This paper introduces a novel approach for the assessment of daylight performance in buildings, venturing beyond existing methods that evaluate 2-dimensional illumination and comfort within a fixed field-of-view in order to predict human responses to light concerning non-visual health potential, visual interest, and gaze behavior in a visually immersive scene. Using a 3D rendered indoor environment to exemplify this coordinated approach, the authors assess an architectural space across a range of view directions to predict non-visual health potential, perceptual visual interest, and gaze behavior at the eye level of an occupant across an immersive field-of-view. This method allows the authors to explore and demonstrate the impact of space, time, and sky condition on three novel daylight performance models developed to predict the effects of ocular light exposure using a humancentric approach. Results for each model will be presented in parallel and then compared to discuss the need for a multi-criteria assessment of daylight-driven human responses in architecture. A parallel and comparative approach can allow the designer to adapt the architectural space based on the program use and occupants needs.

Daylit architecture is perceived as a dynamic luminous composition, yet most existing performance metrics were designed to evaluate natural illumination for its ability to adequately illuminate a twodimensional task surface and avoid glare-based discomfort. It may be argued that task-driven approaches based on surface illumination and glare ignore the likelihood that contrast can provide positive impacts on our visual perception of space. Advances in these metrics to accommodate climate-based sky conditions and occupant behavior have improved our ability to evaluate task illumination and glare, yet the same attention has not been paid to evaluating positive perceptual responses to daylight. Existing studies have attempted to link subjective ratings of composition to simple global contrast metrics without reaching consensus. More advanced metrics have been developed in computational graphics and vision fields, but have not been applied to studies in qualitative lighting research. This paper introduces the results from an online experiment where subject ratings of daylight composition are compared to quantitative contrast measures across a series of renderings. This paper will identify which measures correlate to subjects' ratings of visual interest, and introduces a modified contrast algorithm, which can be used as a novel prediction model for visual interest in daylit renderings.

a b s t r a c tUnlike artificial light sources, which can be calibrated to meet a desired luminous effect regardless of latitude, climate, or time of day, daylight is a dynamic light source, which produces variable shadow patterns and fluctuating levels of brightness. While we know that perceptual impacts of daylight such as contrast and temporal variability are important factors in architectural design, we are left with an imbalanced set of performance indicators e and few, if any, which address the positive visual and temporal qualities of daylight from an occupant point-of-view. If visual characteristics of daylight, such as contrast and spatial compositions, can be objectively measured, we can contribute to a more holistic analysis of daylit architecture with metrics that complement existing illumination and comfort-based performance criteria. Using image processing techniques, this paper will propose a proof-of-concept methodology for quantifying contrast-based visual effects within renderings of daylit architecture. Two new metrics will be proposed; annual spatial contrast and annual luminance variability. Using 56 time-step instances (taken symmetrically from across the day and year) this paper will introduce a method for quantifying local contrast values within a set of rendered images and plot those instances over time to visualize hourly and seasonal fluctuations in contrast composition. Using the same 56 instances, this paper will also introduce a method for quantifying variations in luminance (brightness) between instances to measure fluctuations in brightness. This paper pre-validates each of the proposed methods by calculating annual spatial contrast and annual luminance variability across ten abstract digital models and comparing those results to the authors' own intuitive ranking.

Over the last several decades, designers have used digital screens to view images of real and simulated spaces and make critical design decisions. Screen technology has improved during this time, as technologies like OLED have replaced legacy displays (CRT, plasma, and LCD). These new screens provide a higher pixel resolution, luminous output and contrast ratio. Immersive head-mounted displays now allow designers to view immersive images, and recent developments in real-time rendering have encouraged the uptake of virtual reality (VR) head-mounted displays in mainstream practice and design education. This paper presents an experiment on lighting perception using a series of LED lighting conditions in a real space and a virtual representation of those conditions captured using a 360° head-mounted display camera and presented on an HTC Vive Pro HMD. Fifty-three participants were asked to rate each lighting condition by viewing it in a real space (n = 30) or via immersive HDR photographs displayed in a VR HMD (n = 23). The results show that ratings of visual comfort, pleasantness, evenness, contrast and glare are similar between the HTC Vive Pro HMD and our real space when evaluating well-lit scenes, but significant differences emerge in dim and highly contrasted scenes for a number of rating scales.

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