Computer Vision – ECCV 2006

Volume 3951 of the series Lecture Notes in Computer Science pp 198-210

A Fluid Motion Estimator for Schlieren Image Velocimetry

  • Elise ArnaudAffiliated withDisi, Università di Genova
  • , Etienne MéminAffiliated withIRISA, Université de Rennes 1
  • , Roberto SosaAffiliated withFacultad de Ingeniería, Universitad de Buenos Aires
  • , Guillermo ArtanaAffiliated withFacultad de Ingeniería, Universitad de Buenos Aires

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In this paper, we address the problem of estimating the motion of fluid flows that are visualized through a Schlieren system. Such a system is well known in fluid mechanics as it enables the visualization of unseeded flows. As the resulting images exhibit very low photometric contrasts, classical motion estimation methods based on the brightness consistency assumption (correlation-based approaches, optical flow methods) are completely inefficient. This work aims at proposing a sound energy based estimator dedicated to these particular images. The energy function to be minimized is composed of (a) a novel data term describing the fact that the observed luminance is linked to the gradient of the fluid density and (b) a specific div curl regularization term. The relevance of our estimator is demonstrated on real-world sequences.