Infomation Media Processing for Security. Using an Adaptive Discriminant Feature Space in Hierarchical Face Recognition

We propose the use of an adaptive discriminant space constructed from facial images of candidate faces to optimally distinguish the faces of certain candidates. Firstly, our method to select the set of candidates uses a hierarchical combination of the four-directional features for face-direction estimation and recognition based on linear discriminant analysis. Next, the exact directions of the faces are estimated from the respective discriminant spaces for face-direction estimation. Finally, our method creates a new discriminant space from the facial images of candidates that were selected on the basis of the results of the procedure for face-direction estimation. This adaptive discriminant space is used in opimally selecting from among the candidates. Experiments showed that our method improved the accuracy in recognition by 1.6% to 99.2% by hierarchical face recognition of 105, 000 images from 150 subjects facing in 35 different directions.