Optimal Parameter Estimation for MRF Stereo Matching

Riccardo Gherardi, Umberto Castellani, Andrea Fusiello, Vittorio Murino

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 based on the Reactive Tabu Search strategy, and requires to define a suitable fitness function that measures the performance of the MRF stereo algorithm with a given parameters set. This approach have been made possible by the recent availability of ground-truth disparity maps. Experiments with synthetic and real images illustrate the approach.