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  • Application of optical flow technique and photogrammetry for rockfall dynamics: A case study on a field test

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    Version of Record (VoR)
    Author(s)
    Kim, DH
    Gratchev, I
    Griffith University Author(s)
    Gratchev, Ivan
    Year published
    2021
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    Abstract
    Optical flow is a vision-based approach that is used for tracking the movement of objects. This robust technique can be an effective tool for determining the source of failures on slope surfaces, including the dynamic behavior of rockfall. However, optical flow-based measurement still remains an issue as the data from optical flow algorithms can be affected by the varied photographing environment, such as weather and illuminations. To address such problems, this paper presents an optical flow-based tracking algorithm that can be employed to extract motion data from video records for slope monitoring. Additionally, a workflow ...
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    Optical flow is a vision-based approach that is used for tracking the movement of objects. This robust technique can be an effective tool for determining the source of failures on slope surfaces, including the dynamic behavior of rockfall. However, optical flow-based measurement still remains an issue as the data from optical flow algorithms can be affected by the varied photographing environment, such as weather and illuminations. To address such problems, this paper presents an optical flow-based tracking algorithm that can be employed to extract motion data from video records for slope monitoring. Additionally, a workflow combined with photogrammetry and the optical flow technique has been proposed for producing highly accurate estimations of rockfall motion. The effectiveness of the proposed approach has been evaluated with the dataset obtained from a photogrammetry survey of field rockfall tests performed by the authors in 2015. The results show that the workflow adopted in this study can be suitable to identify rockfall events overtime in a slope monitoring system. The limitations of the current approach are also discussed.
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    Journal Title
    Remote Sensing
    Volume
    13
    Issue
    20
    DOI
    https://doi.org/10.3390/rs13204124
    Copyright Statement
    © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Physical geography and environmental geoscience
    Geomatic engineering
    Classical physics
    Publication URI
    http://hdl.handle.net/10072/409973
    Collection
    • Journal articles

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