基于UKF的窗口自适应Mean-Shift算法  

Mean-Shift Algorithm with Adaptive Window Based on UKF

作　　者：杨帆[1] 郑春红[1] 杨刚[1] 

机构地区：[1]西安电子科技大学电子工程学院,西安710071

出　　处：《计算机工程》2011年第14期158-160,共3页Computer Engineering

摘　　要：传统的Mean-Shift跟踪算法窗口固定,不能对尺度任意变化的目标进行有效跟踪。为此,提出一种多尺度理论与无味卡尔曼滤波器(UKF)相结合的视频跟踪改进算法。利用多尺度理论统计跟踪窗内的信息量,使用UKF对得到的信息量进行预测,通过修正后的信息量计算窗口变化比例系数,对尺度任意变化的目标进行跟踪。实验结果证明,该算法能对尺度任意变换的目标进行有效跟踪。The traditional fixed bandwidth Mean-Shift tracking algorithm can not have an effective tracking for any changes in targets.An novel method is proposed that is multi-scale space theory combined with Unscented Kalman Filter（UKF）.UKF filter is introduced to predict the information in the tracking window which is calculated by the multi-scale space theory.The proportion of the target image area is got by the modified information.It is implemented by the combination of the Mean-Shift tracking algorithm and UKF to track targets.Experimental result confirms the effectiveness of the improved algorithm.

关 键 词：目标跟踪 无味卡尔曼滤波器 MEAN-SHIFT算法 信息度量 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]