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基于最大互信息区域跟踪的人体行为检测算法

DOI: 10.3724/SP.J.1004.2012.02023, PP. 2023-2031

Keywords: 行为检测,行为识别,随机森林,稠密轨迹,互信息

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Abstract:

?人体行为检测问题不仅需要判断行为的类别,而且需要估计行为发生的时间和位置,有重要的现实应用意义.人体行为检测的主要难点在于参数空间维度高以及背景运动干扰.针对上述难点,本文提出了一种基于最大互信息区域跟踪的人体行为检测算法.该算法将行为区域定义为最大互信息矩形区域,采用稠密轨迹作为底层特征,利用随机森林学习轨迹特征与行为类别的互信息函数,利用轨迹的时间连续性对行为区域进行大时间跨度的预测和跟踪.实验结果表明,该算法不仅能够有效地识别不同类别的行为,而且能够适应现实场景中背景运动的干扰,从而准确地检测和跟踪行为区域.

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