Automatic 3D face verification from range data

We present a novel approach for automatic 3D face verification from range data. The method consists of range data registration and comparison. There are two steps in the registration procedure: a coarse step conducting normalization by exploiting a priori knowledge of the human face and facial features; a fine step aligning the input data with the model stored in the database by the partial directed Hausdorff distance. To speed up the registration, a simplified version of the model is generated for each model in the model database. During the face comparison, the partial Hausdorff distance is employed as the similarity metric. Experiments have been carried out on a database with 30 individuals, and the best EER of 3.24% is achieved.