A Camera Calibration Method Based on 2D Homography

In this paper, a new method for camera calibration is presented based on 2D homography. First, intrinsic parameters are separated into two parts which are then solved out respectively using the least squares method. Compared with other techniques, the proposed method can obtain a much better initial guess which will subsequently improve the efficiency of the nonlinear-optimization algorithm and the precision of the final result. For the convenience of different applications in practice, two objective functions are proposed for nonlinear optimization, and correspondingly, two different kinds of radical distortion coefficients are obtained. While the former is well suited to infer 2D image coordinates from 3D information, the latter is more helpful to obtain 3D information from 2D image signals. Simulation results are provided to demonstrate the superior performance of the method.