Tetrahedral meshing via maximal Poisson-disk sampling
dc.contributor.author | Guo, Jianwei | |
dc.contributor.author | Yan, Dongming | |
dc.contributor.author | Chen, Li | |
dc.contributor.author | Zhang, Xiaopeng | |
dc.contributor.author | Deussen, Oliver | |
dc.contributor.author | Wonka, Peter | |
dc.date.accessioned | 2016-02-16T13:56:41Z | |
dc.date.available | 2016-02-16T13:56:41Z | |
dc.date.issued | 2016-02-15 | |
dc.identifier.citation | Tetrahedral meshing via maximal Poisson-disk sampling 2016 Computer Aided Geometric Design | |
dc.identifier.issn | 01678396 | |
dc.identifier.doi | 10.1016/j.cagd.2016.02.004 | |
dc.identifier.uri | http://hdl.handle.net/10754/596364 | |
dc.description.abstract | In this paper, we propose a simple yet effective method to generate 3D-conforming tetrahedral meshes from closed 2-manifold surfaces. Our approach is inspired by recent work on maximal Poisson-disk sampling (MPS), which can generate well-distributed point sets in arbitrary domains. We first perform MPS on the boundary of the input domain, we then sample the interior of the domain, and we finally extract the tetrahedral mesh from the samples by using 3D Delaunay or regular triangulation for uniform or adaptive sampling, respectively. We also propose an efficient optimization strategy to protect the domain boundaries and to remove slivers to improve the meshing quality. We present various experimental results to illustrate the efficiency and the robustness of our proposed approach. We demonstrate that the performance and quality (e.g., minimal dihedral angle) of our approach are superior to current state-of-the-art optimization-based approaches. | |
dc.language.iso | en | |
dc.publisher | Elsevier BV | |
dc.relation.url | http://linkinghub.elsevier.com/retrieve/pii/S016783961630005X | |
dc.rights | NOTICE: this is the author’s version of a work that was accepted for publication in Computer Aided Geometric Design. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Aided Geometric Design, 15 February 2016. DOI: 10.1016/j.cagd.2016.02.004. | |
dc.subject | Tetrahedral mesh generation | |
dc.subject | Maximal poisson-disk sampling | |
dc.subject | Sliver removal | |
dc.subject | Mesh optimization | |
dc.title | Tetrahedral meshing via maximal Poisson-disk sampling | |
dc.type | Article | |
dc.contributor.department | Computer Science Program | |
dc.contributor.department | Visual Computing Center (VCC) | |
dc.identifier.journal | Computer Aided Geometric Design | |
dc.eprint.version | Post-print | |
dc.contributor.institution | National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China | |
dc.contributor.institution | School of Software, Tsinghua University, Beijing 100084, China | |
dc.contributor.institution | University of Konstanz, Konstanz 78457, Germany | |
dc.contributor.institution | Shenzhen Key Lab of Visual Computing and Visual Analytics/SIAT, Shenzhen 518055, China | |
dc.contributor.affiliation | King Abdullah University of Science and Technology (KAUST) | |
kaust.person | Wonka, Peter | |
refterms.dateFOA | 2018-02-15T00:00:00Z | |
dc.date.published-online | 2016-02-15 | |
dc.date.published-print | 2016-03 |
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