Visual search in virtual reality (VR) relies on the coordination of peripheral vision, eye movements, and head movements. In dense immersive scenes, inter-object spacing is expected to influence search behavior by modulating local visual interference, while also changing the angular extent of the explored scene. In this article, we investigate how inter-object spacing shapes visual search strategies in VR using ecologically valid textured 3D objects. We conducted a user study in which participants searched for target objects among distractors under three spacing conditions, while keeping the number of objects constant and recording both eye and head movements. Conventional visual search measures, such as search time, fixation count, and mean fixation duration, are typically expected to vary consistently with task difficulty. However, our results reveal a mixed pattern: search time and fixation count increase with spacing, whereas mean fixation duration decreases. This apparent paradox highlights the limitations of standard metrics in VR, where performance is strongly influenced by scene extent and head contribution. To address this, we complement traditional measures with detailed scanpath analyses. We show that dense layouts induce more refixations, more frequent direction changes, and less stable exploration patterns. Although absolute scanpath length increases with spacing, normalization by inter-object distance reveals that the relative exploration cost is highest in the densest condition. In contrast, wider spacing is associated with a stronger contribution of head movements to the search process. Taken together, these findings show that inter-object spacing does not simply make search globally easier or harder, but reorganizes visual exploration strategies in immersive VR in a way that is consistent with visual crowding principles, while also reflecting other spacing-dependent factors such as scene extent, effective field of view, and head-movement demands.
While the number of studies about online content warning labels are on the rise, the graphical design of these labels has been understudied. To begin filling this gap, we perform a 13-arm between-subjects experiment (N = 1,288) across two graphic elements of warning labels: intrusiveness and color. We find that highly intrusive labels that require click-through to view content are significantly less effective at decreasing trust in false information than lesser intrusive designs—conditional on those consumers clicking through the highly intrusive label to actively engage with the content. However, highly intrusive warning labels are still better than having no warning label. We find no evidence that color impacts the recall or effectiveness of content warning labels. These results should be taken in concert with the limitations of the study, which are discussed in depth in the article.
New augmented reality (AR) techniques enable increasingly advanced modifications of body representation. This representation and its control are crucial from a social perspective, with many studies focusing on body representation in medical contexts. In this article, we propose a device that allows, in AR, the modification of the user’s appearance by controlling the width of their body. We then conduct a user study to investigate the impact of this modification on body perception, specifically its perceived affordance. Additionally, we record the participant’s internal perception (Sense of Embodiment, body-shape perception) to study their interaction with body perception. Our results show that this system can effectively modify the perceived affordances. They also highlight the strong variability of body perception and its interaction with several factors such as Sense of Embodiment and initial body perception. This work contributes to expanding knowledge of body perception within the specific context of AR and provides significant perspectives for enriching the understanding and treatment of individuals suffering from body image misperception.
Tactile properties of fabrics convey vital information and influence customer decision and satisfaction. The understanding of the tactile properties is not comprehensive due to the multiple tactile properties and the various ways of assessing them. Here, we designed a series of psychophysical experiments to evaluate the multiple tactile properties, including flexible-stiff, smooth-rough, soft-firm, spongy-crisp, warm-cool, using images of flat fabric, draped fabric, rotating fabric, and real fabrics where only touch was allowed, only vision was allowed, and both touch and vision were allowed. Our results show that it is necessary to study the separate tactile properties rather than treat them as a whole. The tactile perception remained consistent yet slightly different among images, videos, and real fabrics. However, for warm-cool, highly consistent perception can be obtained regardless of the condition. Additionally, the tactile properties are not completely independent to each other. Positive and negative correlations among the different tactile perceptions were also observed in our study. In addition, the differences between visual representations of fabrics and real fabrics were also observed for the perception of flexible-stiff, smooth-rough, soft-firm, and warm-cool.
This paper presents an innovative pipeline to eye-tracking with computational efficiency, utilizing a fully event-based algorithm. Traditional eye-tracking methods often rely on grayscale or infrared imaging, which can be computationally intensive and raise privacy concerns. Our research addresses these issues by developing an algorithm that exclusively uses data from event-based sensors, optimizing for settings with limited computational power. The system relies on simple geometrical operations, enabling efficient real-time processing. Experimental results demonstrate the feasibility of this approach, offering a promising solution for eye-tracking in compact, computationally constrained devices.
