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» Parallel Hidden Markov Models for American Sign Language Rec...
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CVPR
2012
IEEE
12 years 12 months ago
Enhanced continuous sign language recognition using PCA and neural network features
In this work a Gaussian Hidden Markov Model (GHMM) based automatic sign language recognition system is built on the SIGNUM database. The system is trained on appearance-based feat...
Yannick L. Gweth, Christian Plahl, Hermann Ney
105
Voted
AMFG
2007
IEEE
255views Biometrics» more  AMFG 2007»
15 years 1 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
ICMI
2003
Springer
166views Biometrics» more  ICMI 2003»
15 years 2 months ago
Georgia tech gesture toolkit: supporting experiments in gesture recognition
Gesture recognition is becoming a more common interaction tool in the fields of ubiquitous and wearable computing. Designing a system to perform gesture recognition, however, can...
Tracy L. Westeyn, Helene Brashear, Amin Atrash, Th...
86
Voted
WACV
2005
IEEE
15 years 3 months ago
Automatic Recognition of Colloquial Australian Sign Language
This paper presents an automatic Australian sign language (Auslan) recognition system, which tracks multiple target objects (the face and hands) throughout an image sequence and e...
Eun-Jung Holden, Gareth Lee, Robyn A. Owens
GW
2007
Springer
93views Biometrics» more  GW 2007»
15 years 3 months ago
Sequential Belief-Based Fusion of Manual and Non-manual Information for Recognizing Isolated Signs
Abstract. This work aims to recognize signs which have both manual and nonmanual components by providing a sequential belief-based fusion mechanism. We propose a methodology based ...
Oya Aran, Thomas Burger, Alice Caplier, Lale Akaru...