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基于局部背景感知的目标跟踪

DOI: 10.3724/SP.J.1004.2012.01985, PP. 1985-1995

Keywords: 目标跟踪,带权点集,K近邻,均值漂移

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Abstract:

?经典视觉跟踪方法通常仅以目标区域内信息作为目标描述.实际中,目标局部背景信息也影响着跟踪性能.本文首先在目标描述中引入局部背景信息,并将目标表示为一带权点集.然后通过K近邻计算目标观测概率,并联合目标先验信息得到搜索区域内各点后验概率值.最后,利用均值漂移(Meanshift)算法估计目标状态.本文算法优点如下:1)目标描述中联合局部背景信息,增强了目标模型.因此,跟踪过程中提高了目标与背景的区分能力,并进一步使跟踪算法更加稳定,跟踪结果更加精准.2)目标初始化时,利用Meanshift对目标进行一次重定位.由此解决了不精确初始化时跟踪算法容易失效的问题.在不同视频上进行了定性和定量的实验验证.结果表明本文算法具有较高的跟踪稳定性和准确性,尤其当目标初始化比较粗糙时.

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