Regularization Terms for Motion Estimation - Links with Spatial Correlations
Yann Lepoittevin, Isabelle Herlin
2016
Abstract
Motion estimation from image data has been widely studied in the literature. Due to the aperture problem, one equation with two unknowns, a Tikhonov regularization is usually applied, which constrains the estimated motion field. The paper demonstrates that the use of regularization functions is equivalent to the definition of correlations between pixels and the formulation of the corresponding correlation matrices is given. This equivalence allows to better understand the impact of the regularization with a display of the correlation values as images. Such equivalence is of major interest in the context of image assimilation as these methods are based on the minimization of errors that are correlated on the space-time domain. It also allows to characterize the role of the errors during the assimilation process.
References
- Baker, S., Scharstein, D., Lewis, J. P., Roth, S., Black, M. J., and Szeliski, R. (2011). A database and evaluation methodology for optical flow. International Journal on Computer Vision, 92(1):1-31.
- Béréziat, D. and Herlin, I. (2011). Solving ill-posed image processing problems using data assimilation. Numerical Algorithms, 56(2):219-252.
- Fortun, D., Bouthemy, P., and Kervrann, C. (2015). Optical flow modeling and computation: A survey. Computer Vision and Image Understanding, 134:1 - 21.
- Hadamard, J. (1923). Lecture on Cauchy's Problem in Linear Partial Differential Equations. Yale University Press, New Haven.
- Horn, B. and Schunk, B. (1981). Determining optical flow. Artificial Intelligence, 17:185-203.
- Le Dimet, F. and Talagrand, O. (1986). Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus Series A : Dynamic meteorology and oceanography, 38(2):97-110.
- Nagel, H.-H. (1995). Nibelungen-platz. www.ira.uka.de.
- Nagel, H. H. and Enkelmann, W. (1986). An investigation of smoothness constraints for the estimation of displacement vector fields from image sequences. Pattern Analysis and Machine Intelligence, PAMI8(5):565-593.
- Nielsen, M., Florack, L., and Deriche, R. (1994). Regularisation and scale space. Technical Report RR 2352, INRIA.
- Oliver, D. (1998). Calculation of the inverse of the covariance. Mathematical Geology, 30(7):911-933.
- Papadakis, N., Mémin, E., Cuzol, A., and Gengembre, N. (2010). Data assimilation with the weighted ensemble Kalman filter. Tellus Series A : Dynamic meteorology and oceanography, 62(5):673-697.
- Ridal, M., Lindskog, M., Gustafsson, N., and Haase, G. (2011). Optimized advection of radar reflectivities. Atmospheric Research, 100(2-3):213-225.
- Sun, D., Roth, S., and Black, M. (2010). Secrets of optical flow estimation and their principles. In European Conference on Computer Vision, pages 2432-2439.
- Tikhonov, A. N. (1963). Regularization of incorrectly posed problems. Soviet mathematics - Doklady, 4:1624- 1627.
- Werlberger, M., Pock, T., and Bischof, H. (2010). Motion estimation with non-local total variation regularization. In Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA.
Paper Citation
in Harvard Style
Lepoittevin Y. and Herlin I. (2016). Regularization Terms for Motion Estimation - Links with Spatial Correlations . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 456-464. DOI: 10.5220/0005712104560464
in Bibtex Style
@conference{visapp16,
author={Yann Lepoittevin and Isabelle Herlin},
title={Regularization Terms for Motion Estimation - Links with Spatial Correlations},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={456-464},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005712104560464},
isbn={978-989-758-175-5},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Regularization Terms for Motion Estimation - Links with Spatial Correlations
SN - 978-989-758-175-5
AU - Lepoittevin Y.
AU - Herlin I.
PY - 2016
SP - 456
EP - 464
DO - 10.5220/0005712104560464