Data Source
AI summary
A method includes generating a disparity map according to two sets of image data, identifying at least one object in the disparity map, mapping the at least one object onto a plane view, tracking at least one object on the plane view, and providing a robust algorithm about a cross-line time interval and a cross-line degree. The robust algorithm includes detecting whether the at least one object enters a predetermined region when the at least one object crosses a predetermined boundary.