Moving vehicle target tracking based on improved Mean shift algorithm

DOI

10.2991/icmmcce-15.2015.282How to use a DOI?

Keywords

Bhattacharyya distance; Mean shift; Particle filter; Target tracking

Abstract

This article proposes a tracking algorithm based on mean shift and particle filter according to the characteristics of moving vehicles. Firstly, the algorithms establish auto target motion model that the core is RGB color histogram. Secondly, using the Bhattacharyya distance measures similarity of particle region and the target model, and updating the weights of particles according to the similarity. Lastly, the measure improves the estimated position of the particle by using mean shift algorithm, which makes the candidate regions of these particles can be more close to the true target position. Experimental results show that the algorithm has good real-time performance and robustness, and can achieve stable tracking of target vehicle.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fei Lei
AU  - Xiaoqiong Meng
PY  - 2015/12
DA  - 2015/12
TI  - Moving vehicle target tracking based on improved Mean shift algorithm
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.282
DO  - 10.2991/icmmcce-15.2015.282
ID  - Lei2015/12
ER  -