Automatic frontal view face image synthesis

This paper introduces a novel method to automatically synthesizing frontal view face images from more than one ill-posed face images. Rather than relying on a uniform warping function to the whole image, our deformation strategy is specific to each pixel. And rather than relying on inaccurate pose estimation, the contribution of each input image is determined automatically to minimize the non-rigid deformation contained in frontal view synthesizing. It can be learned intuitively from our experimental results that this synthesizing strategy is effective, and under the FERET evaluation methodology, it is proved that this strategy is helpful to improve the performance of face recognition algorithms.