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Sparse surface reconstruction with adaptive partition of unity and radial basis functions

Published: 01 January 2006 Publication History

Abstract

A new implicit surface fitting method for surface reconstruction from scattered point data is proposed. The method combines an adaptive partition of unity approximation with least-squares RBF fitting and is capable of generating a high quality surface reconstruction. Given a set of points scattered over a smooth surface, first a sparse set of overlapped local approximations is constructed. The partition of unity generated from these local approximants already gives a faithful surface reconstruction. The final reconstruction is obtained by adding compactly supported RBFs. The main feature of the developed approach consists of using various regularization schemes which lead to economical, yet accurate surface reconstruction.

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Published In

cover image Graphical Models
Graphical Models  Volume 68, Issue 1
Special issue on SMI 2004
January 2006
64 pages

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Academic Press Professional, Inc.

United States

Publication History

Published: 01 January 2006

Author Tags

  1. adaptive partition of unity approximation
  2. least-squares RBF fitting
  3. surface reconstruction from scattered data

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