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Décompositions spatio-temporelles pour l'étude des textures dynamiques : contribution à l'indexation vidéo

Abstract : This report is focused on the study and the characterization of Dynamic Textures (DTs), with the aim of video indexing in large databases.This research topic being new and emerging, we propose a taxonomy, a definition of DTs and a state of the art. The most representative DT class is described by a model that considers DTs as the superposition of several wavefronts and local oscillating phenomena.The design of spatio-temporal analysis tools adapted to DT is our main contribution. We first show that the 2D+T curvelet transform is relevant for representing wavefronts. In order to analyse and better understand the DTs, we propose in a second step to adapt the Morphological Component Analysis approach using new thresholding strategies. These methods are tested on several applications: decomposition of DTs, spatio-temporal segmentation, global motion estimation of a DT, ...We have shown that Morphological Component Analysis and multi-scale approaches enable significant results for content-based retrieval applications and dynamic texture indexing on the DynTex database. This thesis constitutes a first step towards automatic indexing of DTs in image sequences and opens the way for many new developments in this topic. Moreover, the proposed approaches are generic and could be applied in a broader context, for instance the processing of 3D data.
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Sloven Dubois. Décompositions spatio-temporelles pour l'étude des textures dynamiques : contribution à l'indexation vidéo. Autre [cs.OH]. Université de La Rochelle, 2010. Français. ⟨NNT : 2010LAROS310⟩. ⟨tel-00605667⟩

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