Preferred Model of Adaptation to Dark for Virtual Reality Headsets

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Abstract

The human visual system has the ability to adapt to various lighting conditions. In this work, we simulate the dark adaptation process using a custom virtual reality framework. The high dynamic range (HDR) image is rendered, tone mapped and displayed in the head-mounted-display (HMD) equipped with the eye tracker. Observer’s adaptation state is predicted by analysing the HDR image in the surrounding of his/her gaze point. This state is applied during tone mapping to simulate how an observer would see the whole scene being adapted to an arbitrary luminance level. We take into account the spatial extent of the visual adaptation, loss of colour vision, and time course of adaptation. Our main goal is to mimic the adaptation process naturally implemented by the human visual system. However, we prove in the psychophysical experiments that people prefer shorter adaptation while watching a virtual environment. We also justify that a complex perceptual model of adaptation to dark can be replaced with simpler linear formulas.

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APA

Wernikowski, M., Mantiuk, R., & Piórkowski, R. (2019). Preferred Model of Adaptation to Dark for Virtual Reality Headsets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11295 LNCS, pp. 118–129). Springer Verlag. https://doi.org/10.1007/978-3-030-05710-7_10

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