/Automated Reverse Engineering of Buildings

Automated Reverse Engineering of Buildings

Portrait of Automated Reverse Engineering of Buildings
Heads: Daniel Huber and Burcu Akinci
Contact: Daniel Huber
Last Project Publication Year: 2013

Laser scanners have proven to be an effective method for measuring the 3D shape of facilities, such as buildings and process plants. The results of scanning can be used to model the as-built or as-is conditions of a facility, which may be very different from the original design plans. Unfortunately, laser scanners produce data in the form of a set of points (known as a point cloud), but people using the data need higher-level information like the identity, location, and shape of walls, doors, and windows. In practice this high-level information is usually represented as a building information model (BIM). Our research is exploring methods to automatically create BIMs from point clouds and to address specific challenges in representing such “as-built” BIMs. Our modeling work utilizes techniques from the fields of computer vision and machine learning to automatically segment, model, and recognize the core components of a building’s envelope, including walls, floors, ceilings, doors, and windows. Our representation work is addressing problems specific to as-built BIMs. One such problem is the representation of occluded regions. Normally, when a room is scanned, some parts of the walls will be blocked by furniture or other obstructions. When the as-built BIM is created, the modeled walls are extended to fill in these occluded regions. However, the representation makes no distinction between regions that were filled in and regions that were measured directly. A downstream stakeholder may then make poor decisions based on incorrect assumptions about the accuracy of the data in these originally occluded regions.



Currently, we are investigating several different aspects of the problem of automatic reverse engineering of buildings:



This project is funded in part, by the National Science Foundation (CMMI-0856558) and by the Pennsylvania Infrastructure Technology Alliance.

Displaying 8 Publications
Automatic Creation of Semantically Rich 3D Building Models from Laser Scanner Data
Xuehan Xiong, Antonio Adan Oliver, Burcu Akinci and Daniel Huber

Journal Article, Carnegie Mellon University, Automation in Construction, Vol. 31, pp. 325-337, May, 2013
Automatic Creation of Semantically Rich 3D Building Models from Laser Scanner Data
Antonio Adan Oliver, Xuehan Xiong, Burcu Akinci and Daniel Huber

Conference Paper, Proceedings of the International Symposium on Automation and Robotics in Construction (ISARC), June, 2011
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

Conference Paper, International Symposium on Automation and Robotics in Construction (ISARC), June, 2011
Representation Requirements of As-Is Building Information Models Generated from Laser Scanned Point Cloud Data
Engin Anil, Burcu Akinci and Daniel Huber

Conference Paper, Proceedings of the International Symposium on Automation and Robotics in Construction, June, 2011
3D Reconstruction of Interior Wall Surfaces Under Occlusion and Clutter
Antonio Adan Oliver and Daniel Huber

Conference Paper, Proceedings of 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), May, 2011
Methods for Automatically Modeling and Representing As-built Building Information Models
Daniel Huber, Burcu Akinci, Antonio Adan Oliver, Engin Anil, Brian E. Okorn and Xuehan Xiong

Conference Paper, Proceedings of the NSF CMMI Research Innovation Conference, January, 2011
Toward Automated Modeling of Floor Plans
Brian E. Okorn, Xuehan Xiong, Burcu Akinci and Daniel Huber

Conference Paper, Proceedings of the Symposium on 3D Data Processing, Visualization and Transmission, May, 2010
Using Laser Scanners for Modeling and Analysis in Architecture, Engineering, and Construction
Daniel Huber, Burcu Akinci, Pingbo Tang, Antonio Adan Oliver, Brian E. Okorn and Xuehan Xiong

Conference Paper, Proceedings of the Conference on Information Sciences and Systems (CISS), March, 2010

Past Project People

  • Xuehan Xiong
  • Enrique Valero Rodriguez
  • Siddharth Soundararajan
  • Emiliano Perez Hernandez
  • Engin Anil
  • Antonio Adan Oliver
2017-09-13T10:40:50+00:00