TY - GEN
T1 - "BIM-TO-SCAN" FOR SCAN-TO-BIM
T2 - European Conference on Computing in Construction, EC3 2021
AU - Noichl, Florian
AU - Braun, Alexander
AU - Borrmann, André
N1 - Publisher Copyright:
© 2021, European Council on Computing in Construction (EC3). All rights reserved.
PY - 2021
Y1 - 2021
N2 - In the field of Scan-to-BIM, recent developments achieve promising results in accuracy and flexibility, leveraging tools from the field of deep learning for semantic segmentation of raw point cloud data. Those methods demand large-scale, domain-specific datasets for training. Promising ideas to fulfill this need use primitive synthetic point cloud data, which predominantly lack distinct point cloud properties, such as missing patches due to occlusions in the scene. To solve this issue, we use a specialized laser scan simulation tool from the domain of Geosciences in a toolchain that allows generating realistic ground truth data based on 3D models. In this context, we introduce a comprehensive taxonomy for the industrial point cloud context. Furthermore, we provide the missing link for a comprehensive, open-source toolchain that is flexible towards any use case in the field.
AB - In the field of Scan-to-BIM, recent developments achieve promising results in accuracy and flexibility, leveraging tools from the field of deep learning for semantic segmentation of raw point cloud data. Those methods demand large-scale, domain-specific datasets for training. Promising ideas to fulfill this need use primitive synthetic point cloud data, which predominantly lack distinct point cloud properties, such as missing patches due to occlusions in the scene. To solve this issue, we use a specialized laser scan simulation tool from the domain of Geosciences in a toolchain that allows generating realistic ground truth data based on 3D models. In this context, we introduce a comprehensive taxonomy for the industrial point cloud context. Furthermore, we provide the missing link for a comprehensive, open-source toolchain that is flexible towards any use case in the field.
UR - http://www.scopus.com/inward/record.url?scp=85142769312&partnerID=8YFLogxK
U2 - 10.35490/EC3.2021.166
DO - 10.35490/EC3.2021.166
M3 - Conference contribution
AN - SCOPUS:85142769312
SN - 9783907234549
T3 - Proceedings of the European Conference on Computing in Construction
SP - 164
EP - 172
BT - Proceedings of the 2021 European Conference on Computing in Construction
A2 - Hall, Daniel M.
A2 - Chassiakos, Athanasios
A2 - O'Donnell, James
A2 - Nikolic, Dragana
A2 - Xenides, Yiannis
PB - European Council on Computing in Construction (EC3)
Y2 - 26 July 2021 through 28 July 2021
ER -