Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/70324
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Type: Conference paper
Title: Robust visual tracking via transfer learning
Author: Luo, Wenhan
Li, Xi
Li, Wei
Hu, Weiming
Citation: Proceedings of the 2011 18th IEEE International Conference on Image Processing, 2011: pp.485-488
Publisher: IEEE
Issue Date: 2011
ISBN: 9781457713033
Conference Name: IEEE International Conference on Image Processing (18th : 2011 : Brussels, Belgium)
ICIP 2011
School/Discipline: School of Computer Science
Statement of
Responsibility: 
Wenhan Luo, Xi Li, Wei Li, Weiming Hu
Abstract: In this paper, we propose a boosting based tracking framework using transfer learning. To deal with complex appearance variations, the proposed tracking framework tries to utilize discriminative information from previous frames to conduct the tracking task in the current frame, and thus transfers some prior knowledge from the previous source data domain to the current target data domain, resulting in a high discriminative tracker for distinguishing the object from the background. The proposed tracking system has been tested on several challenging sequences. Experimental results demonstrate the effectiveness of the proposed tracking framework.
Keywords: tracking; transfer learning; boosting
Rights: Copyright © 2011 by IEEE.
RMID: 0020116906
DOI: 10.1109/ICIP.2011.6116557
Appears in Collections:Computer Science publications

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