Multi-perspective long-focus camera calibration algorithm based on parallel perspective projection model

Abstract

To overcome the limitations of conventional long-focus camera calibration, this paper proposes an improved algorithm for calibrating multi-perspective long-focus cameras based on the parallel perspective projection model. The algorithm employs an affine approximation projection model to describe the imaging process of long-focus cameras. By capturing images of the same static scene from different viewpoints and utilizing multi-view images and bundle adjustment, the algorithm jointly estimates camera parameters, including focal length, distortion coefficients, and rotation matrices, facilitating rapid, flexible, and accurate calibration of long-focus cameras. Finally, the proposed algorithm is compared with the Zhang Zhengyou calibration algorithm by calibrating a Canon EOS 60D18-200 camera with a 100mm focal length. The precision and stability of the proposed algorithm are verified through comparison, laying a foundation for subsequent tasks in computer vision, such as 3D reconstruction and image fusion.