A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse
coding is presented. In addition to using class labels of training data, we also associate label …

A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse
coding is presented. In addition to using class labels of training data, we also associate label …

Dictionary learning (DL) for sparse coding has shown promising results in classification
tasks, while how to adaptively build the relationship between dictionary atoms and class …

In this paper, we propose a low-rank sparse coding (LRSC) method that exploits local
structure information among features in an image for the purpose of image-level …

A greedy-based approach to learn a compact and discriminative dictionary for sparse
representation is presented. We propose an objective function consisting of two …

For sparse representation or sparse coding based image classification, the dictionary, which
is required to faithfully and robustly represent query images, plays an important role on its …

Motivated by image reconstruction, sparse representation based classification (SRC) has
been shown to be an effective method for applications like face recognition. In this paper, we …

Recent research has shown the effectiveness of using sparse coding (Sc) to solve many
computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear …

Conventional dictionary learning algorithms suffer from the following problems when applied
to face recognition. First, since in most face recognition applications there are only a limited …

In a sparse-representation-based face recognition scheme, the desired dictionary should
have good representational power (ie, being able to span the subspace of all faces) while …