A Novel Discriminant Non-Negative Matrix Factorization and its Application to Facial Expression Recognition

Abstract:

Article Preview

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 et al., "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:

$35.00

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