状況と行動の因果関係に着目した人間の行動モデル化手法 HSMMの適用による時系列データの変化速度を考慮したモデル化

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: 2021/02/01

タイトル(英語): Human Action Modeling Method based on the Causality between a Sitution and an Action Modeling by Considering Change Speed of Time-series Data with HSMM

著者名: 道木　加絵（愛知工業大学），橋本　幸二郎（公立諏訪東京理科大学），舟洞　佑記（名古屋大学），道木　慎二（名古屋大学），鳥井　昭宏（愛知工業大学）

著者名(英語): Kae Doki (Aichi Institute of Technology), Kohjiro Hashimoto (Suwa University of Science), Yuki Funabora (Nagoya University), Shinji Doki (Nagoya University), Akihiro Torii (Aichi Institute of Technology)

キーワード: 人間の行動モデル，時系列データ，隠れセミマルコフモデル，If-thenルール_x000D_　　human behavior model，time series data，hidden Semi-Markov Model，If-then rule

要約(英語): We have proposed a modeling method of human actions based on the causality between a situation and an action. In this method, a human action rule is expressed by an If-the-rule style, assumed that a person changes his current action to the next one according to the situation around him. In the previous method, a human action and a situation in a human action rule is modeled with a Hidden Markov Model(HMM). HMM is one of powerful tools for modeling time series data, but it ignores the change speed of time series data. In addition, time series data on human actions and situations are classified by Continuous Dynamic Programming. This means that two types of criteria should be set for modeling. In order to overcome these problems, we propose a new modeling method of human actions with Hidden Semi-Markov Model(HSMM) in this paper. In the proposed method, both clustering and modeling of time series data are executed with HSMM. The usefulness of the proposed method is discussed through some modeling results of human actions on operating a radio-controlled vehicle.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.141 No.2 （2021） 特集I：IoT社会の進歩を促進するワイヤレス技術　　特集Ⅱ：ディジタル信号処理のためのシステム技術

本誌掲載ページ: 193-204 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/141/2/141_193/_article/-char/ja/