Automatic Reconstruction of Parametric, Volumetric Building Models from 3D Point Clouds
dc.contributor.advisor | Klein, Reinhard | |
dc.contributor.author | Ochmann, Sebastian Klaus | |
dc.date.accessioned | 2020-04-26T12:24:59Z | |
dc.date.available | 2020-04-26T12:24:59Z | |
dc.date.issued | 02.05.2019 | |
dc.identifier.uri | https://hdl.handle.net/20.500.11811/7907 | |
dc.description.abstract | Planning, construction, modification, and analysis of buildings requires means of representing a building's physical structure and related semantics in a meaningful way. With the rise of novel technologies and increasing requirements in the architecture, engineering and construction (AEC) domain, two general concepts for representing buildings have gained particular attention in recent years. First, the concept of Building Information Modeling (BIM) is increasingly used as a modern means for representing and managing a building's as-planned state digitally, including not only a geometric model but also various additional semantic properties. Second, point cloud measurements are now widely used for capturing a building's as-built condition by means of laser scanning techniques. A particular challenge and topic of current research are methods for combining the strengths of both point cloud measurements and Building Information Modeling concepts to quickly obtain accurate building models from measured data. In this thesis, we present our recent approaches to tackle the intermeshed challenges of automated indoor point cloud interpretation using targeted segmentation methods, and the automatic reconstruction of high-level, parametric and volumetric building models as the basis for further usage in BIM scenarios. In contrast to most reconstruction methods available at the time, we fundamentally base our approaches on BIM principles and standards, and overcome critical limitations of previous approaches in order to reconstruct globally plausible, volumetric, and parametric models. | en |
dc.description.abstract | Automatische Rekonstruktion von parametrischen, volumetrischen Gebäudemodellen aus 3D Punktwolken | en |
dc.language.iso | eng | |
dc.rights | In Copyright | |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
dc.subject | Punktwolken | |
dc.subject | Gebäudemodelle | |
dc.subject | Rekonstruktion | |
dc.subject | Modellierung | |
dc.subject | Optimierung | |
dc.subject | Point clouds | |
dc.subject | Building models | |
dc.subject | Reconstruction | |
dc.subject | Modeling | |
dc.subject | Optimization | |
dc.subject.ddc | 004 Informatik | |
dc.title | Automatic Reconstruction of Parametric, Volumetric Building Models from 3D Point Clouds | |
dc.type | Dissertation oder Habilitation | |
dc.publisher.name | Universitäts- und Landesbibliothek Bonn | |
dc.publisher.location | Bonn | |
dc.rights.accessRights | openAccess | |
dc.identifier.urn | https://nbn-resolving.org/urn:nbn:de:hbz:5n-54199 | |
ulbbn.pubtype | Erstveröffentlichung | |
ulbbnediss.affiliation.name | Rheinische Friedrich-Wilhelms-Universität Bonn | |
ulbbnediss.affiliation.location | Bonn | |
ulbbnediss.thesis.level | Dissertation | |
ulbbnediss.dissID | 5419 | |
ulbbnediss.date.accepted | 20.03.2019 | |
ulbbnediss.institute | Mathematisch-Naturwissenschaftliche Fakultät : Fachgruppe Informatik / Institut für Informatik | |
ulbbnediss.fakultaet | Mathematisch-Naturwissenschaftliche Fakultät | |
dc.contributor.coReferee | Pajarola, Renato |
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