Face Perception using Tensor Approach

Suriani, Binti Abdul Rahman and Jacey Lynn, Minoi and Hamimah, Binti Ujir (2018) Face Perception using Tensor Approach. In: IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), 3-6 December 2018, Kuching, Sarawak, Malaysia..

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Principal Component Analysis (PCA) is one of the common statistical techniques that can also be used for face perception. This approach introduces a single two-dimensional representation for facial attributes, allowing only one attribute to be different at a time. While a face consists of a set of edges that will define the shape and positions of facial features, these face properties may contribute differently and influence the actual face recognition performance. Therefore in this paper, we propose to extend the traditional PCA approach to a multidimensional tensor-based method. This approach could efficiently separate the facial attributes. Experiment was conducted and the obtained results have shown a higher recognition rates compared to the traditional PCA method.

Item Type: Proceeding (Paper)
Uncontrolled Keywords: face, brain, tensor, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak.
Subjects: Q Science > QA Mathematics
T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Gani
Date Deposited: 06 Mar 2019 08:04
Last Modified: 06 Mar 2019 08:04
URI: http://ir.unimas.my/id/eprint/23833

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