Real-time American Sign Language recognition from video using hidden Markov models

I
ISCV
1995
International Symposium on Computer Vision
Abstract - Real-time American Sign Language recognition from video using hidden Markov models

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	Similar Articles Articles by T. Starner Articles by A. Pentland

International Symposium on Computer Vision

Coral Gables, Florida

November 21-November 23

ISBN: 0-8186-7190-4

	ASCII Text	x
	T. Starner, A. Pentland, "Real-time American Sign Language recognition from video using hidden Markov models," Computer Vision, International Symposium on, pp. 265, International Symposium on Computer Vision, 1995.

	BibTex	x
	@article{ 10.1109/ISCV.1995.477012, author = {T. Starner and A. Pentland}, title = {Real-time American Sign Language recognition from video using hidden Markov models}, journal ={Computer Vision, International Symposium on}, volume = {0}, year = {1995}, isbn = {0-8186-7190-4}, pages = {265}, doi = {http://doi.ieeecomputersociety.org/10.1109/ISCV.1995.477012}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer Vision, International Symposium on TI - Real-time American Sign Language recognition from video using hidden Markov models SN - 0-8186-7190-4 SP EP A1 - T. Starner, A1 - A. Pentland, PY - 1995 KW - hidden Markov models; handicapped aids; image recognition; real-time systems; American Sign Language recognition; hidden Markov models; visual recognition; hand gestures; sign language; American Sign Language; real-time; HMM-based system VL - 0 JA - Computer Vision, International Symposium on ER -

T. Starner, Perceptual Comput. Sect., MIT, Cambridge, MA, USA

A. Pentland, Perceptual Comput. Sect., MIT, Cambridge, MA, USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISCV.1995.477012

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.

Index Terms:

hidden Markov models; handicapped aids; image recognition; real-time systems; American Sign Language recognition; hidden Markov models; visual recognition; hand gestures; sign language; American Sign Language; real-time; HMM-based system

Citation:

T. Starner, A. Pentland, "Real-time American Sign Language recognition from video using hidden Markov models," iscv, pp.265, International Symposium on Computer Vision, 1995

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