With the development of Virtual Reality (VR) technology and the increasing demand for human-computer interaction performance and experience, gesture recognition is one of the important technologies affecting the interaction in VR, and its accuracy needs to be improved. Aiming at the problem that the current gesture recognition method performs poorly in some similar gesture recognition, a multi-feature dynamic gesture recognition method is proposed. Firstly, this method uses Leap Motion to track the dynamic gestures to acquire data, then adds the displacement vector angle and the inflection point judgment in the feature extraction process, after that performs the training of the dynamic gesture Hidden Markov Model (HMM). Finally, the recognition is carried out according to the matching ratio of the gesture to be tested and the model. It is concluded from the experimental results that the multi-feature recognition method can improve the recognition rate of similar gestures.