A sharpness dependent filter for mesh smoothing

Chen, Chun‐Yen; Cheng, K. Y.

doi:10.1016/j.cagd.2005.04.003

Cited by 71 publications

(47 citation statements)

References 7 publications

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“…We employ the idea of anisotropic vector diffusion [35,49] and apply it to the normals of the surface mesh being considered. This normal-based approach turns out to preserve sharp features and prevent volume shrinkages [15,47] better than the traditional vertex-based approach. Figure 2(c) shows the result after the mesh coarsening and normal-based mesh smoothing.…”

Section: Surface Mesh Coarsening and Smoothingmentioning

confidence: 99%

Feature-preserving adaptive mesh generation for molecular shape modeling and simulation

Holst

McCammon

2008

Journal of Molecular Graphics and Modelling

106

122

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We describe a chain of algorithms for molecular surface and volumetric mesh generation. We take as inputs the centers and radii of all atoms of a molecule and the toolchain outputs both triangular and tetrahedral meshes that can be used for molecular shape modeling and simulation. Experiments on a number of molecules are demonstrated, showing that our methods possess several desirable properties: feature-preservation, local adaptivity, high quality, and smoothness (for surface meshes). We also demonstrate an example of molecular simulation using the finite element method and the meshes generated by our method. The approaches presented and their implementations are also applicable to other types of inputs such as 3D scalar volumes and triangular surface meshes with low quality, and hence can be used for generation/improvment of meshes in a broad range of applications.

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Section: Surface Mesh Coarsening and Smoothingmentioning

confidence: 99%

Feature-preserving adaptive mesh generation for molecular shape modeling and simulation

Holst

McCammon

2008

Journal of Molecular Graphics and Modelling

106

122

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“…An extensive overview is beyond the scope of this paper, but can be found on remeshing [Alliez et al 2005] and geometric signal processing [Taubin 2000]. More recent surveys on mesh smoothing are available in [Hildebrandt and Polthier 2005], [Bobenko and Schröder 2005] and [Chen and Cheng 2005]. Vertex relocation for remeshing.…”

Section: Related Workmentioning

confidence: 99%

Laplacian mesh optimization

Nealen

Igarashi

Sorkine

et al. 2006

Proceedings of the 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast As

277

167

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We introduce a framework for triangle shape optimization and feature preserving smoothing of triangular meshes that is guided by the vertex Laplacians, specifically, the uniformly weighted Laplacian and the discrete mean curvature normal. Vertices are relocated so that they approximate prescribed Laplacians and positions in a weighted least-squares sense; the resulting linear system leads to an efficient, non-iterative solution. We provide different weighting schemes and demonstrate the effectiveness of the framework on a number of detailed and highly irregular meshes; our technique successfully improves the quality of the triangulation while remaining faithful to the original surface geometry, and it is also capable of smoothing the surface while preserving geometric features.

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“…The first approach is to move the vertices based on certain criteria, such as the Laplacian operator [44] and mean curvature flows [18,33]. In contrast, the normal-based approach smoothes meshes using the normal information of neighboring triangles, which turns out to preserve sharp features and prevent volume shrinkages [14] better than the vertex-based approach. In our mesh generator, we utilize the normal-based approach.…”

Section: Normal-based Anisotropic Surface Smoothingmentioning

confidence: 99%

High-fidelity geometric modeling for biomedical applications

Holst

McCammon

2008

Finite Elements in Analysis and Design

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We describe a combination of algorithms for high fidelity geometric modeling and mesh generation. Although our methods and implementations are application-neutral, our primary target application is multiscale biomedical models that range in scales across the molecular, cellular, and organ levels. Our software toolchain implementing these algorithms is general in the sense that it can take as input a molecule in PDB/PQR forms, a 3D scalar volume, or a user-defined triangular surface mesh that may have very low quality. The main goal of our work presented is to generate high quality and smooth surface triangulations from the aforementioned inputs, and to reduce the mesh sizes by mesh coarsening. Tetrahedral meshes are also generated for finite element analysis in biomedical applications. Experiments on a number of bio-structures are demonstrated, showing that our approach possesses several desirable properties: feature-preservation, local adaptivity, high quality, and smoothness (for surface meshes). The availability of this software toolchain will give researchers in computational biomedicine and other modeling areas access to higher-fidelity geometric models.

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A sharpness dependent filter for mesh smoothing

Cited by 71 publications

References 7 publications

Feature-preserving adaptive mesh generation for molecular shape modeling and simulation

Feature-preserving adaptive mesh generation for molecular shape modeling and simulation

Laplacian mesh optimization

High-fidelity geometric modeling for biomedical applications

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