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 …

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 …

As one of the most popular research topics, sparse representation and dictionary learning
technique has received an increasing amount of interest in recent years. Sparse …

During the past several years, as one of the most successful applications of sparse coding
and dictionary learning, dictionary-based face recognition has received significant attention …

Recently, sparse representation based classification (SRC) and collaborative representation
based classification (CRC) have been successfully used for visual recognition and have …

In sparse dictionary learning based face recognition (FR), a discriminative dictionary is
learned from the training set so that good classification performance can be achieved on …

In recent years, there has been a growing interest in the study of dictionary learning for face
recognition. Most of the conventional dictionary learning methods focus only on a single …

Dictionary learning has become a research hotspot. How to construct a robust dictionary is a
key issue. In face recognition problem, differences in expressions, postures, and lighting …

Dictionary learning is one of the most important algorithms for face recognition. However,
many dictionary learning algorithms for face recognition have the problems of small sample …

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 …