[1]王绍钰 蔡自兴,陈爱斌.改进的粒子滤波器目标跟踪方法[J].智能系统学报,2008,3(3):189-194.
WANG Shao-yu,CAI Zi-xing,CHEN Ai-bin.Improved object tracking method for particle filters[J].CAAI Transactions on Intelligent Systems,2008,3(3):189-194.
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WANG Shao-yu,CAI Zi-xing,CHEN Ai-bin.Improved object tracking method for particle filters[J].CAAI Transactions on Intelligent Systems,2008,3(3):189-194.
改进的粒子滤波器目标跟踪方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
3
期数:
2008年第3期
页码:
189-194
栏目:
学术论文—智能系统
出版日期:
2008-06-25
- Title:
- Improved object tracking method for particle filters
- 文章编号:
- 1673-4785(2008)03-0189-06
- Keywords:
- object tracking; particle filtering; Euclidian distance; histogram
- 分类号:
- TP242
- 文献标志码:
- A
- 摘要:
- 针对现有的粒子滤波跟踪方法存在的不足,提出了一种改进的粒子滤波器方法用于运动目标跟踪.将颜色直方图和边缘直方图结合起来建立目标的参考模型,有效地克服了使用单一特征建模的缺点,提高了跟踪的准确性.分别计算目标颜色模型和目标边缘模型与粒子的欧几里德距离,使用这2个距离作为粒子权值计算的重要依据.实验结果表明该算法具有较高的实时性、准确性和鲁棒性.
- Abstract:
- The op timal design of stack filters is actually an op timization of a positive Boolean function. In order to speed up the op timizing rate and p roduce a global op timal design of the stack filters, an imp roved clonal selection algorithm ( ICSA) is p resented, which introduces a polyclonal operator and simultaneous evolution of the memory u2 nit and the reserved group. The number of clonal particles in the memory unit can adap tively change with their af2 finity concentration. Regroup ing operations are made between parent generations and child generations in the mem2 ory unit, avoiding p roblems caused by breeding two close particles. The p reservation of group mutations guarantees diversity. Our experimental results confirmed that stack filters op timized with ICSA p roduce better filtering results in less time.
- 参考文献/References:
-
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[3] 庄严,战洪斌,王伟,王珂. 基于加权颜色直方图和粒子滤波的彩色物体跟踪[J]控制与决策, 2006,(08) .
[4] Paul Viola,MichaelJ.Jones. Robust Real-Time Face Detection[J] International Journal of Computer Vision, 2004,57, (2) :137~154.
[5] Ying Wu,ThomasS.Huang. Robust Visual Tracking by Integrating Multiple Cues Based on Co-Inference Learning[J] International Journal of Computer Vision, 2004,58, (1) :55~71.
[6] Yil maz A,Javed O,Shah M. Object Tracking:A Survey .ACM Computing surveys, 2006,38, 38 (4) :1~45 .
[7] YING W,HUANG TS. Robust Visual Tracking by Integrating Mul-tiple Cues Based on Co-Inference Learning .International Journa of Computer Vision. 2004,581, 58(1) :55-71 .
[8] YANG C J,DURAISWAMI R,DAVIS L. Fast multiple ob-ject tracking via a hierarchical particle filter[C] .Proceed-ings of the Tenth IEEE International Conference on Comput-er Vision. Beijing,China. 2005, :212-219 .
[9] VIOLA P,JONES M J. Robust real-time face detection[J] .International Journal of Computer Vision, 2004,52, 52 (2) :137-154 .
[10] NUMMIAROK,KOLLER M E,VAN G L. Object tracking with an adaptive color-based particle filter[C] .Proc of the Symposium for Pattern Recognition of the DAGM. Switzer-land. 2002, :353-360 .
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备注/Memo
收稿日期：2007-12-10
基金项目：国家基础科学研究基金资助项目(A1420060159)
作者简介：
王绍钰 男 ，1982年生，硕士研究生，主要研究方向为视频图像处理，目标跟踪。
蔡自兴 男， 1938年生，教授，博士生导师，主要研究方向为人工智能，机器人等。获科技奖励30多项，其中国家级奖励2项，省部级奖励20多项，已在国内外发表论文550余篇，出版专著和材料共26部。
陈爱斌 男，1971年生，博士研究生，主要研究方向为多机器人目标跟踪。
更新日期/Last Update:
2009-05-11