Multi-angle Gait Recognition Based on Skeletal Tracking Data

• Item type: Journal(1)
• 公開日: 2016-04-15
• タイトル: Multi-angle Gait Recognition Based on Skeletal Tracking Data
• タイトル / 言語: en
• タイトル: Multi-angle Gait Recognition Based on Skeletal Tracking Data
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集：インタラクションの理解および基盤・応用技術] multi-angle view, gait recognition, soft biometrics and skeletal tracking
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Chiba Institute of Technology
• 著者所属: AISOL, INC.
• 著者所属: Chiba Institute of Technology
• 著者所属(英): en
• 著者所属(英): Chiba Institute of Technology
• 著者所属(英): en
• 著者所属(英): AISOL, INC.
• 著者所属(英): en
• 著者所属(英): Chiba Institute of Technology
• 著者名: Yusuke, Manabe; Keisuke, Matsumoto; Kenji, Sugawara
• 著者名(英): Yusuke, Manabe; Keisuke, Matsumoto; Kenji, Sugawara
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Human gait recognition is one of the most important authentication technologies as it can often happen that people approach a computer system or a robot by walking. Therefore in this study, a multi-angle gait recognition method has been proposed by using skeletal tracking data, measured by an RGB-D camera. The proposed method includes a two stage process, which estimates an optimal gait angle view from the five discrete angles at the first stage and subsequently recognizes human gait based on the specific features for the respective gait angle views. In order to evaluate the proposed method, two types of experiments have been done: gait angle estimation and gait recognition. From the result of the first experiment, the best estimation of 97.4% accuracy has been achieved. In the second experiment, the best gait recognition accuracy was 96.4%. Finally the best gait recognition accuracy with the two stage process has been estimated as 93.9%.; \n------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.24(2016) No.3 (online); ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Human gait recognition is one of the most important authentication technologies as it can often happen that people approach a computer system or a robot by walking. Therefore in this study, a multi-angle gait recognition method has been proposed by using skeletal tracking data, measured by an RGB-D camera. The proposed method includes a two stage process, which estimates an optimal gait angle view from the five discrete angles at the first stage and subsequently recognizes human gait based on the specific features for the respective gait angle views. In order to evaluate the proposed method, two types of experiments have been done: gait angle estimation and gait recognition. From the result of the first experiment, the best estimation of 97.4% accuracy has been achieved. In the second experiment, the best gait recognition accuracy was 96.4%. Finally the best gait recognition accuracy with the two stage process has been estimated as 93.9%.; \n------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.24(2016) No.3 (online); ------------------------------
• 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: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 57, 号 4, 発行日 2016-04-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764