Through a series of experiments, we have measured the extent to which 3D visualizations of a variety of lighting conditions in an indoor environment can accurately convey primary perceptual attributes. Our goal was to build and rigorously test perceptually accurate visual simulation tooling, which can be valuable in the design, development, and control of complex digital solid-state lighting systems. The experiments included assessments of lighting-related perceptual attributes in a real-world environment and a variety of virtual presentations. Iteratively improving choices in modeling, light simulation, tonemapping, and display led to a robust and honest visualization pipeline that provides a perceptual match of the real world for most perceptual attributes and that is nearly equivalent in perceptual performance to photography. One persistently difficult attribute is scene brightness, as observers consistently overestimate the brightness of dimmed scenes in virtual presentations. In this paper we explain the experimental 3D visualization pipeline variables that were addressed, the perceptual attributes that were measured, and the statistical methods that were applied to evaluate our success.

Visual adaptation (and especially dark adaptation) has been studied extensively in the past, however, mainly addressing adaptation to fully dark backgrounds. At this stage, it is unclear whether these results are not too simple to be applied to complex situations, such as predicting adaptation of a motorist driving at night. To fill this gap we set up a study investigating how spatially complex backgrounds influence temporal dark adaptation. Our results showed that dark adaptation to spatially complex backgrounds leads to much longer adaptation times than dark adaptation to spatially uniform backgrounds. We conclude therefore that the adaptation models based on past studies overestimate the visual system's sensitivity to detect luminance variations in spatially complex environments. Our results also showed large variations in adaptation times when varying the degree of spatial complexity of the background. Hence, we may conclude that it is important to take into account models that are based on spatially complex backgrounds when predicting dark adaptation for complex environments.

Rendered images of varied lighting conditions in a virtual environment have been shown to provide a perceptually accurate visual impression of those in a real environment, providing a valuable tool set for the development and communication of new lighting solutions. In order to further improve this tool set, an experiment was conducted to assess the impact of image size and viewing interactivity on perceptual accuracy. It was found that a high-quality TVsized display outperforms a smaller laptop screen and a larger projected image on most measures, and that the expected value of the interactive panoramic format was masked by the fatigue of using it repeatedly.