Face appearance in support of biometric recognition has been conventional with researcher for many years. Face systems have successfully made the changeover from the research laboratory to the commercial zone. Biometric detection should make use of dimensions that are solely subject-intrinsic, avoiding integration of other contaminate inputs and the property of imaging system revolution as much...

Title of Thesis: CONTOUR BASED 3D FACE MODELING FROM MONOCULAR VIDEO Himaanshu Gupta, Master of Science, 2003 Thesis directed by: Professor Rama Chellappa Department of Electrical and Computer Engineering Constructing 3D models from video is one of the most important problems in computer vision. We propose a novel 3D face modeling approach from monocular video captured by a conventional camera....

The use of 3D data in face image processing applications has received considerable attention during the last few years. A major issue for the implementation of 3D face processing systems is the accurate and real time acquisition of 3D faces using low cost equipment. In this paper we provide a survey of 3D reconstruction methods used for generating the 3D appearance of a face using either a sing...

This paper presents a part-based face detection approach where the spatial relationship between the face parts is represented by a hidden 3D model with six parameters. The computational complexity of the search in the six dimensional pose space is addressed by proposing meaningful 3D pose candidates by image-based regression from detected face keypoint locations. The 3D pose candidates are eval...

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 ...

In this paper a new complete system for 3D face recognition is presented. 3D face recognition presents several advantages against 2D face recognition, as, for example, invariance to illumination conditions. The proposed system makes use of a stereo methodology, that does not require any expensive range sensors. The 3D image of the face is modelled using Multilevel B-Splines coefficients, that a...

In this paper we propose a novel method that performs 3D face reconstruction, and non-constrained and non-contact gaze estimation on a moving object, whose head-pose can freely change, from multi-view video. The main idea is to first reconstruct the 3D face with high accuracy using symmetry prior. Then we generate a super-resolution virtual frontal face video from the estimated 3D face geometry...

The problem human face shape reconstruction basing on information about human skull is very important for many applications beginning with archeology and finishing with crime expertise. World recognition was received with a face shape reconstruction technique proposed by M. Gerasimov [1]. This method up to now is the general method for face reconstruction of unknown person. It operates with the...

This paper aims to address the ill-posed problem of reconstructing 3D faces from single 2D face images. An extended Tikhonov regularization method is connected with the standard 3D morphable model in order to reconstruct the 3D face shapes from a small set of 2D facial points. Further, by interpolating the input 2D texture with the model texture and warping the interpolated texture to the recon...

Principle Component Analysis (PCA)-based statistical 3D face modeling using example faces is a popular technique for modeling 3D faces and has been widely used for 3D face reconstruction and face recognition. The capability of the model to depict a new 3D face depends on the exemplar faces in the training set. Although a few 3D face databases are available to the research community and they hav...