Dual eigenspace method forhuman face recognition

13 February 1997

journal article
Published by Institution of Engineering and Technology (IET) in Electronics Letters

Vol. 33 (4) , 283-284
https://doi.org/10.1049/el:19970203

Abstract

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).

Keywords

AUTOMATED FACE RECOGNITION
K-L TRANSFORM
TWO-LAYER MINIMUM DISTANCE CLASSIFIER
ALGEBRAIC FEATURES EXTRACTION
HUMAN FACE RECOGNITION
FACE IDENTIFICATION
DUAL EIGENSPACE METHOD
TRAINING SAMPLES

This publication has 2 references indexed in Scilit:

Human and machine recognition of faces: a survey
Proceedings of the IEEE, 1995
Face recognition using view-based and modular eigenspaces
Published by SPIE-Intl Soc Optical Eng ,1994