Article ID Journal Published Year Pages File Type
525862 Computer Vision and Image Understanding 2009 17 Pages PDF
Abstract

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)(MS) — a graph representation of the 3D Medial Axis  (MA)(MA) — of the original surface undergoes abrupt topological changes (transitions) such that the MSMS of the unorganized point set is significantly different from that of the original surface. The algorithm seeks a sequence of transformations of the MSMS to invert this process. Specifically, some MSMS curves (junctions of 3 MAMA 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 MSMS by “removing” suitable candidate MSMS curves (gap transform) from a rank-ordered list sorted by a combination of properties of the MSMS 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.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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