Orthogonal discriminant local tangent space alignment

0Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this paper, a novel linear subspace leaning algorithm called orthogonal discriminant local tangent space alignment (O-DLTSA) is proposed. Derived from local tangent space alignment (LTSA), O-DLTSA not only inherits the advantages of LTSA which uses local tangent space as a representation of the local geometry so as to preserve the local structure, but also makes full use of class information and orthogonal subspace to improve discriminant power. The experimental results of applying O-DLTSA to standard face databases demonstrate the effectiveness of the proposed method. © 2010 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

Lei, Y. K., Wang, H. J., Zhang, S. W., Wang, S. L., & Ding, Z. G. (2010). Orthogonal discriminant local tangent space alignment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6215 LNCS, pp. 423–429). https://doi.org/10.1007/978-3-642-14922-1_52

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free