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首页> 外文会议>2017 International Conference on Security, Pattern Analysis, and Cybernetics >An unsupervised abnormal crowd behavior detection algorithm
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An unsupervised abnormal crowd behavior detection algorithm

机译：一种无监督的异常人群行为检测算法

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摘要

In this paper, we propose a detection algorithm based on people counting for two special kinds of abnormal crowd behavior, gathering and dispersing. We use an efficient foreground segmentation algorithm for calculating the number of people, which uses an approximate median filter and double background model to obtain a reliable foreground. Further, counting people globally based on potential energy model in crowd scenes. In order to detecting unnormal crowd behavior happened, a crowd distribution curve is proposed, which combines results of counting and crowd entropy to evaluate the spatial distribution of throng, and describes the global distribution as a good feature. Experiments prove that our proposed method is able to detect the abnormal crowd behavior efficiently without camera calibration or supervised training.
机译：在本文中，我们提出了一种基于人员计数的检测算法，用于对两种特殊人群异常行为（聚集和分散）进行计数。我们使用高效的前景分割算法来计算人数，该算法使用近似中值滤波器和双重背景模型来获得可靠的前景。此外，根据人群场景中的潜在能量模型对全球人数进行计数。为了检测人群发生异常行为，提出了人群分布曲线，结合计数结果和人群熵评价人群的空间分布，并将全局分布描述为一个很好的特征。实验证明，我们提出的方法无需相机校准或监督训练就能有效地检测出异常人群行为。

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