Optimal parameter estimation for MRF stereo matching

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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. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Gherardi, R., Castellani, U., Fusiello, A., & Murino, V. (2005). Optimal parameter estimation for MRF stereo matching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3617 LNCS, pp. 818–825). https://doi.org/10.1007/11553595_100

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