Sign language recognition using model-based tracking and a 3D Hopfield neural network
Machine Vision and Applications
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parametric Hidden Markov Models for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Appearance-based hand sign recognition from intensity image sequences
Computer Vision and Image Understanding
Extraction of 2D Motion Trajectories and Its Application to Hand Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fast Sign Word Recognition Method for Chinese Sign Language
ICMI '00 Proceedings of the Third International Conference on Advances in Multimodal Interfaces
A Parallel Multistream Model for Integration of Sign Language Recognition and Lip Motion
ICMI '00 Proceedings of the Third International Conference on Advances in Multimodal Interfaces
Video-Based Sign Language Recognition Using Hidden Markov Models
Proceedings of the International Gesture Workshop on Gesture and Sign Language in Human-Computer Interaction
HMM-Based Continuous Sign Language Recognition Using Stochastic Grammars
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
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
Recognition of Local Features for Camera-Based Sign Language Recognition System
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Signer-Independent Sign Language Recognition Based on SOFM/HMM
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Using Multiple Sensors for Mobile Sign Language Recognition
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
American sign language recognition: reducing the complexity of the task with phoneme-based modeling and parallel hidden markov models
A Novel Approach to Automatically Extracting Basic Units from Chinese Sign Language
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
A vision-based sign language recognition system using tied-mixture density HMM
Proceedings of the 6th international conference on Multimodal interfaces
Multilayer architecture in sign language recognition system
Proceedings of the 6th international conference on Multimodal interfaces
Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Geodesic Self-Organizing Map and its error analysis
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
Sign Recognition using Depth Image Streams
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Recognition of Arabic sign language alphabet using polynomial classifiers
EURASIP Journal on Applied Signal Processing
Recent developments in visual sign language recognition
Universal Access in the Information Society
Sign Language Recognition by Combining Statistical DTW and Independent Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sign Language Spotting with a Threshold Model Based on Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
SOMM: Self organizing Markov map for gesture recognition
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Chinese sign language recognition system based on SOFM/SRN/HMM
Pattern Recognition
GSLC: creation and annotation of a Greek sign language corpus for HCI
UAHCI'07 Proceedings of the 4th international conference on Universal access in human computer interaction: coping with diversity
Large lexicon detection of sign language
HCI'07 Proceedings of the 2007 IEEE international conference on Human-computer interaction
A new instrumented approach for translating American sign language into sound and text
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Transition movement models for large vocabulary continuous sign language recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A boosted classifier tree for hand shape detection
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Appearance-Based recognition of words in american sign language
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
Robust person-independent visual sign language recognition
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
A fuzzy rule-based approach to spatio-temporal hand gesturerecognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A Framework for Sign Language Sentence Recognition by Commonsense Context
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Large vocabulary sign language recognition based on fuzzy decision trees
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost.