Unmanned Aerial Vehicles (UAVs) are gaining popularity in civil and military
applications. However, uncontrolled access to restricted areas threatens
privacy and security. Thus, prevention and detection of UAVs are pivotal to
guarantee confidentiality and safety. Although active scanning, mainly based on
radars, is one of the most accurate technologies, it can be expensive and less
versatile than passive inspections, e.g., object recognition. Dynamic vision
sensors (DVS) are bio-inspired event-based vision models that leverage
timestamped pixel-level brightness changes in fast-moving scenes that adapt
well to low-latency object detection. This paper presents F-UAV-D (Fast
Unmanned Aerial Vehicle Detector), an embedded system that enables fast-moving
drone detection. In particular, we propose a setup to exploit DVS as an
alternative to RGB cameras in a real-time and low-power configuration. Our
approach leverages the high-dynamic range (HDR) and background suppression of
DVS and, when trained with various fast-moving drones, outperforms RGB input in
suboptimal ambient conditions such as low illumination and fast-moving scenes.
Our results show that F-UAV-D can (i) detect drones by using less than <15 W on
average and (ii) perform real-time inference (i.e., <50 ms) by leveraging the
CPU and GPU nodes of our edge computer.

本文介绍了一种嵌入式系统 F-UAV-D（Fast Unmanned Aerial Vehicle Detector），利用动态视觉传感器（DVS）作为实时低功耗配置中 RGB 摄像头的替代品，通过利用 DVS 的高动态范围（HDR）和背景抑制，在亚优化的环境条件下检测快速移动的无人机的性能优于 RGB 输入。