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Detecting Suspicious Behavior in Surveillance Images

机译:检测监视图像中的可疑行为

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摘要

We introduce a novel technique to detect anomalies in images. The notion of normalcy is given by a baseline of images, under the assumption that the majority of such images is normal. The key of our approach is a featureless probabilistic representation of images, based on the length of the codeword necessary to represent each image. Such codeword's lengths are then used for anomaly detection based on statistical testing. Our techniques were tested on synthetic and real data sets. The results show that our approach can achieve high true positive and low false positive rates.
机译:我们介绍了一种新颖的技术来检测图像中的异常。在大多数此类图像是正常的假设下,正常性的概念由图像的基线给出。我们的方法的关键是基于表示每个图像所需的代码字的长度,对图像进行无特征的概率表示。然后,基于统计测试,将此类码字的长度用于异常检测。我们的技术已在综合和真实数据集上进行了测试。结果表明,我们的方法可以实现较高的真实阳性率和较低的假阳性率。

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