On the Locality of Extracting a 2-Manifold inR3

Daniel Dumitriu, Stefan Funke, Martin Kutz, Nikola Milosavljevic

Abstract. Algorithms for reconstructing a 2-manifold from a point sample in R3 based on Voronoi-filtering like CRUST or CoCone still require – after identifying a set of candidate triangles – a so-called manifold extraction step which identifies a subset of the candidate triangles to form the final reconstruction surface. Non-locality of the latter step is caused by so-called slivers – configurations of four almost cocircular points having an empty circumsphere with center close to the manifold surface.
We prove that under a certain mild condition – local uniformity – which typically holds in practice but can also be enforced theoretically, one can compute a reconstruction using an algorithm whose decisions about the adjacencies of a point only depend on nearby points.
While the theoretical proof requires an extremely high sampling density, our prototype implementation, described in a companion paper, performs well on typical sample sets. Due to its local mode of computation, it might be particularly suited for parallel computing or external memory scenarios.

Proc. 11th Scandinavian Workshop on Algorithm Theory (SWAT) 2008, Göteborg
(Springer LNCS 5124, pp. 270–281)

Copyright retained by Springer-Verlag; a link to the published article on their website.

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