Advanced Search
中文
Volume 44 Issue 3
Mar.  2022
Turn off MathJax
Article Contents
Abstract
References
Related Articles
ZHANG Jin, WANG Yuanyu, LIN Dandan, DU Xinyue, LIN Yu, LAN Ge. Anti-occlusion Process of Infrared Target Tracking Based on Correlation Filters[J]. Infrared Technology , 2022, 44(3): 277-285.
Citation: ZHANG Jin, WANG Yuanyu, LIN Dandan, DU Xinyue, LIN Yu, LAN Ge. Anti-occlusion Process of Infrared Target Tracking Based on Correlation Filters[J]. Infrared Technology , 2022, 44(3): 277-285.
shu

Anti-occlusion Process of Infrared Target Tracking Based on Correlation Filters

  • Kunming Institute of Physics, Kunming 650223, China

More Information
  • Received Date: December 12, 2021
  • Revised Date: January 27, 2022
    Graphical Abstract
    • Abstract
  • Focusing on the issue that traditional correlation filters have poor performance in infrared target tracking with occlusion, an anti-occlusion and real-time target-tracking algorithm based on a multi-scale filter tracker and a deep learning detector is proposed. First, the peak response value is calculated using the tracker; if the peak value is less than the threshold, the target is occluded or tracking is lost. Second, the detector stops updating when the target is occluded or tracking is lost. The position of the target changes significantly when it comes in frame again after occlusion, and the speed of target searching with the tracker will be very slow. At this time, a detector is employed to detect the targets in the subsequent frames without loss of tracking accuracy and speed. The peak values are calculated for each target box that is detected by the detector, and the target with a maximum peak value larger than the threshold is tracked. The results of the experiment compared with the multi-scale correlation filter show that the proposed real-time tracking algorithm can not only effectively solve infrared target occlusion, but also has higher tracking robustness and accuracy.
    • FullText(HTML)
    • References (13)
  • [1]
    蔡毅. 红外系统中的扫描型和凝视型FPA[J]. 红外技术, 2001, 23(1): 1-5, 18. DOI: 10.3969/j.issn.1001-8891.2001.01.002

    CAI Yi. The scanning and starring FPA in infrared systems[J]. Infrared Technology, 2001, 23(1): 1-5, 18. DOI: 10.3969/j.issn.1001-8891.2001.01.002
    [2]
    范晋祥, 杨建宇. 军用红外成像探测跟踪技术发展趋势与新技术研究进展[C]//第十届全国光电技术学术交流会论文集, 2012: 125-134.

    FAN Jinxiang, YANG Jianyu. Development trend and research progress of military infrared imaging detection and tracking technology[C]//Proceedings of the 10th National Symposium on Optoelectronic Technology, 2012: 125-134.
    [3]
    王云萍. 美国天基红外导弹预警技术分析[J]. 光电技术应用, 2019, 34(3): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYG201903001.htm

    WANG Yunping. Analysis of space-based infrared missile warning system in America[J]. Electro-Optic Technology Application, 2019, 34(3): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-GDYG201903001.htm
    [4]
    FU Z, CHANG Z, YONG H, et al. Foreground gated network for surveillance object detection[C]//2018 IEEE Fourth International Conference on Multimedia Big Data (BigMM), 2018: 1-7.
    [5]
    Danelljan M, Hager G, Khan F S, et al. Learning spatially regularized correlation filters for visual tracking[C]//IEEE International Conference on Computer Vision, 2015: 4310-4318.
    [6]
    Bolme D S, Beveridge J R, Draper B A, et al. Visual object tracking using adaptive correlation filters[C]//The Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2010: 13-18.
    [7]
    Henriques J F, Rui C, Martins P, et al. Exploiting the circulant structure of tracking-by-detection with kernels[C]//Proceedings of the 12th European Conference on Computer Vision, 2012: 702-715.
    [8]
    Henriques J F, Caseiro R, Martins P, et al. High-speed tracking with kernelized correlation filters[C]//IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015, 37: 583-596.
    [9]
    Danelljan M, Häger G, Khan F S, et al. Accurate scale estimation for robust visual tracking[C]//British Machine Vision Conference, 2014(65): 1-11.
    [10]
    Danelljan M, Häger G, Khan F S, et al. Discriminative scale space tracking[C]//IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(8): 1561-1575.
    [11]
    Bochkovskiy A, WANG C Y, LIAO H. YOLOv4: optimal speed and accuracy of object detection[J/OL]. Computer Vision and Pattern Recognition, arXiv: 2004.10934. https://arxiv.org/abs/2004.10934.
    [12]
    Felzenszwalb P F, Girshick R B, Mc Allester D, et al. Object detection with discriminatively trained part-based models[C]//IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32: 1627-1645.
    [13]
    WU Y, LIM J, YANG M H. Object tracking benchmark[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015, 37: 1834-1848.
    • Related Articles

  • Related Articles

    [1]CHEN Jia, YU Chengbo, WANG Shibing, JIANG Qichao, HE Xin, ZHANG Wei. IR Image Classification and Detection of Power Equipment Based on CBAM Improvement[J]. Infrared Technology , 2025, 47(1): 72-80.
    [2]WANG Xiaodong, LYU Tongfa, BAO Mingzheng, HE Yongchun, XIN Peng, WU Tao. Infrared Image Recognition Method for Power Equipment Based on Improved YOLO v5[J]. Infrared Technology , 2024, 46(6): 722-727.
    [3]HUANG Zhihong, XIAO Jian, XU Xianyong, ZHANG Hui. Spectral Residual Transformation for Thermal Defect Detection of Power Equipment[J]. Infrared Technology , 2023, 45(8): 884-889.
    [4]LIU Yunfeng, ZHAO Hongshan, YANG Jinbiao, HAN Jinfeng, LIU Bingcong. Super Resolution Method for Power Equipment Infrared Imaging Based on Gradient Norm-ratio Prior[J]. Infrared Technology , 2023, 45(1): 40-48.
    [5]LIANG Jian, HUANG Zhihong, ZHANG Keren. Multi-scale Guided Filter and Decision Fusion for Thermal Fault Diagnosis of Power Equipment[J]. Infrared Technology , 2022, 44(12): 1344-1350.
    [6]HUANG Zhihong, HONG Feng, HUANG Wei. Shape Adaptation Low Rank Representation for Thermal Fault Diagnosis of Power Equipments[J]. Infrared Technology , 2022, 44(8): 870-874.
    [7]SU Haifeng, ZHAO Yan, WU Zejun, CHENG Bo, LYU Linfei. Refined Infrared Object Detection Model for Power Equipment Based on Improved RetinaNet[J]. Infrared Technology , 2021, 43(11): 1104-1111.
    [8]HUANG Zhihong, WU Sheng, XIAO Jian, ZHANG Keren, HUANG Wei. Thermal Fault Diagnosis of Power Equipments Based on Guided Filter[J]. Infrared Technology , 2021, 43(9): 910-915.
    [9]WANG Xiaofang, MAO Huamin. Infrared Image Segmentation Method for Power Equipment in Complex Background[J]. Infrared Technology , 2019, 41(12): 1111-1116.
    [10]CHEN Jishun, XIAO Lijun, WAN Xinyu, MAI Ruijie, QIN Huiping, LI Lei. Research on Enhancement and Segmentation of Power Equipment Infrared Heat Map in Complex Environment[J]. Infrared Technology , 2018, 40(11): 1112-1118.

  • Cited by

    Periodical cited type(1)

    1. 肖永平，马世娟，倪晓东. 频率源中关键信号电磁兼容研究. 电子设计工程. 2024(19): 115-118+123 .

    Other cited types(1)

Catalog

    Get Citation
    PDF
    XML
    Article views (233) PDF downloads (64) Cited by(2)
    Related

    Copyright © 《Infrared Technology》Editorial Office滇ICP备12000354号-3

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return