Hand recognition for augmented reality

Abstract

In recent years, Augmented Reality (AR) becomes the focus of attention as a technology for obtaining some information. Most AR systems have used some markers to display any information. However, since markerless AR systems can be used intuitively, they are researched actively. In this paper, we study about the AR system based on the hand recognition as a markerless system. The reason why we used a hand is that we don't need to prepare or carry on any tool, and can easy to watch any information on a hand. Taehee Lee et al. introduced HandyAR which employ the hand recognition. In this method, there are some problems. At first, when the method learns skin model, it needs many learning data. This is because it uses RGB color model. Secondly, it is difficult to get hand because hand images which are extracted by the skin model have noise. Thirdly, the method uses finger positions to estimate the hand coordinate. Therefore it is sensitive to finger state. We improved HandyAR to solve these problems. Experimental result showed that our method had higher performance than conventional methods. © 2011 The Institute of Electrical Engineers of Japan.