3D Trajectory Reconstruction of Drones using a Single Camera

• URL: http://arxiv.org/abs/2309.02801v1
• Date: Wed, 6 Sep 2023 07:39:51 GMT
• Title: 3D Trajectory Reconstruction of Drones using a Single Camera
• Authors: Seobin Hwang, Hanyoung Kim, Chaeyeon Heo, Youkyoung Na, Cheongeun Lee, and Yeongjun Cho
• Abstract summary: We propose a novel framework for reconstructing 3D trajectories of drones using a single camera. We automatically track the drones in 2D images using the drone tracker and estimate their 2D rotations. To address the lack of public drone datasets, we also create synthetic 2D and 3D drone datasets.
• Score: 0.5937476291232799
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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