Stereo-Matching Techniques Optimisation Using Evolutionary Algorithms

  • Vitoantonio Bevilacqua
  • Giuseppe Mastronardi
  • Filippo Menolascina
  • Davide Nitti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)


In this paper we present a novel approach to 3D stereo-matching which uses an evolutionary algorithm in order to optimise 3D reconstruction. Common techniques in the field of 3D models generation are employed together with a Genetic Algorithm (GA) which is able to improve the results of the matching process. A general overview of the most relevant approaches is given in order to contextualise our method and to analyse its strength-points and potentialities. Details of the implemented GA are discussed with a particular focus on the constraints used in order to obtain better results. Experimental results of the trials carried out are given in a final stage together with concluding remarks and some cues for further research.


Matched Point Stereo Match Epipolar Line Genetic Algorithm Parameter Gaussian Window 
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 2006

Authors and Affiliations

  • Vitoantonio Bevilacqua
    • 1
  • Giuseppe Mastronardi
    • 1
  • Filippo Menolascina
    • 1
  • Davide Nitti
    • 1
  1. 1.Dipartimento di Elettrotecnica ed ElettronicaPolytechnic of BariBariItaly

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