Using Optical Flow as Evidence for Probabilistic Tracking

In this paper, we presen t an observation model based on the Lucas and Kanade algorithm for computing optical ow, to trac k objects using particle lter algorithms. Although optical ow information enables us to know the displacement of objects present in a scene, it cannot be used directly to displace an object model since ow calculation techniques lack the necessary precision. In view of the fact that probabilistic tracking algorithms enable imprecise or incomplete information to be handled naturally, this model has been used as a natural means of incorporating ow information into the trac king.