In this paper, we describe a novel neural network architecture, which can recognize human faces with any view in a certain viewing angle range (from left 30 degrees to right 30 degrees out of plane rotation). View-specific eigenface analysis is used as the front-end 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.
Index Terms:
face recognition, eigenface, ensemble neural network, pose invariant
Citation:
Fu Jie Huang, Tsuhan Chen, Zhihua Zhou, Hong-Jiang Zhang, "Pose Invariant Face Recognition," fg, pp.245, Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), 2000