Tone mapping operators aim to remap content to a display’s dynamic range. Virtual reality is a popular new display modality that has significant differences from other media, making the use of traditional tone mapping techniques difficult. Moreover, real-time adaptive estimation of tone curves that faithfully maintain appearance remains a significant challenge. In this work, we propose a real-time perceptual contrast-matching framework, that allows us to optimally remap scenes for target displays. Our framework is optimized for efficiency and runs on a mobile Quest 2 headset in under 1ms per frame. A subjective study on an HDR-VR prototype demonstrates our method’s effectiveness across a wide range of display luminances, producing imagery that is preferred to alternatives tone mapped at peak luminances an order of magnitude higher. This result highlights the importance of good tone mapping for visual quality in VR.

With advances in Virtual Reality (VR) technology, user expectation for a near-perfect experience is also increasing. The push for a wider field-of-view can increase the challenges of correcting lens distortion. Past studies on imperfect VR experiences have focused on motion sickness provoked by vection-inducing VR stimuli and discomfort due to mismatches in accommodation and binocular convergence. Disorientation and discomfort due to unintended optical flow induced by lens distortion, referred to as dynamic distortion (DD), has, to date, received little attention. This study examines and models the effects of DD during head rotations with various fixed gazes stabilized by vestibulo-ocular reflex (VOR). Increases in DD levels comparable to lens parameters from poorly designed commercial VR lenses significantly increase discomfort scores of viewers in relation to disorientation, dizziness, and eye strain. Cross-validated results indicate that the model is able to predict significant differences in subjective scores resulting from different commercial VR lenses and these predictions correlated with empirical data. The present work provides new insights to understand symptoms of discomfort in VR during user interactions with static world-locked / space-stabilized scenes and contributes to the design of discomfort-free VR headset lenses.