Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition

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-d...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhang XiuJun, Liu Chang
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/608158
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832556160214892544
author Zhang XiuJun
Liu Chang
author_facet Zhang XiuJun
Liu Chang
author_sort Zhang XiuJun
collection DOAJ
description 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.
format Article
id doaj-art-bf35627287e74728bbd6487c7a803ea7
institution Kabale University
issn 2356-6140
1537-744X
language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-bf35627287e74728bbd6487c7a803ea72025-02-03T05:46:12ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/608158608158Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression RecognitionZhang XiuJun0Liu Chang1College of Information Science and Technology, Chengdu University, Chengdu 610106, ChinaCollege of Information Science and Technology, Chengdu University, Chengdu 610106, ChinaIn 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.http://dx.doi.org/10.1155/2014/608158
spellingShingle Zhang XiuJun
Liu Chang
Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition
The Scientific World Journal
title Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition
title_full Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition
title_fullStr Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition
title_full_unstemmed Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition
title_short Generalized Discriminant Orthogonal Nonnegative Tensor Factorization for Facial Expression Recognition
title_sort generalized discriminant orthogonal nonnegative tensor factorization for facial expression recognition
url http://dx.doi.org/10.1155/2014/608158
work_keys_str_mv AT zhangxiujun generalizeddiscriminantorthogonalnonnegativetensorfactorizationforfacialexpressionrecognition
AT liuchang generalizeddiscriminantorthogonalnonnegativetensorfactorizationforfacialexpressionrecognition