Abstract
This paper presents algorithms for vision-based monitoring of weaving sections. These algorithms have been developed for the Minnesota Department of Transportation in order to acquire data for several weaving sections in the Twin Cities area. Unlike commercially available systems, the proposed algorithms can track and count vehicles as they change lanes. Furthermore, they provide the velocity and the direction of each vehicle in the weaving section. Experimental results from various weaving sections under various weather conditions are presented. The proposed methods are based on the establishment of correspondences among blobs and vehicles as the vehicles move through the weaving section. The blob tracking problem is formulated as a bipartite graph optimization problem.
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