Adaptive structure tensors and their applications

Thomas Brox 1 Rein Van den Boomgaard 2 François Lauze 3 Joost Van de Weijer 2 Joachim Weickert 1 Pavel Mrázek 1 Pierre Kornprobst 4
4 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 : The structure tensor, also known as second moment matrix or Förstner interest operator, is a very popular tool in image processing. Its purpose is the estimation of orientation and the local analysis of structure in general. It is based on the integration of data from a local neighborhood. Normally, this neighborhood is defined by a Gaussian window function and the structure tensor is computed by the weighted sum within this window. Some recently proposed methods, however, adapt the computation of the structure tensor to the image data. There are several ways how to do that. This chapter wants to give an overview of the different approaches, whereas the focus lies on the methods based on robust statistics and nonlinear diffusion. Furthermore, the data-adaptive structure tensors are evaluated in some applications. Here the main focus lies on optic flow estimation, but also texture analysis and corner detection are considered.
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Chapitre d'ouvrage
Joachim Weickert and Hans Hagen. Visualization and image processing of tensor fields, Springer, pp.17--47, 2006, Mathematics and Visualization, 978-3-540-25032-6. 〈10.1007/3-540-31272-2〉
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https://hal.inria.fr/inria-00548598
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Soumis le : lundi 20 décembre 2010 - 09:49:57
Dernière modification le : vendredi 25 mai 2018 - 12:02:04

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Thomas Brox, Rein Van den Boomgaard, François Lauze, Joost Van de Weijer, Joachim Weickert, et al.. Adaptive structure tensors and their applications. Joachim Weickert and Hans Hagen. Visualization and image processing of tensor fields, Springer, pp.17--47, 2006, Mathematics and Visualization, 978-3-540-25032-6. 〈10.1007/3-540-31272-2〉. 〈inria-00548598〉

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