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dc.contributor.authorBalado Frías, Jesús 
dc.contributor.authorDíaz Vilariño, Lucía 
dc.contributor.authorArias Sánchez, Pedro 
dc.contributor.authorGonzález Jorge, Higinio 
dc.date.accessioned2019-10-29T12:46:20Z
dc.date.available2020-03-01T00:15:06Z
dc.date.issued2018-02
dc.identifier.citationAutomation in Construction, 86, 226-239 (2018)spa
dc.identifier.issn09265805
dc.identifier.urihttp://hdl.handle.net/11093/1350
dc.description.abstractAccessibility diagnosis of as-built urban environments is essential for path planning, especially in case of people with reduced mobility and it requires an in-depth knowledge of ground elements. In this paper, we present a new approach for automatically detect and classify urban ground elements from 3D point clouds. The methodology enables a high level of detail classification from the combination of geometric and topological information. The method starts by a planar segmentation followed by a refinement based on split and merge operations. Next, a feature analysis and a geometric decision tree are followed to classify regions in preliminary classes. Finally, adjacency is studied to verify and correct the preliminary classification based on a comparison with a topological graph library. The methodology is tested in four real complex case studies acquired with a Mobile Laser Scanner Device. In total, five classes are considered (roads, sidewalks, treads, risers and curbs). Results show a success rate of 97% in point classification, enough to analyse extensive urban areas from an accessibility point of view. The combination of topology and geometry improves a 10% to 20% the success rate obtained with only the use of geometry.spa
dc.description.sponsorshipCátedra SCI-EYSA. Smart cities e seguridade vialspa
dc.description.sponsorshipXunta de Galicia. ED481B 2016/079-0spa
dc.description.sponsorshipMinisterio de Economía y Competitividad. TIN2016-77158-C4-2-Rspa
dc.language.isoengspa
dc.publisherAutomation in Constructionspa
dc.titleAutomatic classification of urban ground elements from mobile laser scanning dataspa
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.relation.projectIDinfo:eu-repo/grantAgreement/EU/H2020/720661spa
dc.identifier.doi10.1016/j.autcon.2017.09.004
dc.identifier.editorhttps://linkinghub.elsevier.com/retrieve/pii/S092658051730153Xspa
dc.publisher.departamentoEnxeñaría dos recursos naturais e medio ambientespa
dc.publisher.grupoinvestigacionXeotecnoloxías Aplicadasspa
dc.subject.unesco330522 Metrología de la edificación
dc.subject.unesco331102 Ingeniería de control
dc.subject.unesco330534 Topografía de la edificación
dc.date.updated2019-10-29T11:12:42Z


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