2019
DOI: 10.1016/j.autcon.2019.01.002
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Non-contact sensing based geometric quality assessment of buildings and civil structures: A review

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Cited by 65 publications
(28 citation statements)
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“…However, these two traditional flatness assessment methods are performed manually or by contact-type devices, which are time-consuming, labor-intensive and prone to human errors. As an alternative, terrestrial laser scanner (TLS) has been widely used and considered as a promising 3D data acquisition technology for concrete surface inspection because of the nature of noncontact and accurate measurement [9][10][11][12][13][14][15][16][17]. Nevertheless, there are still limitations according to previous studies in order to ensure the feasibility of the TLS-based surface flatness inspection.…”
Section: Introductionmentioning
confidence: 99%
“…However, these two traditional flatness assessment methods are performed manually or by contact-type devices, which are time-consuming, labor-intensive and prone to human errors. As an alternative, terrestrial laser scanner (TLS) has been widely used and considered as a promising 3D data acquisition technology for concrete surface inspection because of the nature of noncontact and accurate measurement [9][10][11][12][13][14][15][16][17]. Nevertheless, there are still limitations according to previous studies in order to ensure the feasibility of the TLS-based surface flatness inspection.…”
Section: Introductionmentioning
confidence: 99%
“…This demonstrates the significance of implementing intelligent asset documentation and structural health monitoring (SHM) approaches for existing built assets. Laser scanning has been widely used to document and monitor existing conditions of real-world assets in the form of point clouds [3,4]. A point cloud is an unstructured low-level digital representation, which by itself does not contain any meaningful information of the documented asset.…”
Section: Introductionmentioning
confidence: 99%
“…Wang and Rezazadeh Azar, 2019), sensing systems (e.g. Kim et al, 2019) and Unmanned Aerial Vehicles (UAVs) (e.g. Zhou and Gheisari, 2018).…”
Section: Introductionmentioning
confidence: 99%