ROBUST METHOD FOR SELF-CALIBRATION OF CAMERAS HAVING THE VARYING INTRINSIC PARAMETERS

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 hand, the cameras are characterized by varying intrinsic parameters, and on the other hand the use of only two images to estimate these parameters). The main idea of this method is based on the formulation of a non-linear cost function from the relationship between three matches which are the projection of three points representing vertices of parallelogram, and the relationship between the images of the absolute conic of the two images to estimate the intrinsic parameters of the different cameras. The performance of our approach in terms of accuracy and convergence is shown by the experimental results and the simulations realized.

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