Computer Science Department
School of Computer Science, Carnegie Mellon University


Rotation Invariant Neural Network-Based Face Detection

Henry A. Rowley, Shumeet Baluja*, Takeo Kanade

December 1997

Keywords: Face detection, pattern recognition, computer vision, artificial neural networks, machine learning

In this paper, we present a 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 a "router" network which processes each input window to determine its orientation and then uses this information to prepare the window for one or more "detector" networks. We present the training methods for both types of networks. We also perform sensitivity analysis on the networks, and present empirical results on a large test set. Finally, we present preliminary results for detecting faces which are rotated out of the image plane, such as profiles and semi-profiles.

15 pages

*Justsystem Pittsburgh Research Center, 4616 Henry Street, Pittsburgh, PA 15213, and School of Computer Science, Carnegie Mellon University.

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