Title
Improving dynamic texture recognition by using a color spatio-temporal decomposition
Abstract
The study of Dynamic Textures (DT) is a recent research topic in the field of video processing. Description and recognition of this phenomena is notoriously a difficult problem but necessary, for example, in video indexation system or video synthesis. The contribution of this paper is to show that it is possible to improve the recognition of a color DT with only a part of its information. In our approach, we propose to split a color image sequence into two components (a geometrical component and a textural component) using the Vectorial Rudin-Osher-Fatemi (VROF) model. The obtained components are used in an application of dynamic texture recognition. The experimental results clearly show that the textural part gives better recognition rates than those obtained with the geometrical part or the original video.
Year
Venue
Keywords
2013
Signal Processing Conference
image colour analysis,image sequences,image texture,object recognition,color DT recognition,color image sequence,color spatio-temporal decomposition,dynamic texture recognition,geometrical component,textural component,vectorial Rudin-Osher-Fatemi model,video indexation system,video processing,video synthesis,ARMA processes,Color Dynamic Textures,Color Spatio-Temporal Decomposition,recognition
Field
DocType
Citations 
Computer vision,Indexation,Video processing,Pattern recognition,Computer science,Texture recognition,Artificial intelligence,Color image
Conference
0
PageRank 
References 
Authors
0.34
8
4
Name
Order
Citations
PageRank
Rahul Mourya110.70
Sloven Dubois200.34
Olivier Alata311819.81
alain tremeau423034.42