Human communicate with robot by hand gesture
Abstract:
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 thismethod on the robot and
validated it in the context of interaction between human and robot guide in
museum.
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