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山东大学学报 (工学版) ›› 2023, Vol. 53 ›› Issue (2): 61-69.doi: 10.6040/j.issn.1672-3961.0.2022.135

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基于轨迹掩膜的在线多目标跟踪方法

余明骏1,刁红军1,凌兴宏1,2,3*   

  1. 1.苏州大学计算机科学与技术学院, 江苏 苏州 215006;2.苏州城市学院计算科学与人工智能学院, 江苏 苏州 215104;3.吉林大学符号计算与知识工程教育部重点实验室, 吉林 长春 130012
  • 收稿日期:2022-04-11 出版日期:2023-04-22 发布日期:2023-04-21
  • 作者简介:余明骏(1998— ),男,浙江金华人,硕士研究生,主要研究方向为机器学习. E-mail:820926575@qq.com. *通信作者简介:凌兴宏(1968— ),男,江苏扬州人,副教授,硕士生导师,主要研究方向为机器学习. E-mail:lingxinghong@suda.edu.cn.
  • 基金资助:
    符号计算与知识工程教育部重点实验室(吉林大学)开放课题项目(93K172021K08);江苏高校优势学科建设工程资助项目(PAPD)

Online multi-object tracking method based on trajectory mask

YU Mingjun1, DIAO Hongjun1, LING Xinghong1,2,3*   

  1. 1. School of Computer Science and Technology, Soochow University, Suzhou 215006, Jiangsu, China;
    2. School of Computational Science and Artificial Intelligence, Suzhou City University, Suzhou 215104, Jiangsu, China;
    3. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, Jilin, China
  • Received:2022-04-11 Online:2023-04-22 Published:2023-04-21

摘要: 针对现有多目标跟踪方法易受到遮挡、运动模糊等问题干扰的情况,提出基于轨迹掩膜的在线多目标跟踪方法(online multi-object tracking method based on trajectory mask, OMTMTM)。提出轨迹掩膜生成算法,利用前一帧跟踪轨迹结果生成轨迹掩膜,设计轨迹掩膜网络对轨迹掩膜提取多维度特征,包含目标可见区域的估计值、大致位置及形状等信息;将该特征与基础骨干网络提取的原始图像特征融合后进行多目标检测跟踪。OMTMTM的目标跟踪器具备先验判断能力,可实现遮挡情况下的准确跟踪;OMTMTM利用目标跟踪轨迹的时空信息,恢复出部分漏检或低置信待检目标,使轨迹掩膜更加合理,有利于后续跟踪。对OMTMTM的性能进行多维度评估,并结合基线模型进行对比分析。试验结果表明,OMTMTM具有先进的多目标跟踪性能。

关键词: 多目标跟踪, 目标检测, 轨迹掩膜, 视频流, 遮挡

中图分类号: 

  • TP391
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