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...
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2014-01-01
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Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2014/608158 |
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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 |