Seeing jelly

Abstract

Taking advantage of computer graphics technologies, recent psychophysical study on material perception has revealed how human vision estimates the mechanical property of objects, such as liquid viscosity, from image features. Here we consider how human perceive another important mechanical material property-elasticity. We simulated scenes in which a transparent cube falling on the floor, while manipulating the elasticity of the cube. We asked observers to rate the elasticity using a 5-point scale. Human observers were quite sensitive to the change in the simulated elasticity of the cube. In comparison with the original condition, the elasticity was overestimated when only the cube contour deformation was visible, whereas underestimated when the cube contour deformation was hidden and only internal optical deformation was visible. The effects of contour and optical deformations on elasticity rating were almost the same when the observers viewed white noise fields that reproduced the optical flow fields of the cube movies. Increasing frame duration (which decreased image speed) also increased the apparent elasticity. These results suggest that human elasticity judgment is based on the pattern of image motion arising from contour and optical deformations. This scientific finding may provide a hint for computationally efficient rendering of perceptually realistic dynamic scenes.

Inferring the stiffness of unfamiliar objects from optical, shape, and motion cues

“…They showed observers animated scenes in which a rigid cylinder interacted with cubes of varying stiffness and optical appearance, either (a) by pushing into the cubes from above (i.e., indenting the cubes) or (b) by retracting from the rear edge of the cubes (i.e., setting the cubes into reverberating motion). In line with the findings by Kawabe and Nishida (2016), perceived stiffness varied along with the deformation of the cubes' shape in both scenarios (i.e., either with the magnitude of the penetration of the cylinder into the cube or with the amount of shape change across the cube's motion; also see Fakhourny, Culmer, & Henson, 2015). Then, Paulun et al (2017) obtained stiffness ratings for the cubes in the first scenario (cylinder pushing into cube) and in the second scenario (cube set into motion) when rendered with different optical materials, ranging from hard (e.g., steel, copper) to soft (e.g., latex, velvet).…”

“…This was true even when the deformations had to be inferred from the motion of a random noise field. Kawabe and Nishida (2016) also demonstrated the role of motion for the perceived stiffness: when shape information was removed by showing only the internal motion of the cube, observers were still able to infer the different stiffness levels from the different motion patterns. Finally, perceived stiffness increased with increasing animation speed (also see the related work on inference of liquid characteristics from image motion speed and smoothness of motion flow; Kawabe, Maruya, Fleming, & Nishida, 2015).…”

“…In other scenarios-with familiar base shapes or animated transformations in dynamic scenes (e.g., Experiment 4; Paulun et al, 2017)-shape cues gain more weight. For example, animating the transformations strengthens the perceived changes in shape: a number of previous studies demonstrate a key role of motion cues in the estimation of material properties (e.g., Bi & Xiao, 2016;Bouman, Xiao, Battaglia, & Freeman, 2013;Kawabe et al, 2015;Kawabe & Nishida, 2016;Masuda et al, 2013;Masuda, Matsubara, Utsumi, & Wada, 2015). Consequently, in these scenarios, shape cues dominate estimations of stiffness.…”

“…In a similar paradigm, in which participants also rated the stiffness of a free-falling transparent cube, Kawabe and Nishida (2016) showed that differences in stiffness could be estimated from shape contour deformation alone (even though contour stimuli were generally rated softer compared with the full renderings of the cubes). This was true even when the deformations had to be inferred from the motion of a random noise field.…”

Image deformation as a cue to material category judgment

“…10]. Moreover, the human visual system can utilize the dynamic pattern of image deformation due to refraction as a cue to a material’s elasticity11.…”