A flexible solution for detection and tracking of multiple objects

This paper proposes a two-level approach to the multiple objects tracking problem. One particle filter-based tracker will search the whole state space for new hypotheses, and when a hypothesis becomes strong enough, an individual object tracker will be activated, which will track it until the object is lost. The initialization tracker and the individual object trackers use two types of cues, a stereovision-based obstacle grid and a symmetry measure computed by grayscale image processing. The proposed solution is a simple and robust one, adaptable to different types of object models and extendable to different types of sensors.