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dc.contributor.author Ugail, H.
dc.contributor.author Doherty, V.
dc.contributor.author Zwiggelaar, R.
dc.contributor.author Appleyard, S.
dc.contributor.author Huddy, G.
dc.contributor.author Rajoub, B.
dc.contributor.author Yap, M. H.
dc.date.accessioned 2012-06-13T12:08:47Z
dc.date.available 2012-06-13T12:08:47Z
dc.date.issued 2012-06-13
dc.identifier.citation Ugail , H , Doherty , V , Zwiggelaar , R , Appleyard , S , Huddy , G , Rajoub , B & Yap , M H 2012 , ' A Short Review of Methods for Face Detection and Multifractal Analysis ' pp. 7-11 . en
dc.identifier.other PURE: 185467
dc.identifier.other dspace: 2160/7843
dc.identifier.uri http://hdl.handle.net/2160/7843
dc.description M.H. Yap, H. Ugail, R. Zwiggelaar, B. Rajoub, V. Doherty, S. Appleyard, G. Huddy, ¿A Short Review of Methods for Face Detection and Multifractal Analysis¿, 2009 International Conference on Cyberworlds, 7-11 September 2009, University of Bradford, UK, IEEE Computer Society. ISBN: 978-0-7695-3791-7 en
dc.description.abstract The purpose of this paper is to present short reviews the face detection techniques and to study the effect of Multifractal analysis in detecting facial features. In reviewing the existing techniques, we have compared the performance of Nilsson et al¿s algorithm, Haar Training implemented within Open Source Computer Vision Library (OpenCV) and Keinzle¿s algorithm in face detection. Then, we have produced some experimental results suggesting that the Multifractal approach would help to extract key facial features of a human face. We conclude the paper with some discussions on how the work can be taken further. en
dc.format.extent 5 en
dc.language.iso eng
dc.relation.ispartof en
dc.title A Short Review of Methods for Face Detection and Multifractal Analysis en
dc.type Text en
dc.type.publicationtype Conference paper en
dc.contributor.institution Department of Computer Science en
dc.description.status Non peer reviewed en


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