From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings
ICube Laboratory, Photogrammetry and Geomatics Group, National Institute of Applied Sciences (INSA),24 Boulevard de la Victoire, 67084 Strasbourg CEDEX, France
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Appl. Sci. 2017, 7(10), 1030; https://doi.org/10.3390/app7101030
Received: 13 September 2017 / Revised: 1 October 2017 / Accepted: 2 October 2017 / Published: 12 October 2017
(This article belongs to the Special Issue Laser Scanning)
The creation of as-built Building Information Models requires the acquisition of the as-is state of existing buildings. Laser scanners are widely used to achieve this goal since they permit to collect information about object geometry in form of point clouds and provide a large amount of accurate data in a very fast way and with a high level of details. Unfortunately, the scan-to-BIM (Building Information Model) process remains currently largely a manual process which is time consuming and error-prone. In this paper, a semi-automatic approach is presented for the 3D reconstruction of indoors of existing buildings from point clouds. Several segmentations are performed so that point clouds corresponding to grounds, ceilings and walls are extracted. Based on these point clouds, walls and slabs of buildings are reconstructed and described in the IFC format in order to be integrated into BIM software. The assessment of the approach is proposed thanks to two datasets. The evaluation items are the degree of automation, the transferability of the approach and the geometric quality of results of the 3D reconstruction. Additionally, quality indexes are introduced to inspect the results in order to be able to detect potential errors of reconstruction.
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Keywords:
as-built BIM; building indoor environments; Terrestrial Laser Scanning; point clouds; 3D reconstruction; assessment; automation; transferability; quality
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MDPI and ACS Style
Macher, H.; Landes, T.; Grussenmeyer, P. From Point Clouds to Building Information Models: 3D Semi-Automatic Reconstruction of Indoors of Existing Buildings. Appl. Sci. 2017, 7, 1030.
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