This paper presents a novel approach for estimating parameters for MRF-based stereo algorithms. This approach is based on a new formulation of stereo as a maximum a posterior (MAP...
—This paper presents a novel approach for estimating the parameters for MRF-based stereo algorithms. This approach is based on a new formulation of stereo as a maximum a posterio...
Abstract. This paper presents an optimisation technique to select automatically a set of control parameters for a Markov Random Field applied to stereo matching. The method is base...
Riccardo Gherardi, Umberto Castellani, Andrea Fusi...
This paper presents an optimisation technique to automatically select a set of control parameters for a Markov Random Field. The method is based on the Reactive Tabu Search strate...
Umberto Castellani, Andrea Fusiello, Riccardo Gher...
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...