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 paper, 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 evaluation of Photo Sleuth one month 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.
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CITATION STYLE
Mohanty, V., Mehta, S., Thames, D., & Luther, K. (2019). Photo Sleuth: Combining human expertise and face recognition to identify historical portraits. In International Conference on Intelligent User Interfaces, Proceedings IUI (Vol. Part F147615, pp. 547–557). Association for Computing Machinery. https://doi.org/10.1145/3301275.3302301
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