IMPROVED KERNEL BASED TRACKING FOR FAST MOVING OBJECT

Dang Xiaoyan, Yao Anbang, Wang Wei, Zhang Ya, Wang Zhuo, Wang Zhihua

2010

Abstract

A novel approach of discriminative object representation and multiple-kernel tracking is proposed. We first employ a discriminative object representation, which introduces the foreground and background modelling ingredient to select the most discriminative features from a set of candidates via classification procedure. In the context of using kernel based tracking algorithm, a multiple-kernel strategy is employed to handle the difficulties resulted from fast motion through refining the ill-initialization position according to pre-refinement method. Extensive experiments demonstrate that the proposed tracker works better than Camshift and traditional kernel tracker.

References

  1. Dorin Comaniciu, Visvanathan Ramesh, Peter Meer, 2003. Kernel-Based Object Tracking, IEEE transaction on Pattern Analysis and Machine Intelligence, Vol 25, Issue 5, pp. 564-577.
  2. Klaus Robert Muller, Sebastian Mka, Gunnar Ratsch, 2001. An Introduction to Kernel Based Learning Algorithms, IEEE Transactions on Neural Networks, Vol 12, No 2, pp. 181-201.
  3. Faith Porikli, Oncel Tuzel. 2005. Multi-Kernel Object Tracking, ICME, pp. 1234-1237.
  4. Hanger G D, Dewan M. 2004. Multiple Kernel Tracking with SSD, Proc. CVPR. Vol.1, pp. 790-797.
  5. Ahmed Elgammal, Ramani Duraiswami, David Harwood. 2002. Background and Foreground Modeling using nonparametric kernel density estimation for visual surveillance. Proceedings of the IEEE , Vol 90, Issue 7, pp. 1151-1163.
  6. Arulampalam, M. S. Maskell, S. Gordon. 2002. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Transaction on Signal Processing. Vol 50, No 2, pp. 174-188.
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Paper Citation


in Harvard Style

Xiaoyan D., Anbang Y., Wei W., Ya Z., Zhuo W. and Zhihua W. (2010). IMPROVED KERNEL BASED TRACKING FOR FAST MOVING OBJECT . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-028-3, pages 261-266. DOI: 10.5220/0002766902610266


in Bibtex Style

@conference{visapp10,
author={Dang Xiaoyan and Yao Anbang and Wang Wei and Zhang Ya and Wang Zhuo and Wang Zhihua},
title={IMPROVED KERNEL BASED TRACKING FOR FAST MOVING OBJECT},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={261-266},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002766902610266},
isbn={978-989-674-028-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)
TI - IMPROVED KERNEL BASED TRACKING FOR FAST MOVING OBJECT
SN - 978-989-674-028-3
AU - Xiaoyan D.
AU - Anbang Y.
AU - Wei W.
AU - Ya Z.
AU - Zhuo W.
AU - Zhihua W.
PY - 2010
SP - 261
EP - 266
DO - 10.5220/0002766902610266