Person-Independent 3D Sign Language Recognition
نویسندگان
چکیده
We present an automatic sign language recognition system that is vision-based, person-independent, and non-obtrusive. Its task is to evaluate the correctness of an isolated sign. The unique features are an adaptive skin model to find the hands, 3D features, Dynamic Time Warping for synchronising signs and automatic feature selection for finding the best sign representation. A Dutch 120-sign vocabulary, trained on 60 persons and tested on 10 others, yielded a recognition rate of 95% at a 5% false positive rate. This is high compared to other person-independent systems. The system is meant to be used in schools for the deaf.
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