Evidence map›Paper›PMID 40678016›Full record

ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference2025

VisiMark: Characterizing and Augmenting Landmarks for People with Low Vision in Augmented Reality to Support Indoor Navigation.

Ruijia Chen, Junru Jiang, Pragati Maheshwary, Brianna R Cochran, Yuhang Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ruijia ChenDepartment of Computer Sciences University of Wisconsin-Madison Madison, Wisconsin, USA.
Junru JiangDepartment of Computer Sciences University of Wisconsin-Madison Madison, Wisconsin, USA.
Pragati MaheshwaryHuman Computer Interaction Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA.
Brianna R CochranDepartment of Computer Sciences University of Wisconsin-Madison Madison, Wisconsin, USA.
Yuhang ZhaoDepartment of Computer Sciences University of Wisconsin-Madison Madison, Wisconsin, USA.

Funding

SCH: Scene-Aware AR Systems for Low Vision People in Activities of Daily LivingR01EY037100 · NEI · UNIVERSITY OF WISCONSIN-MADISON · PI Yapeng Tian, Yuhang Zhao · 2024 to 2026
$915k
NEI NIH HHS R01 EY037100
6 · The paper itself

Abstract

Landmarks are critical in navigation, supporting self-orientation and mental model development. Similar to sighted people, people with low vision (PLV) frequently look for landmarks via visual cues but face difficulties identifying some important landmarks due to vision loss. We first conducted a formative study with six PLV to characterize their challenges and strategies in landmark selection, identifying their unique landmark categories (e.g., area silhouettes, accessibility-related objects) and preferred landmark augmentations. We then designed

Indexed as

AccessibilityIndividuals with Disabilities & Assistive TechnologiesVirtual/Augmented Reality

Identifiers

PMID40678016
PMCPMC12269830

What OpenQuestion holds

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LicenceCC BY-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.