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Fast and efficient face recognition system using random forest and histograms of oriented gradients

dc.contributor.authorSalhi, Abdel Ilah
dc.contributor.authorKardouchi, Mustapha
dc.contributor.authorBelacel, Nabil
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.date.accessioned2018-11-19T13:16:37Z
dc.date.available2018-11-19T13:16:37Z
dc.date.issued2012
dc.description.abstractThe efficient face recognition systems are those which are able to achieve higher recognition rate with lower computational cost. To develop such systems both feature representation and classification method should be accurate and less time consuming.Aiming to satisfy these criteria we coupled the HOG descriptor (Histograms of Oriented Gradients) with the Random Forest classifier (RF). Although rarely used in face recognition, HOG have proven to be a power descriptor in this task with a lower computational time. As regards classification method, recent works have shown that apart from their accuracy when compared with its competitors, Random Forest exhibits a low computational time in both training and testing phase. Experimental results on ORL database have demonstrated the efficiency of this combination.en
dc.identifier.isbn978-3-88579-290-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/18305
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.titleFast and efficient face recognition system using random forest and histograms of oriented gradientsen
dc.typeText/Conference Paper
gi.citation.endPage303
gi.citation.publisherPlaceBonn
gi.citation.startPage293
gi.conference.date06.-07. September 2012
gi.conference.locationDarmstadt
gi.conference.sessiontitleRegular Research Papers

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