计算机科学 ›› 2010, Vol. 37 ›› Issue (8): 273-275289.

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窗口尺寸变化目标的遮挡跟踪

林庆,陈远祥,王士同,詹永照   

  1. (江苏大学计算机科学与通信工程学院 镇江212013),(南京理工大学计算机系 南京210094),(江南大学信息学院 无锡214122)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金项目((60673190)资助。

MeanShift Tracking Algorithm with the Adaptive Bandwidth of the Target in Occlusions

LIN Qing,CHEN Yuan-xiang,WANG Shi-tong,ZHAN Yong-zhao   

  • Online:2018-12-01 Published:2018-12-01

摘要: 针对传统的McanShift跟踪算法在目标发生遮档时容易导致目标丢失的情况,提出了一种改进的McanShift跟踪算法。将多尺度空间理论、Kalman滤波器与遮档算法相结合,当目标发生遮挡后,利用Kalman佑计目标信息量,能对目标尺寸有后续跟踪能力。实验结果表明,当目标发生遮档后,改进的跟踪算法对目标无论增大或减小都能连续地、自动地选择大小合适的跟踪窗口。

关键词: Kalman,信息量,MeanShift,遮挡

Abstract: An improved Mean-Shift based tracking algorithm was proposed to solve the poor tracking ability problem in occlusions. Combinating multi-scale space theory, Kalman filter and occlusion, it can have a good tracking about scale using Kalman when target has been occluded. The experimental results show that the improved algorithm can select the proper size of the tracking window in the scenarios when the target has been occluded.

Key words: Kalman, Amount of information measure, McanShift, Occlusion

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