Predicting the Light Spectrum of Virtual Reality Scenarios for Non-Image-Forming Visual Evaluation

Sun, Yitong, Wang, Hanchun, Satilmis, Pinar, Pourshahrokhi, Narges, Harvey, Carlo ORCID: https://orcid.org/0000-0002-4809-1592 and Asadipour, Ali (2025) Predicting the Light Spectrum of Virtual Reality Scenarios for Non-Image-Forming Visual Evaluation. interactives, 1 (1). ISSN 2755-6336

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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.