自律飛行型レスキュードローンのためのDeep Neural Networkと代替学習による高精度人物検知システムの構築

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2019/02/01

タイトル(英語): Study on Human Detection System Using Deep Neural Network and Alternative Learning for Autonomous Flying Drones

著者名: 長山　格（琉球大学工学部知能情報コース），上原　和加貴（琉球大学大学院理工学研究科情報工学専攻），宮里　大也（琉球大学大学院理工学研究科情報工学専攻）

著者名(英語): Itaru Nagayama (Department of Information Engineering,University of the Ryukyus), Wakaki Uehara (Graduate School of Engineering, University of the Ryukyus), Takaya Miyazato (Graduate School of Engineering, University of the Ryukyus)

キーワード: ドローン，災害救助ロボット，物体認識，Deep Neural Network，代替学習　　drone，rescue robot，object recognition，deep Neural Network，alternative learning

要約(英語): 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.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.139 No.2 （2019） 特集：ドローンとロボット組み込み/サスティナブルシステム

本誌掲載ページ: 149-157 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/139/2/139_149/_article/-char/ja/