无人机航拍图像实时位姿估计.

Aiming at the problems of scale uncertainty, traj ectory drift caused by accumulated errors in large scenes and relative pose in a local coordinate system when monocular vision SLAM was used for pose estimation of U AV aerial images, this paper proposed a real-time pose estimation scheme for U AV aerial images. Firstly, this scheme tracked the visual image in real time, then obtained the transformation relationship between the visual coordinate system and the world coordinate system by introducing RTK information, and solved the problems of scale uncertainty and trajectory drift. Finally, it obtained a pose in the world coordinate system. Considering that the video stream processed by visual SLAM would process redundant images and increase the pressure of image storage, shooting and calculation, this scheme used the processing of discontinuous low overlap images to calculate the pose to avoid these problems. In real scene experiments, the experimental results show that the accuracy of the scheme is higher than that of the current mainstream open source frameworks ORB-SLAM2, DSO and OpenMVG, and the average of the overall trajectory error is less than 10 cm. [ABSTRACT FROM AUTHOR]