From point cloud to IFC: A masonry arch bridge case study

Ana Sánchez-Rodríguez, Sebastian Esser, Jimmy Abualdenien, André Borrmann, Belén Riveiro

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

7 Zitate (Scopus)

Abstract

For the last several years, laser scanning has become one of the reference technologies when talking about the monitoring of assets. Nowadays, the trend is to use these data for creating semantically rich three-dimensional (3D) models, broadly known as digital twins. The bottleneck appears when processing the large amount of data acquired with the laser scanner. This paper tackles the creation of IFC data models using classified point cloud data. The point labelling methodology is based on one in the state-of-the-art, whose results have been improved. Then, each group of points is converted to a triangulated mesh, and the resultant geometrical objects are placed in an IFC-based model in a low and high level of detail. Moreover, the resultant IFC model allows the enrichment of the captured geometry with additional information.

OriginalspracheEnglisch
TitelEG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings
Redakteure/-innenLucian-Constantin Ungureanu, Timo Hartmann
Herausgeber (Verlag)Universitatsverlag der TU Berlin
Seiten422-431
Seitenumfang10
ISBN (elektronisch)9783798331556
PublikationsstatusVeröffentlicht - 2020
Veranstaltung27th EG-ICE International Workshop on Intelligent Computing in Engineering 2020 - Virtual, Online, Deutschland
Dauer: 1 Juli 20204 Juli 2020

Publikationsreihe

NameEG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings

Konferenz

Konferenz27th EG-ICE International Workshop on Intelligent Computing in Engineering 2020
Land/GebietDeutschland
OrtVirtual, Online
Zeitraum1/07/204/07/20

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