Abstract
In the simultaneous contrast effect, lightness judgments of a central patch are affected by surrounding surfaces of different luminance. Similar contextual effects in gloss perception have not been extensively studied yet because past experiments have mainly focused on only one material property (Fleming et al., 2003; Doerschner et al., 2010). We used a Maximum Likelihood Conjoint Measurement (Luce & Tukey, 1964; Knoblauch & Maloney, 2012, Chapt. 8) procedure that allows us to quantify simultaneously how two different contextual features (luminance and gloss) can potentially influence perceived lightness and gloss of the central surface. We rendered a glossy mid gray surface as the center and presented it surrounded by various backgrounds. Background images were chosen randomly out of 25 possible images (5 luminance levels × 5 gloss levels). In two experiments participants were presented with two images consecutively and they were either asked to indicate which center was lighter (Experiment 1) or which center was glossier (Experiment 2). We used the additive model of MLCM, assigned perceptual scale values to each lightness and gloss level of the background, and modeled the contribution of both features to the central surface. We found the standard simultaneous contrast when judging the lightness of the center. A lighter background produced a darker appearance of the center. Having a glossy background enhanced a little this simultaneous contrast. For gloss judgments, we found a strong assimilation effect: perceived gloss of the center increased with glossy backgrounds. In addition, participants could not ignore the lightness of the background when judging gloss. Lighter backgrounds reduced perceived gloss of the center, indicating that participants are influenced by the simultaneous lightness contrast when judging gloss. To conclude, conjoint measurements lead us to a better understanding of contextual effects in gloss perception and the role of gloss in the standard simultaneous contrast.
Meeting abstract presented at VSS 2016