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

Yitong Sun; Hanchun Wang; Pinar Satilmis; Narges Pourshahrokh; Carlo Harvey; Ali Asadipour

doi:10.1109/VRW58643.2023.00238

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

Yitong Sun^*, Hanchun Wang, Pinar Satilmis, Narges Pourshahrokh, Carlo Harvey, Ali Asadipour

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	IEEE Conference on Virtual Reality and 3D User Interfaces
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	791-792
Number of pages	2
DOIs	https://doi.org/10.1109/VRW58643.2023.00238
Publication status	Published (VoR) - 25 Mar 2023

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title = "Predicting the light spectrum of virtual reality scenarios for Non-Image-Forming visual evaluation",

abstract = "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.",

author = "Yitong Sun and Hanchun Wang and Pinar Satilmis and Narges Pourshahrokh and Carlo Harvey and Ali Asadipour",

year = "2023",

month = mar,

day = "25",

doi = "10.1109/VRW58643.2023.00238",

language = "English",

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booktitle = "IEEE Conference on Virtual Reality and 3D User Interfaces",

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Predicting the light spectrum of virtual reality scenarios for Non-Image-Forming visual evaluation. / Sun, Yitong; Wang, Hanchun; Satilmis, Pinar et al.
IEEE Conference on Virtual Reality and 3D User Interfaces. Institute of Electrical and Electronics Engineers Inc., 2023. p. 791-792.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Predicting the light spectrum of virtual reality scenarios for Non-Image-Forming visual evaluation

AU - Sun, Yitong

AU - Wang, Hanchun

AU - Satilmis, Pinar

AU - Pourshahrokh, Narges

AU - Harvey, Carlo

AU - Asadipour, Ali

PY - 2023/3/25

Y1 - 2023/3/25

N2 - 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.

AB - 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.

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DO - 10.1109/VRW58643.2023.00238

M3 - Conference contribution

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EP - 792

BT - IEEE Conference on Virtual Reality and 3D User Interfaces

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

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

Abstract

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