# A PatchMatch-based Dense-field Algorithm for Video Copy-Move Detection and Localization

## TL;DR

This paper introduces a robust dense-field algorithm based on PatchMatch for detecting and localizing video copy-moves, effectively handling challenging scenarios with post-processing and occlusion.

## Contribution

It presents a novel PatchMatch-based dense-field approach with a multiresolution strategy for reliable video copy-move detection and localization.

## Key findings

- High accuracy in detecting copy-moves in challenging conditions
- Robustness to post-processing operations and occlusions
- Effective localization of manipulated regions

## Abstract

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.