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Automatic Recognition of Head Movement Gestures in Sign Language Sentences
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TLDR
Experiments show the proposed framework is capable of classifying three different head movement gestures and identifying 15 other head movements as movements which are outside of the training set, and an area under the curve measurement of 0:936 for the best performing feature vector.Abstract:
A novel system for the recognition of head movement
gestures used to convey non-manual information in
sign language is presented. We propose a framework for
recognizing a set of head movement gestures and identifying
head movements outside of this set. Experiments show our
proposed system is capable of classifying three different head
movement gestures and identifying 15 other head movements as
movements which are outside of the training set. In this paper
we perform experiments to investigate the best feature vectors
for discriminating between positive a negative head movement
gestures and a ROC analysis of the systems classifications
performance showed an area under the curve measurement
of 0:936 for the best performing feature vector.read more
Citations
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Journal ArticleDOI
Machine learning based sign language recognition: a review and its research frontier
TL;DR: The impact of machine learning in the state of the art literature on sign language recognition and classification is investigated and the potential gaps that machine learning approaches need to address for the real-time signlanguage recognition are discussed.
Journal ArticleDOI
Non-manual grammatical marker recognition based on multi-scale, spatio-temporal analysis of head pose and facial expressions
TL;DR: This paper proposes an automatic recognition system for non-manual grammatical markers in American Sign Language (ASL) based on a multi-scale, spatio-temporal analysis of head pose and facial expressions, which employs learning methods for accurate recognition of non- manual grammatic markers in ASL sentences.
Proceedings Article
Recognition of Nonmanual Markers in American Sign Language (ASL) Using Non-Parametric Adaptive 2D-3D Face Tracking
TL;DR: The proposed new framework makes it possible to detect grammatically significant nonmanual expressions from continuous signing and to differentiate successfully among linguistically significant expressions that involve subtle differences in appearance.
Journal ArticleDOI
Evaluation of Pattern Recognition Methods for Head Gesture-Based Interface of a Virtual Reality Helmet Equipped with a Single IMU Sensor.
Tomasz Hachaj,Marcin Piekarczyk +1 more
TL;DR: Among the most important applications of the proposed method is improving life quality for people who are disabled below the neck by supporting, for example, an assistive autonomous power chair with a head gesture interface or remote controlled interfaces in robotics.
Journal ArticleDOI
A comprehensive survey and taxonomy of sign language research
E. M. El-Alfy,Hamzah Luqman +1 more
TL;DR: Sign language relies on visual gestures of human body parts to convey meaning and plays a vital role in modern society to communicate and interact with people having hearing difficulty as well as for human-machine interaction applications as mentioned in this paper .
References
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Journal ArticleDOI
A tutorial on hidden Markov models and selected applications in speech recognition
TL;DR: In this paper, the authors provide an overview of the basic theory of hidden Markov models (HMMs) as originated by L.E. Baum and T. Petrie (1966) and give practical details on methods of implementation of the theory along with a description of selected applications of HMMs to distinct problems in speech recognition.
Proceedings ArticleDOI
Rapid object detection using a boosted cascade of simple features
Paul A. Viola,Michael Jones +1 more
TL;DR: A machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates and the introduction of a new image representation called the "integral image" which allows the features used by the detector to be computed very quickly.
Journal ArticleDOI
An HMM-based threshold model approach for gesture recognition
Hyeon-Kyu Lee,Jin Hyung Kim +1 more
TL;DR: A new method is developed using the hidden Markov model (HMM) based technique that calculates the likelihood threshold of an input pattern and provides a confirmation mechanism for the provisionally matched gesture patterns.
Journal ArticleDOI
Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning
TL;DR: Data acquisition, feature extraction and classification methods employed for the analysis of sign language gestures are examined and the overall progress toward a true test of sign recognition systems--dealing with natural signing by native signers is discussed.
Journal ArticleDOI
Recent developments in visual sign language recognition
TL;DR: A comprehensive concept for robust visual sign language recognition is described, which represents the recent developments in this field and aims for signer-independent operation and utilizes a single video camera for data acquisition to ensure user-friendliness.
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