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An integrated sign language recognition system

Published:07 October 2013Publication History

ABSTRACT

The South African Sign Language research group at the University of the Western Cape has created several systems to recognize Sign Language gestures using single parameters. Research has shown that five parameters are required to recognize any sign language gesture: hand shape, location, orientation and motion, as well as facial expressions. Using a single parameter can cause conflicts in recognition of signs that are similarly signed. This paper pioneers research at the group towards combining multiple parameters to better distinguish between similar signs. This eventually aims to enable the recognition of a large SASL vocabulary. The proposed methodology combines hand location and hand shape recognition into one combined recognition system. The recognition approach is applied to 12 SASL signs that consist of six pairs of signs with the same hand shape performed at two different locations. It is shown that the approach is able to achieve a high average recognition accuracy of 79% across all signs and distinguish between the signs effectively. It is also shown to be robust to variations in test subjects.

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  1. An integrated sign language recognition system

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            cover image ACM Other conferences
            SAICSIT '13: Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference
            October 2013
            398 pages
            ISBN:9781450321129
            DOI:10.1145/2513456

            Copyright © 2013 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 7 October 2013

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            Acceptance Rates

            SAICSIT '13 Paper Acceptance Rate48of89submissions,54%Overall Acceptance Rate187of439submissions,43%

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