Supporting Historical Photo Identification with Face Recognition and Crowdsourced Human Expertise (Extended Abstract)

Supporting Historical Photo Identification with Face Recognition and Crowdsourced Human Expertise (Extended Abstract)

Vikram Mohanty, David Thames, Sneha Mehta, Kurt Luther

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Sister Conferences Best Papers. Pages 4755-4759. https://doi.org/10.24963/ijcai.2020/660

Identifying people in historical photographs is important for interpreting material culture, correcting the historical record, and creating economic value, but it is also a complex and challenging task. In this paper, we focus on identifying portraits of soldiers who participated in the American Civil War (1861-65). Millions of these portraits survive, but only 10-20% are identified. We created Photo Sleuth, a web-based platform that combines crowdsourced human expertise and automated face recognition to support Civil War portrait identification. Our mixed-methods evaluation of Photo Sleuth one month after its public launch showed that it helped users successfully identify unknown portraits.
Keywords:
Humans and AI: Human-AI Collaboration
Humans and AI: Human-Computer Interaction
Humans and AI: Human Computation and Crowdsourcing
Computer Vision: Biometrics, Face and Gesture Recognition