Robust Appearance Modeling for Pedestrian and Vehicle Tracking

Abstract. This paper describes a system for tracking people and vehicles for stationary-camera visual surveillance. The appearance of objects being tracked is modeled using mixtures of mixtures of Gaussians. Particles filters are used to track the states of object. Results show the robustness of the system to various lighting and object conditions.