Abstract
AbstractIn 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.KeywordsDimensionality reductionsubspace learningmanifold learningface recognition
Published Version
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