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Poster session 7
Time: 29/Aug/2019: 11:00am-12:30pm · Location: Jubileumzaal
Visual inference for warm/cold perception of surfaces
1NTT Communication Science Labs, NTT Corporation, Japan; 2Toyohashi University of Technology, Japan; 3The University of Electro-Communications, Japan; 4Kyoto University of Education, Japan
Humans can make warm/cold judgments based on the sight of a surface only. This process presumably involves inference of thermal experience from visual information. As there is a long-held belief that reddish colors induce warm feelings while bluish colors induce cold feelings, we aim to examine whether and how color information relates to warm/cold perception of surfaces. Here we asked participants to give warm/cold ratings to 1934 color photographs of surfaces from various material categories and analyzed color histograms of these images in L*a*b* color space. We used L-1 regularized regression and multiple-domain adaptation techniques with pre-defined image statistics and regions in color histogram as predictors to examine the contribution from color features. We found that color features can explain about 30-40% of the variance in warm/cold ratings. The most influential ones are mean values in a* channel (red-green) and b* channel (yellow-blue) and colors with hue angles between 45-90 degree (orange-yellow). Inclusion of the knowledge of material-temperature association (e.g. metal is cold) could increase the explanation power to 55-60%. These findings indicate that the visual inference process for warm/cold perception of surfaces depends on low-level color statistics and cognitive factors such as the knowledge of color-temperature / material-temperature correspondences.
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