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Hand Gesture Interface Using Mobile Camera Devices  

Lee, Chan-Su (영남대학교 전자공학과)
Chun, Sung-Yong (영남대학교 전자공학과)
Sohn, Myoung-Gyu (대구경북과학기술원 미래산업융합기술연구부)
Lee, Sang-Heon (대구경북과학기술원 미래산업융합기술연구부)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.16, no.5, 2010 , pp. 621-625 More about this Journal
Abstract
This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.
Keywords
Hand gesture recognition; motion estimation; gesture interface; optical flow; mobile device;
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