Multi-Epoch and Multi-Imagery (MEMI) Photogrammetric Workflow for Enhanced Change Detection Using Time-Lapse Cameras
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RISKNAT Research Group, GEOMODELS Research Institute, Faculty of Earth Sciences, Universitat de Barcelona, 08028 Barcelona, Spain
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Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, 01069 Dresden, Germany
3
Center for Research on the Alpine Environment (CREALP), Sion, CH1950 Valais, Switzerland
4
Institute of Applied Geosciences, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Roland Perko
Remote Sens. 2021, 13(8), 1460; https://doi.org/10.3390/rs13081460
Received: 24 March 2021
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Revised: 6 April 2021
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Accepted: 7 April 2021
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Published: 9 April 2021
(This article belongs to the Special Issue Advances in Photogrammetry and Remote Sensing: Data Processing and Innovative Applications)
Photogrammetric models have become a standard tool for the study of surfaces, structures and natural elements. As an alternative to Light Detection and Ranging (LiDAR), photogrammetry allows 3D point clouds to be obtained at a much lower cost. This paper presents an enhanced workflow for image-based 3D reconstruction of high-resolution models designed to work with fixed time-lapse camera systems, based on multi-epoch multi-images (MEMI) to exploit redundancy. This workflow is part of a fully automatic working setup that includes all steps: from capturing the images to obtaining clusters from change detection. The workflow is capable of obtaining photogrammetric models with a higher quality than the classic Structure from Motion (SfM) time-lapse photogrammetry workflow. The MEMI workflow reduced the error up to a factor of 2 when compared to the previous approach, allowing for M3C2 standard deviation of 1.5 cm. In terms of absolute accuracy, using LiDAR data as a reference, our proposed method is 20% more accurate than models obtained with the classic workflow. The automation of the method as well as the improvement of the quality of the 3D reconstructed models enables accurate 4D photogrammetric analysis in near-real time.
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Keywords:
time-lapse photogrammetry; multi-view stereo; 3D point clouds; change detection; rockslope monitoring; Multi-Epoch and Multi-Imagery (MEMI)
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MDPI and ACS Style
Blanch, X.; Eltner, A.; Guinau, M.; Abellan, A. Multi-Epoch and Multi-Imagery (MEMI) Photogrammetric Workflow for Enhanced Change Detection Using Time-Lapse Cameras. Remote Sens. 2021, 13, 1460. https://doi.org/10.3390/rs13081460
AMA Style
Blanch X, Eltner A, Guinau M, Abellan A. Multi-Epoch and Multi-Imagery (MEMI) Photogrammetric Workflow for Enhanced Change Detection Using Time-Lapse Cameras. Remote Sensing. 2021; 13(8):1460. https://doi.org/10.3390/rs13081460
Chicago/Turabian StyleBlanch, Xabier, Anette Eltner, Marta Guinau, and Antonio Abellan. 2021. "Multi-Epoch and Multi-Imagery (MEMI) Photogrammetric Workflow for Enhanced Change Detection Using Time-Lapse Cameras" Remote Sensing 13, no. 8: 1460. https://doi.org/10.3390/rs13081460
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