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The goal of this research project was to determine the most effective facial recognition applications that could be implemented into digital archive image collections from libraries, museums, and cultural heritage institutions. Computer scientists and librarians at Florida International University collaborated to conduct qualitative assessments of both face detection and face search using photographs from FIU’s digital collections. Specifically, the facial recognition platforms OpenCV, Face++, and Amazon AWS were analyzed. This project seeks to assist LYRASIS community members who wish to incorporate facial recognition and other artificial intelligence technology into their digital collections and repositories as a method to reduce research time and enhance their collections with more complete metadata.
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Bakker, Rebecca; Rowan, Kelley; Hu, Liting; Guan, Boyuan; Liu, Pinchao; Li, Zhongzhou; He, Ruizhe; and Monge, Christine, "AI for Archives: Using Facial Recognition to Enhance Metadata" (2020). Works of the FIU Libraries. 93.
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This project was made possible in part by a 2019 award from the Catalyst Fund at LYRASIS.