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Journal ArticleDOI

Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques

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TLDR
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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This article is published in Automation in Construction.The article was published on 2010-11-01. It has received 789 citations till now. The article focuses on the topics: Information model & Computer Aided Design.

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Citations
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Fully automated generation of parametric BIM for MEP scenes based on terrestrial laser scanning data

TL;DR: The proposed technique could successfully transform laser scanning data of MEP scenes to as-built BIMs with sufficient accuracy for facility management purpose and was validated with point clouds acquired from three scenes in Hong Kong.
Journal ArticleDOI

Automatic Generation of Semantically Rich As‐Built Building Information Models Using 2D Images: A Derivative‐Free Optimization Approach

TL;DR: A novel segmentation‐free derivative‐free optimization (DFO) approach that translates the generation of as‐built BIMs from 2D images into an optimization problem of fitting BIM components regarding architectural and topological constraints and exploits online open BIM component information for semantic enrichment.
Journal ArticleDOI

A Review and Scientometric Analysis of Global Building Information Modeling (BIM) Research in the Architecture, Engineering and Construction (AEC) Industry

Ziwen Liu, +2 more
- 09 Jul 2019 - 
TL;DR: This study has identified the top productive and influential researchers, research institutes, regions/countries, subject categories and journals in the BIM field and distinguished 11 clusters of global BIM research into 3 stages, namely formulating stage, accelerating stage and transforming stage.
Journal ArticleDOI

Development of Kinematic 3D Laser Scanning System for Indoor Mapping and As-Built BIM Using Constrained SLAM

TL;DR: In the present study, kinematic scanning with and without constrained adjustment were comparatively evaluated in two test sites, and the results confirmed the effectiveness of the proposed system.
Journal ArticleDOI

Principal Axes Descriptor for Automated Construction-Equipment Classification from Point Clouds

TL;DR: A novel principal axes descriptor (PAD) for construction-equipment classification from point cloud data is introduced and machine learning methods such as k-nearest neighbors and support vector machine are employed to determine class membership among major construction-Equipment categories.
References
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Journal ArticleDOI

Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Journal ArticleDOI

A taxonomy and evaluation of dense two-frame stereo correspondence algorithms

TL;DR: This paper has designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms.
Journal ArticleDOI

Recognition-by-Components: A Theory of Human Image Understanding.

TL;DR: Recognition-by-components (RBC) provides a principled account of the heretofore undecided relation between the classic principles of perceptual organization and pattern recognition.
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The FERET evaluation methodology for face-recognition algorithms

TL;DR: Two of the most critical requirements in support of producing reliable face-recognition systems are a large database of facial images and a testing procedure to evaluate systems.
Proceedings ArticleDOI

A volumetric method for building complex models from range images

TL;DR: This paper presents a volumetric method for integrating range images that is able to integrate a large number of range images yielding seamless, high-detail models of up to 2.6 million triangles.
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