Pose invariant face recognition

Abstract

In this paper, we describe a novel neural network architecture, which can recognize human faces with any view in a certain viewing angle range (fromy left 30 degrees to right 30 degrees out of plane rotation). View-specific eigenface analysis is used as the frontend of the system to extract features, and the neural network ensemble is used for recognition. Experimental results show that the recognition accuracy of our network ensemble is higher than conventional methods such as using a single neural network to recognize faces of a specific view.