Dynamic hand gesture recognition using HMM-BPNN model

This paper proposes a new method, combining Hidden Markov Model and BP Neutral Network (called HMM-BPNN Model), to solve the problem of dynamic hand gesture recognition. Specifically, first extract the information of hand gesture feature from 3D depth image using the finger tracking module of Intel perceptual equipment; second, the resulting information of hand gesture feature is modeled with the method of Hidden Markov Model (HMM); third, BP Neutral Network (BPNN), as the classifier, recognizes the inputting dynamic hand gesture. Finally, the results of simulation and experiment verify the feasibility of the proposed method in this paper.