Predicting lightness judgments from luminance distributions of matte and glossy virtual objects M Toscani, M Valsecchi, M D Dilger, A Zirbes, K R Gegenfurtner |
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Abteilung Allgemeine Psychologie, Justus-Liebig Universität Giessen, Germany
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| Humans are able to estimate the reflective properties of a surface (albedo) of an object despite the large variability in the reflected light due to shading. We investigated which statistics of the luminance distribution of matte and glossy three-dimensional virtual objects are used to estimate albedo. Seven naive observers were asked to sort six objects in an achromatic virtual scene in terms of their albedo. The objects were uniformly spaced on a horizontal plane under a directional diffuse illuminant. Six different reflectances have been chosen for the objects to allow better than chance, but not perfect discrimination performance. The position of the objects in the scene and their reflectances were balanced over trials. Observers were significantly better in ranking matte objects (50% correct) than glossy ones (33% correct). The physical ranking of matte objects was best predicted by the maximum of the luminance distribution whereas the best predictor for the glossy objects was the mean of the distribution. Observers seemed to exploit these optimal cues: their rankings were mainly based on the maximum and the mean of the luminance distributions for the matte objects and dominated by the mean for the glossy ones. |
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