2nd International Conference On Systems Engineering and Modeling (ICSEM-13)

Object Tracking Based on Corrected Background-Weighted Histogram Mean Shift and Kalman Filter

Authors
Yu Yang, Yongxing Jia, Chuanzhen Rong, Ying Zhu, Yuan Wang, Zhenjun Yue, Zhenxing Gao
Corresponding Author
Yu Yang
Available Online April 2013.
DOI
https://doi.org/10.2991/icsem.2013.140How to use a DOI?
Keywords
object tracking, mean shift, background information, Kalman filter
Abstract
The classical mean shift (MS) algorithm is the best color-based method for object tracking. However, in the real environment it presents some limitations, especially under the presence of noise, objects with partial and full occlusions in complex environments. In order to deal with these problems, this paper proposes a reliable object tracking algorithm using corrected background-weighted histogram (CBWH) and the Kalman filter (KF) based on the MS method. The experimental results show that the proposed method is superior to the traditional MS tracking in the following aspects: 1) it provides consistent object tracking throughout the video; 2) it is not influenced by the objects with partial and full occlusions; 3) it is less prone to the background clutter.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2013
ISBN
978-94-91216-42-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/icsem.2013.140How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yu Yang
AU  - Yongxing Jia
AU  - Chuanzhen Rong
AU  - Ying Zhu
AU  - Yuan Wang
AU  - Zhenjun Yue
AU  - Zhenxing Gao
PY  - 2013/04
DA  - 2013/04
TI  - Object Tracking Based on Corrected Background-Weighted Histogram Mean Shift and Kalman Filter
BT  - 2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.140
DO  - https://doi.org/10.2991/icsem.2013.140
ID  - Yang2013/04
ER  -