Papadakis07b

N. Papadakis, E. Mémin. A variational framework for spatio-temporal smoothing of fluid motions. In Proc. Conf. Scale-Space and Variational Meth. (SSVM'07), Pages 603-615, Ischia, Italy, June 2007.

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Abstract

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.

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Etienne Mémin

BibTex Reference

@InProceedings{Papadakis07b,
   Author = {Papadakis, N. and Mémin, E.},
   Title = {A variational framework for spatio-temporal smoothing of fluid motions},
   BookTitle = {Proc. Conf. Scale-Space and Variational Meth. (SSVM'07)},
   Pages = {603--615},
   Address = {Ischia, Italy},
   Month = {June},
   Year = {2007}
}

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