Camera calibration based on divided region LS-SVM

Camera calibration is one of fundamental issues in computer vision and required for achieving accurate visual measurements. Least Squares Support Vector Machines (LS-SVM) are used to achieve the camera calibration. It doesn´t need to confirm the intrinsic and extrinsic parameter of the camera. For a little more accurate calibration, acquired image is divided into two regions according to radial distortion of lens and Least Squares Support Vector Machines is applied to each region. A simple and flexible camera calibration using divided Least Squares Support Vector Machines (DLS-SVM) is proposed in this paper. Experiment results and comparison with BP neural network and Least Squares Support Vector Machines prove the validity of the proposed camera calibration.