LAUSR

Eye tracking has been an essential tool within the vision science community for many years. However, the majority of studies involving eye-tracking technology employ a relatively passive approach through the use of static imagery, prescribed motion, or video stimuli. This is in contrast to our everyday interaction with the natural world where we navigate our environment while actively seeking and using task-relevant visual information. For this reason, an increasing number of vision researchers are employing virtual environment platforms, which offer interactive, realistic visual environments while maintaining a substantial level of experimental control. Here, we recorded eye movement behavior while subjects freely navigated through a rich, open-world virtual environment. Within this environment, subjects completed a visual search task where they were asked to find and count occurrence of specific targets among numerous distractor items. We assigned each participant into one of four target conditions: Humvees, motorcycles, aircraft, or furniture. Our results show a statistically significant relationship between gaze behavior and target objects across Target Conditions with increased visual attention toward assigned targets. Specifically, we see an increase in the number of fixations and an increase in dwell time on target relative to distractor objects. In addition, we included a divided attention task to investigate how search changed with the addition of a secondary task. With increased cognitive load, subjects slowed their speed, decreased gaze on objects, and increased the number of objects scanned in the environment. Overall, our results confirm previous findings and support that complex virtual environments can be used for active visual search experimentation, maintaining a high level of precision in the quantification of gaze information and visual attention. This study contributes to our understanding of how individuals search for information in a naturalistic (open-world) virtual environment. Likewise, our paradigm provides an intriguing look into the heterogeneity of individual behaviors when completing an un-timed visual search task while actively navigating.