Effective and robust object tracking in constrained environments

We present a new scheme for efficient and robust video object tracking in constrained environments. It finds its application in security surveillance, traffic monitoring, etc. In these applications movements of objects are restricted by the environments; therefore, environment constraints can be exploited as heuristic information for improving the performance of tracking. In this paper we use the distance field to represent environment constraints and integrate it into the framework of particle filtering. Experiments on some video surveillance sequences demonstrate the effectiveness of our approach.