In order to deal with the problem of low recognition rate of traditional hand gesture recognition algorithm with complex background

a gesture recognition algorithm based on depth information is proposed. Depth image is obtained by the depth camera of Kinect

pre-processing is performed after dividing the gesture area.Geometric features of hand gesture are extracted

character of concentric distribution histogram of depth information is presented. Learn and train random forest classifier for gesture recognition

the geometric features of the hand gestures and the histograms of the concentric circles of the depth information are used to recognize the tested hand gesture via random forest classifier. Three kinds of gestures

such as stone

scissors and cloth

are tested under complex background. The experimental results show that the proposed method has better translation

rotation and scaling invariance

and can adapt to the change of complex environment.