Gestural Interaction Using Feature Classification
نویسنده
چکیده
This paper describes our ongoing research work on deviceless interaction using hand gesture recognition with a calibrated stereo system. Video-based interaction is one of the most intuitive kinds of Human-Computer-Interaction with Virtual-Reality applications due to the fact that users are not wired to a computer. If interaction with three-dimensional environments is considered, pointing, grabbing and releasing are the most intuitive gestures used by humans. This paper describes our video-based gesture recognition system that observes the user in front of a large displaying screen, identifying three different hand gestures in real time using 2D feature classification and determines 3D information like the 3D position of the user’s hand or the pointing direction if performed. Different scenario applications like a virtual chess game against the computer or an industrial scenario have been developed and tested. To estimate the possible count of distinguishable gestures a sign language recognition application has been developed and tested using a single uncalibrated camera only.
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تاریخ انتشار 2008