A survey of local feature methods for 3D face recognition

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.