---
title: "Supporting Historical Photo Identification with Face Recognition and Crowdsourced Human Expertise (Extended Abstract)"
authors:
  - "Vikram Mohanty"
  - "David Thames"
  - "Sneha Mehta"
  - "Kurt Luther"
doi: "10.24963/ijcai.2020/660"
url: "https://ijcai.org/proceedings/2020/660"
pdf: "https://ijcai.org/proceedings/2020/0660.pdf"
venue: "Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence"
year: 2020
pages: "4755-4759"
track: "Sister Conferences Best Papers"
keywords:
  - "Computer Vision: Biometrics, Face and Gesture Recognition"
  - "Humans and AI: Human-Computer Interaction"
  - "Humans and AI: Human-AI Collaboration"
  - "Humans and AI: Human Computation and Crowdsourcing"
---

# 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*, pages 4755-4759. DOI: [10.24963/ijcai.2020/660](https://doi.org/10.24963/ijcai.2020/660)

## Abstract

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.