DocumentCode
2129261
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
fYear
2012
fDate
21-23 April 2012
Firstpage
3107
Lastpage
3110
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
Conference_Location
Yichang
Print_ISBN
978-1-4577-1414-6
Type
conf
DOI
10.1109/CECNet.2012.6202080
Filename
6202080
Link To Document