Abstract.
In this paper, we address the problem of estimating the mo- tion 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 photomet- ric contrasts, classical motion estimation methods based on the bright- ness consistency assumption (correlation-based approaches, optical flow methods) are completely ineficient. 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.