Recognition and anticipation of hand motions using a recurrent neural network

Abstract

Previous work in recognition of hand gestures has concentrated on classification of hand shapes, with relatively little work done on hand motions. This paper describes a recurrent neural network which has been trained to classify sixteen different hand trajectories, including relatively complex paths such as circles and back-and-forth motions. The network's ability to anticipate the classification of an incomplete gesture is also examined, and its implications for segmentation of gestures is discussed.