Symmetrical Dense Optical Flow Estimation with Occlusions Detection

Luis Alvarez 1 Rachid Deriche 2 Théodore Papadopoulo 2 Javier Sánchez 1
2 ODYSSEE - Computer and biological vision
DI-ENS - Département d'informatique de l'École normale supérieure, CRISAM - Inria Sophia Antipolis - Méditerranée , ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, ENPC - École des Ponts ParisTech
Abstract : Traditional techniques of dense optical flow estimation do not generally yield symmetrical solutions: the results will differ if they are applied between images I1 and I2 or between images I2 and I1. In this work, we present a method to recover a dense optical flow field map from two images, while explicitely taking into account the symmetry across the images as well as possible occlusions in the flow field. The idea is to consider both displacements vectors from I1 to I2 and I2 to I1 and to minimise an energy functional that explicitely encodes all those properties. This variational problem is then solved using the gradient flow defined by the Euler–Lagrange equations associated to the energy. To prove the importance of the concepts of symmetry and occlusions for optical flow computation, we have extended a classical approach to handle those. Experiments clearly showthe added value of these properties to improve the accuracy of the computed flows.
Type de document :
Article dans une revue
International Journal of Computer Vision, Springer Verlag, 2007, 75 (3), pp.371-385. 〈10.1007/s11263-007-0041-4〉
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Soumis le : mercredi 28 octobre 2009 - 16:52:12
Dernière modification le : mardi 24 avril 2018 - 17:20:11

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Luis Alvarez, Rachid Deriche, Théodore Papadopoulo, Javier Sánchez. Symmetrical Dense Optical Flow Estimation with Occlusions Detection. International Journal of Computer Vision, Springer Verlag, 2007, 75 (3), pp.371-385. 〈10.1007/s11263-007-0041-4〉. 〈inria-00427151〉

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