Lighting quality research using rendered images of offices

Forty participants viewed a series of high-quality, colour images of a typical open-plan partitioned office, and rated them for attractiveness. The images were projected at realistic luminances and 33% of full size. The images were geometrically identical, but the outputs of four lighting circuits depicted in the renderings were independently manipulated. Initially, the lighting circuit outputs were random, but a genetic algorithm was used to generate new images that retained features of prior, highly-rated, images. As a result, the images converged on an individual's preferred scene. Luminances in the preferred image were similar to preferred luminances chosen by people in real settings. A sub-set of images was rated on Brightness, Non-Uniformity and Attraction scales. Ratings were significantly related to simple photometric descriptors of the images. In particular, around 50% of the variance in Attraction ratings was predicted by average image luminance and its square, or by average image luminance and a measure of luminance variability.Quarante (40) participants ont visionn\ue9 une s\ue9rie d?images polychromes de haute qualit\ue9 montrant un bureau \ue0 aires ouvertes \ue0 cloisons type, puis les ont cot\ue9es quant \ue0 l?aspect esth\ue9tique. Les images \ue9taient projet\ue9es \ue0 des niveaux d?\ue9clairement r\ue9alistes et \ue0 une \ue9chelle de 33 %. Les images pr\ue9sent\ue9es \ue9taient identique au point de vue g\ue9om\ue9trique, mais on manipulait ind\ue9pendamment les signaux de quatre (4) circuits d?\ue9clairage repr\ue9sent\ue9s par les rendus d?image. \uc0 l'origine, les signaux des circuits d'\ue9clairement \ue9taient al\ue9atoires, mais on a utilis\ue9 un algorithme g\ue9n\ue9tique pour produire de nouvelles images qui comportaient certaines des caract\ue9ristiques des images pr\ue9c\ue9dentes les mieux cot\ue9es. Les images convergeaient donc vers la sc\ue8ne pr\ue9f\ue9r\ue9e d?un participant. Les niveaux d?\ue9clairement de l?image pr\ue9f\ue9r\ue9e se sont r\ue9v\ue9l\ue9s semblables aux niveaux d?\ue9clairement pr\ue9f\ue9r\ue9s choisis par des personnes en situations r\ue9elles. Un sous-ensemble d?images a \ue9t\ue9 cot\ue9 quant aux bar\ue8mes de luminance, de non-uniformit\ue9 et d?attrait (esth\ue9tique). Les cotes ont \ue9t\ue9 corr\ue9l\ue9es de fa\ue7on appr\ue9ciable \ue0 de simples descripteurs photom\ue9triques des images. Plus particuli\ue8rement, environ 50 % de la variance dans les cotes du bar\ue8me de l?attrait (esth\ue9tique) a \ue9t\ue9 pr\ue9dite par le niveau d?\ue9clairement moyen de l?image et son carr\ue9, ou par le niveau d?\ue9clairement moyen de l?image et une mesure de la variabilit\ue9 de l?\ue9clairement.Peer reviewed: YesNRC publication: Ye