TY  - JOUR
T1  - Model-Based Active Appearance Model Approach For Face Recognition
AU - Gheni, Eman A. AU - M. Ali, Zahraa AU - N. Abul-Wadood, Dalia 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 9
SP  - 2988
EP  - 2992
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.2988.2992
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.2988.2992
KW  - Face biometric
KW  -human face recognition facial features
KW  -AFR
KW  -AAM
KW  -YALEB
KW  -evaluation
AB  - Recently, the most user-friendly systems in the biometric world are face recognition systems. In
addition, they are one of the active research fields while the researchers work to ameliorate the effectiveness
and competence of biometric implementations. The major challenge to be in these implementations is to extract
the useful features sets which are not disturbed caused by number of factors, including person movement,
illuminations, camera’s differences and other ecological and physical changes. Thus, AMM (Active
Appearance Model) is one of the good population solutions which it can be used as a features extraction
technique by accurate modeling under different physical and environmental situations. In this research, an
AAM based face recognition system is proposed. Then, three different data sets YALEB, FERET and CASIA
V5 which have been utilized for the first time in the evaluation. The experimental results showed that the
performance of AAM is very powerful with face recognition.
ER  -