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The Scientific World Journal
Volume 2014 (2014), Article ID 608158, 5 pages
Research Article

Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition

1College of Information Science and Technology, Chengdu University, Chengdu 610106, China
2Key Laboratory of Pattern Recognition and Intelligent Information Processing in Sichuan, Chengdu 610106, China

Received 4 August 2013; Accepted 6 January 2014; Published 26 March 2014

Academic Editors: S. Bourennane and J. Marot

Copyright © 2014 Zhang XiuJun and Liu Chang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In order to overcome the limitation of traditional nonnegative factorization algorithms, the paper presents a generalized discriminant orthogonal non-negative tensor factorization algorithm. At first, the algorithm takes the orthogonal constraint into account to ensure the nonnegativity of the low-dimensional features. Furthermore, the discriminant constraint is imposed on low-dimensional weights to strengthen the discriminant capability of the low-dimensional features. The experiments on facial expression recognition have demonstrated that the algorithm is superior to other non-negative factorization algorithms.