Camera Calibration by Vanishing Lines for 3-D Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Real-time Computer Vision System for Measuring Traffic Parameters
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
The Comparison of Camera Calibration Methods Based on Structured-Light Measurement
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02
An algorithm to estimate mean traffic speed using uncalibrated cameras
IEEE Transactions on Intelligent Transportation Systems
Detection and classification of vehicles
IEEE Transactions on Intelligent Transportation Systems
Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
Lane detection by orientation and length discrimination
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Dynamic Calibration of Pan–Tilt–Zoom Cameras for Traffic Monitoring
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
PixNet: interference-free wireless links using LCD-camera pairs
Proceedings of the sixteenth annual international conference on Mobile computing and networking
Automatic on-the-fly extrinsic camera calibration of onboard vehicular cameras
Expert Systems with Applications: An International Journal
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Many vision-based automatic traffic-monitoring systems require a calibrated camera to compute the speeds and length-based classifications of tracked vehicles. A number of techniques, both manual and automatic, have been proposed for performing such calibration, but no study has yet focused on evaluating the relative strengths of these different alternatives. We present a taxonomy for roadside camera calibration that not only encompasses the existing methods (VVW, VWH, and VWL) but also includes several novel methods (VVH, VVL, VLH, VVD, VWD, and VHD). We also introduce an overconstrained (OC) approach that takes into account all the available measurements, resulting in reduced error and overcoming the inherent ambiguity in single-vanishing-point solutions. This important but oft-neglected ambiguity has not received the attention that it deserves; we analyze it and propose several ways of overcoming it. Our analysis includes the relative tradeoffs between two-vanishing-point solutions, single-vanishing-point solutions, and solutions that require the distance to the road to be known. The various methods are compared using simulations and experiments with real images, showing that methods that use a known length generally outperform the others in terms of error and that the OC method reduces errors even further.