Multi‐directional local adjacency descriptors (MDLAD) for heterogeneous face recognition

Face recognition using Weber local descriptors

This paper presents a method for face recognition using multi-scale Weber local descriptors (WLDs) and multi-level information fusion. Our method introduces the WLD, a novel and robust local descriptor, to describe the facial images and modifies it by a non-linear quantization approach to enhance its discriminative power. Moreover, a multi-scale framework for WLD extraction with multi-level inf...

Multidirectional Binary Pattern for Face Recognition

Automatic Face Recognition via Local Directional Patterns

Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...

Face , Age and Gender Recognition using Local Descriptors

This thesis focuses on the area of face processing and aims at designing a reliable framework to facilitate face, age, and gender recognition. A Bag-of-Words framework has been optimized for the task of face recognition by evaluating different feature descriptors and different bag-of-words configurations. More specifically, we choose a compact set of features (e.g., descriptors, window location...

Multidirectional 2DPCA Based Face Recognition System

In this paper, Multidirectional 2DPCA is employed for face recognition of two different databases. All face images are rotated and their two dimensional principal components are calculated as features as features of facial images. These features in various directions are fused to form features of an individual’s facial image. The results of this technique is compared over FERET database and an ...