ISSN :2582-9793
Omer Abdulhaleem Naser and Sharifah Mumtazah
Adv. Artif. Intell. Mach. Learn., 4 (3):2545-2574
Omer Abdulhaleem Naser : A final-year Ph.D. student at the University Putra Malaysia, Faculty of Engineering. I majored in computational methods in engineering. The specified research field is biometrics, particularly facial recognition for occluded faces.
Sharifah Mumtazah : Department of Computer and Communication System Engineering, Faculty of Engineering, University Putra Malaysia (UPM), Serdang, Malaysia
Article History: Received on: 04-Jul-24, Accepted on: 16-Sep-24, Published on: 23-Sep-24
Corresponding Author: Omer Abdulhaleem Naser
Email: omar.abdulhalem592@gmail.com
Citation: Omer Abdulhaleem Naser, Sharifah Mumtazah Syed Ahmad, Khairulmizam Samsudin, Marsyita Hanafi. (2024). Enhancing 2D Face Recognition Systems: Addressing Yaw Poses and Occlusions with Masks, Glasses, and both. Adv. Artif. Intell. Mach. Learn., 4 (3 ):2545-2574
Biometric identification in general and face recognition in
particular are used to solve a great number of tasks, both security-related and
related to device authentication. Although research in face recognition is
state-of-the-art today, real face recognition systems still have real problems
in real environments, for example, the problems of pose variation and
occlusion. In particular, the given paper is devoted to the study of the
effects of 2D face recognition depending on the yaw angles and occlusions that
include masks and glasses or their combination. In this regard, the UPM dataset
is employed to compare the face recognition models using MTCNN, FaceNet, SVC,
MLP, and the ensemble model with the hard voting mechanism for the final
decision. The following will be used in the assessment; accuracy, F1 score,
confusion, classification matrix, and ROC curve. These outcomes reveal the
variations in the recognition efficiency in the context of different occlusion
circumstances, along with prospects and limitations concerning their use.