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|Title:||Robust visual tracking via transfer learning|
|Citation:||Proceedings of the 2011 18th IEEE International Conference on Image Processing, 2011: pp.485-488|
|Conference Name:||IEEE International Conference on Image Processing (18th : 2011 : Brussels, Belgium)|
|School/Discipline:||School of Computer Science|
|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.|
|Appears in Collections:||Computer Science publications|
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