A hand gesture recognition system based on local linear embedding

Even after more than two decades of input devices development, many people still find the interaction with computers an uncomfortable experience. Efforts should be made to adapt computers to our natural means of communication: speech and body language. The aim of this paper is to propose a real-time vision system within visual interaction environments through hand gesture recognition, using general-purpose hardware and low-cost sensors, like a simple computer and an USB web camera, so any user could make use of it in his office or at home. The basis of our method is a fast detection process to obtain the meaningful hand region from the whole image, which is able to deal with a large number of hand gestures against different indoor backgrounds and lighting condition, and a recognition process that identifies the hand gestures from the images of the normalized hand. The most important part of the recognition method is a feature extraction process using local linear embedding. This paper includes experimental evaluations of the recognition process of 30 hand gestures that belong to Chinese sign language (CSL) alphabet and discusses the results. Experiments show that the new approach can achieve a 90% average rate and is suitable for real-time application.