The invention provides a step-by-step
video camera self-calibration method, which comprises the following steps: in the first phase, shooting two images of the same scene at different focal lengths, performing
feature extraction and matching on the images and eliminating mismatching points, and solving
principal point coordinates of the
video camera by using matching point pairs; and in the second phase, shooting the same scene from different angles to obtain three images available for matching, and performing
feature extraction and matching on the images and eliminating mismatching points, and then based on Kruppa equation, substituting the obtained
principal point coordinates into the equation to accomplish solving the three parameters of an obliquity factor, as well as scale factors of the
video camera in the directions U and V axes of an imaging plane. By using the method provided by the invention, the calibration accuracy of the
principal point coordinates of the video camera is relatively high, and the
coefficient matrix size of the Kruppa equation is reduced, the amount of solving computation is reduced, and the method has the characteristic of being real-time. The method is applicable to video camera calibration of a vision
system and can be used in the fields of three-dimensional measurement, three-dimensional reconstruction,
machine navigation,
augment reality and the like.