A survey of local feature methods for 3D face recognition.

A survey of 3D face methods with the main focus on local features is conducted.The popular 3D face databases are described along with their acquisition technology.3D local descriptors are divided into key-points, curves, and surface-based methods.The surveyed approaches are summarized and compared under different conditions. One of the main modules in a face recognition system is feature extraction, which has a significant effect on the whole system performance. In the past decades, various types of feature extractors and descriptors have been proposed for 3D face recognition. Although several literature reviews have been carried out on 3D face recognition algorithms, only a few studies have been performed on feature extraction methods. The latter have a vital role to overcome degradation conditions, such as face expression variations and occlusions. Depending on the types of features used in 3D face recognition, these methods can be divided into two categories: global and local feature-based methods. Local feature-based methods have been effectively applied in the literature, as they are more robust to occlusions and missing data. This survey presents a state-of-the-art for 3D face recognition using local features, with the main focus being the extraction of these features.