Real-Time American Sign Language Recognition from Video Using Hidden Markov Models [chapter]

Thad Starner, Alex Pentland
1997 Computational Imaging and Vision  
Hidden Markov models (HMM's) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal f o r visual recognition of complex, structured hand gestures such as are found in sign language. We describe a real-time HMM-based system for recognizing sentence level American Sign Language (ASL) which attains a word accuracy of 99.2% without explicitly modeling the fingers.
doi:10.1007/978-94-015-8935-2_10 fatcat:wb756l47snc27cuvpoij6xjtsi