Real-time hand shape recognition for human interface

Recently, a natural and user-friendly human interface has been actively researched. Although conventional user interfaces are based on keyboards and mice, human body actions can be used for a human-machine interface. From this point of view, we have researched into vision-based real-time human motion analysis. The important point is that we have employed vision-based methods, because they do not impose any physical restrictions on users. We present a robust hand shape recognition system based on an eigenspace method, in which we employ a simple additional learning feature, and we show its performance through some experiments.