Multi-cue-based CamShift guided particle filter tracking

Authors:
Minghao Yin;Jin Zhang;Hongguang Sun;Wenxiang Gu
Affiliations:
College of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, PR China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of ...;College of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, PR China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of ...;College of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, PR China;College of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, PR China
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

The traditional particle filter algorithm cannot solve the validity of particles ideally. In this situation, a large amount of particles are required to guarantee tracking performance and tracking windows cannot change scale with targets adaptively. In addition, the particle filter algorithm which uses a single cue cannot achieve stable tracking regarding sudden illumination variation and similarly coloured background clutters. In this paper, an algorithm that combines CamShift with particle filter using multiple cues is proposed. The effectiveness of particles is improved and the tracking window can change scale with the target adaptively because of the use of CamShift. At the same time, an adaptive integration method is used to combine colour information with motion information, so the problems can be solved which are encountered in tracking an object with illumination variation and the background color clutter. Moreover, an occlusion handler is proposed to handle the full occlusion for a long time.