Spatio-temporal auxiliary particle filtering with l1-Norm- Based Appearance Model Learning for Robust Visual Tracking

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Spatio-temporal auxiliary particle filtering with l1-Norm- Based Appearance Model Learning for Robust Visual Tracking

In this paper, we propose an efficient and accurate visual tracker equipped with a new particle filtering algorithm and robust subspace learning-based appearance model. The proposed visual tracker avoids drifting problems caused by abrupt motion changes and severe appearance variations that are well...

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Bibliographic Details
Main Authors:	Kim, Du Yong, Jeon, M.
Format:	Journal Article
Published:	IEEE 2013
Online Access:	http://hdl.handle.net/20.500.11937/56045

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