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@inproceedings{490477,
author = {Matula, Pavel and Svoboda, David},
address = {Berlin Heidelberg New York},
booktitle = {Discrete Geometry for Computer Imagery},
keywords = {spherical objects; object reconstruction; deformable models; sparse data; simplex mesh; volumetric image segmentation},
language = {eng},
location = {Berlin Heidelberg New York},
isbn = {3-540-20499-7},
note = {LNCS 2886},
pages = {524-533},
publisher = {Springer-Verlag},
title = {Spherical Object Reconstruction Using Simplex Meshes from Sparse Data},
url = {http://www.springerlink.com/content/t2t0bw1wul5ay8kd/},
year = {2003}
}
TY - JOUR
ID - 490477
AU - Matula, Pavel - Svoboda, David
PY - 2003
TI - Spherical Object Reconstruction Using Simplex Meshes from Sparse Data
PB - Springer-Verlag
CY - Berlin Heidelberg New York
SN - 3540204997
N1 - LNCS 2886
KW - spherical objects
KW - object reconstruction
KW - deformable models
KW - sparse data
KW - simplex mesh
KW - volumetric image segmentation
UR - http://www.springerlink.com/content/t2t0bw1wul5ay8kd/
N2 - A new method for spherical object reconstruction based on deformation of star-shaped simplex meshes has been developed in our laboratory and published recently. The method can handle volumetric as well as three-dimensional range data and is easy to use and relatively fast. The method, however, can yield wrong results for sparse data. The goal of this paper is to describe a modification of the method that is suitable also for sparse data. The performance of the proposed modification is demonstrated on real biomedical data.
ER -
MATULA, Pavel and David SVOBODA. Spherical Object Reconstruction Using Simplex Meshes from Sparse Data. In \textit{Discrete Geometry for Computer Imagery}. Berlin Heidelberg New York: Springer-Verlag, 2003, p.~524-533. ISBN~3-540-20499-7.
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