In recent years, 3D face recognition has obtained much attention. Using 2D face image as probe and 3D face data as gallery is an alternative method to deal with computation complexity, expensive equipment and fussy pretreatment in 3D face recognition systems. In this paper we propose a learning based 2D-3D face matching method using the CCA to learn the mapping between 2D face image and 3D face...

The 2D face recognition systems encounter difficulties in recognizing faces with illumination variations. The depth map of the 3D face data has the potential to handle the variation in illumination of face images. The view variations are handled by using the moment invariants. Moment Invariants are used as rotation invariant features of the face image. For feature matching an efficient fuzzy-ne...

This paper presents a technique for decomposing an unseen 3D face under any facial expression into an estimated 3D neutral face and expression deformations (the shape residue between the non-neutral and the estimated neutral 3D face). We show that this decomposition gives a robust facial expression classification and improves the accuracy of an off-the-shelf 3D face recognition system. The prop...

In this paper we apply template protection to an authentication system based on 3D face data in order to protect the privacy of its users. We use the template protection system based on the helper data system (HDS). The experimental results performed on the FRGC v2.0 database demonstrate that the performance of the protected system is of the same order as the performance of the unprotected syst...

We present a novel approach to view and pose invariant face recognition that combines two recent advances in the computer vision field: component-based recognition and 3D morphable models. In a first step a 3D morphable model is used to generate 3D face models from only two input images from each person in the training database. By rendering the 3D models under varying pose and illumination con...

Rapid development of 3D scanning technologies lead researchers to use them for people recognition, cameras are faster, models are less noisy and with higher resolution. 3D facial models have been widely used for many biometrics applications. Nevertheless 3D face recognition topics mainly assume that scans contain a face and the face is mostly in a frontal position. In real world we might have a...

In spite of the significant progress in automatic face recognition , there is still a need to perform many face recognition tasks by human operators due to both the special requirements in certain application scenarios and the poor performance of automatic face recognition in uncontrolled environments. In this paper, a novel system to assist human face recognition is proposed. The system utiliz...

We present a novel approach to pose and illumination invariant face recognition that combines two recent advances in the computer vision field: component-based recognition and 3D morphable models. In a first step a 3D morphable model is used to generate 3D face models from only two input images from each person in the training database. By rendering the 3D models under varying pose and illumina...