Tetrahedral meshing via maximal Poisson-disk sampling

Zitieren

Dateien zu dieser Ressource

Prüfsumme: MD5:d021c4e26cf5c5ab4cedf547c3d61059

GUO, Jianwei, Dong-Ming YAN, Li CHEN, Xiaopeng ZHANG, Oliver DEUSSEN, Peter WONKA, 2016. Tetrahedral meshing via maximal Poisson-disk sampling. In: Computer Aided Geometric Design. 43, pp. 186-199. ISSN 0167-8396. eISSN 1879-2332

@article{Guo2016-02Tetra-33525, title={Tetrahedral meshing via maximal Poisson-disk sampling}, year={2016}, doi={10.1016/j.cagd.2016.02.004}, volume={43}, issn={0167-8396}, journal={Computer Aided Geometric Design}, pages={186--199}, author={Guo, Jianwei and Yan, Dong-Ming and Chen, Li and Zhang, Xiaopeng and Deussen, Oliver and Wonka, Peter} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/33525"> <dc:contributor>Wonka, Peter</dc:contributor> <dc:creator>Zhang, Xiaopeng</dc:creator> <dc:contributor>Chen, Li</dc:contributor> <dc:contributor>Zhang, Xiaopeng</dc:contributor> <dcterms:title>Tetrahedral meshing via maximal Poisson-disk sampling</dcterms:title> <dcterms:rights rdf:resource="http://nbn-resolving.de/urn:nbn:de:bsz:352-20150914100631302-4485392-8"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-04-01T07:55:35Z</dcterms:available> <dc:creator>Deussen, Oliver</dc:creator> <dc:creator>Chen, Li</dc:creator> <dc:creator>Guo, Jianwei</dc:creator> <dc:contributor>Yan, Dong-Ming</dc:contributor> <dc:contributor>Guo, Jianwei</dc:contributor> <dc:creator>Wonka, Peter</dc:creator> <dc:language>eng</dc:language> <dcterms:issued>2016-02</dcterms:issued> <dc:creator>Yan, Dong-Ming</dc:creator> <dcterms:abstract xml:lang="eng">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.</dcterms:abstract> <dc:contributor>Deussen, Oliver</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-04-01T07:55:35Z</dc:date> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/33525"/> </rdf:Description> </rdf:RDF>

Das Dokument erscheint in:

KOPS Suche


Stöbern

Mein Benutzerkonto