Estimating mechanical properties of cloth from videos using dense motion trajectories: Human psychophysics and machine learning

Modeling surface color discrimination under different lighting environments using image chromatic statistics and convolutional neural networks

We modeled discrimination thresholds for object colors under different lighting environments [J. Opt. Soc. Am. 35, B244 (2018)]. First, we built models based on chromatic statistics, testing 60 models in total. Second, we trained convolutional neural networks (CNNs), using 160,280 images labeled by either the ground-truth or human responses. No single chromatic statistics model was sufficient to describe human discrimination thresholds across conditions, while human-response-trained CNNs nearly perfectly predicted human thresholds. Guided by region-of-interest analysis of the network, we modified the chromatic statistics models to use only the lower regions of the objects, which substantially improved performance.

Delay and Speed of Visual Feedback of a Keystroke Cause Illusory Heaviness and Stiffness

Imposing a delay between an action (e.g., a limb movement) and its related visual feedback (e.g., a cursor movement on the display) induces a peculiar sensation of heaviness or stiffness. Earlier studies have examined this delay-induced heaviness or stiffness sensation in relation to the non-arbitrary causal relationship between an action and its effect. Here, “non-arbitrary causal relationship” means that an action produces a specific and deterministic pattern of visual feedback; for example, a leftward limb movement consistently and deterministically causes a leftward visual motion. In modern graphical user interfaces, on the other hand, users often control visual information by pressing keys, wherein the relationship between the keystroke and the change in visual information is arbitrary. The present study examined whether the sensation of heaviness, stiffness and bumpiness could be caused when participants' keystroke produced a delayed arbitrary visual feedback. Participants were asked to press and hold down an assigned key to cause temporal luminance changes in a square centered on the display, an arbitrary visual feedback of their keystroke. Not only the onset delay of the temporal luminance change from the participant's keystroke but also the speed of the temporal luminance change were examined as a visual cue to heaviness, stiffness, or bumpiness. In Experiment 1, the participants' task was to give a rating for the strength of the heaviness, stiffness, or bumpiness perceived when they pressed the key. Our results showed that the heaviness and stiffness ratings increased as the delay increased and decreased as the speed increased. To check whether the manipulation of the delay and speed of the visual feedback caused changes in the subjective evaluation of sensorimotor incongruence, in Experiment 2, we asked the participants to give a rating for the sense of agency. The rating scores decreased as the delay increased and increased as the speed increased. The delay and speed influenced the rating scores for the sense of agency in the opposite direction to those for heaviness/stiffness. We discuss that the brain determines the heaviness and stiffness during a keystroke based on internalized statistics relating to the delay and speed of the action feedback.

Perceptual judgments for the softness of materials under indentation

Humans can judge the softness of elastic materials through only visual cues. However, factors contributing to the judgment of visual softness are not yet fully understood. We conducted a psychophysical experiment to determine which factors and motion features contribute to the apparent softness of materials. Observers watched video clips in which materials were indented from the top surface to a certain depth, and reported the apparent softness of the materials. The depth and speed of indentation were systematically manipulated. As physical characteristics of materials, compliance was also controlled. It was found that higher indentation speeds resulted in larger softness rating scores and the variation with the indentation speed was successfully explained by the image motion speed. The indentation depth had a powerful effect on the softness rating scores and the variation with the indentation depth was consistently explained by motion features related to overall deformation. Higher material compliance resulted in higher softness rating scores and these variation with the material compliance can be explained also by overall deformation. We conclude that the brain makes visual judgments about the softness of materials under indentation on the basis of the motion speed and deformation magnitude.

Visual discrimination of optical material properties: A large-scale study

Complex visual processing involved in perceiving the object materials can be better elucidated by taking a variety of research approaches. Sharing stimulus and response data is an effective strategy to make the results of different studies directly comparable and can assist researchers with different backgrounds to jump into the field. Here, we constructed a database containing several sets of material images annotated with visual discrimination performance. We created the material images using physically based computer graphics techniques and conducted psychophysical experiments with them in both laboratory and crowdsourcing settings. The observer's task was to discriminate materials on one of six dimensions (gloss contrast, gloss distinctness of image, translucent vs. opaque, metal vs. plastic, metal vs. glass, and glossy vs. painted). The illumination consistency and object geometry were also varied. We used a nonverbal procedure (an oddity task) applicable for diverse use cases, such as cross-cultural, cross-species, clinical, or developmental studies. Results showed that the material discrimination depended on the illuminations and geometries and that the ability to discriminate the spatial consistency of specular highlights in glossiness perception showed larger individual differences than in other tasks. In addition, analysis of visual features showed that the parameters of higher order color texture statistics can partially, but not completely, explain task performance. The results obtained through crowdsourcing were highly correlated with those obtained in the laboratory, suggesting that our database can be used even when the experimental conditions are not strictly controlled in the laboratory. Several projects using our dataset are underway.

The look and feel of soft are similar across different softness dimensions

The softness of objects can be perceived through several senses. For instance, to judge the softness of a cat's fur, we do not only look at it, we often also run our fingers through its coat. Recently, we have shown that haptically perceived softness covaries with the compliance, viscosity, granularity, and furriness of materials (Dovencioglu, Üstün, Doerschner, & Drewing, 2020). However, it is unknown whether vision can provide similar information about the various aspects of perceived softness. Here, we investigated this question in an experiment with three conditions: in the haptic condition, blindfolded participants explored materials with their hands, in the static visual condition participants were presented with close-up photographs of the same materials, and in the dynamic visual condition participants watched videos of the hand-material interactions that were recorded in the haptic condition. After haptically or visually exploring the materials, participants rated them on various attributes. Our results show a high overall perceptual correspondence among the three experimental conditions. With a few exceptions, this correspondence tended to be strongest between haptic and dynamic visual conditions. These results are discussed with respect to information potentially available through the senses, or through prior experience, when judging the softness of materials.

Recognising the dynamic form of fire

Encoding and recognising complex natural sequences provides a challenge for human vision. We found that observers could recognise a previously presented segment of a video of a hearth fire when embedded in a longer sequence. Recognition performance declined when the test video was spatially inverted, but not when it was hue reversed or temporally reversed. Sampled motion degraded forwards/reversed playback discrimination, indicating observers were sensitive to the asymmetric pattern of motion of flames. For brief targets, performance increased with target length. More generally, performance depended on the relative lengths of the target and embedding sequence. Increased errors with embedded sequence length were driven by positive responses to non-target sequences (false alarms) rather than omissions. Taken together these observations favour interpreting performance in terms of an incremental decision-making model based on a sequential statistical analysis in which evidence accrues for one of two alternatives. We also suggest that prediction could provide a means of providing and evaluating evidence in a sequential analysis model.

Perceptual Properties of the Poisson Effect

When an elastic material (e.g., fabric) is horizontally stretched (or compressed), the material is compressed (or extended) vertically – so-called the Poisson effect. In the different case of the Poisson effect, when an elastic material (e.g., rubber) is vertically squashed, the material is horizontally extended. In both cases, the visual system receives image deformations involving horizontal expansion and vertical compression. How does the brain disentangle the two cases and accurately distinguish stretching from squashing events? Manipulating the relative magnitude of the deformation of a square between horizontal and vertical dimensions in the two-dimensional stimuli, we asked observers to judge the force direction in the stimuli. Specifically, the participants reported whether the square was stretched or squashed. In general, the participant’s judgment was dependent on the relative deformation magnitude. We also checked the anisotropic effect of deformation direction [i.e., horizontal vs. vertical stretching (or squashing)] and found that the participant’s judgment was strongly biased toward horizontal stretching. We also observed that the asymmetric deformation pattern, which indicated the specific context of force direction, was also a strong cue to the force direction judgment. We suggest that the brain judges the force direction in the Poisson effect on the basis of assumptions about the relationship between image deformation and force direction, in addition to the relative image deformation magnitudes between horizontal and vertical dimensions.

Softness and weight from shape: Material properties inferred from local shape features

Object shape is an important cue to material identity and for the estimation of material properties. Shape features can affect material perception at different levels: at a microscale (surface roughness), mesoscale (textures and local object shape), or megascale (global object shape) level. Examples for local shape features include ripples in drapery, clots in viscous liquids, or spiraling creases in twisted objects. Here, we set out to test the role of such shape features on judgments of material properties softness and weight. For this, we created a large number of novel stimuli with varying surface shape features. We show that those features have distinct effects on softness and weight ratings depending on their type, as well as amplitude and frequency, for example, increasing numbers and pointedness of spikes makes objects appear harder and heavier. By also asking participants to name familiar objects, materials, and transformations they associate with our stimuli, we can show that softness and weight judgments do not merely follow from semantic associations between particular stimuli and real-world object shapes. Rather, softness and weight are estimated from surface shape, presumably based on learned heuristics about the relationship between a particular expression of surface features and material properties. In line with this, we show that correlations between perceived softness or weight and surface curvature vary depending on the type of surface feature. We conclude that local shape features have to be considered when testing the effects of shape on the perception of material properties such as softness and weight.

Measuring and Modeling Visual Appearance

In studying visual perception, we seek to develop models of processing that accurately predict perceptual judgments. Much of this work is focused on judgments of discrimination, and there is a large literature concerning models of visual discrimination. There are, however, non-threshold visual judgments, such as judgments of the magnitude of differences between visual stimuli, that provide a means to bridge the gap between threshold and appearance. We describe two such models of suprathreshold judgments, maximum likelihood difference scaling and maximum likelihood conjoint measurement, and review recent literature that has exploited them.

The Veiled Virgin illustrates visual segmentation of shape by cause

How the brain reconstructs three-dimensional object shape from two-dimensional retinal light patterns remains a mystery. Most research has investigated how cues—such as shading, texture, or perspective—help us estimate visible surface points on the outside of objects. However, our findings show the brain achieves much more than this. Observers not only infer the visible outer surface but also the hidden internal structure of objects—seeing “beneath the skin.” Our findings suggest the brain parses shapes’ features according to their physical causes, potentially allowing us to separate a single continuous surface into multiple superimposed depth layers. This ability likely aids our interactions with objects, by indicating which surface locations are firmly supported from the inside and thus suitable for grasping.

Three-dimensional (3D) shape perception is one of the most important functions of vision. It is crucial for many tasks, from object recognition to tool use, and yet how the brain represents shape remains poorly understood. Most theories focus on purely geometrical computations (e.g., estimating depths, curvatures, symmetries). Here, however, we find that shape perception also involves sophisticated inferences that parse shapes into features with distinct causal origins. Inspired by marble sculptures such as Strazza’s The Veiled Virgin (1850), which vividly depict figures swathed in cloth, we created composite shapes by wrapping unfamiliar forms in textile, so that the observable surface relief was the result of complex interactions between the underlying object and overlying fabric. Making sense of such structures requires segmenting the shape based on their causes, to distinguish whether lumps and ridges are due to the shrouded object or to the ripples and folds of the overlying cloth. Three-dimensional scans of the objects with and without the textile provided ground-truth measures of the true physical surface reliefs, against which observers’ judgments could be compared. In a virtual painting task, participants indicated which surface ridges appeared to be caused by the hidden object and which were due to the drapery. In another experiment, participants indicated the perceived depth profile of both surface layers. Their responses reveal that they can robustly distinguish features belonging to the textile from those due to the underlying object. Together, these findings reveal the operation of visual shape-segmentation processes that parse shapes based on their causal origin.

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.

FleXeen: Visually Manipulating Perceived Fabric Bending Stiffness in Spatial Augmented Reality

The appearance of fabric motion is suggested to affect the human perception of bending stiffness. This study presents a novel spatial augmented reality, or projection mapping, approach that can visually manipulate the perceived bending stiffness of a fabric. Particularly, we proposed a flow enhancement method that can change the apparent fabric motion by using a simple optical flow analysis technique rather than complex physical simulations for interactive applications. Through a psychophysical experiment, we investigated the relationship between the magnification factor of our flow enhancement and the perceived bending stiffness of a fabric. Furthermore, we constructed a prototype application system that allows users to control the stiffness of a fabric without changing the actual physical fabric. By evaluating the prototype, we confirmed that the proposed technique can manipulate the perceived stiffness of various materials (i.e., cotton, polyester, and mixed cotton and linen) at an average accuracy of 90.3 percent.

Visual assessment of causality in the Poisson effect

When a material is stretched along a spatial axis, it is causally compressed along the orthogonal axis, as quantified in the Poisson effect. The present study examined how human observers assess this causality. Stimuli were video clips of a white rectangular region that was horizontally stretched while it was vertically compressed, with spatially sinusoidal modulation of the magnitude of vertical compressions. It was found that the Poisson’s ratio—a well-defined index of the Poisson effect—was not an explanatory factor for the degree of reported causality. Instead, reported causality was explained by image features related to deformation magnitudes. Comparing a material’s shape before and after deformation was not always required for the causality assessment. This suggests that human observers determine causality in the Poisson effect by using heuristics based on image features not necessarily related to the physical properties of the material.

Visual communication of how fabrics feel

Although product photos and movies are abundantly present in online shopping environments, little is known about how much of the real product experience they capture. While previous studies have shown that movies or interactive imagery give users the impression that these communication forms are more effective, there are no studies addressing this issue quantitatively. We used nine different samples of jeans, because in general fabrics represent a large and interesting product category and specifically because jeans can visually be rather similar while haptically be rather different. In the first experiment we let observers match a haptic stimulus to a visual representation and found that movies were more informative about how objects would feel than photos. In a second experiment we wanted to confirm this finding by using a different experimental paradigm that we deemed a better general paradigm for future studies on this topic: correlations of pairwise similarity ratings. However, the beneficial effect of the movies was absent when using this new paradigm. In the third experiment we investigated this issue by letting people visually observe other people in making haptic similarity judgments. Here, we did find a significant correlation between haptic and visual data. Together, the three experiments suggest that there is a small but significant effect of movies over photos (Experiment 1) but at the same time a significant difference between visual representations and visually perceiving products in reality (Experiments 2 and 3). This finding suggests a substantial theoretical potential for decreasing the gap between virtual and real product presentation.

Visual perception of shape-transforming processes: 'Shape Scission'

Shape-deforming processes (e.g., squashing, bending, twisting) can radically alter objects' shapes. After such a transformation, some features are due to the object's original form, while others are due to the transformation, yet it is challenging to separate the two. We tested whether observers can distinguish the causal origin of different features, teasing apart the characteristics of the original shape from those imposed by transformations, a process we call 'shape scission'. Using computer graphics, we created 8 unfamiliar objects and subjected each to 8 transformations (e.g., "twisted", "inflated", "melted"). One group of participants named transformations consistently. A second group arranged cards depicting the objects into classes according to either (i) the original shape or (ii) the type of transformation. They could do this almost perfectly, suggesting that they readily distinguish the causal origin of shape features. Another group used a digital painting interface to indicate which locations on the objects appeared transformed, with responses suggesting they can localise features caused by transformations. Finally, we parametrically varied the magnitude of the transformations, and asked another group to rate the degree of transformation. Ratings correlated strongly with transformation magnitude with a tendency to overestimate small magnitudes. Responses were predicted by both the magnitude and area affected by the transformation. Together, the findings suggest that observers can scission object shapes into original shape and transformation features and access the resulting representational layers at will.

Linear Motion Coverage as a Determinant of Transparent Liquid Perception

When a transparent liquid flows, the background image behind the flow dynamically deforms due to light refraction. The dynamic deformations of a background image (dynamic image deformations) are one of the visual features used by the visual system to infer the existence of a transparent liquid flow. Although previous studies have discussed the role of the narrow band components of the spatiotemporal deformation frequency, it was still unclear whether motion signals, one of the constituents of dynamic image deformations, were the determinant of the perception of a transparent liquid. Manipulating the flow speed of image deformation, which is a critical parameter for changing motion signals in dynamic image deformations, we asked observers to judge whether a transparent liquid was included in the clips or not. We found that the proportions of reporting that they saw a transparent liquid increased with the flow speed of image deformations. Analyzing motion signals of the stimulus clips, we found that the faster the flow of image deformations the fewer linear motion signals were contained. The results indicate that the perception of a transparent liquid arises when the dynamic image deformations contain fewer linear motion signals.