A visual tracking algorithm via confidence-based multi-feature correlation filtering

2021 ◽  
Author(s):  
Sheng Fang ◽  
Yichen Ma ◽  
Zhe Li ◽  
Bin Zhang
Keyword(s):  
Visual Tracking ◽  
Tracking Algorithm ◽  
Feature Correlation ◽  
Correlation Filtering

scholarly journals Fusion detection mechanism of robust correlation filtering visual tracking algorithm

2019 ◽  
Vol 40 (5) ◽  
pp. 795-804
Author(s):  
HOU Zhingqiang ◽  
WANG Shuai ◽  
YU Wangsheng ◽  
LI Youmou ◽  
MA Sugang
Keyword(s):  
Visual Tracking ◽  
Tracking Algorithm ◽  
Detection Mechanism ◽  
Fusion Detection ◽  
Correlation Filtering

Multi-Scale Correlation Filtering Visual Tracking Algorithm Combined with Target Detection

2019 ◽  
Vol 39 (1) ◽  
pp. 0115004
Author(s):  
王红雨 Wang Hongyu ◽  
汪梁 Wang Liang ◽  
尹午荣 Yin Wurong ◽  
胡江颢 Hu Jianghao ◽  
乔文超 Qiao Wenchao
Keyword(s):  
Target Detection ◽  
Visual Tracking ◽  
Tracking Algorithm ◽  
Multi Scale ◽  
Correlation Filtering

Vision-based target point tracking and aiming method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiao Bo Liang ◽  
Xinghua Qu ◽  
YuanJun Zhang ◽  
Lianyin Xu ◽  
Fumin Zhang
Keyword(s):  
Standard Deviation ◽  
Target Tracking ◽  
High Precision ◽  
Visual Tracking ◽  
Laser Ranging ◽  
Content Type ◽  
Mean Error ◽  
Wide Range ◽  
The Mean ◽  
Correlation Filtering

Purpose Laser absolute distance measurement has the characteristics of high precision, wide range and non-contact. In laser ranging system, tracking and aiming measurement point is the precondition of automatic measurement. To solve this problem, this paper aims to propose a novel method. Design/methodology/approach For the central point of the hollow angle coupled mirror, this paper proposes a method based on correlation filtering and ellipse fitting. For non-cooperative target points, this paper proposes an extraction method based on correlation filtering and feature matching. Finally, a visual tracking and aiming system was constructed by combining the two-axis turntable, and experiments were carried out. Findings The target tracking algorithm has an accuracy of 91.15% and a speed of 19.5 frames per second. The algorithm can adapt to the change of target scale and short-term occlusion. The mean error and standard deviation of the center point extraction of the hollow Angle coupling mirror are 0.20 and 0.09 mm. The mean error and standard deviation of feature points matching for non-cooperative target were 0.06 mm and 0.16 mm. The visual tracking and aiming system can track a target running at a speed of 0.7 m/s, aiming error mean is 1.74 pixels and standard deviation is 0.67 pixel. Originality/value The results show that this method can achieve fast and high precision target tracking and aiming and has great application value in laser ranging.

Visual tracking algorithm based on the sparse-regularized subspace

2018 ◽  
Vol 26 (4) ◽  
pp. 989-997
Author(s):  
陈典兵 CHEN Dian-bing ◽  
朱明 ZHU Ming ◽  
王慧利 WANG Hui-li ◽  
杨航 YANG Hang
Keyword(s):  
Visual Tracking ◽  
Tracking Algorithm
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