Efficient Hand Gesture Rendering and Decoding using a Simple Gesture Library

Abstract

Recent work in hand gesture rendering and decoding has treated the two fields as separate and distinct. As the work of rendering evolves, it emphasizes exact movement replication, including more muscle and skeletal parameterization. The work in gesture decoding is largely centered on trained systems, which require large amounts of time in front of a camera rendering a gesture in order to decode movement. This paper presents a new scheme which more tightly couples the gesture rendering and decoding processes. While this scheme is simpler than existing techniques, the rendering remains natural looking, and decoding a new gesture does not require extensive training.