Online Visual Recognition of Dynamic Gestures Using Dynamic Bayesian Networks
نویسندگان
چکیده
Gestures are a natural and effective altenative to command mobile robots. This paper describes an online visual recognition system to recognize a set of 5 dynamic gestures executed with the user’s right hand and oriented to command mobile robots. The system employs a radial scan segmentation algorithm combined with a statistical-based skin detection method to find the candidate face of the user and to track his right-hand. It uses 4 simple features to describe the user’s right-hand movement and Dynamic Bayesian Networks as recognition technique. This system is able to recognize these five gestures in real time with an average recognition rate of 84.01%, better result than using hidden Markov models for recognition.
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تاریخ انتشار 2002