A hybrid occlusion free object tracking method using particle filter and modified galaxy based search meta-heuristic algorithm

Abstract

An important problem in tracking methods is how to manage the changes in object appearance, such as illumination changes, partial/full occlusion, scale, and pose variation during the tracking process. In this paper, we propose an occlusion free object tracking method together with a simple adaptive appearance model. The proposed appearance model which is updated at the end of each time step includes three components: the first component consists of a fixed template of target object, the second component shows rapid changes in object appearance, and the third one maintains slow changes generated along the object path. The proposed tracking method not only can detect occlusion and handle it, but also it is robust against changes in the object appearance model. It is based on particle filter which is a robust technique in tracking and handles non-linear and non-Gaussian problems. We have also employed a meta-heuristic approach that is called Modified Galaxy based Search Algorithm (MGbSA), to reinforce finding the optimum state in the particle filter state space. The proposed method was applied to some benchmark videos and its results were satisfactory and better than results of related works.