Digital Anti-Aging in Face Images

Abstract

We study a problem called digital facial anti-aging, which aims at making human faces look younger in digital photos. This novel problem is different from the traditional age synthesis where new faces are synthesized at older ages using other example face images. In contrast, our facial anti-aging works on a single digital photo without using any other faces. The proposed system contains several modules. First, an input color face image is decomposed into three layers: face structure, aging detail, and color. Second, the specular highlight in the original face image is recovered. Third, the face structure, color, and the recovered specular highlight are combined to form an anti-aging face image. Further, the system can deal with hair coloring and eyebrow change if needed, since these factors influence human judges of ages. Our approach keeps facial identities and delivers high-quality outputs. We show that the anti-aging system can be built based on adapting and integrating the state-of-the-art methods that were originally proposed to solve other problems. The anti-aging faces are evaluated by humans to demonstrate the performance.