In this paper, facial age estimation is discussed in a novel viewpoint – how to jointly exploit the supervised training data and human annotations to improve the age estimation precision. This is motivated by the lacking of data problem in age estimation and the current web booming. To do so, fuzzy age label is firstly defined, and it is then merged into the Support Vector Regression (SVR) fram...

Age estimation has many useful applications, such as age-based face classification, finding lost children, surveillance monitoring, and face recognition invariant to age progression. Among many factors affecting age estimation accuracy, gender and facial expression can have negative effects. In our research, the effects of gender and facial expression on age estimation using support vector regr...

Computer based methods for facial age estimation can be improved by incorporating experimental findings from human psychophysics. Moreover, the latter can be used in creating systems that are not necessarily more accurate in age estimation, but strongly resemble human age estimations. In this paper we investigate the perceptual hypothesis that contrast is a useful cue for estimating age from fa...

Human face aging is irreversible process causing changes in human face characteristics such us hair whitening, muscles drop and wrinkles. Due to the importance of human face aging in biometrics systems, age estimation became an attractive area for researchers. This paper presents a novel method to estimate the age from face images, using binarized statistical image features (BSIF) and local bin...

The principal objective of this project is to develop methods for the estimation of the gender and the age of a person based on a facial image, using classification for the gender estimation and regression for the age. The extracted information can be useful in, for example, security or commercial applications. This is a difficult estimation problem, since the only information we have is the im...

Automatic age estimation based on facial images is important but challenging in face recognition research. A Super-Resolution Reconstruction algorithm was proposed to implement the age estimation of facial images, which cut the facial image into small pieces. Then after building high resolution images by using the Super-Resolution Reconstruction algorithm, the RBF neural network was used to tra...