Login
       
  • Predicting the light spectrum of virtual reality scenarios for Non-Image-Forming visual evaluation

Sun, Yitong ORCID: https://orcid.org/0000-0002-9469-7157, Wang, Hanchun, Satilmis, Pinar, Pourshahrokhi, Narges, Harvey, Carlo and Asadipour, Ali, 2023, Book Section, Predicting the light spectrum of virtual reality scenarios for Non-Image-Forming visual evaluation 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE, New York, USA, pp. 1-2. ISBN 979-8-3503-4839-2

Abstract or Description:

Virtual reality (VR) headsets, while providing realistic simulated environments, are also over-stimulating the human eye, particularly for the Non-Image-Forming (NIF) visual system. Therefore, it is crucial to predict the spectrum emitted by the VR headset and to perform light stimulation evaluations during the virtual environment construction phase. We propose a framework for spectrum prediction of VR scenes only by importing a pre-acquired optical profile of the VR headset. It is successively converted into "Five Photoreceptors Radiation Efficacy" (FPRE) maps and the "Melanopic Equivalent Daylight Illuminance" (M-EDI) value to visually predict the detailed stimulation of virtual scenes to the human eye.

Official URL: https://ieeexplore.ieee.org/abstract/document/1010...
Subjects: Other > Mathematical and Computer Sciences > G400 Computer Science
School or Centre: Research Centres > Computer Science Research Centre
Copyright Holders: Yitong Sun, Conputer Science Reseach Centre, RCA
Identification Number or DOI: https://doi.org/10.1109/VRW58643.2023.00238
Date Deposited: 19 Jun 2023 15:24
Last Modified: 19 Jun 2023 15:24
URI: https://researchonline.rca.ac.uk/id/eprint/5423
Edit Item (login required) Edit Item (login required)