arXiv subjects

Apurv Varshney

Publications and source records attributed to Apurv Varshney.

6 recordsLinked to original sources

arXiv2026

Cross-Modal Guidance for Out-of-View Object Search in Simulated Prosthetic Vision

Out-of-view guidance is well established in virtual and augmented reality, but its effectiveness may depend on the visual bandwidth available to the user. We test this under simulated prosthetic vision (SPV), where visual guidance must share the same sparse representation used to inspect the scene. Nineteen participants performed object search under two SPV conditions differing in electrode density and phosphene spread (10x10 and 20x20) and four guidance conditions (no guidance, visual, haptic, audio) all driven by the same horizontal target-offset variable. All three modalities reduced search time and head movement. The tested auditory and haptic cues produced approximately 25% faster overall search and 11-13% faster target acquisition than the visual cue, despite similarly direct orienting trajectories. The tested haptic and auditory cues also shortened post-acquisition search. Final head-target angular offset was reduced substantially more in the 10x10 SPV condition; there, all three cues also reduced vertical localization error by approximately 45-58% despite providing no elevation information. Under severe visual constraints, guidance performance depended on cue implementation and search stage.

cs.HC↗

arXiv2026

SABER: Spatial Attention, Brain, Extended Reality

Tracking moving objects is a critical skill for many everyday tasks, such as crossing a busy street, driving a car or catching a ball. Attention is a key cognitive function that supports object tracking; however, our understanding of the brain mechanisms that support attention is almost exclusively based on evidence from tasks that present stable objects at fixed locations. Accounts of multiple object tracking are also limited because they are largely based on behavioral data alone and involve tracking objects in a 2D plane. Consequently, the neural mechanisms that enable moment-by-moment tracking of goal-relevant objects remain poorly understood. To address this knowledge gap, we developed SABER (Spatial Attention, Brain, Extended Reality), a new framework for studying the behavioral and neural dynamics of attention to objects moving in 3D. Participants (n=32) completed variants of a task inspired by the popular virtual reality (VR) game, Beat Saber, where they used virtual sabers to strike stationary and moving color-defined target spheres while we recorded electroencephalography (EEG). We first established that standard univariate EEG metrics which are typically used to study spatial attention to static objects presented on 2D screens, can generalize effectively to an immersive VR context involving both static and dynamic 3D stimuli. We then used a computational modeling approach to reconstruct moment-by-moment attention to the locations of stationary and moving objects from oscillatory brain activity, demonstrating the feasibility of precisely tracking attention in a 3D space. These results validate SABER, and provide a foundation for future research that is critical not only for understanding how attention works in the physical world, but is also directly relevant to the development of better VR applications.

cs.HC↗

arXiv2026

Actionable Guidance Outperforms Map and Compass Cues in Demanding Immersive VR Wayfinding

Navigation aids are central to immersive virtual reality (VR) experiences that involve physical locomotion. Their effectiveness depends not only on how much spatial information they provide, but also on how directly that information supports movement decisions. We compared three common guidance techniques for immersive VR wayfinding: a directional arrow, a minimap, and a compass. In a controlled room-scale VR study with 42 participants completing 1008 trials, participants navigated to target landmarks in a time-pressured maze with reduced visibility and forced route replanning. Across behavioral and eye-tracking measures, arrow guidance produced the strongest navigation performance, minimap guidance yielded intermediate performance, and compass cues performed worst, suggesting that during immersive locomotion users benefit from guidance that can be interpreted rapidly while moving. These results suggest that in demanding immersive locomotion tasks, interfaces that translate spatial information directly into actionable movement cues can outperform richer but more interpretive spatial representations. Our findings highlight the importance of designing XR navigation interfaces that minimize the cognitive translation between spatial information and movement decisions.

cs.HC↗

arXiv2025

Static or Temporal? Semantic Scene Simplification to Aid Wayfinding in Immersive Simulations of Bionic Vision

Visual neuroprostheses (bionic eye) aim to restore a rudimentary form of vision by translating camera input into patterns of electrical stimulation. To improve scene understanding under extreme resolution and bandwidth constraints, prior work has explored computer vision techniques such as semantic segmentation and depth estimation. However, presenting all task-relevant information simultaneously can overwhelm users in cluttered environments. We compare two complementary approaches to semantic preprocessing in immersive virtual reality: SemanticEdges, which highlights all relevant objects at once, and SemanticRaster, which staggers object categories over time to reduce visual clutter. Using a biologically grounded simulation of prosthetic vision, 18 sighted participants performed a wayfinding task in a dynamic urban environment across three conditions: edge-based baseline (Control), SemanticEdges, and SemanticRaster. Both semantic strategies improved performance and user experience relative to the baseline, with each offering distinct trade-offs: SemanticEdges increased the odds of success, while SemanticRaster boosted the likelihood of collision-free completions. These findings underscore the value of adaptive semantic preprocessing for prosthetic vision and, more broadly, may inform the design of low-bandwidth visual interfaces in XR that must balance information density, task relevance, and perceptual clarity.

cs.HC↗

arXiv2025

Navigating the Last Mile: Evaluating Head- and Cane-Mounted Cameras for Egocentric Spatial Awareness

Robust navigational guidance is an important XR application for both sighted and non-sighted populations. In this paper, we mainly focus on blind pedestrians, who continue to face "last-mile" challenges such as locating entrances and navigating cluttered spaces. While smartglasses and wearables are maturing, a foundational design question remains underexplored: where on the body should cameras be placed to best support navigation? We present a mixed-methods investigation that focuses on the question of camera placement for generating spatial data supporting ego-centric navigation. A survey of 10 blind cane users surfaced practices for last-mile navigation and perceptions of body-mounted XR devices. A controlled case study with a blind co-author compared head- and cane-mounted cameras using synchronized Project Aria glasses while traversing five real-world environments. Using Simultaneous Localization and Mapping (SLAM) and Neural Radiance Fields (NeRFs) as diagnostic probes, we find the central trade-off appears to be not simply head versus cane but localization stability versus near-ground coverage, with the combined head+cane view providing complementary information for scene reconstruction. We translate these findings into architectural considerations for hybrid XR systems that extend the cane without interfering with tactile and auditory cues.

cs.HC↗

arXiv2025

Simulated prosthetic vision confirms checkerboard as an effective raster pattern for epiretinal implants

Spatial scheduling of electrode activation ("rastering") is essential for safely operating high-density retinal implants, yet its perceptual consequences remain poorly understood. This study systematically evaluates the impact of raster patterns, or spatial arrangements of sequential electrode activation, on performance and perceived difficulty in simulated prosthetic vision (SPV). By addressing this gap, we aimed to identify patterns that optimize functional vision in retinal implants. Sighted participants completed letter recognition and motion discrimination tasks under four raster patterns (horizontal, vertical, checkerboard, and random) using an immersive SPV system. The simulations emulated epiretinal implant perception and employed psychophysically validated models of electrode activation, phosphene appearance, nonlinear spatial summation, and temporal dynamics, ensuring realistic representation of prosthetic vision. Performance accuracy and self-reported difficulty were analyzed to assess the effects of raster patterning. The checkerboard pattern consistently outperformed other raster patterns, yielding significantly higher accuracy and lower difficulty ratings across both tasks. The horizontal and vertical patterns introduced biases aligned with apparent motion artifacts, while the checkerboard minimized such effects. Random patterns resulted in the lowest performance, underscoring the importance of structured activation. Notably, checkerboard matched performance in the "No Raster" condition, despite conforming to groupwise safety constraints. This is the first quantitative, task-based evaluation of raster patterns in SPV. Checkerboard-style scheduling enhances perceptual clarity without increasing computational load, offering a low-overhead, clinically relevant strategy for improving usability in next-generation retinal prostheses.

cs.HC↗