Factors Influencing the Detection of Spatially-Varying Surface Gloss

In this study, we investigate the ability of human observers to detect spatial inhomogeneities in the glossiness of a surface and how the performance in this task depends on several context factors. We used computer-generated stimuli showing a single object in three-dimensional space whose surface was split into two spatial areas with different microscale smoothness. The context factors were the kind of illumination, the object’s shape, the availability of motion information, the degree of edge blurring, the spatial proportions between the two areas of different smoothness, and the general smoothness level. Detection thresholds were determined using a two-alternative forced choice (2AFC) task implemented in a double random staircase procedure, where the subjects had to indicate for each stimulus whether or not the surface appears to have a spatially uniform material. We found evidence that two different cues are used for this task: luminance differences and differences in highlight properties between areas of different microscale smoothness. While the visual system seems to be highly sensitive in detecting gloss differences based on luminance contrast information, detection thresholds were considerably higher when the judgment was mainly based on differences in highlight features, such as their size, intensity, and sharpness.