木構造型アンサンブル分類器を用いた行動およびジェスチャ認識のための計算コスト削減手法

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: 2015/06/01

タイトル(英語): Reducing Computation Costs for Activity and Gesture Recognition Using a Tree-Structured Ensemble Classifier

著者名: Joseph Korpela（大阪大学情報科学研究科マルチメディア工学専攻），前川　卓也（大阪大学情報科学研究科マルチメディア工学専攻），Julien Eberle（School for Computer and Communication Science, Ecole Polytechnique Federale de Lausanne），Dipanjan Chakraborty（IBM Research India），Karl Aberer（School for Computer and Commun

著者名(英語): Joseph Korpela (Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University), Takuya Maekawa (Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University), Julien Eberle (School for Computer and Communication Science, Ecole Polytechnique Federale de Lausanne), Dipanjan Chakraborty (IBM Research India), Karl Aberer (School for Computer and Communication Science, Ecole Polytechnique Federale de Lausanne)

キーワード: 加速度センサ，ジェスチャ認識，行動認識　　Accelerometer，Gesture recognition，Activity recognition

要約(英語): This paper proposes a new method that can recognize both activities and gestures by using acceleration data. While both activity recognition techniques and gesture recognition techniques employ acceleration data, these techniques are studied independently due to the large difference between the characteristics of activity sensor data and gesture sensor data. In this study, we combine their recognition using several weak classifiers that are widely used to recognize activities and/or gestures (e.g., FFT-based and DTW-based classifiers).

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.135 No.6 （2015） 特集：データからの知識発見とその応用

本誌掲載ページ: 637-643 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/135/6/135_637/_article/-char/ja/