GWAgeER – A GroupWise Age Ranking Framework for Human Age Estimation
Olufade F. W. Onifade, Joseph Damilola Akinyemi · International Journal of Image Graphics and Signal Processing · 2015
The task of estimating the age of humans from facial image is a challenging one due to the non-linear and personalized pattern of aging differing from one individual to another.In this work, we investigated the problem of estimating the age of humans from their facial image using a GroupWise age ranking approach complemented by ageing pattern correlation learning.In our proposed GroupWise age-ranking approach, we constructed a reference image set grouped according to ages for each individual in the reference set and used this to obtain age-ranks for each age group in the reference set.The constructed reference set was used to obtain transformed LBP features called age-rank-biased LBP (arLBP) features which were used with attached ageranks to train an age estimating function for predicting the ages of test images.Our experiments on the publicly available FG-NET dataset and a locally collected dataset (FAGE) shows the best known age estimation accuracy with MAE of 2.34 years on FG-NET using the leave-oneperson-out strategy.