Homography-based camera pose estimation with known gravity direction for UAV navigation

Relative pose estimation has become a fundamental and important problem in visual simultaneous localization and mapping. This paper statistically optimizes the solution for the homography-based relative pose estimation problem. Assuming a known gravity direction and a dominant ground plane, the homography representation in the normalized image plane enables a least squares pose estimation between two views. Furthermore, an iterative estimation method of the camera trajectory is developed for visual odometry. The accuracy and robustness of the proposed algorithm are experimentally tested on synthetic and real data in indoor and outdoor environments. Various metrics confirm the effectiveness of the proposed method in practical applications.