SIA OpenIR  > 光电信息技术研究室
Moving Object Tracking via Hausdorff Distance and Particle Filter
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
会议录名称2005 International Conference on Intelligent Computing (ICIC’05)
2005
页码853-854
产权排序1
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.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/9721
专题光电信息技术研究室
通讯作者Wang JQ(王俊卿)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences
2.Graduate School of the Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Wang JQ,Shi ZL,Huang SB. Moving Object Tracking via Hausdorff Distance and Particle Filter[C],2005:853-854.
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