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Automatic Detection of Object-Based Forgery in Advanced Video

机译:自动检测高级视频中基于对象的伪造

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摘要

Passive multimedia forensics has become an active topic in recent years. However, less attention has been paid to video forensics. Research on video forensics, and especially on automatic detection of object-based video forgery, is still in its infancy. In this paper, we develop an approach for automatic identification and forged segment localization of object-based forged video encoded with advanced frameworks. The proposed approach starts with a frame manipulation detector. An automatic algorithm is proposed to identify object-based video forgery based on the frame manipulation detector. Then, a two-stage automatic algorithm is provided to accurately locate the forged video segments in the suspicious video. To construct the proposed frame manipulation detector, motion residuals are generated from the target video frame sequence. We regard the object-based forgery in video frames as image tampering in the motion residuals and employ the feature extractors that are originally built for still image steganalysis to extract forensic features from the motion residuals. The experiments show that the proposed approach achieves excellent results in both forged video identification and automatic forged temporal segment localization.
机译:近年来,被动多媒体取证已经成为一个活跃的话题。但是,对视频取证的关注较少。关于视频取证的研究,尤其是基于对象的视频伪造的自动检测的研究仍处于起步阶段。在本文中,我们开发了一种方法,用于使用高级框架对基于对象的伪造视频进行自动识别和伪造片段定位。所提出的方法从帧操纵检测器开始。提出了一种基于帧操作检测器的基于对象的视频伪造识别算法。然后,提供了两阶段自动算法来准确定位可疑视频中的伪造视频片段。为了构造所提出的帧操纵检测器,从目标视频帧序列中产生运动残差。我们将视频帧中的基于对象的伪造视为运动残差中的图像篡改,并采用最初为静止图像隐写分析而构建的特征提取器,以从运动残差中提取法医特征。实验表明,该方法在伪造视频识别和伪造时间段自动定位方面均取得了优异的效果。

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