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

Authors:
Sloven Dubois;Renaud Péteri;Michel Ménard
Affiliations:
L3i - Laboratoire Informatique Image et Interaction, and MIA - Mathématiques Image et Applications, La Rochelle, France 17042;MIA - Mathématiques Image et Applications, La Rochelle, France 17042;L3i - Laboratoire Informatique Image et Interaction,
Venue:
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Year:
2009

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Abstract

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 [11] 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.