Human faces in surveillance videos often suffer from severe image blur, dramatic pose
variations, and occlusion. In this paper, we propose a comprehensive framework based on …

Feature extraction is vital for face recognition. In this paper, we focus on the general feature
extraction framework for robust face recognition. We collect about 300 papers regarding face …

Pose and expression normalization is a crucial step to recover the canonical view of faces
under arbitrary conditions, so as to improve the face recognition performance. An ideal …

Abstract Local Binary Patterns (LBP) have emerged as one of the most prominent and
widely studied local texture descriptors. Truly a large number of LBP variants has been …

Deep learning, in particular Convolutional Neural Network (CNN), has achieved promising
results in face recognition recently. However, it remains an open question: why CNNs work …

To perform unconstrained face recognition robust to variations in illumination, pose and
expression, this paper presents a new scheme to extract “Multi-Directional Multi-Level Dual …

Interest in the security of individuals has increased in recent years. This increase has in turn
led to much wider deployment of surveillance cameras worldwide, and consequently …

Starting in the seventies, face recognition has become one of the most researched topics in
computer vision and biometrics. Traditional methods based on hand-crafted features and …

Sparse representation (or coding)-based classification (SRC) has gained great success in
face recognition in recent years. However, SRC emphasizes the sparsity too much and …

In most current nondestructive testing systems, a magnetic flux leakage (MFL) method is
widely used in various industry fields, where the structural integrity of specimens is of vital …