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Table 3 UAV-driven methods for civil infrastructure condition assessment

From: Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works

Application Data Analytics Literature
Structural damage assessment • Image-based 3D reconstruction
• Image segmentation and object classification for damage feature extraction
(Fernandez Galarreta et al. 2015); (Kerle 2999)
• Machine learning-based classification of damaged buildings using feature sets obtained from feature extraction and transformation in images (Ye et al. 2014)
Infrastructure inspection • Image-based 3D reconstruction
• Geometrical feature recognition and classification for planning laser scans
(Oskouie et al. 2015)
• Creating comprehensive, high-resolution, semantically rich 3D models of infrastructure (ARIA (Team 2015))
Urban monitoring • Image-based 3D reconstruction for inferring geometric characteristics of buildings
• Segmentation using geometric features obtained from 3D point cloud along with radiometric features
(Vetrivel 2999)
• 4D image registration for change detection
• Orthophoto mapping and multi-primitive image segmentation for object-based decision tree analysis
(Qin 2014)
Road Assessment • Image-based 3D reconstruction • Feature extraction through image filtering (Dobson et al. 2013)
• Analyzing the size and dimension of road surface distresses
• Feature extraction and Orthophoto mapping
(Zhang & Elaksher 2012)
Surveying • Image-based 3D reconstruction
• Surveying post-disaster sites
(Yamamoto et al. 2014)
Solar power plant investigations • Leveraging aerial triangulation using ImageStation Automatic Triangulation (ISAT) software (Matsuoka et al. 2012)
Geo-hazard investigations • Orthophoto mapping and visual interpretation to inspect geologic hazards along oil and gas pipelines (Gao et al. 2011)