Exploring Appropriate Clusters in Subspace for Human Activity Recognition

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: 2013/12/02

タイトル(英語): Exploring Appropriate Clusters in Subspace for Human Activity Recognition

著者名: Huiquan Zhang (Graduate School of Information, Production and Systems, Waseda University), Sha Luo (Graduate School of Information, Production and Systems, Waseda University), Osamu Yoshie (Graduate School of Information, Production and Systems, Waseda Un

著者名(英語): Huiquan Zhang (Graduate School of Information, Production and Systems, Waseda University), Sha Luo (Graduate School of Information, Production and Systems, Waseda University), Osamu Yoshie (Graduate School of Information, Production and Systems, Waseda University)

キーワード: Activity recognition，subspaces clustering，multi-dimensional data，pattern extraction

要約(英語): Activity recognition, which has emerged as a pivotal research topic in pervasive sensing over the last several years, utilizes a collection of data from sensors to capture human behavior, detect anomalies and provide warning or guidance information. This paper presents an approach to explore appropriate clusters in subspace for human activity recognition. The approach includes two major phases: discovery of human activity (extraction of human behavior patterns and generation of human activity clusters), and recognition of human activity (application of similarity function to recognize activities). Different from many existing works, the proposed approach applies a subspace clustering based algorithm to generate clusters of human activity. This approach aims to accumulate human activity by approximating the generated clusters to the activity from a conceptual human perspective. The experiments were implemented using radio-frequency identification (RFID) based systems. The results show that the proposed approach is effective in improving the accuracy of both activity discovery and activity recognition.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.133 No.12 （2013） 特集：電気関係学会東海支部連合大会

本誌掲載ページ: 2282-2290 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/133/12/133_2282/_article/-char/ja/