A Novel Hand Gesture Recognition Method using Principal Directional Features

被引：0
|
作者：
Jasim, Mahmood [1 ]
Zhang, Tao [2 ]
Hasanuzzaman, Md. [1 ]
机构：
[1] Univ Dhaka, Dept Comp Sci & Engn, Dhaka 1000, Bangladesh
[2] Tsinghua Univ, Dept Automat, Sch Informat Sci & Technol, Beijing 100084, Peoples R China
来源：
2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO) | 2013年
关键词：
D O I：
暂无
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
This paper presents a novel hand gesture recognition method based on Principal Directional Features (PDF). The image sequence is captured using a fixed mounted monocular camera to recognize dynamic gestures. Haar-like feature based cascaded classifier is used for hand area segmentation. Text based Principal Directional Features are extracted from the segmented images. Longest Common Subsequence algorithm is used to recognize the gestures from text based PDF. The Directional Gesture dataset is prepared containing complex dynamic gestures to test this system and achieved 94% accuracy in recognizing dynamic hand gestures.
引用
收藏
页码：1264 / 1269
页数：6
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