Abstract
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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Bevilacqua, V., Mastronardi, G., Menolascina, F., Nitti, D. (2006). Stereo-Matching Techniques Optimisation Using Evolutionary Algorithms. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_73
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DOI: https://doi.org/10.1007/11816157_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
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