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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, pp. 75-102.
  • 2C. 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, pp. 1–7.
  • 3T. 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, pp. 160–178.

    http://www.irisa.fr/fluminance/publi/papers/2008_Tellus_Corpetti.pdf
  • 4T. Corpetti, D. Heitz, G. Arroyo, E. Mémin, A. Santa-Cruz.

    Fluid experimental flow estimation based on an optical-flow scheme, in: Experiments in fluids, 2006, vol. 40, pp. 80–97.
  • 5A. 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, pp. 1278–1293.
  • 6A. Gronskis, D. Heitz, E. Mémin.

    Inflow and initial conditions for direct numerical simulation based on adjoint data assimilation, in: Journal of Computational Physics, 2013, vol. 242, pp. 480-497. [ DOI : 10.1016/j.jcp.2013.01.051 ]

    http://www.sciencedirect.com/science/article/pii/S0021999113001290
  • 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, pp. 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, pp. 6238-6250.
  • 9N. 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, pp. 81–103.

    http://www.irisa.fr/fluminance/publi/papers/Papadakis-Memin-JMIV07.pdf
  • 10J. 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, pp. 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

  • 13C. Avenel, E. Mémin, P. Pérez.

    Stochastic level set dynamics to track closed curves through image data, in: Journal of Mathematical Imaging and Vision, June 2014, vol. 49, no 2, pp. 296-316. [ DOI : 10.1007/s10851-013-0464-1 ]

    https://hal.inria.fr/hal-00854420
  • 14T. Corpetti, V. Dubreuil, E. Mémin, N. Papadakis, O. Planchon, C. Thomas.

    Outils méthodologiques l'analyse d'images MSG : estimation du mouvement, suivi de masses nuageuses et détéction de fronts, in: Revue Française de Photogrammétrie et de Télédétection, 2014, vol. 205, pp. 3-18.

    https://hal.archives-ouvertes.fr/hal-01102978
  • 15A. Cuzol, J.-L. Marchand, E. Mémin.

    Image data assimilation with filtering methods, in: Journal de la Société Française de Statistiques, 2014, pp. 1-11.

    https://hal.archives-ouvertes.fr/hal-01074991
  • 16A. Cuzol, E. Mémin.

    Monte Carlo fixed-lag smoothing in state-space models, in: Nonlinear Processes in Geophysics, 2014, vol. 21, pp. 633 - 643. [ DOI : 10.5194/npg-21-633-2014 ]

    https://hal.archives-ouvertes.fr/hal-01074987
  • 17E. Mémin.

    Fluid flow dynamics under location uncertainty, in: Geophysical and Astrophysical Fluid Dynamics, May 2014, vol. 108, no 2, pp. 119-146. [ DOI : 10.1080/03091929.2013.836190 ]

    https://hal.inria.fr/hal-00852874
  • 18S. Walton, K. Berger, J. Thiyagalingam, M. Chen.

    Visualising temporal cardiovascular imagery, in: Progress in Biophysics and Molecular Biology, 2014.

    https://hal.inria.fr/hal-00993179

International Conferences with Proceedings

  • 19T.-B. Airimitoaie, C. Collewet.

    Improving robust stability by increasing the number of controlled degrees of freedom, in: 7th AIAA Flow Control Conference, Atlanta, United States, June 2014.

    https://hal.inria.fr/hal-01101089
  • 20T.-B. Airimitoaie, C. Collewet.

    Indirect adaptive control of unknown diffusion equation, in: 7th AIAA Flow Control Conference, Atlanta, Antarctica, June 2014.

    https://hal.inria.fr/hal-01101083
  • 21M. Chen, S. Walton, K. Berger, J. Thiyagalingam, B. Duffy, H. Fang, C. Holloway, A. Trefethen.

    Visual Multiplexing, in: EuroVis, Swanssea, United Kingdom, July 2014.

    https://hal.inria.fr/hal-00993183
  • 22A. Drémeau, P. Héas, C. Herzet.

    Combining sparsity and dynamics: an efficient way, in: international - Traveling Workshop on Interactions between Sparse models and Technology (iTwist), Namur, Belgium, August 2014.

    https://hal.inria.fr/hal-01096259
  • 23A. Drémeau, P. Héas, C. Herzet.

    Sparse representations in nested non-linear models, in: IEEE International Conference on Speech, Acoustic and Signal Processing (ICASSP), Firenze, Italy, May 2014. [ DOI : 10.1109/ICASSP.2014.6855147 ]

    https://hal.inria.fr/hal-01096254
  • 24C. Herzet, C. Soussen.

    Enhanced Recovery Conditions for OMP/OLS by Exploiting both Coherence and Decay, in: international - Traveling Workshop on Interactions between Sparse models and Technology (iTwist'14), Namur, Belgium, August 2014, pp. 36-37.

    https://hal.inria.fr/hal-01096266

Internal Reports

  • 25I. D. Landau, T.-B. Airimitoaie, M. Alma.

    Adaptive Feedforward Compensation Algorithms for Active Vibration Control with Mechanical Coupling and Local Feedback - a unified approach, January 2014.

    https://hal.archives-ouvertes.fr/hal-00922912

Other Publications

References in notes
  • 29R. Adrian.

    Particle imaging techniques for experimental fluid mechanics, in: Annal Rev. Fluid Mech., 1991, vol. 23, pp. 261-304.
  • 30T. Bewley.

    Flow control: new challenges for a new Renaissance, in: Progress in Aerospace Sciences, 2001, vol. 37, pp. 21–58.
  • 31K. Breuer.

    Sensors, Actuators and Algorithms for practical implementations of turbulence boundary layer control, in: 3rd Japan Symposium on Turbulence and Flow Control, Tokyo, Japan, March 2002.
  • 32F. Chaumette, S. Hutchinson.

    Visual servoing and visual tracking, in: Handbook of Robotics, B. Siciliano, O. Khatib (editors), Springer, 2008, chap. 24, pp. 563–583.
  • 33H. Choi, P. Moin, J. Kim.

    Direct numerical simulation of turbulent flow over riblets, in: Journal of Fluid Mechanics, 1993, vol. 255, pp. 503–539.
  • 34S. S. Collis, R. D. Joslin, A. Seifert, V. Theofilis.

    Issues in active flow control: theory, control, simulation, and experiment, in: Progress in Aerospace Sciences, 2004, vol. 4, pp. 237–289.
  • 35E. Doebelin.

    Control System Principles and Design, John Wiley and Sons, New York, 1985.
  • 36G. E. Elsinga, F. Scarano, B. Wieneke, B. W. van Oudheusden.

    Tomographic particle image velocimetry, in: Exp. in Fluids, 2006, vol. 41, pp. 933-947.
  • 37G. Evensen.

    Sequential data assimilation with a non linear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, in: J. Geophys. Res., 1994, vol. 99 (C5), no 10, pp. 143–162.
  • 38J. Favier.

    Contrôle d'écoulements : approche expérimentale et modélisation de dimension réduite, Institut National Polytechnique de Toulouse, 2007.
  • 39J. Favier, A. Kourta, G. Leplat.

    Control of flow separation on a wing profile using PIV measurements and POD analysis, in: IUTAM Symposium on Flow Control and MEMS, London, UK, September 19-22, 2006.
  • 40N. Gordon, D. Salmond, A. Smith.

    Novel approach to non-linear/non-Gaussian Bayesian state estimation, in: IEEE Processing-F, April 1993, vol. 140, no 2.
  • 41A. Guégan, P. Schmid, P. Huerre.

    Optimal energy growth and optimal control in swept Hiemenz flow, in: J. Fluid Mech., 2006, vol. 566, pp. 11–45.
  • 42B. Horn, B. Schunck.

    Determining Optical Flow, in: Artificial Intelligence, August 1981, vol. 17, no 1-3, pp. 185–203.
  • 43J. Hœpffner, M. Chevalier, T. Bewley, D. S. Henningson.

    State estimation in wall-bounded flow systems. Part 1. Perturbed laminar flows, in: Journal of Fluid Mechanics, 2005, vol. 534, pp. 263–294.
  • 44F.-X. Le Dimet, O. Talagrand.

    Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects, in: Tellus, 1986, no 38A, pp. 97–110.
  • 45J. Lions.

    Optimal Control of Systems Governed by Partial Differential Equations, Springer-Verlag, 1971.
  • 46L. Mathelin, O. Le Maître.

    Robust control of uncertain cylinder wake flows based on robust reduced order models, in: Computer and Fluids, 2009, vol. 38, pp. 1168–1182.
  • 47B. Protas, J. Wesfreid.

    Drag force in the open-loop control of the cylinder wake in the laminar regime, in: Physics of Fluids, February 2002, vol. 14, no 2, pp. 810–826.
  • 48C. Samson, M. Le Borgne, B. Espiau.

    Robot Control: the Task Function Approach, Clarendon Press, Oxford, United Kingdom, 1991.
  • 49G. Settles.

    Schlieren and shadowgraph tecniques, Spinger Verlag series on experimental fluid mechanics, 2001.
  • 50A. Svizher, J. Cohen.

    Holographic particle image velocimetry system for measurements of hairpin vortices in air channel flow, in: Exp. in Fluids, 2006, vol. 40, no 5, pp. 708-722.
  • 51R. Tatsambon Fomena, C. Collewet.

    Fluid Flow Control: a Vision-Based Approach, in: International Journal of Flow Control, 2011, vol. 3, no 23, pp. 133–169.

    http://hal.inria.fr/hal-00701080
  • 52I. Wygnanski.

    Boundary layer flow control by periodic addition of momentum, in: 4th AIAA Shear Flow Control Conference, USA, June 29-July 2, 1997.


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