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dc.contributor.authorAkça, Mehmet Devrimen_US
dc.contributor.authorAydar, Umuten_US
dc.contributor.authorAltan, Mehmet Orhanen_US
dc.contributor.authorAkyılmaz, Orhanen_US
dc.date.accessioned2015-11-25T13:04:54Z
dc.date.available2015-11-25T13:04:54Z
dc.date.issued2012-08-25
dc.identifier.citationAydar, U., Altan, M. O., Akyılmaz, O. & Akça, M. D. (2012). Co-registration of 3D point clouds by using an errors-in-variables model. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 39, 151-155.en_US
dc.identifier.issn2194-9034
dc.identifier.issn1682-1750
dc.identifier.urihttps://hdl.handle.net/11729/723
dc.description.abstractCo-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of co-registration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In the literature, one of the most popular methods is the ICP (Iterative Closest Point) algorithm and its variants. There exist the 3D least squares (LS) matching methods as well. In most of the co-registration methods, the stochastic properties of the search surfaces are usually omitted. This omission is expected to be minor and does not disturb the solution vector significantly. However, the a posteriori covariance matrix will be affected by the neglected uncertainty of the function values. This causes deterioration in the realistic precision estimates. In order to overcome this limitation, we propose a new method where the stochastic properties of both (template and search) surfaces are considered under an errors-in-variables (EIV) model. The experiments have been carried out using a close range laser scanning data set and the results of the conventional and EIV types of the ICP matching methods have been compared.en_US
dc.language.isoengen_US
dc.publisherCopernicus Gesellschaft MBHen_US
dc.relation.ispartofseriesInternational Archives of the Photogrammetry Remote Sensing and Spatial Information Sciencesen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCovariance matrixen_US
dc.subjectErrorsen_US
dc.subjectErrors-in-variables (EIV) modelen_US
dc.subjectErrors-in-variables modelsen_US
dc.subjectEstimationen_US
dc.subjectIterative closest pointsen_US
dc.subjectIterative methodsen_US
dc.subjectLaser applicationsen_US
dc.subjectLaser scanningen_US
dc.subjectLeast squares approximationsen_US
dc.subjectMatchingen_US
dc.subjectPhotogrammetryen_US
dc.subjectPoint clouden_US
dc.subjectRegistrationen_US
dc.subjectRemote sensingen_US
dc.subjectSpatial transformationen_US
dc.subjectStochastic modelsen_US
dc.subjectStochastic systemsen_US
dc.subjectSurface analysisen_US
dc.subjectTotal least-squaresen_US
dc.subjectTransformationen_US
dc.titleCo-registration of 3d point clouds by using an errors-in-variables modelen_US
dc.typeconferenceObjecten_US
dc.description.versionPublisher's Versionen_US
dc.relation.journalXXII ISPRS Congress, Technical Commission Ven_US
dc.contributor.departmentIşık Üniversitesi, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümüen_US
dc.contributor.departmentIşık University, Faculty of Engineering, Department of Civil Engineeringen_US
dc.contributor.authorID0000-0002-1510-8677
dc.identifier.volume39-B5
dc.identifier.startpage151
dc.identifier.endpage155
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorAkça, Mehmet Devrimen_US
dc.relation.indexWOSen_US
dc.relation.indexScopusen_US
dc.relation.indexConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.description.wosidWOS:000358240300026


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