To tackle occlusions, a hierarchical part matching method based on a layered appearance model for object tracking is
presented in this paper, which integrates global and partial region matching together to search the target object in a
coarse to fine manner. In order to reduce the ambiguity of object localization, only the discriminative parts are selected
for similarity computing with respect to their cornerness measure. The similarity between parts is computed in a layerwised
manner, based on which the state of occlusions can be inferred correctly. When occluded partially, the object can
be localized accurately, when occluded completely, the historical information of motion is applied to predict its position
by a Kalman filter. The proposed tracking method is tested on practical video sequences, and the experimental results
show it can consistently provides accurate positions of the object for stable tracking, even under severe occlusions.