Automatic identification and classification of portraits in a corpus of historical photographs
Abstract
There have been recent calls for an increased focus on the application of computer vision to the study and curation of digitised cultural heritage materials. In this short paper, we present an approach to bridge the gap between existing algorithms and humanistically driven annotations through a case study in which we create an algorithm to detect and and classify portrait photography. We apply this method to a collection of about 40,000 photographs and present a preliminary analysis of the constructed data. The work is part of the larger ongoing study that applies computer vision to the computational analysis of over a million U.S. documentary photographs from the early twentieth century.
Document Type
Article
Publication Date
12-2022
Publisher Statement
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)
CEUR Workshop Proceedings (CEUR-WS.org)
Recommended Citation
Arnold, T., Tilton, L. C. and Wigard, J. (2023). Automatic identification and classification of portraits in a corpus of historical photographs. CEUR Workshop Proceedings. https://ceur-ws.org/Vol-3290/short_paper5571.pdf