Feature extraction using orthogonal discriminant local tangent space alignment

Authors:
Ying-Ke Lei;Yang-Ming Xu;Jun-An Yang;Zhi-Guo Ding;Jie Gui
Affiliations:
Electronic Engineering Institute, State Key Laboratory of Pulsed Power Laser Technology, 230027, Hefei, Anhui, China and Chinese Academy of Sciences, Intelligent Computing Lab, Institute of Intell ...;Electronic Engineering Institute, State Key Laboratory of Pulsed Power Laser Technology, 230027, Hefei, Anhui, China;Electronic Engineering Institute, State Key Laboratory of Pulsed Power Laser Technology, 230027, Hefei, Anhui, China;Electronic Engineering Institute, State Key Laboratory of Pulsed Power Laser Technology, 230027, Hefei, Anhui, China;Chinese Academy of Sciences, Intelligent Computing Lab, Institute of Intelligent Machines, P.O. Box 1130, 230031, Hefei, Anhui, China
Venue:
Pattern Analysis & Applications
Year:
2012

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Abstract

A novel algorithm called orthogonal discriminant local tangent space alignment (O-DLTSA) is proposed for supervised feature extraction. 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.