Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Real images are often corrupted by noise from various sources. Bilateral filtering is a nonlinear filter that considers intensity variations as well as spatial closeness in the no...
We present an efficient generalization of the sparse pseudo-input Gaussian process (SPGP) model developed by Snelson and Ghahramani [1], applying it to binary classification pro...
We present a background subtraction algorithm aimed at efciency and robustness to common sources of disturbance such as illumination changes, camera gain and exposure variations, ...
Alessandro Lanza, Federico Tombari, Luigi di Stefa...
In this paper, a statistical learning approach to spatial context exploitation for semantic image analysis is presented. The proposed method constitutes an extension of the key pa...