Traditional methods for the extraction and identification of the data of dynamic isolated gestures

which constitute a complex and high cost

which is easy to be disturbed by the external environment

and the recognition accuracy is low. The study of dynamic hand gesture recognition method based on Kinect

obtaining the depth information of dynamic gesture using Kinect sensor

the human hand positioning real-time and accurate tracking

feature and image denoising processing

the extraction of hand movement; finally introduce the hidden Markov model (HMM) for effective training on dynamic gesture and moving track sample set

to achieve dynamic hand gesture recognition. Experiments show that the proposed method has high recognition rate and high robustness in the environment of noise interference and light loss.