Evidence map›Paper›PMID 30193343›Full record

ArticleJournal of vision2018

Creating correct blur and its effect on accommodation.

Steven A Cholewiak, Gordon D Love, Martin S Banks

Open access · goldAbstract read
In one paragraph

Article in Journal of vision, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
18.6field-weighted citation impact, top 1% of its field
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

21 citing papers in PubMed, 116 citations in OpenAlex.

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  9. Rendering algorithms for aberrated human vision simulation.Visual computing for industry, biomedicine, and art · 2023
    Review
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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

3 authors at 2 institutions in 2 countries.

Steven A CholewiakOptometry & Vision Science, University of California, Berkeley, Berkeley, CA, USA.
Gordon D LoveComputer Science & Physics, Durham University, Durham, UK.
Martin S BanksOptometry & Vision Science, University of California, Berkeley, Berkeley, CA, USA.
University of California, Berkeley · USDurham University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blur occurs naturally when the eye is focused at one distance and an object is presented at another distance. Computer-graphics engineers and vision scientists often wish to create display images that reproduce such depth-dependent blur, but their methods are incorrect for that purpose. They take into account the scene geometry, pupil size, and focal distances, but do not properly take into account the optical aberrations of the human eye. We developed a method that, by incorporating the viewer's optics, yields displayed images that produce retinal images close to the ones that occur in natural viewing. We concentrated on the effects of defocus, chromatic aberration, astigmatism, and spherical aberration and evaluated their effectiveness by conducting experiments in which we attempted to drive the eye's focusing response (accommodation) through the rendering of these aberrations. We found that accommodation is not driven at all by conventional rendering methods, but that it is driven surprisingly quickly and accurately by our method with defocus and chromatic aberration incorporated. We found some effect of astigmatism but none of spherical aberration. We discuss how the rendering approach can be used in vision science experiments and in the development of ophthalmic/optometric devices and augmented- and virtual-reality displays.

Indexed as

Optics and PhotonicsAccommodation, OcularAdultAstigmatismFemaleHumansMaleMathematicsPsychophysicsRefraction, OcularRetinaVision, OcularYoung Adult

Identifiers

PMID30193343
PMCPMC6126933
OpenAlexW2891406280

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.