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Bibliography

Major publications by the team in recent years
  • 1E. Arnaud, E. Mémin.

    Partial linear Gaussian model for tracking in image sequences using sequential Monte Carlo methods, in: International Journal of Computer Vision, 2007, vol. 74, no 1, p. 75-102.
  • 2C. Braud, D. Heitz, P. Braud, G. Arroyo, J. Delville.

    Analysis of the wake-mixing-layer interaction using multiple plane PIV and 3D classical POD, in: Exp. in Fluids, 2004, vol. 37, no 1, p. 95–104.
  • 3C. Collewet, E. Marchand.

    Modeling complex luminance variations for target tracking, in: IEEE Int. Conf. on Computer Vision and Pattern Recognition, CVPR'08, Anchorage, Alaska, June 2008, p. 1–7.
  • 4T. Corpetti, P. Héas, E. Mémin, N. Papadakis.

    Pressure image assimilation for atmospheric motion estimation, in: Tellus Series A: Dynamic Meteorology and Oceanography, 2009, vol. 61, no 1, p. 160–178.

    http://www.irisa.fr/fluminance/publi/papers/2008_Tellus_Corpetti.pdf
  • 5T. Corpetti, E. Mémin, P. Pérez.

    Dense Estimation of Fluid Flows, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, March 2002, vol. 24, no 3, p. 365–380.
  • 6A. Cuzol, E. Mémin.

    A stochastic filter technique for fluid flows velocity fields tracking, in: IEEE Trans. Pattern Analysis and Machine Intelligence, 2009, vol. 31, no 7, p. 1278–1293.
  • 7D. Heitz, E. Mémin, C. Schnoerr.

    Variational Fluid Flow Measurements from Image Sequences: Synopsis and Perspectives, in: Experiments in fluids, 2010, vol. 48, no 3, p. 369–393.
  • 8C. Herzet, K. Woradit, H. Wymeersch, L. Vandendorpe.

    Code-Aided Maximum-Likelihood Ambiguity Resolution Through Free-Energy Minimization, in: IEEE Trans. Signal Processing, 2010, vol. 58, no 12, p. 6238-6250.
  • 9P. Héas, E. Mémin.

    3D motion estimation of atmospheric layers from image sequences, in: IEEE Trans. on Geoscience and Remote Sensing, 2008, vol. 46, no 8, p. 2385–2396.
  • 10N. Papadakis, E. Mémin.

    A variational technique for time consistent tracking of curves and motion, in: Journal of Mathematical Imaging and Vision, 2008, vol. 31, no 1, p. 81–103.

    http://www.irisa.fr/fluminance/publi/papers/Papadakis-Memin-JMIV07.pdf
  • 11P. Parnaudeau, J. Carlier, D. Heitz, E. Lamballais.

    Experimental and numerical studies of the flow over a circular cylinder at Reynolds number 3900, in: Phys. of Fluids, 2008, vol. 20, no 8.
  • 12J. Yuan, C. Schnoerr, E. Mémin.

    Discrete orthogonal decomposition and variational fluid flow estimation, in: Journal of Mathematical Imaging and Vision, 2007, vol. 28, no 1, p. 67–80.

    http://www.irisa.fr/fluminance/publi/papers/Yuan-et-al-JMIV06.pdf
Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 15G. Artana, A. Cammilleri, J. Carlier, E. Mémin.

    Strong and weak constraint variational assimilation for reduced order fluid flow modeling, in: Journ. of Comp. Physics, April 2012, vol. 213, no 8, p. 3264–3288.
  • 16S. Beyou, T. Corpetti, S. Gorthi, E. Mémin.

    Fluid flow estimation with multiscale ensemble filters based on motion measurements under location uncertainty, in: Numerical Mathematics: Theory , Methods and Applications., 2012, accepted for publication.

    http://hal.inria.fr/hal-00736457
  • 17S. Beyou, A. Cuzol, S. Gorthi, E. Mémin.

    Weighted Ensemble Transform Kalman Filter for Image Assimilation, in: Tellus A, 2012, accepted for publication.
  • 18T. Corpetti, E. Mémin.

    Stochastic uncertainty models for the luminance consistency assumption, in: IEEE Transaction on Image Processing, January 2012, vol. 21, no 2, p. 481-493. [ DOI : 10.1109/TIP.2011.2162742 ]

    http://hal.inria.fr/hal-00694584
  • 19P. Dérian, P. Héas, C. Herzet, E. Mémin.

    Wavelets and Optical Flow Motion Estimation, in: Numerical Mathematics: Theory, Methods and Applications, 2012.

    http://hal.inria.fr/hal-00737566
  • 20M. Gouiffès, C. Collewet, C. Fernandez, A. Trémeau.

    A study on local photometric models and their application to robust tracking, in: Computer Vision and Image Understanding, April 2012, vol. 116, p. 896-907. [ DOI : 10.1016/j.cviu.2012.04.002 ]

    http://hal.inria.fr/hal-00726513
  • 21P. Héas, C. Herzet, E. Mémin, D. Heitz, P. D. Mininni.

    Bayesian estimation of turbulent motion, in: IEEE transactions on Pattern Analysis And Machine Inteligence, December 2012.

    http://hal.inria.fr/hal-00745814
  • 22P. Héas, C. Herzet, E. Mémin.

    Bayesian inference of models and hyper-parameters for robust optic-flow estimation, in: IEEE Transactions on Image Processing, April 2012.

    http://hal.inria.fr/hal-00670375
  • 23P. Héas, E. Mémin, D. Heitz, P. D. Mininni.

    Power laws and inverse motion modeling: application to turbulence measurements from satellite images, in: Tellus A, January 2012.

    http://hal.inria.fr/hal-00670364
  • 24S. Kadri Harouna, P. Dérian, P. Héas, E. Mémin.

    Divergence-free Wavelets and High Order Regularization, in: International Journal of Computer Vision, 2012, accepted for publication.

    http://hal.archives-ouvertes.fr/hal-00646104

International Conferences with Proceedings

  • 25C. Avenel, E. Mémin, P. Pérez.

    Tracking Level Set Representation Driven by a Stochastic Dynamics, in: International Conference on Curves and Surfaces, Avignon, France, Lecture Notes in Computer Science, Springer, January 2012, vol. 6920/2012, p. 130-141. [ DOI : 10.1007/978-3-642-27413-8_8 ]

    http://hal.inria.fr/hal-00694591
  • 26X.-Q. Dao, C. Collewet.

    Drag Reduction of the Plane Poiseuille Flow by Partitioned Visual Servo Control, in: American control conference, Montréal, Canada, June 2012, p. 4084-4089.

    http://hal.inria.fr/hal-00726528
  • 27X.-Q. Dao, C. Collewet.

    Réduction de la traînée de l'écoulement de Poiseuille 2D par asservissement visuel partitionné, in: Conférence Internationale Francophone d'Automatique, Grenoble, France, July 2012, p. 449-454.

    http://hal.inria.fr/hal-00726532
  • 28X.-Q. Dao, C. Collewet.

    Simultaneous Drag Reduction and Kinetic Energy Density of the Plane Poiseuille Flow, in: 6th AIAA Flow Control Conference, New Orleans, United States, June 2012.

    http://hal.inria.fr/hal-00707173
  • 29A. Drémeau, C. Herzet, L. Daudet.

    Structured Bayesian Orthogonal Matching Pursuit, in: IEEE ICASSP 2012, Kyoto, Japan, March 2012.

    http://hal.inria.fr/hal-00754995

Conferences without Proceedings

  • 30P. Arbogast, O. Pannekoucke, E. Mémin.

    Object-oriented processing of CRM precipitation forecasts by stochastic filtering, in: International Conference on Ensemble Methods in Geophysical Sciences, Météo-France, Toulouse, November 2012.
  • 31C. Avenel, E. Mémin, P. Pérez.

    Stochastic level set dynamics for the tracking of closed curves from image data, in: International Conference on Ensemble Methods in Geophysical Sciences, Météo-France, Toulouse, November 2012.
  • 32S. Beyou, A. Cuzol, E. Mémin.

    A particle stochastic filter for fluid flow recovery from images, in: GlobCurrent Workshop, Ifremer, Brest, March 2012.
  • 33S. Beyou, A. Cuzol, E. Mémin.

    Weighted Ensemble Transform Kalman Filter for Image Assimilation, in: International Conference on Ensemble Methods in Geophysical Sciences, Météo-France, Toulouse, November 2012.
  • 34S. Beyou, E. Mémin, S. Reynaud.

    Assimilation de vitesse de surface en mer d'Iroise par filtrage de Kalman d'ensemble pondéré, in: Colloque National Assimilation de Données, CNA12, Nice, December 2012.
  • 35C. Robinson, Y. Yang, D. Heitz, E. Mémin.

    Evaluation of an ensemble based 4D var assimilation, in: Colloque National Assimilation de Données, CNA12, Nice, December 2012.

Other Publications

References in notes
  • 40R. Adrian.

    Particle imaging techniques for experimental fluid mechanics, in: Annal Rev. Fluid Mech., 1991, vol. 23, p. 261-304.
  • 41C. Braud, D. Heitz, G. Arroyo, L. Perret, J. Delville, J. Bonnet.

    Low-dimensional analysis, using POD, for two mixing layer-wake interactions, in: International journal of heat and fluid flow, 2004, vol. 25, p. 351–363.
  • 42E. Candes, L. Demanet.

    The Curvelet Representation of Wave Propagators is Optimally Sparse, in: Comm. Pure Appl. Math, 2005, vol. 58, no 11, p. 1472-1528.
  • 43F. Chaumette, S. Hutchinson.

    Visual servoing and visual tracking, in: Handbook of Robotics, B. Siciliano, O. Khatib (editors), Springer, 2008, chap. 24, p. 563–583.
  • 44G.-H. Cottet, P. Koumoutsakos.

    Vortex methods: theory and practice, Cambridge University Press, 2000.
  • 45B. Horn, B. Schunck.

    Determining Optical Flow, in: Artificial Intelligence, August 1981, vol. 17, no 1-3, p. 185–203.
  • 46F.-X. Le Dimet, O. Talagrand.

    Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects, in: Tellus, 1986, no 38A, p. 97–110.
  • 47J. Lions.

    Optimal Control of Systems Governed by Partial Differential Equations, Springer-Verlag, 1971.
  • 48S. Osher, J. Sethian.

    Fronts propagating with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulation, in: Journal of Computational Physics, 1988, vol. 79, p. 12-49.
  • 49P. Parnaudeau, D. Heitz, E. Lamballais, J. Silvestrini.

    Direct numerical simulations of vortex shedding behind circular cylinders with spanwise linear nonuniformity, in: Journal of Turbulence, 2007, vol. 8, no 13.
  • 50P. Parnaudeau, E. Lamballais, D. Heitz, J. Silvestrini.

    Combination of the immersed boundary method with compact schemes for DNS of flows in complex geometry, in: Direct and large-eddy simulation 5, Kluwer academic publishers, 2003.
  • 51C. Samson, M. Le Borgne, B. Espiau.

    Robot Control: the Task Function Approach, Clarendon Press, Oxford, United Kingdom, 1991.


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