A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Making large-scale support vector machine learning practical
Advances in kernel methods
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Robust Real-Time Face Detection
International Journal of Computer Vision
Australian sign language recognition
Machine Vision and Applications
Improvements to Platt's SMO Algorithm for SVM Classifier Design
Neural Computation
Hidden Conditional Random Fields for Gesture Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Sign Language Spotting with a Threshold Model Based on Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hand movement recognition for brazilian sign language: a study using distance-based neural networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Discriminative Models-Based Hand Gesture Recognition
ICMV '09 Proceedings of the 2009 Second International Conference on Machine Vision
Automatic recognition of finger spelling for LIBRAS based on a two-layer architecture
Proceedings of the 2010 ACM Symposium on Applied Computing
American sign language recognition with the kinect
ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A Framework for Hand Gesture Recognition Based on Accelerometer and EMG Sensors
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition
IEEE Transactions on Audio, Speech, and Language Processing
Proceedings of the 11th Brazilian Symposium on Human Factors in Computing Systems
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This paper describes the authors' experiments with Support Vector Machines and Hidden Conditional Random Fields on the classification of freely articulated sign words drawn from the Brazilian Sign Language (Libras). While our previous works focused specifically on fingerspelling recognition on tightly controlled environment conditions, in this work we perform the classification of natural signed words in an unconstrained background without the aid of gloves or wearable tracking devices. We show how our choice of feature vector, extracted from depth information and based on linguistic investigations, is rather effective for this task. Again we provide comparison results against Artificial Neural Networks and Hidden Markov Models, reporting statistically significant results favoring our choice of classifiers; and we validate our findings using the chance-corrected Cohen's Kappa statistic for contingency tables.