TY - GEN
T1 - From point cloud to IFC
T2 - 27th EG-ICE International Workshop on Intelligent Computing in Engineering 2020
AU - Sánchez-Rodríguez, Ana
AU - Esser, Sebastian
AU - Abualdenien, Jimmy
AU - Borrmann, André
AU - Riveiro, Belén
N1 - Publisher Copyright:
© EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings. All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85091042409&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85091042409
T3 - EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings
SP - 422
EP - 431
BT - EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings
A2 - Ungureanu, Lucian-Constantin
A2 - Hartmann, Timo
PB - Universitatsverlag der TU Berlin
Y2 - 1 July 2020 through 4 July 2020
ER -