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
Stereo – Matching Techniques using Optimisation Using Evolutionary Algorithms / Bevilacqua, Vitoantonio; Mastronardi, Giuseppe; Menolascina, F.; Nitti, D.. - LNCS 4113:(2006), pp. 612-621. [10.1007/11816157_73]
Stereo – Matching Techniques using Optimisation Using Evolutionary Algorithms
BEVILACQUA, Vitoantonio;MASTRONARDI, Giuseppe;
2006-01-01
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 researchI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.