计算机科学
人工智能
计算机视觉
帧(网络)
对象(语法)
视频跟踪
鉴定(生物学)
运动补偿
目标检测
探测器
特征(语言学)
视频压缩图片类型
块匹配算法
隐写分析技术
特征提取
模式识别(心理学)
图像(数学)
隐写术
语言学
电信
哲学
植物
生物
作者
Shengda Chen,Shunquan Tan,Bin Li,Jiwu Huang
标识
DOI:10.1109/tcsvt.2015.2473436
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.
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