A robust gesture recognition based on depth data

Lee Jaemin, Hironori Takimoto, Hitoshi Yamauchi, Akihiro Kanazawa, Yasue Mitsukura

研究成果: Conference contribution

15 被引用数 (Scopus)

抄録

In this paper, we propose a novel method for gesture recognition using depth data captured by Microsoft Kinect sensor. Conventionally, the features which have been used for gesture recognition are divided into two parts, hand shape and arm movement. In conventional methods, only two-dimensional hand features are used because human's hand consists of the multiple joint structure. Furthermore, conventional arm movement feature are influenced by environmental changing, such as individual differences in body size, camera position and so on. Therefore, to assist in the recognition, a method of feature extraction is proposed, which involves the hand shape with 3D feature and the arm movement with angle between joints of body. In order to show effectiveness of the proposed method, performance for gesture recognition is compared with conventional methods using Japanese language.

本文言語English
ホスト出版物のタイトルFCV 2013 - Proceedings of the 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision
ページ127-131
ページ数5
DOI
出版ステータスPublished - 2013 4 15
イベント19th Korea-Japan Joint Workshop on Frontiers of Computer Vision, FCV 2013 - Incheon, Korea, Republic of
継続期間: 2013 1 302013 2 1

出版物シリーズ

名前FCV 2013 - Proceedings of the 19th Korea-Japan Joint Workshop on Frontiers of Computer Vision

Other

Other19th Korea-Japan Joint Workshop on Frontiers of Computer Vision, FCV 2013
CountryKorea, Republic of
CityIncheon
Period13/1/3013/2/1

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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