Real-time hand gestures system based on leap motion

In the three-dimensional human-computer interaction, the identification of dynamic and static gestures is a very important and challenging work in the field of machine vision, In this paper, we propose a new gesture recognition system. Leap Motion device is a kind of equipment, which is specially used for hand recognition, which can get the feature data to realize the gesture recognition in real time. The system is mainly composed of the following two parts. For static gestures, we use a kind of feature information based on the distance, direction, and bending degree of the fingertip, and bring the support vector machine into the training to realize the static gesture recognition. For dynamic gestures, we use gesture length as a benchmark to reject non-key gestures and preprocess frames with abnormal gesture sequences. The average recognition rate of static gestures reaches 99.98%, and the recognition rate of dynamic gestures reaches 96.20%. The experimental results show that the algorithm has a good effect on gesture recognition, and it is suitable for the simple interaction between gestures, people and people and daily communication of daily communication barriers.