Disentangling top-down vs. bottom-up and low-level vs. high-level influences on eye movements over time

TL;DR

This study analyzes how top-down, bottom-up, low-level, and high-level factors influence eye movements over time, revealing a phased exploration process and the dominance of high-level and top-down influences in scene viewing.

Contribution

The paper introduces a novel temporal analysis of eye movement influences using combined saliency models and large datasets, clarifying the roles of different factors over time.

Findings

Initial saccades are driven mainly by low-level bottom-up factors.

High-level features significantly influence fixation locations after 200 ms.

Top-down processes dominate fixation control during search tasks.

Abstract

Bottom-up and top-down, as well as low-level and high-level factors influence where we fixate when viewing natural scenes. However, the importance of each of these factors and how they interact remains a matter of debate. Here, we disentangle these factors by analysing their influence over time. For this purpose we develop a saliency model which is based on the internal representation of a recent early spatial vision model to measure the low-level bottom-up factor. To measure the influence of high-level bottom-up features, we use a recent DNN-based saliency model. To account for top-down influences, we evaluate the models on two large datasets with different tasks: first, a memorisation task and, second, a search task. Our results lend support to a separation of visual scene exploration into three phases: The first saccade, an initial guided exploration characterised by a gradual broadening of the fixation density, and an steady state which is reached after roughly 10 fixations. Saccade target selection during the initial exploration and in the steady state are related to similar areas of interest, which are better predicted when including high-level features. In the search dataset, fixation locations are determined predominantly by top-down processes. In contrast, the first fixation follows a different fixation density and contains a strong central fixation bias. Nonetheless, first fixations are guided strongly by image properties and as early as 200 ms after image onset, fixations are better predicted by high-level information. We conclude that any low-level bottom-up factors are mainly limited to the generation of the first saccade. All saccades are better explained when high-level features are considered, and later this high-level bottom-up control can be overruled by top-down influences.