Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gravity-Center Template Based Human Face Feature Detection
ICMI '00 Proceedings of the Third International Conference on Advances in Multimodal Interfaces
HandTalker: A Multimodal Dialog System Using Sign Language and 3-D Virtual Human
ICMI '00 Proceedings of the Third International Conference on Advances in Multimodal Interfaces
The Recognition Algorithm with Non-contact for Japanese Sign Language Using Morphological Analysis
Proceedings of the International Gesture Workshop on Gesture and Sign Language in Human-Computer Interaction
A Real-Time Continuous Gesture Recognition System for Sign Language
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Relevant Features for Video-Based Continuous Sign Language Recognition
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
A vision-based sign language recognition system using tied-mixture density HMM
Proceedings of the 6th international conference on Multimodal interfaces
Non-manual cues in automatic sign language recognition
Personal and Ubiquitous Computing
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In this paper, a new sign-wise tied mixture HMM (SWTM-HMM) is proposed and applied in vision-based sign language recognition (SLR). In the SWTMHMM, the mixture densities of the same sign model are tied so that the states belonging to the same sign share a common local codebook, which leads to robust model parameters estimation and efficient computation of probability densities. For the sign feature extraction, an effective hierarchical feature description scheme with different scales of features to characterize sign language is presented. Experimental results based on 439 frequently used Chinese sign language (CSL) signs show that the proposed methods can work well for the medium vocabulary SLR in the unconstrained environment.