An automatic facial age progression estimation system

Khalifa, Othman Omran and Omar, Ayub Ahmed and Ahmed, Muhammed Zaharadeen and Saeed, Rashid Abdelhaleem and Hassan Abdalla Hashim, Aisha and Esgiar, Abdelrahim Nasser (2021) An automatic facial age progression estimation system. In: 2021 International Congress of Advanced Technology and Engineering (ICOTEN), 4-5 July 2021, Yamen.

	PDF (conference article) - Published Version Restricted to Registered users only Download (2MB) | Request a copy
	PDF (schedule) - Supplemental Material Restricted to Registered users only Download (4MB) | Request a copy
	PDF (certificate) - Supplemental Material Restricted to Registered users only Download (841kB) | Request a copy

Abstract

Linear age progression models which are largely used in prototype and conventional approaches usually produce synthesized images that are lack of quality because of the aging variations. Therefore, in this paper, a facial age progression model that captures non-linear age variances is designed by using a deep learning-based method called Generative Adversarial Network. The proposed face aging model aims to achieve convincing and visually plausible aging effects by controlling the age attribute. The model first maps the face via a convolutional encoder to a latent vector, then the vector is projected by a deconvolutional generator to the face manifold based on age, and finally the encoder and the generator are imposed on two adversarial networks respectively. The proposed model is trained on UTKFace dataset using Pytorch machine learning library. The experimental results demonstrate the capability of the proposed Generative Advanced Network (GAN) model of generating photorealistic aging faces and preserving the original identity property.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	4119/91152
Uncontrolled Keywords:	Age estimation, Face, Feature, Classification
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	Prof. Dr Othman O. Khalifa
Date Deposited:	03 Aug 2021 17:22
Last Modified:	03 Aug 2021 17:22
URI:	http://irep.iium.edu.my/id/eprint/91152

Actions (login required)

View Item