XIA, Gui-Song; FERRADANS, Sira; PEYRÉ, Gabriel; AUJOL, Jean-François

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XIA, Gui-Song
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]

FERRADANS, Sira
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]

PEYRÉ, Gabriel
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]

Langue

Communication dans un congrès

Ce document a été publié dans

Proc. ICIP'12, Proc. ICIP'12, ICIP'12, 2012-09. 2012-09p. ?

Résumé en anglais

This paper addresses the problem of modeling stationary color dynamic textures with Gaussian processes. We detail two particular classes of such processes that are parameterized by a small number of compactly supported linear filters, so-called dynamical textons (\emph{dynTextons}). The first class extends previous works on the spot noise texture model to the dynamical setting. It directly estimates the dynTexton to fit a translation-invariant covariance from the exemplar. The second class is a specialization of the auto-regressive (AR) dynamic texture method to the setting of space and time stationary textures. This allows one to parameterize the process covariance using only a few linear filters. Numerical experiments on a database of stationary textures shows that the methods, despite their extreme simplicity, provide state of the art results to synthesize space stationary dynamical texture.< Réduire

Mots clés en anglais

Dynamic texture

texture synthesis

autoregressive process

spot noise

URI

https://oskar-bordeaux.fr/handle/20.500.12278/189890

Project ANR

Adaptivité pour la représentation des images naturelles et des textures - ANR-08-EMER-0009

Origine

Importé de hal

Unités de recherche

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251