3D face recognition algorithms are a group of methods which utilize 3D
geometry of face and facial feature for recognition. In comparison with 2D face
recognition algorithms that employ intensity or color based features, they are generally
robust against lighting condition, head orientation, facial expression and make-up. 3D
face recognition has several advantages. Firstly, the shape and the related features of
3D face can be acquired independent from lighting condition. Secondly, the pose of 3D
face data can be easily corrected and used for subsequent pose invariant feature
extraction. Thirdly, 3D face data are less affected by skin color, face cosmetic and
similar face reflectance factors. 3D face recognition may include several stages such as
3D image acquisition, face localization, feature extraction and face recognition. In this
article, different algorithms and the pipeline for 3D face recognition are discussed.
Keywords: 3D Face matching, 3D Face recognition, 3D Face registration, 3D
Image acquisition, 3D Surface descriptors active triangulation, Biometric
identifiers, Curvature descriptors, Face alignment, Face analysis, Face recognition
face segmentation, Facial features, Facial landmarks, Feature extraction, Head
pose estimation, Human identification, Laser scanner, Nose tip detection, Range
images.