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An interactive approach to investigate brightness perception of daylighting in Immersive Virtual Environments: Comparing subjective responses and quantitative metrics

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Abstract

Daylighting plays an eminent role in the performance of indoor environments and their occupants, thus necessitating the need to investigate daylight perception of potential occupants at early design stages. The present study introduces an interactive approach to collect and visualize brightness perception of daylighting in a large-scale immersive virtual environment, using a game engine as a daylight simulation tool. The developed system allows users to explore building models freely at different day times set in virtual reality and report their perceptions in real time. Following a validation study (N=36) to investigate the consistency of brightness perceptions in a real environment and its virtual replica, a set of 24 participants were recruited to use the system to report their brightness perception in a virtual model of a daylit art museum, through snapshotting the scenes where they perceive as one of the following in terms of daylighting: (very dark, dark, bright, or very bright). Using an output of 419 snapshots, a “Perceptual Light Map” (PLM) was developed to visualize the collective brightness perception of participants as a heat map. Subjective responses were found to be positively correlated with four daylight metrics, with the highest correlation to mean luminance and the lowest to luminance ratio. The findings of this exploratory study represent a step towards a user-oriented supplement tool to the existing quantitative daylight metrics, validating game engines’ adequacy as a daylight simulation tool, and illustrating the potentials of immersion and interaction principles for the perception of daylit spaces in virtual reality.

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Correspondence to Muhammad Hegazy.

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Hegazy, M., Yasufuku, K. & Abe, H. An interactive approach to investigate brightness perception of daylighting in Immersive Virtual Environments: Comparing subjective responses and quantitative metrics. Build. Simul. 15, 41–68 (2022). https://doi.org/10.1007/s12273-021-0798-3

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  • DOI: https://doi.org/10.1007/s12273-021-0798-3

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