Abstract
In this paper we propose a non uniform multiresolution method defining a new approach for coarse to fine grid generation. It allows to locally increase the resolution of the grid according to the studied problem. Each added node refines the grid in a region of interest and increases the numerical accuracy of the solution in this region. We make use of such a method for solving the optical flow equation with a non quadratic regularization scheme allowing the computation of optical flow field while preserving its discontinuities. This new scheme is used for processing oceanographic and atmospheric image sequences.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Preview
Unable to display preview. Download preview PDF.
References
J.L. Barron, D.J. Fleet, and S.S. Beauchemin. Performance of optical flow techniques. International Journal of Computer Vision, 12(1):43–77, February 1994.
P. G. Ciarlet. The finite element methods for elliptic problems. NORTHHOLLAND, Amsterdam, 1987.
I. Cohen and I. Herlin. A motion computation and interpretation framework for oceanographic satellite images. In IEEE, Computer Vision Symposium, pages 13–18, Florida, November 1995.
R. Glowinski. Numerical Methods for Nonlinear Variational Problems. Springer-Verlag, New-York, 1984. Springer Series in Computational Physics.
B.K.P. Horn and G. Schunck. Determining optical flow. Artificial Intelligence, 17:185–203, 1981.
M. Irani, B. Rousso, and S. Peleg. Detecting and tracking multiple moving objects using temporal integration. In Proceedings of the Second European Conference on Computer Vision 1992, pages 282–287, May 1992.
J.R. Muller, P. Anandan, and J.R. Bergen. Adaptive-complexity registration of images. In IEEE Proceedings of Computer Vision and Pattern Recognition, pages 953–957, 1994.
L.I. Rudin, S. Osher, and E. Fatemi. Nonlinear total variation based noise removal algorithms. In Ecoles CEA-EDF-INRIA; Problèmes Non Linéaires Appliqués: Modélisation Mathématique pour le traitement d'images, pages 149–179, March 1992.
H. Samet. The Design and Analysis of Spatial Data Structures. Addison-Wesley, 1989.
R. Szeliski and H.Y. Shum. Motion estimation with quadtree splines. Technical report, DEC Cambridge Research Lab, March 1995.
M. Vasilescu and D. Terzopoulos. Adaptive meshes and shells: Irregular triangulation, discontinuities, and hierarchical subdivision. In IEEE Proceedings of Computer Vision and Pattern Recognition, pages 829–832, June 1992.
A. Verri and T. Poggio. Motion field and optical flow: Qualitative properties. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(5):490–498, May 1989.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag London Limited
About this paper
Cite this paper
Cohen, I., Herlin, I. (1996). Non uniform multiresolution method for optical flow computation. In: Berger, MO., Deriche, R., Herlin, I., Jaffré, J., Morel, JM. (eds) ICAOS '96. Lecture Notes in Control and Information Sciences, vol 219. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-76076-8_144
Download citation
DOI: https://doi.org/10.1007/3-540-76076-8_144
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76076-4
Online ISBN: 978-3-540-40945-8
eBook Packages: Springer Book Archive