Paper Info
Title
Curve skeleton extraction from incomplete point cloud
Abstract
We present an algorithm for curve skeleton extraction from imperfect point clouds where large portions of the data may be missing. Our construction is primarily based on a novel notion of generalized rotational symmetry axis (ROSA) of an oriented point set. Specifically, given a subset S of oriented points, we introduce a variational definition for an oriented point that is most rotationally symmetric with respect to S. Our formulation effectively utilizes normal information to compensate for the missing data and leads to robust curve skeleton computation over regions of a shape that are generally cylindrical. We present an iterative algorithm via planar cuts to compute the ROSA of a point cloud. This is complemented by special handling of non-cylindrical joint regions to obtain a centered, topologically clean, and complete 1D skeleton. We demonstrate that quality curve skeletons can be extracted from a variety of shapes captured by incomplete point clouds. Finally, we show how our algorithm assists in shape completion under these challenges by developing a skeleton-driven point cloud completion scheme.
Year
DOI
Venue
2009
10.1145/1576246.1531377
ACM Trans. Graph.
Keywords
Field
DocType
quality curve skeleton,oriented point set,robust curve skeleton computation,point cloud,incomplete data,iterative algorithm,skeleton-driven point cloud completion,incomplete point cloud,oriented point,rotational symmetry,curve skeleton,curve skeleton extraction,imperfect point cloud,missing data
Rotational symmetry,Mathematical optimization,Imperfect,Iterative method,Computer science,Cylinder,Planar,Missing data,Point cloud,Computation
Journal
Volume
Issue
ISSN
28
3
0730-0301
Citations 
PageRank 
References 
103
2.20
35
Authors
3
Search Limit
100103
Name
Order
Citations
PageRank
Andrea Tagliasacchi171631.90
Hao Zhang23037115.96
Daniel Cohen-Or310588533.55