Unmanned Aerial Vehicle (UAV) Based Running Person Detection from a Real-Time Moving Camera*

Happiness Ugochi Dike, Qingtian Wu, Yimin Zhou, Gong Liang
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引用次数: 8

Abstract

The information captured by Unmanned Aerial Vehicles (UAVs) are highly exploited to detect a running person which is given in this paper. In this scheme, 11 frame per seconds and an adequate detection precision in outdoor background was realized, using one dispensation thread without resorting to distinct hardware. The high precision and realtime detection were made promising by two aids. First, we used a progression of preprocessing procedures to extract the regions of interest (ROI), this includes spatial domain analysis, calculating the optical flow in every two consecutive images and having a predefined threshold built on optical flow to select actual areas as ROIs. Secondly, we also used relatively minor-batch models to train our 5-layer convolutional neural networks (CNN) in order to realize an adequate detection ratio. The experiments from numerous videos shot in diverse time and locations proved that the proposed scheme can detect running person in outdoors efficiently and enhance the Realtime necessity with a very high detection ratio.
基于实时移动摄像机的无人机(UAV)跑人检测*
本文提出了一种利用无人机捕获的信息对奔跑者进行检测的方法。该方案在室外背景下使用一个分配线程,无需使用不同的硬件,实现了每秒11帧和足够的检测精度。通过两种辅助手段实现了高精度、实时性的检测。首先,我们使用一系列预处理程序提取感兴趣区域(ROI),这包括空间域分析,计算每两个连续图像中的光流,并在光流上建立预定义阈值以选择实际区域作为ROI。其次,我们还使用相对小批量的模型来训练我们的5层卷积神经网络(CNN),以实现足够的检测比。在不同时间和地点拍摄的大量视频中进行的实验证明,该方法可以有效地检测室外奔跑的人,提高了实时性,具有很高的检测率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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