Computing the coefficients of lens distortion models using planar surfaces

Although there is a wide variety of lens distortion models, computing their parameters remains an open problem. To this end, we introduce a criterion that uses the null space of a matrix that arises from the estimation of the homography. We provide experimental results obtained from laboratory images of calibration patterns, apply our method to images taken in natural settings, study the effect of feature location, and compare it with other approaches. The results suggest that the method works best for cases where the full set of intrinsic or extrinsic camera parameters are not needed, the camera is no longer available, or the optical parameters change over the image sequence.