In recent years, deep learning has revolutionized computer vision and has been widely used
for monitoring in diverse visual scenes. However, in terms of some aspects such as …

Abstract Correlation Filters (CFs) have recently demonstrated excellent performance in
terms of rapidly tracking objects under challenging photometric and geometric variations …

During the recent years, correlation filters have shown dominant and spectacular results for
visual object tracking. The types of the features that are employed in this family of trackers …

In recent years, discriminative correlation filter (DCF) based algorithms have significantly
advanced the state of the art in visual object tracking. The key to the success of DCF is an …

In this paper, we present a simple yet fast and robust algorithm which exploits the dense
spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal …

Visual object tracking is a significant technology for camera-based sensor networks
applications. Multilayer convolutional features comprehensively used in correlation filter …

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 …

For visual tracking methods based on kernel support vector machines (SVMs), data
sampling is usually adopted to reduce the computational cost in training. In addition …

Enormous uncertainties in unconstrained environments lead to a fundamental dilemma that
many tracking algorithms have to face in practice: Tracking has to be computationally …

Recently, combining multiple features into discriminative correlation filters to improve
tracking representation has shown great potential in object tracking. Existing trackers apply …