A Component-based Architecture for Vision-based Gesture Recognition
نویسندگان
چکیده
In this paper we present our research on developing a vision-based gesture recognition system. This system has three abstract layers each with their own specific type and requirements of data which enable us to implement them as separate components. The first layer is the skin detection layer. One of our contributions to the research is an adaptive skin detection algorithm that forms the core of this layer. This component provides a set of disperse skin pixels for a tracker that forms the second layer. This second component is based on the Mean-shift algorithm which has been improved for robustness against noise using our novel fuzzy-based edge estimation method that makes the tracker suitable for real world applications. The third component is the gesture recognition layer which is based on a gesture modelling technique and a classification method that we have developed for this purpose. We have used the angle space to model the input gesture and artificial neuralnetworks for classification of the gesture.
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