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dc.contributor.authorMabrouk, Sabra
dc.contributor.authorChaieb, Faten
dc.contributor.authorGhorbel, Faouzi
dc.contributor.editorSkala, Václav
dc.date.accessioned2018-05-18T13:05:32Z-
dc.date.available2018-05-18T13:05:32Z-
dc.date.issued2016
dc.identifier.citationWSCG '2016: short communications proceedings: The 24th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2016 in co-operation with EUROGRAPHICS: University of West Bohemia, Plzen, Czech RepublicMay 30 - June 3 2016, p. 327-333.en
dc.identifier.isbn978-80-86943-58-9
dc.identifier.issn2464-4617
dc.identifier.uriwscg.zcu.cz/WSCG2016/!!_CSRN-2602.pdf
dc.identifier.urihttp://hdl.handle.net/11025/29720
dc.description.abstractWe propose a new 3D mesh segmentation method based on the HMRF-EM framework. The clustering method relies on the curvature attribute and considers the spatial information encoded by the mutual influences of neighboring mesh elements. A region growing process is then carried out in order to extract connected regions followed by a merging procedure. The purpose of this latter process is to only preserve meaningful regions. Experiments conducted on different meshes are encouraging and show that the proposed method gives satisfying results compared with classical statistical ones such as kmeans and EM algorithms.en
dc.format7 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.relation.ispartofseriesWSCG '2016: short communications proceedingsen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectHMRF-EM algoritmuscs
dc.subjectrůstu regionucs
dc.subjectsloučení regionůcs
dc.subjectsegmentace okcs
dc.titleAn unsupervised 3D mesh segmentation based on HMRF-EM algorithmen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedHMRF-EM algorithmen
dc.subject.translatedregion growingen
dc.subject.translatedregion mergingen
dc.subject.translatedmesh segmentationen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG '2016: Short Papers Proceedings

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