Title of article :
Multi-cue-based CamShift guided particle filter tracking
Author/Authors :
Yin، نويسنده , , MingHao and Zhang، نويسنده , , Jin and Sun، نويسنده , , Hongguang and Gu، نويسنده , , Wenxiang، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
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.
Keywords :
particle filter , CamShift , Occlusion strategy , Scale variation , Multiple cues
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications