Calibration method for large-field-of-view stereo vision system based on distance-related distortion model

Abstract

Large-field-of-view stereo vision system lacks flexible and high-precision calibration methods. To this end, we proposed a new distance-related distortion model based calibration method combining 3D points and checkerboards. The experiment indicates that the proposed method has a root mean square of fewer than 0.08 pixels for the reprojection error on the calibration dataset, and the mean relative error of length measurement in a volume of 5.0 m × 2.0 m × 16.0 m is 3.6‰. Compared with other distance-related models, the proposed model has the lowest reprojection error on the test dataset. Besides, in contrast to other calibration methods, our method offers enhanced accuracy and greater flexibility.