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dc.contributor.authorShafey, Laurent El
dc.contributor.authorWallace, Roy
dc.contributor.authorMarcel, Sébastien
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.date.accessioned2018-11-19T13:16:39Z
dc.date.available2018-11-19T13:16:39Z
dc.date.issued2012
dc.identifier.isbn978-3-88579-290-1
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/18315
dc.description.abstractThe search for robust features for face recognition in uncontrolled environments is an important topic of research. In particular, there is a high interest in Gaborbased features which have invariance properties to simple geometrical transformations. In this paper, we first reinterpret Gabor filtering as a frequency decomposition into bands, and analyze the influence of each band separately for face recognition. Then, a new face verification scheme is proposed, combining the strengths of Gabor filtering with Gaussian Mixture Model (GMM) modelling. Finally, this new system is evaluated on the BANCA and MOBIO databases with respect to well known face recognition algorithms. The proposed system demonstrates up to 52\% relative improvement in verification error rate compared to a standard GMM approach, and outperforms the state-of-the-art Local Gabor Binary Pattern Histogram Sequence (LGBPHS) technique for several face verification protocols on two different databases.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2012
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-196
dc.titleFace verification using Gabor filtering and adapted Gaussian mixture modelsen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages397-408
mci.conference.sessiontitleRegular Research Papers
mci.conference.locationDarmstadt
mci.conference.date06.-07. September 2012


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