Fluid Motion Recovery by Coupling Dense and Parametric Vector Fields

Étienne Mémin, Patrick Pérez

Abstract: Addresses the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context, standard motion estimation techniques are not well-adapted, and more dedicated approaches have to be designed. We thus propose to estimate, in a joint and cooperative way, a dense motion field and a peculiar parametric representation of the flow. The parametric model is derived from an extension of the Rankine vortex model and includes a laminar flow field. Dense and parametric fields are estimated by minimizing a robust global objective function, thanks to a specific alternate scheme. The method has been validated on different kinds of meteorological image sequences.