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GW
2005
Springer
129views Biometrics» more  GW 2005»
15 years 5 months ago
Visual Sign Language Recognition Based on HMMs and Auto-regressive HMMs
Abstract. A sign language recognition system based on Hidden Markov Models(HMMs) and Auto-regressive Hidden Markov Models(ARHMMs) has been proposed in this paper. ARHMMs fully cons...
Xiaolin Yang, Feng Jiang, Han Liu, Hongxun Yao, We...
CVPR
2009
IEEE
16 years 6 months ago
Automated Extraction of Signs from Continuous Sign Language Sentences using Iterated Conditional Modes
Recognition of signs in sentences requires a training set constructed out of signs found in continuous sentences. Currently, this is done manually, which is a tedious process. I...
Barbara L. Loeding, Sudeep Sarkar, Sunita Nayak
AMFG
2007
IEEE
255views Biometrics» more  AMFG 2007»
15 years 3 months ago
A New Probabilistic Model for Recognizing Signs with Systematic Modulations
Abstract. This paper addresses an aspect of sign language (SL) recognition that has largely been overlooked in previous work and yet is integral to signed communication. It is the ...
Sylvie C. W. Ong, Surendra Ranganath
FGR
2008
IEEE
165views Biometrics» more  FGR 2008»
15 years 1 months ago
Efficient approximations to model-based joint tracking and recognition of continuous sign language
We propose several tracking adaptation approaches to recover from early tracking errors in sign language recognition by optimizing the obtained tracking paths w.r.t. to the hypoth...
Philippe Dreuw, Jens Forster, Thomas Deselaers, He...
CVPR
2007
IEEE
16 years 1 months ago
Enhanced Level Building Algorithm for the Movement Epenthesis Problem in Sign Language Recognition
One of the hard problems in automated sign language recognition is the movement epenthesis (me) problem. Movement epenthesis is the gesture movement that bridges two consecutive s...
Ruiduo Yang, Sudeep Sarkar, Barbara L. Loeding