Self-calibration of the distortion of a zooming camera by matching points at different resolutions

This paper presents a new method for the self-calibration of the lens distortion of a zooming camera, which appears for short focal lengths. The proposed technique does not need any special calibration pattern nor any prior knowledge about the environment. The key idea is to match points between a distorted image and an undistorted image taken at different resolutions. A new method for automatically matching points in the two images is proposed. The scale factor between the images is not needed for the matching algorithm. Matched points are used to compute invariants to the pinhole camera parameters. Then, lens distortion parameters are estimated in order to obtain the same invariants in both images. This approach is well suited to autonomous robotic vision applications. In fact, the self-calibration of the camera is done before moving the robot. Experiment with ground truth and tests on real images provide good results.