Academic Journals

  1. P-M Boulvard and E. Mémin, Diagnostic of the Lévy area for geophysical flow models in view of defining high order stochastic discrete-time schemes, AIMS Foundations of Data Science, in press, 2023.
  2. O. Lang, D. Crisan, E. Mémin, Analytical Properties for a Stochastic Rotating Shallow Water Model Under Location Uncertainty, Journal of Mathematical Fluid Mechanics, , 25 (2), pp.29, 2023. PDF .
  3. A. Debussche, B. Hug, E. Mémin, A consistent stochastic large-scale representation of the Navier-Stokes equations, Journal of Mathematical Fluid Mechanics, 25 (1), pp. 19, 2023. PDF
  4. L. Li, B. Deremble, N. Lahaye, E. Mémin, Stochastic Data-Driven Parameterization of Unresolved Eddy Effects in a Baroclinic Quasi-Geostrophic Model, Journal of Advances in Modelling Earth Systems, 15 (2), 2023. PDF
  5. G. Tissot, A. V. G. Cavalieri, E. Mémin, Input-output analysis of the stochastic Navier-Stokes equations: application to turbulent channel flow, Physical Review Fluids, 8 (3), 033904, 2023. PDF
  6. M. Yacine Ben Ali, G. Tissot, S. Aguinaga, D. Heitz, E. Mémin, Mean wind flow reconstruction of a high-rise building based on variational data assimilation using sparse pressure measurements, Journal of Wind Engineering and Industrial Aerodynamics, 231 (105204), pp.16/105204, 2022. PDF
  7. E. Dinvay, E. Mémin, Hamiltonian formulation of the stochastic surface wave problem, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, pp.1-26, 2022. PDF
  8. Z. Yicun, B. Chapron, E. Mémin, L. Peng, Eigenvalues of Autocovariance Matrix: A Practical Method to Identify the Koopman Eigenfrequencies, Physical Review E , American Physical Society (APS), 105 (3), pp.1-12, 2022. PDF
  9. V. Resseguier, B. Chapron, E. Mémin, Effects of smooth divergence-free flows on tracer gradients and spectra: Eulerian prognosis description, Journal of Physical Oceanography, American Meteorological Society, 52 (1), pp.53-74, 2022. PDF
  10. B. Dufée, E. Mémin, D. Crisan, Stochastic parametrization: an alternative to inflation in Ensemble Kalman filters, Quarterly Journal of the Royal Meteorological Society, Wiley, pp.1-30, 2022. PDF
  11. G. Tissot, A. Cavalieri, E. Mémin, Stochastic linear modes in a turbulent channel flow, Journal of Fluid Mechanics, Cambridge University Press (CUP), 912, pp.1-33, 2021. PDF
  12. V. Resseguier, A. Picard, E. Mémin, B. Chapron, Quantifying truncation-related uncertainties in unsteady fluid dynamics reduced order models, SIAM/ASA Journal on Uncertainty Quantification, American Statistical Association, 2021, 9 (3), pp.1152-1183, 2021. PDF
  13. R. Brecht, L. Li, W. Bauer, E. Mémin , Rotating shallow water flow under location uncertainty with a structure- preserving discretization, Journal of Advances in Modeling Earth Systems, American Geophysical Union,13, 2021. PDF
  14. R. Fablet, B. Chapron, L. Drumetz, E. Mémin, O. Pannekoucke, F. Rousseau, Learning Variational Data Assimilation Models and Solvers, Journal of Advances in Modeling Earth Systems, American Geophysical Union, 13, 2021. PDF
  15. G. Tissot, A. Cavalieri, E. Mémin, Stochastic linear modes in a turbulent channel flow, J. of Fluid Mech., 912, pp.1-33, 2021, PDF .
  16. B. Pinier, R. Lewandowski, E. Mémin, P. Chandramouli,Testing a one-closure equation turbulence model in neutral boundary layers, Comp. Meth. in Applied Mech. and Eng., 376, 113662, 2021, PDF .
  17. W. Bauer, P. Chandramouli, B. Chapron, L. Li, E. Mémin, Deciphering the role of small-scale inhomogeneity on geophysical flow structuration: a stochastic approach, J. of Phys. Oceanography, 50 (4): 983--1003, 2020, PDF .
  18. W. Bauer, P. Chandramouli, L. Li, E. Mémin, Stochastic representation of mesoscale eddy effects in coarse-resolution barotropic models, Ocean Modelling, 151: 1--50, 2020, PDF .
  19. V. Resseguier, L. Li, G. Jouan, P. Dérian, E. Mémin, B. Chapron, New trends in ensemble forecast strategy: uncertainty quantification for coarse-grid computational fluid dynamics, Arch. of Comp. Meth. in Eng., https://doi.org/10.1007/s11831-020-09437-x, 2020, PDF .
  20. R. Schuster, D. Heitz, P. Georgeault, E. Mémin, On-site airflow measurement of a laboratory fume hood using customized large-scale image-based velocimetry, Indoor and Built Environment, 29 (6): 810-819, 2020, PDF .
  21. P. Chandramouli, E. Mémin , D. Heitz, 4D large scale variational data assimilation of a turbulent flow with a dynamics error model, J. of Comp. Phys., 412 (1): 109446, 2020, PDF .
  22. B. Pinier, E. Mémin, S. Laizet, R. Lewandowski, Stochastic flow approach to model the mean velocity profile of wall-bounded flows, Physical Review E, 99 (6): 063101, 2019, PDF .
  23. P. Chandramouli, E. Memim, D. Heitz, L. Fiabane, "Fast 3D flow reconstructions from 2D cross-plane observations", Experiments in Fluids, 60 (30), 2019, PDF .
  24. M. Khalid, L. Pénard, E. Mémin, Optical Flow For Image-Based River Velocity Estimation, Flow Measurement and Instrumentation, 65:110-121, 2019, PDF .
  25. Y. Yang, E. Mémin, Estimation of physical parameters under location uncertainty using an Ensemble^2-Expectation-Maximization algorithm, Quaterly journal of the royal meteorological society, 145 (719): 418--433, 2019, PDF
  26. B. Chapron, P. Dérian, E. Mémin, V. Resseguier, Large scale flows under location uncertainty: a consistent stochastic framework, Quarterly Journal of the Royal Meteorological Society, 144(710): 251-260, 2018, PDF
  27. P. Chandramouli, D. Heitz, S. Laizet, E. Mémin, Coarse large-eddy simulations in a transitional wake flow with flow models under location uncertainty, Computers and Fluids, 168:170-189, 2018, PDF .
  28. S. Cai, E. Mémin, P. Dérian, C. Xu, Motion Estimation under Location Uncertainty for Turbulent Fluid Flow, Experiments in Fluids, 59(8), 2018. PDF .
  29. S. Kadri-Harouna and E. Mémin, Stochastic representation of the Reynolds transport theorem: revisiting large-scale modeling, Comp. and Fluids, 156: 456-469, 2017 PDF .
  30. V. Resseguier, E. Mémin, D. Heitz and B. Chapron, Stochastic modeling and diffusion modes for POD models and small-scale flow analysis, J. of Fluid Mech., 828: 888-917, 2017, PDF .
  31. Y. Yang and E. Mémin, High-resolution data assimilation through stochastic subgrid tensor and parameter estimation from 4DEnVar, 2017, Tellus A, 69 (1), 2017, PDF .
  32. V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part I: Random transport and general models, Geophysical & Astrophysical Fluid Dynamics, 2017, 111(3): 149-176, PDF
  33. V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part II: Quasigeostrophic models and efficient ensemble spreading, Geophysical & Astrophysical Fluid Dynamics, 2017, 111(3): 177-208, PDF
  34. V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part III: SQG and frontal dynamics under strong turbulence, Geophysical & Astrophysical Fluid Dynamics, accepted for publication, 2017, 111(3): 209-227, PDF
  35. P. Arbogast, O. Pannekoucke, L. Raynaud, R. Lalanne and E. Mémin, Object-oriented processing of CRM precipitation forecasts by stochastic filtering, QJRMS, 2016 PDF
  36. V. Resseguier, E. Mémin, B. Chapron, Reduced flow models from a stochastic Navier-Stokes representation, Annales de l'ISUP, 2015 PDF
  37. B. Combés, D. Heitz, A. Guibert and E. Mémin, A particle filter to reconstruct a free-surface flow from a depth camera, 47, Fluid Dyn. Res., 2015 PDF
  38. Y. Yang, C. Robinson, D. Heitz and E., Mémin. Enhanced ensemble-based 4DVar scheme for data assimilation. Computer and Fluids, 115, 201--210, 2015. PDF
  39. A. Cuzol and E., Mémin. Monte carlo fixed-lag smoothing in state-space models. Nonlin. Processes Geophys., 21, 633-643, 2014. PDF
  40. E. Mémin. Fluid flow dynamics under location uncertainty. Geophysical & Astrophysical Fluid Dynamics, 108(2): 119-146, 2014. PDF
  41. C. Avenel, E. Mémin, P. Pérez. Stochastic level set dynamics to track closed curves through image data. Journ of Math. Imaging and Vision, 49:296-316., 2014. PDF
  42. A. Gronskis, D. Heitz, E. Mémin. Inflow and initial conditions for direct numerical simulation based on adjoint data assimilation. Journ. Comp. Phys, 242(6):480-497, 2013. PDF
  43. A. Cammilleri, F. Gueniat, J. Carlier, L. Pastur, E. Mémin, F. Lusseyran, G. Artana. POD-Spectral Decomposition for Fluid Flow Analysis and Model Reduction. Theor. and Comp. Fluid Dyn, 27:787-815, 2013. PDF
  44. P. Héas, C. Herzet, E. Mémin, D. Heitz, P.D. Mininni. Bayesian estimation of turbulent motion. IEEE transactions on Pattern Analysis And Machine Learning, 35(6):1343-1356, 2013. PDF
  45. S. Kadri Harouna, P. Dérian, P. Héas, E. Mémin. Divergence-free Wavelets and High Order Regularization. International Journal of Computer Vision, 103(1):80-99, May 2013. PDF
  46. P. Dérian, P. Héas, C. Herzet, E. Mémin. Wavelets and Optical Flow Motion Estimation. Numerical Mathematics: Theory, Methods and Applications, 6(1):116-137, January 2013. PDF
  47. S. Beyou, T. Corpetti, S. Gorthi, E. Mémin. Fluid flow estimation with multiscale ensemble filters based on motion measurements under location uncertainty. Numerical Mathematics: Theory, Methods and Applications, 6(1):21-46, January 2013. PDF
  48. S. Beyou, A. Cuzol, S. Gorthi, E. Mémin. Weighted Ensemble Transform Kalman Filter for Image Assimilation. Tellus A, 65(18803), January 2013. PDF
  49. P. Héas, E. Mémin, D. Heitz, P. Mininni. Power laws and inverse motion modeling: application to turbulence measurements from satellite images. Tellus Series A: Dynamic Meteorology and Oceanography, 64(10962), 2012. PDF
  50. P. Héas, C. Herzet, E. Mémin. Bayesian inference of models and hyper-parameters for robust optic-flow estimation. IEEE Trans on Image processing, 21(4):1437-1451, 2012. PDF
  51. G. Artana, A. Cammilleri, J. Carlier, E. Mémin. Strong and weak constraint variational assimilation for reduced order fluid flow modeling. Journ. of Comp. Physics, 213(8):3264-3288, April 2012. PDF
  52. T. Corpetti, E. Mémin. Stochastic uncertainty models for the luminance consistency assumption. IEEE Transaction on Image Processing, 21(2):481-493, January 2012. PDF
  53. D. Heitz, E. Mémin, C. Schnörr. Variational fluid flow measurements from image sequences: synopsis and perspectives. Exp. Fluids, 48(3):369-393, 2010. PDF
  54. N. Papadakis, E. Mémin, A. Cuzol, N. Gengembre. Data assimilation with the Weighted Ensemble Kalman Filter. Tellus-A, 62(5):673-697, 2010. PDF
  55. C. Thomas, T. Corpetti, E. Mémin. Data assimilation for convective cells tracking on meteorological image sequences. IEEE Trans. on Geoscience and Remote sensing, 2010. PDF
  56. T. Corpetti, P. Héas, E. Mémin, N. Papadakis. Pressure image assimilation for atmospheric motion estimation. Tellus Series A: Dynamic Meteorology and Oceanography, 61(1):160-178, 2009. PDF
  57. R. Sosa, E. Arnaud, E. Mémin, G. Artana. Study of the Flow Induced by a Sliding Discharge. IEEE Trans. on Dielectrics and Electrical Insulation, 16:305-311, 2009. PDF
  58. A. Cuzol, E. Mémin. A stochastic filtering technique for fluid flows velocity fields tracking. IEEE Trans. on Pattern Analysis and Machine Intelligence, 31(7):1278-1293, 2009. PDF
  59. D. Heitz, P. Héas, E. Mémin, J. Carlier. Dynamic consistent correlation-variational approach for robust optical flow estimation. Exp. Fluids, 45(4):595-608, 2008. PDF
  60. P. Héas, E. Mémin. 3D motion estimation of atmospheric layers from image sequences. IEEE Trans. on Geoscience and Remote Sensing, 46(8):2385-2396, 2008. PDF
  61. N. Papadakis, E. Mémin. Variational assimilation of fluid motion from image sequences. SIAM Journal on Imaging Science, 1(4):343-363, 2008. PDF
  62. N. Papadakis, E. Mémin. A variational technique for time consistent tracking of curves and motion. Journal of Mathematical Imaging and Vision, 31(1):81-103, 2008. PDF
  63. E. Arnaud, E. Mémin. Partial linear Gaussian models for tracking in image sequences using sequential Monte-Carlo methods. International Journal of Computer Vision, 74(1):75-102, 2007. PDF
  64. A. Cuzol, P. Hellier, E. Mémin. A low dimensional fluid motion estimator. International Journal of Computer Vision, 75(3):329-349, 2007. PDF
  65. J. D'Adamo, N. Papadakis, E. Mémin, G. Artana. Variational assimilation of POD low-order dynamical systems. Journal of Turbulence, 8(9):1-22, 2007. PDF
  66. P. Héas, E. Mémin, N. Papadakis, A. Szantai. Layered estimation of atmospheric mesoscale dynamics from satellite imagery. IEEE Trans. Geoscience and Remote Sensing, 45(12):4087-4104, 2007. PDF
  67. J. Yuan, C Schnörr, E. Mémin. Discrete orthogonal decomposition and variational fluid flow estimation. Journal of Mathematical Imaging and Vision, 28(1):67-80, 2007. PDF
  68. T. Corpetti, D. Heitz, G. Arroyo, E. Mémin, A. Santa Cruz. Fluid experimental flow estimation based on an optical-flow scheme. Exp. Fluids, 40(1):80-97, 2006. PDF
  69. E. Arnaud, E. Mémin, B. Cernuschi Frias. Conditional filters for image sequence based tracking - Application to point tracking. IEEE Trans. on Image Processing, 14(1):63-79, 2005. PDF
  70. T. Corpetti, E. Mémin, P. Pérez. Extraction of Singular Points from Dense Motion Fields: an Analytic Approach. Journal of Mathematical Imaging and Vision, 19(3):175-198, 2003. PDF
  71. I. Pratikakis, C. Barillot, P. Hellier, E. Mémin. Robust multiscale deformable registration of 3D Ultrasound images. International Journal of Image and Graphics, 3(4):547-566, 2003. PDF
  72. L. Oisel, E. Mémin, L. Morin, F. Galpin. 1D dense disparity estimation for 3D reconstruction. IEEE Trans. on Image Processing, 12(9):1107-1119, September 2003. PDF
  73. T. Corpetti, E. Mémin, P. Pérez. Dense Estimation of Fluid Flows. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(3):365-380, March 2002. PDF
  74. E. Mémin, P. Pérez. Hierarchical estimation and segmentation of dense motion fields. Int. Journal of Computer Vision, 46(2):129-155, February 2002. PDF
  75. P. Hellier, C. Barillot, E. Mémin, P. Pérez. Hierarchical estimation of a dense deformation field for 3D robust registration. IEEE Transaction on Medical Imaging, 20(5):388-402, May 2001. PDF
  76. E. Mémin, T. Risset. VLSI design methodoloy for edge-preserving image reconstruction. Real Time Imaging, 7(1):109-126, February 2001. PDF
  77. E. Mémin, T. Risset. On the study of VLSI derivation for optical flow estimation. Int. Journal of Pattern Recogition and Artificial Intelligence, 14(4):441-462, June 2000. PDF
  78. E. Mémin, P. Pérez. Optical flow estimation and object-based segmentation with robust techniques. IEEE Trans. on Image Processing, 7(5):703-719, May 1998. PDF
  79. E. Mémin, F. Heitz, F. Charot. Efficient parallel nonlinear multigrid relaxation algorithms for low-level vision applications. Journal of Parallel and Distributed Computing, 29:96-103, 1995. PDF

Academic Journals (National audience)

  1. T. Corpetti, V. Dubreuil, E. Mémin, O. Planchon, C. Thomas. Outils méthodologiques l'analyse d'images MSG : estimation du mouvement, suivi de masses nuageuses et détection de fronts. Revue Française de Photogrammétrie et de Télédétection, 2014.
  2. A. Cuzol, J-L. Marchand, E. Mémin. Image data assimilation with filtering methods. Journal de la Société Française de Statistique, 2014.
  3. P. Héas, D. Heitz, E. Mémin. La turbulence par l'image. La Recherche, 444, September 2010. PDF
  4. P. Hellier, C. Barillot, E. Mémin, P. Pérez. Estimation robuse 3D d'un champ de déformation pour le recalage non-linéaire inter-sujet d'images cérébrales. Traitement du signal, 17(2):99-112, 2000.

Book Chapters

  1. E. Mémin, P. Pérez. Motion estimation and visual tracking. In Inverse problems in vision and 3D tomography, A. Mohammad-Djafari (ed.), Chap. 6, pp. 191-249, Digital signal and image processing, Wiley, December 2009.
  2. E. Mémin, P. Pérez. Estimation de mouvement apparent et suivi visuel. In Problèmes Inverses en Imagerie et en Vision, A. Mohammad-Djafari (ed.), Vol. 1, Chap. 6, pp. 201-252, Traité IC2, Hermès, September 2009.

International Conferences

  1. A. Gronskis, D. Heitz and E. Mémin, A new hybrid algorithm for variational data assimilation of unsteady wake flow. 2nd Workshop on Data Assimilation & CFD Processing for Particle Image and Tracking Velocimetry, December 13 to 14, 217, Delft, The Netherlands
  2. Pranav Chandramouli, Dominique Heitz, Etienne Mémin, Sylvain Laizet Analysis of Models Under Location Uncertainty within the Framework of Coarse Large Eddy Simulation (cLES)", The 16th European Turbulence Conference, Stockholm, SE, 2017.
  3. V. Resseguier, E. Mémin, B. Chapron. Oceanic models under uncertainty. In CMG 2016 : 31st IUGG Conference on Mathematical Geophysics, Paris, 6-12 June 2016,.
  4. V. Resseguier, E. Mémin, B. Chapron. Likely chaotic transitions of large-scale fluid flows using a stochastic transport model. In 9th Chaos Modeling and Simulation International Conference (CHAOS2016), London, 23-26 May 2016,.
  5. V. Resseguier, E. Mémin, B. Chapron. Stochastic Reynolds theorem and generalized subgrid tensor . In 15th European Turbulence Conference, Delft, Netherlands. August 2015.
  6. V. Resseguier, E. Mémin, B. Chapron. Stochastic fluid dynamics model and dimensional reduction. In 9th Int. Symp. on Turbulence and Shear Flow Phenomena, TSFP-9, Melbourne, Australia, June 2015.
  7. S. Kadri Harouna, E. Mémin. Navier-Stokes simulation with f location uncertainty. In 8th Int. Symp. on Turbulence and Shear Flow Phenomena, TSFP-8, Poitiers, France, August 2013.
  8. I. Barbu, C. Herzet, C, E. Mémin. Joint Estimation of Volume and Velocity in TomoPIV. In 10TH INTERNATIONAL SYMPOSIUM ON PARTICLE IMAGE VELOCIMETRY - PIV13, Delft, The Netherlands, July 2013. PDF
  9. A. Gronskis, C. Robinson, D. Heitz, E. Mémin. A 4DVar PIV-data assimilation for flow spatio-temporal reconstruction. In 10TH INTERNATIONAL SYMPOSIUM ON PARTICLE IMAGE VELOCIMETRY - PIV13, Delft, The Netherlands, July 2013.
  10. S. D. Mayor, P. Dérian, C. F. Mauzey, T. Henry, E. Mémin, M. Hamada, D. Scott. Two-component wind fields from scanning aerosol lidar and motion estimation algorithms. In WindPower 2013, Chicago IL, May 2013.
  11. S. Gorthi, S. Beyou, E. Mémin. Analysis of SST Images by Weighted Ensemble Transform Kalman Filter. In IEEE Int. Geoscience and Remote sensing symposium (IGARSS'11), 2011.
  12. S. Gorthi, S. Beyou, T. Corpetti, E. Mémin. Multiscale Weighted Ensemble Kalman Filter for Fluid Flow Estimation. In Scale Space Methods and Variational Methods (SSVM) in Computer Vision, 2011.
  13. T. Corpetti, E. Mémin. Stochastic models for local optical flow estimation. In Scale Space and Variational Methods in Computer Vision, SSVM'11, 2011.
  14. B. Combès, A. Guibert, E. Mémin, D. Heitz. Free-surface flows from Kinect: feasability and limits. In FVR2011, Poitiers, France, December 2011. PDF
  15. I. Barbu, C. Herzet, E. Mémin. Sparse models and pursuit algorithms for PIV Tomography. In Forum on recent developments in Volume Reconstruction techniques applied to 3D fluid and solid mechanics, Poitiers, France, November 2011. PDF
  16. P. Dérian, P. Héas, C. Herzet, E. Mémin. Wavelets to reconstruct turbulence multifractals from experimental image sequences. In 7th Int. Symp. on Turbulence and Shear Flow Phenomena, TSFP-7, Ottawa, Canada, July 2011. PDF
  17. A. Gronskis, D. Heitz, E. Mémin. Inflow and initial conditions for direct numerical simulation based on adjoint data assimilation. In 7th Int. Symp. on Turbulence and Shear Flow Phenomena, TSFP-7, Ottawa, Canada, July 2011. PDF
  18. P. Héas, C. Herzet, E. Mémin. Robust optic-flow estimation with Bayesian inference of model and hyper-parameters. In Proc. Conf. Scale-Space and Variational Meth. (SSVM'11), Israel, June 2011. PDF
  19. P. Dérian, P. Héas, C. Herzet, E. Mémin. Wavelet-based fluid motion estimation. In Scale Space Methods and Variational Methods (SSVM) in Computer Vision, Israel, June 2011. PDF
  20. C. Avenel, E. Mémin, P. Pérez. Stochastic filtering of level sets for curve tracking. In International Conference on Pattern Recognition (ICPR'10), Istanbul, Turkey, 2010.
  21. P. Dérian, P. Héas, E. Mémin, S. Mayor. Dense motion estimation from eye-safe aerosol lidar data. In International Laser Radar Conference, ILRC, St Petersbourg, Russia, 2010. PDF
  22. S.D. Mayor, C. Chico, P. Dérian, P. Héas, E. Mémin. Two-component horizontal motion vectors from scanning eye-safe aerosol lidar. In 19th Symposium on Boundary Layers and Turbulence, Poster presentation, Keystone, USA, August 2010. PDF
  23. C. Avenel, E. Mémin, P. Pérez. Tracking levels representation driven by a stochastic dynamics. In 7th International Conference on Curves and Surfaces, Poster presentation, Avignon, France, June 2010.
  24. P. Héas, D. Heitz, E. Mémin. Evidence of turbulence power laws from image data. In International Conference and Advanced School "Turbulent Mixing and Beyond", The Abdus Salam International Centre for Theoretical Physics, Trieste, Italy, 2009.
  25. C. Thomas, T. Corpetti, E. Mémin. Data Assimilation for Convective Cells Tracking in MSG images. In IEEE Int. Geoscience and Remote Sensing Symp, IGARSS '09, Cape Town, South Africa, 2009.
  26. P. Héas, E. Mémin, D. Heitz, P.D. Mininni. Bayesian selection of scaling laws for motion modeling in images. In International Conference on Computer Vision (ICCV'09), Kyoto, Japan, October 2009. PDF
  27. P. Héas, D. Heitz, E. Mémin. Multiscale regularization based on turbulent kinetic energy decay for PIV estimations with high spatial resolution. In 8th Int. Symposium on Particle Image Velocimetry (PIV09), Melbourne, Australia, August 2009. PDF
  28. P. Héas, E. Mémin. Inference on Gibbs optic flow prior : application to atmospheric turbulence. In Proc. Conf. IEEE International geoscience and remote sensing symposium (IGARSS'09), Cap Town, South Africa, July 2009. PDF
  29. C. Avenel, E. Mémin, P. Pérez. Tracking closed curves with non-linear stochastic filters. In Conf. on Scale Space and Variational Methods (SSVM'09), Voss, Norway, June 2009. PDF
  30. P. Héas, E. Mémin, D. Heitz. Self-similar regularization of optic-flow for turbulent motion estimation. In Proc. ECCV'08, Int Workshop on Machine Learning for Vision-based Motion Analysis, Marseille, France, 2008. PDF
  31. T. Corpetti, P. Héas, E. Mémin, N. Papadakis. Variational pressure image assimilation for atmospheric motion estimation. In Proc. Int. Geoscience and Remote Sensing Symp. (IGARSS'08), Volume 2, Pages 505-508, Boston, MA, July 2008.
  32. P. Héas, E. Mémin. Optical-flow for 3D atmospheric motion estimation. In Proc. Int. Conf. on Computer Vision Theory and Applications (VISAPP'08), Volume 2, Pages 399-406, Funchal, Portugal, January 2008.
  33. N. Papadakis, P. Héas, E. Mémin. Image assimilation for motion estimation of atmospheric layers with shallow-water model. In Proc. Asian. Conf. Comp. Vis. (ACCV'07), Tokyo, Japan, November 2007. PDF
  34. N. Papadakis, E. Mémin. Variational optimal control technique for the tracking of deformable objects. In Proc. Int. Conf. Comp. Vis.(ICCV'07), Pages 1-7, Rio de Janeiro, Brazil, October 2007. PDF
  35. N. Papadakis, T. Corpetti, E. Mémin. Dynamically consistent optical flow estimation. In Proc. Int. Conf. Comp. Vis.(ICCV'07), Pages 1-7, Rio de Janeiro, Brazil, October 2007. PDF
  36. P. Héas, K. Krissian, E. Mémin, A. Szantai. Reconstruction and visualization of 3D wind fields from satellite image sequences. In 15th Satellite Meteorology and Oceanography Conf. of the American Meteorological Soc, Pages 1-8, Amsterdam, The Netherlands, September 2007. PDF
  37. P. Héas, N. Papadakis, E. Mémin, A. Szantai. Motion estimation of 2D atmospheric layers from satellite image sequences. In 15th Satellite Meteorology and Oceanography Conf. of the American Meteorological Soc, Pages 1-8, Amsterdam, The Netherlands, September 2007.
  38. D. Heitz, P. Héas, V. Navaza, J. Carlier, E. Mémin. Spatio-temporal correlation-variational approach for robust optical flow estimation. In Symposium on Particle Image Velocimetry (PIV'07), Pages 1-9, Roma, Italy, September 2007. PDF
  39. N. Papadakis, P. Héas, E. Mémin. Motion estimation of 2D atmospheric layers with variational assimilation techniques. In 15th Satellite Meteorology and Oceanography Conf. of the American Meteorological Soc, Pages 1-8, Amsterdam, The Netherlands, September 2007.
  40. T. Corpetti, N. Papadakis, E. Mémin. Dense estimation of motion fields on Meteosat Second Generation images using a dynamical consistency. In IEEE Int. Geoscience and Remote Sensing Symp.(IGARSS'07), Pages 4749-4752, Barcelona, Spain, July 2007.
  41. P. Héas, E. Mémin, N. Papadakis. A consistent spatio-temporal motion estimator for atmospheric layers. In Proc. Conf. Scale-Space and Variational Meth. (SSVM'07), Pages 251-263, Ischia, Italy, June 2007. PDF
  42. 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. PDF
  43. N. Papadakis, E. Mémin, T. Corpetti. Variational estimation of 2D time consistent dense motion from image sequence. In Proc. Eur. Geoscience Union, Nonlinear Processes in Geophysics, Data Assimilation in the Presence of Nonlinearities, Vienna, Austria, April 2007.
  44. R. Sosa, E. Arnaud, E. Mémin, G. Artana. Schlieren image velocimetry applied to EHD flows. In Int. Symposium on Electrohydrodynamics, Pages 1-4, Buenos-Aires, Argentina, 2006.
  45. P. Héas, E. Mémin, N. Papadakis. Dense estimation of layer motions in the atmosphere. In Int. Conf. Pattern Recognition (ICPR'06), Volume 3, Hong-Kong, China, August 2006. PDF
  46. E. Arnaud, E. Mémin, R. Sosa, G. Artana. A fluid motion estimator for Schlieren imaging velocymetry. In Proc. European Conf. Comp. Vision (ECCV'06), Volume 3951 (LNCS), Pages 198-210, Graz, Austria, May 2006. PDF
  47. A. Szantai, P. Héas, E. Mémin. Comparison of atmospheric motion vectors and dense vector fields calculated from MSG images. In Proc. Int. Winds Workshop, Beijing, China, April 2006.
  48. E. Arnaud, B. Fauvet, E. Mémin, P. Bouthemy. A robust and automatic face tracker dedicated to broadcast videos. In Proc. Int. Conf. on Image Processing (ICIP'05), Genova, Italy, 2005.
  49. A. Cuzol, E. Mémin. Vortex and source particles for fluid motion estimation. In 5th Int. Conf. on Scale-Space and PDE methods in Computer Vision (Scale-Space'05), Hofgeismar, Germany, Volume 3459, Pages 254-266, Hofgeismar, Germany, 2005.
  50. J. Yuan, P. Ruhnau, E. Mémin, C. Schnörr. Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation. In 5th Int. Conf. on Scale-Space and PDE methods in Computer Vision (Scale-Space'05), Hofgeismar, Germany, Volume 3459, Pages 267-278, Hofgeismar, Germany, 2005.
  51. A. Cuzol, E. Mémin. A stochastic filter for fluid motion tracking. In Proc. Int. Conf. on Computer Vision (ICCV'05), Pages 396-402, Beijing, China, October 2005. PDF
  52. N. Papadakis, E. Mémin, F. Cao. A variational approach for object contour tracking. In Proc. ICCV'05 Workshop on Variational, Geometric and Level Set Methods in Computer Vision, Pages 259-270, Beijing, China, October 2005.
  53. E. Arnaud, E. Mémin. An efficient Rao-Blackwellised particle filter for object tracking. In Proc. Int. Conf. on Image Processing (ICIP'05), Genova, Italy, September 2005.
  54. D. Heitz, J. Carlier, E. Mémin. Fluid dedicated Optical-flow scheme. In PIVChallenge 05, Pasadena, USA, September 2005.
  55. A. Cuzol, P. Hellier, E. Mémin. A novel parametric method for non-rigid image registration. In Proc. Information Processing in Medical Imaging (IPMI'05), G. Christensen, M. Sonka (eds.), LNCS, Pages 456-467, Glenwood Springes, Colorado, USA, July 2005.
  56. T. Corpetti, D. Heitz, G. Arroyo, E. Mémin, A. Santa Cruz. Estimation of motion using a PIV correlation-based method and an optical-flow one for two experimental flows: quantitative and qulitative comparison. In 12th International symposium Applications of laser techniques to fluid mechanics, Lisbon, Portugal, 2004.
  57. F. Lauze, P. Kornprobst, E. Mémin. A coarse to fine multiscale approach For linear least square based optical flow estimation. In Proc. British Machine Vision Conference, London, U.-K, September 2004. PDF
  58. E. Arnaud, E. Mémin. Optimal importance sampling for tracking in image sequences:application to point tracking. In European Conference on Computer Vision, ECCV'04, Volume 3023, Pages 302-314, Prague, Czech Republic, May 2004. PDF
  59. E. Arnaud, E. Mémin, B. Cernushi Frias. A robust stochastic filter for point tracking in image sequences. In Asian Conference on Computer Vision (ACCV'04), Jeju Island, Korea, January 2004.
  60. T. Kohlberger, E. Mémin, C. Schnörr. Variational dense motion estimation using a DIV-CURL higher order regularization. In Int. Symp. on Signal Processing and Its Applications, ISSPA'03, Paris, France, 2003.
  61. T. Corpetti, E. Mémin, A. Santa-Cruz, D. Heitz, G. Arroyo. Optical flow estimation in experimental fluid mechanics. In Seventh Int. Symp. on Signal Processing and its Applications, ISSPA'03, Paris, France, July 2003.
  62. T. Kohlberger, E. Mémin, C. Schnörr. Variational dense motion estimation using the Helmholtz decomposition. In Scale Space 03, L.D. Griffin, M. Lillholm (eds.), Lecture notes in computer science, Volume 2695, Pages 432-448, Isle of Skye, UK, June 2003.
  63. T. Corpetti, E. Mémin, P. Pérez. Dense Motion Analysis in Fluid Imagery. In Eur. Conf. on Computer Vision, ECCV'2002, LNCS 2350, Pages 676-691, Copenhagen, Denmark, May 2002. PDF
  64. T. Corpetti, E. Mémin, P. Pérez. Estimating fluid optical flow. In IAPR Int. Conf. on Pattern Recognition, ICPR 2000, Volume 3, Pages 1045-1049, Barcelone, Espagne, September 2000.
  65. T. Corpetti, E. Mémin, P. Pérez. Adaptation of standard optic methods to fluid motion. In Int. Symposium on Flow Visualization, paper 62, Pages 1-10, Edinburgh, Scotland, August 2000.
  66. P. Hellier, C. Barillot, E. Mémin, P. Pérez. An energy-based framework for dense 3D registration of volumetric brain image. In IEEE Conf. Computer Vision and Pattern Recognition, CVPR'2000, Volume II, Pages 270-275, Hilton Head Island, South Carolina, USA, June 2000. PDF
  67. L. Oisel, E. Mémin, L. Morin. Geometric Driven Optical Flow Estimation and Segmentation for 3D Reconstruction. In European Conference on Computer Vision, ECCV 2000, LNCS 1843, Volume 2, Pages 849-863, Dublin, Irland, June 2000.
  68. C. Papin, P. Bouthemy, E. Mémin, G. Rochard. Tracking and Characterization of Highly Deformable Cloud Structures. In European Conference on Computer Vision, ECCV 2000, LNCS 1843, Volume 2, Pages 428-442, Dublin, Irland, June 2000.
  69. A. Szantai, F. Desalmand, M. Desbois, P. Lecomte, E. Mémin, S. Zimeras. Tracking low-level clouds over Central Africa on Meteosat image. In 2000 EUMETSAT Meteorological Satellite Data Users' Conference, Pages 813-820, Bologna, Italy, May 2000.
  70. E. Mémin, P. Pérez. Dense/parametric estimation of fluid flows. In IEEE Int. Conf. on Image Processing, ICIP'99, Kobe, Japan, October 1999.
  71. P. Hellier, C. Barillot, E. Mémin, P. Pérez. Medical image registration with robust multigrid techniques. In Proc. of the 2nd Int. Conf. on Medical Image Computing and Computer-Assisted Intervention, MICCAI, C. Taylor, A. Colchester (eds.), Lecture Notes in Computer Science, Volume 1679, Pages 680-687, September 1999.
  72. E. Mémin, P. Pérez. Fluid motion recovery by coupling dense and parametric fields. In IEEE Int. Conf. on Computer Vision, ICCV'99, Volume 1, Pages 620-625, Kerkira, Greece, September 1999. PDF
  73. C. Papin, P. Bouthemy, E. Mémin, G. Rochard. Tracking and characterization of convective clouds from satellite images. In 1999 Eumetsat Meteorological Satellite Data User's Conference, Copenhague, Danemark, September 1999. PDF
  74. L. Oisel, L. Morin, E. Mémin, C. Labit. Planar facets segmentation using a multiresolution dense disparity field estimation. In Int. Conf. on Image Processing (ICIP'98), Volume 2, Pages 617-621, Chicago, Illinois, October 1998.
  75. E. Mémin, P. Pérez. Joint estimation-segmentation of optic flow. In Proc. of the 5th European Conf. on Computer Vision, ECCV'98, Volume 2, Pages 563-580, Freiburg, Germany, June 1998. PDF
  76. E. Mémin, P. Pérez. A multigrid approach to hierarchical motion estimation. In Proc. Int. Conf. on Computer Vision, ICCV'98, Pages 933-938, Bombay, India, January 1998. PDF
  77. L. Oisel, E. Mémin, L. Morin, C. Labit. Epipolar constrained motion estimation for reconstruction from video sequences. In Spie Conf. on Visual Communications and Image Processing, VCIP, Volume 3309, San-Jose, California, January 1998.
  78. P. Piscaglia, B. Macq, E. Mémin, P. Pérez, L. Labit. Parallelized robust multiresollution motion estimation. In Proc. 3rd IEEE Int. Conf. Image Processing, Lausanne, Switzerland, September 1996.
  79. E. Mémin, P. Pérez. Robust discontinuity-preserving model for estimating optical flow. In Proc. 13th Int. Conf. Pattern Recognition, ICPR96, Vienna, Austria, August 1996.
  80. E. Mémin, F. Heitz, F. Charot. Efficient parallel multigrid relaxation algorithms for MRF-based low level vision applications. In IEEE Conf. Computer Vision and Pattern Recognition, Seattle, Washington, June 1994.
  81. E. Mémin, F. Charot, F. Heitz. Parallel architecture for multiscale Markov Random Field-based image analysis. In Computer Architecture for Machine Perception (CAMP'91), B. Zavidovique, P.L. Wendel (eds.), Pages 309-320, Paris, France, December 1991.
  82. F. Heitz, E. Mémin, P. Bouthemy. Markov Random Fields and Parallel Algorithms for 2D Motion Analysis. In Imacs World Congress on Computation and Applied Mathematics, Dublin, Ireland, January 1991.

Invited Conferences

  1. E. Mémin. Stochastic transport to track closed curves through image data. In Classical and Modern Results in Nonlinear Filtering and Applications, Imperial College London, November 2018, GB.
  2. V. Resseguier, E. Mémin, B. Chapron . Uncertainty quantification and ensemble forecast in coarse-grid or dimensionally-reduced computational fluid dynamics, In ECCM - ECFD 2018 - 6th European Conference on Computational Mechanics - 7th European Conference on Computational Fluid Dynamics. Glasgow, GB.
  3. E. Mémin. Stochastic transport for large-scale fluid flow dynamics representation. In Particle methods and data assimilation, Imperial College London, May 2018, GB.
  4. E. Mémin. Stochastic geophysical flow representation. Center for Earth System Research and Sustainability, Hamburg, December 2017, Ger.
  5. E. Mémin. Stochastic geophysical flow representation. Mathematics for planet earth, Imperial College London, November 2017, GB.
  6. E. Mémin. Stochastic geophysical flow representation. Comodo workshop, Grenoble, December 2017, Fr.
  7. E. Mémin. Fluid dynamics under uncertainty. In Labex CIMI - Trimestre EDP & Probabilités, Toulouse, France, January 2014.
  8. E. Mémin. Fluid flow analysis from image sequences. In Labex CIMI - Trimestre EDP & Probabilités, Toulouse, France, January 2014.
  9. E. Mémin. Fluid dynamics under uncertainty. In workshop "2D to 3D Ocean Dynamics from Space" Ifremer, Brest, France, 2013.
  10. E. Mémin. Assimilation d'images satellites océaniques: filtrage stochastique et définition de dynamiques adaptées. In Colloque Gretsi de traitment du signal et des images, Brest, France, 2013.
  11. E. Mémin. Fluid flow velocity measurements from image sequences. In 51st AIAA Aerospace Sciences Meeting, 2013.
  12. E. Mémin. In Seminar LFD-FIUBA, Buenos Aires, Argentina, November 2012.
  13. E. Mémin. In Workshop on Tolopology in Fluid flow visualization, Pisa, Italy, June 2012.
  14. E. Mémin. In "Conf'luences" IMFT, Toulouse, France, April 2012.
  15. E. Mémin. Filtrage particulaire pour l'analyse d'écoulements à partir de séquence d'images. In Journée thématique LEFE "Assimilation et incertitudes", ENS Paris, Paris, France, February 2012.
  16. R. Tatsambon Fomena, C. Collewet, E. Mémin. A New approach for Fluid Flows control. In Symposium on Advances in Control of Fluid Dynamics and Challenges facing the US Defense Department's thrust on Unmanned Autonomous Systems for the SIAM Conference on Control and Its Applications, Baltimore, USA, July 2011.
  17. E. Mémin. In Séminaire LIMSI Analyse d'écoulements fluides à partir d'images, Paris, France, May 2011.
  18. E. Mémin. In Séminaire Météo-France Filtrage et assimilation de données images, Toulouse, France, May 2010.
  19. E. Mémin. Analyse d'écoulements fluides à partir d'images. In Séminaire ENSPS Strasbourg, Strasbourg, France, February 2010.
  20. E. Mémin. Méthodes variationnelles pour l'analyse d'écoulements fluides à partir d'images. In Séminaire en l'honneur de F.-X. Le Dimet, Grenoble, France, March 2009.

National Conferences

  1. Pranav Chandramouli, Dominique Heitz, Etienne Mémin, Sylvain Laizet A Comparative Study of LES Models Under Location Uncertainty, Congrès Français de Mécanique, Lille, 2017.
  2. R. Schuster, D. Heitz, E. Mémin, A. Guibert, P. Loisel, Modèle d'observation stochastique pour la mesure du mouvement grand champ, 23ième Congrès Français de Mécanique, Lille, 2017.
  3. I. Barbu, C. Herzet, C, E. Mémin. Estimation 3D jointe des volumes et des vitesses pour la Tomographie PIV. In 15ème Congres Français de Visualisation et de Traitement d'Images en Mécanique des Fluides, Orléans, France, November 2013. PDF
  4. S. Beyou, A. Cuzol, S. Gorthi, E. Mémin. Assimilation de température de surface par filtre de Kalman de transformation d'ensemble pondéré. In XXIII colloque GRETSI, 2011.
  5. D. Heitz, P. Héas, E. Mémin. Apport des modèles de lois de puissance pour l'estimation du mouvement turbulent en PIV. In 20ème congrès français de mécanique, Besançon, France, 2011. PDF
  6. I. Barbu, C. Herzet, E. Mémin. Représentation et algorithmes parcimonieux pour la Tomographie PIV. In 14ème Congres Français de Visualisation et de Traitement d'Images en Mécanique des Fluides, Lille, France, November 2011. PDF
  7. V. Souchaud, C. Herzet, E. Mémin. Construction d'une base de type POD à partir d'une séquence d'images. In GRETSI, Bordeaux, France, September 2011. PDF
  8. J. Carlier, N. Papadakis, E Mémin. Assimilation variationnelle de données dans un système dynamique d'ordre réduit. In 19ème Congrès Français de Mécanique, Marseille, France, 2009. PDF
  9. N. Papadakis, E. Mémin. Estimation variationnelle et cohérente en temps de mouvements fluides. In Congrès Francophone de Reconnaissance des Formes et Intelligence Artificielle (RFIA'08), Pages 1-8, Amiens, January 2008.
  10. D. Heitz, P. Héas, V. Navaza, J. Carlier, E. Mémin. Collaboration corrélation-variationnelle pour une estimation robuste du flot-optique. In 18ème Congrès Français de Mécanique (CFM), Pages 1-7, Grenoble, August 2007. PDF
  11. N. Papadakis, E. Mémin, J. D'adamo, G. Artana. Assimilation variationelle de systèmes dynamiques d'ordre faible. In 3e Congrès national de mathématiques appliquées et industrielles (SMAI 2007), Grenoble, France, June 2007.
  12. N. Papadakis, A. Cuzol, E. Mémin. Suivi du mouvement fluide: approche stochastique et variationnelle. In Proc. Journées AUM/AFM, Pages 117-122, La Rochelle, September 2006.
  13. A. Cuzol, E. Mémin. Suivi de mouvement fluide par filtrage stochastique. In Congrès Francophone de Reconnaissance des Formes et Intelligence Artificielle (RFIA'06), Pages 1-8, Tours, January 2006.
  14. N. Papadakis, E. Mémin. Une approche variationelle pour le suivi de contours. In Proc. Congrès Francophone de Reconnaissance des Formes et Intelligence Artificielle (RFIA'06), Pages 1-8, Tours, January 2006.
  15. D. Heitz, T. Corpetti, J. Carlier, G. Arroyo, E. Mémin. Évaluation d'un estimateur de flot optique dédié aux écoulements. In 11ème Congrès de Visualisation et de Traitement d'Images en Mécanique des Fluides - FLUVISU 11, Ecully, France, June 2005. PDF
  16. E. Arnaud, E. Mémin, B. Cernushi Frias. Filtrage conditionnel pour la trajectographie dans des séquences d'images - Application au suivi de points. In 14ème Congrès Francophone AFRIF-AFIA de Reconnaissance des Formes et Intelligence Artificielle (RFIA'04), Toulouse, France, January 2004.
  17. T. Corpetti, E. Mémin, P. Pérez. Régularisation Div-Curl et Équation de Continuité pour l'Estimation du Mouvement Fluide. In 13ème Congrès Francophone AFRIF-AFIA de Reconnaissance des Formes et Intelligence Artificielle, RFIA 2002, Volume 3, Pages 887-898, Angers, France, January 2002.
  18. T. Corpetti, E. Mémin, P. Pérez. Estimation dense du mouvement en imagerie fluide. In 9ème colloque francophone de visualisation et de traitement d'images en mécanique des fluides, FLUVISU'2001, Rouen, June 2001.
  19. C. Papin, P. Bouthemy, E. Mémin. Suivi de l'activité convective de cellules nuageuses dans des séquences d'images satellitaires. In 12ème Congrès Reconnaissance des Formes et Intelligence Artificielle, RFIA'2000, Volume 1, Pages 369-378, Paris, February 2000.
  20. P. Hellier, C. Barillot, E. Mémin, P. Pérez. Recalage d'images cérébrales par estimation robuste contextuelle du flot optique. In 17eme Colloque Gretsi sur le traitement du signal et des images, Volume 4, Pages 1077-1080, Vannes, September 1999.
  21. E. Mémin, P. Pérez. Estimation conjointe de champs de vitesse denses et paramétriques pour des écoulement fluides. In 17eme Colloque Gretsi sur le traitement du signal et des images, Volume 2, Pages 247-250, Vannes, September 1999.
  22. L. Oisel, L. Morin, E. Mémin, C. Labit. Reconstruction 3D de scènes complexes par maillage de cartes de disparité. In 17eme Colloque Gretsi sur le traitement du signal et des images, Volume 2, Pages 391-394, Vannes, September 1999.
  23. E. Mémin, P. Pérez. Champ de Markov multirésolution et algorithme multigrille pour l'estimation du mouvement. In Proc. 15ème Colloque GRETSI, Juan-les-Pins, France, September 1995.
  24. E. Mémin, F. Heitz, F. Charot. Algorithmes parallèles pour les champs markoviens multiéchelles: spécification et mise en oeuvre sur une architecture SIMD. In 14ème congrès Gretsi, Juan-les-Pins, France, September 1993.
  25. E. Mémin, F. Heitz. Parallélisation des algorithmes d'analyse d'images par champs markoviens dans un contexte pyramidal. In 13ème congrès Gretsi, Juan-les-Pins, France, September 1991.

Research Reports

  1. P. Dérian, P. Héas, C. Herzet, E. Mémin. Wavelet Expansion and High-order Regularization for Multiscale Fluid-motion Estimation. Research Report INRIA, No 7348, 2010. PDF
  2. P. Héas, E. Mémin, D. Heitz, P.D. Mininni. Turbulence power laws and inverse motion modeling in images. Research Report INRIA, 2009. PDF
  3. T. Corpetti, P. Héas, E. Mémin, N. Papadakis. Pressure image assimilation for atmospheric motion estimation. Research Report INRIA, 2008. PDF
  4. P. Héas, N. Papadakis, E. Mémin. Time-consistent estimators of 2D/3D motion of atmospheric layers from pressure images. Research Report INRIA, No 6292, September 2007. PDF
  5. N. Papadakis, E. Mémin. A variational method for joint tracking of curve and motion. Research Report INRIA, No 6283, September 2007. PDF
  6. N. Jain, E. Mémin, C. Pérez. Parallelization of Dense Fluid Motion Estimation Application using OpenMP. Research Report INRIA, No 4556, September 2002. PDF
  7. T. Corpetti, E. Mémin, P. Pérez. Dense fluid flow estimation. Research Report INRIA, No 4009, September 2000. PDF
  8. P. Hellier, C. Barillot, E. Mémin, P. Pérez. Estimation robuste 3D d'un champ de déformation pour le recalage non-linéaire inter-sujet d'images cérébrales. Research Report INRIA, No 3812, November 1999. PDF
  9. E. Mémin, T. Risset. Hardware driven considerations for energy based applications. Research Report IRISA, No 1220, April 1999. PDF
  10. E. Mémin, P. Pérez. Semi-parametric estimation and segmentation of optic flow. Research Report Irisa, No 1197, July 1998. PDF
  11. E. Mémin, P. Pérez. Adaptative multigrid and variable parameterization for optical-flow estimation. Research Report INRIA, No 3102, January 1997. PDF
  12. E. Mémin, P. Pérez, D. Machecourt. Dense estimation and object-based segmentation of the optical flow with robust techniques. Research Report INRIA, No 2836, March 1996. PDF
  13. E. Mémin, F. Heitz, F. Charot. Efficient parallel non-linear multigrid relaxation algorithms for low-level vision applications. Research Report INRIA, No 2184, April 1994. PDF

Misc

  1. A. Cuzol, E. Mémin. Image assimilation with the weighted ensemble Kalman filter. 9th International Workshop on Adjoint Model Applications in Dynamic Meteorolog, Cefalu, Sicily, Italy, October 2011.
  2. D. Heitz, P. Héas, J. Carlier, T. Corpetti, N. Papadakis, E. Mémin. Estimation du flot optique dans les écoulements turbulents. GdR Turbulence "Couplage modèle donnés", Cemagref, Rennes, France, 2008.
  3. P. Héas, D. Heitz, E. Mémin. Cascade d'énergie comme a priori pour l'estimation du flot optique. GdR Turbulence "Couplage modèle donnés", Cemagref, Rennes, France, 2008.
  4. C. Tilmant, L. Sarry, Th. Corpetti, P. Motrefi, E. Geoffroy, J.-R. Lusson, E. Mémin, J.-Y. Boire. Suivi d'objets pour l'analyse du mouvement en imagerie ultrasonore. Congrès Jeunes Chercheurs en Vision par Ordinateur (ORASIS'05), Fournols, France, May 2005.
  5. E. Arnaud, E. Mémin, B. Cernushi Frias. Filtrage conditionnel pour le suivi de points dans des séquences d'images. Congrès Francophone de Vision par Ordinateur, ORASIS'03, pp. 211-220, Gerardmer, France, May 2003.
  6. T. Corpetti, E. Mémin, P. Pérez. Estimation de mouvement fluide basée sur l'équation de continuité associée à une régularisation Div-Curl. Actes des journées francophones des jeunes chercheurs en analyse d'images et perception visuelle, ORASIS'2001, pp. 481-490, Cahors, June 2001.
  7. F. Desalmand, M. Desbois, P. Leconte, A. Szantai, E. Mémin, P. Pérez, S. Zimeras. Calculation of low level winds over land. February 2000.
  8. P. Hellier, C. Barillot, E. Mémin, P. Pérez. Recalage d'images cérébrales par estimation robuste contextuelle du flot optique. ORASIS'99, Actes des journées francophones des jeunes chercheurs en analyse d'images et perception visuelle, pp. 85-91, Aussois, France, April 1999.
  9. C. Papin, P. Bouthemy, E. Mémin, G. Rochard. Détection, suivi et caractérisation des nuages convectifs à partir d'images satellitaires. ORASIS'99, Actes des journées francophones des jeunes chercheurs en analyse d'images et perception visuelle, pp. 51-60, Aussois, France, April 1999.

PhD Thesis

  1. E. Mémin. Estimation du flot optique : contribution et panorama de différentes approches. Habilitation à diriger des recherches Université de Rennes 1, July 2003.
  2. E. Mémin. Algorithmes et architectures parallèles pour les approches markoviennes en analyse d'images. PhD Thesis Université de Rennes 1, Informatique, June 1993.

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