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The impression of a space depends hugely on the light in the space, more specifically on the intensity, colour, beam shape and position of the light sources in that space. This relation though is very complex. The present study aims at understanding the relation between parameters of a lighting design and the resulting perceptions, focusing on the effect that overall brightness and perceived uniformity of the light in the space have on the perceived atmosphere of that space. Employing high-quality visualisations, we found that atmosphere perception can be accurately described by a second-order polynomial as a function of the two perceptual light attributes. In addition, we evaluated how well objective measures reported in literature predict brightness and perceived uniformity.

The impression of a space depends highly on the illumination in the space, which usually is a combination of electric light and daylight. In the present study, we compared three methodologies to study the influence of electric light and daylight on the perception of the light and the perception of the atmosphere of the space. In two experiments, rating scales were used (with a blocked and a random design, respectively) and in a third experiment the paired-comparison method was used to evaluate the light and the atmosphere of the space. In all experiments, visualizations were used to create differently illuminated spaces. All methodologies showed similar effects of daylight and electric light, which attests to the convergent validity of the research methods. However, the methodologies revealed different effect sizes, rendering the paired-comparison design most sensitive to detect the smallest differences. The results also allowed us to explore the contribution of electric light and daylight in creating an atmosphere. The use of visualizations enabled us to control the luminance of daylight and to disentangle the effects of daylight entering a window from the view from a window. The outcomes show that daylight plays a smaller role than electric light on the perception of light and atmosphere in a space when the luminance of daylight is controlled and there is no view outside.

Complex solid-state lighting systems demand accurate 3D visualization for design, development, and control. In the creation of visualizations, choices in modeling, light simulation, tonemapping, and display affect perceptual accuracy. A series of experiments has uncovered these effects and led to a robust and honest visualization pipeline for indoor lighting scenes.

Among those concerned with practical matters of office design, demonstrations that the work environment affects employees’ well-being and work behaviors are thought to be important to support client decision making. Veitch, Newsham, Boyce, and Jones developed a conceptual model in which lighting appraisal and visual capabilities predicted aesthetic judgments, mood, and performance. This article extends that model to include measures of work engagement, using experimental data originally reported by Newsham, Veitch, Arsenault, and Duval. Structural equation modeling showed strong fit to a model in which lighting appraisals indirectly influenced work engagement through aesthetic judgments and mood. This evidence that providing a satisfactory work environment can contribute to employee effectiveness merits further study by environmental and organizational psychologists.

Performing psychophysical experiments to investigate lighting perception can be expensive and time consuming if complex lighting systems need to be implemented. In this paper, display-based experiments are explored as a cost effective and less time consuming alternative to real-world experiments. The aim of this work is to better understand the upper limit of prediction accuracy that can be achieved when presenting an image on a display rather than the real-world scene. We compare the predictive value of photographs and physically-based renderings on a number of perceptual lighting attributes. It is shown that the photographs convey statistically the same lighting perception as in a real-world scenario. Initial renderings have an inferior performance, but are shown to converge towards the performance of the photographs through iterative improvements.