Letters: View-independent face recognition with Mixture of Experts

Authors:
Reza Ebrahimpour;Ehsanollah Kabir;Hossein Esteky;Mohammad Reza Yousefi
Affiliations:
School of Cognitive Sciences, Institute for Studies on Theoretical Physics and Mathematics, P.O. Box 19395-5746, Niavaran, Tehran, Iran and Department of Electrical Engineering, Shahid Rajaee Univ ...;Department of Electrical Engineering, Tarbiat Modarres University, P.O. Box 14115-143, Tehran, Iran;School of Cognitive Sciences, Institute for Studies on Theoretical Physics and Mathematics, P.O. Box 19395-5746, Niavaran, Tehran, Iran and Research Group for Brain and Cognitive Sciences, School ...;Department of Electrical Engineering, Shahid Rajaee University, Tehran, Iran
Venue:
Neurocomputing
Year:
2008

Citing 12
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Abstract

A model for view-independent face recognition, based on Mixture of Experts, ME, is presented. Instead of allowing ME to partition the face space automatically, it is directed to adapt to a particular partitioning corresponding to predetermined views. Experimental results show that this model performs well in recognizing faces of intermediate unseen views. There are neurophysiological evidences that underpin the proposed model, reporting similar mechanisms of pooling the outputs of several view-specific modules to perform view-independent face recognition.