Semi-Supervised Half-Quadratic Nonnegative Matrix Factorization for Face Recognition

Semi-Supervised Half-Quadratic Nonnegative Matrix Factorization for Face Recognition

Face recognition is a challenging problem in computer vision. Difficulties such as slight differences between similar faces of different people, changes in facial expressions, light and illumination condition, and pose variations add extra complications to the face recognition research. Many algorit...

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Bibliographic Details
Main Author: Alghamdi, Masheal M.
Other Authors: Gao, Xin
Language:en
Published: 2014
Subjects:
Semi-Supervised
NMF
Face recognition
M-estimator
Half-Quadratic
Graph embedding
Online Access:Alghamdi, M. M. (2014). Semi-Supervised Half-Quadratic Nonnegative Matrix Factorization for Face Recognition. KAUST Research Repository. https://doi.org/10.25781/KAUST-7780X
http://hdl.handle.net/10754/317308

Internet

Alghamdi, M. M. (2014). Semi-Supervised Half-Quadratic Nonnegative Matrix Factorization for Face Recognition. KAUST Research Repository. https://doi.org/10.25781/KAUST-7780X
http://hdl.handle.net/10754/317308

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