深層学習による時系列挙動認識を用いた次世代型知的防犯カメラシステム

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2019/09/01

タイトル(英語): A Study on Intelligent Security Camera System based on Sequential Motion Recognition by using Deep Learning

著者名: 長山　格（琉球大学工学部知能情報コース），宮原　彬（琉球大学大学院理工学研究科情報工学専攻），島袋　航一（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), Akira Miyahara (Graduate School of Engineering, University of the Ryukyus), Koichi Shimabukuro (Graduate School of Engineering, University of the Ryukyus)

キーワード: Deep Learning，LSTM，夜間の路上，ひったくり，防犯カメラ　　Deep Learning，LSTM，nightly road，snatching incident，security camera

要約(英語): In this paper, we propose a new intelligent security camera system, that is named COMDES, for automated detection of snatching incidents on streets during the night by using LSTM network. Although over a half of all snatching incidents occur at night, this has not been considered in past studies. Thus, we have proposed an intelligent security camera system using a deep neural network and snapshot of a video frame to detect snatching incidents in the night by our previous paper. The COMDES can perform more efficient detection of snatching than our previous paper, by using sequential frames observed in the criminal scene and LSTM. It can classifies the situations into criminal or non-criminal scenes precisely. The experimental results show that the system, COMDES, can effectively detect snatching incidents with an accuracy of 98.89%.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.139 No.9 （2019） 特集：知能メカトロニクス分野と連携する知覚情報技術

本誌掲載ページ: 986-992 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/ieejeiss/139/9/139_986/_article/-char/ja/