The objects in our environment are made of a wide range of materials. The color appearance of the objects is influenced by many factors, including the geometry of the illumination, the shape of the objects, and the reflectance properties of their materials. Only few studies have investigated the effect of material properties on color perception, mostly with stimuli rendered on a computer screen. Here we set out to investigate color perception for real objects made of different materials. The surface properties of the materials ranged from smooth and glossy to matte and corrugated. We tested objects with similar colors made from different materials and objects made from the same material that differed only in color. Observers matched the color appearance of the objects by adjusting the chromaticity and the luminance of a homogeneous, uniformly colored disk presented on a CRT screen. The observers matched the hue of the objects quite accurately. Chroma matches were modulated by the lightness of the objects. For dark objects, chroma was overestimated, while for light objects it was underestimated. For lightness, observers matched the brightest points of the objects excluding highlights. This is a suitable strategy to compensate for variations in surface geometry and illumination.
People often make rapid visual judgments of the properties of surfaces they are going to walk on or touch. How do they do this when the interactions of illumination geometry with 3-D material structure and object shape result in images that inverse optics algorithms cannot resolve without externally imposed constraints? A possibly effective strategy would be to use heuristics based on information that can be gleaned rapidly from retinal images. By using perceptual scaling of a large sample of images, combined with correspondence and canonical correlation analyses, we discovered that material properties, such as roughness, thickness, and undulations, are characterized by specific scales of luminance variations. Using movies, we demonstrate that observers' percepts of these 3-D qualities vary continuously as a function of the relative energy in corresponding 2-D frequency bands. In addition, we show that judgments of roughness, thickness, and undulations are predictably altered by adaptation to dynamic noise at the corresponding scales. These results establish that the scale of local 3-D structure is critical in perceiving material properties, and that relative contrast at particular spatial frequencies is important for perceiving the critical 3-D structure from shading cues, so that cortical mechanisms for estimating material properties could be constructed by combining the parallel outputs of sets of frequency-selective neurons. These results also provide methods for remote sensing of material properties in machine vision, and rapid synthesis, editing and transfer of material properties for computer graphics and animation.
Studies of chromatic discrimination are typically based on homogeneously colored patches. Surfaces of natural objects, however, cannot be characterized by a single color. Instead, they have a chromatic texture, that is, a distribution of different chromaticities. Here we study chromatic discrimination for natural images and synthetic stimuli with a distribution of different chromaticities under various states of adaptation. Discrimination was measured at the adaptation point, where the mean chromaticity of the test stimuli was the same as the chromaticity of the adapting background, and away from the adaptation point. At the adaptation point, discrimination for natural objects resulted in threshold contours that were selectively elongated in a direction of color space matching the chromatic variation of the colors within the natural object. Similar effects occurred for synthetic stimuli. Away from the adaptation point, discrimination thresholds increased and threshold ellipses were elongated along the contrast axis connecting adapting color and test color. Away from the adaptation point, no significant differences between the different stimulus classes were found. The effect of the chromatic texture on discrimination seemed to be masked by the overall increase in discrimination thresholds. Our results show that discrimination of chromatic textures, either synthetic or natural, differs from that of simple uniform patches when the chromatic variation is centered at the adaptation point.
Color discrimination is influenced by chromatic distributions such as they appear on differently illuminated 3D surfaces (T. Hansen, M. Giesel, & K. R. Gegenfurtner, 2008). Here, we measured discrimination thresholds for chromatically variegated stimuli and modeled the data employing a model with multiple chromatic mechanisms. Each mechanism has a differently tuned half-wave-rectified cosine-shaped sensitivity profile centered at a different chromatic direction. To estimate thresholds, the model's responses to a test and a comparison stimulus are determined. A detection variable is calculated by taking the difference of the responses to the two stimuli and by a subsequent nonlinear combination of the responses. The model was fitted to the data presented in T. Hansen et al. (2008) and to data from two new experiments. In the first experiment, we measured discrimination thresholds for stimuli chromatically variegated along a direction orthogonal to the one used in the previous experiments. In the second experiment, we investigated the interplay between chromatic distributions and different mean contrast levels. We found that a model with eight mechanisms accounted for the effect of chromatic variation within the stimuli and provided a better fit to the discrimination thresholds than a four mechanisms model.
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