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

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

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.

Original languageEnglish
Title of host publicationEG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings
EditorsLucian-Constantin Ungureanu, Timo Hartmann
PublisherUniversitatsverlag der TU Berlin
Pages422-431
Number of pages10
ISBN (Electronic)9783798331556
StatePublished - 2020
Event27th EG-ICE International Workshop on Intelligent Computing in Engineering 2020 - Virtual, Online, Germany
Duration: 1 Jul 20204 Jul 2020

Publication series

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

Conference

Conference27th EG-ICE International Workshop on Intelligent Computing in Engineering 2020
Country/TerritoryGermany
CityVirtual, Online
Period1/07/204/07/20

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