Abstract
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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Acknowledgment
We would like to thank Juan Chao and Dongyang Cheng for the fruitful technical discussion. We also show our appreciation to Yuxing Wu and Peisong He for their incredible patience in creating the forged video dataset. This work was supported by the National Science Foundation of China under Grants 61071153, 61170220, 61272249, and 61272439, the Specialized Research Fund for the Doctoral Program of Higher Education under Grant 20120073110053, and by the Project of International Cooperation and Exchanges supported by Shanghai Committee of Science and Technology under Grant 12510708500. Credits for the use of the TRECVID SED video dataset are given to the National Institute of Standards and Technology (NIST).
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Wang, W., Jiang, X., Wang, S., Wan, M., Sun, T. (2014). Identifying Video Forgery Process Using Optical Flow. In: Shi, Y., Kim, HJ., Pérez-González, F. (eds) Digital-Forensics and Watermarking. IWDW 2013. Lecture Notes in Computer Science(), vol 8389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43886-2_18
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DOI: https://doi.org/10.1007/978-3-662-43886-2_18
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