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dc.contributor.authorBrilakis, Ioannisen
dc.contributor.authorLourakis, Manolisen
dc.contributor.authorSacks, Rafaelen
dc.contributor.authorSavarese, Silvioen
dc.contributor.authorChristodoulou, Symeon E.en
dc.contributor.authorTeizer, Jochenen
dc.contributor.authorMakhmalbaf, Atefeen
dc.creatorBrilakis, Ioannisen
dc.creatorLourakis, Manolisen
dc.creatorSacks, Rafaelen
dc.creatorSavarese, Silvioen
dc.creatorChristodoulou, Symeon E.en
dc.creatorTeizer, Jochenen
dc.creatorMakhmalbaf, Atefeen
dc.date.accessioned2019-04-18T06:18:39Z
dc.date.available2019-04-18T06:18:39Z
dc.date.issued2010
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/45229
dc.description.abstractOnly very few constructed facilities today have a complete record of as-built information. Despite the growing use of Building Information Modelling and the improvement in as-built records, several more years will be required before guidelines that require as-built data modelling will be implemented for the majority of constructed facilities, and this will still not address the stock of existing buildings. A technical solution for scanning buildings and compiling Building Information Models is needed. However, this is a multidisciplinary problem, requiring expertise in scanning, computer vision and videogrammetry, machine learning, and parametric object modelling. This paper outlines the technical approach proposed by a consortium of researchers that has gathered to tackle the ambitious goal of automating as-built modelling as far as possible. The top level framework of the proposed solution is presented, and each process, input and output is explained, along with the steps needed to validate them. Preliminary experiments on the earlier stages (i.e. processes) of the framework proposed are conducted and results are shownen
dc.description.abstractthe work toward implementation of the remainder is ongoing.en
dc.language.isoengen
dc.sourceAdvanced Engineering Informaticsen
dc.source.urihttp://search.proquest.com/docview/831151914?accountid=17200
dc.subjectComputersen
dc.subjectModelsen
dc.subjectLearning algorithmsen
dc.subjectScanningen
dc.subjectData processingen
dc.subjectComputer visionen
dc.subjectImage processingen
dc.subjectBuilding information modelingen
dc.subjectHybridsen
dc.subjectInformaticsen
dc.subjectMachine learningen
dc.subjectToxicology Abstractsen
dc.subjectVideogrammetryen
dc.subjectVisionen
dc.subjectX 24390:Radioactive Materialsen
dc.titleToward automated generation of parametric BIMs based on hybrid video and laser scanning dataen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doihttp://dx.doi.org/10.1016/j.aei.2010.06.006
dc.description.volume24
dc.description.issue4
dc.description.startingpage456
dc.description.endingpage465
dc.author.facultyΠολυτεχνική Σχολή / Faculty of Engineering
dc.author.departmentΤμήμα Πολιτικών Μηχανικών και Μηχανικών Περιβάλλοντος / Department of Civil and Environmental Engineering
dc.type.uhtypeArticleen
dc.contributor.orcidChristodoulou, Symeon E. [0000-0002-9859-0381]
dc.gnosis.orcid0000-0002-9859-0381


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