Improved Hand-Tracking Framework with a Recovery Mechanism

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dc.contributor.authorAchmed, Imran
dc.contributor.authorVenter, Isabella M.
dc.contributor.authorEisert, Peter
dc.date.accessioned2014-08-15T10:09:17Z
dc.date.available2014-08-15T10:09:17Z
dc.date.issued2013
dc.description.abstractAbstract−Hand-tracking is fundamental to translating sign language to a spoken language. Accurate and reliable sign language translation depends on effective and accurate hand-tracking. This paper proposes an improved hand-tracking framework that includes a tracking recovery algorithm optimising a previous framework to better handle occlusion. It integrates the tracking recovery algorithm to improve the discrimination between hands and the tracking of hands. The framework was evaluated on 30 South African Sign Language phrases that use: a single hand; both hands without occlusion; and both hands with occlusion. Ten individuals in constrained and unconstrained environments performed the gestures. Overall, the proposed framework achieved an average success rate of 91.8% compared to an average success rate of 81.1% using the previous framework. The results show an improved tracking accuracy across all signs in constrained and unconstrained environments.en_US
dc.identifier.citationAchmed, I., Venter, I.M. & Eisert, P. (2013). Improved Hand-Tracking Framework with a Recovery Mechanism. In. Proc. Southern African Telecommunication Networks and Applications Conference, pp. 185-190, Stellenbosch, South Africaen_US
dc.identifier.isbn978-0-620-57882-0
dc.identifier.urihttp://hdl.handle.net/10566/1186
dc.language.isoenen_US
dc.privacy.showsubmitterFALSE
dc.publisherTelkomen_US
dc.rightsCopyright 2013, Telkom. This file may be freely used for educational purposes, as long as it is not altered in any way. Acknowledgement of the authors and the source is required.
dc.status.ispeerreviewedTRUE
dc.subjectHand-trackingen_US
dc.subjectOcclusion handlingen_US
dc.subjectScale Invariant Features Transform (SIFT)en_US
dc.subjectSign language recognitionen_US
dc.titleImproved Hand-Tracking Framework with a Recovery Mechanismen_US
dc.typeConference Proceedingsen_US

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