– In the past few years considerable demand for user oriented multimedia information systems has developed. These systems must provide a rich set of functionality so that new, co...
We introduce a stochastic model to characterize the online computational process of an object recognition system based on a hierarchy of classifiers. The model is a graphical netwo...
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Subspace tracking methods are widespread in signal and image processing. To reduce the influence of perturbations or outliers on the measurements, some authors have used a stocha...
Quentin Rentmeesters, Pierre-Antoine Absil, Paul V...