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    CMU-CS-97-201 
    Computer Science Department 
    School of Computer Science, Carnegie Mellon University
    
      
 
 
CMU-CS-97-201
Rotation Invariant Neural Network-Based Face Detection 
Henry A. Rowley, Shumeet Baluja*, Takeo Kanade 
December 1997  
CMU-CS-97-201.ps  
 
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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