Th eme 3 | I n teraction homme-machine, images, donn ees, connaissances Projet MOVI Rapport de recherche n3338 | Janvier 1998 | 34 pagesAbstract: 3D measurements can berecovered from several views by triangulation. This paper deals with the problem of where to place the cameras in order to obtain a minimal error in the 3D measurements, also called camera network design in photogrammetry. We pose the problem in terms of an optimization design, dividing it into two main components: 1 an analytical part dedicated to the analysis of error propagation from which a criterion is derived, 2 a global optimization process to minimizes this criterion. In this way, the approach consists of an uncertainty analysis applied to the reconstruction process from which a covariance matrix is computed. This matrix represents the uncertainty of the detection from which the criterion is derived. Moreover, the optimization has discontinuities mainly due to the unobservability of points, which leads to a combinatorial optimization process. These aspects are solved using a multicellular genetic algorithm. Experimental results are provided to illustrate the e ectiveness and e ciency of the solution.Keywords: Camera network design, uncertainty analysis, global optimization, covariance matrix, genetic algorithms.R esum e : tsvp De ce côt e-l a, l'approche consiste en une analyse d'incertitude appliqu ee au processus de reconstruction d'o u une matrice de covariance sera calcul ee. Cette matrice repr esente l'incertitude de la detection pour lequel le crit ere est d eriv e. Par ailleurs, l'optimisation a des aspects discontinus essentiellement dû a l'inobservabilit e des points. Ce facteur va nous amener a utiliser un processus d'optimisation combinatoire que nous avons r esolu en utilisant un algorithme g en etique multicellulaire. Des resultats exp erimentaux sont inclus pour illustrer l'e cacit e et la rapidit e de la solution.