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UAV Photogrammetry-Based 3D Road Distress Detection
by
Li, Yunxin
, Tan, Yumin
in
Accuracy
/ Algorithms
/ Automation
/ Cameras
/ Condition monitoring
/ Detection
/ digital surface model
/ Dimensions
/ Efficiency
/ Image reconstruction
/ Lasers
/ Low cost
/ Maneuverability
/ Manoeuvrability
/ Methods
/ monitoring
/ pavements
/ Photogrammetry
/ point cloud
/ region growing algorithm
/ Rehabilitation
/ road distress detection
/ Road maintenance
/ roads
/ Roads & highways
/ Software
/ spatial data
/ Surveying
/ surveys
/ Three dimensional models
/ UAV
/ Unmanned aerial vehicles
/ Vehicles
2019
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UAV Photogrammetry-Based 3D Road Distress Detection
by
Li, Yunxin
, Tan, Yumin
in
Accuracy
/ Algorithms
/ Automation
/ Cameras
/ Condition monitoring
/ Detection
/ digital surface model
/ Dimensions
/ Efficiency
/ Image reconstruction
/ Lasers
/ Low cost
/ Maneuverability
/ Manoeuvrability
/ Methods
/ monitoring
/ pavements
/ Photogrammetry
/ point cloud
/ region growing algorithm
/ Rehabilitation
/ road distress detection
/ Road maintenance
/ roads
/ Roads & highways
/ Software
/ spatial data
/ Surveying
/ surveys
/ Three dimensional models
/ UAV
/ Unmanned aerial vehicles
/ Vehicles
2019
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Do you wish to request the book?
UAV Photogrammetry-Based 3D Road Distress Detection
by
Li, Yunxin
, Tan, Yumin
in
Accuracy
/ Algorithms
/ Automation
/ Cameras
/ Condition monitoring
/ Detection
/ digital surface model
/ Dimensions
/ Efficiency
/ Image reconstruction
/ Lasers
/ Low cost
/ Maneuverability
/ Manoeuvrability
/ Methods
/ monitoring
/ pavements
/ Photogrammetry
/ point cloud
/ region growing algorithm
/ Rehabilitation
/ road distress detection
/ Road maintenance
/ roads
/ Roads & highways
/ Software
/ spatial data
/ Surveying
/ surveys
/ Three dimensional models
/ UAV
/ Unmanned aerial vehicles
/ Vehicles
2019
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Journal Article
UAV Photogrammetry-Based 3D Road Distress Detection
2019
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Overview
The timely and proper rehabilitation of damaged roads is essential for road maintenance, and an effective method to detect road surface distress with high efficiency and low cost is urgently needed. Meanwhile, unmanned aerial vehicles (UAVs), with the advantages of high flexibility, low cost, and easy maneuverability, are a new fascinating choice for road condition monitoring. In this paper, road images from UAV oblique photogrammetry are used to reconstruct road three-dimensional (3D) models, from which road pavement distress is automatically detected and the corresponding dimensions are extracted using the developed algorithm. Compared with a field survey, the detection result presents a high precision with an error of around 1 cm in the height dimension for most cases, demonstrating the potential of the proposed method for future engineering practice.
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