Face recognition with variant pose, illumination and expression (PIE) is a challenging problem. In this paper, we propose an analysis-by-synthesis framework for face recognition with variant PIE. First, an efficient 2D-to-3D integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with neutral expression and normal illumi...

Face recognition is a very challenging issue and has attracted much attention over the past decades. This paper makes a new attempt to face recognition based on 3D point clouds by constructing 3D eigenfaces. First, a 3D mesh model is built to represent the face shape provided by the point cloud. Then, the principle component analysis (PCA) is used to construct the 3D eigenfaces, which describe ...

This paper investigates the enhancement of identification performance when using voice classifier to help 3D face recognition. 3D face recognition is well known for its being superior to 2D due to the invariance in illumination, make-ups and pose. However, it is still challenged by expression variance. The partial ICP method we used for 3D face recognition could implicitly and dynamically extra...

In this chapter we present a system for face recognition that combines two recent advances in computer graphics and computer vision: 3D morphable models and component-based recognition. By fitting a morphable model to a triplet of face images we generate a 3D head model for each person in our face database. The 3D models are rendered under varying pose and illumination conditions to build a lar...

We introduce novel subspace-based methods for learning from the azimuth angle of surface normals for 3D face recognition. We show that the normal azimuth angles combined with Principal Component Analysis (PCA) using a cosine-based distance measure can be used for robust face recognition from facial surfaces. The proposed algorithms are well-suited for all types of 3D facial data including data ...

Abstract Nowadays, we frequently use a lot of biometric identification technology means, such as: iris recognition, voice recognition and face but compared with other human features, information is easier to collect more easily accepted by the public. According survey, in interpersonal contact, most people get based on first impression, even if there are changes external conditions as age, expr...

ABSTRACT: 3D face recognition has the potential to achieve better accuracy than its 2D counterpart by measuring geometry of rigid features on the face. This avoids such pitfalls of 2D face recognition algorithms as change in lighting, different facial expressions, make-up and head orientation. Another approach is to use the 3D model to improve accuracy of traditional image based recognition by ...