Target Detection and Tracking Algorithm based on the Improved Multi-feature Camshift

DOI

10.2991/meic-14.2014.347How to use a DOI?

Keywords

Target Tracking; GMM; Camshift Algorithm; multi-feature; EKF

Abstract

In this paper, a vision-based target detection and tracking approach using improved multi-feature camshift is presented. Because the traditional camshift based on single feature is not robust when the background color, illuminate and target deformation change, it may lead to lose target or failure of tracking. In order to solve this problem, we presented target detection and tracking algorithm based on improved multi-feature camshift. The foreground image was obtained by Gaussian Mixture Model (GMM), which was used to modify the kernel function of target model. Due to the advantage of colour and texture feature in describing the target appearance, these features were used as recognition features. Additionally, EKF was integrated in tracking system to improve the accuracy of target tracking and predict the object position when the target was occluded. This paper details the architecture of the presented method and gives some experimental results to verify the effectiveness of the proposed method.

Copyright

© 2014, 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/).

Download article (PDF)

TY  - CONF
AU  - Naihui Fang
AU  - Wei Fu
PY  - 2014/11
DA  - 2014/11
TI  - Target Detection and Tracking Algorithm based on the Improved Multi-feature Camshift
BT  - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 1539
EP  - 1542
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-14.2014.347
DO  - 10.2991/meic-14.2014.347
ID  - Fang2014/11
ER  -