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融合判别性与细粒度特征的抗遮挡红外目标跟踪算法

吴捷 马小虎

吴捷, 马小虎. 融合判别性与细粒度特征的抗遮挡红外目标跟踪算法[J]. 红外技术, 2022, 44(11): 1139-1145.
引用本文: 吴捷, 马小虎. 融合判别性与细粒度特征的抗遮挡红外目标跟踪算法[J]. 红外技术, 2022, 44(11): 1139-1145.
WU Jie, MA Xiaohu. Anti-Occlusion Infrared Target Tracking AlgorithmBased on Fusion of Discriminant and Fine-Grained Features[J]. Infrared Technology , 2022, 44(11): 1139-1145.
Citation: WU Jie, MA Xiaohu. Anti-Occlusion Infrared Target Tracking AlgorithmBased on Fusion of Discriminant and Fine-Grained Features[J]. Infrared Technology , 2022, 44(11): 1139-1145.

融合判别性与细粒度特征的抗遮挡红外目标跟踪算法

基金项目: 

国家自然科学基金 61402310

江苏省自然科学基金 BK20141195

泰州职业技术学院重点科研项目 1821819039

详细信息
    作者简介:

    吴捷(1982-),男,副教授,主要研究方向:视觉目标跟踪。E-mail: 37323736@qq.com

  • 中图分类号: TN911.73

Anti-Occlusion Infrared Target Tracking AlgorithmBased on Fusion of Discriminant and Fine-Grained Features

  • 摘要: 针对现有热红外目标跟踪算法难以处理相似物干扰和目标遮挡的问题,引入MMNet(Multi-task Matching Network)算法中的多任务框架获取热红外目标特定的判别性特征和细粒度特征,并将这两种特征相互融合,用于在类间和类内识别热红外对象。此外,利用峰值旁瓣比动态设置模型更新参数以更高效地获取目标变化信息并对跟踪结果进行评估。对于不可靠跟踪结果利用卡尔曼滤波对目标位置进行预测。在LSOTB-TIR(Large-Scale Thermal Infrared Object Tracking Benchmark)红外数据集上的实验结果表明,提出的改进算法性能较好,相比MMNet跟踪精确度和成功率分别提高了5.7%和4.2%,且能有效应对遮挡、变形等挑战,可以应用于红外目标跟踪领域。
  • 图  1  多任务匹配网络(MMNet)框架图

    Figure  1.  Architecture of Multi-task Matching Network (MMNet)

    图  2  细粒度感知网络(FANet)的体系结构

    Figure  2.  Architecture of Fine-grained Aware Network (FANet)

    图  3  8种算法在LSOTB-TIR的距离精度曲线图和成功率曲线

    Figure  3.  Distance accuracy curves and success rate curves of eight algorithms in LSOTB-TIR

    图  4  8种算法在LSOTB-TIR的6种挑战性场景下精确度曲线图

    Figure  4.  Accuracy curve of eight algorithms in six challenging scenarios of LSOTB-TIR

    图  5  本文算法与MMNet算法跟踪结果比较

    Figure  5.  Comparison of tracking results between our algorithm and MMNet

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    ZHANG Jin, WANG Yuanyu, LIN Dandan, et al. Anti-occlusion process of infrared target tracking based on correlation filters[J]. Infrared Technology, 2022, 44(3): 277-285. http://hwjs.nvir.cn/article/id/98939f6c-0de2-4692-9c34-9eabbb68205e
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    LI Chang, YANG Dedong, SONG Pen, et al. Global-Aware siamese network for thermal infrared object tracking[J]. Acta Optica Sinica, 2021, 41(6): 0615002-1-0615002-11. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB202106019.htm
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    LIU Yaosheng, LIAO Yurong, LIN Cunbao. Video satellite object tracking algorithm based on kernel correlation filter[J]. Fire Control & Command Control, 2022, 47(2): 49-55. https://www.cnki.com.cn/Article/CJFDTOTAL-HLYZ202202009.htm
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出版历程
  • 收稿日期:  2022-06-18
  • 修回日期:  2022-08-31
  • 刊出日期:  2022-11-20

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