Multiscale Weighted Ensemble Kalman Filter for Fluid Flow Estimation

Abstract : This paper proposes a novel multi-scale uid ow data as- similation approach, which integrates and complements the advantages of a Bayesian sequential assimilation technique, the Weighted Ensem- ble Kalman lter (WEnKF) [12], and an improved multiscale stochastic formulation of the Lucas-Kanade (LK) estimator. The proposed scheme enables to enforce a physically plausible dynamical consistency of the estimated motion elds along the image sequence. 1
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Alfred M. Bruckstein, Bart M. ter Haar Romeny, Alexander M. Bronstein, Michael M. Bronstein. 3rd International conference on scale space and variational methods in computer vision (SSVM), May 2011, Ein-Gedi, Israel. Springer Verlag, 6667, 2011, Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 - June 2, 2011, Revised Selected Papers; Lecture notes in Computer Sciences
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Dernière modification le : mercredi 14 décembre 2016 - 01:07:19
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Sai Gorthi, Sébastien Beyou, Thomas Corpetti, Etienne Memin. Multiscale Weighted Ensemble Kalman Filter for Fluid Flow Estimation. Alfred M. Bruckstein, Bart M. ter Haar Romeny, Alexander M. Bronstein, Michael M. Bronstein. 3rd International conference on scale space and variational methods in computer vision (SSVM), May 2011, Ein-Gedi, Israel. Springer Verlag, 6667, 2011, Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 - June 2, 2011, Revised Selected Papers; Lecture notes in Computer Sciences. <hal-00694975>

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