在监控图像中检测可疑行为

Daniel Barbará, C. Domeniconi, Zoran Duric, M. Filippone, Richard Mansfield, E. Lawson
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引用次数: 16

摘要

我们介绍了一种新的图像异常检测技术。正态性的概念是由图像的基线给出的,假设这些图像中的大多数是正常的。我们方法的关键是基于表示每个图像所需的码字长度的图像的无特征概率表示。这样的码字长度然后用于基于统计测试的异常检测。我们的技术在合成数据集和真实数据集上进行了测试。结果表明,该方法可以实现高真阳性率和低假阳性率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting Suspicious Behavior in Surveillance Images
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.
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