This paper presents an optimization technique to automatically select a set of control parameters for a Markov random field. Themethod is based on the reactive tabu search strategy, and requires to define a suitable fitness function that measures the performanceof the MRF algorithm with a given parameters set. The technique is applied to stereo matching thanks to the availability of ground truthdisparity maps. Experiments with synthetic and real images illustrate the approach.
Automatic selection of MRF control parameters by reactive tabu search
CASTELLANI, Umberto
;FUSIELLO, Andrea;GHERARDI, Riccardo;MURINO, Vittorio
2007-01-01
Abstract
This paper presents an optimization technique to automatically select a set of control parameters for a Markov random field. Themethod is based on the reactive tabu search strategy, and requires to define a suitable fitness function that measures the performanceof the MRF algorithm with a given parameters set. The technique is applied to stereo matching thanks to the availability of ground truthdisparity maps. Experiments with synthetic and real images illustrate the approach.
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