Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Appearance-based hand sign recognition from intensity image sequences
Computer Vision and Image Understanding
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
A model-based hand gesture recognition system
Machine Vision and Applications
Extraction of 2D Motion Trajectories and Its Application to Hand Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards Appearance-Based Multi-Channel Gesture Recognition
Proceedings of Gesture Workshop on Progress in Gestural Interaction
Towards an Automatic Sign Language Recognition System Using Subunits
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Hands Tracking from Frontal View for Vision-Based Gesture Recognition
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
A Novel Two-Layer PCA/MDA Scheme for Hand Posture Recognition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
An Appearance-Based Framework for 3D Hand Shape Classification and Camera Viewpoint Estimation
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Extraction of 3D Hand Shape and Posture from Image Sequences for Sign Language Recognition
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Active Appearance Models Revisited
International Journal of Computer Vision
Data Driven Image Models through Continuous Joint Alignment
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of skin-color modeling and detection methods
Pattern Recognition
Recent developments in visual sign language recognition
Universal Access in the Information Society
Introduction to digital speech processing
Foundations and Trends in Signal Processing
Modelling and recognition of the linguistic components in American Sign Language
Image and Vision Computing
Generic vs. person specific active appearance models
Image and Vision Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exploiting phonological constraints for handshape inference in ASL video
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Sign Language Recognition using Sequential Pattern Trees
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
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We propose the novel approach of dynamic affine-invariant shape-appearance model (Aff-SAM) and employ it for handshape classification and sign recognition in sign language (SL) videos. Aff-SAM offers a compact and descriptive representation of hand configurations as well as regularized model-fitting, assisting hand tracking and extracting handshape features. We construct SA images representing the hand's shape and appearance without landmark points. We model the variation of the images by linear combinations of eigenimages followed by affine transformations, accounting for 3D hand pose changes and improving model's compactness. We also incorporate static and dynamic handshape priors, offering robustness in occlusions, which occur often in signing. The approach includes an affine signer adaptation component at the visual level, without requiring training from scratch a new singer-specific model. We rather employ a short development data set to adapt the models for a new signer. Experiments on the Boston-University-400 continuous SL corpus demonstrate improvements on handshape classification when compared to other feature extraction approaches. Supplementary evaluations of sign recognition experiments, are conducted on a multi-signer, 100-sign data set, from the Greek sign language lemmas corpus. These explore the fusion with movement cues as well as signer adaptation of Aff-SAM to multiple signers providing promising results.