R. Adrian, Particle-Imaging Techniques for Experimental Fluid Mechanics, Annual Review of Fluid Mechanics, vol.23, issue.1, pp.261-304, 1991.
DOI : 10.1146/annurev.fl.23.010191.001401

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.5404

A. Amini, A scalar function formulation for optical flow, Proceedings Europ Conf Computer Vision, pp.125-131, 1994.
DOI : 10.1007/3-540-57956-7_13

L. Bannehr, R. Rohn, and G. Warnecke, A functional analytic method to derive displacement vector fields from satellite image sequences, International Journal of Remote Sensing, vol.17, issue.2, pp.383-392, 1996.
DOI : 10.1109/36.124227

J. Barron, D. Fleet, and S. Beauchemin, Performance of optical flow techniques, International Journal of Computer Vision, vol.54, issue.1, pp.43-77, 1994.
DOI : 10.1007/BF01420984

D. Be´re´ziatbe´re´be´re´ziat, I. Herlin, and L. Younes, A generalized optical flow constraint and its physical interpretation, Proceedings Conf Comp Vision Pattern Rec, pp.487-492, 2000.

M. Black, Recursive non-linear estimation of discontinuous flow fields, Proceedings Europ Conf Computer Vision, pp.138-145, 1994.
DOI : 10.1007/3-540-57956-7_15

M. Black and A. Rangarajan, On the unification of line processes, outlier rejection, and robust statistics with applications in early vision, International Journal of Computer Vision, vol.8, issue.4, pp.75-104, 1996.
DOI : 10.1007/BF00131148

M. Bloor and J. Gerrard, Measurements on Turbulent Vortices in a Cylinder Wake, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.294, issue.1438, pp.319-342, 1966.
DOI : 10.1098/rspa.1966.0210

I. Cohen and I. Herlin, Non uniform multiresolution method for optical flow and phase portrait models: environmental applications, International Journal of Computer Vision, vol.33, issue.1, pp.29-49, 1999.
DOI : 10.1023/A:1008161130332

URL : https://hal.archives-ouvertes.fr/inria-00073872

T. Corpetti, E. Me´minme´min, and P. Pe´rezpe´rez, Dense estimation of fluid flows, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.3, pp.365-380, 2002.
DOI : 10.1109/34.990137

URL : https://hal.archives-ouvertes.fr/hal-00329724

J. Fitzpatrick, The existence of geometrical density-image transformations corresponding to object motion, Computer Vision, Graphics, and Image Processing, vol.44, issue.2, pp.155-174, 1988.
DOI : 10.1016/S0734-189X(88)80003-3

D. Geman and G. Reynolds, Constrained restoration and the recovery of discontinuities, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.14, issue.3, pp.367-383, 1992.
DOI : 10.1109/34.120331

S. Gupta and J. Prince, Stochastic models for DIV-CURL optical flow methods, IEEE Signal Processing Letters, vol.3, issue.2, pp.32-34, 1996.
DOI : 10.1109/97.484208

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.49.3953

D. Heitz, Etude expe´rimentaleexpe´rimentale du sillage d'un barreau cylindrique se de´veloppantde´veloppant dans une couche de meíange plane turbulente, 1999.

P. Holland and R. Welsch, Robust regression using iteratively reweighted least-squares, Communications in Statistics - Theory and Methods, vol.3, issue.9, pp.813-827, 1977.
DOI : 10.1214/aos/1176342503

B. Horn and B. Schunck, Determining optical flow, Artificial Intelligence, vol.17, issue.1-3, pp.185-203, 1981.
DOI : 10.1016/0004-3702(81)90024-2

P. Huber, R. Deriche, and A. G. , Robust statistics Image sequence analysis via partial differential equations, J Math Imaging Vis, vol.11, issue.1, pp.5-26, 1981.

R. Larsen, K. Conradsen, and B. Ersboll, Estimation of dense image flow fields in fluids, IEEE Transactions on Geoscience and Remote Sensing, vol.36, issue.1, pp.256-264, 1998.
DOI : 10.1109/36.655334

A. Lecuona, U. Ruiz-rivas, and P. Rodriguez-aumente, Near field vortex dynamics in axially forced, co-flowing jets: quantitative description of a low-frequency configuration, European Journal of Mechanics - B/Fluids, vol.21, issue.6, pp.701-720, 2002.
DOI : 10.1016/S0997-7546(02)01210-4

L. Lourenco and A. Krothapalli, On the accuracy of velocity and vorticity measurements with PIV, Experiments in Fluids, vol.26, issue.6, pp.421-428, 1995.
DOI : 10.1007/BF00208464

L. Lourenco and A. Krothapalli, True resolution piv: a mesh-free second-order accurate algoritm, 10th International symposium on applications of laser techniques in fluid mechanics, 2000.

S. Mckenna and W. Mcgillis, Performance of digital image velocimetry processing techniques, Experiments in Fluids, vol.32, issue.1, pp.106-115, 2002.
DOI : 10.1007/s003480200011

E. Me´minme´min and P. Pe´rezpe´rez, Dense estimation and object-based segmentation of the optical flow with robust techniques, IEEE Transactions on Image Processing, vol.7, issue.5, pp.703-719, 1998.
DOI : 10.1109/83.668027

E. Me´minme´min and P. Pe´rezpe´rez, A multigrid approach for hierarchical motion estimation, Proceedings of international conference on computer vision, pp.933-938, 1998.

E. Me´minme´min and P. Pe´rezpe´rez, Fluid motion recovery by coupling dense and parametric motion fields, Proceedings of international conference on computer vision, pp.732-736, 1999.

E. Me´minme´min and P. Pe´rezpe´rez, Hierarchical estimation and segmentation of dense motion fields, International Journal of Computer Vision, vol.46, issue.2, pp.129-155, 2002.
DOI : 10.1023/A:1013539930159

J. Nogueira, A. Lecuona, and P. Rodriguez, Identification of a new source of peak locking, analysis and its removal in conventional and super-resolution PIV techniques, Experiments in Fluids, vol.30, issue.3, pp.309-316, 2001.
DOI : 10.1007/s003480000179

A. Nomura, H. Miike, and K. Koga, Field theory approach for determining optical flow, Pattern Recognition Letters, vol.12, issue.3, pp.183-190, 1991.
DOI : 10.1016/0167-8655(91)90048-Q

G. Que´notque´not, Performance evaluation of an optical flow technique applied to PIV using the VSJ standard images, pp.579-584, 1999.

G. Que´notque´not, J. Pakleza, and A. Kowalewski, Particle image velocimetry with optical flow, Exp Fluid, vol.25, issue.3, pp.177-189, 1998.

M. Raffel, C. Willert, and J. Kompenhans, Particle image velocimetry Variational optical flow estimation for particle image velocimetry, Exp Fluids, pp.21-32, 2000.

F. Scarano and L. Reithmuller, Advances in iterative multigrid piv image processing The motion constraint equation for optical flow Computation of 3D velocity fields from 3D cine and CT images of human heart, Proceedings Int Conf Pattern Recognition, pp.51-60, 1984.

D. Suter, Motion estimation and vector splines, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94, pp.939-942, 1994.
DOI : 10.1109/CVPR.1994.323929

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.57.4768

J. Wallace and J. Foss, The Measurement of Vorticity in Turbulent Flows, Annual Review of Fluid Mechanics, vol.27, issue.1, pp.469-514, 1995.
DOI : 10.1146/annurev.fl.27.010195.002345

S. Wereley and C. Meinhart, Second-order accurate particle image velocimetry, Experiments in Fluids, vol.31, issue.3, pp.258-268, 2001.
DOI : 10.1007/s003480100281

P. Wernert, W. Geissler, M. Raffel, and J. Kompenhans, Experimental and numerical investigations of dynamic stall on a pitching airfoil, AIAA Journal, vol.34, issue.5, pp.982-989, 1996.
DOI : 10.2514/3.13177

R. Wildes, M. Amabile, A. Lanzillotto, and T. Leu, Physically based fluid flow recovery from image sequences, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.969-975, 1997.
DOI : 10.1109/CVPR.1997.609445

C. Willert and M. Gharib, Digital particle image velocimetry, Experiments in Fluids, vol.10, issue.4, pp.181-193, 1991.
DOI : 10.1007/BF00190388

L. Zhou, C. Kambhamettu, and D. Goldgof, Fluid structure and motion analysis from multi-spectrum 2D cloud image sequences, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), pp.744-751, 2000.
DOI : 10.1109/CVPR.2000.854949