Optimal Parameter Estimation for MRF Stereo Matching

  • R. Gherardi
  • U. Castellani
  • A. Fusiello
  • V. Murino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)


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.


Markov Random Fields Observation Model Tabu List Stereo Match Stereo Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • R. Gherardi
    • 1
  • U. Castellani
    • 1
  • A. Fusiello
    • 1
  • V. Murino
    • 1
  1. 1.Dipartimento di InformaticaUniversità di VeronaVeronaItaly

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