Aiming at the problem that the traditional correlation filter tracking algorithm is prone to
tracking failure under the target's scale change and occlusion environment, we propose a …

The tracking approaches based on correlation filter have shown their particular importance
due to the performance superiority from the perspectives of accuracy and speed. However …

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

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 …

In order to solve the problem of fixed target size in Kernel Correlation Filtering (KCF) tracker,
a scale adaptive tracking method was proposed. Firstly, the Lucas-Kanade optical flow …

Target tracking has always been an important research direction in the field of computer
vision. The target tracking method based on correlation filtering has become a research …

In order to solve the problem of object drift caused by Kernelized Correlation Filter (KCF)
tracking algorithm when scale changes, a Fast Scale Adaptive tracking of Correlation Filter …

摘要 In order to solve the scale prediction problem in visual object tracking, a scale
estimation strategy is given in the framework of tracking with kernelized correlation filters, the …

Focusing on the issue that the conventional Kernel Correlation Filter (KCF) algorithm has
poor performance in handling scale change and obscured objects, this paper proposes an …

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 …