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Automated extraction of free surface topography using SfM-MVS photogrammetry

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journal contribution
posted on 06.03.2017 by Edgar Ferreira, Jim Chandler, Rene Wackrow, Koji Shiono
This paper describes a spatial measurement technique to measure the free surface of natural fluid flows in laboratory applications. This effective solution is based on “Structure-from- Motion/Multi-view Stereo” (SfM-MVS) photogrammetry and is capable of reconstructing water surface morphology, both at an instant and with a high spatial resolution. The efficiency and accuracy of the method is dependent upon the acquisition of high quality imagery (i.e. sharply focussed, no motion blur) with appropriate multi-frame camera coverage and configuration, and data processing must utilise appropriate camera calibration data. The potential of the technique for developing hydraulic understanding is demonstrated using two contrasting approaches. First, the water surface behind a living vegetation element is analysed along a single transect. Second, the full three-dimensional characteristics of the captured water surfaces are examined using statistical methods which demonstrate surface dissimilarity between vegetated and non-vegetated cases. The technique is transferable to real-world field sites.

Funding

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) [Grant: EP/K004891/1].

History

School

  • Architecture, Building and Civil Engineering

Published in

Flow Measurement and Instrumentation

Volume

54

Pages

243-249

Citation

FERREIRA, E. ... et al, 2017. Automated extraction of free surface topography using SfM-MVS photogrammetry. Flow Measurement and Instrumentation, 54, pp. 243-249.

Publisher

Elsevier / © The Authors

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

05/02/2017

Publication date

2017-02-07

Notes

This is an Open Access article published by Elsevier and distributed under the terms of the Creative Commons Attribution Licence, CC BY 4.0, https://creativecommons.org/licenses/by/4.0/

ISSN

0955-5986

Language

en

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