Video-based freeway-monitoring system using recursive vehicle tracking

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Abstract
An image processing and object tracking approach is proposed for the design of a video-based freeway traffic monitoring system. Proper estimation of the traffic speed in different lanes of a freeway allows for timely detection of possible congestions. The proposed method consists of a road modeling stage and a vehicle tracking stage. In the first stage, a three-dimensional model of the background road image is generated using several initial frames. In the tracking stage, each car in the scene is isolated and tracked over many frames, and by mapping its coordinates to the road's 3D model, an estimate of its velocity on the road is produced. The algorithm runs in real-time on a workstation. Experimental results on frame sequences taken from Santa Ana area freeways will be presented.

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