| 基于UKF的窗口自适应Mean-Shift算法 |
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| 引用本文： | 杨帆,郑春红,杨刚.基于UKF的窗口自适应Mean-Shift算法[J].计算机工程,2011,37(14):158-160. |
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| 作者姓名： | 杨帆 郑春红 杨刚 |
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| 作者单位： | 西安电子科技大学电子工程学院,西安,710071 |
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| 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...
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| 关 键 词： | 目标跟踪 无味卡尔曼滤波器 Mean-Shift算法 信息度量 |
| 收稿时间： | 2011-01-03 |
Mean-Shift Algorithm with Adaptive Window Based on UKF |
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| YANG Fan,ZHENG Chun-hong,YANG Gang.Mean-Shift Algorithm with Adaptive Window Based on UKF[J].Computer Engineering,2011,37(14):158-160. |
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| Authors: | YANG Fan ZHENG Chun-hong YANG Gang |
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| Affiliation: | (School of Electronic Engineering,Xidian University,Xi’an 710071,China) |
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| Abstract: | 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. |
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| Keywords: | object tracking Unscented Kalman Filter（UKF） Mean-Shift algorithm information measure |
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