Skip to main content
Article thumbnail
Location of Repository

SIViP manuscript No. (will be inserted by the editor) Characterization and Recognition of Dynamic Textures based on 2D+T Curvelet Transform

By Sloven Dubois, Renaud Péteri and Michel MénardSloven Dubois, Renaud Péteri and Michel Ménard

Abstract

Abstract The research context of this article is the recognition and description of dynamic textures. In image processing, the wavelet transform has been successfully used for characterizing static textures. To our best knowledge, only two works are using spatio-temporal multiscale decomposition based on tensor product for dynamic texture recognition. One contribution of this article is to analyse and compare the ability of the 2D+T curvelet transform, a geometric multiscale decomposition, for characterizing dynamic textures in image sequences. Two approaches using the 2D+T curvelet transform are presented and compared using three new large databases. A second contribution is the construction of these three publicly available benchmarks of increasing complexity. Existing benchmarks are either too small, not available or not always constructed using a reference database. Feature vectors used for recognition are describe

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.372.130
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://hal.archives-ouvertes.f... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.