Automatic selection of MRF control parameters by reactive tabu search

This paper presents an optimization technique to automatically select a set of control parameters for a Markov random field. 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 algorithm with a given parameters set. The technique is applied to stereo matching thanks to the availability of ground truth disparity maps. Experiments with synthetic and real images illustrate the approach.