Clustering For Surface Reconstruction
Clustering for Surface Reconstruction
Francesco Isgr o
DISI - Universit a di Genova
sgro@disi.unige.it
www.disi.unige.it/person/IsgroF
Francesca Odone
DISI - Universit a di Genova
odone@disi.unige.it
www.disi.unige.it/person/OdoneF
Waqar Saleem
Max-Planck-Institut f¨ur Informatik
wsaleem@mpi-sb.mpg.de
www.mpi-sb.mpg.de/wsaleem
Oliver Schall
Max-Planck-Institut f¨ur Informatik
schall@mpi-sb.mpg.de
www.mpi-sb.mpg.de/schall
Abstract
We consider applications of clustering techniques,
Mean Shift and Self-Organizing
Maps, to surface reconstruction (meshing)
from scattered point data and review
a novel kernel-based clustering method.
Keywords: clustering, meshing, scattered
data
Introduction
Clustering of a set of objects consists of partitioning
the set into groups (clusters) of similar
objects. Clustering is one of the core data mining
techniques. This paper describes an ongoing
joint research between DISI and MPII teams
with AIM@SHAPE project......
View the rest of this paper...
Approximate Word Count: 3371
Approximate Pages: 14 (250 words per double-spaced page)
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