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Title:
mean shift tracking with kernel co-occurrence matrices
Author: Chen Jianjun ; Zhang Suofei ; Wu Zhenyang ; An Guocheng
Source: 1st Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics, PrimeAsia 2009
Conference Name: 1st Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics, PrimeAsia 2009
Conference Date: 40848
Issued Date: 2009
Conference Place: Shanghai, China
Keyword: Algorithms ; Matrix algebra ; Microelectronics ; Pixels ; Targets ; Vector quantization
Publish Place: United States
Indexed Type: ei
ISBN: 9781424446698
Department: (1) School of Information Science and Engineering, Southeast University, Nanjing 210096, China; (2) Intelligence Engineering Lab., Institute of Software Chinese Academy of Sciences, Beijing 100190, China
Sponsorship: IEEE Circuits and Systems Society
English Abstract: We construct Kernel Co-occurrence Matrices (KCMs) to represent the target model and the target candidates. Then those matrices are employed as the tracking cues in mean shift framework. Some improvements are presented in the implementation of the algorithm. First, the angle relation between pixel-pairs is redefined to depict the asymmetric characteristic of the object. Second, the KCMs of the target model and the candidates are normalized to a same integer to increase calculation accuracy. Third, the computation of each pixel weight is modified to improve operation speed. The tracking results of several real world sequences with dark illumination or lighting variance show that the proposed algorithm can track the target effectively. ©2009 IEEE.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/8442
Appears in Collections:中科院软件所图书馆_2009年期刊/会议论文

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Recommended Citation:
Chen Jianjun,Zhang Suofei,Wu Zhenyang,et al. mean shift tracking with kernel co-occurrence matrices[C]. 见:1st Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics, PrimeAsia 2009. Shanghai, China. 40848.
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