Abstract
Object tracking is a key objective of research in image engineering and considerable research has been directed toward developing tracking techniques based on particle filtering, which generally utilizes similarities in color, shape, texture, and other attributes of a target in likelihood calculations. However, partial occlusion of the target tends to reduce the accuracy of target recognition and is thus a significant obstacle to effective tracking. We therefore propose a technique for robust object tracking even when the target is partially occluded. It employs hierarchical likelihood calculations in particle filtering.
