Geometry-Aware Scattering Compensation for 3D Printing

Commercially available full-color 3D printing allows for detailed control of material deposition in a volume, but an exact reproduction of a target surface appearance is hampered by the strong subsurface scattering that causes nontrivial volumetric cross-talk at the print surface. Previous work showed how an iterative optimization scheme based on accumulating absorptive materials at the surface can be used to find a volumetric distribution of print materials that closely approximates a given target appearance. // In this work, we first revisit the assumption that pushing the absorptive materials to the surface results in minimal volumetric cross-talk. We design a full-fledged optimization on a small domain for this task and confirm this previously reported heuristic. Then, we extend the above approach that is critically limited to color reproduction on planar surfaces, to arbitrary 3D shapes. Our proposed method enables high-fidelity color texture reproduction on 3D prints by effectively compensating for internal light scattering within arbitrarily shaped objects. In addition, we propose a content-aware gamut mapping that significantly improves color reproduction for the pathological case of thin geometric features. Using a wide range of sample objects with complex textures and geometries, we demonstrate color reproduction whose fidelity is superior to state-of-the-art drivers for color 3D printers

A Radiative Transfer Framework for Spatially-Correlated Materials

We introduce a non-exponential radiative framework that takes into account the local spatial correlation of scattering particles in a medium. Most previous works in graphics have ignored this, assuming uncorrelated media with a uniform, random local distribution of particles. However, positive and negative correlation lead to slower- and faster-than-exponential attenuation respectively, which cannot be predicted by the Beer-Lambert law. As our results show, this has a major effect on extinction, and thus appearance. From recent advances in neutron transport, we first introduce our Extended Generalized Boltzmann Equation, and develop a general framework for light transport in correlated media. We lift the limitations of the original formulation, including an analysis of the boundary conditions, and present a model suitable for computer graphics, based on optical properties of the media and statistical distributions of scatterers. In addition, we present an analytic expression for transmittance in the case of positive correlation, and show how to incorporate it efficiently into a Monte Carlo renderer. We show results with a wide range of both positive and negative correlation, and demonstrate the differences compared to classic light transport

Downsampling scattering parameters for rendering anisotropic media

© 2016 ACM. Volumetric micro-appearance models have provided remarkably high-quality renderings, but are highly data intensive and usually require tens of gigabytes in storage. When an object is viewed from a distance, the highest level of detail offered by these models is usually unnecessary, but traditional linear downsampling weakens the object's intrinsic shadowing structures and can yield poor accuracy. We introduce a joint optimization of single-scattering albedos and phase functions to accurately downsample heterogeneous and anisotropic media. Our method is built upon scaled phase functions, a new representation combining abledos and (standard) phase functions. We also show that modularity can be exploited to greatly reduce the amortized optimization overhead by allowing multiple synthesized models to share one set of downsampled parameters. Our optimized parameters generalize well to novel lighting and viewing configurations, and the resulting data sets offer several orders of magnitude storage savings

Downsampling Scattering Parameters for Rendering Anisotropic Media

Volumetric micro-appearance models have provided remarkably high-quality renderings, but are highly data intensive and usually require tens of gigabytes in storage. When an object is viewed from a distance, the highest level of detail offered by these models is usually unnecessary, but traditional linear downsampling weakens the object's intrinsic shadowing structures and can yield poor accuracy. We introduce a joint optimization of single-scattering albedos and phase functions to accurately downsample heterogeneous and anisotropic media. Our method is built upon scaled phase functions , a new representation combining abledos and (standard) phase functions. We also show that modularity can be exploited to greatly reduce the amortized optimization overhead by allowing multiple synthesized models to share one set of down-sampled parameters. Our optimized parameters generalize well to novel lighting and viewing configurations, and the resulting data sets offer several orders of magnitude storage savings