This Ph.D thesis work is dedicated to 3D facial surface analysis, processing as well as to the newly proposed 3D face recognition modality, which is based on mapping techniques. Facial surface processing and analysis is one of the most important steps for 3D face recognition algorithms. Automatic anthropometric facial features localization also plays an important role for face localization, fac...

An approach to multi-view face detection based on head pose estimation is presented in this paper. Support Vector Regression is employed to solve the problem of pose estimation. Three methods, the eigenface method, the Support Vector Machine (SVM) based method, and a combination of the two methods, are investigated. The eigenface method, which seeks to estimate the overall probability distribut...

We present a fast algorithm for face detection and precise pose estimation. Our detection scheme is based on a tree-structured hierarchy of face vs. background classifiers combined with a lazy evaluation strategy which concentrates computation on ambiguous areas of the image. The hierarchy corresponds to successive partitions of the pose parameter space, and thereby provides, at no additional c...

In this paper we propose a fully automatic scheme for 3D face recognition. In our scheme, the original 3D data is automatically converted into the normalized 3D data, then the discriminant common vector (DCV) is introduced for 3D face recognition. We also compare DCV with two common methods, i.e., principal component analysis (PCA) and linear discriminant analysis (LDA). Our experiments are bas...

Face-based speech synthesis provides a practical solution to generate voices from human faces. However, directly using 2D face images leads the problems of uninterpretability and entanglement. In this paper, address issues, we introduce 3D shape which (1) has an anatomical relationship between voice characteristics, partaking in "bone conduction" timbre production, (2) is naturally independent ...

One unresolved question about face perception is: what is the role of three-dimensional information in face recognition? In this study, recognition performance was compared across changes in viewpoint in different depth conditions: a 2D condition without stereo information and a 3D condition where stereo information was present (by viewing the same face images as anaglyphs through 3D glasses). ...

The paper studies the stability of unsupported tunnel faces by analyzing results a large number 3D numerical analyses, in various ground conditions and overburden depths. analyses calculate average face extrusion (Uh) averaging axial displacement over face. Limiting occurs when becomes very convergence problematic. Using dimensionless “face parameter” is defined, which depends on suitable combi...

This report is concerned with understanding the interplay between 3D face reconstruction and recognition. We provide analysis for the effect of adaptive sparse 3D reconstructions on recognition rate. This work illustrates that, for 3D face recognition, a proper mesh containing nearly 2% of the facial information and about 5 times the initial/root mesh provides similar recognition rate as one wi...

Machine vision will play a significant role in the next generation of IR 4.0 systems. Recognition and analysis faces are essential many vision-based applications. Deep Learning provides thrust for advancement visual recognition. An important tool recognition tasks is Convolution Neural networks (CNN). However, 2D methods machine suffer from Pose, Illumination, Expression (PIE) challenges occlus...