Gesture recognition using recurrent neural networks
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Recognition Algorithm with Non-contact for Japanese Sign Language Using Morphological Analysis
Proceedings of the International Gesture Workshop on Gesture and Sign Language in Human-Computer Interaction
ARGo: An Architecture for Sign Language Recognition and Interpretation
Proceedings of Gesture Workshop on Progress in Gestural Interaction
A Real-Time Continuous Gesture Recognition System for Sign Language
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
ASL Recognition Based on a Coupling Between HMMs and 3D Motion Analysis
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Research on Computer Science and Sign Language: Ethical Aspects
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Study on Semantic Representations of French Sign Language Sentences
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Automatic Sign Language Analysis: A Survey and the Future beyond Lexical Meaning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Understanding gestures with systematic variations in movement dynamics
Pattern Recognition
Effort analysis in signer-independent sign gestures
Journal of Experimental & Theoretical Artificial Intelligence
A new probabilistic model for recognizing signs with systematic modulations
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Deciphering gestures with layered meanings and signer adaptation
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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There are expressions using spatial relationships in sign language that are called directional verbs. To understand a sign-language sentence that includes a directional verb, it is necessary to analyze the spatial relationship between the recognized sign-language words and to find the proper combination of a directional verb and the sign-language words related to it. In this paper, we propose an analysis method for evaluatingthe spatial relationship between a directional verb and other sign-language words according to the distribution of the parameters representing the spatial relationship.