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ECCV
1996
Springer

Image Recognition with Occlusions

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Image Recognition with Occlusions
We study the problem of how to detect \interesting objects" appeared in a given image, I. Our approach is to treat it as a function approximation problem based on an over-redundant basis. Since the basis (a library of image templates) is over-redundant, there are in nitely many ways to decompose I. To select the \best" decomposition we rst propose a global optimization procedure that considers a concave cost function derived from a \weighted Lp
Tyng-Luh Liu, Michael J. Donahue, Davi Geiger, Rob
Added 16 Oct 2009
Updated 16 Oct 2009
Type Conference
Year 1996
Where ECCV
Authors Tyng-Luh Liu, Michael J. Donahue, Davi Geiger, Robert A. Hummel
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