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嵌入卡尔曼预测器的粒子滤波目标跟踪算法


摘 要:针对经典的粒子滤波视频目标跟踪算法进行粒子传播采用随机游走的方式,以及传统颜色直方图无法反映目标空间特征的问题,提出了一种改进的基于颜色的粒子滤波目标跟踪算法。该算法在统计目标二阶颜色直方图的基础上,获得粒子的观察概率密度函数,利用卡尔曼滤波确定粒子动态传播模型中的确定性漂移部分,使粒子状态估计值分布更精确地趋向目标的概率分布,大大提高了粒子的利用效率。实验表明,该改进算法的性能优于经典基于单一颜色特征的粒子滤波算法。
  关键词:颜色直方图; 粒子滤波; 卡尔曼预测; 目标跟踪
  中图分类号:TP309
  文献标志码:A
  
  文章编号:1001-3695(2010)02-0468-04
  doi:10.3969/j.issn.1001-3695.2010.02.017
  
  Particle filter and embedded in Kalman predictor for target tracking
  
  WANG Yue-ling, WANG Rang-ding
  
  (CKC Software Laboratory, Ningbo University, Ningbo Zhejiang 315211, China)
  
  Abstract:The standard color particle filter spreads each particle with random walk method for target tracking. The traditional color histogram is used that can not reflect the characteristics of the target space. This paper proposed a novel color-based particle filter target tracking algorithms. The second-order color histogram was applied to get the observation of particle probability density function. In addition, used the Kalman filter to determine the spread of particle dynamic model of the uncertainty in the drift of the state. The distribution of particles was more accurately close to the probability distribution of the target, thus the use efficiency of particles was greatly improved. Computer simulation results demonstrate that the proposed algorithm is more robust as compare to the traditional color-based particle filter tracking algorithm. ......
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