Detection, Modeling, and Classification of Moldings for Automated Reverse Engineering of Buildings from 3D Data

Enrique Valero Rodriguez, Antonio Adan Oliver, Daniel Huber, and Carlos Cerrada
International Symposium on Automation and Robotics in Construction (ISARC), June, 2011.


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Abstract
Laser scanner data is increasingly being used for the detailed reverse engineering of buildings. This process is currently primarily manual, but recent research has shown that basic structures, such as walls, ceilings, floors, doorways, and windows, can be detected and modeled automatically. Building on this previous research, we focus on the modeling of those linear moldings that typically surround doorways, windows, and divide ceilings from walls and walls from floors. These structures may be secondary and merely ornamental, but many projects nevertheless require that they be modeled. Moldings can be difficult to model manually owing to missing data caused by occlusions or to the ambiguity caused by low data density. Our molding modeling approach consists of two steps: 1) estimating the path of the molding; and 2) estimating the shape of the molding profile. In the first step, we iteratively update the molding’s line of extrusion by optimizing the similarity of cross-sections sampled along the path, thereby compensating for imperfections in the initial orientation estimate. In the second step, a unified profile is extracted using data from the entire length of the molding, which allows for partial missing data from occlusions. The profile is then characterized by a specific shape descriptor. Finally, a KNN algorithm classifies the molding into a database which has been constructed with profiles originating from various molding manufacturers. We demonstrate the method using real 3D laser scanner data of various types of moldings, both simple and complex.

Keywords
BIM, moldings, laser scanner data, segmentation, modeling

Notes
Associated Lab(s) / Group(s): 3D Vision and Intelligent Systems Group
Associated Project(s): Automated Reverse Engineering of Buildings and Detailed Wall Modeling in Cluttered Environments
Note: This research has been carried out under contract with the Spanish CICYT through the DPI-2008-05444 and DPI2009-14024-C02 projects. It also belongs to the activities carried out in the frame of the RoboCity2030-II excellence research network of the CAM (ref. S2009/DPI-1559). This material is based upon work supported, in part, by the National Science Foundation under Grant No. 0856558. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Text Reference
Enrique Valero Rodriguez, Antonio Adan Oliver, Daniel Huber, and Carlos Cerrada, "Detection, Modeling, and Classification of Moldings for Automated Reverse Engineering of Buildings from 3D Data," International Symposium on Automation and Robotics in Construction (ISARC), June, 2011.

BibTeX Reference
@inproceedings{Valero_Rodriguez_2011_6860,
   author = "Enrique {Valero Rodriguez} and Antonio {Adan Oliver} and Daniel Huber and Carlos Cerrada",
   title = "Detection, Modeling, and Classification of Moldings for Automated Reverse Engineering of Buildings from 3D Data",
   booktitle = "International Symposium on Automation and Robotics in Construction (ISARC)",
   month = "June",
   year = "2011",
   Notes = "This research has been carried out under contract with the Spanish CICYT through the DPI-2008-05444 and DPI2009-14024-C02 projects. It also belongs to the activities carried out in the frame of the RoboCity2030-II excellence research network of the CAM (ref. S2009/DPI-1559). This material is based upon work supported, in part, by the National Science Foundation under Grant No. 0856558. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. "
}