  Drones have been widely utilized in various fields, but the number of drones
being used illegally and for hazardous purposes has increased recently. To
prevent those illegal drones, in this work, we propose a novel framework for
reconstructing 3D trajectories of drones using a single camera. By leveraging
calibrated cameras, we exploit the relationship between 2D and 3D spaces. We
automatically track the drones in 2D images using the drone tracker and
estimate their 2D rotations. By combining the estimated 2D drone positions with
their actual length information and camera parameters, we geometrically infer
the 3D trajectories of the drones. To address the lack of public drone
datasets, we also create synthetic 2D and 3D drone datasets. The experimental
results show that the proposed methods accurately reconstruct drone
trajectories in 3D space, and demonstrate the potential of our framework for
single camera-based surveillance systems.
