How can human communicate with robot by hand gesture?

The use of hand gestures provides an attractive alternative to cumbersome interface devices for human — machine interaction (HMI). However, recognition of hand gestures is not a simple problem. In this paper, we propose to decompose the hand gesture recognition problem into 2 steps. In the first step, we detect skin regions using a very fast algorithm of color segmentation. In the second step, each skin region will be classified into one of hand posture class using cascaded Adaboost classifier and shape analysis techniques. The contribution of this paper is twofold. First, we proposed using both techniques for hand gesture recognition that reduces significantly the computational time in comparison with the traditional use of cascaded Adaboost classifier. Secondly, we integrated successfully this method on the robot and validated it in the context of interaction between human and robot guide in museum.