Empirically, we find that, despite the class-specific features owned by the objects appearing
in the images, the objects from different categories usually share some common patterns …

Empirically, we find that despite the most exclusively discriminative features owned by one
specific object category, the various classes of objects usually share some common …

Despite the fact that different objects possess distinct class-specific features, they also
usually share common patterns. This observation has been exploited partially in a recently …

The employed dictionary plays an important role in sparse representation or sparse coding
based image reconstruction and classification, while learning dictionaries from the training …

Discriminative dictionary learning aims to learn a dictionary from training samples to
enhance the discriminative capability of their coding vectors. Several discrimination terms …

Discriminative dictionary learning (DDL) has demonstrated significantly improved
performance for image classification. However, most of the existing DDL methods just adopt …

Dictionary learning (DL) has been successfully applied to various pattern classification tasks
in recent years. However, analysis dictionary learning (ADL), as a major branch of DL, has …

Image classification is an important research task in multimedia content analysis and
processing. Learning a compact dictionary easying to derive sparse representation is one of …

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 …

The sparse coding technique has shown flexibility and capability in image representation
and analysis. It is a powerful tool in many visual applications. Some recent work has shown …