  Video-based vehicle detection and tracking is one of the most important
components for Intelligent Transportation Systems (ITS). When it comes to road
junctions, the problem becomes even more difficult due to the occlusions and
complex interactions among vehicles. In order to get a precise detection and
tracking result, in this work we propose a novel tracking-by-detection
framework. In the detection stage, we present a sequential detection model to
deal with serious occlusions. In the tracking stage, we model group behavior to
treat complex interactions with overlaps and ambiguities. The main
contributions of this paper are twofold: 1) Shape prior is exploited in the
sequential detection model to tackle occlusions in crowded scene. 2) Traffic
force is defined in the traffic scene to model group behavior, and it can
assist to handle complex interactions among vehicles. We evaluate the proposed
approach on real surveillance videos at road junctions and the performance has
demonstrated the effectiveness of our method.
