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Facial Feature Reconstruction using Structure from Motion

dc.contributor.advisorDu Preez, J. A.
dc.contributor.advisorHerbst, B. M.
dc.contributor.authorRautenbach, Pieter Albertusen_ZA
dc.contributor.otherUniversity of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.
dc.date.accessioned2008-08-12T09:33:50Zen_ZA
dc.date.accessioned2010-06-01T09:00:37Z
dc.date.available2008-08-12T09:33:50Zen_ZA
dc.date.available2010-06-01T09:00:37Z
dc.date.issued2005-03
dc.identifier.urihttp://hdl.handle.net/10019.1/2875
dc.descriptionThesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005.
dc.description.abstractStructure from Motion suggests that an object or scene’s three-dimensional structure can be determined from its observed two-dimensional motion. Human efforts, manifested in computer algorithms, try to mimic the enormous power of the visual processing capabilities of the human brain. We present an algorithm to estimate structure, using the Unscented Kalman Filter, from the motion of point-wise features, produced by the Kanade-Lucas-Tomasi feature tracker. The algorithm is evaluated critically against an extensive set of motion sequences, with special attention paid to facial feature reconstruction.en_ZA
dc.language.isoenen_ZA
dc.publisherStellenbosch : University of Stellenbosch
dc.subjectTheses -- Electrical and electronic engineeringen_ZA
dc.subjectDissertations -- Electrical and electronic engineeringen_ZA
dc.subject.lcshThree-dimensional display systemsen_ZA
dc.subject.lcshComputer visionen_ZA
dc.subject.lcshComputer graphicsen_ZA
dc.subject.otherElectrical and Electronic Engineeringen_ZA
dc.titleFacial Feature Reconstruction using Structure from Motionen_ZA
dc.typeThesisen_ZA
dc.rights.holderUniversity of Stellenbosch


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