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| Research on Dynamic Gesture Recognition Based on Hidden Markov Model |
| DING Ze-yu GONG Wei |
| 1. Changzhi University
2. Guangzhou University of Chinese Medicine
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Abstract With the rapid development of virtual reality technology, more and more researchers are devoting themselves to the research of dynamic gestures recognition. Gesture recognition is a natural and friendly way of human-computer interaction. In this paper, a dynamic gesture recognition system based on Hidden Markov Model (HMM) is built. This system collects dynamic gesture data through Leap Motion and can recognize 36 letters and numbers of gestures (digits 0-9 and A-Z). A lot of experiments show that the system has strong robustness and can recognize individual hands. The recognition rate of potential can reach 93.2%.
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Published: 12 August 2019
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