Region tracking for non-rigid video objects in a non-parametric MAP framework

This paper presents a non-parametric maximum a posteriori MAP framework for tracking non-rigid video objects. We formulate the region tracking problem as a MAP probability problem and define the probabilistic models in terms of the distances between the intensity distribution of the object and that of its spatial- and temporal-neighborhood. Furthermore, in order to better model the complex intensity changes due to non-rigid movement, we propose to use a non-parametric method to approximate the likelihood and prior terms in the MAP problem. The proposed non-parametric estimation algorithm mostly relies on intensity features and requires no time-consuming motion estimation. Finally, we employ a contour evolution method in the MAP optimization step to iteratively track the object contour. The experimental results demonstrate that the proposed method achieves satisfactory results and outperforms the previous parametric method.