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4-D尺度空间中基于Mean-Shift的目标跟踪

王宇雄 章毓晋 王晓华

王宇雄, 章毓晋, 王晓华. 4-D尺度空间中基于Mean-Shift的目标跟踪[J]. 电子与信息学报, 2010, 32(7): 1626-1632. doi: 10.3724/SP.J.1146.2009.01000
引用本文: 王宇雄, 章毓晋, 王晓华. 4-D尺度空间中基于Mean-Shift的目标跟踪[J]. 电子与信息学报, 2010, 32(7): 1626-1632. doi: 10.3724/SP.J.1146.2009.01000
Wang Yu-xiong, Zhang Yu-jin, Wang Xiao-hua. Mean-Shift Object tracking through 4-D Scale Space[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1626-1632. doi: 10.3724/SP.J.1146.2009.01000
Citation: Wang Yu-xiong, Zhang Yu-jin, Wang Xiao-hua. Mean-Shift Object tracking through 4-D Scale Space[J]. Journal of Electronics & Information Technology, 2010, 32(7): 1626-1632. doi: 10.3724/SP.J.1146.2009.01000

4-D尺度空间中基于Mean-Shift的目标跟踪

doi: 10.3724/SP.J.1146.2009.01000

Mean-Shift Object tracking through 4-D Scale Space

  • 摘要: 在基于Mean-Shift的目标跟踪算法中,尺度自适应机制是算法研究的一个重要方向。一种典型的方法采用Lindeberg的尺度空间理论以获取目标尺度信息。但现有算法中将尺度由2-D矢量压缩为1-D量,未能精细地刻画目标仿射变换时的尺度变化,从而限制了算法的适用范围。为此,该文将尺度维1-D滤波推广至2-D,构造得到了相应的4-D尺度空间,并利用空间维和尺度维的Mean-Shift交替迭代,实现了同时在空间位置和尺度方向对目标的有效跟踪,提高了算法在目标尺度变化时的自适应性,并扩大了算法的适用范围。
  • Cheng Y. Mean shift, mode seeking, and clustering [J].IEEETransactions on Pattern Analysis and Machine Intelligence.1995, 17(8):790-799[2]Comaniciu D, Ramesh V, and Meer P. Real-time tracking ofnon-rigid objects using mean shift [C]. IEEE Conference onComputer Vision and Pattern Recognition, Hilton Head, SC,USA, 2000, II: 142-149.[3]Yilmaz A. Object tracking by asymmetric kernel mean shiftwith automatic scale and orientation selection [C]. IEEEConference on Computer Vision and Pattern Recognition,Minneapolis, MN, USA, 2007: 1-6.[4]Yao An-bang, Wang Gui-jin, Lin Xing-gang, and Wang Hao.Kernel based articulated object tracking with scaleadaptation and model update [C]. IEEE InternationalConference on Acoustics, Speech and Signal Processing, LasVegas, NV, USA, 2008: 945-948.Chen Xiao-peng, Zhou You-xue, Huang Xiao-san, and LiCheng-rong. Adaptive bandwidth mean shift object tracking[C]. IEEE Conference on Robotics, Automation andMechatronics, Chengdu, China, 2008: 1011-1017.Jiang Zhuo-lin, Li Shao-fa, Jia Xi-ping, and Zhu Hong-li. Animproved mean shift tracking method based onnonparametric clustering and adaptive bandwidth [C].Proceedings of the Seventh International Conference onMachine Learning and Cybernetics, Kunming, China, 2008:12-15.[5]Collins R T. Mean-shift blob tracking through scale space [C].IEEE Conference on Computer Vision and PatternRecognition, Baltimore, USA, 2003, 2: 234-240.[6]彭宁嵩, 杨杰, 刘志, 张凤超. Mean Shift 跟踪算法中核函数窗宽的自动选取 [J]. 软件学报, 2005, 16(9): 1542-1550.Peng Ning-song, Yang Jie, Liu Zhi, and Zhang Feng-chao.Automatic selection of kernel-bandwidth for Mean-Shiftobject tracking [J]. Journal of Software, 2005, 16(9):1542-1550.[7]章毓晋. 图像工程. 上册, 图像处理 [M]. 第2 版, 北京: 清华大学出版社, 2006: 62-71.Zhang Yu-jin. Image Engineering (I), Image Processing [M].Second Edition, Beijing: Tsinghua University Press, 2006:62-71.[8]Lindeberg T. Scale-Space Theory in Computer Vision [M].Netherlands: Kluwer Academic Publisher, 1994, Chapter 13.
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出版历程
  • 收稿日期:  2009-07-14
  • 修回日期:  2009-11-14
  • 刊出日期:  2010-07-19

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