Cuing Multiple-Targets for Visual Search in Virtual Reality

Visual search is a common task, especially given the high amount of spatial information we process visually. To aid in searching an environment for targets, various cues have been developed and implemented for augmented reality (AR) head-mounted displays (HMDs). A variety of designs have emerged from prior literature including the gaze line, 2D wedge, and 3D arrow, each with unique design characteristics. However, many of these designs are not evaluated beyond their initial design proposals. Results favored the gaze line cue for search time, accuracy, and reported mental effort, potentially highlighting the benefit of having both direction and location information embedded into the cue.

Authors

Institutions

Publication Details

Published
2025-03-08
DOI
https://doi.org/10.1109/vrw66409.2025.00257
Primary Topic
Advanced Image and Video Retrieval Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cuing Multiple-Targets for Visual Search in Virtual Reality

Brendan Kelley, Christopher D. Wickens, Francisco R. Ortega, Benjamin A. Clegg et al.
Advanced Image and Video Retrieval Techniques
article

Cuing Multiple-Targets for Visual Search in Virtual Reality

Brendan Kelley, Christopher D. Wickens, Francisco R. Ortega, Benjamin A. Clegg, Ryan P. McMahan
article en

Abstract

Visual search is a common task, especially given the high amount of spatial information we process visually. To aid in searching an environment for targets, various cues have been developed and implemented for augmented reality (AR) head-mounted displays (HMDs). A variety of designs have emerged from prior literature including the gaze line, 2D wedge, and 3D arrow, each with unique design characteristics. However, many of these designs are not evaluated beyond their initial design proposals. Results favored the gaze line cue for search time, accuracy, and reported mental effort, potentially highlighting the benefit of having both direction and location information embedded into the cue.

Montana State University (US), Virginia Tech (US), Colorado State University (US)
Openalex Percentile: Top 93%
Advanced Image and Video Retrieval Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.