Small target tracking using KCF and adaptive thresholding

2019 ◽  
Author(s):  
Sun-Gu Sun ◽  
Eui-Hyuk Lee
Keyword(s):  
Target Tracking ◽  
Adaptive Thresholding ◽  
Small Target

Anti-Interference Small Target Tracking from Infrared Dual Waveband Imagery

2021 ◽  
pp. 103882
Author(s):  
Kun Qian ◽  
Sheng Hui Rong ◽  
Kuan Hong Cheng
Keyword(s):  
Target Tracking ◽  
Small Target

Infrared Dim-Small Target Tracking Based on Guided Image Filtering and Kernelized Correlation Filtering

2018 ◽  
Vol 38 (2) ◽  
pp. 0204004
Author(s):  
赵东 Zhao Dong ◽  
周慧鑫 Zhou Huixin ◽  
秦翰林 Qin Hanlin ◽  
钱琨 Qian Kun ◽  
荣生辉 Rong Shenghui ◽  
...  
Keyword(s):  
Target Tracking ◽  
Image Filtering ◽  
Small Target ◽  
Guided Image Filtering ◽  
Correlation Filtering

Infrared small target tracking algorithm based on temporal-spatial structure sparse Bayesian estimation

2020 ◽  
Vol 105 ◽  
pp. 103160 ◽  
Author(s):  
Zhengzhou Li ◽  
Cheng Chen ◽  
Depeng Liu ◽  
Chao Zhang ◽  
Jingjie Zeng ◽  
...  
Keyword(s):  
Spatial Structure ◽  
Target Tracking ◽  
Bayesian Estimation ◽  
Tracking Algorithm ◽  
Small Target ◽  
Infrared Small Target

The study on infrared small target tracking technology under complex background

2012 ◽  
Author(s):  
Lei Liu ◽  
Xin Wang ◽  
Jilu Chen ◽  
Tao Pan
Keyword(s):  
Target Tracking ◽  
Small Target ◽  
Complex Background ◽  
Infrared Small Target ◽  
Tracking Technology

scholarly journals Infrared Small Target Tracking Based on Target Spatial Distribution With Improved Kernelized Correlation Filtering

2021 ◽  
Author(s):  
ZhiQiang Kou ◽  
Askar Hamdulla
Keyword(s):  
Target Tracking ◽  
Correlation Energy ◽  
Weighting Function ◽  
Target Position ◽  
Feature Weighting ◽  
Small Target ◽  
Tracking Accuracy ◽  
Detection Mechanism ◽  
Infrared Small Target ◽  
Correlation Filtering

Abstract The application of correlation filtering in infrared small target tracking has been a mature research field. Traditionalcorrelation filtering is to describe the target features by using a single feature, which can not solve the problem of target occlusion. Because of the fast moving speed and lack of re-detection mechanism, the target tracking will produce offset, which leads to the performance of the tracker to decline. In view of the above problems, a new multi feature re detection framework is proposed for long-term tracking of small targets. The feature selects multi feature weighting function, considers the importance of intensity feature to infrared target and different regions, calculates the gray distribution weighting function of the target, and combines the weighting function into the correlation filter. Before updating the template, to verify the reliability of target detection, the average peak correlation energy is used as the confidence of candidate region. When the target is completely occluded, the prediction result of Kalman filter is used as the optimal estimation of target position in the next frame. A large number of experimental results on different video sequences show that the tracking accuracy of this method is greatly improved compared with the baseline method.

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