犯行映像のGabor特徴情報と多数決ネットワークによる街頭犯罪の高精度検知

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: 2016/10/01

タイトル(英語): Automated Video Surveillance for Snatching Detection using Majority Rule Network and Gabor Features

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

キーワード: 防犯カメラ，Gabor特徴，動画像解析，犯罪検知，AIシステム　　security camera，Gabor features，video processing，crime scene detection，AI system

要約(英語): In this paper, we propose an intelligent security camera system for automated detection of snatching incidents in which a bicycle is used. In addition, the effectiveness of the Basic Snatching Action Model (BSAM) and Gabor features for automated detection of snatching incidents is presented. The localization of moving objects in a video stream and human behavior estimation are the key techniques applied in the proposed system. Gabor features are determined from video streams and, using a majority rule network (MRN) composed of various artificial intelligence (AI) systems, the video streams are automatically classified into criminal or non-criminal scenes. In our experiments, we considered some scenarios of snatching incidents in which the perpetrator uses a bicycle. The experimental results show that the proposed system can effectively detect criminal scenes with high accuracy.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.136 No.10 （2016） 特集：Okinawa型ロボット組み込み/サスティナブルシステム

本誌掲載ページ: 735-743 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/136/10/136_735/_article/-char/ja/