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题名: Moving Object Tracking via Hausdorff Distance and Particle Filter
作者: Wang JQ(王俊卿) ; Shi ZL(史泽林) ; Huang SB(黄莎白)
作者部门: 光电信息研究室
会议名称: 2005 International Conference on Intelligent Computing (ICIC’05)
会议日期: August 23-26, 2005
会议地点: Hefei, China
会议录: 2005 International Conference on Intelligent Computing (ICIC’05)
出版日期: 2005
页码: 853-854
摘要: Moving object tracking is widely applied in computer vision. A novel method for moving object tracking, which utilizes particle filter and Hausdorff distance is proposed in this paper. This algorithm consists of system model, measure model, the strategy of template update with adaptive tracking window and solution to occlusion in the particle filter framework. In system model, Hausdorff distance and edge information of target are applied to improve the robustness against variation of rotation, scale, translation and illumination of target. In measure model, this new similarity metric defined based on gray histogram not only enhances tracking fault-tolerant property, but its computational cost has also been greatly reduced. The strategy of update template of adaptive tracking window and solution to occlusion makes tracking more stable and robust. The experimental results also illustrate that this algorithm is stable and efficient to track deformable objects in image sequences.
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内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/9721
Appears in Collections:光电信息技术研究室_会议论文

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Recommended Citation:
王俊卿; 史泽林; 黄莎白.Moving Object Tracking via Hausdorff Distance and Particle Filter.见:.2005 International Conference on Intelligent Computing (ICIC’05),,2005,853-854
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