An internal web application built by Carnegie Mellon University Libraries faculty and staff leverages computer vision to improve the discoverability of archival photos by allowing archivists to quickly find groups of images depicting similar subjects and add descriptive metadata tags in bulk.
Computer-Aided Metadata generation for Photo archives Initiative (CAMPI), was inspired by a request from the CMU Marketing and Communications team, which regularly works with the University Archives to source images for online and print materials.
“We know, from experience, that our photo collection is not fully inventoried, and there are images with incorrect descriptions,” said University Archivist Julia Corrin. “I was interested in a tool that would let me to see if I could identify any earlier photos of the Computation Center space or find other images that were improperly labeled.”
The University Archives has approximately one million photos in its collection, 20,000 of which are digitized. That number grows larger each year as new materials are added. Growing at this rate makes it impossible for archivists to individually describe and categorize each picture — a necessary step to make them searchable by the public — so labels often lack specificity. There are so many images tagged with “Computers,” “Computing,” and “Students in Lab” that the archivists do not often have time to sort through the many images with generic tags. They focus on images with more specific labels, such as “Computation Center,” which can mean that other, perhaps better, images are never identified.
CAMPI allows the archivists to do this at scale by using computer vision, a term that refers to software that performs visual tasks with images, such as clustering together similar photographs, assigning photographs to predefined categories, and identifying objects and faces in photographs.
For now, CAMPI is just a prototype. While the first exploratory project is over, data from the tagging and deduplication work done during this project will be used as the photographs are migrated to a new digital collections system that will make them publicly accessible. A white paper explaining the project in greater depth that is now available includes a high-level technical architecture that discusses how such a system would connect to existing collection catalogues and image databases that libraries and archives already use.
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