Constant dimensionality reduction for large databases using localized PCA with an application to face recognition

This paper aims to reduce the complexities such as computation and storage of the facial data much further as compared to the methods described by PCA and LDA whilst keeping the discriminatory information, which is achieved by using a modified PCA technique along with an idea involving `separation of classes' similar to LDA. Furthermore the problem that, `reduced dimensionality' ironically increases with a growing database, is solved. Additionally, the possibility of updating the facial database dynamically for facilitating the most recent capture of a person is concluded to be much more feasible.

[1]  R. Chellappa,et al.  Subspace Linear Discriminant Analysis for Face Recognition , 1999 .

[2]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[3]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[4]  Xiaoou Tang,et al.  Dual-space linear discriminant analysis for face recognition , 2004, CVPR 2004.

[5]  Srinivasulu Asadi,et al.  A Comparative study of Face Recognition with Principal Component Analysis and Cross-Correlation Technique , 2010 .

[6]  Rama Chellappa,et al.  Image-Based Face Recognition: Issues and Methods , 2002 .

[7]  Ralph Gross,et al.  Quo vadis Face Recognition , 2001 .

[8]  L Sirovich,et al.  Low-dimensional procedure for the characterization of human faces. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[9]  Gregory Shakhnarovich,et al.  Face Recognition in Subspaces , 2011, Handbook of Face Recognition.

[10]  Hua Yu,et al.  A direct LDA algorithm for high-dimensional data - with application to face recognition , 2001, Pattern Recognit..

[11]  Lawrence Sirovich,et al.  Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  P. N. Bellhumer Eigenfaces vs. fisherfaces : Recognition using class specific linear projection , 1997 .

[13]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[14]  I M Mario Chacon State of the Art in Face Recognition , 2009 .