Proceedings ArticleDOI
A robust feature extraction algorithm based on class-Modular Image Principal Component Analysis for face verification
Jose Francisco Pereira,Rafael M. Barreto,George D. C. Cavalcanti,Ing Ren Tsang +3 more
- pp 1469-1472
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TLDR
Experimental results performed over three well-known face databases showed that the class-Modular Image Principal Component Analysis (cMIMPCA) obtains promising results for the face verification task.Abstract:
Face verification systems reach good performance on ideal environmental conditions. Conversely, they are very sensitive to non-controlled environments. This work proposes the class-Modular Image Principal Component Analysis (cMIMPCA) algorithm for face verification. It extracts local and global information of the user faces aiming to reduce the effects caused by illumination, facial expression and head pose changes. Experimental results performed over three well-known face databases showed that cMIMPCA obtains promising results for the face verification task.read more
Citations
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Journal ArticleDOI
A review on face recognition systems: recent approaches and challenges
TL;DR: A critical review on the different issues of face recognition systems are presented, and different approaches to solving these issues are analyzed by presenting existing techniques that have been proposed in the literature.
Journal ArticleDOI
Weighted Modular Image Principal Component Analysis for face recognition
TL;DR: This paper proposes two feature extraction techniques that minimizes the effects of distortions generated by variations in illumination, rotation and, head pose in automatic face recognition systems using modular image decomposition.
Journal ArticleDOI
PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.
TL;DR: This research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity, indicating lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems.
Journal ArticleDOI
An MPCA/LDA Based Dimensionality Reduction Algorithm for Face Recognition
TL;DR: A face recognition algorithm based on both the multilinear principal component analysis (MPCA) and linear discriminant analysis (LDA) to find the optimal tensor subspace for accomplishing dimension reduction.
Journal ArticleDOI
A novel partition selection method for modular face recognition approaches on occlusion problem
TL;DR: In this paper, the authors proposed a new method to detect and to use the non-occluded parts of face image for modular face recognition approaches, where the occlusion of a partition is decided using the combination of three coefficients which can be easily derived: (i) image entropy, (ii) image correlation, (iii) root-mean-square error.
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