Adaptive Multiple Component Metric Learning for Robust Visual Tracking
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Bozorgtabar, Behzad
Goecke, Roland
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Springer
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In this paper, we present a new robust visual tracking approach that incorporates an adaptive metric learning in a multiple components framework. Using a similar overall approach to other state-of-the-art tracking methods, which pose object tracking as a
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Lecture Notes in Computer Science (LNCS)
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Restricted until
2037-12-31