A Coarse to Fine 3D Registration Method based on Robust Fuzzy Clustering
Abstract
An important problem in computer vision is to determine how features extracted
from images are connected to an existing model. In this paper, we focus
on solving the registration problem, i.e. obtaining rigid
transformation parameters between several 3D data sets, whether partial or
exhaustive. The difficulty of this problem is to obtain a method which is
robust with respect to outliers and at the same time accurate. We present a
general method performing robust
3D localization and fitting based on a fuzzy clustering method. The fuzzy set
approach
is known for its practical efficiency in uncertain environments. To illustrate
the advantages of this approach on the registration problem, we show results
on synthetic and real 3D data.
Reference
@ARTICLE{jpt-cviu98,
author = {Tarel, J.-P. and Boujemaa, N.},
title = {A Coarse to Fine 3D Registration Method Based on Robust Fuzzy Clustering},
journal = {Computer Vision and Image Understanding},
volume = {73},
number = {1},
month = jan,
pages = {14--28},
year = 1999,
note = {http://perso.lcpc.fr/tarel.jean-philippe/publis/cviu99.html}
}
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