Noise-Coded Illumination for Forensic and Photometric Video Analysis

TL;DR

This paper introduces a noise-coded illumination technique that embeds a temporal watermark into videos, aiding in the detection of manipulated content by creating an information asymmetry favoring verification.

Contribution

It proposes a novel method of embedding a scene image as a temporal watermark through subtle illumination modulations to improve video authenticity verification.

Findings

Effective in embedding scene images as watermarks

Increases difficulty for adversaries to create plausible fake videos

Enhances verification in high-stakes video scenarios

Abstract

The proliferation of advanced tools for manipulating video has led to an arms race, pitting those who wish to sow disinformation against those who want to detect and expose it. Unfortunately, time favors the ill-intentioned in this race, with fake videos growing increasingly difficult to distinguish from real ones. At the root of this trend is a fundamental advantage held by those manipulating media: equal access to a distribution of what we consider authentic (i.e., "natural") video. In this paper, we show how coding very subtle, noise-like modulations into the illumination of a scene can help combat this advantage by creating an information asymmetry that favors verification. Our approach effectively adds a temporal watermark to any video recorded under coded illumination. However, rather than encoding a specific message, this watermark encodes an image of the unmanipulated scene as it would appear lit only by the coded illumination. We show that even when an adversary knows that our technique is being used, creating a plausible coded fake video amounts to solving a second, more difficult version of the original adversarial content creation problem at an information disadvantage. This is a promising avenue for protecting high-stakes settings like public events and interviews, where the content on display is a likely target for manipulation, and while the illumination can be controlled, the cameras capturing video cannot.