A robust hand tracking and gesture recognition method for wearable visual interfaces and its applications

Gesture-based interface is one of the most promising modes of human-computer interaction for wearable computers. This paper proposes a robust hand tracking and gesture recognition method for wearable visual interfaces, which is an extension of ICONDENSATION algorithm. The method integrates shape and depth information for robust hand tracking. Gesture recognition is realized through the maximum posterior estimation of several pre-defined gestures. The experimental results show that the proposed method works well in dynamic and complex background. Several promising applications in wearable computers are also discussed.