Dual eigenspace method for human face recognition
The authors present an effective scheme called the dual eigenspace method (DEM) for automated face recognition. Based on the K-L transform, the dual eigenspaces are constructed by extracting algebraic features of training samples and applied to face identification with a two-layer minimium distance classifier. Experimental results show that DEM is significantly better than the traditional eigenface method (TEM).