Return to search

The Efficacy of the Eigenvector Approach to South African Sign Language Identification

Masters of Science / The communication barriers between deaf and hearing society mean that interaction between these communities is kept to a minimum. The South African Sign Language research group, Integration of Signed and Verbal Communication: South African Sign Language Recognition and Animation (SASL), at the University of the Western Cape aims to create technologies to bridge the communication gap. In this thesis we address the subject of whole hand gesture recognition. We demonstrate a method to identify South African Sign Language classifiers using an eigenvector approach. The classifiers researched within this thesis are based on those outlined by the Thibologa Sign Language Institute for SASL. Gesture recognition is achieved in real time. Utilising a pre-processing method for image registration we are able to increase
the recognition rates for the eigenvector approach.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uwc/oai:etd.uwc.ac.za:11394/8867
Date January 2010
CreatorsSegers, Vaughn Mackman
ContributorsConnan, James
PublisherUniversity of the Western Cape
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
RightsUniversity of the Western Cape

Page generated in 0.0017 seconds