Effect of Low‐level Visual Details in Perception of Deformation

Abstract

Figure 1: Frames taken from two stimuli. They are rendered from a physically based simulation of deformable sphere models with differing Young's Modulus. We combine different levels of contrast and spatial frequency to create 25 different checkerboard textures, two of which are shown above. We further study how backgrounds can influence the effect of low-level visual details using stimuli like the lower one. AbstractWe quantitatively measure how different low-level visual details can influence people's perceived stiffness of a deformable sphere under physically based simulation. The result can be used to create a metric for artists in designing textures to enhance or reduce the stiffness perceived by a viewer. We use a checkerboard texture to render the simulation of a free falling sphere that collides with the ground and bounces up. We vary the spatial frequency and contrast of the checkerboard pattern according to results seen in a previous study on the Spatial-Temporal Contrast Sensitivity Function (CSF). We find that checkerboard pattern with certain combinations of spatial frequency and contrast can reduce the perceived stiffness. We also add a high contrast checkerboard background to study how complex backgrounds can influence the effect of low-level details in textures of foreground objects. Our study shows that the effect of low-level visual details in foreground objects observed previously disappears in this situation. This indicates the importance of background, even if it is static.

Shape, motion, and optical cues to stiffness of elastic objects

“…For example, where the material yields lower local contrast, the optic flow information will be sparser, leading to more noisy estimates of the motion cues, and a correspondingly weaker estimate of the softness. Similarly, translucency or texture may facilitate the detection of deformation within the object and along its contours, as suggested by previous studies (Han & Keyser, 2016;Kawabe & Nishida, 2016). Due to our experimental design, such low-level influence would lead to an unsystematic interaction between optical properties and deformation as we found in our data.…”

“…They showed that high-level properties have little influence on the perception of deformation-for example, the deformation of a sphere is detected equally likely when the sphere has the optical appearance of a soccer ball or that of a billiard ball (Han & Keyser, 2015). In contrast, the detection of deformation may be facilitated through the low-level features of the texture, like contrast and spatial frequency (Han & Keyser, 2016). Scenes in which an elastic object falls down are in some sense less complex because the external force (gravity) is at least potentially known to the observer-as we are highly familiar with the acceleration of falling objects.…”

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

“…Material merely played a role by modulating the extent to which the shape deformation could be perceived (e.g., materials with rich texture show more details of the deformation; therefore, objects were perceived as softer). Han and Keyser (2016) support this notion by demonstrating that dropping balls were perceived as softer when their checkerboard texture (defined by contrast and spatial frequency) allowed for more details of the shape deformation to be seen. Consequently, both studies assign a rather small weight to optical material cues while showing that shape cues are relatively strong in determining perceived stiffness.…”

Perceptual evaluation of liquid simulation methods

“…While there are interesting studies that investigate individual visual stimuli (Han and Keyser 2016) and the in uence of di erent rendering methods for liquid simulations (Bojrab et al 2013), our goal is to calculate the perceptual scores for uid simulations on a high-level from animations produced with di erent simulation ACM Transactions on Graphics,Vol. 36,No.…”

“…While there are interesting studies that investigate individual visual stimuli (Han and Keyser 2016) and the in uence of di erent rendering methods for liquid simulations (Bojrab et al 2013), our goal is to calculate the perceptual scores for uid simulations on a high-level from animations produced with di erent simulation methods. We will demonstrate that a robust perceptual evaluation framework can be realized using crowd-sourced user studies that utilize carefully chosen simulation setups and a reference video.…”