Automatic Generation of Semantically Rich As-Built Building Information Models Using 2D Images: A Derivative-Free Optimization Approach
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- @Article{Fan_Xue:CACIE,
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author = "Fan Xue and Weisheng Lu and Ke Chen",
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title = "Automatic Generation of Semantically Rich As-Built
Building Information Models Using {2D} Images: A
Derivative-Free Optimization Approach",
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journal = "Computer-Aided Civil and Infrastructure Engineering",
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year = "2018",
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volume = "33",
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number = "11",
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pages = "926--942",
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month = nov,
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keywords = "genetic algorithms, genetic programming",
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ISSN = "1467-8667",
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URL = "https://onlinelibrary.wiley.com/doi/abs/10.1111/mice.12378",
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DOI = "doi:10.1111/mice.12378",
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size = "16 pages",
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abstract = "Over the past decade a considerable number of studies
have focused on generating semantically rich as-built
building information models (BIMs). However, the
prevailing methods rely on laborious manual
segmentation or automatic but error-prone segmentation.
In addition, the methods failed to make good use of
existing semantics sources. This article presents 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. The
semantics of the BIMs are subsequently enriched by
linking the fitted components with existing semantics
sources. The approach was prototyped in two experiments
using an outdoor and an indoor case, respectively. The
results showed that in the outdoor case 12 out of 13
BIM components were correctly generated within 1.5
hours, and in the indoor case all target BIM components
were correctly generated with a root-mean-square
deviation (RMSD) of 3.9cm in about 2.5 hours. The main
computational novelties of this study are: (1) to
translate the automatic as-built BIM generation from 2D
images as an optimization problem; (2) to develop an
effective and segmentation-free approach that is
fundamentally different from prevailing methods; and
(3) to exploit online open BIM component information
for semantic enrichment, which, to a certain extent,
alleviates the dilemma between information inadequacy
and information overload in BIM development.",
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notes = "Entered for 2018 HUMIES",
- }
Genetic Programming entries for
Fan Xue
Wilson W S Lu
Ke Chen
Citations