Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.423
This paper presents methods for vision-based detection and tracking of vehicles in monocular image sequences of traffic scenes recorded by a stationary camera. The goal of this research is to develop suitable methods for automatic visual traffic surveillance to perform detection, tracking and traffic parameter estimation of multiple vehicles in real time as well as tackle environment illumination changes and vehicle occlusion. Each of detected vehicles is assigned a camshift tracker which can quickly and exactly track object with different size and shape. Experimental results from traffic scenes demonstrate the effectiveness and robustness of the methods.
Zhe Liu, Yangzhou Chen, Zhenlong Li, "Camshift-Based Real-Time Multiple Vehicle Tracking for Visual Traffic Surveillance", CSIE, 2009, Computer Science and Information Engineering, World Congress on, Computer Science and Information Engineering, World Congress on 2009, pp. 477-482, doi:10.1109/CSIE.2009.423