Camera calibration from multiple views of a 2D object, using a global nonlinear minimization method

An important task in most 3D vision systems is camera calibration. Many camera models, numerical methods and experimental set-ups have been proposed in the literature to solve the calibration problem. We have analysed and tried many methods, and we conclude that the main problems lie in the choice of the numerical methods and on the calibration object. We propose in this paper a method which is based on a camera model that incorporates lens distortion, and involves a nonlinear minimization technique which can be performed using multiple views of a single 2D object and subpixel feature extraction. We present an application for which only a 2D calibration object can be used.