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 Geometry-based Dynamic Hand Gesture Recognition
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Tác giả hoặc Nhóm tác giả: Duc-Hoang Vo, Huu-Hung Huynh, and Jean Meunier
Nơi đăng: Issue on Information and Communications Technology
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; Số: Vol 1 (1);Từ->đến trang: 13-19;Năm: 2015
Lĩnh vực: Công nghệ thông tin; Loại: Bài báo khoa học; Thể loại: Trong nước
TÓM TẮT
Hand gestures play an important role in communication in the hard-of-hearing community. They are used to convey information instead of words. Besides, a system which is developed to identify gestures can be also used forhuman-computer interaction. In this paper, we propose a vision-based approach for recognizing dynamic hand gestures. Ourprocessing consists of three main stages: pre-processing, feature extraction and recognition. The first stage involves twosub-stages: segmentation which locates the hand and extracts the corresponding silhouette using color information;separation that removes the arm based on geometrical properties. Some characteristics which describe the hand posture arethen extracted. Finally, the recognition is performed using two popular algorithms, which are Dynamic Time Warping andHidden Markov Model. The experiment is conducted on SKIG dataset with a comparison of classification accuraciescorresponding to the two mentioned methods.
ABSTRACT
Hand gestures play an important role in communication in the hard-of-hearing community. They are used to convey information instead of words. Besides, a system which is developed to identify gestures can be also used forhuman-computer interaction. In this paper, we propose a vision-based approach for recognizing dynamic hand gestures. Ourprocessing consists of three main stages: pre-processing, feature extraction and recognition. The first stage involves twosub-stages: segmentation which locates the hand and extracts the corresponding silhouette using color information;separation that removes the arm based on geometrical properties. Some characteristics which describe the hand posture arethen extracted. Finally, the recognition is performed using two popular algorithms, which are Dynamic Time Warping andHidden Markov Model. The experiment is conducted on SKIG dataset with a comparison of classification accuraciescorresponding to the two mentioned methods.
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