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中文摘要：
针对传统均值漂移跟踪算法在目标特征提取、模板匹配度量和带宽固定方面存在缺陷，提出一种双环Mean Shift视频跟踪算法．该算法采用万向椭圆的特征提取方式，能更有效地抑制背景信息影响，较好地提高目标模型质量．引入双环描述因子能突出目标本身特征权重，改善图像匹配峰值特性，并通过双环之间的关系自适应地更新核函数的带宽．仿真实验结果表明该算法在目标具有明显尺度变化、姿态扭曲和部分遮挡的情况下，可以获得准确和鲁棒的跟踪效果．
英文摘要：
A tracking algorithm based on double-ring Mean Shift is proposed to solve the deficiency of target representation, template similarity measure and fixed kernel-bandwidth in traditional Mean Shift tracking algorithm. The feature extraction model based on universal elliptical region is used to reduce the influence of background feature and improve the quality of target model effectively. Double-ring descriptor is presented to emphasize the importance of target feature and improve the peak modality of matching function. The proposed method updates the bandwidth of kernel-function adaptively by the relationship of double-ring. The experimental results show that the proposed tracking approach is robust and invariant to scale, pose and partial occlusions.
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An optimal symmetrical null space criterion of Fisher discriminant for feature extraction and recogn
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