Generalized multi-ethnic face age-estimation

Age estimation from digital pictures of the face is a very promising research field that is now receiving wide attention. As with any good research problem, face age-estimation is wrought with many challenging interactions that cannot easily be separated out. In general, aging patterns are well understood for all humans, however, these patterns become confounded by intrinsic factors of genetics, gender differences, and ethnic deviations and, equally as important, extrinsic factors of the environment and behavior choices (i.e. sun exposure, drugs, cigarettes, etc). This novel work focuses on the development of a generalized multi-ethnic age-estimation technique - the first of its kind. In addition to the novelty of this approach, the system´s overall performance measure (MAE) is ldquoon parrdquo with algorithms that are tuned for a specific ethnic group. Further, the proposed system performance proves to be far more stable across age than the best published results.