Title: DeepVeil: deep learning for identification of face, gender, expression recognition under veiled conditions

Authors: Ahmad B.A. Hassanat; Abeer Ahmad Albustanji; Ahmad S. Tarawneh; Malek Alrashidi; Hani Alharbi; Mohammed Alanazi; Mansoor Alghamdi; Ibrahim S. Alkhazi; V.B. Surya Prasath

Addresses: Faculty of Information Technology, Mutah University, Karak, Jordan ' Ministry of Environment, Amman, Jordan ' Department of Algorithm and Their Applications, Eötvós Loránd University, Budapest, Hungary ' Computer Science Department, Community College, University of Tabuk, Tabuk 71491, Saudi Arabia ' Faculty of Computer and Information Systems, Islamic University of Madinah, Saudi Arabia ' Centre for Computational Engineering Sciences, Cranfield University, UK ' Computer Science Department, Community College, University of Tabuk, Tabuk 71491, Saudi Arabia ' College of Computers and Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia ' Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, OH 45267, USA

Abstract: Biometric recognition based on the full face is an extensive research area. However, using only partially visible faces, such as in the case of veiled-persons, is a challenging task. Deep convolutional neural network (CNN) is used in this work to extract the features from veiled-person face images. We found that the sixth and the seventh fully connected layers, FC6 and FC7 respectively, in the structure of the VGG19 network provide robust features with each of these two layers containing 4,096 features. The main objective of this work is to test the ability of deep learning-based automated computer system to identify not only persons, but also to perform recognition of gender, age, and facial expressions such as eye smile. Our experimental results indicate that we obtain high accuracy for all the tasks. The best recorded accuracy values are up to 99.95% for identifying persons, 99.9% for gender recognition, 99.9% for age recognition and 80.9% for facial expression (eye smile) recognition.

Keywords: veiled-face recognition; deep learning; convolutional neural networks; age recognition; gender recognition; facial expression recognition; FER; eye smile recognition.

DOI: 10.1504/IJBM.2022.124683

International Journal of Biometrics, 2022 Vol.14 No.3/4, pp.453 - 480

Received: 23 Dec 2020
Accepted: 19 Apr 2021
Published online: 05 Aug 2022 *

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