Self-calibration of a camera with a non-linear model

Camera calibration is an indispensable step to obtain 3D geometric information from 2D images. Self-calibration of a camera with a linear model (hereafter called a linear camera) has become one of the major research directions in computer vision field. Since a linear camera model cannot in general accurately represent the imaging geometry of a real camera, it is both necessary and important to explore ways of self-calibrating a non-linear camera. In this paper, a self-calibration method of a non-linear camera is proposed. The basic principle of the method is to model the non-linear camera as a linear camera plus a non-linear distortion part, then a set of non-linear constraints on the non-intrinsic parameters is derived by means of fundamental matrices or homographies associated with linear camera. Experiments with simulated data as well as with real images show that the proposed method is workable, and applicable in real applications.