@inproceedings{ad6e3f0ae15a49e1a775a96bbaadd3b1,
title = "An improved object tracking method based on particle filter",
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 = "combined model, ensemble kalman filter, particle filter, proposal distribution",
author = "Nan Liang and Lei Guo and Ying Wang",
year = "2012",
doi = "10.1109/CECNet.2012.6202080",
language = "英语",
isbn = "9781457714153",
series = "2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Proceedings",
pages = "3107--3110",
booktitle = "2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 - Proceedings",
note = "2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012 ; Conference date: 21-04-2012 Through 23-04-2012",
}