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Surface reconstruction from point clouds by transforming the medial scaffold

Leymarie, Frederic Fol; Chang, Ming-Ching and Kimia, Benjamin B.. 2009. Surface reconstruction from point clouds by transforming the medial scaffold. Computer Vision and Image Understanding, 113(11), pp. 1130-1146. ISSN 1077-3142 [Article]

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Abstract or Description

We propose an algorithm for surface reconstruction from unorganized points based on a view of the sampling process as a deformation from the original surface. In the course of this deformation the Medial Scaffold(MS) — a graph representation of the 3D Medial Axis(MA) — of the original surface undergoes abrupt topological changes (transitions) such that the MS of the unorganized point set is significantly different from that of the original surface. The algorithm seeks a sequence of transformations of the MS to invert this process. Specifically, some MS curves (junctions of 3 MA sheets) correspond to triplets of points on the surface and represent candidates for generating a (Delaunay) triangle to mesh that portion of the surface. We devise a greedy algorithm that iteratively transforms the MS by “removing” suitable candidate MS curves (gap transform) from a rank-ordered list sorted by a combination of properties of the MS curve and its neighborhood context. This approach is general and applicable to surfaces which are: non-closed (with boundaries), non-orientable, non-uniformly sampled, non-manifold (with self-intersections), non-smooth (with sharp features: seams, ridges). In addition, the method is comparable in speed and complexity to current popular Voronoi/Delaunay-based algorithms, and is applicable to very large datasets.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1016/j.cviu.2009.04.001

Departments, Centres and Research Units:

Computing
Research Office > REF2014

Dates:

DateEvent
2009Published

Item ID:

9256

Date Deposited:

24 Oct 2013 14:16

Last Modified:

20 Jun 2017 10:09

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

http://research.gold.ac.uk/id/eprint/9256

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