PT Journal
AU Wenjuan Gong
   W.Zhang
   Jordi Gonzalez
   Y.Ren
   Z.Li
TI Enhanced Asymmetric Bilinear Model for Face Recognition
SO International Journal of Distributed Sensor Networks
JI IJDSN
PY 2015
BP Article ID 218514
DI 10.1155/2015/218514
AB Bilinear models have been successfully applied to separate two factors, for example, pose variances and different identities in face recognition problems. Asymmetric model is a type of bilinear model which models a system in the most concise way. But seldom there are works exploring the applications of asymmetric bilinear model on face recognition problem with illumination changes. In this work, we propose enhanced asymmetric model for illumination-robust face recognition. Instead of initializing the factor probabilities randomly, we initialize them with nearest neighbor method and optimize them for the test data. Above that, we update the factor model to be identified. We validate the proposed method on a designed data sample and extended Yale B dataset. The experiment results show that the enhanced asymmetric models give promising results and good recognition accuracies.
ER