In this paper, we investigated the effects of visual and auditory adaptation on material appearance. The target in this study was metallic perception. First, participants evaluated CG images using sounds and other images. In the experiment, we prepared metallic stimulus under various adaptation conditions with different combinations of metal image, non-metal image, metal sound, and non-metal sound stimuli. After these adaptations, the participants answered "metal" or "non-metal" after viewing a displayed reference image. The reference images were generated by interpolating metal and non-metal images. Next, we analyzed the results and clarified the effects of visual, auditory, and audiovisual adaptations on the metallic perception. For analyzing results, we used a logistic regression analysis based on Bayesian statistics. From the analysis results, we found visual and auditory adaptation effects. On the other hand, we did not find the cross-modal effects of audiovisual adaptation. Finally, we created a model of the linear sum of the visual and audio adaptation effects on metallic material appearance.
The well-known simultaneous contrast effect describes how surrounding surfaces influence lightness perception. Similar contextual effects are ubiquitous in the lightness literature. Contextual effects in gloss perception however, have not yet been studied intensively. Here, we describe two distinct studies that investigate the role of spatial interactions between different glossy materials. In a first study we produced real surfaces that contain two different materials and compared perceived gloss in two conditions: in isolation and in context with a second material. Our results provide strong evidence that the context largely influences perceived gloss. Gloss ratings of identical materials differed depending on the presentation mode. In a second study we wished to quantify the strength of these contextual effects using Maximum likelihood conjoint measurement. We used glossy versions of the simultaneous contrast display and again found strong influences of albedo and gloss of the surroundings on perceived gloss and lightness. Both studies hint towards a profound influence of the context on perceived gloss. Investigating spatial interactions between materials within a scene has largely been studied in the lightness literature but only received moderate attention in the gloss literature. Our results provide confirmatory evidence that perceived gloss is shaped by other materials in the scene.
We propose novel techniques for the evaluation of perceived facial gloss across subjects with varying surface reflections. Given a database of facial skin images from multiple subjects, ordered according to perceived gloss within each subject, we propose a head-tail (least and most glossy image of each subject) selective comparison approach for ordering the entire database. We conducted a two-alternative forced-choice empirical study to compare the facial gloss across subjects within each group. Using the gloss scores of selected candidates and the gloss range of a reference subject, we fit each within-subject gloss range to a global gloss range and quantized the scores into distinct gloss levels. We then conducted another empirical study to validate the quantized gloss levels. The results show that in 90% of the cases, the levels are consistent with human judgments. Based on the database with quantized gloss levels, we develop a max-margin learning model for facial skin gloss estimation. The model relies on gloss related statistics extracted from surface and subsurface reflection images obtained using multimodal photography. The predicted gloss level is decided by the nearest neighbors using the learned scoring function. Performance tests demonstrate that the best performance, with 82% accuracy, is obtained when we combine local statistics from both surface and subsurface reflections.
How do different object properties combine for the purposes of object identification? We developed a paradigm that allows us measure the degree to which human observers rely on one object property (e.g., color) vs. another (e.g., material) when they make forced-choice similarity judgments. On each trial of our experiment, observers viewed a target object paired with two test objects: a material match, that differed from the target only in color (along a green-blue axis) and a color match, that differed from the target only in material (along a glossy-matte axis). Across trials, the target was paired with different combinations of material-match and color-match tests and observers selected the test that appeared more similar to the target. To analyze observer responses, we developed a model (a two-dimensional generalization of the maximum-likelihood difference scaling method) that allows us to recover (1) the color-material weight, reflecting the relative importance of color vs. material in object identification and (2) the underlying positions of the material-match and color-match tests in a perceptual color-material space. Our results reveal large individual differences in the relative weighting of color vs. material.