In this paper, a novel camera calibration method for video-surveillance applications is presented. The proposed method works on the hypothesis of a fixed TV camera and it is developed in order to minimize the human intervention during the calibration process. For the application, the proposed algorithm needs the 3D measure of only one point in the scene. Other measures are simulated by using a moving object whose geometry is known and by estimating the 3D position of the object by means of an extended Kalman filter. Experimental results show that the proposed algorithm, other than simplify the installation step of video-surveillance systems, considerably improves the accuracy of the calibration with respect to similar algorithms presented in the state of the art.