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|Title:||AUTOMATIC AGE ESTIMATION AND GENDER CLASSIFICATION IN THE WILD|
|Keywords:||Age estimation, Gender classification, Local Binary Pattern, Support Vector Machines|
|Abstract:||Automatic age estimation and gender classification through facial images are attractive topics in computer vision. They can be used in many real-life applications such as face recognition and internet safety for minors. In this paper, we present a novel approach for age estimation and gender classification under uncontrolled conditions following the standard protocols for fair comparaison. Our proposed approach is based on Multi Level Local Binary Pattern (ML-LBP) features which are extracted from normalized face images. Two different Support Vector Machines (SVM) models are used to predict the age group and the gender of a person. The experimental results on benchmark Image of Groups dataset showed the superiority of our approach compared to that of the state-ofthe- art methods.|
|Appears in Collections:||Communications Internationales|
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|AUTOMATIC AGE ESTIMATION AND GENDER CLASSIFICATION IN THE WILD.pdf||1,54 MB||Adobe PDF||View/Open|
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