Pose invariant Face Recognition using Neural Networks and PCA


  • Prof. Nagarkar Raviraj Prakash TPO, BMIT, Solapur
  • Dr. Kazi Kutubuddin Sayyad Liyakat Associate Professor,BMIT, Solapur


Eigen values, face Recognition, PCA, EPOCH, Neural networks


In this paper, human face as biometric is considered. Original method of feature extraction from image data is introduced using feed forward Neural networks (multilayer perceptron) and PCA (principal component analysis). This method is used in human face recognition system and results are compared to face recognition system using PCA directly, to a system with direct classification of input images by Neural network, and to a system using NN as a feature extractor and NN network in the role of classifier. In order to obtain deeper insight into eight presented methods, also visualizations of internal representation of input data obtained by neural networks are presented.


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How to Cite

Prof. Nagarkar Raviraj Prakash, & Dr. Kazi Kutubuddin Sayyad Liyakat. (2019). Pose invariant Face Recognition using Neural Networks and PCA. International Engineering Journal For Research & Development, 4(Special Issue), 4. Retrieved from http://www.iejrd.com/index.php/ /article/view/270