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Automatic Reconstruction of As-Built Building Information Models from Laser-Scanned Point Clouds: A Review of Related Techniques

Published

Author(s)

Robert R. Lipman, Pingbo Tang, Daniel Huber, Burcu Akinci, Alan M. Lytle

Abstract

Building information models (BIMs) are maturing as a new paradigm for storing and exchanging knowledge about a facility. BIMs constructed from a CAD model do not generally capture details of a facility as it was actually built. Laser scanners can be used to capture dense 3D measurements of a facility’s as-built condition and the resulting point cloud can be manually processed to create an as-built BIM – a time-consuming, subjective, and error-prone process that could benefit significantly from automation. This article surveys techniques developed in civil engineering and computer science that can be utilized to automate the process of creating as-built BIMs. We sub-divide the overall process into three core operations: geometric modeling, object recognition, and object relationship modeling. We survey the state-of-the-art methods for each operation and discuss their potential application to automated as-built BIM creation. We also outline the main methods used by these algorithms for representing knowledge about shape, identity, and relationships. In addition, we formalize the possible variations of the overall as-built BIM creation problem and outline performance evaluation measures for comparing as-built BIM creation algorithms and tracking progress of the field. Finally, we identify and discuss technology gaps that need to be addressed in future research.
Citation
Journal of Computing in Civil Engineering
Volume
19
Issue
7

Keywords

Building information models, building reconstruction, laser scanners, object recognition, geometric modeling, relationship modeling, shape representation

Citation

Lipman, R. , Tang, P. , Huber, D. , Akinci, B. and Lytle, A. (2010), Automatic Reconstruction of As-Built Building Information Models from Laser-Scanned Point Clouds: A Review of Related Techniques, Journal of Computing in Civil Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=904018 (Accessed April 17, 2024)
Created November 1, 2010, Updated February 19, 2017