Method for Frame Removal Detection in Static Camera Surveillance Video

A. Bavrina
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Abstract

A method is proposed for passive protection of a surveillance camera video from a video fragment deletion attack. The method is based on the construction of local features for the samples of two consecutive frames, followed by a multilayer neural network classification. Post-processing and calculation of statistics based on the results of the classification make it possible to decide whether a given pair of frames is sequential or a number of frames were cut between them. Experiments show the efficiency of detecting the fact of a fragment removal even from stationary scenes, when such a deletion is visually imperceptible.
静态摄像机监控视频中帧移除检测方法
提出了一种被动保护监控摄像机视频免受视频片段删除攻击的方法。该方法基于对连续两帧的样本进行局部特征构建,然后进行多层神经网络分类。基于分类结果的后处理和统计计算使得确定给定的一对帧是连续的还是在它们之间剪切了许多帧成为可能。实验表明,即使从静止的场景中检测到片段删除的事实,当这种删除在视觉上是不可察觉的。
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