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Joint estimation-segmentation of optic flow

  • Étienne Mémin
  • Patrick Pérez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1407)

Abstract

In this paper we address the intricate issue of jointly recovering the apparent velocity field between two consecutive frames and its underlying partition. We design a global cost functional including robust estimators. These estimators enable to deal with the large deviations occurring in the different energy terms and offer the possibility to introduce a simple coupling between a dense optical flow field and a segmentation. This coupling is also reinforced by a parametric likeness term. The resulting estimation-segmentation model thus involves a tight cooperation between a local estimation process and a global modelization. The minimization of the final cost function is conducted efficiently by a multigrid optimization algorithm.

Keywords

Optical Flow Motion Estimation Markov Random Field Motion Field Global Deformation 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Étienne Mémin
    • 1
    • 2
  • Patrick Pérez
    • 3
  1. 1.Valoria, Université de Bretagne SudVannesFrance
  2. 2.IRISARennes Cedex
  3. 3.IRISA/INRIARennes CedexFrance

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