Abstract
We define a generalized distance function on an unoriented 3D point set and describe how it may be used to reconstruct a surface approximating these points. This distance function is shown to be a Mahalanobis distance in a higher-dimensional embedding space of the points, and the resulting reconstruction algorithm a natural extension of the classical Radial Basis Function (RBF) approach. Experimental results show the superiority of our reconstruction algorithm to RBF and other methods in a variety of practical scenarios.
Original language | English |
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Pages (from-to) | 2479-2491 |
Number of pages | 13 |
Journal | Computer Graphics Forum |
Volume | 29 |
Issue number | 8 |
DOIs | |
State | Published - Dec 2010 |
Keywords
- Distance measure
- Point clouds
- Surface reconstruction
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design