Identifying influences between artists based on artwork faces and geographic proximity

Abstract

The investigation of influences in artists’ works has been a subject of interest for art historians for many years. Therefore, computational methods can provide a new perspective for identifying these influences’ relationships. Indeed, several studies in computer science have proposed techniques to analyze similarities between paintings using various features. Faces are a crucial aspect of perception in art and have also been the focus of several studies in computational aesthetics. In our previous work, we proposed a method for analyzing artworks and evaluating the influence of artists. The present study improves upon the previous research by extending the analysis of influences considering second-degree influences between artists and the impact of geographic proximity, obtaining better results in terms of Recall than the previous work. In addition, we evaluated the capability of our method to detect work-to-work relationships between each pair of artworks by the artists, and we found plausible and interesting results, even though they have not yet been proven in the literature. By conducting further analysis of data extracted from the faces of works of art, the goal is to enhance the previous findings in the literature and foster further discussion and collaboration between the fields of art and computer science. The objective is not to provide a definitive answer to the question of influences but to stimulate further research in this area, pointing out new possibilities of influence and explanations about these influences.