TY - JOUR
T1 - Octree-based, automatic building façade generation from LiDAR data
AU - Truong-Hong, Linh
AU - Laefer, Debra F.
N1 - Funding Information:
This work was generously supported by Science Foundation Ireland Grant 05/PICA/I830 and the European Union Grant ERC StG 2012-307836-RETURN . Further thanks to Donal Lennon of UCD’s Earth Institute for his assistance with terrestrial data acquisition.
PY - 2014/8
Y1 - 2014/8
N2 - This paper introduces a new, octree-based algorithm to assist in the automated conversion of laser scanning point cloud data into solid models appropriate for computational analysis. The focus of the work is for typical, urban, vernacular structures to assist in better damage prediction prior to tunnelling. The proposed FaçadeVoxel algorithm automatically detects boundaries of building façades and their openings. Next, it checks and automatically fills unintentional occlusions. The proposed method produced robust and efficient reconstructions of building models from various data densities. When compared to measured drawings, the reconstructed building models were in good agreement, with only 1% relative errors in overall dimensions and 3% errors in openings. In addition, the proposed algorithm was significantly faster than other automatic approaches without compromising accuracy.
AB - This paper introduces a new, octree-based algorithm to assist in the automated conversion of laser scanning point cloud data into solid models appropriate for computational analysis. The focus of the work is for typical, urban, vernacular structures to assist in better damage prediction prior to tunnelling. The proposed FaçadeVoxel algorithm automatically detects boundaries of building façades and their openings. Next, it checks and automatically fills unintentional occlusions. The proposed method produced robust and efficient reconstructions of building models from various data densities. When compared to measured drawings, the reconstructed building models were in good agreement, with only 1% relative errors in overall dimensions and 3% errors in openings. In addition, the proposed algorithm was significantly faster than other automatic approaches without compromising accuracy.
KW - Computational modelling
KW - Finite element modelling
KW - Geometric modelling
KW - Light Detection and Ranging (LiDAR)
KW - Masonry buildings
KW - Terrestrial laser scanning
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U2 - 10.1016/j.cad.2014.03.001
DO - 10.1016/j.cad.2014.03.001
M3 - Article
AN - SCOPUS:84898810356
SN - 0010-4485
VL - 53
SP - 46
EP - 61
JO - CAD Computer Aided Design
JF - CAD Computer Aided Design
ER -