Face recognition with occlusion is common in the real world. Inspired by the works of
structured sparse representation, we try to explore the structure of the error incurred by …

Occlusion in face recognition is a common yet challenging problem. While sparse
representation based classification (SRC) has been shown promising performance in …

Recently the sparse representation (or coding) based classification (SRC) has been
successfully used in face recognition. In SRC, the testing image is represented as a sparse …

The single sample per person (SSPP) face recognition is a major problem and it is also an
important challenge for practical face recognition systems due to the lack of sample data …

Sparse representation based classification (SRC) has recently been proposed for robust
face recognition. To deal with occlusion, SRC introduces an identity matrix as an occlusion …

By coding the input testing image as a sparse linear combination of the training samples via
l 1-norm minimization, sparse representation based classification (SRC) has been recently …

We consider the problem of automatically recognizing human faces from frontal views with
varying expression and illumination, as well as occlusion and disguise. We cast the …

Robust face recognition (FR) is an active topic in computer vision and biometrics, while face
occlusion is one of the most challenging problems for robust FR. Recently, the …

In this paper, we consider the robust face recognition problem via iterative re-constrained
group sparse classifier (IRGSC) with adaptive weights learning. Specifically, we propose a …

Recently the sparse representation based classification (SRC) has been proposed for robust
face recognition (FR). In SRC, the testing image is coded as a sparse linear combination of …