Affiliation:
1. Virginia Tech, Arlington, VA, USA
2. Virginia Tech and Google, Seattle, WA, USA
Abstract
Identifying people in historical photographs is important for preserving material culture, correcting the historical record, and creating economic value, but it is also a complex and challenging task. In this article, we focus on identifying portraits of soldiers who participated in the American Civil War (1861--65), the first widely photographed conflict. Many thousands 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 evaluations of Photo Sleuth one month and 11 months after its public launch showed that it helped users successfully identify unknown portraits and provided a sustainable model for volunteer contribution. We also discuss implications for crowd-AI interaction and person identification pipelines.
Funder
NSF
Virginia Tech ICTAS Junior Faculty Award
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Human-Computer Interaction
Reference86 articles.
1. 1860. Liljenquist Family Collection of Civil War Photographs—About this Collection. Retrieved from www.loc.gov/pictures/collection/lilj/. 1860. Liljenquist Family Collection of Civil War Photographs—About this Collection. Retrieved from www.loc.gov/pictures/collection/lilj/.
2. Amazon. 2018. Amazon Rekognition Customers—Amazon Web Services (AWS). Retrieved from https://aws.amazon.com/rekognition/customers/. Amazon. 2018. Amazon Rekognition Customers—Amazon Web Services (AWS). Retrieved from https://aws.amazon.com/rekognition/customers/.
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