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dc.contributor.authorLuo, Wenhanen
dc.contributor.authorLi, Xien
dc.contributor.authorLi, Weien
dc.contributor.authorHu, Weimingen
dc.identifier.citationProceedings of the 2011 18th IEEE International Conference on Image Processing, 2011: pp.485-488en
dc.description.abstractIn 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.en
dc.description.statementofresponsibilityWenhan Luo, Xi Li, Wei Li, Weiming Huen
dc.rightsCopyright © 2011 by IEEE.en
dc.subjecttracking; transfer learning; boostingen
dc.titleRobust visual tracking via transfer learningen
dc.typeConference paperen
dc.contributor.schoolSchool of Computer Scienceen
dc.contributor.conferenceIEEE International Conference on Image Processing (18th : 2011 : Brussels, Belgium)en
dc.contributor.conferenceICIP 2011en
Appears in Collections:Computer Science publications

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