title: Generalized discriminant orthogonal nonnegative tensor factorization for facial expression recognition.
abstract: 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.
authors: College of Information Science and Technology, Chengdu University, Chengdu 610106, China ; Key Laboratory of Pattern Recognition and Intelligent Information Processing in Sichuan, Chengdu 610106, China.
authors: Zhang
authors: Z
authors: XiuJun
authors: College of Information Science and Technology, Chengdu University, Chengdu 610106, China ; Key Laboratory of Pattern Recognition and Intelligent Information Processing in Sichuan, Chengdu 610106, China.
authors: Liu
authors: L
authors: Chang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005149:Facial Expression; D006801:Humans; D010363:Pattern Recognition, Automated