A 2-D Hand Gesture Recognition System for Robot Control  (undergraduate research)
(collaborators: Aditya Ramamoorthy at Iowa State, Santanu Chaudhury and Subhashis Bannerjee at IIT-Delhi)

This paper is concerned with the problem of recognition of dynamic hand gestures. We have considered gestures which are sequences of distinct hand poses. In these gestures hand poses can undergo motion and discrete changes. We have developed a recognition engine which can reliably recognize these gestures despite individual variations. The engine also has the ability to detect start and end of gesture sequences in an automated fashion. The recognition strategy uses a combination of static shape recognition (performed using PCA and contour discriminant analysis), Kalman filter based hand tracking and a HMM based temporal characterization scheme. The system is fairly robust to background clutter and uses skin color for static shape recognition and tracking. A real time implementation on standard hardware is developed. Experimental results establish the effectiveness of the approach.