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Math. Comput. Appl. 2017, 22(1), 3; doi:10.3390/mca22010003

Robust Object Tracking in Infrared Video via Adaptive Weighted Patches

Department of Physical and Electronic Information, Huaibei Normal University, No. 100 Dongshan Street, Huaibei 235000, China
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Author to whom correspondence should be addressed.
Academic Editor: Fazal M. Mahomed
Received: 12 October 2016 / Revised: 7 December 2016 / Accepted: 23 December 2016 / Published: 30 December 2016
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Abstract

With the quick development of computer and electronic techniques, infrared sensor-based object tracking has become a hot research topic in recent years. However, infrared object tracking is still a challenging task due to low resolution, lack of representing information, and occlusion. In this work, we present an adaptive weighted patch-based infrared object tracking scheme. First, the candidate local region is divided into non-overlapping sub regions, and a set of belief weights is set on these patches. After this, a particle filtering-based infrared object tracking system is realized. In the last, the belief weight of each patch is evaluated based on the linear discriminative analysis (LDA) and particle sampling scheme. Experimental results on challenging infrared sequences show that the proposed algorithm can effectively locate the tracking object. View Full-Text
Keywords: infrared object tracking; linear discriminative analysis; particle filter; patch-based tracker infrared object tracking; linear discriminative analysis; particle filter; patch-based tracker
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, J.; Zhang, J. Robust Object Tracking in Infrared Video via Adaptive Weighted Patches. Math. Comput. Appl. 2017, 22, 3.

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