The sparse representation based classification (SRC) method and collaborative
representation based classification (CRC) method have attracted more and more attention in …

This paper proposes a novel approach for learning discriminative and sparse
representations. It consists of utilizing two different models. A predefined number of non …

Facial occlusion, such as sunglasses, mask etc., is one important factor that affects the
accuracy of face recognition. Unfortunately, faces with occlusion are quite common in the …

It is a challenging issue to deal with kinds of appearance variations in visual tracking.
Existing tracking algorithms build appearance models upon target templates. Those models …

Pattern classification algorithms based on sparse dictionary learning are derived. After
training a discriminative dictionary and a linear classifier using the samples of the individual …

In this paper, we propose a discriminative sparse feature for speech mode classification
(SMC). We use sparse representation, to calculate efficient representations of speech signal …

Dictionary learning (DL) and sparse representation (SR) based classifiers have greatly
impacted the classification performance and have had good recognition rate on image data …

Scene recognition is a significant topic in the field of computer vision. Most of the existing
scene recognition models require a large amount of labeled training samples to achieve a …

Image foreground extraction is a classical problem in image processing and vision, with a
large range of applications. In this dissertation, we focus on the extraction of text and …

This paper presents a novel nonlinear transform model for learning of collaboration
structured, discriminative and sparse representations. The idea is to model a collaboration …