A Fully Automated Face Recognition System Under Different Conditions

Authors:
Affiliations:
Venue:
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Year:
1998

Citing 6
Cited 0

Locating human faces in photographs

International Journal of Computer Vision
Neural Network-Based Face Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: Features Versus Templates

IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable templates for face recognition

Journal of Cognitive Neuroscience
Eigenfaces for recognition

Journal of Cognitive Neuroscience
Face recognition/detection by probabilistic decision-based neural network

IEEE Transactions on Neural Networks

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Abstract

In this paper, we present a fully automated face recognition system (FAFRS) which contains two components: eyes detection and face recognition. Firstly, hybrid neural method is proposed to localize human eyes. Then, dual eigenspaces method (DEM) is developed to extract algebraic features from normalized facial images and perform the recognition task. Experimental results show that the proposed system is effective and robust under different conditions.