A limited number of available training samples have become one bottleneck of face
recognition. In real-world applications, the face image might have various changes owing to …

Representation-based classification methods are all constructed on the basis of the
conventional representation, which first expresses the test sample as a linear combination of …

Our team certainly regards 3D biometrics as a very potential research field, and has worked
on it since 2005. We are the first group that developed the 3D palmprint technology and …

Face recognition is one of the fundamental problems of computer vision and pattern
recognition. Based on the recent success of Low-Rank Representation (LRR), we propose a …

In this paper, we propose a sparse representation method for bimodal biometrics. The
proposed method first accomplishes the feature level fusion by combining the samples of the …

In this paper, we propose a novel method for face recognition. Its basic idea is to use a
coarse to fine strategy based on Scale Invariant Feature Transform (SIFT) feature. To …

Sparse representation based classification method has led to a wide variety of extensions of
representation based methods for face recognition. All of these methods partially reveal that …

In sparse representation algorithms, a test sample can be sufficiently represented by
exploiting only the training samples from the same class. However, due to variations of facial …

Abstract Sparse Representation Method has been proved to outperform conventional face
recognition (FR) methods and is widely applied in recent years. A novel Kernel-based …

In this paper, we propose a novel method to recognize the partially occluded face images
based on sparse representation. Generally, occlusions, such as glasses and scarf, fall on …