Proceedings ArticleDOI
The ASDMCon Project: The Challenge of Detecting Defects on Construction Sites
Kui Yue,Daniel Huber,Burcu Akinci,Ramesh Krishnamurti +3 more
- pp 1048-1055
TLDR
An overview of the ASDMCon project, its 4D visualization environment, and the 3D segmentation and recognition strategies that are being employed to automate defect detection are presented.Abstract:
Techniques for three dimensional (3D) imaging and analysis of as-built conditions of buildings are gaining acceptance in the Architecture, Engineering, and Construction (AEC) community. Early detection of defects on construction sites is one domain where these techniques have the potential to revolutionize an industry, since construction defects can consume a significant portion of a project?s budget. The ASDMCon project is developing methods to aid site managers in detecting and managing construction defects using 3D imaging and other advanced sensor technologies. This paper presents an overview of the project, its 4D visualization environment, and the 3D segmentation and recognition strategies that are being employed to automate defect detection.read more
Citations
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Building Information Modeling (BIM) for existing buildings — Literature review and future needs
TL;DR: Results show scarce BIM implementation in existing buildings yet, due to challenges of (1) high modeling/conversion effort from captured building data into semantic BIM objects, (2) updating of information in BIM and (3) handling of uncertain data, objects and relations in B IM occurring inexisting buildings.
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Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques
TL;DR: This article surveys techniques developed in civil engineering and computer science that can be utilized to automate the process of creating as-built BIMs and outlines the main methods used by these algorithms for representing knowledge about shape, identity, and relationships.
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Automatic Reconstruction of As-Built Building Information Models from Laser-Scanned Point Clouds: A Review of Related Techniques | NIST
TL;DR: A survey of state-of-the-art methods for automated as-built BIM creation can be found in this article, where the main methods used by these algorithms for representing knowledge about shape, identity, and relationships.
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Automatic Creation of Semantically Rich 3D Building Models from Laser Scanner Data
TL;DR: A method to automatically convert the raw 3D point data from a laser scanner positioned at multiple locations throughout a facility into a compact, semantically rich information model that is capable of identifying and modeling the main visible structural components of an indoor environment despite the presence of significant clutter and occlusion.
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Deviation analysis method for the assessment of the quality of the as-is Building Information Models generated from point cloud data
TL;DR: The research described in this paper provides a taxonomy for patterns of deviations and sources of errors and demonstrates that it is possible to identify the source, magnitude, and nature of errors by analyzing the deviation patterns.
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