Fast Complete Discriminant Locality Preserving Projections for Face Recognition
LU Gui-Fu1,2, WANG Yong 2, JIN Zhong1
1.School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094 2.School of Computer and Information, Anhui Polytechnic University, Wuhu 241000
Abstract Fast complete discriminant locality preserving projections (FCDLPP) is proposed. There is only one step of economic QR factorization for FCDLPP algorithm to obtain the optimal discriminant vectors in the null space of locality preserving within-class scatter. Then, one step of eigen-decomposition is used to obtain the optimal discriminant vectors in the principal space of the locality preserving within-class scatter. Besides, FCDLPP fuses the regular discriminant features in the principal space and irregular discriminant features in the null space. Theoretical analyses and experimental results show that the proposed FCDLPP outperforms complete discriminant locality preserving projections (CDLPP) on computational speed and recognition rates.
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2011, Vol. 24 
