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Proceedings Paper

Multiresolution Markov random field and multigrid algorithm for a discontinuity-preserving estimation of the optical flow
Author(s): Etienne Memin; Patrick Perez
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Paper Abstract

In this paper we address the intricate issue of recovering (long range) velocity fields between consecutive frames of an image sequence. Within the Bayesian estimation framework, we design a global objective function to be minimized. This energy function is classically composed of two terms. The first one reinforces the fragile modeling of the optical flow constraint equation making use of robust estimators, while the second (a priori) term incorporates a discontinuity preserving smoothness constraint. A multiresolution definition of this differential estimation method aims at accessing long range displacements in a coarse-to- fine incremental way. As for the associated successive minimizations, they are processed through a very efficient deterministic multigrid relaxation algorithm.

Paper Details

Date Published: 11 August 1995
PDF: 12 pages
Proc. SPIE 2568, Neural, Morphological, and Stochastic Methods in Image and Signal Processing, (11 August 1995); doi: 10.1117/12.216361
Show Author Affiliations
Etienne Memin, Institut de Recherche en Informatique et Systemes Aleatoires (France)
Patrick Perez, Institut de Recherche en Informatique et Systemes Aleatoires (France)


Published in SPIE Proceedings Vol. 2568:
Neural, Morphological, and Stochastic Methods in Image and Signal Processing
Edward R. Dougherty; Francoise J. Preteux; Sylvia S. Shen, Editor(s)

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