Self-calibration of monocular vision system based on planar points

Yu Zhao, Lichao Xu

Abstract: This paper proposes a method of self-calibration of monocular vision system which is based on planar points. Using the method proposed in this paper we can get the initial value of the three-dimensional (3D) coordinates of the feature points in the scene easily, although there is a nonzero factor between the initial value and the real value of the 3D coordinates of the feature points. From different viewpoints, we can shoot different pictures, and calculate the initial external parameters of these pictures. Finally, through the overall optimization, we can get all the parameters including the internal parameters, the distortion parameters, the external parameters of each picture and the 3D coordinates of the feature points. According to the experimental results, in about 100mm×200mm field of view, the mean error and the variance of 3D coordinates of the feature points is less than 10μm.