AI and the Digitized Photoarchive

Abstract

The Frick Art Reference Library in New York launched a pilot project with Stanford University, Cornell University, and the University of Toronto to develop an algorithm that applies a local classification system based on visual elements to the library’s digitized Photoarchive. As a test case, the Cornell/Toronto/Stanford team focused on a dataset of digital reproductions of North American paintings and drawings and employed recent advances in artificial intelligence and machine learning to produce automatic image classifiers. The results of this preliminary experiment suggest that automatic image classifiers have the potential to become powerful tools in metadata creation and image retrieval.