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)
Department光电信息研究室
Conference Name2005 International Conference on Intelligent Computing (ICIC’05)
Conference DateAugust 23-26, 2005
Conference PlaceHefei, China
Source Publication2005 International Conference on Intelligent Computing (ICIC’05)
2005
Pages853-854
Contribution Rank1
AbstractMoving 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.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/9721
Collection光电信息技术研究室
Corresponding AuthorWang JQ(王俊卿)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences
2.Graduate School of the Chinese Academy of Sciences
Recommended Citation
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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