107 research outputs found
Dynamic Display of BRDFs
This paper deals with the challenge of physically displaying reflectance, i.e., the appearance of a surface and its variation with the observer position and the illuminating environment. This is commonly described by the bidirectional reflectance distribution function (BRDF). We provide a catalogue of criteria for the display of BRDFs, and sketch a few orthogonal approaches to solving the problem in an optically passive way. Our specific implementation is based on a liquid surface, on which we excite waves in order to achieve a varying degree of anisotropic roughness. The resulting probability density function of the surface normal is shown to follow a Gaussian distribution similar to most established BRDF models
A Similarity Measure for Material Appearance
We present a model to measure the similarity in appearance between different
materials, which correlates with human similarity judgments. We first create a
database of 9,000 rendered images depicting objects with varying materials,
shape and illumination. We then gather data on perceived similarity from
crowdsourced experiments; our analysis of over 114,840 answers suggests that
indeed a shared perception of appearance similarity exists. We feed this data
to a deep learning architecture with a novel loss function, which learns a
feature space for materials that correlates with such perceived appearance
similarity. Our evaluation shows that our model outperforms existing metrics.
Last, we demonstrate several applications enabled by our metric, including
appearance-based search for material suggestions, database visualization,
clustering and summarization, and gamut mapping.Comment: 12 pages, 17 figure
An intuitive control space for material appearance
Many different techniques for measuring material appearance have been
proposed in the last few years. These have produced large public datasets,
which have been used for accurate, data-driven appearance modeling. However,
although these datasets have allowed us to reach an unprecedented level of
realism in visual appearance, editing the captured data remains a challenge. In
this paper, we present an intuitive control space for predictable editing of
captured BRDF data, which allows for artistic creation of plausible novel
material appearances, bypassing the difficulty of acquiring novel samples. We
first synthesize novel materials, extending the existing MERL dataset up to 400
mathematically valid BRDFs. We then design a large-scale experiment, gathering
56,000 subjective ratings on the high-level perceptual attributes that best
describe our extended dataset of materials. Using these ratings, we build and
train networks of radial basis functions to act as functionals mapping the
perceptual attributes to an underlying PCA-based representation of BRDFs. We
show that our functionals are excellent predictors of the perceived attributes
of appearance. Our control space enables many applications, including intuitive
material editing of a wide range of visual properties, guidance for gamut
mapping, analysis of the correlation between perceptual attributes, or novel
appearance similarity metrics. Moreover, our methodology can be used to derive
functionals applicable to classic analytic BRDF representations. We release our
code and dataset publicly, in order to support and encourage further research
in this direction
BRDF representation and acquisition
Photorealistic rendering of real world environments is important in a range of different areas; including Visual Special effects, Interior/Exterior Modelling, Architectural Modelling, Cultural Heritage, Computer Games and Automotive Design.
Currently, rendering systems are able to produce photorealistic simulations of the appearance of many real-world materials. In the real world, viewer perception of objects depends on the lighting and object/material/surface characteristics, the way a surface interacts with the light and on how the light is reflected, scattered, absorbed by the surface and the impact these characteristics have on material appearance. In order to re-produce this, it is necessary to understand how materials interact with light. Thus the representation and acquisition of material models has become such an active research area.
This survey of the state-of-the-art of BRDF Representation and Acquisition presents an overview of BRDF (Bidirectional Reflectance Distribution Function) models used to represent surface/material reflection characteristics, and describes current acquisition methods for the capture and rendering of photorealistic materials
BRDF Representation and Acquisition
Photorealistic rendering of real world environments is important in a range of different areas; including Visual Special effects, Interior/Exterior Modelling, Architectural Modelling, Cultural Heritage, Computer Games and Automotive Design. Currently, rendering systems are able to produce photorealistic simulations of the appearance of many real-world materials. In the real world, viewer perception of objects depends on the lighting and object/material/surface characteristics, the way a surface interacts with the light and on how the light is reflected, scattered, absorbed by the surface and the impact these characteristics have on material appearance. In order to re-produce this, it is necessary to understand how materials interact with light. Thus the representation and acquisition of material models has become such an active research area. This survey of the state-of-the-art of BRDF Representation and Acquisition presents an overview of BRDF (Bidirectional Reflectance Distribution Function) models used to represent surface/material reflection characteristics, and describes current acquisition methods for the capture and rendering of photorealistic materials
Intuitive and Accurate Material Appearance Design and Editing
Creating and editing high-quality materials for photorealistic rendering can be a difficult task due to the diversity and complexity of material appearance. Material design is the process by which artists specify the reflectance properties of a surface, such as its diffuse color and specular roughness. Even with the support of commercial software packages, material design can be a time-consuming trial-and-error task due to the counter-intuitive nature of the complex reflectance models. Moreover, many material design tasks require the physical realization of virtually designed materials as the final step, which makes the process even more challenging due to rendering artifacts and the limitations of fabrication. In this dissertation, we propose a series of studies and novel techniques to improve the intuitiveness and accuracy of material design and editing. Our goal is to understand how humans visually perceive materials, simplify user interaction in the design process and, and improve the accuracy of the physical fabrication of designs. Our first work focuses on understanding the perceptual dimensions for measured material data. We build a perceptual space based on a low-dimensional reflectance manifold that is computed from crowd-sourced data using a multi-dimensional scaling model. Our analysis shows the proposed perceptual space is consistent with the physical interpretation of the measured data. We also put forward a new material editing interface that takes advantage of the proposed perceptual space. We visualize each dimension of the manifold to help users understand how it changes the material appearance. Our second work investigates the relationship between translucency and glossiness in material perception. We conduct two human subject studies to test if subsurface scattering impacts gloss perception and examine how the shape of an object influences this perception. Based on our results, we discuss why it is necessary to include transparent and translucent media for future research in gloss perception and material design. Our third work addresses user interaction in the material design system. We present a novel Augmented Reality (AR) material design prototype, which allows users to visualize their designs against a real environment and lighting. We believe introducing AR technology can make the design process more intuitive and improve the authenticity of the results for both novice and experienced users. To test this assumption, we conduct a user study to compare our prototype with the traditional material design system with gray-scale background and synthetic lighting. The results demonstrate that with the help of AR techniques, users perform better in terms of objectively measured accuracy and time and they are subjectively more satisfied with their results. Finally, our last work turns to the challenge presented by the physical realization of designed materials. We propose a learning-based solution to map the virtually designed appearance to a meso-scale geometry that can be easily fabricated. Essentially, this is a fitting problem, but compared with previous solutions, our method can provide the fabrication recipe with higher reconstruction accuracy for a large fitting gamut. We demonstrate the efficacy of our solution by comparing the reconstructions with existing solutions and comparing fabrication results with the original design. We also provide an application of bi-scale material editing using the proposed method
Fabricating BRDFs at high spatial resolution using wave optics
Recent attempts to fabricate surfaces with custom reflectance functions boast impressive angular resolution, yet their spatial resolution is limited. In this paper we present a method to construct spatially varying reflectance at a high resolution of up to 220dpi, orders of magnitude greater than previous attempts, albeit with a lower angular resolution. The resolution of previous approaches is limited by the machining, but more fundamentally, by the geometric optics model on which they are built. Beyond a certain scale geometric optics models break down and wave effects must be taken into account. We present an analysis of incoherent reflectance based on wave optics and gain important insights into reflectance design. We further suggest and demonstrate a practical method, which takes into account the limitations of existing micro-fabrication techniques such as photolithography to design and fabricate a range of reflection effects, based on wave interference.United States-Israel Binational Science FoundationIntel Corporation (Intel Collaborative Research Institute for Computational Intelligence)National Science Foundation (U.S.) (CGV 1116303
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