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     Research Journal of Applied Sciences, Engineering and Technology


Robust Visual Tracking via Fuzzy Kernel Representation

Zhiqiang Wen, Yongxin Long and Zhaoyi Peng
School of Computer and Communication, Hunan University of Technology, Zhuzhou, Hunan, 412008, China
Research Journal of Applied Sciences, Engineering and Technology  2013  11:3212-3218
http://dx.doi.org/10.19026/rjaset.5.4559  |  © The Author(s) 2013
Received: October 17, 2012  |  Accepted: December 10, 2012  |  Published: April 05, 2013

Abstract

A robust visual kernel tracking approach is presented for solving the problem of existing background pixels in object model. At first, after definition of fuzzy set on image is given, a fuzzy factor is embedded into object model to form the fuzzy kernel representation. Secondly, a fuzzy membership functions are generated by center-surround approach and log likelihood ratio of feature distributions. Thirdly, details about fuzzy kernel tracking algorithm is provided. After that, methods of parameter selection and performance evaluation for tracking algorithm are proposed. At last, a mass of experimental results are done to show our method can reduce the influence of the incomplete representation of object model via integrating both color features and background features.

Keywords:

Fuzzy factor, fuzzy kernel histogram, fuzzy membership function, visual tracking,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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