Visual motion and the perception of surface material

Visual softness perception can be manipulated through exploratory procedures

Both visual and haptic softness perception have recently been shown to have multiple dimensions, such as deformability, granularity, fluidity, surface softness, and roughness. During haptic exploration, people adjust their hand motions (exploratory procedures, EPs) based on the material qualities of the object and the particular information they intend to acquire. Some of these EPs are also shown to be associated with perceived softness dimensions, for example, stroking a silk blouse or applying pressure to a pillow. Here, we aimed to investigate whether we can manipulate observers' judgments about softness attributes through exposure to videos of others performing various EPs on everyday soft materials. In two experiments, participants watched two videos of the same material: one with a corresponding EP and the other without correspondence; then, they judged these materials based on 12 softness-related adjectives (semantic differentiation method). The results of the second experiment suggested that when the EP is congruent with the dimension from which the material is chosen, the ratings for the adjectives from the same dimension are higher than the incongruent EP. This study provides evidence that participants can assess material properties from optic and mechanical cues without needing haptic signals. Additionally, our findings indicate that manipulating the hand motion can selectively facilitate material-related judgments.

Effect of material properties on emotion: a virtual reality study

Introduction

Designers know that part of the appreciation of a product comes from the properties of its materials. These materials define the object's appearance and produce emotional reactions that can influence the act of purchase. Although known and observed as important, the affective level of a material remains difficult to assess. While many studies have been conducted regarding material colors, here we focus on two material properties that drive how light is reflected by the object: its metalness and smoothness. In this context, this work aims to study the influence of these properties on the induced emotional response.

Method

We conducted a perceptual user study in virtual reality, allowing participants to visualize and manipulate a neutral object - a mug. We generated 16 material effects by varying it metalness and smoothness characteristics. The emotional reactions produced by the 16 mugs were evaluated on a panel of 29 people using James Russel's circumplex model, for an emotional measurement through two dimensions: arousal (from low to high) and valence (from negative to positive). This scale, used here through VR users' declarative statements allowed us to order their emotional preferences between all the virtual mugs.

Result

Statistical results show significant positive effects of both metalness and smoothness on arousal and valence. Using image processing features, we show that this positive effect is linked to the increasing strength (i.e., sharpness and contrast) of the specular reflections induced by these material properties.

Discussion

The present work is the first to establish this strong relationship between specular reflections induced by material properties and aroused emotions.

Color and gloss constancy under diverse lighting environments

When we look at an object, we simultaneously see how glossy or matte it is, how light or dark, and what color. Yet, at each point on the object's surface, both diffuse and specular reflections are mixed in different proportions, resulting in substantial spatial chromatic and luminance variations. To further complicate matters, this pattern changes radically when the object is viewed under different lighting conditions. The purpose of this study was to simultaneously measure our ability to judge color and gloss using an image set capturing diverse object and illuminant properties. Participants adjusted the hue, lightness, chroma, and specular reflectance of a reference object so that it appeared to be made of the same material as a test object. Critically, the two objects were presented under different lighting environments. We found that hue matches were highly accurate, except for under a chromatically atypical illuminant. Chroma and lightness constancy were generally poor, but these failures correlated well with simple image statistics. Gloss constancy was particularly poor, and these failures were only partially explained by reflection contrast. Importantly, across all measures, participants were highly consistent with one another in their deviations from constancy. Although color and gloss constancy hold well in simple conditions, the variety of lighting and shape in the real world presents significant challenges to our visual system's ability to judge intrinsic material properties.

Unmet expectations about material properties delay perceptual decisions

Based on our expectations about material properties, we can implicitly predict an object's future states, e.g., a wine glass falling down will break when it hits the ground. How these expectations affect relatively low-level perceptual decisions, however, has not been systematically studied previously. To seek an answer to this question, we conducted a behavioral experiment using animations of various familiar objects (e.g., key, wine glass, etc.) freely falling and hitting the ground. During a training session, participants first built expectations about the dynamic properties of those objects. Half of the participants (N = 28) built expectations consistent with their daily lives (e.g., a key bounces rigidly), whereas the other half learned an atypical behavior (e.g., a key wobbles). This was followed by experimental sessions, in which expectations were unmet in 20% of the trials. In both training and experimental sessions, the participant's task was to report whether the objects broke or not upon hitting the ground. Critically, a specific object always remained intact or broke - only the manner in which it did so differed. For example, a key could wobble or remain rigid but never break. We found that participants' reaction times were longer when expectations were unmet, not only for typical material behavior but also when those expectations were atypical and learned during the training session. Furthermore, we found an interplay between long-term and newly learned expectations. Overall, our results show that expectations about material properties can impact relatively low-level perceptual decision-making processes.

Texture statistics involved in specular highlight exclusion for object lightness perception

The human visual system estimates the physical properties of objects, such as their lightness. Previous studies on the lightness perception of glossy three-dimensional objects have suggested that specular highlights are detected and excluded in lightness perception. However, only a few studies have attempted to elucidate the mechanisms underlying this exclusion. This study aimed to elucidate the image features that contribute to the highlight exclusion of lightness perception. We used Portilla-Simoncelli texture statistics (PS statistics), an image feature set similar to the representation in the early visual cortex, to explore their relationships with highlight exclusion for lightness perception. In experiment 1, computer graphics images of bumpy plastic plates with various physical parameters were used as stimuli, and the lightness perception on them was measured using a lightness matching task. We then calculated the highlight exclusion index, which represented the degree of highlight exclusion. Finally, we evaluated the correlation between the highlight exclusion index and the four PS statistic subsets. In experiment 2, an image synthesis algorithm was used to create images in which either the PS statistic subset was manipulated. The highlight exclusion indexes of the synthesized images were then measured. The results revealed that the PS statistic subset consisting of lowest-order image features, such as moment statistics of luminance, acts as a necessary condition for highlight exclusion, whereas the other three subsets consisting of higher order features are not crucial. These results suggest that the low-order image features are the most important among the features in PS statistics for highlight exclusion, even though image features higher order than those in PS statistics must be directly involved.

Unsupervised learning reveals interpretable latent representations for translucency perception

Humans constantly assess the appearance of materials to plan actions, such as stepping on icy roads without slipping. Visual inference of materials is important but challenging because a given material can appear dramatically different in various scenes. This problem especially stands out for translucent materials, whose appearance strongly depends on lighting, geometry, and viewpoint. Despite this, humans can still distinguish between different materials, and it remains unsolved how to systematically discover visual features pertinent to material inference from natural images. Here, we develop an unsupervised style-based image generation model to identify perceptually relevant dimensions for translucent material appearances from photographs. We find our model, with its layer-wise latent representation, can synthesize images of diverse and realistic materials. Importantly, without supervision, human-understandable scene attributes, including the object's shape, material, and body color, spontaneously emerge in the model's layer-wise latent space in a scale-specific manner. By embedding an image into the learned latent space, we can manipulate specific layers' latent code to modify the appearance of the object in the image. Specifically, we find that manipulation on the early-layers (coarse spatial scale) transforms the object's shape, while manipulation on the later-layers (fine spatial scale) modifies its body color. The middle-layers of the latent space selectively encode translucency features and manipulation of such layers coherently modifies the translucency appearance, without changing the object's shape or body color. Moreover, we find the middle-layers of the latent space can successfully predict human translucency ratings, suggesting that translucent impressions are established in mid-to-low spatial scale features. This layer-wise latent representation allows us to systematically discover perceptually relevant image features for human translucency perception. Together, our findings reveal that learning the scale-specific statistical structure of natural images might be crucial for humans to efficiently represent material properties across contexts.

Conditions of a Multi-View 3D Display for Accurate Reproduction of Perceived Glossiness

Visualizing objects as they are perceived in the real world is often critical in our daily experiences. We previously focused on objects' surface glossiness visualized with a 3D display and found that a multi-view 3D display reproduces perceived glossiness more accurately than a 2D display. This improvement of glossiness reproduction can be explained by the fact that a glossy surface visualized by a multi-view 3D display appropriately provides luminance differences between the two eyes and luminance changes accompanying the viewer's lateral head motion. In the present study, to determine the requirements of a multi-view 3D display for the accurate reproduction of perceived glossiness, we developed a simulator of a multi-view 3D display to independently and simultaneously manipulate the viewpoint interval and the magnitude of the optical inter-view crosstalk. Using the simulator, we conducted a psychophysical experiment and found that glossiness reproduction is most accurate when the viewpoint interval is small and there is just a small (but not too small) amount of crosstalk. We proposed a simple yet perceptually valid model that quantitatively predicts the reproduction accuracy of perceived glossiness.

Perceptual scale for transparency: Common fate overrides geometrical and color cues

Objects that pass light through are considered transparent, and we generally expect that the light coming out will match the color of the object. However, when the object is placed on a colored surface, the light coming back to our eyes becomes a composite of surface, illumination, and transparency properties. Despite that, we can often perceive separate overlaid and overlaying layers differing in colors. How neurons separate the information to extract the transparent layer remains unknown, but the physical characteristics of transparent filters generate geometrical and color features in retinal images, which could provide cues for separating layers. We estimated the relative importance of such cues in a perceptual scale for transparency, using stimuli in which X- or T-junctions, different relative motions, and consistent or inconsistent colors cooperated or competed in forced-preference psychophysics experiments. Maximum-likelihood Thurstone scaling revealed that motion increased transparency for X-junctions, but decreased transparency for T-junctions by creating the percept of an opaque patch. However, if the motion of a filter uncovered a dynamically changing but stationary pattern, sharing a common fate with the surround but forming T-junctions, the probability of seeing transparency was almost as high as for moving X-junctions, despite the stimulus being physically improbable. In addition, geometric cues overrode color inconsistency to a great degree. Finally, a linear model of transparency perception as a function of relative motions between filter, overlay, and surround layers, contour continuation, and color consistency, quantified a hierarchy of latent influences on when the filter is seen as a separate transparent layer.

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 Certainty of Ambiguity in Visual Neural Representations

Some images evoke bistable percepts: two different visual experiences seen in alternation while continuously viewing an unchanged stimulus. The Necker Cube and Rubin's Vase are classic examples, each of which gives alternating percepts of different shapes. Other bistable percepts are alternating colors or directions of motion. Although stimuli that result in salient bistability are rare and sometimes cleverly constructed to emphasize ambiguity, they have been influential for over 150 years, since the work of von Helmholtz, who considered them to be evidence for perceptual visual processes that interpret retinal stimuli. While bistability in natural viewing is uncommon, the main point of this review is that implicit ambiguity in visual neural representations is pervasive. Resolving ambiguity, therefore, is a fundamental and ubiquitous process of vision that routinely affects what we see, not an oddity arising from cleverly crafted images. This review focuses on the causes of widespread ambiguity, historical perspectives on it, and modern knowledge and theory about resolving it.

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.

Translucency perception: A review

Translucency is an optical and a perceptual phenomenon that characterizes subsurface light transport through objects and materials. Translucency as an optical property of a material relates to the radiative transfer inside and through this medium, and translucency as a perceptual phenomenon describes the visual sensation experienced by humans when observing a given material under given conditions. The knowledge about the visual mechanisms of the translucency perception remains limited. Accurate prediction of the appearance of the translucent objects can have a significant commercial impact in the fields such as three-dimensional printing. However, little is known how the optical properties of a material relate to a perception evoked in humans. This article overviews the knowledge status about the visual perception of translucency and highlights the applications of the translucency perception research. Furthermore, this review summarizes current knowledge gaps, fundamental challenges and existing ambiguities with a goal to facilitate translucency perception research in the future.

Unsupervised learning predicts human perception and misperception of gloss

Reflectance, lighting and geometry combine in complex ways to create images. How do we disentangle these to perceive individual properties, such as surface glossiness? We suggest that brains disentangle properties by learning to model statistical structure in proximal images. To test this hypothesis, we trained unsupervised generative neural networks on renderings of glossy surfaces and compared their representations with human gloss judgements. The networks spontaneously cluster images according to distal properties such as reflectance and illumination, despite receiving no explicit information about these properties. Intriguingly, the resulting representations also predict the specific patterns of ‘successes’ and ‘errors’ in human perception. Linearly decoding specular reflectance from the model’s internal code predicts human gloss perception better than ground truth, supervised networks or control models, and it predicts, on an image-by-image basis, illusions of gloss perception caused by interactions between material, shape and lighting. Unsupervised learning may underlie many perceptual dimensions in vision and beyond.

Storrs et al. train unsupervised generative neural networks on glossy surfaces and show how gloss perception in humans may emerge in an unsupervised fashion from learning to model statistical structure.

Human brain activity reflecting facial attractiveness from skin reflection

Facial attraction has a great influence on our daily social interactions. Previous studies have mainly focused on the attraction from facial shape and expression. We recently found that faces with radiant skin appear to be more attractive than those with oily-shiny or matte skin. In the present study, we conducted functional magnetic resonance imaging (fMRI) and psychological experiments to determine the human brain activity that reflects facial attractiveness modulated by these skin reflection types. In the fMRI experiment, female subjects were shown successive images of unfamiliar female faces with matte, oily-shiny, or radiant skin. The subjects compared each face with the immediately preceding face in terms of attractiveness, age, and skin reflection, all based on the skin. The medial part of the orbitofrontal cortex (mOFC) was significantly more active when comparing attractiveness than when comparing skin reflection, suggesting that the mOFC is involved in processing facial attractiveness from skin reflection. In the psychological experiment, attractiveness rating was highest for radiant skin, followed by oily-shiny, and then matte skin. Comparison of the results of these experiments showed that mOFC activation level increased with attractiveness rating. These results suggest that the activation level of the mOFC reflects facial attractiveness from skin reflection.

Dynamic dot displays reveal material motion network in the human brain

There is growing research interest in the neural mechanisms underlying the recognition of material categories and properties. This research field, however, is relatively more recent and limited compared to investigations of the neural mechanisms underlying object and scene category recognition. Motion is particularly important for the perception of non-rigid materials, but the neural basis of non-rigid material motion remains unexplored. Using fMRI, we investigated which brain regions respond preferentially to material motion versus other types of motion. We introduce a new database of stimuli - dynamic dot materials - that are animations of moving dots that induce vivid percepts of various materials in motion, e.g. flapping cloth, liquid waves, wobbling jelly. Control stimuli were scrambled versions of these same animations and rigid three-dimensional rotating dots. Results showed that isolating material motion properties with dynamic dots (in contrast with other kinds of motion) activates a network of cortical regions in both ventral and dorsal visual pathways, including areas normally associated with the processing of surface properties and shape, and extending to somatosensory and premotor cortices. We suggest that such a widespread preference for material motion is due to strong associations between stimulus properties. For example viewing dots moving in a specific pattern not only elicits percepts of material motion; one perceives a flexible, non-rigid shape, identifies the object as a cloth flapping in the wind, infers the object's weight under gravity, and anticipates how it would feel to reach out and touch the material. These results are a first important step in mapping out the cortical architecture and dynamics in material-related motion processing.

Expectations affect the perception of material properties

Many objects that we encounter have typical material qualities: spoons are hard, pillows are soft, and Jell-O dessert is wobbly. Over a lifetime of experiences, strong associations between an object and its typical material properties may be formed, and these associations not only include how glossy, rough, or pink an object is, but also how it behaves under force: we expect knocked over vases to shatter, popped bike tires to deflate, and gooey grilled cheese to hang between two slices of bread when pulled apart. Here we ask how such rich visual priors affect the visual perception of material qualities and present a particularly striking example of expectation violation. In a cue conflict design, we pair computer-rendered familiar objects with surprising material behaviors (a linen curtain shattering, a porcelain teacup wrinkling, etc.) and find that material qualities are not solely estimated from the object's kinematics (i.e., its physical [atypical] motion while shattering, wrinkling, wobbling etc.); rather, material appearance is sometimes “pulled” toward the “native” motion, shape, and optical properties that are associated with this object. Our results, in addition to patterns we find in response time data, suggest that visual priors about materials can set up high-level expectations about complex future states of an object and show how these priors modulate material appearance.

The influence of Fresnel effects on gloss perception

Glossy surfaces reflect a mirror image of the environment. The perceived gloss depends (a) on the blurriness of this mirror image, which is a function of surface roughness, and (b) the strength of the mirror reflection, which, according to Fresnel's equations, is a function of the material's refractive index and the angle of the incident light. Investigations on gloss perception often used simplified reflection models, e.g., the Ward model (Ward, 1992), which do not correctly account for Fresnel effects. Here, possible perceptual consequences of this simplification are investigated in three experiments, in which the gloss impression produced by a physically more plausible reflection model (Fresnel-bidirectional reflectance distribution function [BRDF]) is compared to the gloss produced by two variants of the Ward model under identical conditions. The results show that it is, in general, not possible to match the gloss impression elicited by a Fresnel-BRDF with a Ward-BRDF. Furthermore, compared with the Ward-BRDF, the gloss impression produced with the Fresnel-BRDF under identical conditions is, in general, stronger, more vivid, and more realistic. Gloss constancy is also improved, i.e., the gloss impression depends less on the type of illumination, the presence and properties of a floor, and surface shape. These differences are especially evident with relatively homogeneous illuminations. The results of a fourth experiment, which tested gloss constancy under changes in illumination and shape with a matching task, confirm an improved gloss constancy with a Fresnel-BRDF. Together, these findings suggest that Fresnel effects are used as a cue in gloss perception.

Effects of Shape, Roughness and Gloss on the Perceived Reflectance of Colored Surfaces

This study examined perceptual differentiation of specular from diffuse shading for the recovery of surface color and gloss. In Experiment 1, we parametrically varied the mesoscale relief height of globally planar surfaces, specular sharpness and the orientation of the surface relative to the light source. We obtained psychophysical matches for perceived color saturation and value (HSV), but also considered whether the main effects could be influenced by color space used when transforming data to perceptually-uniform CIE LCH space. Results revealed strong interactions between perceived color attributes and the lighting conditions, the structure of specular reflections, and surface relief. Declines in saturation were observed with increasing specular roughness (using an HSV color representation), but no similar decline was observed in chroma (using a CIE LCH color representation). Experiment 2 found strong negative correlations between perceived gloss and specular roughness. Perceived gloss also depended on mesoscopic relief height and orientation of the surface relative to the light source. Declines in perceived gloss moderately accounted for the variability in color saturation and value matches obtained in Experiment 1. We found information about perceived specular coverage could further improve the model's accountability of perceived color saturation and lightness (Experiment 3). These findings together suggest that perceived color saturation and color value depends on the visual system's ability to distinguish the underlying diffuse shading from specular highlights in images.

Learning to see stuff

Materials with complex appearances, like textiles and foodstuffs, pose challenges for conventional theories of vision. But recent advances in unsupervised deep learning provide a framework for explaining how we learn to see them. We suggest that perception does not involve estimating physical quantities like reflectance or lighting. Instead, representations emerge from learning to encode and predict the visual input as efficiently and accurately as possible. Neural networks can be trained to compress natural images or to predict frames in movies without 'ground truth' data about the outside world. Yet, to succeed, such systems may automatically discover how to disentangle distal causal factors. Such 'statistical appearance models' potentially provide a coherent explanation of both failures and successes in perception.

Gloss and Speed Judgments Yield Different Fine Tuning of Saccadic Sampling in Dynamic Scenes

Image motion contains potential cues about the material properties of objects. In earlier work, we proposed motion cues that could predict whether a moving object would be perceived as shiny or matte. However, whether the visual system uses these cues is still uncertain. Herein, we use the tracking of eye movements as a tool to understand what visual information observers use when engaged in material perception. Observers judged either the gloss or the speed of moving blobby shapes in an eye tracking experiment. Results indicate that during glossiness judgments, participants tend to look at gloss-diagnostic dynamic features more than during speed judgments. This suggests a fine tuning of the visual system to properties of moving stimuli: Task relevant information is actively singled out and processed in a dynamically changing environment.

Factors Influencing the Detection of Spatially-Varying Surface Gloss

In this study, we investigate the ability of human observers to detect spatial inhomogeneities in the glossiness of a surface and how the performance in this task depends on several context factors. We used computer-generated stimuli showing a single object in three-dimensional space whose surface was split into two spatial areas with different microscale smoothness. The context factors were the kind of illumination, the object's shape, the availability of motion information, the degree of edge blurring, the spatial proportions between the two areas of different smoothness, and the general smoothness level. Detection thresholds were determined using a two-alternative forced choice (2AFC) task implemented in a double random staircase procedure, where the subjects had to indicate for each stimulus whether or not the surface appears to have a spatially uniform material. We found evidence that two different cues are used for this task: luminance differences and differences in highlight properties between areas of different microscale smoothness. While the visual system seems to be highly sensitive in detecting gloss differences based on luminance contrast information, detection thresholds were considerably higher when the judgment was mainly based on differences in highlight features, such as their size, intensity, and sharpness.

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.

Differences in Stereoscopic Luster Evoked by Static and Dynamic Stimuli

We compared the classic static stereoscopic luster phenomenon with a recently described dynamic variant ("counter modulation") to investigate whether they are related to the same or different processes. In the experiments, we presented pairs of center-surround stimuli haploscopically and measured the effect of the contrast between center colors on perceived luster. The center colors were either static or temporally modulated. In addition, we examined five color conditions (one achromatic, two equiluminant, and two mixed conditions) and three background conditions that influence the channel-wise polarities of the contrast of the two centers to the common surround. The results for static and dynamic stimuli differed in several ways, suggesting that they depend on different mechanisms: Compared with the static version, in dynamic stimuli, luster was perceived at markedly lower contrasts, did not depend on the sign of the contrast polarities, and appeared more steady. However, both phenomena seem also similar in some respects: In both cases, equiluminant stimuli led to lustrous impressions that were considerably less strong than those evoked by stimuli containing luminance variation, and the strength of the perceived luster was generally boosted with reversed contrast polarities.

Naturally glossy: Gloss perception, illumination statistics, and tone mapping

Recognizing materials and understanding their properties is very useful—perhaps critical—in daily life as we encounter objects and plan our interactions with them. Visually derived estimates of material properties guide where and with what force we grasp an object. However, the estimation of material properties, such as glossiness, is a classic ill-posed problem. Image cues that we rely on to estimate gloss are also affected by shape, illumination and, in visual displays, tone-mapping. Here, we focus on the latter two. We define some commonalities present in the structure of natural illumination, and determine whether manipulation of these natural “signatures” impedes gloss constancy. We manipulate the illumination field to violate statistical regularities of natural illumination, such that light comes from below, or the luminance distribution is no longer skewed. These manipulations result in errors in perceived gloss. Similarly, tone mapping has a dramatic effect on perceived gloss. However, when objects are viewed against an informative (rather than plain gray) background that reflects these manipulations, there are some improvements to gloss constancy: in particular, observers are far less susceptible to the effects of tone mapping when judging gloss. We suggest that observers are sensitive to some very simple statistics of the environment when judging gloss.

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.

The Rotating Glass Illusion: Material Appearance Is Bound to Perceived Shape and Motion

We report a novel illusion in which a rotating transparent and refractive triangular prism (glass object) is perceived as being made of a specular reflective material (mirror), and simultaneously, its direction of rotation (clockwise or anticlockwise) is also misperceived. Our findings suggest that physical motion strongly influences viewers' judgements of material in some situations.

Neural Mechanisms of Material Perception: Quest on Shitsukan

In recent years, a growing body of research has addressed the nature and mechanism of material perception. Material perception entails perceiving and recognizing a material, surface quality or internal state of an object based on sensory stimuli such as visual, tactile, and/or auditory sensations. This process is ongoing in every aspect of daily life. We can, for example, easily distinguish whether an object is made of wood or metal, or whether a surface is rough or smooth. Judging whether the ground is wet or dry or whether a fish is fresh also involves material perception. Information obtained through material perception can be used to govern actions toward objects and to make decisions about whether to approach an object or avoid it. Because the physical processes leading to sensory signals related to material perception is complicated, it has been difficult to manipulate experimental stimuli in a rigorous manner. However, that situation is now changing thanks to advances in technology and knowledge in related fields. In this article, we will review what is currently known about the neural mechanisms responsible for material perception. We will show that cortical areas in the ventral visual pathway are strongly involved in material perception. Our main focus is on vision, but every sensory modality is involved in material perception. Information obtained through different sensory modalities is closely linked in material perception. Such cross-modal processing is another important feature of material perception, and will also be covered in this review.

Can Color and Motion Information Be Used to Disentangle the Influence of Multiple Light Sources on Gloss Perception?

Previous results suggest that the glossiness of a surface is systematically underestimated when adjacent highlights from different light sources overlap to such an extent that they appear as a single, expanded highlight. Here we investigated how the availability of color- and motion-induced information, which may help to unravel such merged highlights, affects gloss constancy. We used images of computer-generated scenes where a complex 3D object made of glossy material was illuminated by three point light sources, which had varying distances to each other. The point lights were either all achromatic or they differed clearly in their color and the test object was either presented statically or rotating. The subjects had to adjust the smoothness of a match object illuminated by a single achromatic point light so that it appeared to have the same glossiness as the test object. The results show that color information contributes to gloss constancy in this situation: If it was available, the perceived glossiness remained almost invariant with changes in the degree of overlap between the highlights. This suggests that highlights of different color are processed separately. Motion information had no such effect but only led to a general increase in perceived glossiness.

Firefly: Virtual Illumination Drones for Interactive Visualization

Light specification in three dimensional scenes is a complex problem and several approaches have been presented that aim to automate this process. However, there are many scenarios where a static light setup is insufficient, as the scene content and camera position may change. Simultaneous manual control over the camera and light position imposes a high cognitive load on the user. To address this challenge, we introduce a novel approach for automatic scene illumination with Fireflies. Fireflies are intelligent virtual light drones that illuminate the scene by traveling on a closed path. The Firefly path automatically adapts to changes in the scene based on an outcome-oriented energy function. To achieve interactive performance, we employ a parallel rendering pipeline for the light path evaluations. We provide a catalog of energy functions for various application scenarios and discuss the applicability of our method on several examples.

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

Humans can visually estimate the mechanical properties of deformable objects (e.g., cloth stiffness). While much of the recent work on material perception has focused on static image cues (e.g., textures and shape), little is known about whether humans can integrate information over time to make a judgment. Here we investigated the effect of spatiotemporal information across multiple frames (multiframe motion) on estimating the bending stiffness of cloth. Using high-fidelity cloth animations, we first examined how the perceived bending stiffness changed as a function of the physical bending stiffness defined in the simulation model. Using maximum-likelihood difference-scaling methods, we found that the perceived stiffness and physical bending stiffness were highly correlated. A second experiment in which we scrambled the frame sequences diminished this correlation. This suggests that multiframe motion plays an important role. To provide further evidence for this finding, we extracted dense motion trajectories from the videos across 15 consecutive frames and used the trajectory descriptors to train a machine-learning model with the measured perceptual scales. The model can predict human perceptual scales in new videos with varied winds, optical properties of cloth, and scene setups. When the correct multiframe was removed (using either scrambled videos or two-frame optical flow to train the model), the predictions significantly worsened. Our findings demonstrate that multiframe motion information is important for both humans and machines to estimate the mechanical properties. In addition, we show that dense motion trajectories are effective features to build a successful automatic cloth-estimation system.

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.

Dynamic Visual Cues for Differentiating Mirror and Glass

Mirror materials (perfect specular surfaces such as polished metal) and glass materials (transparent and refraction media) are quite commonly encountered in everyday life. The human visual system can discriminate these complex distorted images formed by reflection or transmission of the surrounding environment even though they do not intrinsically possess surface colour. In this study, we determined the cues that aid mirror and glass discrimination. From video analysis, we found that glass objects have more opposite motion components relative to the direction of object rotation. Then, we hypothesised a model developed using motion transparency because motion information is not only present on the front side, but also on the rear side of the object surface in the glass material object. In materials judging experiments, we found that human performance with rotating video stimuli is higher than that with static stimuli (simple images). Subsequently, we compared the developed model derived from motion coherency to human rating performance for transparency and specular reflection. The model sufficiently identified the different materials using dynamic information. These results suggest that the visual system relies on dynamic cues that indicate the difference between mirror and glass.

The dress and individual differences in the perception of surface properties

This study investigates systematic individual differences in the way observers perceive different kinds of surface properties and their relationship to the dress, which shows striking individual differences in colour perception. We tested whether these individual differences have a common source, namely differences in perceptual strategies according to which observers attribute features in two-dimensional images to surfaces or to their illumination. First, we reanalysed data from two previous experiments on the dress and colour constancy. The comparison of the two experiments revealed that the colour perception of the dress is strongly related to individual differences in colour constancy. Second, two online surveys measured individual differences in the perception of colour-ambiguous images including the dress, in colour constancy, in gloss perception, in the subjective grey-point, in colour naming, and in the perception of an image with ambiguous shading. The results of the surveys replicated and extended previous findings according to which individual differences in the colour perception of the dress are due to implicit assumptions about the illumination. However, results also showed that the individual differences for other phenomena were independent of the dress and of each other. Overall, these results suggest that the striking individual differences in dress colour perception are due to individual differences in the interpretation of illumination cues to achieve colour constancy. At the same time, they undermine the idea of an overall perceptual strategy that encompasses other phenomena more generally related to the interpretation of illumination and surface properties.

Motion of glossy objects does not promote separation of lighting and surface colour

The surface properties of an object, such as texture, glossiness or colour, provide important cues to its identity. However, the actual visual stimulus received by the eye is determined by both the properties of the object and the illumination. We tested whether operational colour constancy for glossy objects (the ability to distinguish changes in spectral reflectance of the object, from changes in the spectrum of the illumination) was affected by rotational motion of either the object or the light source. The different chromatic and geometric properties of the specular and diffuse reflections provide the basis for this discrimination, and we systematically varied specularity to control the available information. Observers viewed animations of isolated objects undergoing either lighting or surface-based spectral transformations accompanied by motion. By varying the axis of rotation, and surface patterning or geometry, we manipulated: (i) motion-related information about the scene, (ii) relative motion between the surface patterning and the specular reflection of the lighting, and (iii) image disruption caused by this motion. Despite large individual differences in performance with static stimuli, motion manipulations neither improved nor degraded performance. As motion significantly disrupts frame-by-frame low-level image statistics, we infer that operational constancy depends on a high-level scene interpretation, which is maintained in all conditions.

Material Perception

Under typical viewing conditions, human observers effortlessly recognize materials and infer their physical, functional, and multisensory properties at a glance. Without touching materials, we can usually tell whether they would feel hard or soft, rough or smooth, wet or dry. We have vivid visual intuitions about how deformable materials like liquids or textiles respond to external forces and how surfaces like chrome, wax, or leather change appearance when formed into different shapes or viewed under different lighting. These achievements are impressive because the retinal image results from complex optical interactions between lighting, shape, and material, which cannot easily be disentangled. Here I argue that because of the diversity, mutability, and complexity of materials, they pose enormous challenges to vision science: What is material appearance, and how do we measure it? How are material properties estimated and represented? Resolving these questions causes us to scrutinize the basic assumptions of mid-level vision.

Adaptation-Induced Blindness Is Orientation-Tuned and Monocular

We examined the recently discovered phenomenon of Adaptation-Induced Blindness (AIB), in which highly visible gratings with gradual onset profiles become invisible after exposure to a rapidly flickering grating, even at very high contrasts. Using very similar stimuli to those in the original AIB experiment, we replicated the original effect across multiple contrast levels, with observers at chance in detecting the gradual onset stimuli at all contrasts. Then, using full-contrast target stimuli with either abrupt or gradual onsets, we tested both the orientation tuning and interocular transfer of AIB. If, as the original authors suggested, AIB were a high-level (perhaps parietally mediated) effect resulting from the ‘gating’ of awareness, we would not expect the effects of AIB to be tuned to the adapting orientation, and the effect should transfer interocularly. Instead, we find that AIB (which was present only for the gradual onset target stimuli) is both tightly orientation-tuned and shows absolutely no interocular transfer, consistent with a very early cortical locus.

Representation of Glossy Material Surface in Ventral Superior Temporal Sulcal Area of Common Marmosets

The common marmoset (Callithrix jacchus) is one of the smallest species of primates, with high visual recognition abilities that allow them to judge the identity and quality of food and objects in their environment. To address the cortical processing of visual information related to material surface features in marmosets, we presented a set of stimuli that have identical three-dimensional shapes (bone, torus or amorphous) but different material appearances (ceramic, glass, fur, leather, metal, stone, wood, or matte) to anesthetized marmoset, and recorded multiunit activities from an area ventral to the superior temporal sulcus (STS) using multi-shanked, and depth resolved multi-electrode array. Out of 143 visually responsive multiunits recorded from four animals, 29% had significant main effect only of the material, 3% only of the shape and 43% of both the material and the shape. Furthermore, we found neuronal cluster(s), in which most cells: (1) showed a significant main effect in material appearance; (2) the best stimulus was a glossy material (glass or metal); and (3) had reduced response to the pixel-shuffled version of the glossy material images. The location of the gloss-selective area was in agreement with previous macaque studies, showing activation in the ventral bank of STS. Our results suggest that perception of gloss is an important ability preserved across wide range of primate species.

'Proto-rivalry': how the binocular brain identifies gloss

Visually identifying glossy surfaces can be crucial for survival (e.g. ice patches on a road), yet estimating gloss is computationally challenging for both human and machine vision. Here, we demonstrate that human gloss perception exploits some surprisingly simple binocular fusion signals, which are likely available early in the visual cortex. In particular, we show that the unusual disparity gradients and vertical offsets produced by reflections create distinctive ‘proto-rivalrous’ (barely fusible) image regions that are a critical indicator of gloss. We find that manipulating the gradients and vertical components of binocular disparities yields predictable changes in material appearance. Removing or occluding proto-rivalrous signals makes surfaces look matte, while artificially adding such signals to images makes them appear glossy. This suggests that the human visual system has internalized the idiosyncratic binocular fusion characteristics of glossy surfaces, providing a straightforward means of estimating surface attributes using low-level image signals.

Touch influences perceived gloss

Identifying an object's material properties supports recognition and action planning: we grasp objects according to how heavy, hard or slippery we expect them to be. Visual cues to material qualities such as gloss have recently received attention, but how they interact with haptic (touch) information has been largely overlooked. Here, we show that touch modulates gloss perception: objects that feel slippery are perceived as glossier (more shiny).Participants explored virtual objects that varied in look and feel. A discrimination paradigm (Experiment 1) revealed that observers integrate visual gloss with haptic information. Observers could easily detect an increase in glossiness when it was paired with a decrease in friction. In contrast, increased glossiness coupled with decreased slipperiness produced a small perceptual change: the visual and haptic changes counteracted each other. Subjective ratings (Experiment 2) reflected a similar interaction - slippery objects were rated as glossier and vice versa. The sensory system treats visual gloss and haptic friction as correlated cues to surface material. Although friction is not a perfect predictor of gloss, the visual system appears to know and use a probabilistic relationship between these variables to bias perception - a sensible strategy given the ambiguity of visual clues to gloss.

Differential processing of binocular and monocular gloss cues in human visual cortex

The visual impression of an object's surface reflectance (“gloss”) relies on a range of visual cues, both monocular and binocular. Whereas previous imaging work has identified processing within ventral visual areas as important for monocular cues, little is known about cortical areas involved in processing binocular cues. Here, we used human functional MRI (fMRI) to test for brain areas selectively involved in the processing of binocular cues. We manipulated stereoscopic information to create four conditions that differed in their disparity structure and in the impression of surface gloss that they evoked. We performed multivoxel pattern analysis to find areas whose fMRI responses allow classes of stimuli to be distinguished based on their depth structure vs. material appearance. We show that higher dorsal areas play a role in processing binocular gloss information, in addition to known ventral areas involved in material processing, with ventral area lateral occipital responding to both object shape and surface material properties. Moreover, we tested for similarities between the representation of gloss from binocular cues and monocular cues. Specifically, we tested for transfer in the decoding performance of an algorithm trained on glossy vs. matte objects defined by either binocular or by monocular cues. We found transfer effects from monocular to binocular cues in dorsal visual area V3B/kinetic occipital (KO), suggesting a shared representation of the two cues in this area. These results indicate the involvement of mid- to high-level visual circuitry in the estimation of surface material properties, with V3B/KO potentially playing a role in integrating monocular and binocular cues.

Human visual cortical responses to specular and matte motion flows

Determining the compositional properties of surfaces in the environment is an important visual capacity. One such property is specular reflectance, which encompasses the range from matte to shiny surfaces. Visual estimation of specular reflectance can be informed by characteristic motion profiles; a surface with a specular reflectance that is difficult to determine while static can be confidently disambiguated when set in motion. Here, we used fMRI to trace the sensitivity of human visual cortex to such motion cues, both with and without photometric cues to specular reflectance. Participants viewed rotating blob-like objects that were rendered as images (photometric) or dots (kinematic) with either matte-consistent or shiny-consistent specular reflectance profiles. We were unable to identify any areas in low and mid-level human visual cortex that responded preferentially to surface specular reflectance from motion. However, univariate and multivariate analyses identified several visual areas; V1, V2, V3, V3A/B, and hMT+, capable of differentiating shiny from matte surface flows. These results indicate that the machinery for extracting kinematic cues is present in human visual cortex, but the areas involved in integrating such information with the photometric cues necessary for surface specular reflectance remain unclear.

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.

Key characteristics of specular stereo

Because specular reflection is view-dependent, shiny surfaces behave radically differently from matte, textured surfaces when viewed with two eyes. As a result, specular reflections pose substantial problems for binocular stereopsis. Here we use a combination of computer graphics and geometrical analysis to characterize the key respects in which specular stereo differs from standard stereo, to identify how and why the human visual system fails to reconstruct depths correctly from specular reflections. We describe rendering of stereoscopic images of specular surfaces in which the disparity information can be varied parametrically and independently of monocular appearance. Using the generated surfaces and images, we explain how stereo correspondence can be established with known and unknown surface geometry. We show that even with known geometry, stereo matching for specular surfaces is nontrivial because points in one eye may have zero, one, or multiple matches in the other eye. Matching features typically yield skew (nonintersecting) rays, leading to substantial ortho-epipolar components to the disparities, which makes deriving depth values from matches nontrivial. We suggest that the human visual system may base its depth estimates solely on the epipolar components of disparities while treating the ortho-epipolar components as a measure of the underlying reliability of the disparity signals. Reconstructing virtual surfaces according to these principles reveals that they are piece-wise smooth with very large discontinuities close to inflection points on the physical surface. Together, these distinctive characteristics lead to cues that the visual system could use to diagnose specular reflections from binocular information.

fMRI evidence for areas that process surface gloss in the human visual cortex

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Glossiness information is mainly processed along ventral visual pathway.

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The posterior fusiform sulcus (pFs) is especially selective to surface gloss.

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V3B/KO responds to gloss, but differentially from the pFs.

Surface gloss is an important cue to the material properties of objects. Recent progress in the study of macaque’s brain has increased our understating of the areas involved in processing information about gloss, however the homologies with the human brain are not yet fully understood. Here we used human functional magnetic resonance imaging (fMRI) measurements to localize brain areas preferentially responding to glossy objects. We measured cortical activity for thirty-two rendered three-dimensional objects that had either Lambertian or specular surface properties. To control for differences in image structure, we overlaid a grid on the images and scrambled its cells. We found activations related to gloss in the posterior fusiform sulcus (pFs) and in area V3B/KO. Subsequent analysis with Granger causality mapping indicated that V3B/KO processes gloss information differently than pFs. Our results identify a small network of mid-level visual areas whose activity may be important in supporting the perception of surface gloss.