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Book Chapter

Quantifying the Confidence in Models Outputted by Scan-To-BIM Processes

  • Shirin Malihi
  • Frederic Bosche
  • Martin Bueno Esposito

3D spatial data is increasingly employed to generate Building Information Models (BIMs) by extension digital twins for various applications in the architecture, engineering, and construction (AEC) sector such as project monitoring, engineering analyses, retrofit planning, etc. The outputted models of Scan-to-BIM processes should satisfy pre-defined levels of quality. In the case of emerging automated Scan-to-BIM solutions, users however currently need to check all generated geometry manually, which is time-consuming. What would help users is if the automated systems could also provide a level of confidence in the detection and modelling of each element. In this paper three generic indicators are defined for analysing the reliability of the generated 3D models: Icoverage estimates the portion of the surface of the modelled element that can be explained by the input point cloud. Idistance defines the closeness of the generated element models to the input point cloud. The confidence of the generated 3D local models can be computed by combining the two aforementioned indices. The proposed indicators are assessed using actual examples and comparisons are conducted between automatically generated 3D BIM models and 3D models generated manually by a BIM modeler

  • Keywords:
  • BIM,
  • point cloud,
  • confidence,
  • indoor modelling,
  • wall,
  • digital twin,
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Shirin Malihi

University of Edinburgh, United Kingdom - ORCID: 0000-0003-1499-8791

Frederic Bosche

University of Edinburgh, United Kingdom - ORCID: 0000-0002-4064-8982

Martin Bueno Esposito

University of Edinburgh, United Kingdom

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  • Publication Year: 2023
  • Pages: 1137-1146

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  • Publication Year: 2023

Chapter Information

Chapter Title

Quantifying the Confidence in Models Outputted by Scan-To-BIM Processes

Authors

Shirin Malihi, Frederic Bosche, Martin Bueno Esposito

DOI

10.36253/979-12-215-0289-3.113

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry

Editors

Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/979-12-215-0289-3

eISBN (pdf)

979-12-215-0289-3

eISBN (xml)

979-12-215-0257-2

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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