A Deformable Template Approach to Detecting Straight Edges in Radar Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine-Vision Systems for Intelligent Transportation Systems
IEEE Intelligent Systems
Video segmentation using fast marching and region growing algorithms
EURASIP Journal on Applied Signal Processing - Image analysis for multimedia interactive services - part I
Fast Marching to Moving Object Location
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
A Real-time Precrash Vehicle Detection System
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
RHODES to Intelligent Transportation Systems
IEEE Intelligent Systems
IVS 05: New Developments and Research Trends for Intelligent Vehicles
IEEE Intelligent Systems
Image analysis and rule-based reasoning for a traffic monitoring system
IEEE Transactions on Intelligent Transportation Systems
Simultaneous detection of lane and pavement boundaries using model-based multisensor fusion
IEEE Transactions on Intelligent Transportation Systems
Detection and classification of vehicles
IEEE Transactions on Intelligent Transportation Systems
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
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During the last two decades, significant research efforts had been made in developing vision-based automatic traffic monitoring systems in order to improve driving efficiency and reduce traffic accidents. This paper presents a practical vehicle waiting time estimation method using adaptive video-based vehicle tracking method. Specifically, it is designed to deal with lower image quality, inappropriate camera positions, vague lane/road markings and complex driving scenarios. The spatio-temporal analysis is integrated with shape hints to improve performance. Experiment results show the effectiveness of the proposed approach.