Multi-part histogram based visual tracking with maximum of posteriori

This paper presents a new multi-part histogram (MPH) based algorithm for non-rigid object tracking with Particle filtering state estimation approach. The reference and target object are represented by some sub-region with integral image technique. Each region has its own histogram and we calculate the weight of each particle based on its region position of target object. The most weighted particle settles on the centre position of the bounded target and gradually decreases the weight of particle vertically and horizontally from the centre position. For smooth tracking Maximum a Posteriori (MAP) is introduced for better observation likelihood calculations. Experiments of proposed tracker show that our system is robust against false target tracking, severe occlusion, and rotation, scaling without extra computational cost.