Non-rigid object tracking using a likelihood spatio-temporal model

In this paper, we present a technique for tracking non-rigid video objects in a sequence. It assumes that the object in the initial image has beeen previously defined by an object partition. Most of object tracking methods usually rely on the motion homogeneity of the object to be tracked. They do not assume that the selected objects present either motion or spatial homogeneity. When they assume these, they employed a spatial or temporal criterion separately to achieve the object tracking. Our proposed object tracking approach relies on the concept of backward partition projection using a likelihood joint spatial-temporal model to deal with occlusion, uncover areas and fast motion problems. Several examples in different scenarios are finally presented in order to demonstrate the performance of the proposed method.