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 backand -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. Introduction Computer recognition of human hand gestures has potential for application in many fields such as virtual reality interfaces, robotic control and automated sign language translation. Hand data can be captured either via a camera and image processing techniques, or directly through an instrumented glove worn by the user. Pattern recognition techniques can then be applied to this data to classify the gesture made by the user. Components of hand gestures Most of the analys...