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Clustering for Surface Reconstruction. ... In the rst part, we consider applications
of clustering to surface reconstruction from scattered point data. ...
Submitted by wsaleem on October 25, 2005
Category: Science
Words: 3371 | Pages: 14
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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 framework 1 on using
clustering techniques for surface reconstruction
from scattered data. The paper consists of
two parts (clusters). In the rst part, we consider
applications of clustering to surface reconstruction
from scattered point data. In the second
part, we briey review an alternative clustering
method which we plan to employ for surface re-
1AIM@SHAPE is a Network of Excellence project
within EU's Sixth Framework Programme. The project
involves research groups from 14 institutions and is
aimed at basic and applied studies of digital shape
modeling.
construction in combination or as an alternative
to the two presented algorithms.
1 Clustering Techniques for
Meshing Scattered Data
...
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