Hand Gesture Recognition based on SOM and ART
نویسنده
چکیده
Gesture recognition is needed for a variety of applications such as human-computer interfaces, communication aids for the deaf, etc. In this paper, we present a SOMART system for the recognition of hand gestures. The sequence of a hand gesture is first projected into a 2-dimensional trajectory on a self-organizing feature map (SOM). Then the problem of recognizing hand gestures is transformed to the problem of recognizing hand-written characters. An ART-like algorithm generates multiple templates for each hand gesture. Finally, an unknown gesture is classified to be the gesture with the maximum similarity in the vocabulary via a template matching technique. A database consisted of 47 static hand gestures and 8 dynamic hand gestures was tested to demonstrate the performance of the proposed method. Key-Words: Sign language recognition, dynamic gesture recognition, character recognition, self-organizing feature maps (SOM), adaptive resonance theory (ART).
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