Statistical Approaches to Face Recognition a Qualifying Examination Report

A comprehensive experimental comparison of the aggregation techniques for face recognition

In face recognition, one of the most important problems to tackle is a large amount of data and the redundancy of information contained in facial images. There are numerous approaches attempting to reduce this redundancy. One of them is information aggregation based on the results of classifiers built on selected facial areas being the most salient regions from the point of view of classificati...

Multilayer Perceptrons versus Hidden Markov Models: Comparisons and Applications to Image Analysis and Visual Pattern Recognition a Qualifying Examination Report

Disguised Face Recognition by Using Local Phase Quantization and Singular Value Decomposition

Disguised face recognition is a major challenge in the field of face recognition which has been taken less attention. Therefore, in this paper a disguised face recognition algorithm based on Local Phase Quantization (LPQ) method and Singular Value Decomposition (SVD) is presented which deals with two main challenges. The first challenge is when an individual intentionally alters the appearance ...

3D Face Recognition using Patch Geodesic Derivative Pattern

In this paper, a novel Patch Geodesic Derivative Pattern (PGDP) describing the texture map of a face through its shape data is proposed. Geodesic adjusted textures are encoded into derivative patterns for similarity measurement between two 3D images with different pose and expression variations. An extensive experimental investigation is conducted using the publicly available Bosphorus and BU-3...

3D Face Recognition Using Range Images

This literature survey will evaluate face recognition algorithms based on range images of human faces. Range images have several advantages over 2D intensity images and 3D meshes. Range images are robust to the change of color and illumination, which causes a significant problem in face recognition using 2D intensity images. Also, 3D information from range images is much easier to utilize than ...