Comparison of Different Neural Network Training Algorithms with Application to Face Recognition

Research in the field of face recognition has been popular for several decades. With advances in technology, approaches to solving this problems haves changed. Main goal of this paper was to compare different training algorithms for neural networks and to apply them for face recognition as it is a nonlinear problem. Algorithm that we have used for face recognition problem was the Eigenface algorithm that belongs to the Principal Component Analysis (PCA) algorithms. Percentage of recognition for all the used training functions is above 90%.

[1]  Bruce A. Draper,et al.  Recognizing faces with PCA and ICA , 2003, Comput. Vis. Image Underst..

[2]  Jeffrey S. Norris.  Face detection and recognition in office environments , 1999 .

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

[4]  Shwu-Huey Yen,et al.  Face Detection Based on Skin Color Segmentation and Neural Network , 2005, 2005 International Conference on Neural Networks and Brain.

[5]  A. A. El-Harby,et al.  Face Recognition: A Literature Review , 2008 .

[6]  Figen Özen,et al.  A Face Recognition System Based on Eigenfaces Method , 2012 .

[7]  Dengpan Mou,et al.  Machine-based Intelligent Face Recognition , 2010 .

[8]  Manish Kumar,et al.  Face Recognition Using Eigen Faces and Artificial Neural Network , 2010 .

[9]  Katta Rama Linga Reddy,et al.  Face recognition based on eigen features of multi scaled face components and an artificial neural network , 2010, Biometrics Technology.

[10]  Mahmoud Hassaballah,et al.  Face recognition: challenges, achievements and future directions , 2015, IET Comput. Vis..

[11]  Z. Bojkovic,et al.  Face Detection Approach in Neural Network Based Method for Video Surveillance , 2006, 2006 8th Seminar on Neural Network Applications in Electrical Engineering.

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

[13]  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.

[14]  Alan L. Yuille,et al.  Feature extraction from faces using deformable templates , 2004, International Journal of Computer Vision.