Generative constraints on image cues for perceived gloss

Image structure is generated by distinct physical sources that include 3-D surface geometry, surface reflectance, and the light field. A fundamental problem in midlevel vision involves understanding how, and how well, the visual system separates images into their underlying sources. A large body of recent work has shown that the perception of gloss exhibits significant dependencies on both 3-D surface geometry and the light field in which the surface is embedded. We recently proposed that these dependencies arise from the visual system relying on a restricted set of dimensions of specular image structure that are heuristically used to estimate surface gloss (Marlow, Kim, & Anderson, 2012). Here, we report a series of studies that manipulate surface geometry and the structure of the light field to prospectively test whether these image cues predict perceived gloss for a broad range of surface geometries and light fields. We identify generative constraints on each of our proposed cues that allow us to predict which cue will vary most for a given surface geometry, reflectance function, and light field. Our psychophysical data reveal that our generative manipulations succeed in promoting the significance of the intended cue, which in turn increases their predictive value in observers' judgments of gloss. Our results suggest that the perception of gloss in static, monocular images relies on a heuristic weighting of cues to specular image structure, and offer a unified explanation of why surface geometry and the light field modulate perceived gloss.