Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
The wavelet transform hierarchically decomposes images with prescribed bases, while multilineal models search for optimal bases to adapt visual data. In this paper, we integrate t...
This paper presents a scheme for unsupervised classification with Gaussian mixture models by means of statistical learning analysis. A Bayesian Ying-Yang harmony learning system a...
Two temporally scalable video coding techniques, temporal subband coding (TSB) and predictive coding, are evaluated both theoretically and in practice to provide comparisons of co...