TraffickCam: Explainable Image Matching For Sex Trafficking Investigations

TL;DR

This paper presents TraffickCam, an explainable image matching system designed to assist law enforcement in sex trafficking investigations by improving accuracy, providing visual explanations, and supporting result exportation.

Contribution

The paper introduces an end-to-end image matching system with enhanced performance, explainability features, and infrastructure for exporting results tailored for law enforcement needs.

Findings

Improved image matching accuracy for hotel room photographs

Visualization methods that highlight image regions influencing matches

Infrastructure enabling export of query results for investigations

Abstract

Investigations of sex trafficking sometimes have access to photographs of victims in hotel rooms. These images directly link victims to places, which can help verify where victims have been trafficked or where traffickers might operate in the future. Current machine learning approaches give promising results in image search to find the matching hotel. This paper explores approaches to make this end-to-end system better support government and law enforcement requirements, including improved performance, visualization approaches that explain what parts of the image led to a match, and infrastructure to support exporting the results of a query.