Paper Title:
A Novel Discriminant Non-Negative Matrix Factorization and its Application to Facial Expression Recognition
  Abstract

The paper proposes a novel discriminant non-negative matrix factorization algorithm and applies it to facial expression recognition. Unlike traditional non-negative matrix factorization algorithms, the algorithm adds discriminant constraints in low-dimensional weights. The experiments on facial expression recognition indicate that the algorithm enhances the discrimination capability of low-dimensional features and achieves better performance than other non-negative matrix factorization algorithms.

  Info
Periodical
Advanced Materials Research (Volumes 143-144)
Edited by
H. Wang, B.J. Zhang, X.Z. Liu, D.Z. Luo, S.B. Zhong
Pages
129-133
DOI
10.4028/www.scientific.net/AMR.143-144.129
Citation
Y. L. Zhu, J. Chen, P. X. Qu, "A Novel Discriminant Non-Negative Matrix Factorization and its Application to Facial Expression Recognition", Advanced Materials Research, Vols. 143-144, pp. 129-133, 2011
Online since
October 2010
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Price
$32.00
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