=Paper= {{Paper |id=Vol-2744/abstract1 |storemode=property |title=Lighting Simulation in 3D Printing (abstract) |pdfUrl=https://ceur-ws.org/Vol-2744/abstract1.pdf |volume=Vol-2744 |authors=Denis Sumin,Karol Myszkowski,Alexey Voloboy }} ==Lighting Simulation in 3D Printing (abstract)== https://ceur-ws.org/Vol-2744/abstract1.pdf 
   Lighting Simulation in 3D Printing (Abstract)*
                          Denis Sumin1, Karol Myszkowski1,
                                  Alexey Voloboy2

                           1Max-Planck-Institute for Informatics,

                                  Saarbrucken, Germany
           2The Keldysh Institute of Applied Mathematics RAS, Moscow, Russia

                                da.sumin@gmail.com



3D printing for rapid prototyping and production of unique objects is being actively
developed. Consumer-grade printers are now commonly available for a range of pur-
poses, while increasingly advanced techniques allow us to fabricate novel shapes,
mechanical properties, and appearances. The printers’ capabilities have improved
dramatically from printing single-material objects to producing detailed structures
with per-voxel material variation. Since the 2010s, it is possible to fabricate full-
colour 3D objects with resolutions of hundreds of DPI (voxels’ dimensions are in the
order of 10 µm). Such capabilities are most prominent in printers based on the photo-
polymer jetting process. Ideally, it should be possible now to produce photorealistic
appearances or visually indistinguishable objects copies for, e.g., cultural-heritage
applications.
    However, the resins used as print materials in commercial devices are inherently
translucent, i.e., exhibit significant sub-surface scattering. This serves effective colour
mixing in full-colour print processes, thus commercial printer drivers offer high-
quality colour reproduction. At the same time, the resulting light diffusion leads to
over-blurring and potential colour bleeding when printing spatially-varying colour
textures. This translucent ‘crosstalk’ between surface points also strongly depends on
the internal structure of the volume surrounding each surface point.
    Previously existing scattering-aware methods used simplified models for light dif-
fusion and accepted the visual blur as an immutable property of the print medium.
    In this talk, we present the series of works conducted by a consortium of several
institutes (Max-Planck Institute for Informatics, Germany; Charles University in Pra-
gue, Czech Republic; Institute of Science and Technology, Austria; University Col-
lege London, United Kingdom; Universita della Svizzera Italiana, Switzerland; The
Keldysh Institute of Applied Mathematics RAS, Russia). Our work counteracts heter-
ogeneous 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.
    We build our iterative method on top of a general Monte-Carlo simulation of het-
erogeneous scattering. We find out that a certain arrangement of materials expands
the gamut of achievable appearances and makes it possible to produce sharp textures.

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Commons License Attribution 4.0 International (CC BY 4.0).
2 D. Sumin et al.


This knowledge built-in into the volume-update step enables convergence just after
10–15 iterations. We verify these findings using an established stochastic gradient-
descent optimization for small canonical objects where it is feasible computationally.
    Expansion of our method to fabrication of arbitrary 3D objects with the translu-
cent resins opens a set of problems of achievable colour combinations on the two
sides of thin shapes, in the extreme convex and concave shapes. Physically correct
lighting simulation enables exploration of these extreme cases where no ideal solution
is possible. It turns out that a re-formulation of established gamut-mapping methods is
needed for the medium with the inherent cross-talk properties such as the scattering
resins of the modern full-colour 3D printers.
    Elaborating further ideas from we also propose a fast forward predictor of the ob-
ject's surface appearance based on a neural network to replace the Monte-Carlo simu-
lation in order to speed up the preparation of the model by 300 times. The achieved
acceleration allows to reduce simulation time to minutes for a single, GPU-equipped
workstation. This makes the print preparation timings practical.