… face recognition system based on both 3D range data as well as 2D gray-level facial images.
… in the 2D domain and Point Signature in the 3D domain. Extracted shape features from …

… of a given subject yielding 951 pairs of 2D and 3D images. Using a PCA-… for 2D and for
3D, we find that 3D outperforms 2D. However, we also find a multi-modal rank-one recognition …

… the 3D spatial domain. Therefore, we aim to investigate … 3D Gabor filter in the spatial domain
for face recognition applications. Various approaches in the domain of 2D face recognition …

… Moreover, they are not suitable for a single model image recognition task, because
multiple model images per person are necessary in order for training the system to “optimal” …

… as a 3D shape recognition method for 3D face recognition. For 2.5D depth images, classical
2D face recognition … images. Pan et al. [16] combined Eigenfaces and PCA for classification. …

… In our system, corresponding 3D range images and 2D gray-level images can be obtained
… a face recognition algorithm using corresponding range and gray-level facial images. It can …

… which reduces the amount of facial information. This paper focuses on tackling the face
recognition problems caused by view variations and facial expression variations and designing a …

… In this section we define some basic notations in the domain of 2D and 3D face recognition,
… that in addition to single 2D images of the subject’s face general 3D knowledge about …

… face recognition using multiple sensors (CCD and range finder). Each sensor captures different
aspects of facial features, 2D … in 2D images and point signatures in the 3D range data to …

… proposed to use a 3D morphable model for face recognition on 2D images [25–27]. … a
recognition rate of 99.8% for neutral frontal images and a recognition rate of 89% for profile images…