Global Calibration Method of a Camera Using the Constraint of Line Features and 3D World Points

Abstract

Abstract We present a reliable calibration method using the constraint of 2D projective lines and 3D world points to elaborate the accuracy of the camera calibration. Based on the relationship between the 3D points and the projective plane, the constraint equations of the transformation matrix are generated from the 3D points and 2D projective lines. The transformation matrix is solved by the singular value decomposition. The proposed method is compared with the point-based calibration to verify the measurement validity. The mean values of the root-mean-square errors using the proposed method are 7.69×10−4, 6.98×10−4, 2.29×10−4, and 1.09×10−3 while the ones of the original method are 8.10×10−4, 1.29×10−2, 2.58×10−2, and 8.12×10−3. Moreover, the average logarithmic errors of the calibration method are evaluated and compared with the former method in different Gaussian noises and projective lines. The variances of the average errors using the proposed method are 1.70×10−5, 1.39×10−4, 1.13×10−4, and 4.06×10−4, which indicates the stability and accuracy of the method.