3D Face Recognition

Abstract

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.