Evidence map›Paper›PMID 39898901›Full record

ArticleJournal of vision2025

VR HMD color calibration and accurate control of emitted light using Three.js.

Killian Duay, Yoko Mizokami, Takehiro Nagai

Abstract read
In one paragraph

Article in Journal of vision, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Killian DuayDepartment of Information and Communications Engineering, Tokyo Institute of Technology, Nagatsuta-Cho, Midori-Ku, Yokohama, Japan.
Yoko MizokamiDepartment of Imaging Sciences, Chiba University, Yayoi-Cho, Inage-Ku, Chiba, Japan.
Takehiro NagaiDepartment of Information and Communications Engineering, Tokyo Institute of Technology, Nagatsuta-Cho, Midori-Ku, Yokohama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Virtual reality (VR) can be used to design and create new types of psychophysical experiments. Its main advantage is that it frees us from the physical limitations of real-life experiments and the hardware and software limitations of experiments running on two-dimensional (2D) displays and computer graphics. However, color calibration of the displays is often required in vision science studies. Recent studies have shown that a standard color calibration of a head-mounted display (HMD) can be very challenging and comes with significant drawbacks. These drawbacks include the need to completely disable tone mapping or to use unlit materials when tone mapping is only partially disabled. In this article, we introduce a new approach that allows for successful color calibration of an HMD and overcomes the disadvantages associated with other solutions. We utilize a new VR engine, Three.js, which offers several advantages. This article details our setup and methodology and provides all the elements required to reproduce the method, including the source code. We also apply our method to evaluate and compare three different HMDs: HTC Vive Pro Eye, Meta Quest Pro, and Meta Quest 3. The results show that the HTC Vive Pro Eye performs excellently, the Meta Quest Pro performs well, and the Meta Quest 3 performs poorly.

Indexed as

Color PerceptionPsychophysicsSmart GlassesVirtual RealityCalibrationColorHumansPhotic Stimulation

Identifiers

PMID39898901
PMCPMC11798340

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.