Understanding the role of phase function in translucent appearance

Gkioulekas, Ioannis; Xiao, Bei; Zhao, Shuang; Adelson, Edward H.; Zickler, Todd; Bala, Kavita

doi:10.1145/2516971.2516972

Cited by 85 publications

(98 citation statements)

References 59 publications

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“…In this context, our work is similar to Pellacini et al [2000] and Wills et al [2009], which propose a perceptual space for gloss, and Gkioulekas et al [2013], where perception of translucent materials is studied. Pellacini et al use standard multi-dimensional scaling (MDS), which is based on the distances between different images reported by a subject, to learn a two-dimensional space of bi-direction reflectance distribution functions (BRDF).…”

Section: Materials Perception In Computer Graphicsmentioning

confidence: 97%

An interaction-aware, perceptual model for non-linear elastic objects

Piovarči

Levin

Rebello³

et al. 2016

ACM Trans. Graph.

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Force-displacement Force histogramPhysically based simulation Stiff Soft Figure 1: 3D printing allows us to print objects with varying deformation properties. The question that we want to answer is: Given a set of printing materials and a 3D object with desired elasticity properties, which material should be used to print the object? For example, given sample ducks (left) with desired elasticity properties (e.g., measured), our system considers several candidate materials that can be used for replicating the ducks (right), and chooses materials that will best match compliance properties when examined by an observer (red and green outlines). Moreover, we can sort all possible materials by their perceived compliance as predicted by our model. The measured compliance is indicated with colors ranging from stiff (blue) to soft (red). AbstractEveryone, from a shopper buying shoes to a doctor palpating a growth, uses their sense of touch to learn about the world. 3D printing is a powerful technology because it gives us the ability to control the haptic impression an object creates. This is critical for both replicating existing, real-world constructs and designing novel ones. However, each 3D printer has different capabilities and supports different materials, leaving us to ask: How can we best replicate a given haptic result on a particular output device? In this work, we address the problem of mapping a real-world material to its nearest 3D printable counterpart by constructing a perceptual model for the compliance of nonlinearly elastic objects. We begin by building a perceptual space from experimentally obtained user comparisons of twelve 3D-printed metamaterials. By comparing this space to a number of hypothetical computational models, we identify those that can be used to accurately and efficiently evaluate human-perceived differences in nonlinear stiffness. Furthermore, we demonstrate how such models can be applied to complex geometries in an interaction-aware way where the compliance is influenced not only by the material properties from which the object is made but also its geometry. We demonstrate several applications of our method in the context of fabrication and evaluate them in a series of user experiments.

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Section: Materials Perception In Computer Graphicsmentioning

confidence: 97%

An interaction-aware, perceptual model for non-linear elastic objects

Piovarči

Levin

Rebello³

et al. 2016

ACM Trans. Graph.

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“…7) could subjectively improve our results even further. In general, the perception of heterogeneous translucency is largely an open topic [Fleming and Bültho 2005;Fleming et al 2004;Gkioulekas et al 2013a] and deserves a dedicated treatment.…”

Section: Printer Defaultmentioning

confidence: 99%

Scattering-aware texture reproduction for 3D printing

Elek

Sumin

Zhang³

et al. 2017

ACM Trans. Graph.

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Fig. 1. A still life photograph of our optimized printouts. The thickness of all the pictured samples is 1 cm.Color texture reproduction in 3D printing commonly ignores volumetric light transport (cross-talk) between surface points on a 3D print. Such light di usion leads to signi cant blur of details and color bleeding, and is particularly severe for highly translucent resin-based print materials. Given their widely varying scattering properties, this cross-talk between surface points strongly depends on the internal structure of the volume surrounding each surface point. Existing scattering-aware methods use simpli ed models for light di usion, and often accept the visual blur as an immutable property of the print medium. In contrast, our work counteracts heterogeneous scattering to obtain the impression of a crisp albedo texture on top of the 3D print, by optimizing for a fully volumetric material distribution that preserves the target appearance. Our method employs an e cient numerical optimizer on top of a general Monte-Carlo simulation of heterogeneous scattering, supported by a practical calibration procedure to obtain scattering parameters from a given set of printer materials. Despite the inherent translucency of the medium, we reproduce detailed surface textures on 3D prints. We evaluate our system using a commercial, ve-tone 3D print process and compare against the printer's native color texturing mode, demonstrating *Oskar Elek and Denis Sumin share the rst authorship of this work. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro t or commercial advantage and that copies bear this notice and the full citation on the rst page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior speci c permission and/or a fee. Request permissions from permissions@acm.org. © 2017 ACM. 0730-0301/2017/11-ART241 $15.00 DOI: 10.1145/3130800.3130890 that our method preserves high-frequency features well without having to compromise on color gamut.

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“…• , 30 [13]. We use density σ t = 1mm −1 and a field of view (length of "position" axis) of approximately one inch.…”

Section: Scattering Near An Orientation Discontinuitymentioning

confidence: 99%

“…As the space of phase functions p(θ) is infinite dimensional, we focus only on its first two angular moments m 1 and m 2 , which have been shown to dominate translucent appearance [13,27]. As shown in Figure 8, increasing the first moment (average direction) increases the normalized radiance of the local extrema, with a smaller effect on their locations.…”

Section: Scattering Materials Parametersmentioning

confidence: 99%

“…This internal scattering can create a variety of image effects, depending on an object's shape and material; its distance from the observer; and the composition of the lighting around it. Common human experience suggests that these image effects contain useful material information, and there is psychophysical evidence that humans can discriminate subtle differences in translucent appearance, recognize translucent material categories, and make inferences about physical scattering parameters [2,11,13,27].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the appearance of translucent edges

Gkioulekas¹,

Walter

Adelson

et al. 2015

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

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Edges in images of translucent objects are very different from edges in images of opaque objects. The physical causes for these differences are hard to characterize analytically and are not well understood. This paper considers one class of translucency edges-those caused by a discontinuity in surface orientation-and describes the physical causes of their appearance. We simulate thousands of translucency edge profiles using many different scattering material parameters, and we explain the resulting variety of edge patterns by qualitatively analyzing light transport. We also discuss the existence of shape and material metamers, or combinations of distinct shape or material parameters that generate the same edge profile. This knowledge is relevant to visual inference tasks that involve translucent objects, such as shape or material estimation.

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Understanding the role of phase function in translucent appearance

Cited by 85 publications

References 59 publications

An interaction-aware, perceptual model for non-linear elastic objects

An interaction-aware, perceptual model for non-linear elastic objects

Scattering-aware texture reproduction for 3D printing

On the appearance of translucent edges

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