Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
We propose an efficient method for complex optimization problems that often arise in computer vision. While our method is general and could be applied to various tasks, it was mai...
We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...
Consider the problem of sampling signals which are not bandlimited, but still have a finite number of degrees of freedom per unit of time, such as, for example, piecewise polynomi...
The context of this work is lateral vehicle control using a camera as a sensor. A natural tool for controlling a vehicle is recursive filtering. The well-known Kalman fil...
Jean-Philippe Tarel, Sio-Song Ieng, Pierre Charbon...