【摘要】 结合灰色预测模型和粒子滤波,提出一种新的视觉目标跟踪算法.由于粒子滤波未考虑先验信息对建议分布产生的指导作用,不能很好地逼近后验概率分布,对此,采用历史状态估计序列作为先验信息,建立该序列的灰色预测模型来预测产生建议分布.与粒子滤波、卡尔曼粒子滤波和无迹粒子滤波进行对比实验,结果表明所提出的算法在视觉目标跟踪中具有更好的性能.更多还原

【Abstract】 In this paper,a visual tracking algorithm is proposed by combining particle filter with grey prediction model.Particle filter does not take into account the guidance of historical prior on the generation of proposal distribution,so that it can not approximate posterior density well.Therefore,the history of state estimation sequence is utilized as prior information to set up grey prediction model for predicting and generating proposal distribution.Through the comparison to particle filter,Kalman particle filter and unscented particle filter,the proposed algorithm exhibits better performance in visual tracking.更多还原