Evidence map›Paper›PMID 34778840›Full record

ArticleSN computer science2022

Colour Calibration of a Head Mounted Display for Colour Vision Research Using Virtual Reality.

Raquel Gil Rodríguez, Florian Bayer, Matteo Toscani, Dar'ya Guarnera, Giuseppe Claudio Guarnera, Karl R Gegenfurtner

Abstract read
In one paragraph

Article in SN computer science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

6 authors.

Raquel Gil RodríguezDepartment of Psychology, Justus-Liebig-Universität Giessen, Giessen, Germany.ORCID 0000-0001-5561-1990
Florian BayerDepartment of Psychology, Justus-Liebig-Universität Giessen, Giessen, Germany.
Matteo ToscaniDepartment of Psychology, Justus-Liebig-Universität Giessen, Giessen, Germany.
Dar'ya GuarneraDepartment of Computer Science, Norwegian University of Science and Technology, Gjøvik, Norway.
Giuseppe Claudio GuarneraDepartment of Computer Science, Norwegian University of Science and Technology, Gjøvik, Norway.
Karl R GegenfurtnerDepartment of Psychology, Justus-Liebig-Universität Giessen, Giessen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Virtual reality (VR) technology offers vision researchers the opportunity to conduct immersive studies in simulated real-world scenes. However, an accurate colour calibration of the VR head mounted display (HMD), both in terms of luminance and chromaticity, is required to precisely control the presented stimuli. Such a calibration presents significant new challenges, for example, due to the large field of view of the HMD, or the software implementation used for scene rendering, which might alter the colour appearance of objects. Here, we propose a framework for calibrating an HMD using an imaging colorimeter, the I29 (Radiant Vision Systems, Redmond, WA, USA). We examine two scenarios, both with and without using a rendering software for visualisation. In addition, we present a colour constancy experiment design for VR through a gaming engine software, Unreal Engine 4. The colours of the objects of study are chosen according to the previously defined calibration. Results show a high-colour constancy performance among participants, in agreement with recent studies performed on real-world scenarios. Our studies show that our methodology allows us to control and measure the colours presented in the HMD, effectively enabling the use of VR technology for colour vision research.

Indexed as

ColorimeterColour calibrationColour constancyColour visionHead mounted displaySpectroradiometerVirtual reality

Identifiers

PMID34778840
PMCPMC8551135

What OpenQuestion holds

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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.