Face replacement based on 2D dense mapping
Han Wen Guo, Dongmei Niu, Xiangyu Kong, Xiuyang Zhao · 2019
Face replacement, also known as face swapping, is a worth investing problem in privacy protection, intelligent human-computer interaction and video effects. In our paper, a new approach is proposed to transform identities of the input images into a target identity while preserving poses and facial features. It is considered that 2D face replacement can be replaced by the problem of 2D graphics dense mapping using 3D morphable models projection. For mapping the input facial region and the target, our method uses planar parameterization and affine transformation to establish a one-to-one dense mapping between 2D graphics. It can enable to reduce the effect on the rotation of non-frontal faces without image preprocessing. Our method then adjusts positions of eyes to keep gaze direction of the input images, and stitches the transformed image and the target image based on seamless cloning to show the authenticity of the images.