Automated digital modeling of existing buildings: A review of visual object recognition methods

Digital building representations enable and promote new forms of simulation, automation, and information sharing. However, creating and maintaining these representations is prohibitively expensive. In an effort to make the adoption of this technology easier, researchers have been automating the digi...

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Bibliographic Details
Published in:Automation in construction 2020-05, Vol.113, p.103131, Article 103131
Main Authors: Czerniawski, Thomas, Leite, Fernanda
Format: Article
Language:English
Subjects:
3D reconstruction
Algorithms
As-built
Automation
BIM
Building components
Building information modeling
Buildings
Ceilings
Computer simulation
Computer vision
Digital building representation
Digitization
Laser scanning
Modelling
Object recognition
Performance evaluation
Representations
Review article
Semantics
Taxonomy
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Summary:Digital building representations enable and promote new forms of simulation, automation, and information sharing. However, creating and maintaining these representations is prohibitively expensive. In an effort to make the adoption of this technology easier, researchers have been automating the digital modeling of existing buildings by applying reality capture devices and computer vision algorithms. This article is a summary of the efforts of the past ten years, with a particular focus on object recognition methods. We rectify three limitations of existing review articles by describing the general structure and variations of object recognition systems and performing an extensive and quantitative comparative performance evaluation. The coverage of building component classes (i.e. semantic coverage) and recognition performances are reported in-depth and framed using a building taxonomy. Research programs demonstrate sparse semantic coverage with a clear bias towards recognizing floor, wall, ceiling, door, and window classes. Comprehensive semantic coverage of building infrastructure will require a radical scaling and diversification of efforts. •Review of building related object recognition methods•Coverage of building component classes reported using a building taxonomy•Object recognition performances summarized and reported•A simple conceptualization of object recognition systems presented
ISSN:0926-5805
1872-7891
DOI:10.1016/j.autcon.2020.103131