Approximation Of Canonical Sets And Their Applications To 2d View Simplification

CVPR'04: Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition(2004)

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摘要
Given a set of patterns and a similarity measure between them, we will present an optimization framework to approximate a small subset, known as a canonical set, whose members closely resemble the members of the original set. We will present a combinatorial formulation of the canonical set problem in terms of quadratic optimization integer programming, present a relaxation through semidefinite programming, and propose a bounded performance rounding procedure for its approximation solution in polynomial time. Through a set of experiments we will investigate the application of canonical sets for computing a summary of views from a dense set of 2D views computed for a 3D object.
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关键词
integer programming,pattern clustering,quadratic programming,set theory,2D view simplification,canonical sets approximation,pattern clustering,quadratic optimization integer programming,
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