Abstract
In order to provide communication between the deaf-dumb people and the hearing people, a two-stage system translating Turkish Sign Language into Turkish is developed by using vision based approach. Hidden Markov models are utilized to determine the global feature group in the dynamic gesture recognition stage, and k nearest neighbor algorithm is used to compare the local features in the static gesture recognition stage. The system can perform person dependent recognition of 172 isolated signs.
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Haberdar, H., Albayrak, S. (2006). A Two-Stage Visual Turkish Sign Language Recognition System Based on Global and Local Features. In: Esposito, F., Raś, Z.W., Malerba, D., Semeraro, G. (eds) Foundations of Intelligent Systems. ISMIS 2006. Lecture Notes in Computer Science(), vol 4203. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875604_5
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DOI: https://doi.org/10.1007/11875604_5
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