Title :
A novel face recognition system using hybrid neural and dual eigenspaces methods
Author :
Zhang, David ; Peng, Hui ; Zhou, Jie ; Pal, Sankar K.
Author_Institution :
Biometrics Res. Centre, Hong Kong Polytech. Univ., Kowloon, China
fDate :
11/1/2002 12:00:00 AM
Abstract :
In this paper, we present an automated face recognition (AFR) system that contains two components: eye detection and face recognition. Based on invariant radial basis function (IRBF) networks and knowledge rules of facial topology, a hybrid neural method is proposed to localize human eyes and segment the face region from a scene. A dual eigenspaces method (DEM) is then developed to extract algebraic features of the face and perform the recognition task with a two-layer minimum distance classifier. Experimental results illustrate that the proposed system is effective and robust.
Keywords :
eigenvalues and eigenfunctions; face recognition; feature extraction; image segmentation; neural nets; radial basis function networks; automated face recognition; dual eigenspaces; eye detection; face region; facial topology; feature extraction; hybrid neural method; invariant radial basis function networks; knowledge rules; Computer vision; Eyes; Face detection; Face recognition; Feature extraction; Humans; Layout; Network topology; Pattern recognition; Robustness;
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
DOI :
10.1109/TSMCA.2003.808252