10th International Meshing Roundtable
Newport Beach, California, U.S.A.
October 7-10, 2001
University of Tubingen
Xinlong Wang and Rob Macleod
Scientific Computing and Imaging Institute
University of Utah, Utah
Email: firstname.lastname@example.org, email@example.com
This paper describes a new method to extract feature lines directly from a surface
point cloud. No surface recon- struction is needed in advance, only the inexpensive
computation of a neighbor graph connecting nearby points. The feature extraction is
performed in two stages. The first stage consists of assigning a penalty weight to
each point that indicates the unlikelihood that the point is part of a feature and
assigning these penalty weights to the edges of a neighbor graph. Extracting a
sub-graph of the neighbor graph that minimizes the edge penalty weights then produces
a set of feature patterns. The second stage is especially useful for noisy data.
It recovers feature lines and junctions by fitting wedges to the crease lines and
corners to the junctions. As the method works on the local neighbor graph only,
it is fast and automatically adapts to the sampling resolution. This makes the
approach ideal as a preprocessing step in mesh generation.
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