A Comparison of Wavelet Based Spatio-temporal Decomposition Methods for Dynamic Texture Recognition
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
A 3D discrete curvelet based method for segmenting dynamic textures
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
DynTex: A comprehensive database of dynamic textures
Pattern Recognition Letters
Dynamic texture synthesis in the YUV color-space
ICEC'07 Proceedings of the 6th international conference on Entertainment Computing
| Hi-index | 0.00 |
Textural appearance of many real word materials is not static but shows progress in time. If such a progress is spatially and temporally homogeneous these materials can be represented by means of dynamic texture (DT). DT modelling is a challenging problem which can add new quality into computer graphics applications. We propose a novel hybrid method for colour DTs modelling. The method is based on eigen-analysis of DT images and subsequent preprocessing and modelling of temporal interpolation eigencoefficients using a causal auto-regressive model. The proposed method shows good performance for most of the tested DTs, which depends mainly on the properties of the original sequence. Moreover, this method compresses significantly the original data and enables extremely fast synthesis of artificial sequence, which can be easily performed by means of contemporary graphics hardware.