EconPapers    
Economics at your fingertips  
 

Facial Expression Recognition Based on Discriminant Neighborhood Preserving Nonnegative Tensor Factorization and ELM

Gaoyun An, Shuai Liu, Yi Jin, Qiuqi Ruan and Shan Lu

Mathematical Problems in Engineering, 2014, vol. 2014, 1-10

Abstract:

A novel facial expression recognition algorithm based on discriminant neighborhood preserving nonnegative tensor factorization (DNPNTF) and extreme learning machine (ELM) is proposed. A discriminant constraint is adopted according to the manifold learning and graph embedding theory. The constraint is useful to exploit the spatial neighborhood structure and the prior defined discriminant properties. The obtained parts-based representations by our algorithm vary smoothly along the geodesics of the data manifold and have good discriminant property. To guarantee the convergence, the project gradient method is used for optimization. Then features extracted by DNPNTF are fed into ELM which is a training method for the single hidden layer feed-forward networks (SLFNs). Experimental results on JAFFE database and Cohn-Kanade database demonstrate that our proposed algorithm could extract effective features and have good performance in facial expression recognition.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2014/390328.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2014/390328.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:390328

DOI: 10.1155/2014/390328

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().

 
Page updated 2025-03-19
Handle: RePEc:hin:jnlmpe:390328