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An improved Mean-shift tracking algorithm based on
color and texture feature |
DAI Yuan-ming, WEI Wei, LIN Yi-ning |
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China |
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Abstract Aimed at the defect of classic Mean-shift tracking algorithm which is vulnerable to similar background inference for using single color feature, an improved color and texture features combined Mean-shift tracking algorithm is presented. Feature joint similarity was introduced for the first time. By maximizing the integrated similarity using Mean-shift algorithm the center of target in the new frame can be obtained accurately and rapidly. Experiments show that the proposed algorithm provides more reliable performance while satisfying the real-time requirements of general target tracking tasks.
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Published: 20 March 2012
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基于颜色纹理特征的均值漂移目标跟踪算法
针对经典均值漂移跟踪算法采用单一的颜色特征对目标进行跟踪检测存在的不足,提出一种将纹理特征与颜色特征相结合的改进均值漂移目标跟踪算法.该算法首次提出特征联合相似度的概念,通过均值漂移算法联合相似度的最大化计算,正确快速地获取新一帧图像跟踪目标的位置.实验结果表明,该算法具有更高的可靠性,同时满足一般目标跟踪任务的实时性要求.
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