Photo sleuth: combining human expertise and face recognition to identify historical portraits

Photo sleuth: combining human expertise and face recognition to identify historical portraits
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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
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发表时间:
2019
期刊:
Proceedings of the 24th ACM Conference on Intelligent User Interfaces (IUI ’19
影响因子:
--
通讯作者:
Luther, Kurt
Luther, Kurt
中科院分区:
--
文献类型:
--
作者:
Mohanty, Vikram;Thames, David;Mehta, Sneha;Luther, Kurt

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在历史照片中辨认人物对于保存物质文化、纠正历史记录、创造经济价值具有重要意义,但也是一项复杂而具有挑战性的任务。在这篇文章中,我们专注于识别参加美国内战(1861-65年)的士兵的肖像,这是第一次被广泛拍摄的冲突。数以千计的这样的肖像画幸存下来,但只有10%-20%被识别出来。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公开发布一个月后的混合方法评估表明,它帮助用户成功识别未知肖像,并为志愿者贡献提供了一个可持续的模式。我们还讨论了人群-人工智能交互和个人识别管道的含义。
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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