Lightness identification of patterned three-dimensional, real objects.

Abstract

Conventional studies of lightness constancy have almost exclusively used flat plain stimuli and have shown that lightness matches across illuminants cannot be explained by physical matches of reflectance or luminance. The perceptual qualities that underlie lightness judgments still remain largely unknown. Real objects are often 3-D and patterned, giving additional cues for identification. We examine the perceptual strategies that underlie material identification of real objects. Stimuli were randomly crumpled papers printed with achromatic patterns with precisely calibrated mean reflectance and reflectance contrast, placed in backgrounds under varying levels of illumination. Observers were asked to identify objects based on physical reflectance differences. Reflectance identification functions were simulated by simple models that perform object identification based on dissimilarities in perceived brightness (luminance dissimilarity modified by light adaptation) or perceived contrast (contrast dissimilarity modified by mean luminance). The reflectance identification results were also recreated in two control experiments, using identical stimuli conditions, where choices were based explicitly on dissimilarities in perceived brightness or contrast. Rather than a reverse optics model of lightness perception where observers first estimate illuminant intensity and then extract relative lightness by discounting the illuminant, this study supports the use of simple percepts such as brightness and contrast.