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Analysis of water flows videos for surface velocityestimation

Musaab Khalid 1, 2 
2 FLUMINANCE - Fluid Flow Analysis, Description and Control from Image Sequences
IRMAR - Institut de Recherche Mathématique de Rennes, IRSTEA - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture, Inria Rennes – Bretagne Atlantique
Abstract : This thesis is an application of computer vision findings to river velocimetry research. Hydraulic research scientists already use various image processing techniques to process image sequences of rivers. The ultimate goal is to estimate free surface velocity of rivers remotely. As such, many risks related to intrusive river gauging techniques could be avoided. Towards this goal, there are two major issues need be addressed. Firstly, the motion of the river in image space need to be estimated. The second issue is related to how to transform this image velocity to real world velocity. Until recently, imagebased velocimetry methods impose many requirements on images and still need considerable amount of field work to be able to estimate rivers velocity with good accuracy. We extend the perimeter of this field by including amateur videos of rivers and we provide better solutions for the aforementioned issues. We propose a motion estimation model that is based on the so-called optical flow, which is a well developed method for rigid motion estimation in image sequences. Contrary to conventional techniques used before, optical flow formulation is flexible enough to incorporate physics equations that govern rivers motion. Our optical flow is based on the scalar transport equation and is augmented with a weighted diffusion term to compensate for small scale (non-captured) contributions. Additionally, since there is no ground truth data for such type of image sequences, we present a new evaluation method to assess the results. It is based on trajectory reconstruction of few Lagrangian particles of interest and a direct comparison against their manually-reconstructed trajectories. The new motion estimation technique outperformed traditional methods in image space. Finally, we propose a specialized geometric modeling of river sites that allows complete and accurate passage from 2D velocity to world velocity, under mild assumptions. This modeling considerably reduces the field work needed before to deploy Ground Reference Points (GRPs). We proceed to show the results of two case studies in which world velocity is estimated from raw videos.
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Submitted on : Thursday, August 30, 2018 - 3:31:20 PM
Last modification on : Tuesday, June 7, 2022 - 1:56:01 PM


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  • HAL Id : tel-01864873, version 1
  • IRSTEA : PUB00058713


Musaab Khalid. Analysis of water flows videos for surface velocityestimation. Signal and Image processing. Université Rennes 1, 2018. English. ⟨NNT : 2018REN1S019⟩. ⟨tel-01864873⟩



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