Development of gesture database for an adaptive gesture recognition system

Abstract

The use of human motions for the interaction between humans and computers is becoming an attractive alternative, especially through the visual interpretation of the human body motion. In particular, hand gesture is used as a non-verbal media for the human to communicate with machines that pertains to the use of human gesture to interact with them. Recently, many studies for recognizing the human gesture have been reported, and most of them deal with the shape and motion of hands. Moreover, they also discuss on factor that contributed to the effect of individual factors in arm motions. This paper mainly concentrated on the development of a gesture database to eliminate individual factors which affect the efficiency of the recognition system. An adaptive gesture recognition system is proposed, and the system could adaptively select the correspond database for the purpose of comparison with the input gesture. A classification algorithm is introduced to investigate whether the individual factor is the primary cause that affects the efficiency of the recognition system. In this study, by examining the characteristics of hand trajectories, motion features are selected and classified by using a statistical approach.