Video face beautification

This paper presents a novel system framework of face beautification. Unlike prior works that deal with single images, the proposed beautification framework is designed for an input video and it is able to improve both the appearance and the shape of a face. Our system adopts a state-of-the-art algorithm to synthesize and track 3D face models using blendshapes. The personalized 3D model can be edited to satisfy personal preference. This interactive process is needed only once per subject. Based on the tracking result and the modified face model, we present an algorithm to beautify the face video efficiently and consistently. Furthermore we develop a variant of content preserving warping to reduce warping distortions along the face boundary. Finally we adopt real time bilateral filtering to remove wrinkles, freckles, and unwanted blemishes. This framework is evaluated on a set of videos. The experiments demonstrate that our framework can generate consistent and pleasant results over video frames while the original expressions and features are persevered naturally.