3D face recognition using kernel-based PCA approach

Peter, M., and Minoi, J.-L., and Hipiny, I.H.M. (2019) 3D face recognition using kernel-based PCA approach. Lecture Notes in Electrical Engineering, 481. pp. 77-86. ISSN 1876-1100

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Abstract

Face recognition is commonly used for biometric security purposes in video surveillance and user authentications. The nature of face exhibits non-linear shapes due to appearance deformations, and face variations presented by facial expressions. Recognizing faces reliably across changes in facial expression has proved to be a more difficult problem leading to low recognition rates in many face recognition experiments. This is mainly due to the tens degree-of-freedom in a non-linear space. Recently, non-linear PCA has been revived as it posed a significant advantage for data representation in high dimensionality space. In this paper, we experimented the use of non-linear kernel approach in 3D face recognition and the results of the recognition rates have shown that the kernel method outperformed the standard PCA. © Springer Nature Singapore Pte Ltd. 2019.

Item Type: E-Article
Uncontrolled Keywords: 3D face recognition, 3D faces, Data representations, Face recognition experiment, Facial recognition, High dimensionality, Kernel PCAU ser authentication, UNIMAS, Universiti Malaysia Sarawak, Malaysia
Subjects: T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: 1 Student
Date Deposited: 04 Jun 2020 07:55
Last Modified: 04 Jun 2020 07:55
URI: http://ir.unimas.my/id/eprint/29654

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