Fabricating BRDFs at high spatial resolution using wave optics

Levin, Anat; Gläsner, Daniel; Xiong, Ying; Durand, Frédo; Freeman, William R.; Matusik, Wojciech; Zickler, Todd

doi:10.1145/2461912.2461981

Cited by 57 publications

(55 citation statements)

References 46 publications

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“…Despite the accumulative nature of these effects, our prototypes convey that physical realizations maintain the overall quality of the target caustic images. An interesting direction for future work, especially once machining precision improves, is to consider the wave nature of light and study the possible resolution of caustics at the limit imposed by diffraction and incorporate partial coherence as in [Levin et al 2013]. …”

Section: Discussion and Limitationsmentioning

confidence: 99%

High-contrast computational caustic design

et al. 2014

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Figure 1: Caustic Brain: Our algorithm computes a 3D surface that refracts uniform light to focus on sharp intensity lines that sketch a human brain. The physical prototype shown on the right has been fabricated in transparent acrylic with a CNC milling machine. The photographs illustrate how the caustic image evolves as the acrylic piece is rotated into position (see also Figure 11 and accompanying video). AbstractWe present a new algorithm for computational caustic design. Our algorithm solves for the shape of a transparent object such that the refracted light paints a desired caustic image on a receiver screen. We introduce an optimal transport formulation to establish a correspondence between the input geometry and the unknown target shape. A subsequent 3D optimization based on an adaptive discretization scheme then finds the target surface from the correspondence map. Our approach supports piecewise smooth surfaces and non-bijective mappings, which eliminates a number of shortcomings of previous methods. This leads to a significantly richer space of caustic images, including smooth transitions, singularities of infinite light density, and completely black areas. We demonstrate the effectiveness of our approach with several simulated and fabricated examples.

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Section: Discussion and Limitationsmentioning

confidence: 99%

High-contrast computational caustic design

et al. 2014

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“…Researchers in graphics have proposed several designs for exploiting diffractive optics in display applications. Recent attempts to fabricate the optical surfaces with desirable BRDFs or BTDFs have been investigated [Glasner et al 2014;Levin et al 2013;Ye et al 2014]. Ye et al [2014] proposed to use multiple diffractive layers to encode a 4D BRDF or BTDF.…”

Section: Related Workmentioning

confidence: 99%

Mix-and-match holography

et al. 2017

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Fig. 1. Overview of mix-and-match holography. We computationally design pairs of diffractive optical elements that encode multiple holograms or target images under different geometric alignments or DOE pairings (top left: encoding scheme, bottom left: fabricated DOEs). By changing the geometric alignment or pairing different DOEs, the individual encoded holograms can be de-multiplexed. Illumination with a pre-determined lighting condition produces the corresponding target image, that can be generalized in a wide range of scenarios (selected results presented on the right: through offset layer pairing (a), combinational pairing (b), multiview images' encoding (c), and animated images through linear translation (d)). The design process makes use of a combination of iterative phase retrieval methods and complex matrix factorization.Computational caustics and light steering displays offer a wide range of interesting applications, ranging from art works and architectural installations to energy efficient HDR projection. In this work we expand on this concept by encoding several target images into pairs of front and rear phasedistorting surfaces. Different target holograms can be decoded by mixing and matching different front and rear surfaces under specific geometric alignments. Our approach, which we call mix-and-match holography, is made possible by moving from a refractive caustic image formation process to a diffractive, holographic one. This provides the extra bandwidth that is required to multiplex several images into pairing surfaces.We derive a detailed image formation model for the setting of holographic projection displays, as well as a multiplexing method based on a combination of phase retrieval methods and complex matrix factorization. We demonstrate several application scenarios in both simulation and physical prototypes.

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“…This means that their BRDF model is a weighted average of differently oriented ink BRDFs, where we have a combination of surface and subsurface scattering effects. Other authors [10,8] improve the microstructure resolution as compared with Weyrich et al [23], but their techniques do not allow for absorption effects. In the work of Levin et al [8], microfacets are at a scale that requires a BRDF model based on wave optics.…”

Section: Related Workmentioning

confidence: 99%

“…Other authors [10,8] improve the microstructure resolution as compared with Weyrich et al [23], but their techniques do not allow for absorption effects. In the work of Levin et al [8], microfacets are at a scale that requires a BRDF model based on wave optics. Our pitches ranging from 50 to 150 microns can safely be modeled using geometrical optics.…”

Section: Related Workmentioning

confidence: 99%

“…This research area has received significant attention [23,11,10,7,8,14] and, recently, tooling was done with the objective of inserting a simple anisotropic surface microstructure into economic manufacturing processes [9]. The intended functionality of the anisotropic surface microstructure was to obtain high reflectance contrast for the surface when viewed from above at orthogonal angles.…”

Section: Introductionmentioning

confidence: 99%

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Modeling the Anisotropic Reflectance of a Surface with Microstructure Engineered to Obtain Visible Contrast After Rotation

Luongo¹,

Falster²,

Doest³

et al. 2017

2017 IEEE International Conference on Computer Vision Workshops (ICCVW)

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Engineering of surface structure to obtain specific anisotropic reflectance properties has interesting applications in large scale production of plastic items. In recent work, surface structure has been engineered to obtain visible reflectance contrast when observing a surface before and after rotating it 90 degrees around its normal axis. We build an analytic anisotropic reflectance model based on the microstructure engineered to obtain such contrast. Using our model to render synthetic images, we predict the above mentioned contrasts and compare our predictions with the measurements reported in previous work. The benefit of an analytical model like the one we provide is its potential to be used in computer vision for estimating the quality of a surface sample. The quality of a sample is indicated by the resemblance of camera-based contrast measurements with contrasts predicted for an idealized surface structure. Our predictive model is also useful in optimization of the microstructure configuration, where the objective for example could be to maximize reflectance contrast.

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Fabricating BRDFs at high spatial resolution using wave optics

Cited by 57 publications

References 46 publications

High-contrast computational caustic design

High-contrast computational caustic design

Mix-and-match holography

Modeling the Anisotropic Reflectance of a Surface with Microstructure Engineered to Obtain Visible Contrast After Rotation

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