李权, 赵勋杰, 彭青艳, 邹薇, 张雪松. 基于主成分分析法的窗口自适应粒子滤波算法[J]. 红外与激光工程, 2014, 43(10): 3474-3479.
引用本文: 李权, 赵勋杰, 彭青艳, 邹薇, 张雪松. 基于主成分分析法的窗口自适应粒子滤波算法[J]. 红外与激光工程, 2014, 43(10): 3474-3479.
Li Quan, Zhao Xunjie, Peng Qingyan, Zou Wei, Zhang Xuesong. Windows adaptive particle filter algorithm based on principal component analysis[J]. Infrared and Laser Engineering, 2014, 43(10): 3474-3479.
Citation: Li Quan, Zhao Xunjie, Peng Qingyan, Zou Wei, Zhang Xuesong. Windows adaptive particle filter algorithm based on principal component analysis[J]. Infrared and Laser Engineering, 2014, 43(10): 3474-3479.

基于主成分分析法的窗口自适应粒子滤波算法

Windows adaptive particle filter algorithm based on principal component analysis

  • 摘要: 传统的窗口固定的粒子滤波跟踪算法在运动目标尺度发生明显变化时不能有效地跟踪目标。针对这一问题,提出了一种跟踪窗口尺寸和方向自适应变化的粒子滤波跟踪方法。该方法将主成分分析法引入到粒子滤波框架中,通过分析目标区域内像素值的协方差矩阵得到包含目标区域取向和尺寸信息的椭圆跟踪窗口。实验结果表明,该跟踪算法能自适应于目标区域形状的变化,在目标尺寸和方向发生变化时能很好地跟踪和确定目标区域。

     

    Abstract: An adaptive bandwidth object tracking method based on particle filter was proposed. Classic Particle Filter based tracking algorithm uses fixed kernel-bandwidth, as the scale changes obviously, the target may not be tracked effectively. So the principal component analysis method was introduced into the particle filtering framework to analysis the covariance matrix of the pixels within the target region. Then the most ideal tracking window including target direction and scale can be calculated. The experimental results show that the method can be adaptive to the variation of local structure of the target, moreover, spatial location and scale are good.

     

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