An on-line calibration method for camera with large FOV based on prior information

Abstract In the large dimensional vision measurement, the parameters of camera with large FOV (field-of-view) are easy to change for the influence of working conditions, which directly affects the precision of measurement. Concerning this issue, an on-line calibration method for camera with large FOV based on prior information is proposed. In this method, sufficient prior information is firstly obtained by the lights whose directions and positions in the space are known before measurement, so as to achieve the high accuracy pre-calibration of camera with large FOV, in which the initial values of camera parameters are acquired. During the measurement, on-line calibration is conducted with several fixed points in the FOV by combining EPnP algorithm, a pose estimation algorithm based on lines, and LM (Levenberg–Marquardt) optimization algorithm, which adjusts the parameters of camera in time. The experiments results show that the precision of the on-line calibration method is equal to that of the off-line traditional calibration methods, whose reconstruction error is within 2 mm with the FOV of 3000 mm × 4000 mm, while the method is less time consuming. The method in this paper is proved suitable for the on-line calibration of camera with large FOV.