Self-calibration of cameras using affine correspondences and known relative rotation angle

This paper proposes a flexible method for camera self-calibration using affine correspondences and known relative rotation angle, which applies to the case that camera and inertial measurement unit (IMU) are tightly fixed. An affine correspondence provides two more constraints for the self-calibration problem than a traditional point correspondence, and the relative rotation angle can be derived from the IMU. Therefore, calibrating intrinsic camera parameters needs fewer correspondences, which can reduce the iterations and improve the algorithm's robustness in the random sample consensus framework. The proposed method does not require rotational alignment between the camera and the IMU. This advantage makes our method more convenient and flexible. The experimental results of both synthetic data and publicly available real datasets demonstrate that our method is effective and accurate for camera self-calibration.