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Isolated sign language recognition using hidden Markov models

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2 Author(s)
Grobel, K. ; Lehrstuhl fur Technische Inf., Tech. Hochschule Aachen, Germany ; Assan, M.

This paper is concerned with the video-based recognition of isolated signs. Concentrating on the manual parameters of sign language, the system aims for the signer dependent recognition of 262 different signs. For hidden Markov modelling a sign is considered a doubly stochastic process, represented by an unobservable state sequence. The observations emitted by the states are regarded as feature vectors, that are extracted from video frames. The system achieves recognition rates up to 94%

Published in:

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on  (Volume:1 )

Date of Conference:

12-15 Oct 1997

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