Nabil El Akkad

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In this paper, we propose an approach based on improved genetic algorithms for the camera calibration having the varying parameters. The present method is based on the formulation of a nonlinear cost function from the determination of the relationship between points of the image planes and all parameters of the cameras. The minimization of this function by(More)
This work presents a practical and new approach of self-calibration of cameras with varying parameters, by an unknown planar scene. We show that the estimation of the different parameters of the cameras used can be made from only two matches between two images of the planar scene. The strong point of our method resides at minimizing constraints on the(More)
This work proposes a method of camera self-calibration having varying intrinsic parameters from a sequence of images of an unknown 3D object. The projection of two points of the 3D scene in the image planes is used with fundamental matrices to determine the projection matrices. The present approach is based on the formulation of a nonlinear cost function(More)
In this paper we present a new method of cameras self-calibration having the varying intrinsic parameters, by an unknown planar scene, and we demonstrate that the estimation of these parameters can be made from three matches between two images, which shows the importance of our approach at minimizing constraints on the self-calibration system (on the one(More)
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