Context-based recognition of manipulative hand gestures for human computer interaction
This paper presents a system recognizing manipulative hand gestures like grasping, moving, holding an object(s) with both hands, and extending or shortening of the object(s) in the virtual world using contextual information. Contextual information is represented by a state transition diagram, each state of which indicates possible gestures at the next moment. Image features obtained from extracted hand regions are used to judge state transition. When we use a gesture recognition system, we sometimes move our hands unintentionally. To solve this problem, our system has a rest state in the state transition diagram. All unintentional actions are considered as taking a rest and ignored. In addition, the system can recognize collaborative gestures with both hands. They are expressed in a single state so that the complexity in combination of gestures of each hand can be avoided. We have realized an experimental human interface system. Operational experiments show promising results.
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