Photo Sleuth
Photo Sleuth
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照片侦探
DOI:
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发表时间:
2020
期刊:
影响因子:
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通讯作者:
K. Luther
中科院分区:
文献类型:
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作者:
V. Mohanty;D. Thames;Sneha Mehta;K. Luther
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.
DOI:
10.3366/ijhac.2014.0119
发表时间:
2014-04
期刊:
Int. J. Humanit. Arts Comput.
影响因子:
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作者:
T. Causer;Melissa Mhairi Terras
通讯作者:
T. Causer;Melissa Mhairi Terras
DOI:
10.1145/3301275.3302301
发表时间:
2019
期刊:
Proceedings of the 24th ACM Conference on Intelligent User Interfaces (IUI ’19
影响因子:
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作者:
Mohanty, Vikram;Thames, David;Mehta, Sneha;Luther, Kurt
通讯作者:
Luther, Kurt