liqin1996

liqin1996

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bidirectional_RNN

bidirectional lstm

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

GAMBIT

This project presents a fast and efficient technique for recognition of continuous hand gestures with a stationary background from video stream. The system consists of four modules- A real time hand tracking module, contour extraction module, tracker detection module, and gesture recognition. First of all, real-time hand tracking and extraction algorithm is applied to trace the moving hand and to extract the hand region, and then motion analysis is performed to characterize the temporal features. We then extract the tracker position from the image. This tracker posture is recognized as a hand gesture. Now it is matched with a set of pre-defined gestures to know its meaning. Before matching gesture, preprocessing is performed to remove other part of human body and to select only part of hand showing some useful gesture.

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