  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.
