[1]张婷婷,于 明,阎 刚. 运动目标追踪的人工鱼群优化粒子滤波算法[J].河北工业大学学报,2016,(04):12-19.[doi:10.14081/j.cnki.hgdxb.2016.04.003]
 ZHANG Tingting,YU Ming,YAN Gang. Moving object tracking based on artificial fish particle filtering[J].Journal of Hebei University of Technology,2016,(04):12-19.[doi:10.14081/j.cnki.hgdxb.2016.04.003]
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 运动目标追踪的人工鱼群优化粒子滤波算法()
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《河北工业大学学报》[ISSN:1007-2373/CN:13-1208/T]

卷:
期数:
2016年04期
页码:
12-19
栏目:
出版日期:
2016-07-31

文章信息/Info

Title:
 Moving object tracking based on artificial fish particle filtering
作者:
 张婷婷于 明阎 刚
 河北工业大学 天津市电子材料与器件重点实验室,天津 300130
Author(s):
 ZHANG TingtingYU MingYAN Gang
 Tianjin Key Laboratory of Electronic Materials and Devices,Hebei University of Technology,Tianjin 300130,China
关键词:
 运动目标跟踪扩展卡尔曼粒子滤波人工鱼群颜色直方图
Keywords:
 moving object trackingextended kalman particle filteringartificial fishcolor histogram
DOI:
10.14081/j.cnki.hgdxb.2016.04.003
文献标志码:
A
摘要:
 为了进一步提高视频图像序列中的运动目标追踪精度,在扩展卡尔曼粒子滤波中引入人工鱼群算法,利用人工鱼群算法优化采样过程,使粒子不断朝高似然区域移动来寻找最优位置;然后对重采样过程优化,提高样本多样性,克服粒子样本贫化问题,提高对系统状态的预估精度;最后以颜色直方图特征描述运动目标,结合目标的运动特征建立游走模式的二阶自回归模型,以提高运动估计精度.对比标准粒子滤波(PF)、扩展卡尔曼粒子滤波(EKPF),人工鱼群优化扩展卡尔曼粒子滤波算法(AFSA-EKPF)能够将滤波结果均方误差的均值和方差分别降低至0.113 86和0.003 09 ,同时在追踪运动目标实验中,能够有效地消除目标遮挡所带来的影响.
Abstract:
 In order to improve the precision of moving object tracking in video image sequence,artificial fish algorithm is induced into extended Kalman particle filtering.The sampling process is optimized by artificial fish algorithm to find the optimal position by making the particle moving towards the highly likelihood region.Then re-sampling process is optimized to improve variety of particle,and overcome the dilution of particle to improve estimated accuracy of system state.Finally,two-order autoregressive model is constructed to improve the precision of moving object tracking by color histogram feature.Comparing with the standard particle filtering and extended Kalman particle filtering,experimental results based on artificial fish-extended Kalman particle filtering can produce highter precision,Mean and variance of MSE are reduced to 0.113 86 and 0.003 09 respectively.Influence of Target occlusion is reduced while tracking the moving object extremely.

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更新日期/Last Update: 2016-10-28