Skeleton-bridged Mesh Saliency and Mesh Simplification

2020 ◽  
Author(s):  
Wanna Luan ◽  
Chengming Liu ◽  
Haibo Pang
Keyword(s):  
Mesh Simplification ◽  
Mesh Saliency

Feature Preserving Mesh Simplification Algorithm Based on Square Volume Measure

2009 ◽  
Vol 32 (2) ◽  
pp. 203-212 ◽  
Author(s):  
Yuan-Feng ZHOU ◽  
Cai-Ming ZHANG ◽  
Ping HE
Keyword(s):  
Mesh Simplification ◽  
Volume Measure ◽  
Feature Preserving

Research on Triangular Mesh Simplification Algorithm of Virtual Object Model

2012 ◽  
Vol 271-272 ◽  
pp. 1410-1414 ◽  
Author(s):  
Yang Ping Wang ◽  
Jian Wu Dang ◽  
Jin Yu Yang ◽  
Song Wang
Keyword(s):  
Triangular Mesh ◽  
Mesh Simplification ◽  
Virtual Object ◽  
Object Model ◽  
Model Simplification ◽  
Model Quality ◽  
Weight Calculation ◽  
Edge Surface

To improve the model quality of mesh simplification, reduce the model deformation and the lost of the detail characteristics with multiple folding, the paper represents a triangular mesh simplification algorithm based on edge-surface folding. The algorithm introduces curvature characteristics of model vertexes into the weight calculation of effective points, and introduces weight of triangular facets at the same time. The facets with the smallest weight adjacent the candidate edge is shrunk. The experiment results show that the algorithm has provided a higher quality of model simplification and effectively kept the graphic features.

scholarly journals Multi-scale mesh saliency based on low-rank and sparse analysis in shape feature space

2015 ◽  
Vol 35-36 ◽  
pp. 206-214 ◽  
Author(s):  
Shengfa Wang ◽  
Nannan Li ◽  
Shuai Li ◽  
Zhongxuan Luo ◽  
Zhixun Su ◽  
...  
Keyword(s):  
Feature Space ◽  
Low Rank ◽  
Shape Feature ◽  
Mesh Saliency ◽  
Multi Scale

Analysis and efficiency of the GNG3D algorithm for mesh simplification

2008 ◽  
Vol 197 (1) ◽  
pp. 29-40 ◽  
Author(s):  
José-Vicente Noguera ◽  
Leandro Tortosa ◽  
Antonio Zamora
Keyword(s):  
Mesh Simplification

Interest Points Guided Mesh Simplification

2012 ◽  
Vol 263-266 ◽  
pp. 2320-2323 ◽  
Author(s):  
Ying Gao ◽  
Rui Zhao Wang ◽  
Jue Yuan
Keyword(s):  
Mesh Simplification ◽  
Experimental Results ◽  
Interest Point ◽  
Interest Points ◽  
Interest Point Detection ◽  
Feature Preserving ◽  
Error Metric ◽  
Point Detection ◽  
Quadric Error Metric

Based on interest point detection, a feature preserving mesh simplification algorithm is proposed. The Harris operator values of all vertices in the mesh were computed firstly. On the base of Garland’s simplification algorithm, we combine the Harris operator value with quadric error metric and change the order of edge collapsing in the simplification. The experimental results show that the proposed algorithm is effective and feature preserving.

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