scholarly journals Discrete Distortion for Surface Meshes

2009 ◽  
pp. 652-661 ◽  
Author(s):  
Mohammed Mostefa Mesmoudi ◽  
Leila De Floriani ◽  
Paola Magillo
Keyword(s):  
Surface Meshes

scholarly journals Multilevel Solvers for Unstructured Surface Meshes

2005 ◽  
Vol 26 (4) ◽  
pp. 1146-1165 ◽  
Author(s):  
Burak Aksoylu ◽  
Andrei Khodakovsky ◽  
Peter Schröder
Keyword(s):  
Surface Meshes

scholarly journals An Improved Laplacian Smoothing Approach for Surface Meshes

2007 ◽  
pp. 318-325
Author(s):  
Ligang Chen ◽  
Yao Zheng ◽  
Jianjun Chen ◽  
Yi Liang
Keyword(s):  
Surface Meshes ◽  
Laplacian Smoothing

Lung lobe modeling and segmentation with individualized surface meshes

2008 ◽  
Author(s):  
Thomas Blaffert ◽  
Hans Barschdorf ◽  
Jens von Berg ◽  
Sebastian Dries ◽  
Astrid Franz ◽  
...  
Keyword(s):  
Lung Lobe ◽  
Surface Meshes

Wavelet Analysis Based Blind Watermarking for 3-D Surface Meshes

2006 ◽  
pp. 123-137 ◽  
Author(s):  
Min-Su Kim ◽  
Jae-Won Cho ◽  
Rémy Prost ◽  
Ho-Youl Jung
Keyword(s):  
Wavelet Analysis ◽  
Blind Watermarking ◽  
Surface Meshes

Laplacian-based 3D mesh simplification with feature preservation

2019 ◽  
Vol 10 (02) ◽  
pp. 1950002 ◽  
Author(s):  
Wei Lyu ◽  
Wei Wu ◽  
Lin Zhang ◽  
Zhaohui Wu ◽  
Zhong Zhou
Keyword(s):  
Clustering Algorithm ◽  
Shape Descriptor ◽  
Mesh Simplification ◽  
Feature Weighting ◽  
Laplacian Operator ◽  
Geometric Features ◽  
Error Statistics ◽  
3D Mesh ◽  
Surface Meshes ◽  
Improving Accuracy

We propose a novel Laplacian-based algorithm that simplifies triangle surface meshes and can provide different preservation ratios of geometric features. Our efficient and fast algorithm uses a 3D mesh model as input and initially detects geometric features by using a Laplacian-based shape descriptor (L-descriptor). The algorithm further performs an optimized clustering approach that combines a Laplacian operator with K-means clustering algorithm to perform vertex classification. Moreover, we introduce a Laplacian weighted cost function based on L-descriptor to perform feature weighting and error statistics comparison, which are further used to change the deletion order of the model elements and preserve the saliency features. Our algorithm can provide different preservation ratios of geometric features and may be extended to handle arbitrary mesh topologies. Our experiments on a variety of 3D surface meshes demonstrate the advantages of our algorithm in terms of improving accuracy and applicability, and preserving saliency geometric features.

Generating smooth surface meshes from multi-region medical images

2011 ◽  
Vol 28 (6-7) ◽  
pp. 642-660 ◽  
Author(s):  
Vinciane d'Otreppe ◽  
Romain Boman ◽  
Jean-Philippe Ponthot
Keyword(s):  
Smooth Surface ◽  
Medical Images ◽  
Surface Meshes
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