In recent years, various gesture recognition systems have been studied for use in television and video games.
In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated. However, with the burgeoning
popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have
become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is
unknown to the user during operation, which imposes several restrictions on his/her actions.
To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture
recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are
prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two
recognition modules of this system are shape analysis using a boosting approach (detection-based approach) and
motion analysis using image frame differences (motion-based approach)(for example, see).
We evaluated this system using sample users and classified the resulting errors into three categories: errors that
depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user
actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture