Assessment of Quality of As-is Building Information Models Generated from Point Clouds Using Deviation Analysis

Engin Anil, Pingbo Tang, Burcu Akinci, and Daniel Huber
Proceedings of the SPIE Vol. 7864A, Electronics Imaging Science and Technology Conference (IS&T), 3D Imaging Metrology, January, 2011.


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Abstract
Three dimensional (3D) imaging sensors, such as laser scanners, are being used to create building information models (BIMs) of the as-is conditions of buildings and other facilities. Quality assurance (QA) needs to be conducted to ensure that the models accurately depict the as-is conditions. We propose a new approach for QA that analyzes patterns in the raw 3D data and compares the 3D data with the as-is BIM geometry to identify potential errors in the model. This “deviation analysis” approach to QA enables users to analyze the regions with significant differences between the 3D data and the reconstructed model or between the 3D data of individual laser scans. This method can help identify the sources of errors and does not require additional physical access to the facility. To show the approach’s potential effectiveness, we conducted case studies of several professionally conducted as-is BIM projects. We compared the deviation analysis method to an alternative method – the physical measurement approach – in terms of errors detected and coverage. We also conducted a survey and evaluation of commercial software with relevant capabilities and identified technology gaps that need to be addressed to fully exploit the deviation analysis approach.

Keywords
Building Information Model, As-is, As-built, Quality Assessment, Laser Scanning, Deviation Analysis Method, Physical Measurement Method

Notes
Associated Lab(s) / Group(s): 3D Vision and Intelligent Systems Group
Associated Project(s): Quality Assessment of As-built Building Information Models using Deviation Analysis
Note: This material is based upon work supported by the U.S. General Services Administration under Grant No. GS00P09CYP0321. We thank Geraldine Cheok and NIST for making their research data available to us.

Text Reference
Engin Anil, Pingbo Tang, Burcu Akinci, and Daniel Huber, "Assessment of Quality of As-is Building Information Models Generated from Point Clouds Using Deviation Analysis," Proceedings of the SPIE Vol. 7864A, Electronics Imaging Science and Technology Conference (IS&T), 3D Imaging Metrology, January, 2011.

BibTeX Reference
@inproceedings{Anil_2011_6862,
   author = "Engin Anil and Pingbo Tang and Burcu Akinci and Daniel Huber",
   title = "Assessment of Quality of As-is Building Information Models Generated from Point Clouds Using Deviation Analysis",
   booktitle = "Proceedings of the SPIE Vol. 7864A, Electronics Imaging Science and Technology Conference (IS&T), 3D Imaging Metrology",
   month = "January",
   year = "2011",
   Notes = "This material is based upon work supported by the U.S. General Services Administration under Grant No. GS00P09CYP0321. We thank Geraldine Cheok and NIST for making their research data available to us."
}