Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

A Novel HRBW-based approach to Mean shift algorithm for Target Tracking

Authors
Xiaowei Wang, Yahui Han, Antong Gao
Corresponding Author
Xiaowei Wang
Available Online March 2017.
DOI
https://doi.org/10.2991/ifmca-16.2017.52How to use a DOI?
Keywords
Target Tracking; Mean Shift; Background Weighted; Corrected Background Weighted; Histogram Ration; Histogram Ration Background Weighted
Abstract
To resolve the problem of localization errors in object tracking, which caused by the background pixels in an object model, a novel target tracking algorithm named Histogram Ration Background Weighted-based mean shift (HRBWBMS)is presented. In the proposed HRBWMS, unlike the standard mean shift, the target model is established based on object/background histogram log-likelihood ratio. A new weight transform method for target model based on object/background histogram log-likelihood ratio was introduced. The experimental results show that the proposed method not only accelerates the convergence, but also enhances anti-interference ability.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
978-94-6252-307-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/ifmca-16.2017.52How 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  - Xiaowei Wang
AU  - Yahui Han
AU  - Antong Gao
PY  - 2017/03
DA  - 2017/03
TI  - A Novel HRBW-based approach to Mean shift algorithm for Target Tracking
BT  - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
PB  - Atlantis Press
SP  - 330
EP  - 336
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifmca-16.2017.52
DO  - https://doi.org/10.2991/ifmca-16.2017.52
ID  - Wang2017/03
ER  -