Multi-layered Hand and Face Tracking for Real-Time Gesture Recognition

This paper presents research leading to the development of a vision-based gesture recognition system. The system comprises of three abstract layers each with their own specific type and requirements of data. The first layer is the skin detection layer. This component provides a set of disperse skin pixels for a tracker that forms the second layer. The second component is based on the Mean-shift algorithm which has been improved for robustness against noise using our novel fuzzy-based edge estimation method making the tracker suitable for real world applications. ne third component is the gesture recognition layer which is based on a gesture modeling technique and artificial neural-networks for classification of the gesture.