This paper describes an improved boosting algorithm, named RegionBoost, and its
application in developing a fast and robust invariant Local Binary Pattern histogram based …

This paper proposes a new scheme for the 2D-3D face recognition problem. Our proposed
framework mainly consists of Restricted Boltzmann Machines (RBMs) and a correlation …

Abstract 3D image data provide several advantages than 2D data for face recognition and
overcome many problems with 2D intensity images based methods. In this paper, we …

The addition of Three Dimensional (3D) data has the potential to greatly improve the
accuracy of Face Recognition Technologies by providing complementary information. In this …

We present an automatic face recognition approach, which relies on the analysis of the three-
dimensional facial surface. The proposed approach consists of two basic steps, namely a …

In modern times, when deep learning-based face recognition is highly in demand, this paper
presents machine learning techniques using the low-level feature extraction. Deep learning …

Due to its wide range of applications, automatic face recognition is a research area with high
popularity. Many different face recognition algorithms have been proposed in the last …

A new approach, called Collective Shape Difference Classifier (CSDC), is proposed to
improve the accuracy and computational efficiency of 3D face recognition. The CSDC learns …

In face recognition literature, 2D image based approaches are possibly the most promising
ones. However, the 2D images/patterns can change dramatically in practice. We first study …

The use of Three Dimensional (3D) data allows new facial recognition algorithms to
overcome factors such as pose and illumination variations which have plagued traditional …