A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for recognizing the simultaneous aspects of American sign language
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Video-Based Sign Language Recognition Using Hidden Markov Models
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
An Approach Based on Phonemes to Large Vocabulary Chinese Sign Language Recognition
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
A vision-based sign language recognition system using tied-mixture density HMM
Proceedings of the 6th international conference on Multimodal interfaces
Using boosting to improve a hybrid HMM/neural network speech recognizer
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Asymmetrically boosted HMM for speech reading
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A boosted classifier tree for hand shape detection
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A dynamic gesture recognition system for the Korean sign language (KSL)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image and video for hearing impaired people
Journal on Image and Video Processing
Novel boosting framework for subunit-based sign language recognition
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Automatic recognition of sign language subwords based on portable accelerometer and EMG sensors
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Hidden Markov model for human to computer interaction: a study on human hand gesture recognition
Artificial Intelligence Review
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Sign language recognition (SLR) plays an important role in human-computer interaction (HCI), especially for the convenient communication between deaf and hearing society. How to enhance the traditional hidden Markov models (HMM) based SLR is an important issue in the SLR community. And how to refine the boundaries of the classifiers to effectively characterize the property of spread-out of the training samples is another significant issue. In this paper, a new classification framework applying adaptive boosting (AdaBoost) strategy to continuous HMM (CHMM) training procedure at the subwords classification level for SLR is presented. The ensemble of multiple composite CHMMs for each subword trained in boosting iterations tends to concentrate more on the hard-to-classify samples so as to generate more complex decision boundary than that of the single HMM classifier. Experimental results on the vocabulary of frequently used Chinese sign language (CSL) subwords show that the proposed boosted CHMM outperforms the conventional CHMM for SLR.