A Real Time Hand Gesture Recognition System Using Motion History Image
Hand gesture recognition based man-machine interface is being developed vigorously in recent years. Due to the effect of lighting and complex background, most visual hand gesture recognition systems work only under restricted environment. An adaptive skin color model based on face detection is utilized to detect skin color regions like hands. To cjassify the dynamic hand gestures, we developed a simple and fast motion history image based method. Four groups of haar like directional patterns were trained for the up, down, left, and right hand gestures classifiers. Together with fist hand and waving hand gestures, there were totally six hand gestures defined. In general, it is suitable to control most home appliances. Five persons doing 250 hand gestures at near. medium, and far distances in front of the web camera were tested. Experimental results show that the accuracy is 941％ in average and the processing time is 3.81 ms per frame. These demonstrated the feasibility of the proposed system.
hand gesture recognition adaptive skin color model motion detection motion history image
Chen-Chiung Hsieh Dung-Hua Liou David Lee
Computer Science and Engineering,Tatung University Taipei, Taiwan Reallusion Inc.2F.No.126.Lane 235, Pao-Chiao Rd.Hsintien, Taipei County 231,Taiwan
国际会议
2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)
大连
英文
1234-1238
2010-07-05（万方平台首次上网日期，不代表论文的发表时间）