%0 Conference Proceedings
%F Papadakis07b
%A Papadakis, N.
%A Mémin, E.
%T A variational framework for spatio-temporal smoothing of fluid motions
%B Proc. Conf. Scale-Space and Variational Meth. (SSVM'07)
%P 603-615
%C Ischia, Italy
%X In this paper, we introduce a variational framework derived from data assimilation principles in order to realize a temporal Bayesian smoothing of fluid flow velocity fields. The velocity measurements are supplied by an optical flow estimator. These noisy measurement are smoothed according to the vorticity-velocity formulation of Navier-Stokes equation. Following optimal control recipes, the associated minimization is conducted through an iterative process involving a forward integration of our dynamical model followed by a backward integration of an adjoint evolution law. Both evolution laws are implemented with second order non-oscillatory scheme. The approach is here validated on a synthetic sequence of turbulent 2D flow provided by Direct Numerical Simulation (DNS) and on a real world meteorological satellite image sequence depicting the evolution of a cyclone.
%U http://www.irisa.fr/fluminance/publi/papers/Papadakis-Memin-SSVM07.pdf
%8 June
%D 2007