Sign Language Recognition
نویسندگان
چکیده
Our goal here is to recognize a sign language measured from wearable sensor gloves. A sign language is expressed as a sequence of gestural patterns to convey a meaning. Hidden Markov models (HMMs) have been shown to be successful in temporal pattern recognition, such as speech, handwriting, and gesture recognition [4]. In this project, we investigate how well HMMs can perform when applied to sign language recognition. We also investigate how different initialization methods and model selections affect the overall performance on classification.
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