Dynamic Camera Calibration Using Moving Vehicle Reflectors
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Solution Overview
Problem
Existing camera calibration methods for traffic monitoring systems require static targets, which disrupt traffic and are costly, as they necessitate road closures or diversion, and can distract motorists, leading to inaccurate speed detection due to improper calibration.
Innovation Solution
A method and system using a test vehicle equipped with a calibration target grid of reflectors that passes through the camera's field of view, allowing for automated identification and calibration without disrupting traffic, utilizing an iterative data alignment and outlier algorithm to construct a camera calibration map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static calibration targets are used for camera calibration, then calibration accuracy is improved, but traffic disruption and cost increase
Solution Approach 1:
The patent transforms the static calibration target into a dynamic one by mounting it on a moving vehicle. The calibration target moves through the camera's field of view with traffic flow, eliminating the need for road closures while still providing sufficient data points for accurate calibration. The system processes multiple frames captured during the vehicle's passage to achieve calibration accuracy comparable to static methods.
Solution Approach 2:
The patent introduces a moving vehicle as an intermediary carrier for the calibration target. This intermediary allows the calibration process to occur within normal traffic flow without requiring direct placement of targets on the road surface, thus avoiding traffic disruption while maintaining calibration effectiveness.
2Ease of manufacture
If static calibration targets are placed on the road, then calibration can be performed, but motorist distraction and safety hazards increase
Solution Approach 1:
The moving vehicle serves as an intermediary that carries the calibration target through traffic rather than placing the target directly in the road. This eliminates the hazard of stationary objects distracting motorists while maintaining the ability to perform calibration during normal traffic conditions.
Solution Approach 2:
The calibration process occurs continuously during normal traffic flow rather than requiring separate road closure events. The calibration target moves continuously with traffic, allowing calibration data to be collected without interrupting the continuous flow of motorists, thus eliminating distraction hazards.
3Measurement precision
If road closures are implemented for camera calibration, then calibration accuracy is improved, but societal cost and productivity loss increase
Solution Approach 1:
The patent employs a dynamic calibration approach where the target moves with traffic flow rather than requiring static placement during road closures. This allows calibration to occur during normal productive traffic conditions, eliminating productivity loss while maintaining accuracy through processing multiple dynamic frames.
Solution Approach 2:
The calibration process occurs continuously during normal traffic operation rather than requiring intermittent road closures. Traffic flow productivity is maintained at full capacity while calibration data is collected continuously as the target vehicle passes through the camera's field of view.
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
Enables accurate camera calibration without traffic disruptions, improving the precision of speed detection and reducing costs associated with road closures, while maintaining continuous traffic flow.
Implementation Method 1
configuring a calibration target comprising calibration reflectors on a test vehicle
Data Source
AI summary
A method and system for camera calibration comprises configuring a calibration target comprising calibration reflectors on a test vehicle. Video of a test scene is collected. Next the test vehicle is identified as it enters the test scene and recorded as it passes through the test scene. The position of the calibration target in each frame of the video is determined and the corresponding individual position of each calibration reflector for each frame of the recorded frames is used to construct a camera calibration map to calibrate the video camera.