Camshift-Based Real-Time Multiple Vehicle Tracking for Visual Traffic Surveillance

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.