Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (14): 161-168.DOI: 10.3778/j.issn.1002-8331.1903-0371

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Research on Tracking Method of Mobile Robot Fusing Depth Information

PAN Rongmin, YUAN Jie, WANG Hongwei, MI Tang   

  1. 1.School of Electrical Engineering, Xinjiang University, Urumqi 830047, China
    2.School of Control Science and Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
  • Online:2020-07-15 Published:2020-07-14



  1. 1.新疆大学 电气工程学院,乌鲁木齐 830047
    2.大连理工大学 控制科学与工程学院,辽宁 大连 116024


In complex scenes and drastic changes in target appearance, the tracking model of the Kernelized Correlation Filter(KCF) method is susceptible to interference, which results in the problem that the tracking window is not adaptive and the target is lost. To this end, a mobile robot tracking system based on depth information is proposed. The target scale frame is estimated by Cross-Searching Edge(CSE) method, and the tracking failure is checked by fluctuations in axial relative kinetic energy method. The target loss is recovered by scale pool and search strategy. Experimental results show that the proposed method combining KCF and scene depth information can effectively realize target tracking window self-adaptation and target recovery after losing, which has a stable application effect on mobile robots.

Key words: target tracking, depth information, Kernelized Correlation Filters(KCF), mobile robot



关键词: 目标跟踪, 深度信息, 核相关滤波器, 移动机器人