TY - JOUR
T1 - Automatic reconstruction of as-built building information models from laser-scanned point clouds
T2 - A review of related techniques
AU - Tang, Pingbo
AU - Huber, Daniel
AU - Akinci, Burcu
AU - Lipman, Robert
AU - Lytle, Alan
N1 - Funding Information:
This research was supported, in part, by the National Institute of Standards and Technology (NIST) under grant 60NANB7D6156 , by the General Services Administration (GSA) under grant GS00P07CYP0233 , and by the National Science Foundation under Grant No. 0856558 . Their support is gratefully acknowledged. Any opinions, findings and conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NIST or the National Science Foundation. Mention of trade names in this article does not imply endorsement by Carnegie Mellon University or NIST.
PY - 2010/11
Y1 - 2010/11
N2 - 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.
AB - 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.
KW - Building information models
KW - Building reconstruction
KW - Geometric modeling
KW - Laser scanners
KW - Object recognition
KW - Relationship modeling
KW - Shape representation
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U2 - 10.1016/j.autcon.2010.06.007
DO - 10.1016/j.autcon.2010.06.007
M3 - Review article
AN - SCOPUS:77956619234
SN - 0926-5805
VL - 19
SP - 829
EP - 843
JO - Automation in Construction
JF - Automation in Construction
IS - 7
ER -