The Perception of Surface Properties: Translucence and Gloss

The human visual system is sensitive to differences in gloss and translucence, two optical properties which are found in conjunction in many natural materials. They are driven by similar underlying physical properties of light transport - the degree to which light is scattered from the surface of a material, or within the material. This thesis aimed to address some fundamental questions about how gloss and translucence are perceived. Two psychophysical methods (maximum likelihood difference scaling, and conjoint measurement) were used throughout, as they provided an appropriate way of investigating how perceptual experiences related to physical variables. In the introduction, I review the literature on the perception of gloss and translucence. Study 1 investigated the relationship between variables controlling light transport in translucent volumes and percepts of translucence. The results show that translucence perception is not based on estimates of light transport properties per se, but probably uses spatially-related statistical pseudocues in conjunction with other cues. Study 2 examined a similar issue, but the translucent material was presented as a layer enveloping a solid object. Behavioural responses were similar for these translucent materials, which were perceived as glossy layers of coating. Study 3 further explored established findings that perceived translucence shows inconstancy under changes in viewing condition. Perceived translucence was dependent in a complex way on both light-scattering in the material and illumination direction in both volumes and layers of translucent materials. Study 4 used similar layers of subsurface light-scattering and -absorbing material and applied them to multiple base materials. Opacity and a lack of mirror-like reflections enabled observers to make the most accurate independent judgements of darkness and cloudiness. Study 5 explored observers' sensitivity to spatial variation of scatter across a surface using similar layers of coating, and the way in which observers might weight cues differently to answer subtly different questions (judgements of 'shininess' vs. 'cleanliness'). Layer thickness and variation of scatter significantly affected perceived shine and cleanliness, with layer thickness influencing decisions more than variation. Scatter variation contributed to decisions significantly more for judgements of cleanliness than shine. Study 6 investigated how tactile surface roughness influenced perceived gloss. Previous findings have shown that tactile compliance and friction influence perceived gloss, and that friction interacts with visual gloss. Our results showed that surface roughness and visual gloss both affected perceived gloss, but there was no interaction, suggesting that different types of haptic information are combined with visual information differently. Finally, study 7 explored the potential cortical basis of perceived translucence. Through testing a neuropsychological patient, we showed that perceived translucence is dependent on cortical areas not responsible for colour or texture discrimination. The thesis concludes with a discussion of additional recent findings, the implications of the research reported in this thesis, and proposals for future research

Estimation of Perceptual Surface Property Using Deep Networks with Attention Models

How we perceive property of surfaces with distinct geometry and reflectance under various illumination conditions is not fully understood. One widely studied approach to understanding perceptual surface property is to derive statistics from images of surfaces with the goal of constructing models that can estimate surface property attributes. This work presents machine learning-based methods to estimate the lightness and glossiness of surfaces. Instead of deriving image statistics and building estimation models on top of them, we use deep networks to estimate the perceptual surface property directly from surface images. We adopt the attention models in our networks, to allow the networks to estimate the surface property based on features in certain parts of images. This approach can rule out image variations due to geometry, reflectance, and illumination when making the estimations. The networks are trained with perceptual lightness and glossiness data obtained from psychophysical experiments. The trained deep networks provide accurate estimations of surface property that correlate well with human perception. The network performances are compared with various image statistics derived for estimation of perceptual surface property

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

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.This project was supported by fellowships to H.B. from the Japan Society for the Promotion of Science (H22.290), KAKENHI26870911

Moore's Dilemma

In 1918 GE Moore questioned the assumptions behind traditional sense-datum theories and offered the Multiple Relational Theory of Appearing, which he said could not be ruled out as a possible alternative. In 1953, Moore eventually came to reject the alternative and recommend endorsement of the traditional sense-datum theory again. This paper explores what Moore’s reservations in 1918 were, what the correct interpretation of the Multiple Relation Theory should be, and why it made sense for him ultimately to reject it. Moore’s paper throws light both on the nature of the argument from illusion as used in the sense-datum tradition, but also as it has been appealed to in more recent discussions of intentional theories of perception

Look but don't touch: Visual cues to surface structure drive somatosensory cortex.

When planning interactions with nearby objects, our brain uses visual information to estimate shape, material composition, and surface structure before we come into contact with them. Here we analyse brain activations elicited by different types of visual appearance, measuring fMRI responses to objects that are glossy, matte, rough, or textured. In addition to activation in visual areas, we found that fMRI responses are evoked in the secondary somatosensory area (S2) when looking at glossy and rough surfaces. This activity could be reliably discriminated on the basis of tactile-related visual properties (gloss, rough, and matte), but importantly, other visual properties (i.e., coloured texture) did not substantially change fMRI activity. The activity could not be solely due to tactile imagination, as asking explicitly to imagine such surface properties did not lead to the same results. These findings suggest that visual cues to an object's surface properties evoke activity in neural circuits associated with tactile stimulation. This activation may reflect the a-priori probability of the physics of the interaction (i.e., the expectation of upcoming friction) that can be used to plan finger placement and grasp force.This project was supported by the Wellcome Trust (095183/Z/10/Z).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.neuroimage.2015.12.05

Measuring perceived gloss of rough surfaces

This thesis is concerned with the visual perception of glossy rough surfaces, specifically those characterised by 1/fB noise. Computer graphics were used to model these natural looking surfaces, which were generated and animated to provide realistic stimuli for observers. Different methods were employed to investigate the effects of varying surface roughness and reflection model parameters on perceived gloss. We first investigated how the perceived gloss of a matte Lambertian surface varies with RMS roughness. Then we estimated the perceived gloss of moderate RMS height surfaces rendered using a gloss reflection model. We found that adjusting parameters of the gloss reflection model on the moderate RMS height surfaces produces similar levels of gloss to the high RMS height Lambertian surfaces. More realistic stimuli were modelled using improvements in the reflection model, rendering technique, illumination and viewing conditions. In contrast with previous research, a non-monotonic relationship was found between perceived gloss and mesoscale roughness when microscale parameters were held constant. Finally, the joint effect of variations in mesoscale roughness (surface geometry) and microscale roughness (reflection model) on perceived gloss was investigated and tested against conjoint measurement models. It was concluded that perceived gloss of rough surfaces is significantly affected by surface roughness in both mesoscale and microscale and can be described by a full conjoint measurement model

The Fractal Evaluation of Wood Texture by the Triangular Prism Surface Area Method

Textures of the surfaces of fifteen wood species were characterized by fractal dimension of the triangular prism surface area method. Fractal dimension ranged from 2 to 3, and sharp lightness variation caused high fractal dimension, whereas low values related to smooth variation. Based on this index, wood specimens were generally divided into a hardwood group with value greater than 2.50 and a softwood group with value less than 2.50. Six types of fractal dimension distribution were explored in our experiments, including plane, inclined plane, concave, convex, zigzag distribution, and hilly distribution. From these both the features of local textures and the general variation tendency of the whole surface could be illustrated. It was strongly proposed that fractal dimension should be adopted to quantitatively evaluate wood texture with coarseness and evenness, because such variation was related to the number of grains, surface orientation, and location. For wood color matching, fractal dimension is of great importance in ensuring texture matching to achieve a constructed surface texture close to the features of natural variation. These distribution patterns were considered as a good reference previous to matching. Little variation of fractal dimension along the grain was observed, and this could be used to simplify texture matching by a very limited number of the indices. No significant relationship was found between fractal dimension and lightness, further implying that fractal dimension was independent of lightness

Perception of material appearance:Aa comparison between painted and rendered images

Painters are masters in replicating the visual appearance of materials.While the perception of material appearance is not yet fully understood, painters seem to have acquired an implicit understanding of the key visual cues that we need to accurately perceive material properties. In this study, we directly compare the perception of material properties in paintings and in renderings by collecting professional realistic paintings of rendered materials. From both type of images, we collect human judgments of material properties and compute a variety of image features that are known to reflect material properties. Our study reveals that, despite important visual differences between the two types of depiction, material properties in paintings and renderings are perceived very similarly and are linked to the same image features. This suggests that we use similar visual cues independently of the medium and that the presence of such cues is sufficient to provide a good appearance perception of the materials. Copyright 2021 The Author

Stereoscopic viewing, roughness and gloss perception

This thesis presents a novel investigation into the effect stereoscopic vision has upon the strength of perceived gloss on rough surfaces. We demonstrate that in certain cases disparity is necessary for accurate judgements of gloss strength. We first detail the process we used to create a two-level taxonomy of property terms, which helped to inform the early direction of this work, before presenting the eleven words which we found categorised the property space. This shaped careful examination of the relevant literature, leading us to conclude that most studies into roughness, gloss, and stereoscopic vision have been performed with unrealistic surfaces and physically inaccurate lighting models. To improve on the stimuli used in these earlier studies, advanced offline rendering techniques were employed to create images of complex, naturalistic, and realistically glossy 1/fβ noise surfaces. These images were rendered using multi-bounce path tracing to account for interreflections and soft shadows, with a reflectance model which observed all common light phenomena. Using these images in a series of psychophysical experiments, we first show that random phase spectra can alter the strength of perceived gloss. These results are presented alongside pairs of the surfaces tested which have similar levels of perceptual gloss. These surface pairs are then used to conclude that naïve observers consistently underestimate how glossy a surface is without the correct surface and highlight disparity, but only on the rougher surfaces presented