Target tracking is currently a hot research topic in Computer Vision and has a wide range of
use in many research fields. However, due to factors such as occlusion, fast motion, blur and …

RGB-D cameras which become popular in recent years have brought new opportunities as
well as challenges to many computer vision tasks. However how to fully make use of the …

Recently, Kernel Correlation Filter (KCF) is recognized as one of the best visual tracking
algorithms which provide excellent tracking performance and high possessing speed …

This paper considers the problem of long-term target tracking in complex scenes when
tracking failures are unavoidable due to illumination change, target deformation, scale …

In the target tracking algorithm, extracting features from images is a vital link. By extracting
the features of the tracking target and the surrounding area samples, the higher the similarity …

In the real scene, the target itself and the background will be unpredictable changes, such
as the occlusion and other factors will bring greater challenges to the object tracking. In this …

In this paper, an improved moving target tracking algorithm with multiple cameras based on
the FOV line is presented. Firstly, a SIFT algorithm is used to select matching points …

In order to solve the tracking failure of kernelized correlation filter (KCF) tracking algorithm in
the case of target fast motion and motion blur, proposing a multi-sampling tracking algorithm …

In this article, a robust long-term object tracking algorithm is proposed. It can tackle the
challenges of scale and rotation changes during the long-term object tracking for security …

In recent year correlation filtering based algorithms have achieved significant performance
in tracking. In traditional, the previous frame has been trained in order to get the prediction …