We propose a new algorithm for the reliable detection and localization of
video copy-move forgeries. Discovering well crafted video copy-moves may be
very difficult, especially when some uniform background is copied to occlude
foreground objects. To reliably detect both additive and occlusive copy-moves
we use a dense-field approach, with invariant features that guarantee
robustness to several post-processing operations. To limit complexity, a
suitable video-oriented version of PatchMatch is used, with a multiresolution
search strategy, and a focus on volumes of interest. Performance assessment
relies on a new dataset, designed ad hoc, with realistic copy-moves and a wide
variety of challenging situations. Experimental results show the proposed
method to detect and localize video copy-moves with good accuracy even in
adverse conditions.

提出了一种新的用于可靠检测和定位视频剪贴 - 移动伪造的算法，该算法使用密集场方法，并具有针对后处理操作的鲁棒性，通过一个专门设计的新数据集的实验结果表明，在各种具有挑战性的情况下，该方法能够准确地检测和定位视频剪贴 - 移动伪造。