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Heás, P.; Herzet, C.; Meḿin, E.; Heitz, D.; Mininni, P.D. "Bayesian estimation of turbulent motion" (2013) IEEE Transactions on Pattern Analysis and Machine Intelligence. 35(6):1343-1356
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Abstract:

Based on physical laws describing the multiscale structure of turbulent flows, this paper proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales. By reformulating this problem from a Bayesian perspective, an algorithm is proposed to jointly estimate motion, regularization hyperparameters, and to select the most likely physical prior among a set of models. Hyperparameter and model inference are conducted by posterior maximization, obtained by marginalizing out non-Gaussian motion variables. The Bayesian estimator is assessed on several image sequences depicting synthetic and real turbulent fluid flows. Results obtained with the proposed approach exceed the state-of-the-art results in fluid flow estimation. © 2013 IEEE.

Registro:

Documento: Artículo
Título:Bayesian estimation of turbulent motion
Autor:Heás, P.; Herzet, C.; Meḿin, E.; Heitz, D.; Mininni, P.D.
Filiación:Inria, Rennes Bretagne-Atlantique, F-35042 Rennes, France
Irstea, UR TERE, F-35044 Rennes, France
Departamento de Fisica, FCEN, UBA Ciudad Universitaria, Buenos Aires 1428, Argentina
National Center for Atmospheric Research, PO Box 3000, Boulder, CO 80307-2000, United States
Palabras clave:Bayesian model selection; Constrained optimization; Optic flow; Robust estimation; Turbulence; Bayesian model selection; Bayesian perspective; Fluid flow estimation; Fluid motion estimation; Multi-scale structures; Optic flow; Robust estimation; Scale-invariance property; Bayesian networks; Computer vision; Constrained optimization; Estimation; Flow of fluids; Turbulence; Models
Año:2013
Volumen:35
Número:6
Página de inicio:1343
Página de fin:1356
DOI: http://dx.doi.org/10.1109/TPAMI.2012.232
Título revista:IEEE Transactions on Pattern Analysis and Machine Intelligence
Título revista abreviado:IEEE Trans Pattern Anal Mach Intell
ISSN:01628828
CODEN:ITPID
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01628828_v35_n6_p1343_Heas

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Citas:

---------- APA ----------
Heás, P., Herzet, C., Meḿin, E., Heitz, D. & Mininni, P.D. (2013) . Bayesian estimation of turbulent motion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(6), 1343-1356.
http://dx.doi.org/10.1109/TPAMI.2012.232
---------- CHICAGO ----------
Heás, P., Herzet, C., Meḿin, E., Heitz, D., Mininni, P.D. "Bayesian estimation of turbulent motion" . IEEE Transactions on Pattern Analysis and Machine Intelligence 35, no. 6 (2013) : 1343-1356.
http://dx.doi.org/10.1109/TPAMI.2012.232
---------- MLA ----------
Heás, P., Herzet, C., Meḿin, E., Heitz, D., Mininni, P.D. "Bayesian estimation of turbulent motion" . IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, no. 6, 2013, pp. 1343-1356.
http://dx.doi.org/10.1109/TPAMI.2012.232
---------- VANCOUVER ----------
Heás, P., Herzet, C., Meḿin, E., Heitz, D., Mininni, P.D. Bayesian estimation of turbulent motion. IEEE Trans Pattern Anal Mach Intell. 2013;35(6):1343-1356.
http://dx.doi.org/10.1109/TPAMI.2012.232