---
_id: '12976'
abstract:
- lang: eng
text: "3D printing based on continuous deposition of materials, such as filament-based
3D printing, has seen widespread adoption thanks to its versatility in working
with a wide range of materials. An important shortcoming of this type of technology
is its limited multi-material capabilities. While there are simple hardware designs
that enable multi-material printing in principle, the required software is heavily
underdeveloped. A typical hardware design fuses together individual materials
fed into a single chamber from multiple inlets before they are deposited. This
design, however, introduces a time delay between the intended material mixture
and its actual deposition. In this work, inspired by diverse path planning research
in robotics, we show that this mechanical challenge can be addressed via improved
printer control. We propose to formulate the search for optimal multi-material
printing policies in a reinforcement\r\nlearning setup. We put forward a simple
numerical deposition model that takes into account the non-linear material mixing
and delayed material deposition. To validate our system we focus on color fabrication,
a problem known for its strict requirements for varying material mixtures at a
high spatial frequency. We demonstrate that our learned control policy outperforms
state-of-the-art hand-crafted algorithms."
acknowledgement: This work is graciously supported by FWF Lise Meitner (Grant M 3319).
Kang Liao sincerely thank Emiliano Luci, Chunyu Lin, and Yao Zhao for their huge
support.
article_processing_charge: No
author:
- first_name: Kang
full_name: Liao, Kang
last_name: Liao
- first_name: Thibault
full_name: Tricard, Thibault
last_name: Tricard
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Hans-Peter
full_name: Seidel, Hans-Peter
last_name: Seidel
- first_name: Vahid
full_name: Babaei, Vahid
last_name: Babaei
citation:
ama: 'Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. Learning deposition policies
for fused multi-material 3D printing. In: 2023 IEEE International Conference
on Robotics and Automation. Vol 2023. IEEE; 2023:12345-12352. doi:10.1109/ICRA48891.2023.10160465'
apa: 'Liao, K., Tricard, T., Piovarci, M., Seidel, H.-P., & Babaei, V. (2023).
Learning deposition policies for fused multi-material 3D printing. In 2023
IEEE International Conference on Robotics and Automation (Vol. 2023, pp. 12345–12352).
London, United Kingdom: IEEE. https://doi.org/10.1109/ICRA48891.2023.10160465'
chicago: Liao, Kang, Thibault Tricard, Michael Piovarci, Hans-Peter Seidel, and
Vahid Babaei. “Learning Deposition Policies for Fused Multi-Material 3D Printing.”
In 2023 IEEE International Conference on Robotics and Automation, 2023:12345–52.
IEEE, 2023. https://doi.org/10.1109/ICRA48891.2023.10160465.
ieee: K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, and V. Babaei, “Learning deposition
policies for fused multi-material 3D printing,” in 2023 IEEE International
Conference on Robotics and Automation, London, United Kingdom, 2023, vol.
2023, pp. 12345–12352.
ista: 'Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. 2023. Learning deposition
policies for fused multi-material 3D printing. 2023 IEEE International Conference
on Robotics and Automation. ICRA: International Conference on Robotics and Automation
vol. 2023, 12345–12352.'
mla: Liao, Kang, et al. “Learning Deposition Policies for Fused Multi-Material 3D
Printing.” 2023 IEEE International Conference on Robotics and Automation,
vol. 2023, IEEE, 2023, pp. 12345–52, doi:10.1109/ICRA48891.2023.10160465.
short: K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, V. Babaei, in:, 2023 IEEE
International Conference on Robotics and Automation, IEEE, 2023, pp. 12345–12352.
conference:
end_date: 2023-06-02
location: London, United Kingdom
name: 'ICRA: International Conference on Robotics and Automation'
start_date: 2023-05-29
date_created: 2023-05-16T09:14:09Z
date_published: 2023-07-04T00:00:00Z
date_updated: 2025-04-15T07:43:52Z
day: '04'
ddc:
- '004'
department:
- _id: BeBi
doi: 10.1109/ICRA48891.2023.10160465
external_id:
isi:
- '001048371104068'
file:
- access_level: open_access
checksum: daeaa67124777d88487f933ea3f77164
content_type: application/pdf
creator: mpiovarc
date_created: 2023-05-16T09:12:05Z
date_updated: 2023-05-16T09:12:05Z
file_id: '12977'
file_name: Liao2023.pdf
file_size: 5367986
relation: main_file
success: 1
file_date_updated: 2023-05-16T09:12:05Z
has_accepted_license: '1'
intvolume: ' 2023'
isi: 1
keyword:
- reinforcement learning
- deposition
- control
- color
- multi-filament
language:
- iso: eng
month: '07'
oa: 1
oa_version: Submitted Version
page: 12345-12352
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
publication: 2023 IEEE International Conference on Robotics and Automation
publication_identifier:
eisbn:
- '9798350323658'
issn:
- 1050-4729
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Learning deposition policies for fused multi-material 3D printing
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2023
year: '2023'
...
---
_id: '12979'
abstract:
- lang: eng
text: 'Color and gloss are fundamental aspects of surface appearance. State-of-the-art
fabrication techniques can manipulate both properties of the printed 3D objects.
However, in the context of appearance reproduction, perceptual aspects of color
and gloss are usually handled separately, even though previous perceptual studies
suggest their interaction. Our work is motivated by previous studies demonstrating
a perceived color shift due to a change in the object''s gloss, i.e., two samples
with the same color but different surface gloss appear as they have different
colors. In this paper, we conduct new experiments which support this observation
and provide insights into the magnitude and direction of the perceived color change.
We use the observations as guidance to design a new method that estimates and
corrects the color shift enabling the fabrication of objects with the same perceived
color but different surface gloss. We formulate the problem as an optimization
procedure solved using differentiable rendering. We evaluate the effectiveness
of our method in perceptual experiments with 3D objects fabricated using a multi-material
3D printer and demonstrate potential applications. '
acknowledgement: We thank Matthew S Zurawski for the 3D model of the car speed shape.
This research has been supported by the Swiss National Science Foundation (SNSF,
Grant 200502) and the FWF Lise Meitner (Grant M 3319).
article_number: '21'
article_processing_charge: Yes (via OA deal)
author:
- first_name: Jorge
full_name: Condor, Jorge
last_name: Condor
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
citation:
ama: 'Condor J, Piovarci M, Bickel B, Didyk P. Gloss-aware color correction for
3D printing. In: SIGGRAPH ’23 Conference Proceedings. Association for Computing
Machinery; 2023. doi:10.1145/3588432.3591546'
apa: 'Condor, J., Piovarci, M., Bickel, B., & Didyk, P. (2023). Gloss-aware
color correction for 3D printing. In SIGGRAPH ’23 Conference Proceedings.
Los Angeles, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3588432.3591546'
chicago: Condor, Jorge, Michael Piovarci, Bernd Bickel, and Piotr Didyk. “Gloss-Aware
Color Correction for 3D Printing.” In SIGGRAPH ’23 Conference Proceedings.
Association for Computing Machinery, 2023. https://doi.org/10.1145/3588432.3591546.
ieee: J. Condor, M. Piovarci, B. Bickel, and P. Didyk, “Gloss-aware color correction
for 3D printing,” in SIGGRAPH ’23 Conference Proceedings, Los Angeles,
CA, United States, 2023.
ista: 'Condor J, Piovarci M, Bickel B, Didyk P. 2023. Gloss-aware color correction
for 3D printing. SIGGRAPH ’23 Conference Proceedings. SIGGRAPH: Computer Graphics
and Interactive Techniques Conference, 21.'
mla: Condor, Jorge, et al. “Gloss-Aware Color Correction for 3D Printing.” SIGGRAPH
’23 Conference Proceedings, 21, Association for Computing Machinery, 2023,
doi:10.1145/3588432.3591546.
short: J. Condor, M. Piovarci, B. Bickel, P. Didyk, in:, SIGGRAPH ’23 Conference
Proceedings, Association for Computing Machinery, 2023.
conference:
end_date: 2023-08-10
location: Los Angeles, CA, United States
name: 'SIGGRAPH: Computer Graphics and Interactive Techniques Conference'
start_date: 2023-08-06
corr_author: '1'
date_created: 2023-05-16T09:34:13Z
date_published: 2023-07-23T00:00:00Z
date_updated: 2025-04-15T07:43:53Z
day: '23'
ddc:
- '004'
department:
- _id: BeBi
doi: 10.1145/3588432.3591546
external_id:
isi:
- '001117690500021'
file:
- access_level: open_access
checksum: 84a437739af5d46507928939b20c0c28
content_type: application/pdf
creator: mpiovarc
date_created: 2023-05-16T09:32:50Z
date_updated: 2023-05-16T09:32:50Z
file_id: '12983'
file_name: Condor2023_supplemental.pdf
file_size: 42323971
relation: main_file
success: 1
- access_level: open_access
checksum: 0f5c8b242e8e7c153c04888c4d0c6f37
content_type: application/pdf
creator: dernst
date_created: 2024-01-29T10:14:10Z
date_updated: 2024-01-29T10:14:10Z
file_id: '14893'
file_name: 2023_Siggraph_Condor.pdf
file_size: 26079404
relation: main_file
success: 1
file_date_updated: 2024-01-29T10:14:10Z
has_accepted_license: '1'
isi: 1
keyword:
- color
- gloss
- perception
- color compensation
- color management
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
publication: SIGGRAPH ’23 Conference Proceedings
publication_identifier:
isbn:
- '9798400701597'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Gloss-aware color correction for 3D printing
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '12984'
abstract:
- lang: eng
text: Tattoos are a highly popular medium, with both artistic and medical applications.
Although the mechanical process of tattoo application has evolved historically,
the results are reliant on the artisanal skill of the artist. This can be especially
challenging for some skin tones, or in cases where artists lack experience. We
provide the first systematic overview of tattooing as a computational fabrication
technique. We built an automated tattooing rig and a recipe for the creation of
silicone sheets mimicking realistic skin tones, which allowed us to create an
accurate model predicting tattoo appearance. This enables several exciting applications
including tattoo previewing, color retargeting, novel ink spectra optimization,
color-accurate prosthetics, and more.
acknowledged_ssus:
- _id: M-Shop
acknowledgement: We thank Todor Asenov and the Miba Machine Shop for their help in
assembling the tattoo machine and manufacturing the substrates. We thank Geysler
Rodrigues for the insightful discussions on tattooing practices from a professional
artist's perspective. We thank Maria Fernanda Portugal for sharing a doctor's perspective
on medical applications of tattoos. This work is graciously supported by the FWF
Lise Meitner (Grant M 3319).
article_number: '67'
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Alexandre
full_name: Chapiro, Alexandre
last_name: Chapiro
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
citation:
ama: 'Piovarci M, Chapiro A, Bickel B. Skin-Screen: A computational fabrication
framework for color tattoos. ACM Transactions on Graphics. 2023;42(4).
doi:10.1145/3592432'
apa: 'Piovarci, M., Chapiro, A., & Bickel, B. (2023). Skin-Screen: A computational
fabrication framework for color tattoos. ACM Transactions on Graphics.
Los Angeles, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3592432'
chicago: 'Piovarci, Michael, Alexandre Chapiro, and Bernd Bickel. “Skin-Screen:
A Computational Fabrication Framework for Color Tattoos.” ACM Transactions
on Graphics. Association for Computing Machinery, 2023. https://doi.org/10.1145/3592432.'
ieee: 'M. Piovarci, A. Chapiro, and B. Bickel, “Skin-Screen: A computational fabrication
framework for color tattoos,” ACM Transactions on Graphics, vol. 42, no.
4. Association for Computing Machinery, 2023.'
ista: 'Piovarci M, Chapiro A, Bickel B. 2023. Skin-Screen: A computational fabrication
framework for color tattoos. ACM Transactions on Graphics. 42(4), 67.'
mla: 'Piovarci, Michael, et al. “Skin-Screen: A Computational Fabrication Framework
for Color Tattoos.” ACM Transactions on Graphics, vol. 42, no. 4, 67, Association
for Computing Machinery, 2023, doi:10.1145/3592432.'
short: M. Piovarci, A. Chapiro, B. Bickel, ACM Transactions on Graphics 42 (2023).
conference:
end_date: 2023-08-10
location: Los Angeles, CA, United States
name: 'SIGGRAPH: Computer Graphics and Interactive Techniques Conference'
start_date: 2023-08-06
corr_author: '1'
date_created: 2023-05-16T09:39:14Z
date_published: 2023-07-26T00:00:00Z
date_updated: 2025-04-15T07:43:53Z
day: '26'
ddc:
- '004'
department:
- _id: BeBi
doi: 10.1145/3592432
external_id:
isi:
- '001044671300033'
file:
- access_level: open_access
checksum: 5f0a6867689e025a661bd0b4fd90b821
content_type: application/pdf
creator: mpiovarc
date_created: 2023-05-16T09:38:25Z
date_updated: 2023-05-16T09:38:25Z
file_id: '12985'
file_name: Piovarci2023.pdf
file_size: 30817343
relation: main_file
success: 1
- access_level: open_access
checksum: 6dd371de5b517e5f184f9c2cbea4b8b3
content_type: application/pdf
creator: dernst
date_created: 2024-04-16T05:52:18Z
date_updated: 2024-04-16T05:52:18Z
file_id: '15324'
file_name: 2023_ACM_Piovarci.pdf
file_size: 30281676
relation: main_file
success: 1
file_date_updated: 2024-04-16T05:52:18Z
has_accepted_license: '1'
intvolume: ' 42'
isi: 1
issue: '4'
keyword:
- appearance
- modeling
- reproduction
- tattoo
- skin color
- gamut mapping
- ink-optimization
- prosthetic
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Skin-Screen: A computational fabrication framework for color tattoos'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 42
year: '2023'
...
---
_id: '9943'
abstract:
- lang: eng
text: Segmentation is the process of partitioning digital images into meaningful
regions. The analysis of biological high content images often requires segmentation
as a first step. We propose ilastik as an easy-to-use tool which allows the user
without expertise in image processing to perform segmentation and classification
in a unified way. ilastik learns from labels provided by the user through a convenient
mouse interface. Based on these labels, ilastik infers a problem specific segmentation.
A random forest classifier is used in the learning step, in which each pixel's
neighborhood is characterized by a set of generic (nonlinear) features. ilastik
supports up to three spatial plus one spectral dimension and makes use of all
dimensions in the feature calculation. ilastik provides realtime feedback that
enables the user to interactively refine the segmentation result and hence further
fine-tune the classifier. An uncertainty measure guides the user to ambiguous
regions in the images. Real time performance is achieved by multi-threading which
fully exploits the capabilities of modern multi-core machines. Once a classifier
has been trained on a set of representative images, it can be exported and used
to automatically process a very large number of images (e.g. using the CellProfiler
pipeline). ilastik is an open source project and released under the BSD license
at www.ilastik.org.
article_processing_charge: No
author:
- first_name: Christoph M
full_name: Sommer, Christoph M
id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87
last_name: Sommer
orcid: 0000-0003-1216-9105
- first_name: Christoph
full_name: Straehle, Christoph
last_name: Straehle
- first_name: Ullrich
full_name: Köthe, Ullrich
last_name: Köthe
- first_name: Fred A.
full_name: Hamprecht, Fred A.
last_name: Hamprecht
citation:
ama: 'Sommer CM, Straehle C, Köthe U, Hamprecht FA. Ilastik: Interactive learning
and segmentation toolkit. In: 2011 IEEE International Symposium on Biomedical
Imaging: From Nano to Micro. Institute of Electrical and Electronics Engineers;
2011. doi:10.1109/isbi.2011.5872394'
apa: 'Sommer, C. M., Straehle, C., Köthe, U., & Hamprecht, F. A. (2011). Ilastik:
Interactive learning and segmentation toolkit. In 2011 IEEE International Symposium
on Biomedical Imaging: from Nano to Micro. Chicago, Illinois, USA: Institute
of Electrical and Electronics Engineers. https://doi.org/10.1109/isbi.2011.5872394'
chicago: 'Sommer, Christoph M, Christoph Straehle, Ullrich Köthe, and Fred A. Hamprecht.
“Ilastik: Interactive Learning and Segmentation Toolkit.” In 2011 IEEE International
Symposium on Biomedical Imaging: From Nano to Micro. Institute of Electrical
and Electronics Engineers, 2011. https://doi.org/10.1109/isbi.2011.5872394.'
ieee: 'C. M. Sommer, C. Straehle, U. Köthe, and F. A. Hamprecht, “Ilastik: Interactive
learning and segmentation toolkit,” in 2011 IEEE International Symposium on
Biomedical Imaging: from Nano to Micro, Chicago, Illinois, USA, 2011.'
ista: 'Sommer CM, Straehle C, Köthe U, Hamprecht FA. 2011. Ilastik: Interactive
learning and segmentation toolkit. 2011 IEEE International Symposium on Biomedical
Imaging: from Nano to Micro. ISBI: International Symposium on Biomedical Imaging.'
mla: 'Sommer, Christoph M., et al. “Ilastik: Interactive Learning and Segmentation
Toolkit.” 2011 IEEE International Symposium on Biomedical Imaging: From Nano
to Micro, Institute of Electrical and Electronics Engineers, 2011, doi:10.1109/isbi.2011.5872394.'
short: 'C.M. Sommer, C. Straehle, U. Köthe, F.A. Hamprecht, in:, 2011 IEEE International
Symposium on Biomedical Imaging: From Nano to Micro, Institute of Electrical and
Electronics Engineers, 2011.'
conference:
end_date: 2011-04-02
location: Chicago, Illinois, USA
name: 'ISBI: International Symposium on Biomedical Imaging'
start_date: 2011-03-30
date_created: 2021-08-19T11:49:58Z
date_published: 2011-06-09T00:00:00Z
date_updated: 2023-02-23T14:13:38Z
day: '09'
department:
- _id: Bio
doi: 10.1109/isbi.2011.5872394
extern: '1'
keyword:
- image segmentation
- biomedical imaging
- three dimensional displays
- neurons
- retina
- observers
- image color analysis
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.researchgate.net/publication/224241106_Ilastik_Interactive_learning_and_segmentation_toolkit
month: '06'
oa: 1
oa_version: Preprint
publication: '2011 IEEE International Symposium on Biomedical Imaging: from Nano to
Micro'
publication_identifier:
eissn:
- 1945-8452
isbn:
- 978-1-4244-4127-3
issn:
- 1945-7928
publication_status: published
publisher: Institute of Electrical and Electronics Engineers
quality_controlled: '1'
status: public
title: 'Ilastik: Interactive learning and segmentation toolkit'
type: conference
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2011'
...