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Automatic Age Estimation And Gender Classification In The Wild

Abstract : Automatic age estimation and gender classification throughfacial images are attractive topics in computer vision. Theycan be used in many real-life applications such as face recog-nition and internet safety for minors. In this paper, we presenta novel approach for age estimation and gender classificationunder uncontrolled conditions following the standard proto-cols for fair comparaison. Our proposed approach is based onMulti Level Local Binary Pattern (ML-LBP) features whichare extracted from normalized face images. Two differentSupport Vector Machines (SVM) models are used to predictthe age group and the gender of a person. The experimen-tal results on benchmark Image of Groups dataset showed thesuperiority of our approach compared to that of the state-of-the-art methods
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Submitted on : Wednesday, November 3, 2021 - 9:18:25 AM
Last modification on : Thursday, November 4, 2021 - 4:07:44 AM


  • HAL Id : hal-03412445, version 1



Salah Eddine Bekhouche, Abdelkrim Ouafi, Azeddine Benlamoudi, Abdelmalik Taleb-Ahmed, Abdenour Hadid. Automatic Age Estimation And Gender Classification In The Wild. International Conference on Automatic control, Telecommunications and Signals (ICATS15), Nov 2015, Annaba, Algeria. ⟨hal-03412445⟩



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