Automatic Camera Calibration Using Pattern Detection for Vision-Based Speed Sensing

Kanhere, Neeraj Krantiveer; Birchfield, Stan; Sarasua, Wayne

doi:10.3141/2086-04

Cited by 25 publications

(18 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The lane boundaries are used to compute the first vanishing point, while the assumption of zero roll angle is used to estimate the second vanishing point from the perpendicular line. In our previous work we used this same formulation for both manual [10] and automatic [11] calibration. Once calibration has been performed, Schoepflin and Dailey [14] mention that the calculated h and d can be used to recalibrate after PTZ movement using a single vanishing point (VHD), though no results are shown.…”

Section: Taxonomy Applied To Existing Methodsmentioning

confidence: 99%

A Taxonomy and Analysis of Camera Calibration Methods for Traffic Monitoring Applications

Kanhere

Birchfield

2010

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

Abstract-Many vision-based automatic traffic monitoring systems require a calibrated camera for computing 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 upon 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 ones as well (VVH, VVL, VLH, VVD, VWD, and VHD). We also introduce an overconstrained approach that takes into account all the available measurements, resulting in reduced error as well as overcoming the inherent ambiguity in the 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 twovanishing-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 overconstrained method reduces errors even further.

show abstract

Section: Taxonomy Applied To Existing Methodsmentioning

confidence: 99%

A Taxonomy and Analysis of Camera Calibration Methods for Traffic Monitoring Applications

Kanhere

Birchfield

2010

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

show abstract

“…While camera calibration methods are well studied for highways [21][22][23], they do not apply to roundabouts due to different features available in the scene. Previous work on camera calibration of highways mostly takes advantage of parallel traffic lanes [21][22][23].…”

Section: Camera Calibrationmentioning

confidence: 99%

“…Previous work on camera calibration of highways mostly takes advantage of parallel traffic lanes [21][22][23]. However, in general, parallel traffic lanes are not available at roundabouts and instead circular lanes exist (for instance the circles in Fig.…”

Section: Camera Calibrationmentioning

confidence: 99%

Development of a tracking-based system for automated traffic data collection for roundabouts

Dinh

Tang

2017

J. Mod. Transport.

View full text Add to dashboard Cite

Traffic data collection is essential for performance assessment, safety improvement and road planning. While automated traffic data collection for highways is relatively mature, that for roundabouts is more challenging due to more complex traffic scenes, data specifications and vehicle behavior. In this paper, the authors propose an automated traffic data collection system dedicated to roundabout scenes. The proposed system has mainly four steps of processing. First, camera calibration is performed for roundabout traffic scenes with a novel circle-based calibration algorithm. Second, the system uses enhanced Mixture of Gaussian algorithm with shaking removal for video segmentation, which can tolerate repeated camera displacements and background movements. Then, Kalman filtering, Kernel-based tracking and overlap-based optimization are employed to track vehicles while they are occluded and to derive the complete vehicle trajectories. The resulting vehicle trajectory of each individual vehicle gives the position, size, shape and speed of the vehicle at each time moment. Finally, a data mining algorithm is used to automatically extract the interested traffic data from the vehicle trajectories. The overall traffic data collection system has been implemented in software and runs on regular PC. The total processing time for a 3-hour video is currently 6 h. The automated traffic data collection system can significantly reduce cost and improve efficiency compared to manual data collection. The extracted traffic data have been compared to accurate manual measurements for 29 videos recorded on 29 different days, and an accuracy of more than 90% has been achieved.

show abstract

“…The results of the method introduced in [12] were reported on videos captured during day using highly elevated cameras. Moreover, [9], [11], [22] methods have reported high error rates and cannot be used in law enforcement applications.…”

Section: Introductionmentioning

confidence: 99%

“…The second type of cameras used in vehicle speed measurement systems are calibrated ones [9], [11], [12], [22]. Methods used in these systems, by using calibration parameters, allow the camera to be set on the roadside with a wide variety of Pan-Tilt angles.…”

Section: Introductionmentioning

confidence: 99%

Precise Vehicle Speed Measurement Based on a Hierarchical Homographic Transform Estimation for Law Enforcement Applications

Eslami

Raie

Faez

2016

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYToday, computer vision is used in different applications for intelligent transportation systems like: traffic surveillance, driver assistance, law enforcement etc. Amongst these applications, we are concentrating on speed measurement for law enforcement. In law enforcement applications, the presence of the license plate in the scene is a presupposition and metric parameters like vehicle's speed are to be estimated with a high degree of precision. The novelty of this paper is to propose a new precise, practical and fast procedure, with hierarchical architecture, to estimate the homraphic transform of the license plate and using this transform to estimate the vehicle's speed. The proposed method uses the RANSAC algorithm to improve the robustness of the estimation. Hence, it is possible to replace the peripheral equipment with vision based systems, or in conjunction with these peripherals, it is possible to improve the accuracy and reliability of the system. Results of experiments on different datasets, with different specifications, show that the proposed method can be used in law enforcement applications to measure the vehicle's speed. key words: feature extraction, RANSAC estimator, license plate, speed measurement, law enforcement

show abstract

Automatic Camera Calibration Using Pattern Detection for Vision-Based Speed Sensing

Cited by 25 publications

References 14 publications

A Taxonomy and Analysis of Camera Calibration Methods for Traffic Monitoring Applications

A Taxonomy and Analysis of Camera Calibration Methods for Traffic Monitoring Applications

Development of a tracking-based system for automated traffic data collection for roundabouts

Precise Vehicle Speed Measurement Based on a Hierarchical Homographic Transform Estimation for Law Enforcement Applications

Contact Info

Product

Resources

About