Camera calibration with precise extraction of feature points using projective transformation

Abstract

In this paper, we propose a method for precise camera calibration which conducts feature point extraction and camera parameter estimation iteratively. Many of conventional researches on camera calibration have focused on how to calculate camera parameters using data obtained from input images, that is, location of feature points. However, these input images suffer from distortions caused by perspective and lens imperfections. In our proposed method, at the beginning of the procedure, projective transformation matrices between image planes and a calibration target and lens distortion parameters are approximately estimated. These parameters are used in order to reduce the influence of distortions in input images. After the removal of distortions, feature points in processed images are localized precisely and used to update/calculate the projective transformation matrices, the lens distortion parameters and intrinsic camera parameters. These procedures are iterated until they converge and this iteration results in precise estimation of the parameters. The effectiveness of the proposed method has been recognized through experiments using synthesized data and real images.