Thursday, November 9

Surface Reconstruction From Scattered Data

The problem of constructing a surface that interpolates or approximates data sampled at arbitrary locations arises often in scientific and engineering applications. The speakers will address recent solutions to these types of modeling problems and several recent applications for functions of two or more variables. Among the topics to be addressed are least squares approximation of scattered data using radial basis functions, interpolation and approximation using both local and global techniques, and smoothing splines with moving least squares methods to construct a locally defined interpolation method. All of the talks will be practical and the audience will gain insight to the problem by observing how these various techniques perform on real and challenging data sets.

Organizer: Thomas A. Foley
Arizona State University

10:00 Recent Advances in Scattered Data Interpolation
Thomas A. Foley, Arizona State University
10:30 Least Squares Multiquadric Approximation: Review and Practical Results
Richard Franke, Naval Postgraduate School
11:00 Local and Global Methods for Scattered Data Approximation
Morten Daehlen, SINTEF, Norway
11:30 Piecewise Thin-Plate Splines
Kes Salkauskas, University of Calgary, Canada

Transportation | Registration | Hotel Information | Program Overview | Speaker Index