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题名: Target tracking based on non-linear kernel density estimation and Kalman filter
作者: Wu Y(吴阳); Zhou XF(周晓锋); Zhang YC(张宜弛)
作者部门: 数字工厂研究室
会议名称: 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
会议日期: June 8-12, 2015
会议地点: Shenyang, China
会议录: 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
会议录出版者: IEEE
会议录出版地: Piscataway, NJ, USA
出版日期: 2015
页码: 462-466
收录类别: EI ; CPCI(ISTP)
ISSN号: 2379-7711
ISBN号: 978-1-4799-8730-6
关键词: target tracking ; non-linear kernel density estimation ; Mean Shift ; Kalman filter
摘要: This paper chooses Mean Shift algorithm to track target based on non-linear kernel density estimation and Kalman filter. Kernel density estimation is a probability density estimation method, which is used to detect moving target and update the target color histogram. The interest targets are obtained by labeling connected region in the detected binary image. Kalman filtering is employed to predict the position of the target being tracked, giving a starting searching window for Mean Shift tracking. Experimental results show that the method proposed is effective and fast in implementation, which satisfies the real-time requirement, it is capable of handling occlusion problem, meanwhile it is robust against the effects of unstable scene illumination.
语种: 英语
产权排序: 2
WOS记录号: WOS:000380502300089
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/18529
Appears in Collections:数字工厂研究室_会议论文

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Recommended Citation:
Wu Y,Zhou XF,Zhang YC. Target tracking based on non-linear kernel density estimation and Kalman filter[C]. 见:2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). Shenyang, China. June 8-12, 2015.
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