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题名:
a mean shift algorithm based on modified parzen window for small target tracking
作者: Chen Jianjun ; An Guocheng ; Zhang Suofei ; Wu Zhenyang
会议文集: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
会议名称: 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
会议日期: March 14,
出版日期: 2010
会议地点: Dallas, TX, United states
关键词: Algorithms ; Graphic methods ; Interpolation ; Signal processing ; Vector quantization ; Video recording
出版地: United States
收录类别: ei
ISSN: 15206149
ISBN: 9781420000000
部门归属: (1) School of Information Science and Engineering, Southeast University, Nanjing, China; (2) Intelligence Engineering Lab, Institute of Software Chinese Academy of Sciences, Beijing, China
主办者: The Institute of Electrical and Electronics Engineers; Signal Processing Society
英文摘要: This paper addresses the problem of small scale target tracking. The divided-by-zero problem in the weight computation of mean shift algorithm and its associated tracking interrupt problem are presented. To tackle these problems, the Parzen window density estimation method is modified to interpolate the histogram of the target candidate. Then the Kullback-Leibler distance is employed as a new similarity measure between the target model and the target candidate. Its corresponding weight computation and new location expressions are derived. On the basis of these works, we propose a new small target tracking algorithm using mean shift framework. The tracking experiments for real world video sequences show that the proposed algorithm can track the target successively and accurately. It can successfully track very small targets with only 6x12 pixels. ©2010 IEEE.
语种: 英语
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8606
Appears in Collections:中科院软件所图书馆_2010软件所会议论文

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Recommended Citation:
Chen Jianjun,An Guocheng,Zhang Suofei,et al. a mean shift algorithm based on modified parzen window for small target tracking[C]. 见:2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010. Dallas, TX, United states. March 14,.
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