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Journal of Electronic Imaging

Object tracking based on bit-planes
Author(s): Na Li; Xiangmo Shao; Ying Liu; Daxiang Li; Shiqian Wu; Feng Zhao
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Paper Abstract

Visual object tracking is one of the most important components in computer vision. The main challenge for robust tracking is to handle illumination change, appearance modification, occlusion, motion blur, and pose variation. But in surveillance videos, factors such as low resolution, high levels of noise, and uneven illumination further increase the difficulty of tracking. To tackle this problem, an object tracking algorithm based on bit-planes is proposed. First, intensity and local binary pattern features represented by bit-planes are used to build two appearance models, respectively. Second, in the neighborhood of the estimated object location, a region that is most similar to the models is detected as the tracked object in the current frame. In the last step, the appearance models are updated with new tracking results in order to deal with environmental and object changes. Experimental results on several challenging video sequences demonstrate the superior performance of our tracker compared with six state-of-the-art tracking algorithms. Additionally, our tracker is more robust to low resolution, uneven illumination, and noisy video sequences.

Paper Details

Date Published: 17 February 2016
PDF: 15 pages
J. Electron. Imaging. 25(1) 013032 doi: 10.1117/1.JEI.25.1.013032
Published in: Journal of Electronic Imaging Volume 25, Issue 1
Show Author Affiliations
Na Li, Chang'an Univ. (China)
Xi’an Univ. of Posts and Telecommunications (China)
Key Lab. of Electronic Information Application Technology for Scene Investigation (China)
Xiangmo Shao, Chang'an Univ. (China)
Ying Liu, Xi’an Univ. of Posts and Telecommunications (China)
Key Lab. of Electronic Information Application Technology for Scene Investigation (China)
Daxiang Li, Xi'an Univ. of Posts & Telecommunications (China)
Key Lab. of Electronic Information Application Technology for Scene Investigation (China)
Shiqian Wu, Wuhan Univ. of Science and Technology (China)
Feng Zhao, Xi'an Univ. of Posts & Telecommunications (China)
Key Lab. of Electronic Information Application Technology for Scene Investigation (China)


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