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

Craven, Michael P.; Curtis, K. Mervyn

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.

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 A. Camurri, & G. Volpe (Eds.), Gesture-based communication in human-computer interaction: 5th International Gesture Workshop, GW 2003: Genova, Italy, April 2003: selected revised papers. Springer. https://doi.org/10.1007/978-3-540-24598-8_21

• Publication Date: Jan 1, 2004
• Deposit Date: Feb 12, 2013
• Publicly Available Date: Feb 12, 2013
• 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
• 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
• Public URL: https://nottingham-repository.worktribe.com/output/1021327
• Publisher URL: http://link.springer.com/chapter/10.1007%2F978-3-540-24598-8_21
• Additional Information: The original publication is available at www.springerlink.com