Identifying Video Forgery Process Using Optical Flow

With the extensive equipment of surveillance systems, the assessment of the integrity of surveillance videos is of vital importance. In this paper, an algorithm based on optical flow and anomaly detection is proposed to authenticate digital videos and further identify the inter-frame forgery process (i.e. frame deletion, insertion, and duplication). This method relies on the fact that forgery operation will introduce discontinuity points to the optical flow variation sequence and these points show different characteristics depending on the type of forgery. The anomaly detection scheme is adopted to distinguish the discontinuity points. Experiments were performed on several real-world surveillance videos delicately forged by volunteers. The results show that the proposed algorithm is effective to identify forgery process with localization, and is robust to some degree of MPEG compression.

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