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2008
IEEE

Optimal bandwidth selection for MLS surfaces

9 years 4 months ago
Optimal bandwidth selection for MLS surfaces
We address the problem of bandwidth selection in MLS surfaces. While the problem has received relatively little attention in the literature, we show that appropriate selection plays a critical role in the quality of reconstructed surfaces. We formulate the MLS polynomial fitting step as a kernel regression problem for both noiseless and noisy data. Based on this framework, we develop fast algorithms to find optimal bandwidths for a large class of weight functions. We show experimental comparisons of our method, which outperforms heuristically chosen functions and weights previously proposed. We conclude with a discussion of the implications of the Levin’s two-step MLS projection for bandwidth selection.
Hao Wang, Carlos Eduardo Scheidegger, Cláud
Added 01 Jun 2010
Updated 01 Jun 2010
Type Conference
Year 2008
Where SMI
Authors Hao Wang, Carlos Eduardo Scheidegger, Cláudio T. Silva
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