A multiple camera position approach for accurate displacement measurement using computer vision
dc.contributor.author | Kromanis, R | |
dc.contributor.author | Kripakaran, P | |
dc.date.accessioned | 2021-03-02T08:49:51Z | |
dc.date.issued | 2021-03-01 | |
dc.description.abstract | Engineers can today capture high-resolution video recordings of bridge movements during routine visual inspections using modern smartphones and compile a historical archive over time. However the recordings are likely to be from cameras of different makes, placed at varying positions. Previous studies have not explored whether such recordings can support monitoring of bridge condition. This is the focus of this study. It evaluates the feasibility of an imaging approach for condition assessment that is independent of the camera positions used for individual recordings. The proposed approach relies on the premise that spatial relationships between multiple structural features remain the same even when images of the structure are taken from different angles or camera positions. It employs coordinate transformation techniques, which use the identified features, to compute structural displacements from images. The proposed approach is applied to a laboratory beam, subject to static loading under various damage scenarios and recorded using multiple cameras in a range of positions. Results show that the response computed from the recordings are accurate, with 5% discrepancy in computed displacements relative to the mean. The approach is also demonstrated on a full-scale pedestrian suspension bridge. Vertical bridge movements, induced by forced excitations, are collected with two smartphones and an action camera. Analysis of the images shows that the measurement discrepancy in computed displacements is 6%. | en_GB |
dc.description.sponsorship | Sustainable Futures, Nottingham Trent University | en_GB |
dc.identifier.citation | Published online 1 March 2021 | en_GB |
dc.identifier.doi | 10.1007/s13349-021-00473-0 | |
dc.identifier.uri | http://hdl.handle.net/10871/124972 | |
dc.language.iso | en | en_GB |
dc.publisher | Springer | en_GB |
dc.rights | © The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | Computer vision | |
dc.subject | Image processing | |
dc.subject | Displacement | |
dc.subject | Signal processing | |
dc.subject | Condition assessment | |
dc.subject | Damage detection | |
dc.subject | Laboratory beam | |
dc.subject | Suspension bridge | |
dc.title | A multiple camera position approach for accurate displacement measurement using computer vision | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2021-03-02T08:49:51Z | |
dc.identifier.issn | 2190-5479 | |
dc.description | This is the final version. Available on open access from Springer via the DOI in this record | en_GB |
dc.identifier.journal | Journal of Civil Structural Health Monitoring | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2021-02-09 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2021-02-09 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2021-03-01T22:38:48Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2021-03-11T10:44:44Z | |
refterms.panel | B | en_GB |
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Except where otherwise noted, this item's licence is described as © The Author(s) 2021. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/