Multi-view face alignment using 3D shape model for view estimation

Abstract

For multi-view face alignment (MVFA), the non-linear variation of shape and texture, and the self-occlusion of facial feature points caused by view change are the two major difficulties. The state-of-the-art MVFA methods are essentially view-based approaches in which views are divided into several categories such as frontal, half profile, full profile etc. and each of them has its own model in MVFA. Therefore the view estimation problem becomes a critical step in MVFA. In this paper, a MVFA method using 3D face shape model for view estimation is presented in which the 3D shape model is used to estimate the pose of the face thereby selecting its model and indicating its self-occluded points. Experiments on different datasets are reported to show the improvement over previous works. © Springer-Verlag Berlin Heidelberg 2009.