Title :
An improved object tracking method based on particle filter
Author :
Liang, Nan ; Guo, Lei ; Wang, Ying
Author_Institution :
Coll. of Autom., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
The conventional particle filter uses system transition as the proposal distribution. In order to improve the performance of particle filter for target tracking, Ensemble kalman filter is proposed to construct proposal distribution for sampling particle. In the tracking process, color model and shape model are combined and updated adaptively. Experimental results show the proposed algorithm improves the stability of the object tracking and enhances the estimation accuracy compared to conventional filters.
Keywords :
Kalman filters; object tracking; particle filtering (numerical methods); color model; conventional particle filter; ensemble Kalman filter; object tracking method; sampling particle; shape model; system transition; target tracking; tracking process; Adaptation models; Color; Filtering algorithms; Kalman filters; Particle filters; Proposals; Target tracking; combined model; ensemble kalman filter; particle filter; proposal distribution;
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
Conference_Location :
Yichang
Print_ISBN :
978-1-4577-1414-6
DOI :
10.1109/CECNet.2012.6202080
