Robust Object Tracking using Log-Gabor Filters and Color Histogram

Oumaima Sliti, Chekib Gmati, Fouzi Benzarti, Hamid Amiri

Abstract

The performance of the tracking algorithm relies heavily on the target structural information accuracy. In this paper, we propose a robust object tracking method based on the log-Gabor texture and color histogram. Our hypothesis is that by adding log-Gabor filter to color features, and then embedded it in the mean shift framework, tracking performances will notably enhance. Compared with several methods of state-of-the-art mean shift trackers, our approach extracts the target information efficiently. Experimental results on various challenging videos show that the proposed method improves the tracking with fewer mean shift iterations.

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Paper Citation


in Harvard Style

Sliti O., Gmati C., Benzarti F. and Amiri H. (2014). Robust Object Tracking using Log-Gabor Filters and Color Histogram . In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 687-694. DOI: 10.5220/0004829306870694


in Bibtex Style

@conference{icpram14,
author={Oumaima Sliti and Chekib Gmati and Fouzi Benzarti and Hamid Amiri},
title={Robust Object Tracking using Log-Gabor Filters and Color Histogram},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={687-694},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004829306870694},
isbn={978-989-758-018-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Robust Object Tracking using Log-Gabor Filters and Color Histogram
SN - 978-989-758-018-5
AU - Sliti O.
AU - Gmati C.
AU - Benzarti F.
AU - Amiri H.
PY - 2014
SP - 687
EP - 694
DO - 10.5220/0004829306870694