---
_id: '14798'
abstract:
- lang: eng
text: 'A faithful reproduction of gloss is inherently difficult because of the limited
dynamic range, peak luminance, and 3D capabilities of display devices. This work
investigates how the display capabilities affect gloss appearance with respect
to a real-world reference object. To this end, we employ an accurate imaging pipeline
to achieve a perceptual gloss match between a virtual and real object presented
side-by-side on an augmented-reality high-dynamic-range (HDR) stereoscopic display,
which has not been previously attained to this extent. Based on this precise gloss
reproduction, we conduct a series of gloss matching experiments to study how gloss
perception degrades based on individual factors: object albedo, display luminance,
dynamic range, stereopsis, and tone mapping. We support the study with a detailed
analysis of individual factors, followed by an in-depth discussion on the observed
perceptual effects. Our experiments demonstrate that stereoscopic presentation
has a limited effect on the gloss matching task on our HDR display. However, both
reduced luminance and dynamic range of the display reduce the perceived gloss.
This means that the visual system cannot compensate for the changes in gloss appearance
across luminance (lack of gloss constancy), and the tone mapping operator should
be carefully selected when reproducing gloss on a low dynamic range (LDR) display.'
acknowledgement: "This work is supported by FWF Lise Meitner (Grant M 3319), Spanish
Agencia Estatal de Investigación (project PID2022-141539NBI00), European Research
Council (ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement\r\nN◦ 725253–EyeCode), Swiss National Science Foundation (Grant
no. 200502), and academic gifts from Meta. We thank Dmitry Lubyako and Ali Özgür
Yöntem for building the turntable for our experiment."
article_number: '90'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Bin
full_name: Chen, Bin
last_name: Chen
- first_name: Akshay
full_name: Jindal, Akshay
last_name: Jindal
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
orcid: 0000-0002-5062-4474
- first_name: Chao
full_name: Wang, Chao
last_name: Wang
- first_name: Hans Peter
full_name: Seidel, Hans Peter
last_name: Seidel
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
- first_name: Ana
full_name: Serrano, Ana
last_name: Serrano
- first_name: Rafał K.
full_name: Mantiuk, Rafał K.
last_name: Mantiuk
citation:
ama: 'Chen B, Jindal A, Piovarci M, et al. The effect of display capabilities on
the gloss consistency between real and virtual objects. In: Proceedings of
the SIGGRAPH Asia 2023 Conference. Association for Computing Machinery; 2023.
doi:10.1145/3610548.3618226'
apa: 'Chen, B., Jindal, A., Piovarci, M., Wang, C., Seidel, H. P., Didyk, P., …
Mantiuk, R. K. (2023). The effect of display capabilities on the gloss consistency
between real and virtual objects. In Proceedings of the SIGGRAPH Asia 2023
Conference. Sydney, Australia: Association for Computing Machinery. https://doi.org/10.1145/3610548.3618226'
chicago: Chen, Bin, Akshay Jindal, Michael Piovarci, Chao Wang, Hans Peter Seidel,
Piotr Didyk, Karol Myszkowski, Ana Serrano, and Rafał K. Mantiuk. “The Effect
of Display Capabilities on the Gloss Consistency between Real and Virtual Objects.”
In Proceedings of the SIGGRAPH Asia 2023 Conference. Association for Computing
Machinery, 2023. https://doi.org/10.1145/3610548.3618226.
ieee: B. Chen et al., “The effect of display capabilities on the gloss consistency
between real and virtual objects,” in Proceedings of the SIGGRAPH Asia 2023
Conference, Sydney, Australia, 2023.
ista: 'Chen B, Jindal A, Piovarci M, Wang C, Seidel HP, Didyk P, Myszkowski K, Serrano
A, Mantiuk RK. 2023. The effect of display capabilities on the gloss consistency
between real and virtual objects. Proceedings of the SIGGRAPH Asia 2023 Conference.
SIGGRAPH: Computer Graphics and Interactive Techniques Conference, 90.'
mla: Chen, Bin, et al. “The Effect of Display Capabilities on the Gloss Consistency
between Real and Virtual Objects.” Proceedings of the SIGGRAPH Asia 2023 Conference,
90, Association for Computing Machinery, 2023, doi:10.1145/3610548.3618226.
short: B. Chen, A. Jindal, M. Piovarci, C. Wang, H.P. Seidel, P. Didyk, K. Myszkowski,
A. Serrano, R.K. Mantiuk, in:, Proceedings of the SIGGRAPH Asia 2023 Conference,
Association for Computing Machinery, 2023.
conference:
end_date: 2023-12-15
location: Sydney, Australia
name: 'SIGGRAPH: Computer Graphics and Interactive Techniques Conference'
start_date: 2023-12-12
date_created: 2024-01-14T23:00:57Z
date_published: 2023-12-10T00:00:00Z
date_updated: 2024-01-17T08:38:35Z
day: '10'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3610548.3618226
file:
- access_level: open_access
checksum: 8abe27432ed222b50d1af9b3388db1b0
content_type: application/pdf
creator: dernst
date_created: 2024-01-17T08:33:06Z
date_updated: 2024-01-17T08:33:06Z
file_id: '14823'
file_name: 2023_SA_Chen.pdf
file_size: 95967451
relation: main_file
success: 1
file_date_updated: 2024-01-17T08:33:06Z
has_accepted_license: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
publication: Proceedings of the SIGGRAPH Asia 2023 Conference
publication_identifier:
isbn:
- '9798400703157'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: The effect of display capabilities on the gloss consistency between real and
virtual objects
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '12972'
abstract:
- lang: eng
text: Embroidery is a long-standing and high-quality approach to making logos and
images on textiles. Nowadays, it can also be performed via automated machines
that weave threads with high spatial accuracy. A characteristic feature of the
appearance of the threads is a high degree of anisotropy. The anisotropic behavior
is caused by depositing thin but long strings of thread. As a result, the stitched
patterns convey both color and direction. Artists leverage this anisotropic behavior
to enhance pure color images with textures, illusions of motion, or depth cues.
However, designing colorful embroidery patterns with prescribed directionality
is a challenging task, one usually requiring an expert designer. In this work,
we propose an interactive algorithm that generates machine-fabricable embroidery
patterns from multi-chromatic images equipped with user-specified directionality
fields.We cast the problem of finding a stitching pattern into vector theory.
To find a suitable stitching pattern, we extract sources and sinks from the divergence
field of the vector field extracted from the input and use them to trace streamlines.
We further optimize the streamlines to guarantee a smooth and connected stitching
pattern. The generated patterns approximate the color distribution constrained
by the directionality field. To allow for further artistic control, the trade-off
between color match and directionality match can be interactively explored via
an intuitive slider. We showcase our approach by fabricating several embroidery
paths.
acknowledgement: This work was supported by the European Research Council (ERC) under
the European Union’s Horizon 2020 research and innovation program (grant agreement
No 715767 – MATERIALIZABLE), and FWF Lise Meitner (Grant M 3319). We thank the anonymous
reviewers for their insightful feedback; Solal Pirelli, Shardul Chiplunkar, and
Paola Mejia for proofreading; everyone in the visual computing group at ISTA for
inspiring lunch and coffee breaks; Thibault Tricard for help producing the results
of Phasor Noise.
article_processing_charge: No
article_type: original
author:
- first_name: Zhenyuan
full_name: Liu, Zhenyuan
id: 70f0d7cf-ae65-11ec-a14f-89dfc5505b19
last_name: Liu
orcid: 0000-0001-9200-5690
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
- first_name: Christian
full_name: Hafner, Christian
id: 400429CC-F248-11E8-B48F-1D18A9856A87
last_name: Hafner
- first_name: Raphael
full_name: Charrondiere, Raphael
id: a3a24133-2cc7-11ec-be88-8ddaf6f464b1
last_name: Charrondiere
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
citation:
ama: Liu Z, Piovarci M, Hafner C, Charrondiere R, Bickel B. Directionality-aware
design of embroidery patterns. Computer Graphics Forum. 2023;42(2):397-409.
doi:10.1111/cgf.14770
apa: 'Liu, Z., Piovarci, M., Hafner, C., Charrondiere, R., & Bickel, B. (2023).
Directionality-aware design of embroidery patterns. Computer Graphics Forum.
Saarbrucken, Germany: Wiley. https://doi.org/10.1111/cgf.14770
'
chicago: Liu, Zhenyuan, Michael Piovarci, Christian Hafner, Raphael Charrondiere,
and Bernd Bickel. “Directionality-Aware Design of Embroidery Patterns.” Computer
Graphics Forum. Wiley, 2023. https://doi.org/10.1111/cgf.14770
.
ieee: Z. Liu, M. Piovarci, C. Hafner, R. Charrondiere, and B. Bickel, “Directionality-aware
design of embroidery patterns,” Computer Graphics Forum, vol. 42, no. 2.
Wiley, pp. 397–409, 2023.
ista: Liu Z, Piovarci M, Hafner C, Charrondiere R, Bickel B. 2023. Directionality-aware
design of embroidery patterns. Computer Graphics Forum. 42(2), 397–409.
mla: Liu, Zhenyuan, et al. “Directionality-Aware Design of Embroidery Patterns.”
Computer Graphics Forum, vol. 42, no. 2, Wiley, 2023, pp. 397–409, doi:10.1111/cgf.14770 .
short: Z. Liu, M. Piovarci, C. Hafner, R. Charrondiere, B. Bickel, Computer Graphics
Forum 42 (2023) 397–409.
conference:
end_date: 2023-05-12
location: Saarbrucken, Germany
name: 'EG: Eurographics'
start_date: 2023-05-08
date_created: 2023-05-16T08:47:25Z
date_published: 2023-05-08T00:00:00Z
date_updated: 2023-08-01T14:47:05Z
day: '08'
ddc:
- '004'
department:
- _id: BeBi
doi: '10.1111/cgf.14770 '
ec_funded: 1
external_id:
isi:
- '001000062600033'
file:
- access_level: open_access
checksum: 4c188c2be4745467a8790bbf5d6491aa
content_type: application/pdf
creator: mpiovarc
date_created: 2023-05-16T08:28:37Z
date_updated: 2023-05-16T08:28:37Z
file_id: '12974'
file_name: Zhenyuan2023.pdf
file_size: 24003702
relation: main_file
success: 1
file_date_updated: 2023-05-16T08:28:37Z
has_accepted_license: '1'
intvolume: ' 42'
isi: 1
issue: '2'
keyword:
- embroidery
- design
- directionality
- density
- image
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '05'
oa: 1
oa_version: Published Version
page: 397-409
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: Computer Graphics Forum
publication_identifier:
issn:
- 1467-8659
publication_status: published
publisher: Wiley
quality_controlled: '1'
status: public
title: Directionality-aware design of embroidery patterns
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 42
year: '2023'
...
---
_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: 2023-12-13T11:20:00Z
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: No
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
date_created: 2023-05-16T09:34:13Z
date_published: 2023-07-23T00:00:00Z
date_updated: 2024-02-28T12:52:04Z
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'
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: 2DF688A6-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: No
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. 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. 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.” 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,” 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. Transactions on Graphics. 42(4), 67.'
mla: 'Piovarci, Michael, et al. “Skin-Screen: A Computational Fabrication Framework
for Color Tattoos.” Transactions on Graphics, vol. 42, no. 4, 67, Association
for Computing Machinery, 2023, doi:10.1145/3592432.'
short: M. Piovarci, A. Chapiro, B. Bickel, 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
date_created: 2023-05-16T09:39:14Z
date_published: 2023-07-26T00:00:00Z
date_updated: 2024-01-29T10:27:23Z
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
file_date_updated: 2023-05-16T09:38:25Z
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: Submitted Version
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
publication: Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
status: public
title: 'Skin-Screen: A computational fabrication framework for color tattoos'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 42
year: '2023'
...
---
_id: '11442'
abstract:
- lang: eng
text: "Enabling additive manufacturing to employ a wide range of novel, functional
materials can be a major boost to this technology. However, making such materials
printable requires painstaking trial-and-error by an expert operator,\r\nas they
typically tend to exhibit peculiar rheological or hysteresis properties. Even
in the case of successfully finding the process parameters, there is no guarantee
of print-to-print consistency due to material differences between batches. These
challenges make closed-loop feedback an attractive option where the process parameters
are adjusted on-the-fly. There are several challenges for designing an efficient
controller: the deposition parameters are complex and highly coupled, artifacts
occur after long time horizons, simulating the deposition is computationally costly,
and learning on hardware is intractable. In this work, we demonstrate the feasibility
of learning a closed-loop control policy for additive manufacturing using reinforcement
learning. We show that approximate, but efficient, numerical simulation is\r\nsufficient
as long as it allows learning the behavioral patterns of deposition that translate
to real-world experiences. In combination with reinforcement learning, our model
can be used to discover control policies that outperform\r\nbaseline controllers.
Furthermore, the recovered policies have a minimal sim-to-real gap. We showcase
this by applying our control policy in-vivo on a single-layer, direct ink writing
printer. "
acknowledgement: "This work is graciously supported by the following grant agencies:
FWF Lise Meitner (Grant M 3319), SNSF (Grant 200502), ERC Starting Grant (MATERIALIZABLE-715767),
NSF (Grant IIS-181507).\r\n"
article_number: '112'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
- first_name: Michael
full_name: Foshey, Michael
last_name: Foshey
- first_name: Jie
full_name: Xu, Jie
last_name: Xu
- first_name: Timothy
full_name: Erps, Timothy
last_name: Erps
- first_name: Vahid
full_name: Babaei, Vahid
last_name: Babaei
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Szymon
full_name: Rusinkiewicz, Szymon
last_name: Rusinkiewicz
- first_name: Wojciech
full_name: Matusik, Wojciech
last_name: Matusik
- 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, Foshey M, Xu J, et al. Closed-loop control of direct ink writing
via reinforcement learning. ACM Transactions on Graphics. 2022;41(4). doi:10.1145/3528223.3530144
apa: Piovarci, M., Foshey, M., Xu, J., Erps, T., Babaei, V., Didyk, P., … Bickel,
B. (2022). Closed-loop control of direct ink writing via reinforcement learning.
ACM Transactions on Graphics. Association for Computing Machinery. https://doi.org/10.1145/3528223.3530144
chicago: Piovarci, Michael, Michael Foshey, Jie Xu, Timothy Erps, Vahid Babaei,
Piotr Didyk, Szymon Rusinkiewicz, Wojciech Matusik, and Bernd Bickel. “Closed-Loop
Control of Direct Ink Writing via Reinforcement Learning.” ACM Transactions
on Graphics. Association for Computing Machinery, 2022. https://doi.org/10.1145/3528223.3530144.
ieee: M. Piovarci et al., “Closed-loop control of direct ink writing via
reinforcement learning,” ACM Transactions on Graphics, vol. 41, no. 4.
Association for Computing Machinery, 2022.
ista: Piovarci M, Foshey M, Xu J, Erps T, Babaei V, Didyk P, Rusinkiewicz S, Matusik
W, Bickel B. 2022. Closed-loop control of direct ink writing via reinforcement
learning. ACM Transactions on Graphics. 41(4), 112.
mla: Piovarci, Michael, et al. “Closed-Loop Control of Direct Ink Writing via Reinforcement
Learning.” ACM Transactions on Graphics, vol. 41, no. 4, 112, Association
for Computing Machinery, 2022, doi:10.1145/3528223.3530144.
short: M. Piovarci, M. Foshey, J. Xu, T. Erps, V. Babaei, P. Didyk, S. Rusinkiewicz,
W. Matusik, B. Bickel, ACM Transactions on Graphics 41 (2022).
date_created: 2022-06-10T06:41:47Z
date_published: 2022-06-01T00:00:00Z
date_updated: 2023-05-31T12:38:21Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3528223.3530144
ec_funded: 1
external_id:
arxiv:
- '2201.11819'
file:
- access_level: open_access
checksum: 27f6fe41c6ff84d50445cc9b0176d45b
content_type: application/pdf
creator: dernst
date_created: 2022-06-28T08:32:58Z
date_updated: 2022-06-28T08:32:58Z
file_id: '11467'
file_name: 2022_ACM_acceptedversion_Piovarci.pdf
file_size: 33994829
relation: main_file
success: 1
file_date_updated: 2022-06-28T08:32:58Z
has_accepted_license: '1'
intvolume: ' 41'
issue: '4'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Submitted Version
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- 1557-7368
issn:
- 0730-0301
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
link:
- description: News on ISTA website
relation: press_release
url: https://ista.ac.at/en/news/machine-learning-3d-printing-fluids/
status: public
title: Closed-loop control of direct ink writing via reinforcement learning
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 41
year: '2022'
...
---
_id: '12135'
abstract:
- lang: eng
text: A good match of material appearance between real-world objects and their digital
on-screen representations is critical for many applications such as fabrication,
design, and e-commerce. However, faithful appearance reproduction is challenging,
especially for complex phenomena, such as gloss. In most cases, the view-dependent
nature of gloss and the range of luminance values required for reproducing glossy
materials exceeds the current capabilities of display devices. As a result, appearance
reproduction poses significant problems even with accurately rendered images.
This paper studies the gap between the gloss perceived from real-world objects
and their digital counterparts. Based on our psychophysical experiments on a wide
range of 3D printed samples and their corresponding photographs, we derive insights
on the influence of geometry, illumination, and the display’s brightness and measure
the change in gloss appearance due to the display limitations. Our evaluation
experiments demonstrate that using the prediction to correct material parameters
in a rendering system improves the match of gloss appearance between real objects
and their visualization on a display device.
acknowledgement: This work is supported by FWF Lise Meitner (Grant M 3319), European
Research Council (project CHAMELEON, Grant no. 682080), Swiss National Science Foundation
(Grant no. 200502), and academic gifts from Meta.
article_number: '35'
article_processing_charge: No
author:
- first_name: Bin
full_name: Chen, Bin
last_name: Chen
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
- first_name: Chao
full_name: Wang, Chao
last_name: Wang
- first_name: Hans-Peter
full_name: Seidel, Hans-Peter
last_name: Seidel
- first_name: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
- first_name: Ana
full_name: Serrano, Ana
last_name: Serrano
citation:
ama: 'Chen B, Piovarci M, Wang C, et al. Gloss management for consistent reproduction
of real and virtual objects. In: SIGGRAPH Asia 2022 Conference Papers.
Vol 2022. Association for Computing Machinery; 2022. doi:10.1145/3550469.3555406'
apa: 'Chen, B., Piovarci, M., Wang, C., Seidel, H.-P., Didyk, P., Myszkowski, K.,
& Serrano, A. (2022). Gloss management for consistent reproduction of real
and virtual objects. In SIGGRAPH Asia 2022 Conference Papers (Vol. 2022).
Daegu, South Korea: Association for Computing Machinery. https://doi.org/10.1145/3550469.3555406'
chicago: Chen, Bin, Michael Piovarci, Chao Wang, Hans-Peter Seidel, Piotr Didyk,
Karol Myszkowski, and Ana Serrano. “Gloss Management for Consistent Reproduction
of Real and Virtual Objects.” In SIGGRAPH Asia 2022 Conference Papers,
Vol. 2022. Association for Computing Machinery, 2022. https://doi.org/10.1145/3550469.3555406.
ieee: B. Chen et al., “Gloss management for consistent reproduction of real
and virtual objects,” in SIGGRAPH Asia 2022 Conference Papers, Daegu, South
Korea, 2022, vol. 2022.
ista: 'Chen B, Piovarci M, Wang C, Seidel H-P, Didyk P, Myszkowski K, Serrano A.
2022. Gloss management for consistent reproduction of real and virtual objects.
SIGGRAPH Asia 2022 Conference Papers. SIGGRAPH: Computer Graphics and Interactive
Techniques Conference vol. 2022, 35.'
mla: Chen, Bin, et al. “Gloss Management for Consistent Reproduction of Real and
Virtual Objects.” SIGGRAPH Asia 2022 Conference Papers, vol. 2022, 35,
Association for Computing Machinery, 2022, doi:10.1145/3550469.3555406.
short: B. Chen, M. Piovarci, C. Wang, H.-P. Seidel, P. Didyk, K. Myszkowski, A.
Serrano, in:, SIGGRAPH Asia 2022 Conference Papers, Association for Computing
Machinery, 2022.
conference:
end_date: 2022-12-09
location: Daegu, South Korea
name: 'SIGGRAPH: Computer Graphics and Interactive Techniques Conference'
start_date: 2022-12-06
date_created: 2023-01-12T12:03:56Z
date_published: 2022-11-01T00:00:00Z
date_updated: 2023-02-13T09:15:25Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3550469.3555406
file:
- access_level: open_access
checksum: f47f3215ab8bb919e3546b3438c34c21
content_type: application/pdf
creator: dernst
date_created: 2023-01-24T07:35:21Z
date_updated: 2023-01-24T07:35:21Z
file_id: '12351'
file_name: 2022_ACM_SIGGRAPH_Chen.pdf
file_size: 28826826
relation: main_file
success: 1
file_date_updated: 2023-01-24T07:35:21Z
has_accepted_license: '1'
intvolume: ' 2022'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: eb901961-77a9-11ec-83b8-f5c883a62027
grant_number: M03319
name: Perception-Aware Appearance Fabrication
publication: SIGGRAPH Asia 2022 Conference Papers
publication_identifier:
isbn:
- '9781450394703'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Gloss management for consistent reproduction of real and virtual objects
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 2022
year: '2022'
...
---
_id: '10148'
abstract:
- lang: eng
text: Tactile feedback of an object’s surface enables us to discern its material
properties and affordances. This understanding is used in digital fabrication
processes by creating objects with high-resolution surface variations to influence
a user’s tactile perception. As the design of such surface haptics commonly relies
on knowledge from real-life experiences, it is unclear how to adapt this information
for digital design methods. In this work, we investigate replicating the haptics
of real materials. Using an existing process for capturing an object’s microgeometry,
we digitize and reproduce the stable surface information of a set of 15 fabric
samples. In a psychophysical experiment, we evaluate the tactile qualities of
our set of original samples and their replicas. From our results, we see that
direct reproduction of surface variations is able to influence different psychophysical
dimensions of the tactile perception of surface textures. While the fabrication
process did not preserve all properties, our approach underlines that replication
of surface microgeometries benefits fabrication methods in terms of haptic perception
by covering a large range of tactile variations. Moreover, by changing the surface
structure of a single fabricated material, its material perception can be influenced.
We conclude by proposing strategies for capturing and reproducing digitized textures
to better resemble the perceived haptics of the originals.
acknowledgement: Our gratitude goes out to Kamila Mushkina, Akhmajon Makhsadov, Jordan
Espenshade, Bruno Fruchard, Roland Bennewitz, and Robert Drumm. This project has
received funding from the EU’s Horizon 2020 research and innovation programme, under
the Marie Skłodowska-Curie grant agreement No 642841 (DISTRO).
article_processing_charge: No
author:
- first_name: Donald
full_name: Degraen, Donald
last_name: Degraen
- first_name: Michael
full_name: Piovarci, Michael
id: 62E473F4-5C99-11EA-A40E-AF823DDC885E
last_name: Piovarci
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Antonio
full_name: Kruger, Antonio
last_name: Kruger
citation:
ama: 'Degraen D, Piovarci M, Bickel B, Kruger A. Capturing tactile properties of
real surfaces for haptic reproduction. In: 34th Annual ACM Symposium. Association
for Computing Machinery; 2021:954-971. doi:10.1145/3472749.3474798'
apa: 'Degraen, D., Piovarci, M., Bickel, B., & Kruger, A. (2021). Capturing
tactile properties of real surfaces for haptic reproduction. In 34th Annual
ACM Symposium (pp. 954–971). Virtual: Association for Computing Machinery.
https://doi.org/10.1145/3472749.3474798'
chicago: Degraen, Donald, Michael Piovarci, Bernd Bickel, and Antonio Kruger. “Capturing
Tactile Properties of Real Surfaces for Haptic Reproduction.” In 34th Annual
ACM Symposium, 954–71. Association for Computing Machinery, 2021. https://doi.org/10.1145/3472749.3474798.
ieee: D. Degraen, M. Piovarci, B. Bickel, and A. Kruger, “Capturing tactile properties
of real surfaces for haptic reproduction,” in 34th Annual ACM Symposium,
Virtual, 2021, pp. 954–971.
ista: 'Degraen D, Piovarci M, Bickel B, Kruger A. 2021. Capturing tactile properties
of real surfaces for haptic reproduction. 34th Annual ACM Symposium. UIST: User
Interface Software and Technology, 954–971.'
mla: Degraen, Donald, et al. “Capturing Tactile Properties of Real Surfaces for
Haptic Reproduction.” 34th Annual ACM Symposium, Association for Computing
Machinery, 2021, pp. 954–71, doi:10.1145/3472749.3474798.
short: D. Degraen, M. Piovarci, B. Bickel, A. Kruger, in:, 34th Annual ACM Symposium,
Association for Computing Machinery, 2021, pp. 954–971.
conference:
end_date: 2021-10-14
location: Virtual
name: 'UIST: User Interface Software and Technology'
start_date: 2021-10-10
date_created: 2021-10-18T07:36:11Z
date_published: 2021-10-10T00:00:00Z
date_updated: 2021-10-19T19:29:06Z
day: '10'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1145/3472749.3474798
ec_funded: 1
file:
- access_level: open_access
checksum: b0b26464df79b3a59e8ed82e4e19ab15
content_type: application/pdf
creator: bbickel
date_created: 2021-10-18T07:36:03Z
date_updated: 2021-10-18T07:36:03Z
file_id: '10149'
file_name: degraen-UIST2021_Texture_Appropriation_CR_preprint.pdf
file_size: 29796364
relation: main_file
file_date_updated: 2021-10-18T07:36:03Z
has_accepted_license: '1'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Preprint
page: 954-971
project:
- _id: 2508E324-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '642841'
name: Distributed 3D Object Design
publication: 34th Annual ACM Symposium
publication_identifier:
isbn:
- 978-1-4503-8635-7
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
status: public
title: Capturing tactile properties of real surfaces for haptic reproduction
type: conference
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '10574'
abstract:
- lang: eng
text: 'The understanding of material appearance perception is a complex problem
due to interactions between material reflectance, surface geometry, and illumination.
Recently, Serrano et al. collected the largest dataset to date with subjective
ratings of material appearance attributes, including glossiness, metallicness,
sharpness and contrast of reflections. In this work, we make use of their dataset
to investigate for the first time the impact of the interactions between illumination,
geometry, and eight different material categories in perceived appearance attributes.
After an initial analysis, we select for further analysis the four material categories
that cover the largest range for all perceptual attributes: fabric, plastic, ceramic,
and metal. Using a cumulative link mixed model (CLMM) for robust regression, we
discover interactions between these material categories and four representative
illuminations and object geometries. We believe that our findings contribute to
expanding the knowledge on material appearance perception and can be useful for
many applications, such as scene design, where any particular material in a given
shape can be aligned with dominant classes of illumination, so that a desired
strength of appearance attributes can be achieved.'
acknowledgement: This project has received funding from the European Union’s Horizon
2020 research and innovation programme under the Marie Sklodowska-Curie, grant agreement
N∘ 765911 (RealVision) and from the European Research Council (ERC), grant agreement
N∘ 804226 (PERDY). Open Access funding enabled and organized by Projekt DEAL.
article_processing_charge: Yes
article_type: original
author:
- first_name: Bin
full_name: Chen, Bin
last_name: Chen
- first_name: Chao
full_name: Wang, Chao
last_name: Wang
- 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: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
- first_name: Ana
full_name: Serrano, Ana
last_name: Serrano
citation:
ama: Chen B, Wang C, Piovarci M, et al. The effect of geometry and illumination
on appearance perception of different material categories. Visual Computer.
2021;37(12):2975-2987. doi:10.1007/s00371-021-02227-x
apa: Chen, B., Wang, C., Piovarci, M., Seidel, H. P., Didyk, P., Myszkowski, K.,
& Serrano, A. (2021). The effect of geometry and illumination on appearance
perception of different material categories. Visual Computer. Springer
Nature. https://doi.org/10.1007/s00371-021-02227-x
chicago: Chen, Bin, Chao Wang, Michael Piovarci, Hans Peter Seidel, Piotr Didyk,
Karol Myszkowski, and Ana Serrano. “The Effect of Geometry and Illumination on
Appearance Perception of Different Material Categories.” Visual Computer.
Springer Nature, 2021. https://doi.org/10.1007/s00371-021-02227-x.
ieee: B. Chen et al., “The effect of geometry and illumination on appearance
perception of different material categories,” Visual Computer, vol. 37,
no. 12. Springer Nature, pp. 2975–2987, 2021.
ista: Chen B, Wang C, Piovarci M, Seidel HP, Didyk P, Myszkowski K, Serrano A. 2021.
The effect of geometry and illumination on appearance perception of different
material categories. Visual Computer. 37(12), 2975–2987.
mla: Chen, Bin, et al. “The Effect of Geometry and Illumination on Appearance Perception
of Different Material Categories.” Visual Computer, vol. 37, no. 12, Springer
Nature, 2021, pp. 2975–87, doi:10.1007/s00371-021-02227-x.
short: B. Chen, C. Wang, M. Piovarci, H.P. Seidel, P. Didyk, K. Myszkowski, A. Serrano,
Visual Computer 37 (2021) 2975–2987.
date_created: 2021-12-26T23:01:26Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2023-08-17T06:29:34Z
day: '01'
ddc:
- '000'
department:
- _id: BeBi
doi: 10.1007/s00371-021-02227-x
external_id:
isi:
- '000673536600003'
file:
- access_level: open_access
checksum: 244cfcac0479ca6e3444c098ab2860a1
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creator: cchlebak
date_created: 2021-12-27T13:51:08Z
date_updated: 2021-12-27T13:51:08Z
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file_name: 2021_VisComput_Chen.pdf
file_size: 5741094
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intvolume: ' 37'
isi: 1
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: 2975-2987
publication: Visual Computer
publication_identifier:
eissn:
- 1432-2315
issn:
- 0178-2789
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: The effect of geometry and illumination on appearance perception of different
material categories
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 37
year: '2021'
...
---
_id: '9820'
abstract:
- lang: eng
text: Material appearance hinges on material reflectance properties but also surface
geometry and illumination. The unlimited number of potential combinations between
these factors makes understanding and predicting material appearance a very challenging
task. In this work, we collect a large-scale dataset of perceptual ratings of
appearance attributes with more than 215,680 responses for 42,120 distinct combinations
of material, shape, and illumination. The goal of this dataset is twofold. First,
we analyze for the first time the effects of illumination and geometry in material
perception across such a large collection of varied appearances. We connect our
findings to those of the literature, discussing how previous knowledge generalizes
across very diverse materials, shapes, and illuminations. Second, we use the collected
dataset to train a deep learning architecture for predicting perceptual attributes
that correlate with human judgments. We demonstrate the consistent and robust
behavior of our predictor in various challenging scenarios, which, for the first
time, enables estimating perceived material attributes from general 2D images.
Since our predictor relies on the final appearance in an image, it can compare
appearance properties across different geometries and illumination conditions.
Finally, we demonstrate several applications that use our predictor, including
appearance reproduction using 3D printing, BRDF editing by integrating our predictor
in a differentiable renderer, illumination design, or material recommendations
for scene design.
acknowledgement: This project has received funding from the European Union’s Horizon
2020 research and innovation programme under the Marie Skłodowska-Curie, grant agreement
Nº 765911 (RealVision) and from the European Research Council (ERC), grant agreement
Nº 804226 (PERDY).
article_number: '125'
article_processing_charge: No
article_type: original
author:
- first_name: Ana
full_name: Serrano, Ana
last_name: Serrano
- first_name: Bin
full_name: Chen, Bin
last_name: Chen
- first_name: Chao
full_name: Wang, Chao
last_name: Wang
- 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: Piotr
full_name: Didyk, Piotr
last_name: Didyk
- first_name: Karol
full_name: Myszkowski, Karol
last_name: Myszkowski
citation:
ama: 'Serrano A, Chen B, Wang C, et al. The effect of shape and illumination on
material perception: Model and applications. ACM Transactions on Graphics.
2021;40(4). doi:10.1145/3450626.3459813'
apa: 'Serrano, A., Chen, B., Wang, C., Piovarci, M., Seidel, H. P., Didyk, P., &
Myszkowski, K. (2021). The effect of shape and illumination on material perception:
Model and applications. ACM Transactions on Graphics. Association for Computing
Machinery. https://doi.org/10.1145/3450626.3459813'
chicago: 'Serrano, Ana, Bin Chen, Chao Wang, Michael Piovarci, Hans Peter Seidel,
Piotr Didyk, and Karol Myszkowski. “The Effect of Shape and Illumination on Material
Perception: Model and Applications.” ACM Transactions on Graphics. Association
for Computing Machinery, 2021. https://doi.org/10.1145/3450626.3459813.'
ieee: 'A. Serrano et al., “The effect of shape and illumination on material
perception: Model and applications,” ACM Transactions on Graphics, vol.
40, no. 4. Association for Computing Machinery, 2021.'
ista: 'Serrano A, Chen B, Wang C, Piovarci M, Seidel HP, Didyk P, Myszkowski K.
2021. The effect of shape and illumination on material perception: Model and applications.
ACM Transactions on Graphics. 40(4), 125.'
mla: 'Serrano, Ana, et al. “The Effect of Shape and Illumination on Material Perception:
Model and Applications.” ACM Transactions on Graphics, vol. 40, no. 4,
125, Association for Computing Machinery, 2021, doi:10.1145/3450626.3459813.'
short: A. Serrano, B. Chen, C. Wang, M. Piovarci, H.P. Seidel, P. Didyk, K. Myszkowski,
ACM Transactions on Graphics 40 (2021).
date_created: 2021-08-08T22:01:28Z
date_published: 2021-08-01T00:00:00Z
date_updated: 2023-08-10T14:20:10Z
day: '01'
department:
- _id: BeBi
doi: 10.1145/3450626.3459813
external_id:
isi:
- '000674930900090'
intvolume: ' 40'
isi: 1
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://zaguan.unizar.es/record/110704/files/texto_completo.pdf
month: '08'
oa: 1
oa_version: Submitted Version
publication: ACM Transactions on Graphics
publication_identifier:
eissn:
- '15577368'
issn:
- '07300301'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'The effect of shape and illumination on material perception: Model and applications'
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 40
year: '2021'
...