Perception of elasticity in the kinetic illusory object with phase differences in inducer motion

Effects of visual and visual-haptic perception of material rigidity on reaching and grasping in the course of development

The development of material property perception for grasping objects is not well explored during early childhood. Therefore, we investigated infants', 3-year-old children's, and adults' unimanual grasping behavior and reaching kinematics for objects of different rigidity using a 3D motion capture system. In Experiment 1, 11-month-old infants and for purposes of comparison adults, and in Experiment 2, 3-year old children were encouraged to lift relatively heavy objects with one of two handles differing in rigidity after visual (Condition 1) and visual-haptic exploration (Condition 2). Experiment 1 revealed that 11-months-olds, after visual object exploration, showed no significant material preference, and thus did not consider the material to facilitate grasping. After visual-haptic object exploration and when grasping the contralateral handles, infants showed an unexpected preference for the soft handles, which were harder to use to lift the object. In contrast, adults generally grasped the rigid handle exploiting their knowledge about efficient and functional grasping in both conditions. Reaching kinematics were barely affected by rigidity, but rather by condition and age. Experiment 2 revealed that 3-year-olds no longer exhibit a preference for grasping soft handles, but still no adult-like preference for rigid handles in both conditions. This suggests that material rigidity plays a minor role in infants' grasping behavior when only visual material information is available. Also, 3-year-olds seem to be on an intermediate level in the development from (1) preferring the pleasant sensation of a soft fabric, to (2) preferring the efficient rigid handle.

Visually inferring elasticity from the motion trajectory of bouncing cubes

Visually inferring the elasticity of a bouncing object poses a challenge to the visual system: The observable behavior of the object depends on its elasticity but also on extrinsic factors, such as its initial position and velocity. Estimating elasticity requires disentangling these different contributions to the observed motion. We created 2-second simulations of a cube bouncing in a room and varied the cube's elasticity in 10 steps. The cube's initial position, orientation, and velocity were varied randomly to gain three random samples for each level of elasticity. We systematically limited the visual information by creating three versions of each stimulus: (a) a full rendering of the scene, (b) the cube in a completely black environment, and (c) a rigid version of the cube following the same trajectories but without rotating or deforming (also in a completely black environment). Thirteen observers rated the apparent elasticity of the cubes and the typicality of their motion. Generally, stimuli were judged as less typical if they showed rigid motion without rotations, highly elastic cubes, or unlikely events. Overall, elasticity judgments correlated strongly with the true elasticity but did not show perfect constancy. Yet, importantly, we found similar results for all three stimulus conditions, despite significant differences in their apparent typicality. This suggests that the trajectory alone contains the information required to make elasticity judgments.

A Computational Mechanism for Seeing Dynamic Deformation

Human observers perceptually discriminate the dynamic deformation of materials in the real world. However, the psychophysical and neural mechanisms responsible for the perception of dynamic deformation have not been fully elucidated. By using a deforming bar as the stimulus, we showed that the spatial frequency of deformation was a critical determinant of deformation perception. Simulating the response of direction-selective units (i.e., MT pattern motion cells) to stimuli, we found that the perception of dynamic deformation was well explained by assuming a higher-order mechanism monitoring the spatial pattern of direction responses. Our model with the higher-order mechanism also successfully explained the appearance of a visual illusion wherein a static bar apparently deforms against a tilted drifting grating. In particular, it was the lower spatial frequencies in this pattern that strongly contributed to the deformation perception. Finally, by manipulating the luminance of the static bar, we observed that the mechanism for the illusory deformation was more sensitive to luminance than contrast cues.

Motion Perception: From Detection to Interpretation

Visual motion processing can be conceptually divided into two levels. In the lower level, local motion signals are detected by spatiotemporal-frequency-selective sensors and then integrated into a motion vector flow. Although the model based on V1-MT physiology provides a good computational framework for this level of processing, it needs to be updated to fully explain psychophysical findings about motion perception, including complex motion signal interactions in the spatiotemporal-frequency and space domains. In the higher level, the velocity map is interpreted. Although there are many motion interpretation processes, we highlight the recent progress in research on the perception of material (e.g., specular reflection, liquid viscosity) and on animacy perception. We then consider possible linking mechanisms of the two levels and propose intrinsic flow decomposition as the key problem. To provide insights into computational mechanisms of motion perception, in addition to psychophysics and neurosciences, we review machine vision studies seeking to solve similar problems.

Estimating Tactile Perception by Observing Explorative Hand Motion of Others

When we acquire tactile information about an object's surface, we actively move our hands. Past studies have shown a correlation between participants' (i.e., touchers') hand motion in tactile exploration and the evaluated tactile attributes of the object, which suggests that tactile perception can be estimated from statistical analysis of touchers' hand motion. Though it has been reported that the statistical analysis of hand motion can indeed estimate tactile perception, whether humans can estimate tactile perception by observing the hand motion of others remains unclear. To investigate this, we conducted experiments wherein observers watched point-light moving hands of touchers in tactile exploration and evaluated the material being touched. Our results show that, although observers' estimation of touchers' perception was not accurate, observers extracted information from touchers' hand motion for estimation, and the correlations within observers' estimation were high. These results suggest that human observers can estimate tactile perception through visual observation of the hand motion of others by adopting common strategies about the relationships between touchers' hand motion and tactile perception.

Dynamic Volume Completion and Deformation

A new class of dynamic volume completion is introduced, where image elements (e.g., occluding semi-ellipses placed at the edge of an object) can link across a gap between two or more objects, leading to the perception of illusory volumes that deform as those image elements are set into relative motion. These new demonstrations provide further evidence that volume completion is not dictated solely by contour relatability constraints, but is instead a dynamic process of 3D shape construction that also takes into account dynamic cues to object shape, even in the absence of any contour relatability whatsoever.

What Property of the Contour of a Deforming Region Biases Percepts toward Liquid?

Human observers can perceive the existence of a transparent surface from dynamic image deformation. They can also easily discriminate a transparent solid material such as plastic and glass from a transparent fluid one such as water and shampoo just by viewing them. However, the image information required for material discrimination of this sort is still unclear. A liquid changes its contour shape non-rigidly. We therefore examined whether additional properties of the contour of a deformation-defined region, which indicated contour non-rigidity, biased percepts of the region toward liquid materials. Our stimuli had a translating circular region wherein a natural texture image was deformed at the spatiotemporal deformation frequency that was optimal for the perception of a transparent layer. In Experiment 1, we dynamically deformed the contour of the circular region and found that large deformation of the contour biased the percept toward liquid. In Experiment 2, we manipulated the blurriness of the contour and observed that a strongly blurred contour biased percepts toward liquid. Taken together, the results suggest that a deforming region lacking a discrete contour biases percepts toward liquid.

Eleven-month-old infants infer differences in the hardness of object surfaces from observation of penetration events

Previous studies have shown different developmental trajectories for object recognition of solid and non-solid objects. However, there is no evidence as to whether infants have expectations regarding certain attributes of objects, such as surface hardness, in the absence of tactile information. In the present study, we examined infants’ perception of the hardness of object surfaces from visually presented penetration events using the familiarization–novelty preference procedure. Experiment 1 showed that by 11 months old infants distinguished a relatively soft surface from a crusty surface based on changes in the velocity of a moving object as the moving object penetrated the surface of the target object. Experiment 2 ruled out the possibility that infants were merely sensitive to differences in the velocity changes in the stimuli.