Spectral Surface Reconstruction From Noisy Point Clouds

Kolluri, Ravikrishna; Shewchuk, Jonathan Richard; O'Brien, James F.

Spectral Surface Reconstruction From Noisy Point Clouds

Files

011-022.pdf (7.36 MB)

Date

2004

Authors

Kolluri, Ravikrishna
Shewchuk, Jonathan Richard
O'Brien, James F.

Publisher

The Eurographics Association

Abstract

We introduce a noise-resistant algorithm for reconstructing a watertight surface from point cloud data. It forms a Delaunay tetrahedralization, then uses a variant of spectral graph partitioning to decide whether each tetrahedron is inside or outside the original object. The reconstructed surface triangulation is the set of triangular faces where inside and outside tetrahedra meet. Because the spectral partitioner makes local decisions based on a global view of the model, it can ignore outliers, patch holes and undersampled regions, and surmount ambiguity due to measurement errors. Our algorithm can optionally produce a manifold surface. We present empirical evidence that our implementation is substantially more robust than several closely related surface reconstruction programs.

        @inproceedings{:10.2312/SGP/SGP04/011-022
,
booktitle = {Symposium on Geometry Processing
},
editor = {Roberto Scopigno and Denis Zorin
},
title = {{Spectral Surface Reconstruction From Noisy Point Clouds
}},
author = {Kolluri, Ravikrishna and 
Shewchuk, Jonathan Richard and 
O'Brien, James F.
},
year = {2004
},
publisher = {The Eurographics Association
},
ISSN = {1727-8384
},
ISBN = {3-905673-13-4
},
DOI = {/10.2312/SGP/SGP04/011-022
}
}