Tetrahedral meshing via maximal Poisson-disk sampling
Tetrahedral meshing via maximal Poisson-disk sampling
Lade...
Dateien
Datum
2016
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
eISSN
item.preview.dc.identifier.isbn
Bibliografische Daten
Verlag
Schriftenreihe
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
EU-Projektnummer
Projekt
Open Access-Veröffentlichung
Sammlungen
Titel in einer weiteren Sprache
Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published
Erschienen in
Computer Aided Geometric Design ; 43 (2016). - S. 186-199. - ISSN 0167-8396. - eISSN 1879-2332
Zusammenfassung
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.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
Rezension
undefined / . - undefined, undefined. - (undefined; undefined)
Zitieren
ISO 690
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. Available under: doi: 10.1016/j.cagd.2016.02.004BibTex
@article{Guo2016-02Tetra-33525, year={2016}, doi={10.1016/j.cagd.2016.02.004}, title={Tetrahedral meshing via maximal Poisson-disk sampling}, 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:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/33525"> <dcterms:issued>2016-02</dcterms:issued> <dc:creator>Yan, Dong-Ming</dc:creator> <dc:contributor>Guo, Jianwei</dc:contributor> <dc:creator>Zhang, Xiaopeng</dc:creator> <dc:contributor>Chen, Li</dc:contributor> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/33525/1/Guo_0-324779.pdf"/> <dc:creator>Chen, Li</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> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Guo, Jianwei</dc:creator> <dc:creator>Deussen, Oliver</dc:creator> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/33525/1/Guo_0-324779.pdf"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-04-01T07:55:35Z</dcterms:available> <dc:contributor>Zhang, Xiaopeng</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2016-04-01T07:55:35Z</dc:date> <dc:contributor>Yan, Dong-Ming</dc:contributor> <dcterms:title>Tetrahedral meshing via maximal Poisson-disk sampling</dcterms:title> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:language>eng</dc:language> <dc:contributor>Wonka, Peter</dc:contributor> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dc:contributor>Deussen, Oliver</dc:contributor> <foaf:homepage rdf:resource="http://localhost:8080/"/> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/33525"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:creator>Wonka, Peter</dc:creator> <dc:rights>terms-of-use</dc:rights> </rdf:Description> </rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja