Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/4140
DC FieldValueLanguage
dc.contributor.authorPoullis, Charalambos-
dc.contributor.otherΠουλλής, Χαράλαμπος-
dc.dateNOV 2013en
dc.date.accessioned2014-04-02T07:06:03Z-
dc.date.accessioned2015-12-09T11:30:35Z-
dc.date.available2014-04-02T07:06:03Z-
dc.date.available2015-12-09T11:30:35Z-
dc.date.issued2014-04-02-
dc.identifier.citationIEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, vol. 35, no. 11, pp. 2563-2575en_US
dc.identifier.issn01628828-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/4140-
dc.description.abstractWe propose a complete framework for the automatic modeling from point cloud data. Initially, the point cloud data are preprocessed into manageable datasets, which are then separated into clusters using a novel two-step, unsupervised clustering algorithm. The boundaries extracted for each cluster are then simplified and refined using a fast energy minimization process. Finally, three-dimensional models are generated based on the roof outlines. The proposed framework has been extensively tested, and the results are reported.en_US
dc.languageEnglishen
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Pattern Analysis and Machine Intelligenceen_US
dc.rights© IEEEen_US
dc.subjectSegmentationen_US
dc.subjectClusteringen_US
dc.titleA Framework for Automatic Modeling from Point Cloud Dataen_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.citation1en
dc.identifier.doi10.1109/TPAMI.2013.64en_US
dc.dept.handle123456789/134en
dc.relation.issue11en_US
dc.relation.volume35en_US
cut.common.academicyear2013-2014en_US
dc.identifier.spage2563en_US
dc.identifier.epage2575en_US
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn1939-3539-
crisitem.journal.publisherIEEE-
crisitem.author.deptDepartment of Multimedia and Graphic Arts-
crisitem.author.facultyFaculty of Fine and Applied Arts-
crisitem.author.orcid0000-0001-5666-5026-
crisitem.author.parentorgFaculty of Fine and Applied Arts-
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