Supporting Historical Photo Identification with Face Recognition and Crowdsourced Human Expertise (Extended Abstract)
Supporting Historical Photo Identification with Face Recognition and Crowdsourced Human Expertise (Extended Abstract)
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DOI：
10.24963/ijcai.2020/660
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发表时间：
2020-07
期刊：
影响因子：
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通讯作者：
Vikram Mohanty;D. Thames;Sneha Mehta;Kurt Luther
中科院分区：
文献类型：
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作者：
Vikram Mohanty;D. Thames;Sneha Mehta;Kurt Luther
在历史照片中识别人物对于解释物质文化、纠正历史记录、创造经济价值具有重要意义，但这也是一项复杂而具有挑战性的任务。在本文中，我们着重于识别参加美国内战（1861-65）的士兵的肖像。数百万幅这样的肖像幸存下来，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面部识别来支持内战肖像识别。在Photo Sleuth公开发布一个月后，我们对其进行了混合方法评估，结果表明它帮助用户成功识别了未知的肖像。
Identifying people in historical photographs is important for interpreting 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). Millions 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.