Abstract
A model-based algorithm for 3D face recognition from range images is presented. The algorithm relies on deforming the triangular meshes of the model to the range data establishing direct model vertices correspondences with other deformed models in the database. These features correspondences greatly facilitate faster computational time, accuracy, and recognition comparisons. By only detecting three facial features and a generic model, we achieved a 90.2% rank one identification rate using a noisy database. The presented method is proved to be useful for face recognition. However, the method can also be sensitive to noisy or missing data under the mesh model. In the conducted experiments, six subjects out of the 61 were not correctly recognized. The wrong recognition was mainly due to the dataset being either very noisy, incomplete, or the query range image set looks very different from the database set. Unfortunately, the range data pre-processing and