Onifade O.F.W and Akinyemi J.D, University of Ibadan, Nigeria

In this paper, we propose a framework for Age Estimation which uses a correlated ageing pattern to rank images and makes necessary inferences from the image ranks to estimate the exact age of images. We use AAM and LBP as complementary feature extraction techniques for extracting facial features in low dimensionality. Our correlated ageing pattern model learns the ageing patterns of different individuals across ages and uses these to determine an agerank for each image. Subsequently, the learned age rank of a reference image set is used to determine the ranks of test images in order to deduce relevant inferences for age estimation. Our approach is significantly different from the previous ranking approaches in that it determines age ranks that do not only represent the correlation of ages of different individuals but also the correlation of ageing patterns of different individuals. Our initial findings look promising with the intuitive manner with which we employ correlated ageing patterns.

Age Estimation, Ageing Pattern, Age Rank, Ranking