Neural nets for human face recognition

A neural network (NN) architecture based on a multilayer perceptron with shared weights is described. This kind of network allows direct gray-level image processing and lets the NN learn to extract image features in its hidden layers. These features allow fast classification of face images. The results of applying the architecture on large databases of varying difficulty, containing images taken in real-life unconstrained condition, are presented. A novel rejection criterion which allows the system to detect intruders is discussed