Title
Robust Segmentation of Multiple Intersecting Manifolds from Unoriented Noisy Point Clouds
Abstract
We present a method for extracting complex manifolds with an arbitrary number of self- intersections from unoriented point clouds containing large amounts of noise. Manifolds are formed in a three-step process. First, small flat neighbourhoods of all possible orientations are created around all points. Next, neighbourhoods are assembled into larger quasi-flat patches, whose overlaps give the global connectivity structure of the point cloud. Finally, curved manifolds are extracted from the patch connectivity graph via a multiple-source flood fill. The manifolds can be reconstructed into meshed surfaces using standard existing surface reconstruction methods. We demonstrate the speed and robustness of our method on several point clouds, with applications in point cloud segmentation, denoising and medial surface reconstruction.
Year
DOI
Venue
2014
10.1111/cgf.12255
Comput. Graph. Forum
Keywords
Field
DocType
languages,computational geometry,segmentation
Noise reduction,Surface reconstruction,Topology,Computer science,Segmentation,Computational geometry,Flood fill,Robustness (computer science),Point cloud,Manifold
Journal
Volume
Issue
ISSN
33
1
0167-7055
Citations 
PageRank 
References 
5
0.45
35
Authors
3
Name
Order
Citations
PageRank
Jacek Kustra1363.59
Andrei Jalba2987.67
Alexandru Telea31520107.14