Octree-based, automatic building façade generation from LiDAR data
|Title:||Octree-based, automatic building façade generation from LiDAR data||Authors:||Truong-Hong, Linh
Laefer, Debra F.
|Permanent link:||http://hdl.handle.net/10197/7451||Date:||Aug-2014||Abstract:||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.||Funding Details:||European Research Council
Science Foundation Ireland
|Type of material:||Journal Article||Publisher:||Elsevier||Copyright (published version):||2014 Elsevier||Keywords:||Light Detection and Ranging (LiDAR); Terrestrial laser scanning; Masonry buildings; Geometric modelling; Computational modelling; Finite element modelling||DOI:||10.1016/j.cad.2014.03.001||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Earth Institute Research Collection|
Civil Engineering Research Collection
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