A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection

Ling Ma, Rafael Sacks, Reem Zeibak-Shini, Sagi Filin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The potential for automated construction quality inspection, construction progress tracking and post-earthquake damage assessment drives research in interpretation of remote sensing data and compilation of semantic models of buildings in different states. However, research efforts are often hampered by a lack of full-scale datasets. This is particularly the case for earthquake damage assessment research, where acquisition of scans is restricted by scarcity of access to post-earthquake sites. To solve this problem, we have developed a procedure for compiling digital specimens in both pre- and post-event states and for generating synthetic data equivalent to which would result from laser scanning in the field. The procedure is validated by comparing the physical and synthetic scans of a damaged beam. Interpretation of the beam damage from the synthetic data demonstrates the feasibility of using this procedure to replace physical specimens with digital models for experimentation and for other civil engineering applications.

LanguageEnglish
Title of host publicationComputing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering, (Austin, TX, 21-23 June 2015)
EditorsWilliam J. O'Brien, Simone Ponticelli
PublisherAmerican Society of Civil Engineers (ASCE)
Pages684-691
Number of pages8
ISBN (Electronic)9780784479247
Publication statusPublished - 2015
Externally publishedYes
Event2015 ASCE International Workshop on Computing in Civil Engineering - Austin, United States
Duration: 21 Jun 201523 Jun 2015
http://www.caee.utexas.edu/asce2015computing/ (Link to Conference Website)

Conference

Conference2015 ASCE International Workshop on Computing in Civil Engineering
Abbreviated titleIWCCE 2015
CountryUnited States
CityAustin
Period21/06/1523/06/15
Internet address

Fingerprint

Earthquakes
Civil engineering
Remote sensing
Inspection
Semantics
Scanning
Lasers

Cite this

Ma, L., Sacks, R., Zeibak-Shini, R., & Filin, S. (2015). A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection. In W. J. O'Brien, & S. Ponticelli (Eds.), Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering, (Austin, TX, 21-23 June 2015) (pp. 684-691). American Society of Civil Engineers (ASCE).
Ma, Ling ; Sacks, Rafael ; Zeibak-Shini, Reem ; Filin, Sagi. / A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection. Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering, (Austin, TX, 21-23 June 2015). editor / William J. O'Brien ; Simone Ponticelli. American Society of Civil Engineers (ASCE), 2015. pp. 684-691
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title = "A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection",
abstract = "The potential for automated construction quality inspection, construction progress tracking and post-earthquake damage assessment drives research in interpretation of remote sensing data and compilation of semantic models of buildings in different states. However, research efforts are often hampered by a lack of full-scale datasets. This is particularly the case for earthquake damage assessment research, where acquisition of scans is restricted by scarcity of access to post-earthquake sites. To solve this problem, we have developed a procedure for compiling digital specimens in both pre- and post-event states and for generating synthetic data equivalent to which would result from laser scanning in the field. The procedure is validated by comparing the physical and synthetic scans of a damaged beam. Interpretation of the beam damage from the synthetic data demonstrates the feasibility of using this procedure to replace physical specimens with digital models for experimentation and for other civil engineering applications.",
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Ma, L, Sacks, R, Zeibak-Shini, R & Filin, S 2015, A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection. in WJ O'Brien & S Ponticelli (eds), Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering, (Austin, TX, 21-23 June 2015). American Society of Civil Engineers (ASCE), pp. 684-691, 2015 ASCE International Workshop on Computing in Civil Engineering, Austin, United States, 21/06/15.

A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection. / Ma, Ling; Sacks, Rafael; Zeibak-Shini, Reem; Filin, Sagi.

Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering, (Austin, TX, 21-23 June 2015). ed. / William J. O'Brien; Simone Ponticelli. American Society of Civil Engineers (ASCE), 2015. p. 684-691.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection

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AU - Sacks, Rafael

AU - Zeibak-Shini, Reem

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AB - The potential for automated construction quality inspection, construction progress tracking and post-earthquake damage assessment drives research in interpretation of remote sensing data and compilation of semantic models of buildings in different states. However, research efforts are often hampered by a lack of full-scale datasets. This is particularly the case for earthquake damage assessment research, where acquisition of scans is restricted by scarcity of access to post-earthquake sites. To solve this problem, we have developed a procedure for compiling digital specimens in both pre- and post-event states and for generating synthetic data equivalent to which would result from laser scanning in the field. The procedure is validated by comparing the physical and synthetic scans of a damaged beam. Interpretation of the beam damage from the synthetic data demonstrates the feasibility of using this procedure to replace physical specimens with digital models for experimentation and for other civil engineering applications.

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M3 - Conference contribution

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Ma L, Sacks R, Zeibak-Shini R, Filin S. A Computational Procedure for Generating Specimens of BIM and Point Cloud Data for Building Change Detection. In O'Brien WJ, Ponticelli S, editors, Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering, (Austin, TX, 21-23 June 2015). American Society of Civil Engineers (ASCE). 2015. p. 684-691