3D Trajectory Reconstruction of Drones using a Single Camera

TL;DR

This paper introduces a novel framework for reconstructing 3D drone trajectories from a single camera, leveraging calibration, 2D tracking, and synthetic datasets to enhance surveillance capabilities.

Contribution

The work presents a new geometric approach for 3D drone trajectory reconstruction using a single camera and introduces synthetic datasets for training and evaluation.

Findings

Accurately reconstructs 3D drone trajectories from 2D images.

Demonstrates effectiveness with synthetic datasets and real-world scenarios.

Potential for single-camera drone surveillance systems.

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.