面向实时快速无人机检测的动态视觉传感器方法
Towards Real-Time Fast Unmanned Aerial Vehicle Detection Using Dynamic Vision Sensors
AI总结：
本文提出基于动态视觉传感器的嵌入式系统F-UAV-D，实现低功耗（<15W）和实时（<50ms）的快速无人机检测，在低照度等条件下优于RGB方法。
摘要：
无人机在民用和军事应用中日益普及。然而，对受限区域的无控制访问威胁着隐私和安全。因此，无人机的预防和检测对于保障机密性和安全性至关重要。尽管主动扫描（主要基于雷达）是最精确的技术之一，但它可能昂贵且不如被动检查（如物体识别）灵活。动态视觉传感器（DVS）是受生物启发的基于事件的视觉模型，利用快速移动场景中带时间戳的像素级亮度变化，非常适合低延迟物体检测。本文提出F-UAV-D（快速无人机检测器），一种能够实现快速移动无人机检测的嵌入式系统。具体而言，我们提出一种设置，在实时和低功耗配置中利用DVS作为RGB相机的替代方案。我们的方法利用DVS的高动态范围（HDR）和背景抑制能力，并在使用各种快速移动无人机训练后，在低照度和快速移动场景等次优环境条件下优于RGB输入。我们的结果表明，F-UAV-D能够（i）平均功耗低于15瓦来检测无人机，并且（ii）利用边缘计算机的CPU和GPU节点执行实时推理（即小于50毫秒）。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
