Facial Skin Beautification Using Region-Aware Mask

In this paper, we present a facial attractiveness enhancement system for three major skin attributes: homogeneity, lighting, and color. To implement specific facial manipulation, we propose a new region-aware mask generation approach based on the state-of-the-art edit propagation techniques. The region-aware masks allow the user to beautify faces without the tedious and time-consuming region selection. In our system, an input portrait is decomposed into smoothness, lighting and color layers by edge-preserving filter. Then, taking the facial landmarks and significant edges as the constraint, layer masks are generated based on the image-guided energy minimization framework. The system could beautify faces automatically using the attractiveness priors of example-sets and psychological knowledge. Experiments illustrate the effectiveness of our method on various face databases, and the comparison with the previous methods indicates the reliability of our region-aware mask.