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Real-Time Detection, Tracking and Classification of Multiple Moving Objects in UAV Videos

机译：无人机视频中多个运动物体的实时检测，跟踪和分类

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摘要

Unnamed Aerial Vehicles (UAVs) are becoming increasingly popular and widely used for surveillance and reconnaissance. There are some recent studies regarding moving object detection, tracking, and classification from UAV videos. A unifying study, which also extends the application scope of such previous works and provides real-time results, is absent from the literature. This paper aims to fill this gap by presenting a framework that can robustly detect, track and classify multiple moving objects in real-time, using commercially available UAV systems and a common laptop computer. The framework can additionally deliver practical information about the detected objects, such as their coordinates and velocities. The performance of the proposed framework, which surpasses human capabilities for moving object detection, is reported and discussed.
机译：无名航空器（UAV）变得越来越流行，并广泛用于监视和侦察。最近有一些有关从无人机视频进行运动物体检测，跟踪和分类的研究。文献中没有进行统一的研究，该研究也扩展了此类先前研究的应用范围并提供了实时结果。本文旨在通过提出一个框架来填补这一空白，该框架可以使用市售的无人机系统和一台普通的笔记本电脑来实时检测，跟踪和分类多个移动物体。该框架还可以提供有关检测到的对象的实用信息，例如它们的坐标和速度。报告并讨论了所提出的框架的性能，该性能超过了人类进行运动物体检测的能力。

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