Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Laplacianfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCIMA '05 Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications
Face recognition using neural networks and pattern averaging
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Intelligent face recognition using feature averaging
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Face recognition by applying wavelet subband representation and kernel associative memory
IEEE Transactions on Neural Networks
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Face recognition has lately attracted more research aimed at developing intelligent machine recognition which uses information within the encoded facial patterns to learn and recognize the objects. This paper investigates the efficiency of using Global and Local pattern averaging for facial data encoding prior to training a neural network using the averaged patterns. Averaging is a simple but efficient method that creates "fuzzy" patterns as compared to multiple "crisp" patterns, which provide the neural network with meaningful learning while reducing computational expense. A real-life application will be presented throughout recognizing the faces of 60 persons using our database and the ORL face database. Experimental results suggest that using pattern averaging; globally or locally, performs well as part of a fast and efficient intelligent face recognition system.