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Deep Random Forest for Facial Age Estimation Based on Face Images

Abstract : The face image of an individual is important for most biometrics systems. The face picture gives loads of helpful informations, including the individual's personal identity, gender, ethnicity, age, emotional expression, and so forth. As of late, a few applications that endeavor age estimation have risen. This paper was aimed to address the problem of image-based human age estimation. It has the following main contributions. We used the advantages of the recent method and algorithms named Gcforest, which proved in several classification tasks, this novel approach includes the power of the decision trees and the advantages of a Cascades structure which allows the interaction between trees. We provide a comparison between two feature types handcrafted and deep feature, we used three databases FG NET, PAL and MORPH II.
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Submitted on : Friday, February 11, 2022 - 2:40:49 PM
Last modification on : Tuesday, May 24, 2022 - 12:48:28 PM

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Distributed under a Creative Commons Attribution - NonCommercial 4.0 International License

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Oussama Guehairia, Abdelmalik Ouamane, Fadi Dornaika, Abdelmalik Taleb-Ahmed. Deep Random Forest for Facial Age Estimation Based on Face Images. 1st International Conference on Communications, Control Systems and Signal Processing (CCSSP 2020), May 2020, El Oued, Algeria. pp.305-309, ⟨10.1109/CCSSP49278.2020.9151621⟩. ⟨hal-03566350⟩

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