| 引用本文: | 邱雪娜,刘士荣,吕强.基于信息分享机制的粒子滤波算法及其在视觉跟踪中的应用[J].控制理论与应用,2010,27(12):1724~1730.[点击复制] |
| QIU Xue-na,LIU Shi-rong,LV Qiang.Particle filter algorithm based on information-shared mechanism and its application to visual tracking[J].Control Theory and Technology,2010,27(12):1724~1730.[点击复制] |
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| 基于信息分享机制的粒子滤波算法及其在视觉跟踪中的应用 |
| Particle filter algorithm based on information-shared mechanism and its application to visual tracking |
| 摘要点击 1537 全文点击 1008 投稿时间：2010-05-05 修订日期：2010-07-16 |
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| DOI编号 10.7641/j.issn.1000-8152.2010.12.PCTA100492 |
| 2010,27(12):1724-1730 |
| 中文关键词 粒子滤波 信息分享机制 视觉跟踪 多目标跟踪 |
| 英文关键词 particle filter information-shared mechanism visual tracking multi-object tracking |
| 基金项目 国家自然科学基金资助项目(60675043); 浙江省科技计划资助项目(2007C21051, 2009C33045); 浙江省宁波市自然科学基金资助项目(2008A610002); 浙江省教育厅科研资助项目(Y200803228); 浙江省自然科学基金资助项目(Y1090426). |
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| 中文摘要 |
| 针对基本粒子滤波方法存在的权值退化和计算效率低问题, 提出了一种基于信息分享机制的粒子滤波算法. 该方法将粒子群优化算法和蚁群优化算法的优化思想共同作用到粒子更新中, 实现粒子之间信息共享, 从而增强粒子的多样性和最优估计能力. 同时分析了该算法的收敛性. 视觉跟踪实验表明, 该算法能用较少的粒子实现单目标和多目标跟踪, 综合跟踪性能优于基本粒子滤波和基于粒子群优化的粒子滤波方法, 验证了本算法的有效性. |
| 英文摘要 |
| To deal with the weight-degeneracy and computation efficiency in particle filter, we propose a novel particle filter algorithm based on the information-shared mechanism. This method combines particle swarm optimization and ant colony optimization to update particles to fully share the population information. The particles diversity is recovered and the estimation precision is improved. The convergence of this algorithm is analyzed. Visual tracking experiments show that the proposed algorithm realizes both single-object tracking and multi-object tracking with fewer particles and better comprehensive tracking-performance than classic particle filters and the particle filter based on particle-swarm optimization. |