Depth-based subtle gaze guidance in virtual reality environments

Sridharan, Srinivas; Pieszala, James; Bailey, Reynold

doi:10.1145/2804408.2814187

Cited by 6 publications

(1 citation statement)

References 2 publications

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“…In this study, we hypothesize that by subtly modifying the visual scene, it is possible to drive the observer's attention away from salient distracting locations, enabling the user to find the target faster. Previously, some attempts were made to apply subtle visual content modification for gaze guidance, where color, luminance, spatial frequency, and other domains were modulated [32][33][34][35][36][37][38][39][40][41]. In this work, blur was selected as a domain for modifying visual content, as it was previously shown that blur, although with limitations, can be used for gaze guidance to an extent where the observer does not even notice the modification [42][43][44].…”

Section: Introductionmentioning

confidence: 99%

Saliency-Aware Subtle Augmentation Improves Human Visual Search Performance in VR

Lukashova-Sanz

Wahl

2021

Brain Sciences

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Visual search becomes challenging when the time to find the target is limited. Here we focus on how performance in visual search can be improved via a subtle saliency-aware modulation of the scene. Specifically, we investigate whether blurring salient regions of the scene can improve participant’s ability to find the target faster when the target is located in non-salient areas. A set of real-world omnidirectional images were displayed in virtual reality with a search target overlaid on the visual scene at a pseudorandom location. Participants performed a visual search task in three conditions defined by blur strength, where the task was to find the target as fast as possible. The mean search time, and the proportion of trials where participants failed to find the target, were compared across different conditions. Furthermore, the number and duration of fixations were evaluated. A significant effect of blur on behavioral and fixation metrics was found using linear mixed models. This study shows that it is possible to improve the performance by a saliency-aware subtle scene modulation in a challenging realistic visual search scenario. The current work provides an insight into potential visual augmentation designs aiming to improve user’s performance in everyday visual search tasks.

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