Gesture recognition using recurrent neural networks

A gesture recognition method for Japanese sign language is presented. We have developed a posture recognition system using neural networks which could recognize a finger alphabet of 42 symbols. We then developed a gesture recognition system where each gesture specifies a word. Gesture recognition is more difficult than posture recognition because it has to handle dynamic processes. To deal with dynamic processes we use a recurrent neural network. Here, we describe a gesture recognition method which can recognize continuous gesture. We then discuss the results of our research.