This paper addresses the problem of face recognition under pose and illumination
variations, and proposes a novel algorithm inspired by the idea of sparse representation …

We propose a pose-robust face recognition method to handle the challenging task of face
recognition in the presence of large pose difference between gallery and probe faces. The …

Face recognition technique has obtained great progress and excellent results on public data
sets. However, traditional algorithms suffer from various changes such as illumination …

In this paper, a novel method is proposed for real-world pose-invariant face recognition from
only a single image in a gallery. A 3D Facial Expression Generic Elastic Model (3D FE-GEM) …

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 …

Face recognition based on few training samples is a challenging task. In daily applications,
sufficient training samples may not be obtained and most of the gained training samples are …

A limited training set usually limits the performance of face recognition in practice. Even
sparse representation-based methods which outperform in face recognition cannot avoid …

Single-sample face recognition is one of the most challenging problems in face recognition.
We propose a novel face recognition algorithm to address this problem based on a sparse …

To address the problem of face recognition where the number of the labeled samples is
insufficient and those samples involve pose, illumination and expression variations, etc., this …

In this paper, a novel method for real-time pose-invariant face recognition is proposed from
only a single image in a gallery including any facial expressions. A 3D Facial Expression …