Recent advances in video generation have made AI-synthesized content increasingly difficult to distinguish from real footage. We propose a physics-based authentication signature that real cameras produce naturally, but that generative models cannot faithfully reproduce. Our approach exploits the Moiré effect: the interference fringes formed when a camera views a compact two-layer grating structure. We derive the Moiré motion invariant, showing that fringe phase and grating image displacement are linearly coupled by optical geometry, independent of viewing distance and grating structure. A verifier extracts both signals from video and tests their correlation. We validate the invariant on both real-captured and AI-generated videos from multiple state-of-the-art generators, and find that real and AI-generated videos produce significantly different correlation signatures, suggesting a robust means of differentiating them. Our work demonstrates that deterministic optical phenomena can serve as physically grounded, verifiable signatures against AI-generated video.

翻译：近期视频生成技术的进步使得AI合成内容与真实拍摄画面的区分日趋困难。我们提出一种基于物理的认证签名——该签名由真实相机自然产生，但生成模型无法准确复现。该方法利用莫尔效应：相机观测紧凑双层光栅结构时形成的干涉条纹。我们推导出莫尔运动不变性，证明条纹相位与光栅图像位移通过光学几何呈线性耦合关系，且此关系与观测距离及光栅结构无关。验证器可从视频中提取两种信号并检验其相关性。我们分别在真实拍摄视频与多种先进生成器生成的AI视频中验证了该不变性，发现真实视频与AI生成视频产生显著不同的相关性签名，表明该方法可有效区分两者。本研究证明确定性光学现象可作为基于物理的可验证签名，用于对抗AI生成视频。