From luminance to brightness: A data-driven approach to support brightness assessments in open plan offices

Abstract

People can instantly distinguish a brighter from a darker environment, but it is still unknown how to estimate brightness from the luminance distribution in complex visual scenes. In this study, we performed a meta-analysis of three experiments in which participants assessed brightness in an open plan office environment. Experiment 1 varied the luminance distribution on the wall, Experiment 2 varied the desk illuminance and Experiment 3 varied the ceiling illumination. Correlating various measures derived from high-resolution luminance images with participants’ brightness ratings, we investigated to what extent brightness could be predicted. In particular, we focused on 19 different luminance distribution characteristics calculated over 11 different areas of the visual field. In line with earlier work, participants could be grouped in two categories, one consisting of participants who substantially and consistently varied in their brightness assessments for the different settings, and the other consisting of participants who responded more evenly, regardless of the setting. Based on the brightness-responsive group of participants, brightness could be best modelled with the logarithm of the median luminance calculated over a 60° horizontal band in the field of view or with the logarithm of the 95th percentile over the median calculated over the 40° horizontal band, explaining, respectively, 38% and 35% of the variance in brightness perception.