A new mesh simplification algorithm combining half-edge data structure with modified quadric error metric

2003 ◽  
Author(s):  
Li Guangming ◽  
Tian Jie ◽  
Zhao Mingchang ◽  
He Huiguang ◽  
Zhang Xiaopeng
Keyword(s):  
Data Structure ◽  
Mesh Simplification ◽  
Error Metric ◽  
Quadric Error Metric

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.

scholarly journals Quadratic Error Metric Mesh Simplification Algorithm Based on Discrete Curvature

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Li Yao ◽  
Shihui Huang ◽  
Hui Xu ◽  
Peilin Li
Keyword(s):  
Computer Graphics ◽  
Mesh Simplification ◽  
Quadratic Error ◽  
Topology Structure ◽  
Discrete Curvature ◽  
And Topology ◽  
Complex Models ◽  
Error Metric ◽  
Polygon Meshes ◽  
Quadric Error Metric

Complex and highly detailed polygon meshes have been adopted for model representation in many areas of computer graphics. Existing works mainly focused on the quadric error metric based complex models approximation, which has not taken the retention of important model details into account. This may lead to visual degeneration. In this paper, we improve Garland and Heckberts’ quadric error metric based algorithm by using the discrete curvature to reserve more features for mesh simplification. Our experiments on various models show that the geometry and topology structure as well as the features of the original models are precisely retained by employing discrete curvature.

scholarly journals High-performance simplification of triangular surfaces using a GPU

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255832
Author(s):  
Mohamed H. Mousa ◽  
Mohamed K. Hussein
Keyword(s):  
Data Structure ◽  
High Performance Computing ◽  
Geometric Modeling ◽  
High Performance ◽  
Priority Queue ◽  
Mesh Simplification ◽  
Strong Impact ◽  
Topological Properties ◽  
Dynamic Memory ◽  
Performance Computing

Due to advances in high-performance computing technologies, computer graphics techniques—especially those related to mesh simplification—have been noticeably improved. These techniques, which have a strong impact on many applications, such as geometric modeling and visualization, have been well studied for more than two decades. Recent advances in GPUs have led to significant improvements in terms of speed and interactivity. In this paper, we present a mesh simplification algorithm that benefits from the parallel framework provided by recent GPUs. We customize the halfedge data structure for adaption with the dynamic memory restrictions of CUDA. The proposed algorithm is fully parallelized by employing a lock-free skip priority queue and a set of disjoint regions of the mesh. The proposed technique accelerates the simplification process while preserving the topological properties of the mesh. Some results and comparisons are provided to verify the efficiency of the proposed algorithm.

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