Computer Science ›› 2013, Vol. 40 ›› Issue (5): 11-18.

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Tensor Local Fisher Discriminant with Null Space Analysis

ZHENG Jian-wei,JIANG Yi-bo and WANG Wan-liang   

  • Online:2018-11-16 Published:2018-11-16

Abstract: The tensor local fisher discriminant algorithm with null space analysis or NSTLFDA for short was proposed which incorporates the merits of three techniques,i.e.,tensor based methods,local Fisher discriminant analysis,and null space analysis.The main features of our implementation include:(i) local Fisher discriminant analysis is improved by inter-class discriminant information for better recognition performance and reduces time complexity.ii) the tensor based method employs two-sided transformations rather than single-sided one,and yields higher compression ratio.iii) while TLFDA directly uses an iterative procedure to calculate the optimal solution of two transformation matrices,the NSTLFDA method takes the advantages of null space information when the training samples number is less than the dimensionality of the vector samples.The effectiveness of our new method was demonstrated by the ORL,Yale,and ExYaleB face databases.

Key words: Fisher discriminant analysis,Null space,Local preservation projection,Tensor subspace analysis

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