Age-Variation Face Recognition Based on Bayes Inference

Studies have discovered that face recognition will benefit from age information. However, since the age estimation is unstable in practice, it is still an open question how to improve face recognition with help of automatic age estimation techniques. This paper presents to improve the performance of face recognition by automatic age estimation. The main contribution is a new age-variational face recognition algorithm based on Bayesian framework (FRAB). By introducing the age estimation result as a prior, the recognition problem is divided into several age-specific sub-problems. As a result, the proposed algorithm leads to two algorithms according to how the age is given. The first one is FRAB-AE, which introduces age estimation result as the age prior. The second one is FRAB-GT, which considers that the ground truth of age information is given. Experimental results are conducted on FG-NET and Morph datasets to evaluate the performance of the proposed framework. It shows that the proposed algorithms is able to make use of age priors to improve the face recognition.