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IEEE International Conference on Shape Modeling and Applications 2006 (SMI'06)
Evolution of T-Spline Level Sets with Distance Field Constraints for Geometry Reconstruction and Image Segmentation
Matsushima, Japan
June 14-June 16
ISBN: 0-7695-2591-1
ASCII Text
x 
 
Huaiping Yang, Matthias Fuchs, Bert Juttler, Otmar Scherzer, "Evolution of T-Spline Level Sets with Distance Field Constraints for Geometry Reconstruction and Image Segmentation," Shape Modeling and Applications, International Conference on, pp. 37, IEEE International Conference on Shape Modeling and Applications 2006 (SMI'06), 2006.
 
 
BibTex
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@article{ 10.1109/SMI.2006.12,
author = {Huaiping Yang and Matthias Fuchs and Bert Juttler and Otmar Scherzer},
title = {Evolution of T-Spline Level Sets with Distance Field Constraints for Geometry Reconstruction and Image Segmentation},
journal ={Shape Modeling and Applications, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2591-1},
pages = {37},
doi = {http://doi.ieeecomputersociety.org/10.1109/SMI.2006.12},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Shape Modeling and Applications, International Conference on
TI - Evolution of T-Spline Level Sets with Distance Field Constraints for Geometry Reconstruction and Image Segmentation
SN - 0-7695-2591-1
SP
EP
A1 - Huaiping Yang,
A1 - Matthias Fuchs,
A1 - Bert Juttler,
A1 - Otmar Scherzer,
PY - 2006
KW - T-spline
KW - level sets
KW - unorganized points
KW - image segmentation
VL - 0
JA - Shape Modeling and Applications, International Conference on
ER -
 
Huaiping Yang, Johannes Kepler University Linz, Austria
Matthias Fuchs, University of Innsbruck, Austria
Bert Juttler, Johannes Kepler University, Austria
Otmar Scherzer, University of Innsbruck, Austria
We study the evolution of T-spline level sets (i.e, implicitly defined T-spline curves and surfaces). The use of T-splines leads to a sparse representation of the geometry and allows for an adaptation to the given data, which can be unorganized points or images. The evolution process is governed by a combination of prescribed, data-driven normal velocities, and additional distance field constraints. By incorporating the distance field constraints we are able to avoid additional branches and singularities of the T-spline level sets without having to use re-initialization steps. Experimental examples are presented to demonstrate the effectiveness of our approach.
Index Terms:
T-spline, level sets, unorganized points, image segmentation
Citation:
Huaiping Yang, Matthias Fuchs, Bert Juttler, Otmar Scherzer, "Evolution of T-Spline Level Sets with Distance Field Constraints for Geometry Reconstruction and Image Segmentation," smi, pp.37, IEEE International Conference on Shape Modeling and Applications 2006 (SMI'06), 2006
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