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Wenyan Bi, Peiran Jin, Hendrikje Nienborg, Bei Xiao; Manipulating patterns of dynamic deformation elicits the impression of cloth with varying stiffness. Journal of Vision 2019;19(5):18. doi: 10.1167/19.5.18.
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Cloth is a common material, and humans can visually estimate its mechanical properties by observing how it deforms under external forces. Here, we ask whether and how dynamic deformation can affect the perception of mechanical properties of cloth. In Experiment 1, we find that both intrinsic mechanical properties and optical properties affect stiffness perception when the stimuli are presented as images. By contrast, in videos, humans can partially discount the effect of optical appearances and exhibit higher sensitivity to stiffness. We further identified an idiosyncratic deformation pattern (i.e., movement uniformity) to differentiate stiffness, which can be reliably measured by six optical flow features. In Experiment 2, we isolate the deformation by creating dynamic dot stimuli from the 3-D mesh of the cloth. We directly alter the movement pattern by manipulating the uniformity of the displacement vectors on the dot stimuli and show that changing the pattern of dynamic deformation alone can alter the perceived stiffness of cloth in a variety of scene setups. Furthermore, by analyzing optical flow fields extracted from the manipulated dynamic dot stimuli, we confirmed the same six optical flow features can be diagnostic of the degree of stiffness of moving cloth across different scenes. Overall, our study demonstrates that manipulating patterns of dynamic deformation alone can elicit the impression of cloth with varying stiffness, suggesting that the human visual system might rely on the idiosyncratic pattern of dynamic deformation for estimating stiffness.
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