TY  - JOUR
TT  - Face Recognition Applications Of Principle Component Analysis Method And Some Of Its Classical And Robust Variants
AU  - Yazar, İşıl
AU  - Yavuz, Hasan Serhan
AU  - Çay, Mehmet Atıf
PY  - 2009
DA  - June
Y2  - 2009
JF  - Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi
JO  - ESOGÜ Müh Mim Fak Derg
PB  - Eskişehir Osmangazi Üniversitesi
WT  - DergiPark
SN  - 2630-5712
SP  - 49
EP  - 63
VL  - 22
IS  - 1
KW  - Yüz tanıma
KW  - temel bileşen analizi
KW  - robust tahmin ediciler
N2  - In this study, face recognition applications on the YALE, ORL and AR face databaseshave been performed by using some classical and robust estimators instead of classical meansubtraction in the principal component analysis method. In the cases where the Normal distributionassumption is not valid or the data set includes outliers, some robust estimators which are known tohave better results were compared with the classical estimators by making face recognitionexperiments using these three databases. In face recognition applications, the dimension of theimage samples is very high as against the number of the samples. That’s why it’s not known whetherthe data set satisfies the Normal distribution condition. Experimental results demonstrated thatrobust methods usually gave beter correct recognition rates than the classical methods in principalcomponent analysis method based face recognition applications.
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UR  - https://dergipark.org.tr/tr/pub/ogummf/issue//325402
L1  - https://dergipark.org.tr/tr/download/article-file/320368
ER  -