On stochastic methods for surface reconstruction

In this article, we present and discuss three statistical methods for surface reconstruction. A typical input to a surface reconstruction technique consists of a large set of points that has been sampled from a smooth surface and contains uncertain data in the form of noise and outliers. We first pr...

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Bibliographic Details
Published in:The Visual computer 2007-06, Vol.23 (6), p.381-395
Main Authors: Saleem, Waqar, Schall, Oliver, Patanè, Giuseppe, Belyaev, Alexander, Seidel, Hans-Peter
Format: Article
Language:English
Subjects:
Outliers (statistics)
Reconstruction
Representations
Statistical methods
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Summary:In this article, we present and discuss three statistical methods for surface reconstruction. A typical input to a surface reconstruction technique consists of a large set of points that has been sampled from a smooth surface and contains uncertain data in the form of noise and outliers. We first present a method that filters out uncertain and redundant information yielding a more accurate and economical surface representation. Then we present two methods, each of which converts the input point data to a standard shape representation; the first produces an implicit representation while the second yields a triangle mesh.
ISSN:0178-2789
1432-2315
DOI:10.1007/s00371-006-0094-3