Target tracking is a hotpot issue in computer vision. This study proposed a robust tracking
algorithm based on kernel correlation filter and multi-feature fusion. Firstly, an effective …

Although the correlation filter-based trackers achieve the competitive results both on
accuracy and robustness, the visual tracking is still a tough problem due to background …

Target tracking is widely used in many fields, but tracking performance still needs to be
improved due to factors such as deformation, illumination and occlusion. In this paper, we …

In order to solve the problems of illumination variation, scale variety and target occlusion
during the process of tracking, the traditional kernel correlation filter tracking algorithm uses …

The traditional kernel correlation filter (KCF) algorithm has poor tracking results in complex
scenes with severe occlusion, deformation, and low resolution and cannot achieve long …

We propose an improved object tracking algorithm based on kernelized correlation filter
(KCF), which can overcome the drawback of traditional KCF algorithms in that they cannot …

Object tracking remains a challenging problem in computer vision. Recently, methods based
on correlation filters have achieved good performance in benchmarks. Usually, most of …

Target tracking is an important research in the field of computer vision. Despite the rapid
development of technology, difficulties still remain in balancing the overall performance for …

Video tracking technology employed to achieve efficient and accurate tracking of targets in
complex scenes has often been one of the challenges to be tackled. When the target is in a …

Tracking with kernelized correlation filters (KCF) is an excellent object tracking algorithm,
which is widely concerned. In KCF, each candidate patch in tracked region corresponds to a …