Recently, sparse coding has been successfully applied in visual tracking. The goal of this
paper is to review the state-of-the-art tracking methods based on sparse coding. We first …

Fast access requirements preclude building L1 instruction caches large enough to capture
the working set of server workloads. Efforts exist to mitigate limited L1 instruction cache …

Sparse representation-based visual tracking approaches have attracted increasing interests
in the community in recent years. The main idea is to linearly represent each target …

Modern technologies have been producing data with complex intrinsic structures, which can
be naturally represented as two-dimensional matrices, such as gray digital images, and …

Abnormal behavior detection has been one of the most important research branches in
intelligent video content analysis. In this paper, we propose a novel abnormal behavior …

The kernelized correlation filter (KCF) is one of the state-of-the-art object trackers. However,
it does not reasonably model the distribution of correlation response during tracking …

In this paper, we present a structured sparse representation appearance model for tracking
an object in a video system. The mechanism behind our method is to model the appearance …

We propose a robust tracking algorithm based on local sparse coding with discriminative
dictionary learning and new keypoint matching schema. This algorithm consists of two parts …

Most existing tracking approaches are based on either the tracking by detection framework
or the tracking by matching framework. The former needs to learn a discriminative classifier …

In recent years, deep learning-based visual object trackers have achieved state-of-the-art
performance on several visual object tracking benchmarks. However, most tracking …