Modern trackers based on traditional image processing or machine learning have made
great progress in recent years but still face the problem of error tracking. To make use of …

Multi-camera target tracking is a research hot spot in the field of computer vision. Because
the field of view covered by the fixed monocular camera is limited, it cannot continuously …

This paper proposes a target tracking algorithm that combines kernelized correlation filter
(KCF) and Kalman filter (KF) prediction to address the problem of poor tracking performance …

Compared with short-term target tracking, long-term target tracking requires processing of
long video sequences and scenes in which the target disappears and reappears. These …

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 …

Target tracking is an important area of research in computer vision where stable target's
tracking has been well solved. But in real world, it is difficult to ensure that the camera or …

Moving target tracking is one of the important research subjects in the current field of
computer vision, in which the correlation filter algorithms become a hotspot in theory …

Robust visual object tracking is one of the most challenging issues in the field of computer
vision. Because of the circular shifts strategy, correlation filter-based trackers show a great …

Correlation filter-based trackers exploit large numbers of cyclically shifted samples to train
the object classifier, which can achieve good results in tracking accuracy and speed …

In the visual tracking, correlation filtering (CF) based on tracking algorithms have shown
favorable performance in recent years, and have the impressive performance on benchmark …