What we look at in paintings: A comparison between experienced and inexperienced art viewers

TL;DR

This study analyzes eye movement patterns of experienced and inexperienced art viewers to understand differences in how they observe paintings, using statistical models and point process analysis.

Contribution

Introduces statistical tools and a stochastic model to compare and analyze eye movement data between experienced and inexperienced art viewers.

Findings

Differences in gaze stop locations between groups

A simple stochastic model fits eye movement data well

Statistical analysis reveals distinct viewing patterns

Abstract

How do people look at art? Are there any differences between how experienced and inexperienced art viewers look at a painting? We approach these questions by analyzing and modeling eye movement data from a cognitive art research experiment, where the eye movements of twenty test subjects, ten experienced and ten inexperienced art viewers, were recorded while they were looking at paintings. Eye movements consist of stops of the gaze as well as jumps between the stops. Hence, the observed gaze stop locations can be thought as a spatial point pattern, which can be modeled by a spatio-temporal point process. We introduce some statistical tools to analyze the spatio-temporal eye movement data, and compare the eye movements of experienced and inexperienced art viewers. In addition, we develop a stochastic model, which is rather simple but fits quite well to the eye movement data, to further investigate the differences between the two groups through functional summary statistics.