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The impact of the calibration method on the accuracy of point clouds derived using unmanned aerial vehicle multi-view stereopsis

Citation

Harwin, SJ and Lucieer, A and Osborn, J, The impact of the calibration method on the accuracy of point clouds derived using unmanned aerial vehicle multi-view stereopsis, Remote Sensing, 7, (9) pp. 11933-11953. ISSN 2072-4292 (2015) [Refereed Article]


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Copyright 2015 Authors Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/

DOI: doi:10.3390/rs70911933

Abstract

In unmanned aerial vehicle (UAV) photogrammetric surveys, the cameracan be pre-calibrated or can be calibrated "on-the-job" using structure-from-motion anda self-calibrating bundle adjustment. This study investigates the impact on mapping accuracyof UAV photogrammetric survey blocks, the bundle adjustment and the 3D reconstructionprocess under a range of typical operating scenarios for centimetre-scale natural landformmapping (in this case, a coastal cliff). We demonstrate the sensitivity of the process tocalibration procedures and the need for careful accuracy assessment. For this investigation, vertical (nadir or near-nadir) and oblique photography were collected with 80%90%overlap and with accurately-surveyed (σ ≤ 2 mm) and densely-distributed ground control.This allowed various scenarios to be tested and the impact on mapping accuracy to beassessed. This paper presents the results of that investigation and provides guidelines thatwill assist with operational decisions regarding camera calibration and ground control forUAV photogrammetry. The results indicate that the use of either a robust pre-calibration ora robust self-calibration results in accurate model creation from vertical-only photography,and additional oblique photography may improve the results. The results indicate thatif a dense array of high accuracy ground control points are deployed and the UAVphotography includes both vertical and oblique images, then either a pre-calibration or anon-the-job self-calibration will yield reliable models (pre-calibration RMSEXY = 7.1 mmand on-the-job self-calibration RMSEXY = 3.2 mm). When oblique photography was Remote Sens. 2015, 7 11934 excluded from the on-the-job self-calibration solution, the accuracy of the model deteriorated(by 3.3 mm horizontally and 4.7 mm vertically). When the accuracy of the ground controlwas then degraded to replicate typical operational practice (σ = 22 mm), the accuracyof the model further deteriorated (e.g., on-the-job self-calibration RMSEXY went from3.27.0 mm). Additionally, when the density of the ground control was reduced, the modelaccuracy also further deteriorated (e.g., on-the-job self-calibration RMSEXY went from7.07.3 mm). However, our results do indicate that loss of accuracy due to sparse groundcontrol can be mitigated by including oblique imagery.

Item Details

Item Type:Refereed Article
Keywords:UAV photogrammetry, accuracy assessment, camera calibration, structure-from-motion, multi-view stereopsis, UAV, calibration, oblique imagery, ground control accuracy
Research Division:Engineering
Research Group:Geomatic Engineering
Research Field:Photogrammetry and Remote Sensing
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Technology
UTAS Author:Harwin, SJ (Mr Stephen Harwin)
UTAS Author:Lucieer, A (Associate Professor Arko Lucieer)
UTAS Author:Osborn, J (Dr Jon Osborn)
ID Code:103225
Year Published:2015
Web of Science® Times Cited:53
Deposited By:Geography and Environmental Studies
Deposited On:2015-09-29
Last Modified:2017-10-25
Downloads:170 View Download Statistics

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