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

Sawayama, Masataka; Dobashi, Yoshinori; Okabe, Masaru; Hosokawa, Kiyoshi; Koumura, Takuya; Saarela, Toni; Olkkonen, Maria; Nishida, Shin’ya

doi:10.1101/800870

Cited by 8 publications

(16 citation statements)

References 75 publications

(104 reference statements)

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“…In recent years, there has been significant progress in developing rendering algorithms and representations that, by modeling the underlying physics, can create realistic reproductions of translucency ( Jensen et al, 2001 ; Donner & Jensen, 2008 ; Gkioulekas et al, 2013 ). As with physics, there have likewise been previous efforts trying to decipher the other major aspect of translucent appearance, namely, its perception by the human visual system ( Fleming & Bülthoff, 2005 ; Motoyoshi, 2010 ; Anderson, 2011 ; Nagai et al, 2013 ; Gkioulekas et al, 2013 ; Xiao et al, 2014 ; Chowdhury et al, 2017 ; Marlow et al, 2017 ; Sawayama et al, 2019 ). Despite these efforts, our understanding of translucency perception remains limited.…”

Section: Introductionmentioning

confidence: 99%

Effect of geometric sharpness on translucent material perception

et al. 2020

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When judging the optical properties of a translucent object, humans often look at sharp geometric features such as edges and thin parts. An analysis of the physics of light transport shows that these sharp geometries are necessary for scientific imaging systems to be able to accurately measure the underlying material optical properties. In this article, we examine whether human perception of translucency is likewise affected by the presence of sharp geometry, by confounding our perceptual inferences about an object's optical properties. We use physically accurate simulations to create visual stimuli of translucent materials with varying shapes and optical properties under different illuminations. We then use these stimuli in psychophysical experiments, where human observers are asked to match an image of a target object by adjusting the material parameters of a match object with different geometric sharpness, lighting, and three-dimensional geometry. We find that the level of geometric sharpness significantly affects perceived translucency by observers. These findings generalize across a few illumination conditions and object shapes. Our results suggest that the perceived translucency of an object depends on both the underlying material's optical parameters and the three-dimensional shape of the object. We also find that models based on image contrast cannot fully predict the perceptual results.

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Section: Introductionmentioning

confidence: 99%

Effect of geometric sharpness on translucent material perception

et al. 2020

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“…We used a subset of the standard image dataset for material recognition research ( Sawayama et al, 2019 ). Of the six material dimensions recorded in the dataset, we used (1) metallic silver versus glass, (2) metallic gold versus plastic yellow, and (3) opaque versus translucent dimensions ( Figure 1 A).…”

Section: Methodsmentioning

confidence: 99%

“…from pure silver to pure glass). For a detailed description of the stimulus images, see Sawayama et al (2019) . Here, we briefly describe the image rendering procedure.…”

Section: Methodsmentioning

confidence: 99%

“…We used three object shapes for each material task, which are shown in the three rows of Figure 1 A. These shapes correspond to objects 1 to 3 in Figure 2 b of Sawayama et al (2019) .…”

Section: Methodsmentioning

confidence: 99%

“…An obstacle in constructing experiments with several types of material dimension involves the difficulty in creating a large and standardized set of images due to a lack of technical expertise, computational resource, or rendering time. Recently, Sawayama and colleagues introduced a standard set of images for material recognition research ( Sawayama, Dobashi, Okabe, Hosokawa, Koumura, Saarela, Olkkonen, & Nishida, 2019 ). This dataset contains images (computer graphics renderings) of a variety of materials with variations in conditions involving illumination context and object shape.…”

Section: Materials Constancy In Perception and Working Memorymentioning

confidence: 99%

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Material constancy in perception and working memory

et al. 2020

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A key challenge for the visual system entails the extraction of constant properties of objects from sensory information that varies moment by moment due to changes in viewing conditions. Although successful performance in constancy tasks requires cooperation between perception and working memory, the function of the memory system has been under-represented in recent material perception literature. Here, we addressed the limits of material constancy by elucidating if and how working memory is involved in constancy tasks by using a variety of material stimuli, such as metals, glass, and translucent objects. We conducted experiments with a simultaneous and a successive matching-to-sample paradigm in which participants matched the perceived material properties of objects with or without a temporal delay under varying illumination contexts. The current study combined a detailed analysis of matching errors, data on the strategy use obtained via a self-report questionnaire, and the statistical image analysis of diagnostic image cues used for material discrimination. We found a comparable material constancy between simultaneous and successive matching conditions, and it was suggested that, in both matching conditions, participants used similar information processing strategies for the discrimination of materials. The study provides converging evidence on the critical role of working memory in material constancy, where working memory serves as a shared processing bottleneck that constrains both simultaneous and successive material constancy. Material constancy in perception and working memory To illustrate the appearance of objects or goods seen around us, we commonly use descriptions, such as glossiness, roughness, or transparency. Recently, perception and recognition of material properties or, more broadly, "shitsukan" (the sense of quality; Komatsu & Goda, 2018) is gaining increased interest in vision science. Although our understanding of material perception is advancing (see Fleming, 2017; Komatsu & Goda, 2018; Schmid & Doerschner, 2019 for recent reviews), it remains a challenging domain. The visual system must detect specific visual features that are diagnostic of particular materials (Fleming, 2014) to achieve perceptual stability, or constancy, in response to changes in viewing conditions. However, the degree of constancy varies depending on illumination, object shape, and viewing angle (e.g. see Chadwick & Kentridge, 2015 for a review of gloss constancy). How the human brain accomplishes (and sometimes fails in) material constancy remains a subject of debate that primarily focuses on the mechanism by which the visual system extracts perceptual properties of material information from low and mid-level image features (Anderson, 2020; Nishida, 2019). In contrast, the role of working memory in material constancy has so far been rarely investigated. Successful performance in constancy tasks requires cooperation between perceptual and memory systems. For example, an individual engaging in foraging activity, and search...

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Crystal or Jelly? Effect of Color on the Perception of Translucent Materials with Photographs of Real-world Objects

Liao

Sawayama²,

Xiao

2021

Preprint

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Translucent materials are ubiquitous in nature (e.g. teeth, food, wax), but our understanding of translucency perception is limited. Previous work in translucency perception has mainly used monochromatic rendered images as stimuli, which are restricted by their diversity and realism. Here, we measure translucency perception with photographs of real-world objects. Specifically, we use three behavior tasks: binary classification of 'translucent' versus 'opaque', semantic attribute rating of perceptual qualities (see-throughness, glossiness, softness, glow and density), and material categorization. Two different groups of observers finish the three tasks with color or grayscale images. We find that observers' agreements depend on the physical material properties of the objects such that translucent materials generate more inter-observer disagreements. Further, there are more disagreements among observers in the grayscale condition in comparison to that in color condition. We also discover that converting images to grayscale substantially affects the distributions of attribute ratings for some images. Furthermore, ratings of see-throughness, glossiness, and glow could predict individual observers' binary classification of images in both grayscale and color conditions. Lastly, converting images to grayscale alters the perceived material categories for some images such that observers tend to misjudge images of food as non-food and vice versa. Our result demonstrates color is informative about material property estimation and recognition. Meanwhile, our analysis shows mid-level semantic estimation of material attributes might be closely related to high-level material recognition. We also discuss individual differences in our results and highlight the importance of such consideration in material perception.

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

Cited by 8 publications

References 75 publications

Effect of geometric sharpness on translucent material perception

Effect of geometric sharpness on translucent material perception

Material constancy in perception and working memory

Crystal or Jelly? Effect of Color on the Perception of Translucent Materials with Photographs of Real-world Objects

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