Department of Pattern Recognition

Real world materials often change their appearance over time. If these variations are spatially and temporally homogeneous then the material visual appearance can be represented by a dynamic texture which is a natural extension of classic texture concept including the time as an extra dimension. In this article we present possible way to handle multispectral dynamic textures based on a combination of input data eigen analysis and subsequent processing of temporal mixing coefficients. The proposed method exhibits overall good performance, offers extremely fast synthesis which is not restricted in temporal dimension and simultaneously enables to compress significantly the original measured visual data.

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 eigen-coefficients using a causal auto-regressive model. The proposed method shows good performance for most of tested DTs, which depends mainly on 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 the means of contemporary graphics hardware.