Dynamic Hand Gesture Recognition Using Kinematic Features Based on Dynamic Time Warping


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Hand gesture provides an attractive alternative to cumbersome interface devices for human computer interface. Many hand gesture recognition methods using visual analysis have been proposed. In our research, we exploit multiple cues including divergence features, vorticity features and hand motion direction vector. Divergence and vorticity are derived from the optical flow for hand gesture recognition in videos. Then these features are computed by principal component analysis method. The hand tracking algorithm finds the hand centroids for every frame, computes hand motion direction vector. At last, we introduced dynamic time warping method to verify the robustness of our features. Those experimental results demonstrate that the proposed approach yields a satisfactory recognition rate.



Edited by:

Yuning Zhong




H. B. Pang and Y. D. Ding, "Dynamic Hand Gesture Recognition Using Kinematic Features Based on Dynamic Time Warping", Applied Mechanics and Materials, Vol. 235, pp. 68-73, 2012

Online since:

November 2012




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