Rotation invariant face recognition using optical neural networks

In this paper, we present an optical neural network based face detection system. Unlike similar systems which are limited to detecting upright, frontal faces, this system detects faces at any degree of rotation in the image plane. The system employs multiple networks; the first is an orientation network which processes each input window to determine its orientation and then uses this information to prepare the window for identifier network. We present the training methods for both types of networks. We also perform analysis on the networks, and present empirical results on a large test set. Finally, we recognize the face using Principal Component Analysis approach.