Modeling Temporal Effects in Re-captured Video

The re-capturing of video content poses significant challenges to algorithms in the fields of video forensics, watermarking, and near-duplicate detection. Using a camera to record a video from a display introduces a variety of artifacts, such as geometric distortions, luminance transformations, and temporal aliasing. A deep understanding of the causes and effects of such phenomena is required for their simulation, and for making the affected algorithms more robust. In this paper, we provide a detailed model of the temporal effects in re-captured video. Such effects typically result in the re-captured frames being a blend of the original video's source frames, where the specific blend ratios are difficult to predict. Our proposed parametric model captures the temporal artifacts introduced by interactions between the video renderer, display device, and camera. The validity of our model is demonstrated through experiments with real re-captured videos containing specially marked frames.

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