How images determine our visual search strategy

TL;DR

This paper investigates how different images influence visual search strategies by analyzing eye movements, introducing a model to simulate and quantify these strategies, revealing the relationship between visual landscapes and search behavior.

Contribution

The study introduces a novel model that captures and simulates eye-tracking trajectories, enabling quantification of search strategies based on image features.

Findings

Different images induce distinct search strategies.

Small variations in images significantly alter search behavior.

The model accurately reproduces experimental eye movement data.

Abstract

When searching for a target within an image our brain can adopt different strategies, but which one does it choose? This question can be answered by tracking the motion of the eye while it executes the task. Following many individuals performing various search tasks we distinguish between two competing strategies. Motivated by these findings, we introduce a model that captures the interplay of the search strategies and allows us to create artificial eye-tracking trajectories, which could be compared to the experimental ones. Identifying the model parameters allows us to quantify the strategy employed in terms of ensemble averages, characterizing each experimental cohort. In this way we can discern with high sensitivity the relation between the visual landscape and the average strategy, disclosing how small variations in the image induce changes in the strategy.