Vehicle tracking based on customized template matching

In this paper we present a template matching based vehicle tracking algorithm designed for traffic analysis purposes. The proposed approach could be integrated in a system able to understand lane changes, gate passages and other behaviours useful for traffic analysis. After reviewing some state-of-the-art object tracking techniques, the proposed approach is presented as a customization of the template matching algorithm by introducing different modules designed to solve specific issues of the application context. The experiments are performed on a dataset compound by real-world cases of vehicle traffic acquired in different scene contexts (e.g., highway, urban, etc.) and weather conditions (e.g., raining, snowing, etc.). The performances of the proposed approach are compared with respect to a baseline technique based on background-foreground separation.