| Author | Search for: Salhi, Abdel Ilah; Search for: Kardouchi, Mustapha; Search for: Belacel, Nabil1 |
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| Affiliation | - National Research Council of Canada. Information and Communication Technologies
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| Format | Text, Article |
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| Conference | 2012 International Conference of the Biometrics Special Interest Group (BIOSIG), 6-7 September 2012, Darmstadt, Germany |
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| Abstract | 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. |
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| Publication date | 2012-09 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 21268094 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | d7f33e83-d1a5-4a34-b194-614aee4a4f9e |
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| Record created | 2013-04-09 |
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| Record modified | 2020-04-21 |
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