AI for Archives: Using Facial Recognition to Enhance Metadata Article

Bakker, Rebecca, Rowan, Kelley, Hu, Liting et al. (2020). AI for Archives: Using Facial Recognition to Enhance Metadata .

cited authors

  • Bakker, Rebecca; Rowan, Kelley; Hu, Liting; Guan, Boyuan; Liu, Pinchao; Li, Zhongzhou; He, Ruizhe; Monge, Christine

authors

abstract

  • 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.

publication date

  • July 31, 2020

keywords

  • Archival Science
  • Artificial Intelligence and Robotics
  • Computer Sciences
  • Library and Information Science

publisher

  • FIU Digital Commons