We introduce a new approach to image forensics: placing physical refractive objects, which we call totems, into a scene so as to protect any photograph taken of that scene. Totems bend and redirect light rays, thus providing multiple, albeit distorted, views of the scene within a single image. A defender can use these distorted totem pixels to detect if an image has been manipulated. Our approach unscrambles the light rays passing through the totems by estimating their positions in the scene and using their known geometric and material properties. To verify a totem-protected image, we detect inconsistencies between the scene reconstructed from totem viewpoints and the scene's appearance from the camera viewpoint. Such an approach makes the adversarial manipulation task more difficult, as the adversary must modify both the totem and image pixels in a geometrically consistent manner without knowing the physical properties of the totem. Unlike prior learning-based approaches, our method does not require training on datasets of specific manipulations, and instead uses physical properties of the scene and camera to solve the forensics problem.
@article{arxiv.2209.13032,
title = {Totems: Physical Objects for Verifying Visual Integrity},
author = {Jingwei Ma and Lucy Chai and Minyoung Huh and Tongzhou Wang and Ser-Nam Lim and Phillip Isola and Antonio Torralba},
journal= {arXiv preprint arXiv:2209.13032},
year = {2022}
}
Comments
ECCV 2022 camera ready version; project page https://jingweim.github.io/totems/