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Variational multi-valued velocity field estimation for transparent sequences

Alonso Ramirez-Manzanares 1 Mariano Rivera 1 Pierre Kornprobst 2 François Lauze 3
CRISAM - Inria Sophia Antipolis - Méditerranée , INRIA Rocquencourt, ENS Paris - École normale supérieure - Paris, UNS - Université Nice Sophia Antipolis (... - 2019), CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : Motion estimation in sequences with transparencies is an important problem in robotics and medical imaging applications. In this work we propose a variational approach for estimating multi-valued velocity fields in transparent sequences. Starting from existing local motion estimators, we derive a variational model for integrating in space and time such a local information in order to obtain a robust estimation of the multi-valued velocity field. With this approach, we can indeed estimate multi-valued velocity fields which are not necessarily piecewise constant on a layer--each layer can evolve according to a non-parametric optical flow. We show how our approach outperforms existing methods; and we illustrate its capabilities on challenging experiments on both synthetic and real sequences.
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Contributor : Pierre Kornprobst Connect in order to contact the contributor
Submitted on : Wednesday, July 17, 2013 - 4:12:11 PM
Last modification on : Friday, October 15, 2021 - 1:40:04 PM

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Alonso Ramirez-Manzanares, Mariano Rivera, Pierre Kornprobst, François Lauze. Variational multi-valued velocity field estimation for transparent sequences. Journal of Mathematical Imaging and Vision, Springer Verlag, 2011, 40 (3), pp.285--304. ⟨10.1007/s10851-011-0260-8⟩. ⟨hal-00845724⟩



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