A Comparison of Wavelet Based Spatio-temporal Decomposition Methods for Dynamic Texture Recognition

Sloven Dubois (1, 2) , Renaud Péteri (1) , Michel Menard (2)

1 MIA - Mathématiques, Image et Applications - EA 3165
2 L3I - Laboratoire Informatique, Image et Interaction - EA 2118

This paper presents four spatio-temporal wavelet decompositions for characterizing dynamic textures. The main goal of this work is to compare the influence of spatial and temporal variables in the wavelet decomposition scheme. Its novelty is to establish a comparison between the only existing method and three other spatio-temporal decompositions. The four decomposition schemes are presented and successfully applied on a large dynamic texture database. Construction of feature descriptors are tackled as well their relevance, and performances of the methods are discussed. Finally, future prospects are exposed.

Mots clés: Spatio-temporal wavelets; dynamic textures; feature descriptors; video indexing

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Sloven Dubois, Renaud Péteri, Michel Menard. A Comparison of Wavelet Based Spatio-temporal Decomposition Methods for Dynamic Texture Recognition. 4th Iberian Conference IbPRIA 2009, Jun 2009, Povoa de Varzim, Portugal. pp.314-321. ⟨hal-00369334⟩