Upper body pose recognition and estimation towards the translation of South African sign language

Simple item page
dc.contributor.advisorConnan, James
dc.contributor.authorAchmed, Imran
dc.contributor.otherDept. of Computer Science
dc.contributor.otherFaculty of Economics and Management Sciences
dc.date.accessioned2013-09-09T11:13:50Z
dc.date.accessioned2024-10-30T14:00:47Z
dc.date.available2011/05/04 12:15
dc.date.available2011/05/04
dc.date.available2013-09-09T11:13:50Z
dc.date.available2024-10-30T14:00:47Z
dc.date.issued2011
dc.descriptionMasters of Scienceen_US
dc.description.abstractRecognising and estimating gestures is a fundamental aspect towards translating from a sign language to a spoken language. It is a challenging problem and at the same time, a growing phenomenon in Computer Vision. This thesis presents two approaches, an example-based and a learning-based approach, for performing integrated detection, segmentation and 3D estimation of the human upper body from a single camera view. It investigates whether an upper body pose can be estimated from a database of exemplars with labelled poses. It also investigates whether an upper body pose can be estimated using skin feature extraction, Support Vector Machines (SVM) and a 3D human body model. The example-based and learning-based approaches obtained success rates of 64% and 88%, respectively. An analysis of the two approaches have shown that, although the learning-based system generally performs better than the example-based system, both approaches are suitable to recognise and estimate upper body poses in a South African sign language recognition and translation system.en_US
dc.description.countrySouth Africa
dc.identifier.urihttps://hdl.handle.net/10566/16954
dc.language.isoenen_US
dc.publisherUniversity of the Western Capeen_US
dc.rights.holderUniversity of the Western Capeen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectSign Languageen_US
dc.subjectMarkov processesen_US
dc.subjectOptical pattern recognitionen_US
dc.subjectTranslationsen_US
dc.subjectTranslators (Computer programs)en_US
dc.titleUpper body pose recognition and estimation towards the translation of South African sign languageen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Achmed_MSC_2011.pdf
Size:
9.65 MB
Format:
Adobe Portable Document Format
Download

Collections

Magister Scientiae - MSc (Computer Science)