Wavelets and optical flow motion estimation

Numerical Mathematics

Volumn 6, Issue 1, 2013, Pages 116-137

  Derian P ^a   Heas P ^b   Herzet, C ^b   Memin E ^b  

^a CALIFORNIA STATE UNIVERSITY   (United States)

^b INRIA   (France)

Author keywords

Fluid flows; Large displacements; Motion estimation; Optical flow; Wavelets

Indexed keywords

EID: 84874031065     PISSN: 10048979     EISSN: 20797338     Source Type: Journal    
DOI: 10.4208/nmtma.2013.mssvm07     Document Type: Article

References (17)

1. C. BERNARD, Wavelets and Ill Posed Problems: Optic Flow and Scattered Data Interpolation, PhD thesis, École Polytechnique, 1999.
2. M. BLACK AND P. ANANDAN, The robust estimation of multiple motions: parametric and piecewise-smooth flow fields, Computer Vision and Image Understanding, 63(1) (1996), pp. 75-104.
3. T. BROX, A. BRUHN, N. PAPENBERG AND J. WEICKERT, High accuracy optical flow estimation based on a theory for warping, Computer Vision-ECCV 2004, pages 25-36, 2004.
4. L. CHEN, H. LIAO AND J. LIN, Wavelet-based optical flow estimation, Circuits and Systems for Video Technology, IEEE Transactions on, 12(1) (2002), pp. 1-12.
5. T. CORPETTI, E. MÉMIN AND P. PÉREZ, Dense estimation of fluid flows, Pattern Anal Mach Intel, 24(3) (2002), pp. 365-380.
6. P. DÉRIAN, P. HÉAS, C. HERZET AND 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.
7. P. HÉAS, E. MÉMIN, D. HEITZ AND P. MININNI, Power laws and inverse motion modelling: application to turbulence measurements from satellite images, Tellus A, 64(1962), 2012.
8. D. HEITZ, J. CARLIER AND G. ARROYO, Final report on the evaluation of the tasks of the work-package 2, FLUID project deliverable 5.4, Technical report, INRIA-Cemagref, 2007.
9. B. HORN AND B. SCHUNCK, Determining optical flow, Artificial Intelligence, 17(1981), pp. 185-203.
10. S. KADRI HAROUNA, P. DÉRIAN, P. HÉAS AND E. MEMIN, Divergence-free wavelets and high order regularization. Accepted for publication in IJCV, 2012
11. B. LUCAS AND T. KANADE, An iterative image registration technique with an application to stere-ovision, In Int. Joint Conf. on Artificial Intel. (IJCAI), pages 674-679, 1981.
12. S. MALLAT, A Wavelet Tour of Signal Processing: The Sparse Way, Academic Press, 2008.
13. J. NOCEDAL AND S. J. WRIGHT, Numerical Optimization, Springer Series in Operations Research, Springer-Verlag, New York, NY, 1999.
14. X. TAI AND J. XU, Global and uniform convergence of subspace correction methods for some convex optimization problems, Math. Comput., 71(237) (2002), pp. 105-124.
15. Y. WU, T. KANADE, C. LI AND J. COHN, Image registration using wavelet-based motion model, Int. J. Computer Vision, 38(2) (2000), pp. 129-152.
16. J. YUAN, C. SCHNÖRR AND E. MEMIN, Discrete orthogonal decomposition and variational fluid flow estimation, J. Math. Imaging Vison, 28(2007), pp. 67-80.
17. J. YUAN, C. SCHNÖRR AND G. STEIDL, Simultaneous higher-order optical flow estimation and decomposition, SIAM J. Sci. Computing, 29(6) (2007), pp. 2283-2304.