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基于卡尔曼滤波器组的MeanShift模板更新算法

DOI: 10.11834/jig.20070314

Keywords: MeanShift算法,卡尔曼滤波器,模板更新

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Abstract:

针对MeanShift算法缺乏必要的模板更新方法的缺陷,提出了一种基于卡尔曼滤波器组的MeanShift模板更新算法。该算法首先将目标在特征空间中的特征值的概率作为模板信息;然后设计了一个滤波器组,其中每个滤波器用于估计特征子空间中一个子特征值概率的变化;最后将这些子特征值概率对应相乘就可以得到整个模板的更新值。由于滤波器的噪声参数是随着输入数据的变化随时动态确定的,因此,根据滤波器残差的变化就可以确定模板的更新策略。实验证明,该新算法不仅能够增强MeanShift算法在目标姿态变化、光照变化下的跟踪效果,而且对阻挡时的鲁棒性也较好。

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