1. Introduction
Human faces contain important information, such as gender, race, mood, and age [2]. Face age estimation has attracted great attentions recently in both research communities and industries, due to its significant role in human computer interaction (HCI), surveillance monitoring, and biometrics. However, there are many intrinsic and extrinsic factors which make it very difficult to predict the ages of human subjects from their face images accurately. The intrinsic factors include genetics, ethnicity, gender, and health conditions. The extrinsic factors include makeup, accessories, facial hair, and the variation of expression, pose and illumination. Furthermore, a face image of size is generally represented by a vector with dimensionality of . It is still a challenging topic to reduce the dimensionality significantly and effectively from the original image space.