DocumentCode :
2773143
Title :
Weak orthogonalization of face and perturbation for recognition
Author :
Nagao, Kenji ; Sohma, Masaki
Author_Institution :
Matsushita Res. Inst. Tokyo Inc., Kawasaki, Japan
fYear :
1998
fDate :
23-25 Jun 1998
Firstpage :
845
Lastpage :
852
Abstract :
This paper describes a new method for face recognition under drastic changes of the imaging processes through which the facial images are acquired. Unlike the conventional methods that use only the face features, the present method exploits the statistical information of the variations between the face image sets being compared, in addition to the features of the faces themselves. To incorporate both of the face and perturbation features for recognition, we develop a technique called weak orthogonalization. Of the two subspaces that transforms the given two overlapped subspaces so that the volume of the intersection of the resulting two subspaces is minimized. Matching operations are performed in the transformed face space that has thus been weakly orthogonalized against perturbation space. Experimental results on real pictures of the frontal faces from drivers´ licenses show that the new algorithm improves the recognition performance over the conventional methods. We also demonstrate the effectiveness of our method on image sets with changes in viewing geometry
Keywords :
face recognition; transforms; face recognition; imaging processes; statistical information; weak orthogonalization; Face recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on
Conference_Location :
Santa Barbara, CA
ISSN :
1063-6919
Print_ISBN :
0-8186-8497-6
Type :
conf
DOI :
10.1109/CVPR.1998.698703
Filename :
698703
Link To Document :
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