Implicit fitting of point cloud data using radial hermite basis functions

Authors:
G. M. Nielson;H. Hagen;K. Lee
Affiliations:
Arizona State University, Computer Science and Engineering Mathematics, 85287-5406, Tempe, Arizona, USA;Arizona State University, Computer Science and Engineering Mathematics, 85287-5406, Tempe, Arizona, USA;Arizona State University, Computer Science and Engineering Mathematics, 85287-5406, Tempe, Arizona, USA
Venue:
Computing - Special issue on Geometric Modeling (Dagstuhl 2005)
Year:
2007

Citing 0
Cited 1

Normalized implicit eigenvector least squares operators for noisy scattered data: radial basis functions

Computing - Geometric Modelling, Dagstuhl 2008

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Abstract

We describe a new technique for fitting noisy scattered point cloud data. The fitting surface is determined as zero level isosurface of a trivariate model which is an implicit least squares fit of the data based upon Radial Hermite Operators (RHO). We illustrate the value of these new techniques with several diverse applications.