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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.
  • 9E. Mémin.

    Fluid flow dynamics under location uncertainty, in: Geophysical & Astrophysical Fluid Dynamics, 2014, vol. 108, no 2, pp. 119-146.

    http://dx.doi.org/10.1080/03091929.2013.836190
  • 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, pp. 81–103.

    http://www.irisa.fr/fluminance/publi/papers/Papadakis-Memin-JMIV07.pdf
  • 11J. Yuan, C. Schnoerr, E. Mémin.

    Discrete orthogonal decomposition and variational fluid flow estimation, in: J. Mathematical Imaging and Vision, 2007, vol. 28, no 1, pp. 67–80.
Publications of the year

Articles in International Peer-Reviewed Journals

  • 12B. Combès, D. Heitz, A. Guibert, E. Mémin.

    A particle filter to reconstruct a free-surface flow from a depth camera, in: Fluid Dynamics Research, October 2015, vol. 47, no 5. [ DOI : 10.1088/0169-5983/47/5/051404 ]

    https://hal.archives-ouvertes.fr/hal-01223693
  • 13D. Queiros-Conde, J. Carlier, L. Grosu, M. Stanislas.

    Entropic-Skins Geometry to Describe Wall Turbulence Intermittency, in: Entropy, 2015, vol. 17, no 4, pp. 2198-2217. [ DOI : 10.3390/e17042198 ]

    https://hal.archives-ouvertes.fr/hal-01233501
  • 14V. Resseguier, E. Mémin, B. Chapron.

    Reduced flow models from a stochastic Navier-Stokes representation, in: Annales de l'ISUP, 2015.

    https://hal.inria.fr/hal-01215301
  • 15Y. Yang, C. Robinson, D. Heitz, E. Mémin.

    Enhanced ensemble-based 4DVar scheme for data assimilation, in: Computers and Fluids, 2015, 15 p. [ DOI : 10.1016/j.compfluid.2015.03.025 ]

    https://hal.inria.fr/hal-01144923

International Conferences with Proceedings

  • 16V. Resseguier, E. Mémin, B. Chapron.

    Stochastic Fluid Dynamic Model and Dimensional Reduction, in: International Symposium on Turbulence and Shear Flow Phenomena (TSFP-9), Melbourne, Australia, June 2015.

    https://hal.inria.fr/hal-01238301
  • 17V. Resseguier, E. Mémin, B. Chapron.

    Stochastic Reynolds theorem and generalized subgrid tensor, in: 15th European Turbulence Conference 2015, Delft, Netherlands, August 2015.

    https://hal.inria.fr/hal-01238281

Conferences without Proceedings

  • 18I. Barbu, C. Herzet.

    A Fast and Sparsity-Aware Generalization of SMART for Tomographic Particle Image Velocimetry, in: Signal Processing with Adaptive Sparse Structured Representations, Cambridge, United Kingdom, July 2015.

    https://hal.inria.fr/hal-01245022
  • 19I. Barbu, C. Herzet.

    A New Approach for Volume Reconstruction in TomoPIV with the Alternating Directions Method of Multipliers, in: The 11th International Symposium on Particle Image Velocimetry, Santa Barbara, United States, September 2015.

    https://hal.inria.fr/hal-01245009
  • 20I. Barbu, C. Herzet.

    Accelerated, Sparsity-Aware Generalizations of Classical Algorithms for TomoPIV, in: The 11th International Symposium on Particle Image Velocimetry, Santa Barbara, United States, September 2015.

    https://hal.inria.fr/hal-01245014
  • 21P. Héas, C. Herzet.

    Inverse Reduced-Order Modeling, in: Reduced Basis, POD and PGD Model Reduction Techniques, Cachan, France, November 2015.

    https://hal.inria.fr/hal-01245051
  • 22V. Resseguier, M. Etienne, B. Chapron.

    Reduced order model from a new stochastic decomposition of fluid flow, in: UNCECOMP International Conference on Uncertainty Quantification in Computational Sciences and Engineering, Hersonissos, Greece, May 2015.

    https://hal.inria.fr/hal-01238289

Other Publications

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