A Gradient-Based Framework for 3D Print Appearance Optimization

Thomas Nindel Tomáš Iser Tobias Rittig Alexander Wilkie Jaroslav Křivánek

Abstract

In full-color inkjet 3D printing, a key problem is determining the material configuration for the millions of voxels that a printed object is made of. The goal is a configuration that minimises the difference between desired target appearance and the result of the printing process. So far, the techniques used to find such a configuration have relied on domain-specific methods or heuristic optimization, which allowed only a limited level of control over the resulting appearance. We propose to use differentiable volume rendering in a continuous materialmixture space, which leads to a framework that can be used as a general tool for optimising inkjet 3D printouts. We demonstrate the technical feasibility of this approach, and use it to attain fine control over the fabricated appearance, and high levels of faithfulness to the specified target

Presentation Video

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August 2021
ACM Transactions on Graphics, Proceedings of SIGGRAPH
Conference Paper, Journal Paper
3D Printing, Appearance modelling, Differentiable Rendering, Monte Carlo, Volume rendering

Reference

Thomas Nindel, Tomáš Iser, Tobias Rittig, Alexander Wilkie, and Jaroslav Křivánek. A Gradient-Based Framework for 3D Print Appearance Optimization. ACM Transactions on Graphics (Proceedings of SIGGRAPH 2021), 40(4), 2021.

Acknowledgments

We thank Sketchfab users Evgeni Yanev (Orange Slice), C. Yamahata and Thot_htp (Nefertiti) for their 3D models, and the reviewers for their valuable feedback. This work has received funding from GA UK project 1164620 of Charles University, and by the Czech Science Foundation under grant number GAČR-19-07626S. This work was further supported by the Charles University grant SVV-260588.

BibTex Citation

				
					@article{10.1145/3450626.3459844,
author = {Nindel, Thomas Klaus and Iser, Tom\'{a}\v{s} and Rittig, Tobias and Wilkie, Alexander and K\v{r}iv\'{a}nek, Jaroslav},
title = {A Gradient-Based Framework for 3D Print Appearance Optimization},
year = {2021},
issue_date = {August 2021},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {40},
number = {4},
issn = {0730-0301},
url = {https://doi.org/10.1145/3450626.3459844},
doi = {10.1145/3450626.3459844},
abstract = {In full-color inkjet 3D printing, a key problem is determining the material configuration
for the millions of voxels that a printed object is made of. The goal is a configuration
that minimises the difference between desired target appearance and the result of
the printing process. So far, the techniques used to find such a configuration have
relied on domain-specific methods or heuristic optimization, which allowed only a
limited level of control over the resulting appearance.We propose to use differentiable
volume rendering in a continuous material-mixture space, which leads to a framework
that can be used as a general tool for optimising inkjet 3D printouts. We demonstrate
the technical feasibility of this approach, and use it to attain fine control over
the fabricated appearance, and high levels of faithfulness to the specified target.},
journal = {ACM Trans. Graph.},
month = jul,
articleno = {178},
numpages = {15},
keywords = {volumetric optimization, large-scale optimization, volumetric light transport, image metrics, computational fabrication, appearance reproduction, 3D printing}
}