Title :
Real-time American Sign Language recognition from video using hidden Markov models
Author :
Starner, Thad ; Pentland, Alex
Author_Institution :
Perceptual Comput. Sect., MIT, Cambridge, MA, USA
Abstract :
Hidden Markov models (HMMs) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for 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
Keywords :
handicapped aids; hidden Markov models; image recognition; real-time systems; American Sign Language; American Sign Language recognition; HMM-based system; hand gestures; hidden Markov models; real-time; sign language; visual recognition; Face recognition; Fingers; Handicapped aids; Handwriting recognition; Hidden Markov models; Laboratories; Natural languages; Real time systems; Shape; Speech recognition;
Conference_Titel :
Computer Vision, 1995. Proceedings., International Symposium on
Conference_Location :
Coral Gables, FL
Print_ISBN :
0-8186-7190-4
DOI :
10.1109/ISCV.1995.477012
