scholarly journals Selective part‐based correlation filter tracking algorithm with reinforcement learning

2021 ◽  
Author(s):  
Zhengzhi Lu ◽  
Guoan Yang ◽  
Deyang Liu ◽  
Junjie Yang ◽  
Yong Yang ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Tracking Algorithm ◽  
Correlation Filter

Weighted Correlation Filter Tracking Algorithm Based on Context and Relocation

2019 ◽  
Vol 39 (4) ◽  
pp. 0415004
Author(s):  
熊昌镇 Xiong Changzhen ◽  
卢颜 Lu Yan ◽  
闫佳庆 Yan Jiaqing
Keyword(s):  
Tracking Algorithm ◽  
Correlation Filter ◽  
Weighted Correlation

Correlation Filter Tracking Algorithm for Adaptive Feature Selection

2019 ◽  
Vol 39 (6) ◽  
pp. 0615004
Author(s):  
刘万军 Wanjun Liu ◽  
孙虎 Hu Sun ◽  
姜文涛 Wentao Jiang
Keyword(s):  
Feature Selection ◽  
Tracking Algorithm ◽  
Correlation Filter ◽  
Adaptive Feature Selection

Foreground-Aware Based Spatiotemporal Correlation Filter Tracking Algorithm

2019 ◽  
Vol 56 (22) ◽  
pp. 221503
Author(s):  
虞跃洋 Yu Yueyang ◽  
史泽林 Shi Zelin ◽  
刘云鹏 Liu Yunpeng
Keyword(s):  
Tracking Algorithm ◽  
Correlation Filter ◽  
Spatiotemporal Correlation

Correlation filter tracking algorithm based on double model

2019 ◽  
Vol 27 (11) ◽  
pp. 2450-2458
Author(s):  
张红颖 ZHANG Hong-ying ◽  
王汇三 WANG Hui-san ◽  
胡文博 HU Wen-bo
Keyword(s):  
Tracking Algorithm ◽  
Correlation Filter

A high-speed multi-scale kernel correlation filter tracking algorithm

2019 ◽  
Author(s):  
Bin Fu ◽  
Zongxi Song ◽  
Feng Wang ◽  
Wei Gao ◽  
Shuang Zhang ◽  
...  
Keyword(s):  
High Speed ◽  
Tracking Algorithm ◽  
Correlation Filter ◽  
Multi Scale ◽  
Kernel Correlation

scholarly journals Scale Adaptive Kernel Correlation Filter Tracking Algorithm Combined with Learning Rate Adjustment

2018 ◽  
Vol 232 ◽  
pp. 03016 ◽  
Author(s):  
Di Wu ◽  
Li Peng
Keyword(s):  
Target Tracking ◽  
Initial Position ◽  
Learning Rate ◽  
Tracking Algorithm ◽  
Correlation Filter ◽  
Average Difference ◽  
Scale Change ◽  
Rate Adjustment ◽  
Adaptive Kernel ◽  
Kernel Correlation

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 scale-adaptive Kernel Correlation Filter (KCF) target tracking algorithm combined with the learning rate adjustment. Firstly, we use the KCF to obtain the initial position of the target, and then adopt a low-complexity scale estimation scheme to get the target's scale, which improves the ability of the proposed algorithm to adapt to the change of the target's scale, and the tracking speed is also ensured. Finally, we use the average difference between two adjacent images to analyze the change of the image, and adjust the learning rate of the target model in segments according to the average difference to solve the tracking failure problem when the target is severely obstructed. Compared the proposed algorithm with other five classic target tracking algorithms, the experimental results show that the proposed algorithm is well adapted to the complex environment such as target’s scale change, severe occlusion and background interference. At the same time, it has a real-time tracking speed of 231 frame/s.

Target tracking algorithm based on image matching and improved kernel correlation filter

2021 ◽  
Author(s):  
Weimin Hou ◽  
Haining Li ◽  
Jia Su ◽  
Huimin Cui ◽  
Xin Luo
Keyword(s):  
Target Tracking ◽  
Image Matching ◽  
Tracking Algorithm ◽  
Correlation Filter ◽  
Kernel Correlation
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