2021/02/04 by David G. Stork, Anthony Bourached, Stork, David G. +7
Arts and Humanities · Computer Science · Neuroscience · #Aesthetic Perception and Analysis #Computer Vision and Pattern Recognition (cs.CV) #Conservation Techniques and Studies #FOS: Computer and information sciences #Music and Audio Processing #cs.CV
paper · pdf · doi:10.48550/arxiv.2102.02732
Accepted as conference paper at Computer Vision and Art Analysis 2021
arxiv created 2021/02/04 · openalex publication_date 2021/02/04 · arxiv updated 2021/02/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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 automatic system based on deep convolutional neural networks and simple knowledge database to identify saints throughout six centuries of Christian art based in large part upon saints symbols or attributes. Our work represents initial steps in the broad task of automatic semantic interpretation of messages and meaning in fine art.