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A neural approach to zoom-lens camera calibration from data with outliers
2002
Image and Vision Computing
Camera systems with zoom lenses are inherently more useful than those with passive lenses due to their flexibility and controllability. However, their calibration raises several challenges. In this paper, 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. To automate the tedious process of
doi:10.1016/s0262-8856(02)00051-3
fatcat:q3tltpzn5bddvl5ujeazda6k5q