A moving body recognition method based on self-adaption weighting meanshift algorithm

DOI

10.2991/emeit.2012.428How to use a DOI?

Keywords

Meanshift, Kalman filter, body tracking, perturbation insensitivity, self-adaption

Abstract

Classic meanshift algorithm is widely used in pattern recognition, but its accuracy decrease large when there is perturbation in background. In this paper, to solve this problem, we put forward an improved meanshift algorithm which is based on self-adaption weighting meanshift algorithm. At first, we catch moving object area. Secondly, we use capture to set new weighting coefficient. Then we track target model by the new coefficient to decrease effect of background. The experiment result of moving body in supervisory control video shows perturbation insensitivity, robustness and stability.

Copyright

© 2012, 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  - Shoujia WANG
AU  - Wenhui LI
AU  - Tianshu YOU
AU  - Mingyu SUN
AU  - Yongjian Liu
PY  - 2012/09
DA  - 2012/09
TI  - A moving body recognition method based on self-adaption weighting meanshift algorithm
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 1936
EP  - 1939
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.428
DO  - 10.2991/emeit.2012.428
ID  - WANG2012/09
ER  -