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Remote Sens. 2015, 7(9), 11753-11775; doi:10.3390/rs70911753

Automatic Geometry Generation from Point Clouds for BIM

Civil, Environmental & Geomatic Engineering, University College London, Gower Street, London WC1E 6BT, UK
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Academic Editors: Fabio Remondino, Diego Gonzalez-Aguilera, Henrique Lorenzo, Norman Kerle and Prasad S. Thenkabail
Received: 21 June 2015 / Revised: 3 September 2015 / Accepted: 8 September 2015 / Published: 14 September 2015
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Abstract

The need for better 3D documentation of the built environment has come to the fore in recent years, led primarily by city modelling at the large scale and Building Information Modelling (BIM) at the smaller scale. Automation is seen as desirable as it removes the time-consuming and therefore costly amount of human intervention in the process of model generation. BIM is the focus of this paper as not only is there a commercial need, as will be shown by the number of commercial solutions, but also wide research interest due to the aspiration of automated 3D models from both Geomatics and Computer Science communities. The aim is to go beyond the current labour-intensive tracing of the point cloud to an automated process that produces geometry that is both open and more verifiable. This work investigates what can be achieved today with automation through both literature review and by proposing a novel point cloud processing process. We present an automated workflow for the generation of BIM data from 3D point clouds. We also present quality indicators for reconstructed geometry elements and a framework in which to assess the quality of the reconstructed geometry against a reference. View Full-Text
Keywords: indoor; automated; 3D Modelling; terrestrial laser scanning; mobile laser scanning; segmentation; reconstruction; BIM indoor; automated; 3D Modelling; terrestrial laser scanning; mobile laser scanning; segmentation; reconstruction; BIM
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Thomson, C.; Boehm, J. Automatic Geometry Generation from Point Clouds for BIM. Remote Sens. 2015, 7, 11753-11775.

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