Recognition of dynamic hand gestures

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摘要

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. However, continuous deformations of the hand shapes are not permitted. 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 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.

论文关键词:Hand gesture,Hidden Markov model,Contour tracking,Real time system

论文评审过程:Received 6 December 2000, Accepted 7 October 2002, Available online 22 April 2003.

论文官网地址:https://doi.org/10.1016/S0031-3203(03)00042-6