Camera Position Estimation for UAVs Using SolvePnP with Kalman Filter

In this paper, we propose an algorithm for obtaining camera coordinates for unmanned aerial vehicles (UAVs) using SolvePnP and Kalman filter (KF). The data and motion of circle can be recognized and tracked through the KF with high accuracy. Then, the recognized circle is used as an image point of the SolvePnP algorithm. The translation and rotation vectors can be extracted from reference of the world coordinate system using the image point. The position of UAVs can be obtained from the extracted information and the results demonstrate that the position can be derived from only camera. The robust performance of the proposed algorithm is demonstrated through experimental results.