Abstract
 The use of zoom and auto-focus modifies the intrinsic calibration parameters of the camera and the parameters of the camera positioning system. It is therefore mandatory to develop methods to automatically recalibrate the visual sensor. We present a neural framework for zoom-lens camera calibration that can capture complex variations in the camera model parameters across continuous ranges in the lens control space, while minimizing the calibration error over all the calibration data. The calibration results of this technique applied to Hitachi CCD cameras with H10x11E Fujinon active lenses are reported.