A large amount of work has been done over the past decades in face recognition (FR). Most
of them deal with uncontrolled variations such as changes in illumination, pose, expression …

Face recognition has attracted great interest due to its importance in many real-world
applications. In this paper, we present a novel low-rank sparse representation-based …

Sparse representation provides an effective tool for classification under the conditions that
every class has sufficient representative training samples and the training data are …

The sparse representation based classification (SRC) performs not very well for small
sample data. A discriminative common vector dictionary based SRC is introduced in this …

Illumination and pose variable face recognition is an important and challenging task in
computer vision. To solve the problem that the accuracy of face recognition reduces with …

Although sparse representation (SR) based on the l 1-norm and l 2-norm have achieved
promising classification results for face recognition (FR) from frontal views, they both require …

Unconstrained face recognition remain a challenging problem due to intra-class variations
caused by occlusion, disguise, varying orientations, facial expressions, age variations and …

Sparse representation-based classification (SRC) has been a breakthrough of face
recognition and signal reconstruction recently. However, few face images from the same …

Representation-based classification methods, such as sparse representation-based
classification, have been a breakthrough for face recognition recently. Under such a …

Face recognition based on Sparse representation idea has recently become an important
research topic in computer vision community. However, the dictionary learning process in …