A novel methodology for the path alignment of visual SLAM in indoor construction inspection

annif.suggestionsindoor air|Three-dimensional imaging|system cameras|artificial intelligence|quality|ventilation|air conditioning|machine learning|building inspection|gas heating|enen
annif.suggestions.linkshttp://www.yso.fi/onto/yso/p5433|http://www.yso.fi/onto/yso/p26739|http://www.yso.fi/onto/yso/p20117|http://www.yso.fi/onto/yso/p2616|http://www.yso.fi/onto/yso/p5029|http://www.yso.fi/onto/yso/p5431|http://www.yso.fi/onto/yso/p6628|http://www.yso.fi/onto/yso/p21846|http://www.yso.fi/onto/yso/p13110|http://www.yso.fi/onto/yso/p23899en
dc.contributor.authorLu, Tao
dc.contributor.authorTervola, Sonja
dc.contributor.authorLü, Xiaoshu
dc.contributor.authorKibert, Charles J.
dc.contributor.authorZhang, Qunli
dc.contributor.authorLi, Tong
dc.contributor.authorYao, Zhitong
dc.contributor.departmentVebic-
dc.contributor.facultyfi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations|-
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2021-05-03T06:32:59Z
dc.date.accessioned2025-06-25T12:57:23Z
dc.date.available2023-07-01T22:00:16Z
dc.date.issued2021-07-01
dc.description.abstractPath alignment is the process of mapping an indoor construction inspection path reconstructed by a visual SLAM system onto a 2D map with user interaction required to pinpoint at least two common tie points. In practice, more points are often needed due to path distortions and linear transformations, potentially resulting in reduced productivity. This paper proposes a methodology that combines two novel algorithms for the path alignment: (1) PCA_STAN_ALGO applies principal component analysis to remove path distortions caused by the xz plane of a camera coordinate system not being parallel to the floor plane; and (2) GRPX_TRANS utilizes a graphical user interface to facilitate the path alignment. The proposed methodology enables the users to utilize just two tie points for successful path alignment. An experimental study showed that applying both PCA_STAN_ALGO and GRPX_TRANS saved about 50% in time compared to using only GRPX_TRANS, a result of needing minimal moving points.-
dc.description.notification©2021 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.description.reviewstatusfi=vertaisarvioitu|en=peerReviewed|-
dc.embargo.lift2023-07-01
dc.embargo.terms2023-07-01
dc.format.bitstreamtrue
dc.format.contentfi=kokoteksti|en=fulltext|-
dc.identifier.olddbid14311
dc.identifier.oldhandle10024/12469
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/1219
dc.identifier.urnURN:NBN:fi-fe2021050328374-
dc.language.isoeng-
dc.publisherElsevier-
dc.relation.doi10.1016/j.autcon.2021.103723-
dc.relation.ispartofjournalAutomation in Construction-
dc.relation.issn1872-7891-
dc.relation.issn0926-5805-
dc.relation.urlhttps://doi.org/10.1016/j.autcon.2021.103723-
dc.relation.volume127-
dc.rightsCC BY-NC-ND 4.0-
dc.source.identifierhttps://osuva.uwasa.fi/handle/10024/12469
dc.subjectPrincipal component analysis-
dc.subjectSimultaneous localization and mapping-
dc.subjectPath alignment-
dc.subjectAffine transformation-
dc.subjectPath distortion-
dc.subject2-Point Scheme-
dc.subject.disciplinefi=Energiatekniikka|en=Energy Technology|-
dc.titleA novel methodology for the path alignment of visual SLAM in indoor construction inspection-
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|en=A1 Peer-reviewed original journal article|sv=A1 Originalartikel i en vetenskaplig tidskrift|-
dc.type.publicationarticle-
dc.type.versionacceptedVersion-

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