论文标题
可见，热传感器的实时无人机检测和跟踪
Real-Time Drone Detection and Tracking With Visible, Thermal and Acoustic Sensors
论文作者
论文摘要
本文探讨了设计自动多传感器无人机检测系统的过程。除了常见的视频和音频传感器外，该系统还包括一个热红外摄像机，这被证明是无人机检测任务的可行解决方案。即使分辨率略低，性能也与可见范围内的相机一样好。还研究了检测器性能随传感器到靶标的范围的函数。此外，使用传感器融合，该系统比单个传感器更强大，有助于减少错误检测。为了抵消缺乏公共数据集，还介绍了一个新颖的视频数据集，其中包含650个带注释的红外和可见视频的无人机，鸟类，飞机和直升机的视频（https://github.com/dronedetectionthesis/drone-detection-dataset）。该数据库配有类无人机，直升机和背景噪声的音频数据集。
This paper explores the process of designing an automatic multi-sensor drone detection system. Besides the common video and audio sensors, the system also includes a thermal infrared camera, which is shown to be a feasible solution to the drone detection task. Even with slightly lower resolution, the performance is just as good as a camera in visible range. The detector performance as a function of the sensor-to-target distance is also investigated. In addition, using sensor fusion, the system is made more robust than the individual sensors, helping to reduce false detections. To counteract the lack of public datasets, a novel video dataset containing 650 annotated infrared and visible videos of drones, birds, airplanes and helicopters is also presented (https://github.com/DroneDetectionThesis/Drone-detection-dataset). The database is complemented with an audio dataset of the classes drones, helicopters and background noise.
