Abstract
The image intensity depends on the illumination, the reflectance properties of objects but also on the reflectance and absorption properties of any intervening media. We recently showed (Hansmann-Roth & Mamassian, VSS 2016) that dark backgrounds increase perceived gloss of central patches. We hypothesized that this simultaneous gloss contrast induced by the dark background causes a perceptual shift in the luminance range. Highlights on the central patch appeared brighter, inducing an increase in perceived gloss. In the current study we present the participant with glossy objects behind partially-transmissive materials. The transparent layer causes an achromatic color shift and compression in contrast, which can affect the perception of the specular reflections of the object behind the transparent layer. We rendered objects with various gloss levels and presented them behind four different transparent layers with varying reflectance properties ranging from black to white (constant transmittance: 0.5). We conducted a maximum likelihood conjoint measurement experiment (Knoblauch & Maloney, 2012) and investigated the contamination of different transparent layers on perceived gloss. We presented two objects simultaneously and asked our participants to indicate which object appears glossier. We used the additive model of MLCM, assigned perceptual scale values to each gloss level of the object and to each reflectance level of the transparent layer, and modeled the contribution of both features to perceived gloss. Our results indicate a significant contribution of the transparent layer when estimating gloss. Highlights and lowlights are affected most by the lightest and darkest transparent layer respectively. In conclusion, we show that disentangling the transparent layer from the underlying object results in a form of gloss induction. Both, the intensification of the lowlights by the darkest layer and the increase of brightness of the highlights by the lightest layer induce an increase in perceived gloss.
Meeting abstract presented at VSS 2017