Study on human detection system using deep neural network and alternative learning for autonomous flying drones

被引:0
作者
Nagayama I. [1 ]
Uehara W. [2 ]
Miyazato T. [2 ]
机构
[1] Department of Information Engineering, University of the Ryukyus, 1, Senbaru Nishihara, Nakagami, Okinawa
[2] Graduate School of Engineering, University of the Ryukyus, 1, Senbaru Nishihara, Nakagami, Okinawa
基金
日本学术振兴会;
关键词
Alternative learning; Deep Neural Network; Drone; Object recognition; Rescue robot;
D O I
10.1541/ieejias.139.149
中图分类号
学科分类号
摘要
An alternative learning and its application to construct an overviewing human detection system (OHDES-V2) of flying drone for emergency rescue and investigation is presented in this paper. In this system, a deep neural network and alternative learning are used key techniques for object recognition from a free viewpoint. Simple appearance-based characteristics is determined from captured images, and the system uses a deep neural network to automatically classify human body, automobiles and so forth. The proposed system shows that several objects can be recognized from a bird’s-eye view. Experimental results show that the system can effectively recognize four types of objects and walking persons with accuraces of 98.5% and 97.12%, respectively. © 2019 The Institute of Electrical Engineers of Japan.
引用
收藏
页码:149 / 157
页数:8
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