Optimal parameter estimation for MRF stereo matching

Authors:
R. Gherardi;U. Castellani;A. Fusiello;V. Murino
Affiliations:
Dipartimento di Informatica, Università di Verona, Verona, Italy;Dipartimento di Informatica, Università di Verona, Verona, Italy;Dipartimento di Informatica, Università di Verona, Verona, Italy;Dipartimento di Informatica, Università di Verona, Verona, Italy
Venue:
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Year:
2005

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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.