In recent years, visual object tracking has become a very active research area. An
increasing number of tracking algorithms are being proposed each year. It is because …

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 …

Aiming at the existing problems that object tracking algorithm fails to track under the
influence of occlusion conditions, the paper has improved the Kernel Correlation Filter …

Short-term tracking is an open and challenging problem for which discriminative correlation
filters (DCF) have shown excellent performance. We introduce the channel and spatial …

Accurate scale estimation of a target is a challenging research problem in visual object
tracking. Most state-of-the-art methods employ an exhaustive scale search to estimate the …

In recent years, many tracking algorithms achieve impressive performance via fusing
multiple types of features, however, most of them fail to fully explore the context among the …

Structured output support vector machine (SVM) based tracking algorithms have shown
favorable performance recently. Nonetheless, the time-consuming candidate sampling and …

In this paper we present a tracker, which is radically different from state-of-the-art trackers:
we apply no model updating, no occlusion detection, no combination of trackers, no …

We propose a novel visual tracking algorithm based on the representations from a
discriminatively trained Convolutional Neural Network (CNN). Our algorithm pretrains a …

Robust and accurate visual tracking is one of the most challenging computer vision
problems. Due to the inherent lack of training data, a robust approach for constructing a …