Empirical Analysis of Computational and Accuracy Tradeoffs Using Compactly Supported Radial Basis Functions for Surface Reconstruction

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Permanent URL	http://hdl.lib.byu.edu/1877/2473
Title	Empirical Analysis of Computational and Accuracy Tradeoffs Using Compactly Supported Radial Basis Functions for Surface Reconstruction
BYU Creator	Liu, Weiming Morse, Bryan S. Otis, Lauralea
Keywords	implicit surfaces; radial basis functions; RBFs; interpolation
Description/Abstract	Implicit surfaces can be constructed from scattered surface points using radial basis functions (RBFs) to interpolate the surface’s embedding function. Many researchers have used thin-plate spline RBFs for this because of their desirable smoothness properties. Others have used compactly supported RBFs, leading to a sparse matrix solution with lower computational complexity and better conditioning. However, the limited radius of support introduces a free parameter that leads to varying solutions as well as varying computational requirements: a larger radius of support leads to smoother and more accurate solutions but requires more computation. This paper presents an empirical analysis of this radius of support. The results using compactly supported RBFs are compared for varying model sizes and radii of support, exploring the relationship between data density and the accuracy of the interpolated surface.
Source	B. Morse, W. Liu, and L. Otis, "Empirical analysis of computational and accuracy tradeoffs using compactly supported radial basis functions for surface reconstruction" in SMI '04: Proceedings of the International Conference on Shape Modeling & Applications, pp. 358-361, June 2004.;
Publisher	IEEE
Date Original	2004-06
Date Digital	2010-09-21
Language	English eng en
Publication Type	Articles Conference Proceedings
Type	Text
Format	application/pdf
Owning Institution	Brigham Young University
BYU College	College of Physical and Mathematical Sciences
BYU Department	Computer Science
Copyright Status	(c) 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.;
Copyright Use Information	http://www.lib.byu.edu/generic_copyright.html

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Empirical Analysis of Computational and Accuracy Tradeoffs Using Compactly Supported Radial Basis Functions for Surface Reconstruction

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