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

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3 Author(s)
Abdel Ilah Salhi ; Computer Science Department, University of Moncton, NB, Canada, E1A 3E9 ; Mustapha Kardouchi ; Nabil Belacel

The 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.

Published in:

Biometrics Special Interest Group (BIOSIG), 2012 BIOSIG - Proceedings of the International Conference of the

Date of Conference:

6-7 Sept. 2012