Photo Sleuth

Photo Sleuth
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照片侦探

DOI:
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发表时间:
2020
期刊:
ACM Trans. Interact. Intell. Syst.
影响因子:
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通讯作者:
K. Luther
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

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历史照片中人物的识别对于保存物质文化、纠正历史记录、创造经济价值具有重要意义,但也是一项复杂而富有挑战性的任务。在这篇文章中,我们将重点关注参加美国内战(1861- 65)的士兵的肖像,这是第一次广泛拍摄的冲突。成千上万的这些肖像幸存下来,但只有10%-20%被确认。我们创建了Photo Sleuth,这是一个基于网络的平台,结合了众包的人类专业知识和自动人脸识别,以支持内战肖像识别。我们对Photo Sleuth公开发布后的一个月和11个月进行的混合方法评估显示,它帮助用户成功识别未知肖像,并为志愿者贡献提供了可持续的模式。我们还讨论了对人群AI交互和人员识别管道的影响。
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: --
作者:
T. Causer;Melissa Mhairi Terras
通讯作者: T. Causer;Melissa Mhairi Terras
照片侦探:结合人类专业知识和人脸识别来识别历史肖像
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: --
作者:
Mohanty, Vikram;Thames, David;Mehta, Sneha;Luther, Kurt
通讯作者: Luther, Kurt