In this paper, we address the problem of fast motion and bound effect about the popular high-
speed correlation filters-based trackers. Such trackers are facing with the contradiction …

For the correlation filtering (CF) tracking algorithm is not robust enough and cannot adapt to
scale changes, target occlusion (OCC) and other complex interferences. We introduce a CF …

During UAV target tracking, there still exist some issues such as severe deformation, scale
variance, occlusion and even fast motion. In this paper, we propose a more stable, real-time …

Aiming at the problem that the positioning accuracy of the KCF tracking algorithm is difficult
to reach the pixel level and cannot adapt to the target scale variation well, the correlation …

Target tracking has also received a great deal of attention from society. The basic problem of
a target tracking algorithm is to select a target of interest in a video or image sequence, and …

In UAV (Unmanned Aerial Vehicle) target tracking, due to the complexity of the ground
scene, it brings great interference to target detection and tracking. Therefore, a method …

Planar tracking is an essential function in computer vision to address the problem of tracking
a planar target affected by illumination, deformation and blurring with real-time performance …

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 …

Moving object tracking is a method used to estimate the trajectory, detect and analyze
changes that occur in an observed object in a video. The moving observed object can be a …

Visual tracking is a challenge in computer vision. Visual tracking has various practical
application scenarios, and is used in intelligent video surveillance system, analysis and …