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GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures

Craven, Michael P.; Curtis, K. Mervyn

Authors

Michael P. Craven michael.craven@nottingham.ac.uk

K. Mervyn Curtis



Contributors

Antonio Camurri
Editor

Gualtiero Volpe
Editor

Abstract

A complete microcomputer system is described, GesRec3D, which facilitates the data acquisition, segmentation, learning, and recognition of 3-Dimensional arm gestures, with application as a Augmentative and Alternative Communication (AAC) aid for people with motor and speech disability. The gesture data is acquired from a Polhemus electro-magnetic tracker system, with sensors attached to the finger, wrist and elbow of one arm. Coded gestures are linked to user-defined text, to be spoken by a text-to-speech engine that is integrated into the system. A segmentation method and an algorithm for classification are presented that includes acceptance/rejection thresholds based on intra-class and inter-class dissimilarity measures. Results of recognition hits, confusion misses and rejection misses are given for two experiments, involving predefined and arbitrary 3D gestures.

Publication Date Jan 1, 2004
Peer Reviewed Peer Reviewed
Issue 2915
Series Title Lecture notes in computer science
Book Title Gesture-based communication in human-computer interaction: 5th International Gesture Workshop, GW 2003: Genova, Italy, April 2003: selected revised papers
ISBN 9783540210726
APA6 Citation Craven, M. P., & Curtis, K. M. (2004). GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures. In G. Volpe, & A. Camurri (Eds.), Gesture-based communication in human-computer interaction: 5th International Gesture Workshop, GW 2003: Genova, Italy, April 2003: selected revised papersSpringer. doi:10.1007/978-3-540-24598-8_21
DOI https://doi.org/10.1007/978-3-540-24598-8_21
Keywords gesture recognition, dissimilarity, similarity, segmentation, text-to-speech, gesture-to-speech, sign language, 3D tracking, Augmentative and Alternative Communication, AAC, human computer interaction, HCI
Publisher URL http://link.springer.com/chapter/10.1007%2F978-3-540-24598-8_21
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
Additional Information The original publication is available at www.springerlink.com

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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