Abstract
The paper considers recognition of isolated words of the Polish Sign Language using a canonical stereo system that observes the signer from a frontal view. Recognition is based on human skin detection and Hidden Markov Models. Several feature vectors taking into account information about the hand shape and 3D position of the hand with respect to the face are examined. To improve the recognition rate the classifiers are combined by voting or by fuzzy integral. We focus on 101 words that can be used at the doctor’s and at the post office.
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