Towards a semi-automatic method for the statistically rigorous ageing of the human face

Forensic age progression for the purpose of ageing a missing child is a discipline currently dominated by artistic methodologies. In order to improve on these techniques, a statistically rigorous approach to the ageing of the human face is presented. The technique is based upon a principal component analysis and involves the definition of an ageing direction through the model space, using an age-weighted combination of model parameters. Pose and expression compensation methods are also incorporated, allowing faces at a wide variety of pose orientations and expressions to be aged accurately. Near photo-quality images are obtained quickly and the resultant ageing effects are realistic and plausible. As a quantitative check of the results, the root mean square error is calculated between the shape vector of the aged face and that of the target face, as well as between the aged face and faces of different identity at the target age. In general, this error is found to be smaller between the aged face and the target face, indicating that the face successfully retains its identity as it is aged. As a further test of the basic plausibility of our results, a regression analysis is performed between the shape model parameters and the age of each subject, assuming a linear relationship. The coefficient of determination is calculated to be r²=0.68 and the relationship between the variables is found to be significant at a level >0.99 upon performance of a standard F-test