Facial image composition based on Active Appearance Model

In this paper, based on Active Appearance Model (AAM), we present an easy-to-use framework for facial image composition, which can automatically exchange the source image's face or facial features onto the target image. The manual interaction is simple and the user only needs to input semantic information of ROI (region of interest) to be exchanged, such as 'face' or 'eyes'. Our framework mainly consists of two steps: model fitting and component compositing. Model fitting is designed to interpret each input image and obtain a synthesized model face of the image. Then by using component compositing, visual pleasing result is generated by solving Poisson equation with the boundary condition, produced automatically from model fitting. Furthermore, we propose a solution for eliminating the artifacts when part of the target face is occluded by hair, glasses, etc. The visually satisfactory results demonstrate the effectiveness of our facial image composition system.