Abstract: By looking at a work of art, an observer enters into a dialogue. In this work, we attempt to analyze this dialogue with both behavioral and computational tools. In two experiments, observers were asked to look at a large number of paintings from different art periods and to rate their visual complexity, or their aesthetic appeal. During these two tasks, their eye movements were recorded. The complexity and aesthetic ratings show clear preferences for certain artistic styles and were based on both low-level and high-level criteria. Eye movements reveal the time course of the aesthetic dialogue as observers try to interpret and understand the painting. Computational analyses of both the ratings (using measures derived from information theory) and the eye tracking data (using two models of saliency) showed that our computational tools are already able to explain some properties of this dialogue.