Totems: Verifying the Integrity of Visual Information using Neural Light Field

In this work, we introduce a new approach to image forensics: physically placing a totem into the scene before taking a photo that needs to be protected from manipulations. A totem is any reflective or refractive object such that when placed in a scene, it displays a distorted version of the scene, which is called a totem view. When an image contains a totem, an adversary needs to modify both the totem view and the rest of the image (camera view) in a geometrically consistent manner in order to not have the manipulation detected. We assume that the adversary does not have access to totem shape and index of refraction (IoR), so achieving this consistency would be extremely difficult. Our work focuses on designing such algorithms that detect inconsistencies between the totem view and camera view given totem shape and IoR. In contrast to prior learning-based approaches that require large datasets of manipulated images, our methods are physics-based and work on a single image.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Ma, Jingwei

Advisor dc:contributor.advisor

• Torralba, Antonio

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/139568

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/139568