We present data collection and recognition experiment focused on multi-view face recognition/descriptor. Many face databases and face recognition systems have been constructed and experimented in terms of various illumination, time, poses, or expressions. However none of databases yet satisfies a large variation of poses to study systematic 3D human face information, which results unsatisfactor...

We present a novel 3D face recognition approach based on geometric invariants introduced by Elad and Kimmel. The key idea of the proposed algorithm is a representation of the facial surface, invariant to isometric deformations, such as those resulting from different expressions and postures of the face. The obtained geometric invariants allow mapping 2D facial texture images into special images...

We propose a vector representation (called a 3D signature) for 3D face shape in biometrics applications. Elements of the vector correspond to fixed surface points in a face-centered coordinate system. Since the elements are registered to the face, comparisons of vectors to produce match scores can be performed without a probe to gallery alignment step such as an invocation of the iterated close...

One critical challenge encountered by existing face recognition techniques lies in the difficulties of handling varying poses. In this paper, we propose a novel pose invariant 3D face recognition scheme to improve regular face recognition from two aspects. Firstly, we propose an effective geometry based alignment approach, which transforms a 3D face mesh model to a well-aligned 2D image. Second...

In this paper, an efficient pose-invariant face recognition method is proposed. This method is multimodal means that it uses 2D (color) and 3D (depth) information of a face for recognition. In the first step, the geodesic distances of all face points from a reference point are computed. Then, the face points are mapped from the 3D space to a new 2D space. The proposed mapping is robust under th...

Face recognition is an interesting issue in pattern recognition. In this paper, we propose a method for face recognition using 3D depth information. The goal is to get minimum features and produce a good recognition rates. We extract 3D clouds points from 3d vrml face Database, then the nose tip for each sample is detected and considered as new origin of the coordinate system, Gaussian Hermite ...

Face recognition technology has been a focus both in academia and industry for the last couple of years because of its wide potential applications and its importance to meet the security needs of today’s world. Most of the systems developed are based on 2D face recognition technology, which uses pictures for data processing. With the development of 3D imaging technology, 3D face recognition eme...

Automated human face recognition is an important computer vision problem with numerous applications including security, surveillance, database retrieval, and human computer interaction. Over two decades of research in the area has resulted in a number of successful techniques for recognition of color/intensity two dimensional (2D) frontal facial images. However, the performance of these algorit...

A personal identiication system based on the analysis of frontal or proole images of the face has applications in human-computer interfaces, access control , surveillance etc. Among many practical face recognition schemes, image based approaches are possibly the most promising ones. However, the 2D im-ages/patterns of 3D face objects can change dramatically due to lighting and viewing variation...

With the rapid development of 3D imaging technology, face recognition using 3D range data has become another alternative in the field of biometrics. Unlike face recognition using 2D intensity images, which has been studied intensively by many researchers since the 1960’s, 3D range data records the exact geometry of a person and it is invariant with respect to illumination changes of the environ...