Fluid motion recovery by coupling dense and parametric vector fields

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.