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基于均值变换的ParticleFilter实时跟踪算法

, PP. 825-830

Keywords: 图像跟踪,均值变换,粒子滤波,实时跟踪

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Abstract:

提出一种基于均值变换(MeanShift)的ParticleFilter图像跟踪算法.算法将目标的状态空间分解为位移子空间和形变子空间.使用均值变换算法跟踪位移子空间变化,获得目标的位置信息.在此基础上使用ParticleFilter跟踪形变子空间变化和补偿均值变换的跟踪误差,由于均值变换算法跟踪的信息使ParticleFilter跟踪的位移子空间大大缩小,减少ParticleFilter所需要的样本数,使ParticleFilter的实时性能提高,而ParticleFilter获得的形状信息补偿了均值变换算法对于形状跟踪的误差.该算法比标准的ParticleFilter算法具有更高的效率,并拥有均值变换算法所不具备的形状跟踪能力.实验结果证明算法的有效性和快速性.

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