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Volume: 33 | Article ID: art00003
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Computational identification of significant actors in paintings through symbols and attributes
  DOI :  10.2352/ISSN.2470-1173.2021.14.CVAA-015  Published OnlineJanuary 2021
Abstract

The automatic analysis of fine art paintings presents a number of novel technical challenges to artificial intelligence, computer vision, machine learning, and knowledge representation quite distinct from those arising in the analysis of traditional photographs. The most important difference is that many realist paintings depict stories or episodes in order to convey a lesson, moral, or meaning. One early step in automatic interpretation and extraction of meaning in artworks is the identifications of figures (“actors”). In Christian art, specifically, one must identify the actors in order to identify the Biblical episode or story depicted, an important step in “understanding” the artwork. We designed an auto-matic system based on deep convolutional neural net-works and simple knowledge database to identify saints throughout six centuries of Christian art based in large part upon saints’ symbols or attributes. Our work rep-resents initial steps in the broad task of automatic se- mantic interpretation of messages and meaning in fine art.

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David G. Stork, Anthony Bourached, George H. Cann, Ryan-Rhys Griffths, "Computational identification of significant actors in paintings through symbols and attributesin Proc. IS&T Int’l. Symp. on Electronic Imaging: Computer Vision and Image Analysis of Art,  2021,  pp 15-1 - 15-8,  https://doi.org/10.2352/ISSN.2470-1173.2021.14.CVAA-015

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