Robust Object Tracking by Simultaneous Generation of an Object Model

Although robust object tracking has a wide variety of applications ranging from video surveillance to recognition from motion, it is not completely solved. Difficulties in tracking objects arise due to abrupt object motion, changing appearance of the object or partial and full object occlusions. To resolve these problems, assumptions are usually made concerning the motion or appearance of an object. However in most applications no models of object motion or appearance are previously available. This paper presents an approach which improves the performance of a tracking algorithm due to simultaneous online model generation of a tracked object. The achieved results testify the stability and the robustness of this approach.