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Time will tell: Material surface cues for the visual perception of material ageing Insights from psychophysics, online experiments, image processing and a science festivalDe Korte, Elisabeth M. January 2022 (has links)
This thesis explores the visual perception of material change over time, a novel topic that has received little attention so far. We aimed to understand the material surface features and mental representations associated with material change over time by the human visual system, and possibly wider cognitive systems. To this end, we performed a series of experiments with varying methodologies. These included a psychophysics experiment, online experiments, and data collection during a science festival. The latter showed that the general public mentioned “Faded (colour)” most often to describe material change over time and that specific material surface change features clustered around specific materials. In another experiment, material type, but not colour or the geometrical distribution, had a significant effect on perceived material change. Other experiments partially contradicted this finding. It was found that perceived material type showed a significant, non-linear association with perceived material change, replicating earlier findings on the effect of material type. In contrast, material surface lightness, a constituent of colour, was associated with perceived material change. The same held for components of the geometrical distribution. They showed a minor contribution to the perception of material change, but a major one to perceived material type. Together, our findings suggest that the human visual system seems to use constituents of material surface colour as a cue to material change over time. The geometrical distribution seems to play a minor role. Although these contributions may vary with material type, as our findings showed that material type affected the perception of material change over time. / DyViTo (Dynamics in Vision and Touch) has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No 765121
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