J-013 Gesture Recognition with Both Hands and Head Pose by using Depth Sensor

• Item type: FIT(1)
• 公開日: 2014-08-19
• タイトル / 言語: en
• タイトル: J-013 Gesture Recognition with Both Hands and Head Pose by using Depth Sensor
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属(英): en
• 著者所属(英): University of Tsukuba, Graduate School of Systems and Information Engineering, Department of Computer Science
• 著者所属(英): en
• 著者所属(英): University of Tsukuba, Graduate School of Systems and Information Engineering, Department of Computer Science
• 著者所属(英): en
• 著者所属(英): University of Tsukuba, Graduate School of Systems and Information Engineering, Department of Computer Science
• 著者名(英): Graciliano, Garcia Torres Galindo Jr; Chendra, Hadi Suryanto; Fukui, Kazuhiro
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This pater proposes both hands and head pose recognition for human-machien interaction system. The goal of our system is to provide more natural interaction than conventional methods by considering the head pose. In the system, we used the set of sequential depth images obtained by usin SoftKinetic DepthSense 325 for the hand shape recognition. On the otherhand, grayscale images are used for head pose recognition. In this initial work, the recognitions for hands and head pose are done separately, ty adopting the kernel orthogonal mutual subspace method framework.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA1242354X
• 書誌情報: 情報科学技術フォーラム講演論文集; 巻 13, 号 3, p. 285-288, 発行日 2014-08-19
• 出版者 / 言語: ja
• 出版者: 情報処理学会