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Proceedings Paper

Kinect-based sign language recognition of static and dynamic hand movements
Author(s): Rando C. Dalawis; Kenneth Deniel R. Olayao; Evan Geoffrey I. Ramos; Mary Jane C. Samonte
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Paper Abstract

A different approach of sign language recognition of static and dynamic hand movements was developed in this study using normalized correlation algorithm. The goal of this research was to translate fingerspelling sign language into text using MATLAB and Microsoft Kinect. Digital input image captured by Kinect devices are matched from template samples stored in a database. This Human Computer Interaction (HCI) prototype was developed to help people with communication disability to express their thoughts with ease. Frame segmentation and feature extraction was used to give meaning to the captured images. Sequential and random testing was used to test both static and dynamic fingerspelling gestures. The researchers explained some factors they encountered causing some misclassification of signs.

Paper Details

Date Published: 8 February 2017
PDF: 6 pages
Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102250I (8 February 2017); doi: 10.1117/12.2266729
Show Author Affiliations
Rando C. Dalawis, Mapua Institute of Technology (Philippines)
Kenneth Deniel R. Olayao, Mapua Institute of Technology (Philippines)
Evan Geoffrey I. Ramos, Mapua Institute of Technology (Philippines)
Mary Jane C. Samonte, Mapua Institute of Technology (Philippines)


Published in SPIE Proceedings Vol. 10225:
Eighth International Conference on Graphic and Image Processing (ICGIP 2016)
Yulin Wang; Tuan D. Pham; Vit Vozenilek; David Zhang; Yi Xie, Editor(s)

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