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PAMI
1998

Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video

9 years 3 months ago
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
—We present two real-time hidden Markov model-based systems for recognizing sentence-level continuous American Sign Language (ASL) using a single camera to track the user’s unadorned hands. The first system observes the user from a desk mounted camera and achieves 92 percent word accuracy. The second system mounts the camera in a cap worn by the user and achieves 98 percent accuracy (97 percent with an unrestricted grammar). Both experiments use a 40-word lexicon.
Thad Starner, Joshua Weaver, Alex Pentland
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 1998
Where PAMI
Authors Thad Starner, Joshua Weaver, Alex Pentland
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