Quadratic correlation filter based target tracking in FLIR image sequences

2005 ◽  
Author(s):  
A. Bal ◽  
M. S. Alam
Keyword(s):  
Target Tracking ◽  
Image Sequences ◽  
Correlation Filter

scholarly journals An Improved Kernelized Correlation Filter Algorithm for Underwater Target Tracking

2018 ◽  
Vol 8 (11) ◽  
pp. 2154 ◽  
Author(s):  
Xingmei Wang ◽  
Guoqiang Wang ◽  
Zhonghua Zhao ◽  
Yue Zhang ◽  
Binghua Duan
Keyword(s):  
Target Tracking ◽  
Adaptive Filter ◽  
Poor Performance ◽  
Image Sequences ◽  
Correlation Filter ◽  
Tracking Errors ◽  
The Poor ◽  
Continuous Scale ◽  
Underwater Target ◽  
Update Strategy

To obtain accurate underwater target tracking results, an improved kernelized correlation filter (IKCF) algorithm is proposed to track the target in forward-looking sonar image sequences. Specifically, a base sample with a dynamically continuous scale is first applied to solve the poor performance of fixed-scale filters. Then, in order to prevent the filter from drifting when the target disappears and appears again, an adaptive filter update strategy with the peak to sidelobe ratio (PSR) of the response diagram is developed to solve the following target tracking errors. Finally, the experimental results show that the proposed IKCF can obtain accurate tracking results for the underwater targets. Compared to other algorithms, the proposed IKCF has obvious superiority and effectiveness.

scholarly journals Aerial Infrared Target Tracking in Complex Background Based on Combined Tracking and Detecting

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Yangguang Hu ◽  
Mingqing Xiao ◽  
Kai Zhang ◽  
Xiaotian Wang
Keyword(s):  
Deep Learning ◽  
Target Tracking ◽  
High Efficiency ◽  
Infrared Image ◽  
Image Sequences ◽  
Correlation Filter ◽  
Weapon Systems ◽  
Complex Background ◽  
Challenging Research ◽  
Comparable Performance

Aerial infrared target tracking is the basis of many weapon systems, especially the air-to-air missile. Till now, it is still challenging research to track the aircraft in the event of complex background. In this paper, we focus on developing an algorithm that could track the aircraft fast and accurately based on infrared image sequence. We proposed a framework composed of a tracker T based on correlation filter and a detector D based on deep learning, which we call combined tracking and detecting (CTAD). With such collaboration, the algorithm enjoys both the high efficiency provided by correlation filter and the strong discriminative power provided by deep learning. Finally, we performed experiments on three representative infrared image sequences and two sequences from VOT-TIR2016 dataset to quantitatively evaluate the performance of our algorithm. To evaluate our algorithm scientifically, we present the experiments performed on two sequences from AMCOM FLIR dataset of the proposed algorithm. The experimental results demonstrate that our algorithm could track the infrared target reliably, which shows comparable performance with the deep tracker, while running at a fast speed of about 18.1 fps.

Infrared target tracking with correlation filter based on adaptive fusion of responses

2019 ◽  
Vol 48 (6) ◽  
pp. 626003
Author(s):  
房胜男 Fang Shengnan ◽  
谷小婧 Gu Xiaojing ◽  
顾幸生 Gu Xingsheng
Keyword(s):  
Target Tracking ◽  
Correlation Filter ◽  
Adaptive Fusion

scholarly journals Adaptive context-aware correlation filter target tracking

2019 ◽  
Vol 1213 ◽  
pp. 052077
Author(s):  
Saijun Zhou ◽  
Chengwang Zhang ◽  
Xuying Xiong ◽  
Ran He ◽  
Jingang Qiu
Keyword(s):  
Target Tracking ◽  
Correlation Filter ◽  
Context Aware
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