Back-view based visual hand gesture recognition system

Abstract

Gesture recognition is a fascinating area of research due to its applications to HCI (human computer interaction), entertainment, and communication between deaf/ mute people etc. Gesture can be dynamic or static depending upon the application. Static gestures can be called postures. Dynamic gestures are collection or sequence of postures. Our method is an attempt to classify various postures in American Sign Language (ASL) for a wearable computer device like “Sixth Sense” (developed at MIT media lab) [17]. We are working with new set of features including verticalhorizontal histogram of a posture-shape. We are using Linear Discriminant Analyzer (LDA) Classifier for the purpose of classification. Also, our work is an attempt to raise some issues regarding the kind of problem that can rise during posture-shape recognition and how a simple classification technique with a new feature set can give fairly good results.