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Plane-based robust registration of a building scan with its BIM

Noaman Akbar Sheik (UGent) , Greet Deruyter (UGent) and Peter Veelaert (UGent)
(2022) REMOTE SENSING. 14(9).
Author
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Abstract
The registration of as-built and as-planned building models is a pre-requisite in automated construction progress monitoring. Due to the numerous challenges associated with the registration process, it is still performed manually. This research study proposes an automated registration method that aligns the as-built point cloud of a building to its as-planned model using its planar features. The proposed method extracts and processes all the plane segments from both the as-built and the as-planned models, then—for both models—groups parallel plane segments into clusters and subsequently determines the directions of these clusters to eventually determine a range of possible rotation matrices. These rotation matrices are then evaluated through a computational framework based on a postulation concerning the matching of plane segments from both models. This framework measures the correspondence between the plane segments through a matching cost algorithm, thus identifying matching plane segments, which ultimately leads to the determination of the transformation parameters to correctly register the as-built point cloud to its as-planned model. The proposed method was validated by applying it to a range of different datasets. The results proved the robustness of the method both in terms of accuracy and efficiency. In addition, the method also proved its correct support for the registration of buildings under construction, which are inherently incomplete, bringing research a step closer to practical and effective construction progress monitoring.
Keywords
BIM, point cloud, registration, buildings, automated, PAIRWISE COARSE REGISTRATION, 3D POINT CLOUDS, AUTOMATIC REGISTRATION, PROGRESS MEASUREMENT, CONGRUENT SETS, CAD MODEL, RANSAC, SEGMENTATION, FEATURES, OBJECTS

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Citation

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MLA
Sheik, Noaman Akbar, et al. “Plane-Based Robust Registration of a Building Scan with Its BIM.” REMOTE SENSING, vol. 14, no. 9, 2022, doi:10.3390/rs14091979.
APA
Sheik, N. A., Deruyter, G., & Veelaert, P. (2022). Plane-based robust registration of a building scan with its BIM. REMOTE SENSING, 14(9). https://doi.org/10.3390/rs14091979
Chicago author-date
Sheik, Noaman Akbar, Greet Deruyter, and Peter Veelaert. 2022. “Plane-Based Robust Registration of a Building Scan with Its BIM.” REMOTE SENSING 14 (9). https://doi.org/10.3390/rs14091979.
Chicago author-date (all authors)
Sheik, Noaman Akbar, Greet Deruyter, and Peter Veelaert. 2022. “Plane-Based Robust Registration of a Building Scan with Its BIM.” REMOTE SENSING 14 (9). doi:10.3390/rs14091979.
Vancouver
1.
Sheik NA, Deruyter G, Veelaert P. Plane-based robust registration of a building scan with its BIM. REMOTE SENSING. 2022;14(9).
IEEE
[1]
N. A. Sheik, G. Deruyter, and P. Veelaert, “Plane-based robust registration of a building scan with its BIM,” REMOTE SENSING, vol. 14, no. 9, 2022.
@article{8755463,
  abstract     = {{The registration of as-built and as-planned building models is a pre-requisite in automated construction progress monitoring. Due to the numerous challenges associated with the registration process, it is still performed manually. This research study proposes an automated registration method that aligns the as-built point cloud of a building to its as-planned model using its planar features. The proposed method extracts and processes all the plane segments from both the as-built and the as-planned models, then—for both models—groups parallel plane segments into clusters and subsequently determines the directions of these clusters to eventually determine a range of possible rotation matrices. These rotation matrices are then evaluated through a computational framework based on a postulation concerning the matching of plane segments from both models. This framework measures the correspondence between the plane segments through a matching cost algorithm, thus identifying matching plane segments, which ultimately leads to the determination of the transformation parameters to correctly register the as-built point cloud to its as-planned model. The proposed method was validated by applying it to a range of different datasets. The results proved the robustness of the method both in terms of accuracy and efficiency. In addition, the method also proved its correct support for the registration of buildings under construction, which are inherently incomplete, bringing research a step closer to practical and effective construction progress monitoring.}},
  articleno    = {{1979}},
  author       = {{Sheik, Noaman Akbar and Deruyter, Greet and Veelaert, Peter}},
  issn         = {{2072-4292}},
  journal      = {{REMOTE SENSING}},
  keywords     = {{BIM,point cloud,registration,buildings,automated,PAIRWISE COARSE REGISTRATION,3D POINT CLOUDS,AUTOMATIC REGISTRATION,PROGRESS MEASUREMENT,CONGRUENT SETS,CAD MODEL,RANSAC,SEGMENTATION,FEATURES,OBJECTS}},
  language     = {{eng}},
  number       = {{9}},
  pages        = {{22}},
  title        = {{Plane-based robust registration of a building scan with its BIM}},
  url          = {{http://doi.org/10.3390/rs14091979}},
  volume       = {{14}},
  year         = {{2022}},
}
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