ArticleBiomedical optics express2023
ChromaCorrect: prescription correction in virtual reality headsets through perceptual guidance.
Article in Biomedical optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 14 citations in OpenAlex.
- Dual-Input Neural Networks for Personalized Image Precompensation.Journal of imaging · 2026Article
- Introduction to Visual and Physiological Optics feature issue ofBiomedical optics express · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A large portion of today's world population suffers from vision impairments and wears prescription eyeglasses. However, prescription glasses cause additional bulk and discomfort when used with virtual reality (VR) headsets, negatively impacting the viewer's visual experience. In this work, we remedy the usage of prescription eyeglasses with screens by shifting the optical complexity into the software. Our proposal is a prescription-aware rendering approach for providing sharper and more immersive imagery for screens, including VR headsets. To this end, we develop a differentiable display and visual perception model encapsulating the human visual system's display-specific parameters, color, visual acuity, and user-specific refractive errors. Using this differentiable visual perception model, we optimize the rendered imagery in the display using gradient-descent solvers. This way, we provide prescription glasses-free sharper images for a person with vision impairments. We evaluate our approach and show significant quality and contrast improvements for users with vision impairments.
Identifiers
What OpenQuestion holds
Registered trials
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.