電動車いす操作支援のための視線・顔向き情報に基づいた意図推定モデルの開発

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: 2022/04/01

タイトル(英語): Development of an Intention Estimation Model Based on Gaze and Face Information for Electric Wheelchair Operation Support

著者名: 比嘉　聖（琉球大学），山田　孝治（琉球大学），神里　志穂子（沖縄工業高等専門学校）

著者名(英語): Sho Higa (University of the Ryukyus), Koji Yamada (University of the Ryukyus), Shihoko Kamisato (National Institute of Technology, Okinawa College)

キーワード: 機械学習，生活支援ロボット，意図推定，視線・顔動作，肢体不自由者　　machine learning，life support robot，estimation of intention，gaze and face behavior，physically disabled persons

要約(英語): In recent years, various user interfaces have been developed to meet the diverse needs of physically disabled persons. In this paper, we developed a method to identify gazing and facial movements based on gaze time and eye/face information and developed an electric wheelchair that can be operated with the user’s "natural gazing and facial movements. This intention estimation model is composed of 1DCNN and LSTM layers. First, 1DCNN is used to extract features from gaze and face information, and then the extracted features are input to LSTM to estimate the user’s intentions regarding movement. The evaluation experiments suggest that the combination of gaze and face information improves the estimation accuracy and contributes to the classification. Furthermore, it was confirmed that adding a convolutional filter layer to the LSTM layer improved the accuracy.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.142 No.4 （2022） 特集：持続可能な社会発展に貢献するスマートレーザプロセシング

本誌掲載ページ: 491-498 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/142/4/142_491/_article/-char/ja/