GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures
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 d...
| Main Authors: | , |
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| Format: | Book Section |
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Springer
2004
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| Online Access: | https://eprints.nottingham.ac.uk/1899/ |
| _version_ | 1848790681742475264 |
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| author | Craven, Michael P. Curtis, K. Mervyn |
| author2 | Camurri, Antonio |
| author_facet | Camurri, Antonio Craven, Michael P. Curtis, K. Mervyn |
| author_sort | Craven, Michael P. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T18:16:29Z |
| format | Book Section |
| id | nottingham-1899 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:16:29Z |
| publishDate | 2004 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-18992020-05-04T20:31:23Z https://eprints.nottingham.ac.uk/1899/ GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures Craven, Michael P. Curtis, K. Mervyn 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. Springer Camurri, Antonio Volpe, Gualtiero 2004 Book Section PeerReviewed Craven, Michael P. and Curtis, K. Mervyn (2004) GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures. In: Gesture-based communication in human-computer interaction: 5th International Gesture Workshop, GW 2003: Genova, Italy, April 2003: selected revised papers. Lecture notes in computer science (2915). Springer, Berlin, pp. 231-238. ISBN 9783540210726 gesture recognition dissimilarity similarity segmentation text-to-speech gesture-to-speech sign language 3D tracking Augmentative and Alternative Communication AAC human computer interaction HCI http://link.springer.com/chapter/10.1007%2F978-3-540-24598-8_21 doi:10.1007/978-3-540-24598-8_21 doi:10.1007/978-3-540-24598-8_21 |
| spellingShingle | gesture recognition dissimilarity similarity segmentation text-to-speech gesture-to-speech sign language 3D tracking Augmentative and Alternative Communication AAC human computer interaction HCI Craven, Michael P. Curtis, K. Mervyn GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures |
| title | GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures |
| title_full | GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures |
| title_fullStr | GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures |
| title_full_unstemmed | GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures |
| title_short | GesRec3D: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures |
| title_sort | gesrec3d: a real-time coded gesture-to-speech system with automatic segmentation and recognition thresholding using dissimilarity measures |
| topic | gesture recognition dissimilarity similarity segmentation text-to-speech gesture-to-speech sign language 3D tracking Augmentative and Alternative Communication AAC human computer interaction HCI |
| url | https://eprints.nottingham.ac.uk/1899/ https://eprints.nottingham.ac.uk/1899/ https://eprints.nottingham.ac.uk/1899/ |