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

作　　者：李权[1,2] 赵勋杰[1] 彭青艳[1] 邹薇[1] 张雪松[2] 

机构地区：[1]苏州大学物理科学与技术学院,江苏苏州215006 [2]光电信息控制和安全技术重点实验室,河北燕郊065201

出　　处：《红外与激光工程》2014年第10期3474-3479,共6页Infrared and Laser Engineering

基　　金：江苏省高校自然科学基金(BK2009116);国防科技重点实验室基金

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。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.

关 键 词：粒子滤波 主成分分析法 协方差矩阵 特征值 自适应窗口 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]