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dc.contributor.authorAthanasiadis, T.en
dc.contributor.authorFudos, I.en
dc.date.accessioned2015-11-24T17:02:28Z-
dc.date.available2015-11-24T17:02:28Z-
dc.identifier.issn0097-8493-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/11057-
dc.rightsDefault Licence-
dc.subjectmesh parameterizationen
dc.subjectmesh segmentationen
dc.subjectfeature detectionen
dc.subjectshape similarity object retrievalen
dc.subjectgpuen
dc.subjectparallel algorithmsen
dc.subjectrange imagesen
dc.subjectdecompositionen
dc.subjectparametrizationen
dc.subjectgenerationen
dc.subjectextractionen
dc.subjectsurfacesen
dc.subjectshapesen
dc.titleParallel computation of spherical parameterizations for mesh analysisen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDOI 10.1016/j.cag.2011.03.022-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.publicationDate2011-
heal.abstractMesh parameterization is central to a broad spectrum of applications. In this paper, we present a novel approach to spherical mesh parameterization based on an iterative quadratic solver that is efficiently parallelizable on modern massively parallel architectures. We present an extensive analysis of performance results on both GPU and multicore architectures. We introduce a number of heuristics that exploit various system characteristics of the underlying architectures to speed up the parallel realization of our algorithms. Furthermore, we demonstrate the applicability of our approach to real-time feature detection, mesh decomposition and similarity-based 3D object retrieval. Finally, we offer visual results and a demonstration video. (C) 2011 Elsevier Ltd. All rights reserved.en
heal.journalNameComputers & Graphics-Uken
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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