Physical Sciences and Mathematics Commons^™

Unsupervised Face Alignment By Robust Nonrigid Mapping, Jianke Zhu, Luc Van Gool, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

We propose a novel approach to unsupervised facial image alignment. Differently from previous approaches, that are confined to affine transformations on either the entire face or separate patches, we extract a nonrigid mapping between facial images. Based on a regularized face model, we frame unsupervised face alignment into the Lucas-Kanade image registration approach. We propose a robust optimization scheme to handle appearance variations. The method is fully automatic and can cope with pose variations and expressions, all in an unsupervised manner. Experiments on a large set of images showed that the approach is effective.