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2011
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Blurred Target Tracking by Blur-driven Tracker

10 years 11 months ago
Blurred Target Tracking by Blur-driven Tracker
Visual tracking plays an important role in many computer vision tasks. A common assumption in previous methods is that the video frames are blur free. In reality, motion blurs are pervasive in the real videos. In this paper we present a novel BLUr-driven Tracker (BLUT) framework for tracking motion-blurred targets. BLUT actively uses the information from blurs without performing deblurring. Specifically, we integrate the tracking problem with the motion-from-blur problem under a unified sparse approximation framework. We further use the motion information inferred by blurs to guide the sampling process in the particle filter based tracking. To evaluate our method, we have collected a large number of video sequences with significant motion blurs and compared BLUT with stateof-the-art trackers. Experimental results show that, while many previous methods are sensitive to motion blurs, BLUT can robustly and reliably track severely blurred targets.
Yi Wu, Haibin Ling, Jingyi Yu, Feng Li, Xue Mei, E
Added 11 Dec 2011
Updated 11 Dec 2011
Type Journal
Year 2011
Where ICCV
Authors Yi Wu, Haibin Ling, Jingyi Yu, Feng Li, Xue Mei, Erkang Cheng
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