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.
CITATION STYLE
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
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