Fast and efficient face recognition system using Random Forest and Histograms of Oriented Gradients

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TypeArticle
Proceedings titleProceedings of the International Conference of the Biometrics Special Interest Group (BIOSIG)
Conference2012 International Conference of the Biometrics Special Interest Group (BIOSIG), 6-7 September 2012, Darmstadt, Germany
ISBN978-1-4673-1010-9
Pages112; # of pages: 12
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.
Publication date
PublisherIEEE
LanguageEnglish
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number21268094
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Record identifierd7f33e83-d1a5-4a34-b194-614aee4a4f9e
Record created2013-04-09
Record modified2016-05-09
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