Abstract

We present a novel approach to matching 3D faces with expressions, deformations and outliers. The matching is performed through an accurate and robust algorithm for registering face meshes. The registration algorithm incorporates prior anthropometric knowledge through the use of suitable landmarks and regions of the face to be used with the Iterative Closest Point (ICP) registration algorithm. The localization of landmarks and regions is achieved through the fitting of a 3D Point Distribution Model (PDM) and is independent of texture, pose and orientation information. We show that the use of expression-invariant facial regions for registration and similarity estimation outperforms the use of the entire face region. Evaluation is performed on the challenging GavabDB database and we achieve 93.7 % rank-1 recognition with an overall retrieval accuracy of 91.1%. 1

Citations