  Age estimation is a technique for predicting human ages from digital facial
images, which analyzes a person's face image and estimates his/her age based on
the year measure. Nowadays, intelligent age estimation and age synthesis have
become particularly prevalent research topics in computer vision and face
verification systems. Age synthesis is defined to render a facial image
aesthetically with rejuvenating and natural aging effects on the person's face.
Age estimation is defined to label a facial image automatically with the age
group (year range) or the exact age (year) of the person's face. In this case
study, we overview the existing models, popular techniques, system
performances, and technical challenges related to the facial image-based age
synthesis and estimation topics. The main goal of this review is to provide an
easy understanding and promising future directions with systematic discussions.
