Infrared target tracking based on multi-feature correlation filter

被引:0
|
作者
He, Yu-Jie [1 ]
Li, Min [1 ]
Zhang, Jin-Li [1 ,2 ]
Yao, Jun-Ping [1 ]
机构
[1] Department of 908, The Second Artillery Engineering University, Xi'an, China
[2] Department of Information Engineering, Engineering University of CAPF, Xi'an, China
关键词
Clutter (information theory);
D O I
10.16136/j.joel.2015.08.0292
中图分类号
学科分类号
摘要
In order to realize robust tracking of infrared target in complicated background with lots of disturbed factors, this paper proposes an infrared target tracking method based on multi-feature correlation filter. Considering the visual attention mechanism and motion mechanism, the spatial feature and motion feature are extracted firstly. Then the multi-feature weighted function is generated by fusing the above two features and the improved convolution feature. Secondly, on the basis of traditional correlation filter, the tracking framework vie weighted correlation filter is presented by introducing multi-feature weighted function which could represent the importances of different candidate regions. Finally, the confidence map which indicates the best target location is computed. The experiments under 6 sequences with different conditions demonstrate that the average increase of success rate of the proposed method has increased by about 15% compared with other traditional methods, and the proposed method is applicable to infrared target tracking under different conditions efficiently, such as similar alias target, occlusion, thermal radiance variation of background and detector motion. ©, 2015, Board of Optronics Lasers. All right reserved.
引用
收藏
页码:1602 / 1610
相关论文
共 50 条
  • [21] Multi-Feature Matching GM-PHD Filter for Radar Multi-Target Tracking
    Tao, Jin
    Jiang, Defu
    Yang, Jialin
    Zhang, Chao
    Wang, Song
    Han, Yan
    SENSORS, 2022, 22 (14)
  • [22] Hierarchical particle filter tracking algorithm based on multi-feature fusion
    Gan, Minggang
    Cheng, Yulong
    Wang, Yanan
    Chen, Jie
    JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2016, 27 (01) : 51 - 62
  • [23] A method of multi-feature particle filter tracking based on video sequences
    Liu, Ya-Hui
    Jia, Qing-Xuan
    Sun, Han-Xu
    Gao, Xin
    Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 2011, 34 (SUPPL.): : 14 - 18
  • [24] Hierarchical particle filter tracking algorithm based on multi-feature fusion
    Minggang Gan
    Yulong Cheng
    Yanan Wang
    Jie Chen
    JournalofSystemsEngineeringandElectronics, 2016, 27 (01) : 51 - 62
  • [25] Object Tracking in Satellite Videos Based on Correlation Filter with Multi-Feature Fusion and Motion Trajectory Compensation
    Liu, Yaosheng
    Liao, Yurong
    Lin, Cunbao
    Jia, Yutong
    Li, Zhaoming
    Yang, Xinyan
    REMOTE SENSING, 2022, 14 (03)
  • [26] Multi-feature combined target tracking algorithm based on channel clipping
    Xie Y.
    Chen Y.
    1600, Chinese Institute of Electronics (42): : 764 - 772
  • [27] Kernelised correlation filters target tracking fused multi-feature based on the unmanned aerial vehicle platform
    Liu, Zhouzhou
    Liu, Mengna
    Zhang, Yangmei
    IET WIRELESS SENSOR SYSTEMS, 2022, 12 (01) : 1 - 11
  • [28] Multi-Feature Adaptive Target Tracking Algorithm Based on Rotational Inertia
    Ding, Yebing
    Tang, Guilin
    INTERNATIONAL JOURNAL OF MULTIPHYSICS, 2024, 18 (02) : 50 - 60
  • [29] Robust Vehicle Tracking Multi-feature Particle Filter
    Yildirim, M. Eren
    Song, Jongkwan
    Park, Jangsik
    Yoon, Byung Woo
    Yu, Yunsik
    MULTIMEDIA, COMPUTER GRAPHICS AND BROADCASTING, PT II, 2011, 263 : 191 - +
  • [30] Adaptive Multi-Feature Reliability Re-Determinative Correlation Filter for Visual Tracking
    Guan, Mingyang
    Wen, Changyun
    IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 23 (23) : 3841 - 3852